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"Report: Enterprises expect remote work to take permanent hold | VentureBeat"
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"https://venturebeat.com/security/report-enterprises-expect-remote-work-to-take-permanent-hold-even-post-pandemic"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Report: Enterprises expect remote work to take permanent hold Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
According to a new report by Aryaka , two-thirds of the enterprises surveyed expect at least 25% of their employees to be permanently remote post-pandemic, and a quarter of enterprises expect up to 75% of their employees to be permanently remote post-pandemic.
The report looks at SD-WAN and secure access service edge (SASE) plans for the coming year and is designed as a resource for enterprise architects and C-levels to use as a companion resource for their planning efforts, supplementing traditional analyst research reports. It delves into four major areas of IT interest, including the hybrid workplace; software-as-a-service (SaaS) application consumption and performance concerns; managing complexity with the adoption of managed services; and the convergence of network, security, and the cloud leading to adoption of a SASE architecture.
Key observations in each of these areas include the permanence of the hybrid workplace, with a full quarter expecting half to 75% of their employees to remain hybrid, and another 43% expecting a quarter to a half to do so.
On the application front, Microsoft Teams was identified by 58% as deployed, speaking to the nature of the Microsoft suite in many enterprises.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Respondents were also keen to adopt managed SD-WAN and SASE, with over two-thirds signaling their intention to do so but looking at an “all-in-one” offer that integrates connectivity, security, optimization, multi-cloud access, and observability.
Finally, diving into SASE , almost two-thirds of enterprises state that they are currently deploying or plan to deploy over the next year what they consider to be SASE, but they identify challenges that include complexity, developing a migration strategy, and market confusion regarding single or multivendor approaches. One eye-opening takeaway is the bullishness on budgets across both networking and security, with a quarter of the respondents expecting growth of 25% or more, and a full three-quarters projecting greater than 10% growth.
The report polled over 1600 enterprises across the globe in October 2021, with responses representing a mix of roles that include CIOs, CISOs, as well as network, security, and cloud practitioners. Enterprises span all verticals including technology, software services, manufacturing, finance, and retail.
Read the full report by Aryaka.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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2,314 | 2,022 |
"Report: 97% of C-level executives worry about videoconference security | VentureBeat"
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"https://venturebeat.com/security/report-97-of-c-level-executives-worry-about-videoconference-security"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Report: 97% of C-level executives worry about videoconference security Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
>>Don’t miss our special issue: How Data Privacy Is Transforming Marketing.
<< A new survey of IT pros from Zerify , a leading cybersecurity company focused on secure videoconferencing solutions, reports that 82% of respondents say nation-state cyberthreats have increased. Sixty-nine percent believe cyberattackers could breach their videoconferencing platforms, and 84% stated that if they were breached, they believed attackers could steal intellectual property, sensitive company data and trade secrets.
Highlights of the survey of 1,000 IT professionals include: 92% reported that they are aware of security vulnerabilities in videoconferencing platforms.
Nation-state cyberthreats have increased at most (81.8%) companies.
The majority of IT professionals (89%) are concerned about foreign attacks as they see a rise in threats.
79% of respondents reported that they were very knowledgeable about the concept and framework of zero-trust cybersecurity, with 86% stating that their company had ZT cybersecurity policies.
Methodology The survey was conducted by an unbiased third-party organization, Propeller Insights, which surveyed 1,000 corporate respondents. 57% were C-level executives and 43% were IT decision-makers. Respondents weren’t paid for answers or told who sponsored the survey.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Read the full report from Zerify.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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2,315 | 2,022 |
"Remote work demands industrial businesses secure critical infrastructure | VentureBeat"
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"https://venturebeat.com/security/remote-work-calls-for-industrial-businesses-to-secure-critical-infrastructure"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Community Remote work demands industrial businesses secure critical infrastructure Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Complex market forces and various sets of challenges have converged over the last decade, leading to the rapid adoption of new digital solutions in power plants.
The growing use of renewables and the digitization of the grid have put competitive pressure on traditional gas-operated power plants to evolve to be more competitive.
The primary challenges driving this change include: Multigenerational workforce – the shortage of experienced plant operators and managers is growing, driving a need for more flexible remote work options and training Global shift to remote work – uncertainty and social-distancing protocols created by the COVID-19 epidemic hastened the urgency of a new remote operational model.
This second trend is, arguably, the most important.
Power generators are beginning to adopt technologies that enable remote or mobile control procedures to ensure business continuity and optimal staffing flexibility and efficiency. Due to growing uncertainties in plant operations, industrial organizations must build their security stack with the goal of controlling their critical infrastructure from a remote location. Plant managers and technicians need the ability to interface with the plant assets from anywhere, at any time.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Traditionally, power plant operators and technicians have only been able to work in a control room or other nearby environment to access the plant’s human-machine interfaces (HMIs). Even if there was a desire for more flexible solutions for remote operations or a need to access systems remotely for technical support, operators were limited physically to the control room. Power plant operators have long been under immense pressure from operations and maintenance (O&M) to meet key performance indicators (KPIs), and the pandemic has added an urgent need for remote flexibility. Developing and executing contingency plans and changing strategies for minimizing the onsite presence of non-essential personnel have become a critical priority.
There are several reasons such limits have been in place, such as international cyber requirements that prevented mobile or offsite use of these controls.
Additionally, there is often a high degree of manual process and procedural limitations when such conditions are in place. Because of this, when remote access becomes necessary at times, it is usually performed through temporary approaches that can put critical infrastructure at risk.
Blending physical security and cybersecurity measures Looking at the division of plant locations and responsibilities today, those in the industry have a good idea of what solutions are needed based on personal roles and responsibilities. However, those needs don’t always coherently tie to a specific strategy.
The strategies needed to meet the business challenges of today and tomorrow range from having occasional remote technical support to contingency operations to a more complex plan for the centralized (remote) operation of many assets from a command center.
A combination of both on-site and remote power plant operators will be able to respond much more effectively, increasing operational efficiency and public safety. In addition, remote staff can monitor and control onsite HMI systems while still allowing on-site control room staff to have ultimate access control. Depending on plant characteristics, entire remote operations may be possible. Mobile users at the plant or elsewhere benefit from a purpose-built interface that includes safety features.
One example illustrating the cost and need for more adaptable remote operations is the middle-of-the-night call for the local technician, who may be several hours away, to respond to an issue during start preparation. Timing is critical, and the speed of response may make the difference between a failed start, delayed start or a missed load ramp or tollgate – resulting in the potential loss of tens of thousands of dollars for a single instance. The physical response required to call the technician to the site also impacts the team’s overall productivity, as that person invariably misses the following workday. If the technician could instead provide support remotely, it would eliminate many of these issues.
Remote access: Re-orienting the cybersecurity strategy Industrial businesses and enterprises must rethink their security stack. Rather than building defenses around the office, organizations must enable: Collaborate with remote staff and experts Increase on-site mobile staff effectiveness and flexibility Improve employee health and safety Operate reliably with reduced staffing Centrally monitor plant operations.
Diagnose and troubleshoot alarms and issues Instruct, guide and dispatch on-site personnel Remotely operate, startup and/or shutdown control system assets Today’s most power plants are equipped with firewall products, which have become standard-issue appliances when needing to secure a network. Today’s next-generation firewalls (NGFW) are more powerful and provide multiple functions such as sandboxing, application-level inspection and intrusion prevention. While NGFWs do a great job at these functions, they are not designed for accessing devices remotely, and there are inherent risks for those who have used them for remote access.
Firewalls can encrypt data streams over a virtual private network (VPN) and tunnel critical information through an untrusted network, such as the internet. However, with today’s technology and the high number of tools and information available to threat actors, it is possible to hack the data communication protocols at the endpoint device where these encrypted data streams are terminated and potentially conduct malicious activities to access critical power plant assets.
Additional areas businesses should consider for their remote security include: Organizations must identify all their critical infrastructure. While this may sound intuitive, it’s crucial to account for system interdependencies. For instance, an IT billing system is vital if it is interdependent on operational technology.
Encrypted browser-based display (VDI) for remote or mobile operator HMI display to desktops, laptops and tablets.
Multifactor authentication (MFA) is a given.
There are many MFA types, but industrial organizations should implement closed-loop, hardware-based token access without cloud access to meet both onsite mobile operator and remote access requirements.
Moderated secure file transfer provides either bidirectional or uni-directional file transfer capabilities for each system connection.
Application and system segmentation ensures systems and applications are logically segmented to limit cyberattacks’ blast radius.
Time-Based access controls limit the time vendors, contractors and plant technicians interact with critical systems.
HMI access sessions by mobile operators and remote users need to be recorded for forensics and training purposes.
As the power industry adapts to the changes presented by a changing workforce and the convergence of IT and OT, remote user access will become even more essential.
Bill Moore is the CEO of Xona Systems.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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2,316 | 2,022 |
"Optimize your tech stack with flexibility and productivity in mind | VentureBeat"
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"https://venturebeat.com/programming-development/optimize-your-tech-stack-with-flexibility-and-productivity-in-mind"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Community Optimize your tech stack with flexibility and productivity in mind Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
If you think about your day-to-day at work — whether you’re working from your home office, a coffee shop or the actual office — we interact with dozens, if not hundreds, of tools regularly. From task management, document collaboration, finance software, calendar apps or messaging platforms, we are constantly interacting with and sharing information — and this is just to manage our individual day-to-day. At a departmental level, the number of applications teams use has grown exponentially. According to a report from Productiv, most departments use between 40 and 60 different applications. That’s a lot of apps for employees to keep track of – and be proficient at using.
Consider the IT and devops teams that are building the multitude of apps and platforms that keep work running smoothly. Businesses are facing an ever-evolving web of processes and applications, and the tools, technologies and languages to iterate on and deliver software are evolving, expanding and specializing faster than ever. These teams are at the heart of software delivery and innovation, but their jobs are becoming more complicated at the same time it is also getting harder to simply build the software that today’s businesses depend on.
That’s why it’s time for tech leaders (like myself) to take a step back and rethink our approach to optimizing and modernizing our tech stacks — a new approach that focuses on team efficiency, solid partnership with the business and successful ideation. When we do so, we create elite performing teams, which, according to Google , have 208 times more frequent code deployments and are 2,604 times faster to recover from incidents.
Focus on the right metrics, not just adding new software I recently spoke with a CTO who said that as they moved to remote work, they rolled out more tools to measure their team’s productivity and output. The result? Their entire engineering team revolted. Rather than making the assumption that adding more software will encourage your team to work harder (in this case, adopting a new tech solution that tracks if your employees are actually working), I recommend a different approach.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! At Slack, we measure productivity and output by “time to audience” or “speed plus quality.” By examining questions like, “How long does it take to specify the work?” “How long does it take to edit and iterate?” or “How long does it take to deploy and measure?” I can easily uncover insights that help speed up or shift my team’s development practices — and I can do that all without just jumping at any new technology that comes down the pipeline.
Old isn’t necessarily bad It’s easy to get distracted by the next new thing, but we often overlook one simple fact when it comes to an optimized tech stack: It’s about how efficiently your engineering teams can work with it, regardless of how old it is. If working with an older tech stack means you can’t make changes quickly, that is not always a tech stack problem, rather it is more of an innovation and devops problem. We need to stop fixating on the use of older tools, like a Java database and SQL server. These are still powerful in their own right. Instead, it’s likely your team can’t make changes quickly, which may be what is actually slowing them down.
For example, say you’re building a new mobile app and it takes three to four minutes to compile, but you want to decrease that time to under a minute. Those few minutes of difference may not sound like they’re that impactful, but imagine you need to compile this app more than 50 times each day. Even if you can save a few mins on each cycle by driving efficiencies in how teams work, that’s a massive impact on ROI to the business.
It’s all about efficiencies in our work, how we can improve ROI through quicker release rates, reduce the time to resolve incidents, or the improvement of change failure rates. It’s not just about how new the tools we’re using, but instead about how we can drive efficiency.
Automate the time-consuming tasks Automating away the mundane, time-consuming tasks that suck up too much energy and effort can free up valuable resources that lead to more actionable insights – across the enterprise. With low-code and automation tools, your company’s IT, devops and engineering teams can focus on solving more complex problems and iterating, testing and rolling out products quicker and more efficiently. With low-code tools in use, we can give more power to the people — technical or not. In fact, Gartner says 80% of technology products and services will be built by those who aren’t technology professionals by 2024.
It’s time for a new model geared for the future of work As companies grapple with the rapid transition to new ways of working, we’re under more pressure than ever to keep businesses running smoothly while testing and deploying new technologies that drive businesses — and our customers — forward.
I call on other IT, devops and engineering leaders to prioritize their greatest assets — their people — by focusing on better processes for innovation, new ways to measure team-level success and dialing in on the tools needed to automate away the complexity that prevents progress.
Steve Wood is the senior vice president of product and platform at Slack DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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2,317 | 2,022 |
"Report: Workplace sustainability is a must-have for 32% of employees | VentureBeat"
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"https://venturebeat.com/enterprise-analytics/report-workplace-sustainability-is-a-must-have-for-32-of-employees"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Report: Workplace sustainability is a must-have for 32% of employees Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Almost a third of total employees (32%) surveyed agreed that they would only work for an employer that prioritizes sustainability. Of that total, 42% of millennials, 30% of Gen-X, and 21% of Boomers somewhat or strongly agreed to the statement, “I would only work for an employer that prioritizes sustainability.” About a third of employees (35%) think that instituting sustainability practices at work would boost productivity rates, position their company as a leader (31%), and open more opportunities for innovation (37%). Forty-three percent think it would improve workplace culture.
In a recent study from Adobe, “Adobe Document Cloud Sustainability at Work Report,” U.S. employees were asked about their opinions and beliefs about sustainable workplace practices in the present and their hope for the future of workplace sustainability.
It depends — hybrid vs. in-office workers Employee perceptions of environmental impact depends on the office setting. Compared to employees that work in a physical office, hybrid and remote employees feel more strongly that office commutes (40% and 52% vs. 27%), physical office footprints (40% and 45% vs. 27%), and business travel (26% and 31% vs. 16%) contribute to their employers’ environmental impact.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! But in-office employees, who are closer to company-wide trash cans, are more concerned about food waste (33%) than hybrid (23%) and remote (16%) employees.
Barriers to workplace sustainability However, employees say rising supply costs (64%), supply chain shortages (48%), and geopolitical issues (29%) will be major challenges for corporate sustainability initiatives in the next five years.
Yet 42% of employees think their company will spend between $100,000-$1,000,000 on sustainable alternatives in that time. One in five ballpark more than a million.
Looking at the future of sustainability practices Fast forward 10 years, most employees expect sustainability to be fully embedded in their work culture. They believe their companies will revamp their internal processes (71%) and have a dedicated sustainability department (64%).
Long story short, employees feel strongly about achieving sustainable workplaces and lifestyles. More than half (62%) say they’ll spend up to $10,000 on sustainable alternatives in the next five years and one in five (19%) predict to spend between $1,000-$5,000.
In the next 10 years, they’re willing to reduce their plastic use (78%), purchase more sustainable products (75%), and change their travel habits (53%) and home energy source (52%). They’re not quite sold on reducing car travel though — only 27% plan to rely more on public transportation.
Reducing the environmental impact of workplaces — in office, hybrid or remote — is a work in progress, but employees have a passion for getting involved.
The Adobe Document Cloud Sustainability at Work Report surveyed 1,400 enterprise knowledge workers in the U.S. from February 25–March 14, 2022 via a 15-minute online survey.
Read the full report from Adobe.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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2,318 | 2,022 |
"Report: 70% of workers want to keep their pandemic-era WFH option | VentureBeat"
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"https://venturebeat.com/data-infrastructure/report-70-of-workers-want-to-keep-their-pandemic-era-wfh-option"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Report: 70% of workers want to keep their pandemic-era WFH option Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
A new study from Deloitte , “2022 Connectivity and Mobile Trends,” shows that “the COVID-19 pandemic propelled U.S. households into an unprecedented societal beta test that accelerated emerging trends in technology and connectivity.” Almost overnight, adult workers and adult and child learners had to negotiate the transition of work and school from fully in-person to fully remote.
And while the previous year’s study showed there were many bumps and hiccups along the way, mostly due to trying to stretch physical space and digital bandwidth to meet the needs of multiple household members, this year’s study shows “consumers are gaining mastery over their digital lives, optimizing the devices they use, and fine-tuning the balance between their virtual and physical worlds.” Remote workers like WFH Almost all workers (99%) who had been working from home ( WFH ) said they “appreciated aspects of the experience.” The top three benefits they named were lack of commute, feeling more comfortable at home and reduced risk of contracting COVID-19. The top three challenges were having family or household responsibilities during working hours, feeling stressed or burned out, and slow or unstable internet service.
However, the study noted that compared to 2021’s study, these issues had decreased due to workers getting used to working from home, there being fewer family members at home in 2022 so there were fewer devices competing for internet bandwidth, and networks and devices becoming more optimized for WFH as the pandemic went on.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! From a mental health and relationships viewpoint, most remote workers felt WFH was a successful experiment. At least half of those who worked remotely over the past year said their “family relationships, physical well-being, and emotional well-being improved through the experience.” From a professional standpoint, while they didn’t report improved working relationships with coworkers, less than 20% reported a negative effect on working relationships.
Going forward, 75% of remote workers and 50% of overall employed adults preferred virtual or hybrid working options once the pandemic eases. Of the remote workers, 43% would prefer completely or mostly virtual work, while 29% of overall employed adults had the same preference.
The report stated that businesses should pay attention to their workers: “Companies that simply ignore employee demands for flexible working arrangements may risk losing a competitive edge in attracting and retaining the best workers.” Remote students The report noted that virtual learning experiences over the course of the pandemic had a major benefit in highlighting that learning is not “one size fits all.” It said that while some students were “anxious to return to the academic and social structure of in-person school, others thrived” in their remote-learning experiences.
A majority of students with remote learning experience (70%) said they would like to have virtual or hybrid learning options in the future. Only 12% said they wanted to attend school completely in person.
Parents, on the other hand, while viewing the remote learning experience as positive overall, preferred their students to be in school, with 40% saying they wanted their children to attend school completely in person, and only 35% preferring fully remote or hybrid learning options.
The study noted, “Remote students need help managing stress and distractions, and they could use technologies or techniques to feel more connected with classmates, teachers, and school culture.” Deloitte’s Center for Technology, Media and Telecommunications surveyed 2,005 U.S. consumers in Q1 2022 for this report.
Read the full report from Deloitte.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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2,319 | 2,022 |
"Cisco partners with Radiflow for its OT security expertise | VentureBeat"
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"https://venturebeat.com/security/cisco-partners-with-radiflow-for-its-ot-security-expertise"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Cisco partners with Radiflow for its OT security expertise Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
With the advent of Industry 4.0 , industrial networks are becoming increasingly digitized.
But while this brings many gains in productivity, quality and efficiency, it introduces new — and never before considered — cybersecurity vulnerabilities.
Due to its critical nature, operational technology (OT) networks — digital networks on the production floor — require specific security tools beyond those used in IT networks themselves. Intrusion detection systems (IDS) are considered one of the most effective of these tools, as they passively monitor network traffic and don’t pose risks to ongoing operational processes.
To help counter growing threats and attacks, cybersecurity company Radiflow today announced a technology partnership with Cisco to provide IDS in Cisco-run OT facilities.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “The shortage of resources with OT security expertise is quite high and keeps growing,” said Ilan Barda, Radiflow ‘s cofounder and CEO. “As such, it is important to use such integrations to reduce the need for manual work.” OT facilities like Cisco’s are a growing attack surface Barda described an “alarming” increase in cybersecurity attacks against OT facilities.
To this point, a Trend Micro survey of industrial cybersecurity in manufacturing, electric and oil and gas companies revealed that nine out of 10 organizations had production or energy supplies impacted by cyberattacks in the past 12 months. The average cost of such attacks was $2.8 million, and more than half (56%) of respondents said disruptions lasted four or more days.
Such disruptions have given rise to new and evolved security tools: According to a recent report from MarketsandMarkets , the OT security market size will grow from an estimated value of $15.5 billion in 2022 to $32.4 billion in 2027, registering a compound annual growth rate (CAGR) of nearly 16%.
The report cites increased use of digital technologies in industrial systems, stringent government regulations related to the common industrial protocol (CIP) to boost the adoption of OT security solutions, and convergence of IT and OT systems as the top factors driving market growth.
Simple, fluent operations Cisco’s network access control (NAC) is a widely used tool for protecting IT networks. It supports network visibility and access management through policy enforcement on devices and users of corporate networks.
Although many companies rely on it to secure their network access control systems, building management systems (BMS) often have no way to account for industry-specific needs or protect against greater cybersecurity risks, said Barda. In BMS settings, OT security systems have to account for specific needs and criticalities of different subsystems — HVAC or elevator operation, for instance, which are often overseen by different personnel and departments.
To deploy IT-oriented tools in OT networks and detect anomalies, mature IDS tools like Radiflow’s platform are needed, said Barda. It integrates directly into Cisco’s popular BMS, protecting connected devices that don’t have embedded access control, and adds a protection layer to a variety of OT networks, keeping security operations “simple and fluent.” This new incorporation “helps alleviate an inherent problem in industrial networks since many of these devices were never designed with embedded access control, introducing a slew of cyber-vulnerabilities,” said Barda.
Controlled, restricted connection As Barda explained, the most common cybersecurity issue in OT networks is unauthorized changes in network topology — for example, a technician’s laptop that is connected to the network and has no limitations on what it can do in the network. Another high-risk issue, said Barda, is that changes in device software — even without any sort of malicious intent — can also change the device’s communication patterns, causing damage to other devices.
Radiflow’s IDS solution discovers network assets and communication patterns, maps inventory details and vulnerabilities, and detects network anomalies. Users at Cisco facilities can discern baseline asset behavior and any deviation in behavior patterns.
“With embedded access control, such threats are mitigated since every device is connected in a controlled and restricted way,” Barda said.
Increased automation Barda explained that the platform passively monitors OT network traffic using a span port from the main switches of the network.
To maximize OT network coverage, Radiflow also provides smart collectors that can connect to the span ports of remote subnetworks and send the relevant data to the server in an optimized way, he said.
Radiflow’s DPI engine parses network traffic and creates a database of network assets, their inventory details and their normal baseline behavior patterns, said Barda. The asset database is enhanced with data of their known common vulnerabilities and exposures (CVEs) and can be presented graphically or exported to other asset management tools.
Once the baseline of the normal behavior is stable, the platform switches to “detection mode” and uses its DPI engine to detect anomalies in traffic flows, said Barda. Such anomalies could include: Changes in network topology.
Changes in communication patterns.
Changes in the firmware and logic of industrial assets.
Signatures of known characteristics of cyber exploits.
Deviations in industrial commands or in ranges of the process.
These anomalies generate events in the platform and are reported to other security control center tools using syslog.
Ultimately, Barda said, they “…greatly simplify both network security and asset management, especially in complex IT-OT networks.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Cisco unveils new WAN forecasting capabilities | VentureBeat"
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"https://venturebeat.com/enterprise-analytics/cisco-unveils-new-wan-forecasting-capabilities"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Cisco unveils new WAN forecasting capabilities Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Cisco Systems , the internet pipefitter that is moving deeper into developing analytics and machine learning to add predictive capabilities to its networking management platform, today announced the launch of ThousandEyes WAN Insights, which should bring a slew of new options to its console of services.
Earlier this year, Cisco introduced its Cisco Predictive Networks , an initiative to bring predictive capabilities across the company’s portfolio of products and offerings. Cisco Predictive Networks is designed to open a new level of reliability and performance by predicting application and network issues before they happen – problems that include hardware and software bottlenecks and security breaches.
“The world has truly changed during the pandemic, and digital transformation has accelerated for most companies,” Mohit Lad, cofounder and GM of Cisco ThousandEyes, wrote in a recent blog post. “We are now supporting employees in offices as well as homes, collaborating with each other using applications that are hosted in the cloud and outside IT environments. We do this while continuing to help the business operate at the same level or better than pre-pandemic. We are now living in a different world compared to two years ago, so we challenged ourselves to find new ways to empower our customers to be able to thrive in this new reality.” Cisco acquired ThousandEyes in August 2020, precisely when the COVID-19 pandemic was on its first major upswing. The ThousandEyes internet and cloud intelligence platform expands administrative visibility into the digital delivery of applications and services over the internet and the cloud. It enables organizations to visualize any network as if it was their own, surfaces actionable insights and collaborates and solves problems with service providers.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The internet is the new corporate backbone So how does Cisco plan to provide optimal networking performance in unpredictable internet environments? “First, we provide the best view of global internet health, covering networks as well as top SaaS applications that organizations rely on,” Lad said. “This lets our customers proactively address major unexpected network or application issues affecting them as soon as they happen by making the desired changes either on their end or their provider’s. A lot of these outages can’t be predicted, and organizations need to react quickly as soon as they happen – real-time visibility is key. However, we do believe many service disruptions can be avoided if we do a better job of looking at all the data and learning from the past. This is the focus of Cisco Predictive Networks and the origination of ThousandEyes WAN Insights.” ThousandEyes WAN Insights improves visibility into SD-WAN environments and gives organizations the ability to look at their top applications, the experience specific sets of users are facing and how that experience can improve by learning from past behaviors, Lad said.
In addition, Cisco provides recommendations and expected improvement metrics (for example, changing routing from internet-A to internet-B, because it will provide a 20% improvement in speed). “At this stage, it’s (only) a recommendation with the vision to work toward more automation in the future,” Lad said.
ThousandEyes WAN Insights recommendations also will show up in Cisco’s vAnalytics application to ensure that network operations teams get the actionable intelligence they need, Lad said.
What does this do for SD-WAN (wide-area network) deployments? “First, think of this technology as a guiding hand – helping you get the most out of the SD-WAN deployments, taking the guesswork out of initial policy setup and optimization,” Lad said. “Second, as environments continue to evolve, you can fine-tune them based on long-term recommendations to ensure the environment delivers the best digital experience possible to your users. This gives you the power to move from reactive to preventative with SD-WAN environments.” Cisco said ThousandEyes WAN Insights will soon be available to its SD-WAN customers, most likely by the end of Q3.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Tableau integrates with Slack to make analytics agile, accessible, and actionable | VentureBeat"
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"https://venturebeat.com/data-infrastructure/tableau-integrates-with-slack-to-make-analytics-agile-accessible-and-actionable"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Tableau integrates with Slack to make analytics agile, accessible, and actionable Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Business intelligence and analytics provider, Tableau , today launched an integration with Slack to improve how businesses retrieve their analytics. The integration will enable users to complete natural language questions to gather insights directly from Slack without leaving the app.
As Francois Ajenstat, chief product officer at Tableau, explained, “Helping people see and understand data is what drives us. Whether you’re an analyst, business person, IT manager, or developer, we’re making analytics easier, faster, and more actionable for anyone, anywhere. By bringing analytics directly where work happens, making it smarter and more actionable, and enabling self-service data management, we will enable more organizations to build a data culture and drive analytics success.” The announcement comes after the pandemic has contributed to a data explosion, with employees moving out of the office and into increasingly digital spaces to support remote work.
It is an environment where many decision-makers are struggling to get access to the insights they need to operate effectively, an environment that Tableau is helping to simplify.
Accessible data analytics In an exclusive interview with VentureBeat, Ajenstat explained why the company is investing in collaboration, “We all work differently than we used to, we’re all digital, work from anywhere, and so analytics has to be in the flow of business, it has to be available where people work.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Ajenstat detailed that Tableau customers will have access to “proactive data insights being built from Slack, so they can stay on top of their data.” In practice, that’s the ability to ask questions in natural language.
Tableau offers natural language capabilities via Slack, so you can ask questions about business data in natural language and receive digital answers. Imagine being able to ask them something sophisticated, such as: “What were my sales in Europe for electric cars last month?” Ajenstat said.
The goal of this approach is to make data “more like a colleague” that you can ask questions to and get immediate answers, rather than a mountainous data set that you need to make sense of with dashboards and reports.
Tableau’s Slack integration shows the company is taking a similar approach to Microsoft Power BI, which offers users a Power BI tab in Microsoft Teams , but goes a step further to offer in-app natural language interaction for users, so they can ask questions rather than passively consuming analytics content.
Improving data literacy During the announcement, Tableau also announced that it was going on a concerted effort to improve data literacy by pledging to train 10 million data professionals. “The skills of the future are going to be data skills. It’s one of the top skills identified by the World Economic Forum,” Ajenstat said.
“Data skills are critical to business success. Those that have access to data are more likely to be thriving than others that are barely surviving. Yet, the demand is outpacing supply. [The International Data Corporation] IDC reports that only 30% of people in organizations are comfortable using data analytics, so there’s this big gap.” Enhancing decision-making capabilities Tableau also unveiled two new products designed to help organizations improve their decision-making; Model Builder and Scenario Planning. Model Builder enables users to collaboratively build and consume predictive models with the Einstein discovery engine, and Scenario Planning enables users to compare alternative scenarios. This will enable decision-makers to make more accurate forecasting decisions and maintain operational excellence.
“Businesses know they must tap into the power of data to stay agile and respond in this rapidly changing environment. For these businesses, success depends on training and enabling everyone in their organization to use data and make better decisions,” Tableau’s president and CEO Mark Nelson, said.
These platforms will help users to navigate their data more efficiently and make better decisions. While these forecasting and data analytics solutions aren’t intended to take over decision-making, they do offer a more streamlined approach to gathering insights than a human could put together alone.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Rocket Chat taps Instagram Direct for omnichannel messaging | VentureBeat"
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"https://venturebeat.com/commerce/rocket-chat-taps-instagram-direct-for-omnichannel-messaging"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Rocket Chat taps Instagram Direct for omnichannel messaging Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
If you’re an enterprise communication platform company that wants to spread its wings and gain visibility points alongside some more well-known applications, you could do worse than to hook up with Instagram.
Rocket.Chat , an enterprise communication provider, today announced a new service called Instagram Direct , which enables businesses to integrate their Instagram business accounts with Rocket.Chat’s omnichannel customer-service package. The new integration is designed to help businesses build relationships with customers by facilitating a conversational commerce experience in the familiar Instagram DM app in addition to providing a single omnichannel platform for the various consumer connecting points, CEO and founder Gabriel Engel told VentureBeat.
Rocket.Chat is a secure, open source-based collaboration platform that is installed on more than 500,000 corporate servers and counts more than 12 million users worldwide, Engel said. It’s also available as a SaaS service. The company counts among its customers the U.S. Navy, the U.S. Air Force, Lockheed Martin, and other organizations desiring complete control and storage of their digital correspondence.
“These customers are looking for privacy as an important feature,” Engel said. “With Rocket.Chat, a company can host its data wherever they want, and they are absolutely certain who is going to have access to that data. And they can even use all the data because it’s already on their servers to model and improve their own AI strategies. This is because they have full access to everything that’s happening in real time.
What Rocket.Chat wants to give to its customers is data ownership and sovereignty, because the platform can run on any infrastructure they own, and they can connect to all the social networks as they come and go, Engel said. “They will still keep the same relationship with single customers, then keep the data. They will have more of a future-proof strategy by using our type of technology,” Engel said.
Software review site G2 lists Rocket.Chat competitors as Microsoft Teams, Cisco Jabber, Slack, LiveChat, Webex App, Mattermost, Zoom, and Bitrix24 — although none of them enables private storage of data.
Combining chat, video, internal communication, customer service Users can run Rocket.Chat with a range of features to tailor their platform: individual and group communication, video conferencing, file uploading, screen sharing, LiveChat, and integration with a variety of different communications platforms.
“Rocket.Chat, as the name says, is a communication platform, but not just for chat,” Engel told VentureBeat. “We do video conferencing and other forms of communication as well. But the whole reason why it was created was to break the silos of having communication systems that are only in the cloud, or only designed for internal communication, or a system that was only designed for customer service. We decided to go to a platform, where you could have two customer services interact in inter-company communication and between different companies. So it’s really a cooperation engine.” Businesses must be ready to embrace conversational commerce (c-commerce) on messaging and chat apps including Instagram DM, Facebook Messenger, and WhatsApp, or through voice technology, to provide improved customer experience and win more sales. Engel said. Conversational commerce — the intersection of messaging apps and shopping — continues to gain traction as consumers look for meaningful engagement and increasingly embrace shopping via chat with their preferred brands. According to a recent Meta study, half of all buyers reported they engage in c-commerce primarily through social media and messaging platforms.
Users expect quick responses all the time Consumers chat with businesses for a wide range of reasons, including product information, gift advice, a store location, flexible delivery, impulse purchases, and receiving personalized support. Research has shown that when commerce is conversational, satisfaction – and sales – increase. However, the effectiveness of c-commerce is driven largely by execution: Consumers expect businesses to answer quickly and provide helpful responses.
However, replying to multiple Instagram messages can be time-consuming for a customer support team. Rocket.Chat’s integration with Instagram DM is designed for the team to quickly respond to customers’ messages from one interface and provides the ability to set up chatbots and quick replies to reduce handling time, Engel said. Chatbots can help customers with frequently-asked questions while saving agents’ time for conversations that require human interaction.
The company has an active community of more than 1,000 developer-contributors who help its core team of developers to improve the product. Rocket.Chat’s long-term vision is to replace email with a real-time federated communications platform, Engel said.Instagram is a powerful marketing tool, with about 500 million daily users.
About 36% of Instagram users follow at least one business on the social media channel.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Zoom launches 'video-optimized' Contact Center into general availability | VentureBeat"
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"https://venturebeat.com/business/zoom-launches-video-optimized-contact-center-into-general-availability"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Zoom launches ‘video-optimized’ Contact Center into general availability Share on Facebook Share on X Share on LinkedIn Agent video chat in the new Zoom Contact Center Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Zoom has officially launched its contact center product , some five months after its planned $14.7 billion Five9 acquisition collapsed.
The cloud contact center market is predicted to become a $45.5 billion industry within four years , up from $11.5 billion in 2020, as companies across the industrial spectrum have been forced to embrace new tools in a world that has rapidly accelerated toward remote work and digital commerce.
Zoom became somewhat synonymous with group video chats through the pandemic, transcending the office environment to power the social interactions of millions globally. But the company has also offered Zoom Phone since 2019, serving as a cloud-based business phone system with enterprise-grade features. And this is a path that Zoom is keen to go deeper into — it wants to distance itself from “ Zoom fatigue ” and go all-in on enterprise communication.
Zoom Contact Center Zoom initially announced plans to acquire cloud contact center company Five9 last July , but the deal fell through after publicly traded company, Five9, failed to gain enough shareholder support. However, Zoom had already announced a cloud contact center product called Zoom Video Engagement Center, which it had planned to launch in early 2022 — and that, effectively, is what is going to market today under a new name.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Zoom Contact Center, as the new product is called, is pitched as an omnichannel contact center that is integrated directly into Zoom, meaning it supports the usual Zoom Chat features directly in the main interface. At launch, Zoom Contact Center is optimized for video calls, though it’s not clear to what extent customers wish to engage with support teams over video — and that is why Zoom’s solution supports voice calls too. The company is also working on SMS and web chat functionality, which are currently available in beta, though there is curiously no mention of support for instant messaging services such as WhatsApp.
On top of that, Zoom Contact Center features such as real-time analytics serve companies with insights into agent productivity, call time, waiting times, service level satisfaction, and more.
While countless other cloud-based contact center companies have gained traction and raised sizable VC funding rounds over the past couple of years, Zoom holds a major trump card in that it’s already familiar to millions of people globally. This, according to Zoom, “reduces ramp time and learning curves” for companies considering a shift from their existing provider, be that a legacy phone system or rival cloud contact center.
Moreover, as businesses continue to embrace a fully-remote or hybrid working setup , Zoom is now better-positioned to serve both its existing customer base and would-be clients in the early stages of their digital transformation efforts.
“A cost-efficient alternative to legacy phone systems, they [cloud contact centers] are hosted over the internet to allow employees to work across one platform, regardless of location,” Zoom wrote in a blog post. “As a result, agents can access customer data quickly and resolve customer issues with ease.” The company added that future releases will include new features such as CRM and workforce management integrations — which will be particularly crucial for larger contact centers — while it’s also planning AI/ML tools to “optimize agent productivity.” Zoom Contact Center hits general availability in the U.S. and Canada from today, with more global launches on the agenda for later in 2022.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"RingCentral acquires conversational AI startup DeepAffects | VentureBeat"
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"https://venturebeat.com/ai/ringcentral-acquires-conversational-ai-startup-deepaffects"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages RingCentral acquires conversational AI startup DeepAffects Share on Facebook Share on X Share on LinkedIn RingCentral Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
RingCentral , a company that creates cloud-based communication and collaboration tools for the enterprise, has acquired conversational AI intelligence startup DeepAffects.
Founded in 2003, Belmont, California-based RingCentral develops a range of cloud products for businesses , including contact center software, business phone and messaging systems, video conferencing, and more. As with other platforms that enabled businesses to transition to remote work during the pandemic, RingCentral has fared very well throughout 2020, with subscription revenue up by a third and its share price more than doubling over the past 12 months to an all-time high of $387 today.
Gartner previously predicted that by 2021, 15% of all customer service interactions will be handled entirely by AI, up 400% from 2017. While that spans all forms of communications, from social media engagements to email inquiries and live web chat, the telephone still plays a major role in outbound and inbound customer interactions, as well as internal communications, which is where DeepAffects comes into play.
Founded out of Milpitas, California in 2017, DeepAffects is setting out to create “the new standard for voice intelligence.” This includes creating voice prints, which can be used to identify individuals from a few seconds of audio, multi-speaker recognition, speech-to-text, emotion recognition, intent detection, and conversational metrics. It’s about enabling companies to analyze all their voice-based conversations and extract insights, which is particularly pertinent as businesses transition to either remote work or a hybrid model. For example, DeepAffects’ analytics can show “talk-to-listen” ratios, revealing who talked or listened most in a meeting, or perhaps who asked the most questions.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The DeepAffects platform already natively supported a number of popular communication platforms, including Zoom, Webex, GoToMeeting, and RingCentral itself. RingCentral said this deal will enable it to offer “smarter video meetings” to its customers, which include the Oakland A’s, Orange, Canal+, BMJ, and Columbia University.
Terms of the deal were not disclosed, though DeepAffects had only raised a small $200,000 in seed funding, according to Crunchbase data , meaning this was unlikely to have been a checkbook-busting deal. Indeed, RingCentral said the acquisition wouldn’t have a “material financial impact” on its year.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"VB Transform 2023: Announcing the nominees for VentureBeat’s 5th annual AI Innovation Awards | VentureBeat"
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"https://venturebeat.com/ai/vb-transform-2023-announcing-the-nominees-for-venturebeats-5th-annual-ai-innovation-awards"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages VB Transform 2023: Announcing the nominees for VentureBeat’s 5th annual AI Innovation Awards Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
As enterprise technical decision-makers from the artificial intelligence (AI) and data community get ready for VentureBeat’s flagship enterprise AI event, VB Transform , we are excited to announce the nominees for the fifth annual AI Innovation Awards.
The winners will be announced during VentureBeat CEO Matt Marshall’s closing remarks on the main stage of Transform on July 12 in San Francisco. The remarks will also be live-streamed on our homepage.
Transform will be a two-day in-person event, July 11 and 12, featuring industry experts and peers coming together to provide comprehensive insights and best practices on enterprises’ data journeys. As a bonus, participants will have numerous opportunities to forge meaningful connections and expand their networks.
At the July 12 in-person event at San Francisco’s Marriott Marquis, VentureBeat will recognize and award various forms of excellence in AI through our fifth annual VB AI Innovation Awards. The winners will be in the following categories: Generative AI Innovator of the Year, Best Enterprise Implementation of Generative AI, Most Promising Generative AI Startup, Generative AI Visionary, Generative AI Diversity and Inclusion, and Generative AI Open Source Contribution.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! >> Follow all our VentureBeat Transform 2023 coverage << The nominees are drawn from our daily editorial coverage and the expertise, knowledge and experience of our nominating committee members. Prepare to witness the trailblazers and game-changers in the realm of generative AI take center stage as we recognize their outstanding contributions.
Thank you to our nominating committee members for their guidance, insights and recommendations: Matei Zaharia, co-founder and CTO at Databricks Tonya Custis, director of AI research, Autodesk Di Mayze, global head of data and AI, WPP Prem Natarajan, chief scientist, head of enterprise AI at Capital One Kalyan Veeramachaneni, principal research scientist at MIT College of Computing Here are the nominees for each category: Generative AI Innovator of the Year This award will go to the company that has pushed the boundaries of generative AI the furthest in the past year and demonstrated the most innovative use of the technology. The winner will have created an application, platform or service that showcases the vast potential of generative AI in a creative, impactful way.
DeepMind Google in April acquired the London-based AI and machine learning (ML) research lab DeepMind with plans to take on the competitive threat posed by OpenAI and its game-changing ChatGPT. DeepMind in June released AlphaDev , a specialized version of AlphaZero, which has made a huge breakthrough by uncovering faster sorting and hashing algorithms.
According to a recent report , a new system called Gemini will combine LLM technology with reinforcement learning techniques used in AlphaGo, with the goal of giving it new planning and problem-solving capabilities.
Nvidia These days, Nvidia is synonymous with AI, Gartner analyst Chirag Dekate told VentureBeat in February. The 2023 AI hype explosion has launched large language models (LLMs) like ChatGPT and DALL·E 2 into the mainstream. This, too, would not have been possible without Nvidia. Today’s massive generative AI models require thousands of GPUs to run — and Nvidia holds about 88% of the GPU market, according to John Peddie Research. In fact, OpenAI reportedly used 10,000 Nvidia GPUs to train ChatGPT. Recently, Snowflake and Nvidia partnered to provide businesses with a platform to create custom generative AI applications within the Snowflake Data Cloud using a business’ proprietary data.
Inworld Inworld AI is an AI developer platform for immersive realities/metaverse spaces. Its platform creates AI-powered virtual characters to populate immersive realities including the metaverse , VR/AR, games and virtual worlds. Inworld AI uses advanced AI to build generative characters whose personalities, thoughts, memories and behaviors are designed to emulate human interaction.
OpenAI These days OpenAI is synonymous with the generative AI revolution taking place across industries. It is known for making significant strides in the field of AI research and its development of advanced AI models such as GPT-3, GPT-4 and DALL·E. Last week OpenAI announced it is taking one of its own in-house plug-ins, Code Interpreter, and making it available to all of its ChatGPT Plus subscribers.
Anthropic Anthropic is an AI safety and research company whose recently-debuted generative AI model Claude is considered a competitor for OpenAI’s ChatGPT. In May Anthropic announced that it had raised $450 million in series C funding led by Spark Capital, a venture capital firm that has backed companies like Twitter, Slack and Coinbase.
Best Enterprise Implementation of Generative AI This award will highlight the top enterprise company that has implemented generative AI technology in a truly transformative way.
Adobe Adobe has used generative AI to evolve its flagship content creation and publication software. It has developed a tool called Adobe Sensei which is an AI and machine learning (ML) learning platform that aims to get users working more efficiently and effectively with their creative assets. Adobe Sensei is used in many of Adobe’s flagship products. In June Adobe announced it will bring Firefly, its image-generating AI that it claims is the only “commercially safe generative AI,” to enterprise users.
Microsoft Microsoft has been working on incorporating generative AI into its Microsoft Dynamics and Power platforms with the goal of enabling enterprise applications with the power of generative AI. The company has also deployed its Copilot generative AI assistant across the Microsoft 365 suite of business productivity and collaboration apps. Recently Microsoft announced a partnership with Moody’s. Moody’s is using the Microsoft Azure OpenAI service as an engine that helps unlock research information and risk assessment capabilities.
Google Google has released its own competitor to ChatGPT, Bard. The company has been testing new uses for generative AI with its campaign creation tools and in efforts to make paid search ads more relevant to queries. Google introduced automatically created assets (ACAs) that analyze a landing page and ads to produce fresh headlines and descriptors for search.
Google in April acquired the London-based AI and ML research lab DeepMind with plans to take on the competitive threat posed by OpenAI and ChatGPT.
Walmart The multinational retail corporation Walmart has been making forays into using generative AI for internal use with employees. The company has also been advancing conversational AI capabilities using OpenAI’s GPT-4. Walmart is using GPT-4 to go further in natural language understanding. This includes boosting existing offerings like text to shop, which allows customers to add Walmart products to their cart by texting or speaking the names of the items they need. Recently Walmart announced its new Generative AI Playground, a platform the company describes as an “early-stage internal GenAI tool where associates can explore and learn about this new technology, while keeping our company and its data safe.” Salesforce Salesforce has launched Einstein GPT, generative AI CRM technology that delivers AI-created content across every sales, service, marketing, commerce and IT interaction at hyper-scale. The company also recently introduced new generative AI workflow tools for Sales Cloud and Service Cloud to simplify workflow and customer engagement for sales and service teams respectively. Recently, Salesforce also announced the launch of AI Cloud, an enterprise AI solution aimed at boosting productivity across all Salesforce applications. The new open platform integrates various Salesforce technologies like Einstein, Data Cloud, Tableau, Flow and MuleSoft, offering real-time generative AI capabilities that can be easily incorporated into business operations.
Most Promising Generative AI Startup This award will go to the most promising startup that has developed an innovative generative AI application and demonstrated high growth potential.
Midjourney Midjourney is an independent research lab. Midjourney generates images from natural language descriptions called “prompts” similar to OpenAI’s DALL·E and Stable Diffusion.
Midjourney stands out because the AI bot can only be accessed via the voice-over internet protocol, instant messaging social platform Discord — rather than via its own website or mobile app.
MosaicML MosaicML , a generative AI startup, was recently acquired by Databricks.
MosaicML is known for its generative AI capabilities and its ability to generate images from natural language descriptions (“prompts”), similar to Midjourney, OpenAI’s DALL·E and Stable Diffusion. The company provides software tools geared to making AI work cheaper. MosaicML is also working on improving neural network algorithmic methods that deliver speed, boost quality and reduce costs for enterprises.
Typeface Typeface is a generative AI application for creating enterprise content. The company helps enterprises create content at scale using AI-generated text and images, with ML training that has been customized to an organization’s content. Recognizing the limitations of generalized LLMs in meeting specific brands’ requirements, the company seeks to bridge the gap. The company recently announced it has raised $100 million in new funding to help expand its go-to-market efforts. Earlier in June Typeface expanded its customized generative AI approach with a Google Cloud partnership. The company has also added partnerships with Microsoft and Salesforce recently, further expanding its reach.
Runway Runway is a generative AI startup focused on bringing state-of-the-art multimodal AI systems to the market with its innovative text-to-image video tool, Gen-2. The company offers a platform for artists to use ML tools in intuitive ways without coding experience for media such as video, audio and text. Runway’s tool was used by one of the film editors for the Oscar-winning film “Everything Everywhere All at Once.” The company recently announced a fresh round of funding, adding $141 million in a series C from Google, Nvidia and Salesforce Ventures, among other investors.
Synthesis AI Synthesis AI is a startup specializing in the use of synthetic data to build more capable and ethical computer vision models. It offers a data generation platform designed to train sophisticated vision models. The platform brings together generative AI models and evolves technologies from the CGI world with an expanded set of pixel-labels, allowing users to build newer and better models. The company recently announced that it has developed a new way to create realistic 3D digital humans from text prompts, which can be used for various applications such as gaming, virtual reality, film and simulation.
Generative AI Visionary This award will go to an individual who has made significant contributions to the field of generative AI through their thought leadership, research, or work building foundational technologies. The winner would be judged based on the novelty and influence of their contributions, as evidenced by publications, patents, or products developed.
Jensen Huang Huang is the cofounder and CEO of Nvidia.
Ilya Sutskever Sutskever is the cofounder and chief scientist of OpenAI.
Jacob Devlin Devlin is a top Google AI researcher who resigned after he warned Alphabet CEO Sundar Pichai and other top executives that Bard was allegedly being trained on data from OpenAI’s chatbot. He was the lead author of a 2018 research paper on training machine learning models for search accuracy that helped initiate the AI boom.
Dario Amodei Amodei is the cofounder and CEO of Anthropic.
Ian Goodfellow Goodfellow is an American computer scientist, engineer and executive, most noted for his work on artificial neural networks and deep learning. He was previously employed as a research scientist at Google Brain and director of machine learning at Apple, and has made several important contributions to the field of deep learning, including the invention of the generative adversarial network (GAN).
Karén Simonyan Simonyan is the cofounder and chief scientist of Inflection AI. He is a leading researcher on deep learning.
Generative AI Diversity and Inclusion This award will recognize the company, organization or individual that has done the most to promote diversity and inclusion in the generative AI field. This could include advancing AI ethics, making AI technologies more accessible, providing opportunities and support for underrepresented groups, or using AI in a way that reduces bias and promotes social justice.
Sara Hooker Hooker is head of Cohere for AI, a nonprofit research lab aiming to solve complex ML problems. She is also the founder of Delta Analytics, a nonprofit organization that provides data science education and consulting to social impact organizations. Hooker has been researching and developing generative AI models that are more efficient, robust, interpretable and fair. Hooker has also been advocating for diversity and inclusion in the generative AI field through her mentorship, teaching and outreach activities.
Timnit Gebru Gebru is a former co-leader of Google’s Ethical Artificial Intelligence Team and a cofounder of Black in AI, a nonprofit organization that aims to increase the presence and inclusion of Black people in the field of artificial intelligence. Gebru has been conducting groundbreaking research on generative AI and its social implications, such as exposing bias in facial recognition systems, developing methods for auditing large-scale language models, and proposing frameworks for data sheets and model cards to document datasets and models. Gebru has also been speaking out against the harms and risks of generative AI, such as misinformation, discrimination and censorship.
Bars Juhasz Juhasz is a cofounder, AI programmer and designer at Undetectable AI , an AI writing tool. Juhasz has been using generative AI to create jobs for people who are disadvantaged, such as refugees, immigrants and people with disabilities. He has also been making generative AI more accessible and inclusive by providing a low-cost and easy-to-use platform that helps users create content in various languages and domains.
Jean-Michel Caye Caye is a senior partner at BCG and a co-author of the book Generative Leadership: The New Way of Leading.
Caye has been promoting diversity and inclusion in the generative AI field by providing tools and frameworks for leaders to harness the power of generative AI for positive impact. Caye has also been supporting initiatives such as the Global AI Action Alliance (GAIA) and the Centre for the New Economy and Society to advance AI ethics and governance.
Fei-Fei Li Li is the Sequoia Professor of Computer Science at Stanford University and co-director of Stanford’s Human-Centered AI Institute. Li has been leading the development of cognitively inspired AI, machine learning, deep learning, computer vision and AI+healthcare, especially ambient intelligent systems for healthcare delivery. Li has also been a national leading voice for advocating diversity in STEM and AI. She is cofounder and chairperson of the national non-profit AI4ALL aimed at increasing inclusion and diversity in AI education. She has also been working with policymakers nationally and locally to ensure the responsible use of generative AI, such as testifying before Congress, serving on the California Future of Work Commission, and being a member of the National Artificial Intelligence Research Resource Task Force.
Renee Cummings Cummings is the first data activist-in-residence at the University of Virginia’s School of Data Science where was named professor of practice in data science. She is also an AI ethicist, criminologist, Columbia University community scholar and founder of Urban AI. Cummings has been using generative AI to address social justice issues, such as reducing bias in criminal justice and policing. She has also been educating and empowering underrepresented groups in the AI field, such as women and people of color, through her mentorship, teaching and advocacy.
Generative AI Open Source Contribution This award highlights the person, team or company that has made the most significant contribution to open-source tools, datasets or other resources to help advance generative AI.
Hugging Face Hugging Face is an AI company that enables AI and data science professionals to communicate with each other with a tool specifically designed for them. It makes publishing datasets and AI models, both trained and untrained, easier. The company is known for its open-source contributions to the ML community and for natural language processing (NLP) and computer vision (CV) applications.
Stability AI Stability AI is a company that has developed open-source AI models for imaging, language, code, audio, video 3D content, design, biotech and scientific research.
Stability AI recently released StableStudio , an open-source version of DreamStudio, its commercial interface for generating Stable Diffusion images. The company said the launch “marks a fresh chapter” for the interface and “showcases Stability AI’s dedication to advancing open-source development within the AI ecosystem.” TensorFlow TensorFlow is an open-source technology effort, led by Google, that provides ML tools to help developers build and train models. TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks. It is a symbolic math library and is also used for ML applications such as neural networks. It was developed by the Google Brain team and is used by several other Google teams and researchers for machine learning and deep learning research.
Google recently rolled out a series of open-source updates for growing the TensorFlow ecosystem.
PyTorch PyTorch is an open-source ML library based on the Torch library. It is used for applications such as NLP. It was developed by Facebook’s artificial intelligence research group and is used by several other Facebook teams and researchers for machine learning research.
Meta-LLaMA Meta has publicly released Large Language Model Meta AI ( LLaMA ), an LLM designed to help researchers advance their work in this subfield of AI. Smaller models like LLaMA require far less computing power and resources to test new approaches, validate others’ work and explore new use cases. Foundation models train on a large set of unlabeled data, which makes them ideal for fine-tuning a variety of tasks.
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"OpenAI adds 'huge set' of ChatGPT updates | VentureBeat"
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"https://venturebeat.com/ai/openai-adds-huge-set-of-chatgpt-updates-including-suggested-prompts-multiple-file-uploads"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages OpenAI adds ‘huge set’ of ChatGPT updates, including suggested prompts, multiple file uploads Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Even while users and researchers continue to debate how the performance of ChatGPT has changed over time , OpenAI is not letting up on adding new features to its signature generative AI chatbot product.
This week, Logan Kilpatrick, OpenAI’s first developer advocate and developer relations expert, posted on X (formerly Twitter) that a “huge set of ChatGPT updates are rolling out over the next week.” Among the new features Kilpatrick highlighted are example prompts (already visible for the author, see screenshot below), suggested replies and follow-up questions (which Kilpatrick wrote is “very useful to reduce fatigue”), a default GPT-4 setting so that paying ChatGPT Plus subscribers don’t have to toggle on the latest/most advanced publicly available OpenAI large language model (LLM) every time they start a new chat, support for multiple file uploads when using the OpenAI Code Interpreter plugin , and more.
Huge set of ChatGPT updates are rolling out over the next week ?? 1. Example prompts: No more staring at a blank page! 2. Suggested replies: ChatGPT automatically synthesizes follow up questions. I’ve been using this the last month and it is very useful to reduce fatigue.… The initial reaction from users was mixed. While some praised the new features, including GPT-4 by default and one that allows users to “stay logged in” beyond the previous two-week period, others on the OpenAI and ChatGPT subreddit communities on Reddit asked , “Is it going to stop apologizing too? I sure hope so.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Some even went so far as to criticize the addition of example prompts as being “terrible for someone with ADHD,” because they are distracting.
Still, it is early on in the addition of the new features, and it remains to be seen which of them users will ultimately adopt and use most in their workflows, and which fail to see uptake or are rejected in the long run.
The new features also come amid reports that OpenAI has filed a trademark application with the U.S. Patent and Trademark Office (USPTO) for GPT-5, the next LLM in its ongoing series, and that the application includes possible features such as “the artificial production of human speech and text,” and “translation text or speech from one language to another.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Meet SeamlessM4T, the Meta AI model that can translate 100 languages into speech or text | VentureBeat"
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"https://venturebeat.com/ai/meet-seamlessm4t-the-meta-ai-model-that-can-translate-100-languages-into-speech-or-text"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Meet SeamlessM4T, the Meta AI model that can translate 100 languages into speech or text Share on Facebook Share on X Share on LinkedIn Woman using voice assistant on smartphone in the rain Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
As part of its broader effort to remove language barriers and keep people connected, Meta has developed a multilingual foundational model that can understand nearly 100 languages from speech or text and generate translations into either or both in real time.
Officially dubbed SeamlessM4T, the multimodal technology has been publicly released to help researchers build on the development and introduce universal applications capable of delivering speech-to-speech, speech-to-text, text-to-speech and text-to-text translations. It has been made available along with SeamlessAlign, a multimodal translation dataset totaling 265,000 hours of mined speech and text alignments.
The offering marks a significant development in AI’s application in linguistics given that it’s a single system performing multiple tasks across speech and text. Prior to this, the approach largely involved different systems for different tasks, such as a dedicated system for speech-to-speech translations.
What can SeamlessM4T do? As Meta explains, SeamlessM4T implicitly recognizes the source language without the need for a separate language identification model. It can detect speech and text in nearly 100 languages and produce text in nearly as many and speech in 36 languages. More interestingly, it can also figure out when more than one language has been mixed in the same sentence and provide translations in a single targeted language (like a sentence spoken in Telugu and Hindi and translated into English speech).
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! When tested with BLASER 2.0, which allows for evaluation across speech and text units, the model performed better against background noises and speaker variations in speech-to-text tasks (with average improvements of 37% and 48%, respectively) compared to the current state-of-the-art models for speech-to-text tasks.
“SeamlessM4T outperforms previous state-of-the-art competitors,” Meta said in a blog post.
“We also significantly improve performance for low and mid-resource languages (with smaller digital footprint) supported, and maintain strong performance on high-resource languages (like English).” When developed, this can lead to large-scale universal translation systems, allowing people who speak different languages to communicate more effectively.
Notably, Google is also working in this direction and has announced Universal Speech Model (USM), which can perform automatic speech recognition (ASR) for both widely-spoken and under-resourced languages.
How it all works? To bring the model to life, Meta mined web data (tens of billions of sentences) and speech (4 million hours) from public sources and aligned them to create the SeamlessAlign dataset. In total, the company said it was able to align more than 443,000 hours of speech with texts and create about 29,000 hours of speech-to-speech alignments. Using this data, the company trained the multitask UnitY model to produce the desired multimodal outcomes.
“The multitask UnitY model consists of three main sequential components,” Meta explains. “Text and speech encoders have the task of recognizing inputs in nearly 100 languages. The text decoder then transfers that meaning into nearly 100 languages for text, followed by a text-to-unit model to decode into discrete acoustic units for 36 speech languages…The decoded discrete units are then converted into speech using a multilingual HiFi-GAN unit vocoder.” Not perfect yet That said, it is important to note that SeamlessM4T is far from perfect right now. Evaluations found that the model has both added toxicity (although 63% less than state-of-the-art models) and gender bias issues.
According to a whitepaper detailing the technology, SeamlessM4T overgeneralizes to masculine forms when translating from neutral terms (with an average preference of approximately 10%) while showing a lack of robustness when varying gender by an amount of about 3%.
“We detect toxicity in both the input and the output for the demo,” Meta said. “If toxicity is only detected in the output, it means that toxicity is added. In this case, we include a warning and do not show the output…Regarding bias, we have started our efforts on evaluating gender bias in languages at scale. We are now able to quantify gender bias in dozens of speech translation directions by extending to speech our previously designed Multilingual HolisticBias dataset.” The company emphasized that this is an ongoing effort, and that it will continue to research and take action in these areas to further improve the robustness and safety of the SeamlessM4T model.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Calling a restaurant? An AI voice may answer thanks to Slang.AI | VentureBeat"
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"https://venturebeat.com/ai/calling-a-restaurant-an-ai-voice-may-answer-now-thanks-to-these-former-spotify-data-scientists"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Calling a restaurant? An AI voice may answer now, thanks to these former Spotify data scientists Share on Facebook Share on X Share on LinkedIn VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Slang.ai , an AI-powered phone answering product for the restaurant industry founded by two former Spotify data scientists, has successfully closed a $20 million Series A funding round led by Hunter Walk’s and Satya Patel’s venture capital outfit Homebrew , with additional backing from other VCs and celebrity restauranteur Tom Colicchio of Top Chef fame.
The funding will support Slang.ai’s goals to equip restaurants and retailers with its generative AI voice products, allowing restaurants and hospitality groups to augment their answering capabilities with human-like artificial voices that can help customers book reservations, or answer common questions about menu items and opening hours.
“Everyone is frustrated with the experience of calling a business,” explained Alex Sambvani, Slang.ai CEO and cofounder. “No one likes waiting on hold with a retailer to check on an order status or calling their local restaurant to make a last-minute reservation and having their call go straight to voicemail. It doesn’t have to be this way. AI has the potential to fix this broken experience, and Slang AI is bringing AI to the phone.” Samvani and his fellow cofounder and Slang.ai CTO Gabriel Duncan both formerly worked at Spotify as data scientists, which is where they “discovered how powerful and beneficial an AI-powered phone concierge could be for the restaurant/hospitality industry,” according to a Slang.ai spokesperson.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! A toast from new and existing investors The company’s Series A round attracted participation from several prominent investors, including Stage 2 Capital, Wing VC, Underscore VC, Active Capital and Collide Capital. Scott Belsky, founder of Behance, also joined the round.
Additionally, existing investors including executives from leading technology companies like Snap and Zoom, upped their previous backing for Slang.ai.
When asked about the specific AI model(s) or technologies behind its product, the company declined to answer directly. However, Sambvani did provide VentureBeat with an emailed answer: “The specific details of our technology stack are confidential. Our AI engine is built upon a range of different technologies. This ensemble approach allows us to leverage the strengths of each individual technology, and is underpinned by a proprietary training dataset of millions of live, industry specific phone conversations.” Avoid ‘robot hostage situation’ Slang.ai says its software is specifically designed for busy restaurants and retail businesses and aims to eliminate the need for customers to wait on hold, leave voicemails or get stuck in overly robotic, pre-programmed phone trees.
“Calling a business shouldn’t feel like a robot-hostage situation, where you’re forced to listen to horrible hold music and can never reach a human,” according to the company’s website. “By 2030, we will save businesses and consumers 1 billion minutes of precious time, while transforming branded voice experiences into the preferred mode of communication.” Using generative AI capabilities, Slang.ai streamlines the phone experience, automates common interactions and enhances customer service.
The company additionally provides businesses with insights into their incoming phone call patterns. By analyzing data about customer inquiries, businesses can find the best opportunities to re-engage with customers and entice them to spend more.
Off to a promising start(er course) Slang.ai has already gained a foothold among the restaurant and hospitality industries. The company counts more than 200 customers so far, including well-known restaurants Slutty Vegan, Palm House Hospitality Group, STUDS, PLANTA, Hammitt and Nikki Beach Miami, and says it has attained 6X revenue growth year-over-year from 2022.
Anthony Drockton, Hammitt cofounder and chairman said in a statement that Slang.ai has significantly improved customer interactions at his leather handbag and wallet company: “Slang.ai has been a game-changer, helping us to answer calls and serve our clients more consistently than we could with our team alone.” Benson Wang, CEO of Palm House Hospitality , echoed that endorsement, saying: “Slang.ai has become an essential tool for our business. Our team is thrilled with the way it has decreased the disruption of phone calls while simultaneously enhancing the overall experience for our guests. With the intentional use of AI at our disposal, we don’t see ourselves going back.” Serving up supporting data Despite the widespread proliferation of restaurant-finding apps and sites, Slang.ai’s research suggests that 60% of customers still prefer to call restaurants on the phone. By handling more than half of inbound calls without human intervention, the company enables businesses to capture potential revenue that might have otherwise been lost to voicemail In a recent study, Slang.ai says it saved 648 hours of phone time for a six-restaurant group while successfully managing reservations and orders.
Paul Weinstein, senior director of restaurants at PLANTA , shared his experience with Slang.ai: “The phone is a channel rich with data, but we had no way to access it before Slang.ai. We now understand categorically what our guests call for and can modify the AI verbiage to quickly address guest needs.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"NetSPI rolls out 2 new open-source pen-testing tools at Black Hat | VentureBeat"
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"https://venturebeat.com/security/netspi-rolls-out-2-new-open-source-pen-testing-tools-at-black-hat"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages NetSPI rolls out 2 new open-source pen-testing tools at Black Hat Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Preventing and mitigating cyberattacks is a day-to-day — sometimes hour-to-hour — is a massive endeavor for enterprises. New, more advanced techniques are revealed constantly, especially with the rise in ransomware-as-a-service, crime syndicates and cybercrime commoditization. Likewise, statistics are seemingly endless, with a regular churn of new, updated reports and research studies revealing worsening conditions.
According to Fortune Business Insights , the worldwide information security market will reach just around $376 billion in 2029. And, IBM research revealed that the average cost of a data breach is $4.35 million.
The harsh truth is that many organizations are exposed due to common software, hardware or organizational process vulnerabilities — and 93% of all networks are open to breaches, according to another recent report.
Cybersecurity must therefore be a team effort, said Scott Sutherland, senior director at NetSPI , which specializes in enterprise penetration testing and attack-surface management.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! New open-source discovery and remediation tools The company today announced the release of two new open-source tools for the information security community: PowerHuntShares and PowerHunt.
Sutherland is demoing both at Black Hat USA this week.
These new tools are aimed at helping defense, identity and access management (IAM) and security operations center (SOC) teams discover vulnerable network shares and improve detections, said Sutherland.
They have been developed — and released in an open-source capacity — to “help ensure our penetration testers and the IT community can more effectively identify and remediate excessive share permissions that are being abused by bad actors like ransomware groups,” said Sutherland.
He added, “They can be used as part of a regular quarterly cadence, but the hope is they’ll be a starting point for companies that lacked awareness around these issues before the tools were released.” Vulnerabilities revealed (by the good guys) The new PowerHuntShares capability inventories, analyzes and reports excessive privilege assigned to server message block (SMB) shares on Microsoft’s Active Directory (AD) domain-joined computers.
SMB allows applications on a computer to read and write to files and to request services from server programs in a computer network.
NetSPI’s new tool helps address risks of excessive share permissions in AD environments that can lead to data exposure, privilege escalation and ransomware attacks within enterprise environments, explained Sutherland.
“PowerHuntShares is focused on identifying shares configured with excessive permissions and providing data insight to understand how they are related to each other, when they were introduced into the environment, who owns them and how exploitable they are,” said Sutherland.
For instance, according to a recent study from cybersecurity company ExtraHop , SMB was the most prevalent protocol exposed in many industries: 34 out of 10,000 devices in financial services; seven out of 10,000 devices in healthcare; and five out of 10,000 devices in state, local and education (SLED).
Enhanced threat hunting Meanwhile, PowerHunt is a modular threat-hunting framework that identifies signs of compromise based on artifacts from common MITRE ATT&CK techniques. It also detects anomalies and outliers specific to the target environment.
The new tool can be used to quickly collect artifacts commonly associated with malicious behavior, explained Sutherland. It automates the collection of artifacts at scale using Microsoft PowerShell and by performing initial analysis. It can also output .csv files that are easy to consume. This allows for additional triage and analysis through other tools and processes.
“While [the PowerHunt tool] calls out suspicious artifacts and statistical anomalies, its greatest value is simply producing data that can be used by other tools during threat-hunting exercises,” said Sutherland.
Collaborative remediation NetSPI offers penetration testing-as-a-service (PTaaS) through its ResolveTM penetration testing and vulnerability management platform. With this, its experts perform deep-dive manual penetration testing across application, network and cloud attack surfaces, said Sutherland. Historically, they test more than one million assets to find 4 million unique vulnerabilities.
The company’s global penetration testing team has also developed several open-source tools , including PowerUpSQL and MicroBurst.
Sutherland underscored the importance of open-source tool development and said that NetSPI actively encourages innovation through collaboration.
Open source offers “the ability to use tools for free to better understand a concept or issue,” he said. And, while most open-source tools may not end up being an enterprise solution, they can bring awareness to specific issues and “encourage exploration of long-term solutions.” The ability to customize code is another advantage — anyone can download an open-source project and customize it to their needs.
Ultimately, open source offers an “incredibly powerful” ability, said Sutherland. “It’s great to be able to learn from someone else’s code, build off that idea, collaborate with a complete stranger and produce something new that you can share with thousands of people instantly around the world.” Specifically relating to PowerHuntShares and PowerHunt, he urged the security community to check them out and contribute to them.
“This will allow the community to better understand our SMB share attack surfaces and improve strategies for remediation — together,” he said.
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"Report: 97% of software testing pros are using automation | VentureBeat"
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"https://venturebeat.com/programming-development/report-97-of-software-testing-pros-are-using-automation"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Report: 97% of software testing pros are using automation Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Is software testing getting easier or harder? Are testers making use of modern tools to accelerate product release cycles, or are they bogged down by manual processes? To better understand the answers to these questions, Kobiton asked 150 testers in companies with at least 50 employees across a range of industries.
It turns out, software testers are relying more on automation than ever before, driven by a desire to lower testing costs and improve software quality and user experience.
For context, there are two kinds of software testing: manual and automated. Manual is still common but it’s not ideal for repetitive tests, leading many testers to choose automation, which can expedite development and app performance. To wit, 40% of testers responding to Kobiton’s study said their primary motivation for using automation is improving user experience.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Automation in software testing has come a long way “In a study we conducted two years ago, half the testers we asked said their automation programs were relatively new, and 76% said they were automating fewer than 50% of all tests,” said Kevin Lee, CEO of Kobiton. “Nearly 100% of testers participating in this year’s study are using automation, which speaks to how far the industry has come.” Testing managers are prioritizing new hires with automation experience, too. Kobiton’s study found that automation experience is one of the three skills managers are most interested in.
And how is automation being used? A plurality (34%) of respondents to Kobiton’s survey said they are using automation for an equal mix of regression and new feature testing.
And it’s made them more efficient. Almost half (47%) of survey respondents said it takes 3-5 days for manual testing before a release, whereas automated tests can have it done in 3-6 hours.
“A desire to increase automation testing was the top priority listed by testers responding to our 2022 study. Automation clearly is the wave of the future,” said Lee.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Tricentis acquires Testim to extend software test automation in the enterprise | VentureBeat"
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"https://venturebeat.com/ai/tricentis-acquires-testim-to-extend-software-test-automation-in-the-enterprise"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Tricentis acquires Testim to extend software test automation in the enterprise Share on Facebook Share on X Share on LinkedIn Testim for Salesforce Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Tricentis , a software test automation company used by companies such as Merck, ANZ, and Dell, has acquired AI-enabled rival Testim.
Terms of the deal were not disclosed.
The acquisition comes as the global test automation market hit an estimated $20.7 billion in 2021 , a figure that’s predicted to more than double within five years. This growth is being driven by the simple fact that just about every company today is a software company, while at the same time pressure to ship new features and products more quickly increases the likelihood of bugs entering the production codebase.
One of Tricentis’s flagship products is Tosca , which brings autonomous continuous testing to developer teams, saving valuable manual resources in the process. Tosca helps DevOps teams design end-to-end software tests across the entire enterprise architecture, including GUIs, APIs, and even ensuring data integrity.
AI meets SaaS Testim, for its part, is a similar proposition , though it lays claims to being “the first test automation solution to use AI,” a foundation that was seemingly instrumental in Tricentis’s decision to go all in and buy Testim outright. And although Tricentis offers some services under a SaaS model, Testim was created as a SaaS from the get-go, making it easier for companies to adopt “cloud-based testing capabilities with flexible consumption models,” according to a statement.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Elsewhere, Testim also recently launched a test automation product specifically for the Salesforce ecosystem, opening the doors to the some 150,000 companies that use the CRM.
Testim boasts an impressive array of customers which will no doubt appeal to Tricentis too — after launching its Defender Advanced Threat Protection (ATP) enterprise security service back in 2016 , Microsoft sought ways to deploy functional, end-to-end test automation on the software to conserve resources across their engineering, QA, and product management teams. They opted for Testim.
While Tricentis and Testim do overlap somewhat, by coming together they are essentially looking to pool their respective strengths.
“We plan to leverage the best technology across our portfolios and integrate our offerings to build world-class solutions for software quality assurance,” Testim founder and CEO Oren Rubin wrote in a blog post.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Mabl aims to automate software testing, nabs $40M | VentureBeat"
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"https://venturebeat.com/ai/mabl-aims-to-automate-software-testing-nabs-40m"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Mabl aims to automate software testing, nabs $40M Share on Facebook Share on X Share on LinkedIn Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
In the enterprise, the pandemic brought about sharp increases in software release cadences and automation. That’s thanks in part to the adoption of low-code development platforms, which abstract away the programming traditionally required to build apps and software. Respondents to a 2021 Statista survey report that low-code tools have enabled them to release apps 40% to 60% faster, while a full 60% of developers tell GitLab that they’re committing code two times faster and bringing higher-impact technologies into their processes.
However, the accelerated pace of development has introduced new blockers, like a backlog of testing and code reviews. GitLab reports that only 45% of developers review code weekly, with 22% opting to do it every other week instead. It’s not that the pace of innovation in software testing is slowing — it isn’t — but that aspects like installation, maintenance, security, and incompatible problems remain hurdles.
The urgency of the challenge — insufficient testing can lead to security vulnerabilities — has put a spotlight on startups like Mabl , which today announced that it raised $40 million in a series C investment led by Vista Equity Partners. Founded in 2017 by Dan Belcher and Izzy Azeri, Mabl is among a crop of newer companies developing platforms that enable software teams to create, run, manage, and automate software and API tests.
“Despite the fact that the testing category is massive, no software-as-a-service leader had emerged in the space [prior to Mabl] … This void left enterprises to choose between legacy testing solutions that were incredibly complex and expensive and self-managed open source frameworks coupled with bespoke infrastructure that were inaccessible to quality assurance professionals,” Belcher told VentureBeat via email. “Mabl envisioned and delivered an end-to-end testing solution for the enterprise that would combine a low-code framework, a software-as-a-service delivery model, deep integration with enterprise environments and workflows, data analytics, and machine intelligence to disrupt the testing industry.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Automating testing at scale Belcher and Azeri are second-time founders, having previously launched Stackdriver, a service that provides performance and diagnostics data to public cloud users. Stackdriver was acquired by Google in 2014 for an undisclosed sum, and recently became a part of Google Cloud’s operations suite.
With Mabl, Belcher and Azeri set out to build a product that lets developers orchestrate browser, API, and mobile and web app tests from a single location. Mabl’s low-code dashboard is designed to automate end-to-end tests locally or in the cloud, running tests with different permutations of data to strengthen individual test cases.
“Lack of effective test automation is a major problem in the software industry, because ineffective testing leads to dramatically lower team productivity due to rework, overhead, and a general bottleneck in throughput, as quality engineering cannot execute with the same velocity as development and operations. Likewise, ineffective testing leads to poor product quality — from not only a functional perspective but also in terms of user experience, performance, accessibility, and more,” Belcher added. “Low-code is critical because it democratizes testing — making it accessible to quality engineers, manual testers, developers, product owners, and others — rather than limiting efforts to a quality engineer or dev.” Above: Mabl’s automated testing orchestration dashboard.
Mabl can generate tests from the contents of emails and PDFs, adapting as the tested app’s UI evolves with development. An AI-driven screenshot comparison feature attempts to mimic real-life visual UI testing to help spot unwanted changes to the UI, while a link-crawling capability autonomously generates tests that cover reachable paths within the app — giving insight into broken links.
“There are a number of areas where we use machine intelligence to benefit customers. In particular … Mabl automatically trains and updates structural and performance models of page elements, and incorporates these models into the timing and logic of test execution,” Belcher explained. “Mabl [also leverages] visual anomaly detection that uses visual models to differentiate between expected changes resulting from dynamic data and dynamic elements from unexpected changes and defects.” Mabl allows customers to update and debug tests without affecting master versions. API endpoints can be used to trigger Mabl tests, as well as plugins for CI/CD platforms including GitHub, Bitbucket Pipelines, and Azure Pipelines. On the analytics side, Mabl shows metrics quantifying how well tests cover an app, identifying gaps based on statistics and interactive elements on a page.
Growing trend Mabl’s users include dev teams at Charles Schwab, ADP, Stack Overflow, and JetBlue, and the Boston, Massachusetts-based company expects to more than double its recurring revenue this year. But the company faces competition from Virtuoso , ProdPerfect , Testim , Functionize , Mesmer , and Sauce Labs , among others. Markets and Markets predicts that the global automation testing market size will grow in size from $12.6 billion in 2019 to $28.8 billion by 2024.
Automated tests aren’t a silver bullet. In a blog post , Amir Ghahrai, lead test consultant at Amido, lays out a few of the common issues that can come up, like wrong expectations of automated tests and automating tests at the wrong layer of the app stack.
Still, a growing number of companies are adopting automated testing tools — especially in light of high-profile ransomware and software supply chain attacks. According to a LogiGear survey , at least 38% of developers have at least tried test automation — even if it failed in its first implementation. Another source estimates that 44% of IT companies automated 50% or more of all testing in 2020.
“Mabl has over 200 customers globally, which includes 10 of the Fortune 500 and 32 of the Fortune Global 2000 companies. We have active, paid users in over 60 countries,” Belcher said. “The Mabl community in Japan has more than doubled in the past six months — reaching nearly 1,500 members. The Japanese customer base has increased by 322% and revenue has increased by over 300% in the past year, now representing 10% of the company’s total global revenue.” Existing investors Amplify Partners, Google Ventures, Presidio Capital, and CRV also participated in 55-employee Mabl’s round. It brings the startup’s total capital raised to over $77 million.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Merlyn Mind launches education-focused LLMs for classroom integration of generative AI | VentureBeat"
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"https://venturebeat.com/ai/merlyn-mind-launches-education-focused-llms-classroom-integration-generative-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Merlyn Mind launches education-focused LLMs for classroom integration of generative AI Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Merlyn Mind , an AI-powered digital assistant platform, announced the launch of a suite of large language models (LLMs) specifically tailored for the education sector under an open-source license.
Merlyn said that its LLMs, developed with an emphasis on education workflows and safety requirements, would empower teachers and students to engage with generative models that operate on user-selected curricula, fostering an enhanced learning experience.
The LLMs, part of the company’s generative AI platform designed for educational purposes, can interact with specific collections of educational content.
“No education-specific LLMs have been announced to date, i.e., at the actual modeling level. Some education services use general-purpose LLMs (most integrate with OpenAI), but these can encounter the drawbacks we’ve been discussing ( hallucinations , lack of ironclad safety, privacy complexities, etc.),” Satya Nitta, CEO and cofounder of Merlyn Mind, told VentureBeat. “By contrast, our purpose-built generative AI platform and LLMs are the first developed and tuned to the needs of education.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! >>Follow VentureBeat’s ongoing generative AI coverage<< According to Nitta, typical LLMs are trained on vast amounts of internet data, resulting in responses generated from that content. These responses may not align with educational requirements. In contrast, Merlyn’s LLMs rely solely on academic corpora chosen by users or institutions, without accessing the broader internet.
“As education institutions, school leaders and teachers make thoughtful strategic choices on the content and curriculum they use to best help students, Merlyn’s AI platform is built for this reality with a solution that draws from the school’s chosen corpora to overcome hallucinations and inaccuracies with a generative AI experience,” added Nitta.
Teachers and students can use the education-focused generative AI platform through the Merlyn voice assistant. In the classroom, users can ask Merlyn questions verbally or request it to generate quizzes and classroom activities based on the ongoing conversation.
The platform also allows teachers to generate content such as slides, lesson plans and assessments tailored to their curriculum and aligned content.
Eliminating hallucinations to provide accurate educational insights Merlyn’s Nitta noted that existing state-of-the-art LLMs often generate inaccurate responses, referred to as hallucinations. For instance, OpenAI’s GPT-4, despite being an improvement over its predecessors, still experiences hallucinations approximately 20% of the time.
He emphasized the importance in education of precise and accurate responses, as user prompts must draw from specific content sources. The company employs various techniques to ensure reliable, accurate responses and minimize hallucinations.
When a user submits a request, such as asking a question or issuing a command to generate assessments, the LLM begins by retrieving the most relevant passages from the content used by the school district or educator for teaching. This content is then presented to the language model.
The model generates responses solely based on the provided content and does not draw from its pretraining materials. To verify the accuracy of the response, it undergoes an additional check by an alternate language model to ensure alignment with the original request.
Merlyn said it has fine-tuned the primary model so that when it cannot produce a high-quality response it admits the failure, rather than generating a false response.
“Hallucination-free responses, with attribution to the source material, are commensurate with the need to preserve the sanctity of information during teaching and learning,” said Nitta. “Our approach is already showing that we hallucinate less than 3% of the time, and we are well on our way to nearly 100% hallucination-free responses, which is our goal.” Privacy, compliance and efficiency The company said it adheres to rigorous privacy standards, ensuring compliance with legal, regulatory and ethical requirements specific to educational environments. These include the Family Educational Rights and Privacy Act (FERPA), the Children’s Online Privacy Protection Act (COPPA), GDPR, and relevant student data privacy laws in the United States. Merlyn explicitly guarantees that personal information will never be sold.
“We screen for and delete personally identifiable information (PII) we detect in our conversational experiences and transcripts. Our policy is to delete text transcripts of voice audio within six months of creation or within 90 days of termination of our customer contract, whichever is sooner,” said Nitta. “We only retain and use de-identified data derived from text transcripts to improve our services and for other lawful purposes.” The company said that its education-focused LLMs are smaller and more efficient than generalist models. Merlyn’s models vary in size from six billion to 40 billion parameters; mainstream general-purpose models typically have over 175 billion.
Nitta also highlighted that the LLMs demonstrate high efficiency in training and operation (inferencing) compared to general-purpose models.
“Merlyn’s LLMs’ average latency is around 90 milliseconds per [generated] word compared to 250+ milliseconds per generated word for the larger models. This becomes an enormous advantage if an LLM or multiple LLMs have to be used sequentially to respond to a user query,” he explained. “Using a 175-billion-parameter [model] three times in succession can lead to unreasonably long latencies, poor user experience, much less efficient use of computing resources — leaving a much larger environmental footprint than Merlyn’s LLMs.” A future of opportunities for LLMs in education Nitta said that generative AI has enormous potential to transform education. But it has to be used correctly, with safety and accuracy paramount.
“We hope that the developer community will download the models and use them to check the safety of their LLM responses as part of their solutions. In addition to our voice assistant, Merlyn is available in a familiar chatbot interface which responds multimodally (including aligned images), and we are also being requested to make Merlyn available through an API,” he said. “For technically oriented users, we are also contributing some of our education LLMs to open source.” He expressed that, similar to other AI advancements, the most impactful solutions within specific industries, such as education, emerge when teams purposefully develop AI technologies.
“These platforms and solutions will be imbued with a deep awareness of domain-specific workflows and needs and will understand specific contexts and domain-specific data,” Nitta said. “When these conditions are met, generative AI will utterly transform industries and segments, ushering in untold gains in productivity and enabling humans to reach our highest potential.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Why the future of community is in your company's own app | VentureBeat"
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"https://venturebeat.com/virtual/why-the-future-of-community-is-in-your-companys-own-app"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Why the future of community is in your company’s own app Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Social media is dying — at least the way businesses have come to know it. Meta’s earnings call is just the latest signal that Facebook is no longer the ultimate destination for brand awareness and connecting with customers. The tech titan’s profits were cut in half compared to the same quarter a year ago. This sent its stock spiraling.
Two main culprits seem to be at play: a significant drop in digital advertising (thanks to Apple’s App Tracking Transparency) and younger users drifting to newer platforms, like TikTok, at the expense of Meta’s Facebook and Instagram.
While a new wave of social apps have experienced explosive growth among Gen Z users and others, a simple truth remains: When you don’t own the platform, you can’t truly control your interactions with your audience. And this should give businesses pause as they think about their next steps.
How did we get here? Facebook, circa 2010, was arguably the place for businesses to build a community. That’s not to say other social platforms didn’t have communities at the time, but Facebook was the lowest common denominator.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! Companies created business pages and encouraged their audiences to “like” them, inviting consumers to engage with content there. This was all well and good — until it wasn’t.
About five years in, businesses noticed that their Facebook pages were generating less and less organic engagement among their fans. On closer inspection, it was apparent that Facebook’s algorithms gained control of what had previously been organic reach. The social giant’s new revenue model was born. Businesses started paying Facebook to show people their content via boosted posts and advertising campaigns.
Now, in light of the iOS 14 update and the cookieless future of advertising, which will limit the amount of user data Facebook collects from third parties — and therefore its ability to target ads with the same granularity — Facebook’s stranglehold on brands isn’t what it used to be. Couple that with younger generations’ preference for other social sites and services, and businesses are at a crossroads.
Organizations spent many years and big dollars building communities on Facebook, but communities, like technology, are constantly evolving. Facebook no longer adequately serves companies’ needs, yet community has never been more important for brands.
Fortunately, there is a better, more decentralized way to build it.
Going solo to build community The community that once made Facebook one of the biggest platforms in the world will now flourish instead within individual applications. These applications can be purposeful and engaging, so that community becomes part of the overall experience. That means the new, best way to build an active, relevant community around your brand is not to hop to another social site but rather to bring it into your own app.
The community is your property, so you set the rules. You have the best read on the pulse of your users and can provide a space that suits their needs to connect with others, find information or create. If you’ve designed an environment that offers the features users want and respects their privacy (assuming you don’t sell or share their data), you have a good shot at creating a flourishing community that adds value to your business.
By taking community in-app, you also have a natural tie-in with your topic or business. Compare these two basic scenarios: A user is playing a video game and he/she pauses the game to compose a Facebook post that goes out to some people who may or may not understand what the person is talking about before he/she resumes the game.
In the middle of gameplay, a user composes topic-based group chat, voice or video messages that go directly to people who are also actively involved in the game.
Which scenario prompts the highest level of engagement and enjoyment? The answer is clear.
Providing an easy way for your community to interact within the context of your topic earns interest and creates connection. While gaming is an obvious example, the same principle holds for marketplaces, streaming platforms, dating apps and just about any other product that invites conversation among users.
But will users show up? In the past, brands have been reluctant to go their own way, in their own app, because Facebook already had a massive audience to draw from. As enticing as it is, when you look closer, in today’s reality it no longer pans out as you’d envision. Sure, Facebook has the audience, but can you actually get that audience’s attention when the marketplace has gotten so crowded and overrun with everything from jokes to politics? The same risk holds for the future of other social platforms.
To stand out, brands have to create authentic quality content and robust conversations that bring users back. That’s where the hard work is, and that work doesn’t change whether the technology platform underneath is Facebook’s or the brand’s own app.
You can’t just show up on Facebook and expect to pull an audience. If you’re going to do the work of creating a great place for conversation around the topics you care about, then what exactly is Facebook or another platform really getting you? This is the question more and more brands are asking.
Is this where conversations remain? In-app communities are an outstanding way to invite more people to engage and have positive experiences with your brand. In fact, they will become table stakes. But other options, like the metaverse , are surfacing. Will they take over before in-app communities develop to their full potential? Meta has poured billions into creating a new online world. It is striving hard to build a new type of community, one where brands and avatars can interact in ways other social platforms have yet to allow. Brands ranging from Wendy’s and Coca-Cola to Nike, Samsung, Gucci and Louis Vuitton are already there. But will it work? It’s a pretty big gamble.
At the recent Meta Connect event, Mark Zuckerberg said, “The metaverse needs to feel inspired.” Yes, it absolutely does, but people and community are what will inspire it — not the better graphics that were unveiled at the event. Users’ presence and their ability to communicate in authentic ways are what will make the metaverse a place worth visiting, and this is a concept Meta has yet to fully master: Allowing the people to build the communities they want, rather than algorithms forcing experiences upon them.
At the end of the day, communities are about people, not technology. The novelty of the metaverse will certainly attract a crowd, but soon technologies that allow people to immerse themselves in AR/VR will become commonly available, and user preferences will be back to square one: Going where they can find authentic connections. Will that come in your app, or as part of someone else’s experience? John S. Kim is the CEO of Sendbird DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Why getting your tech stack right is critical for your business | VentureBeat"
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"https://venturebeat.com/virtual/why-getting-your-tech-stack-right-is-critical-for-your-business"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Why getting your tech stack right is critical for your business Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
As businesses navigate economic uncertainty, leaders need their teams to be empowered to spend more time on work that matters. This means ensuring that their time is spent on the most strategic and impactful initiatives that quickly address business pressures and deliver increased value to customers.
Yet today, teams are spending a significant portion of the working week not on the work that matters but rather on the coordination cost of work: searching for information, switching between apps, managing shifting priorities and chasing the status of work. This not only impacts productivity, but employee experience as more workers find their ability to make a meaningful impact hampered by duplicated work and wasted time.
Remote work is the culprit The cause can be traced back to the shift to remote work during the pandemic, which was a huge democratizer of workplace technology choices that previously hadn’t been necessary for most businesses. Employees adopted apps that suited their personal working styles, but to meet the sudden needs of distributed working, they often did so rapidly with little strategy.
Today, this means a workplace filled with multiple apps and screens, draining employee focus and leaving them with little idea of who’s meant to be working on what, or by when. Most importantly, they are unclear on how their work impacts the company’s goals and objectives.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! What can help solve this? Having business leaders rethink how they are designing an updated and intentional tech stack — one focused on employee experience and business outcomes For a long time, businesses have thought that “more is better” in terms of tech. But leaders need to take a critical look at that assumption and be more strategic about selecting the tools that have the most impact. Technology should decrease the coordination cost of work, not add to it.
So, given the problem started with an overabundance of technology, how can businesses ensure they are building the right kind of tech stack? Disrupting the meeting norm Without eliminating the coordination cost, businesses risk a less productive — and less fulfilled — workforce. A tech stack fit for today’s workplace can change all that, not only by streamlining workflows and improving processes, but by removing the need for time-consuming meetings and calls to check in on the status of tasks.
Often, breaking away from legacy habits of working requires teams to take the plunge for them to see the benefits. For instance, The Work Innovation Lab at Asana asked a group of participants in a “Meeting Reset” study to cancel the small (fewer than five people) recurring meetings in their calendar for 48 hours, and then redesign what the meetings looked like from scratch.
This led to participants challenging their core assumptions about the design of meetings while returning hours to their day in the process. This tells us that it’s not just the meetings themselves that need to change, but how we think about them. We’re so well-practiced at meetings going into calendars and hardly questioning it that you might even say, at our worst, we’re complacent in how we value time.
Businesses need to shift their company mentality to show that clarity is the end goal — and when reached with fewer meetings, even better. This means taking a step back and deciding what the purpose of a meeting or a call is before having it.
We assume teams know what a good meeting looks like, but leaders should ask themselves what they want to get out of it and, crucially, whether their tech stack can do a better job. Because this way, we shift certain coordination and communication activities away from meetings and create asynchronous modes of collaboration that are often more inclusive and more intentional.
Clarity gets the job done A key feature of the modern workplace is enabling people to work how they work best while ensuring that clarity isn’t lost in the process. Silos can stand in the way of this, as can restricted ways of working, meaning workplaces risk their teams not having the visibility, the headspace or the time to properly communicate, absorb, and update.
Missing out on this information can be bad news for a team’s productivity as more time is then spent on duplicate, or even unnecessary, work. At a time when the majority of generations are disengaged in the workplace, more must be done to ensure meaningful activities are replacing unnecessary work.
Organizations can do this by shifting goals away from meetings and email and giving teams the strategic platform they need to see things clearly. Businesses should look to break clarity free of the synchronous structure we’ve long imposed upon it, and support its transition to becoming more intuitive and natural.
This gives the green light to productive and creative contributions. Empowering teams to work how they want to achieve their goals will, in turn, grow their confidence and their engagement.
Get change management right Better connecting technology strategy with overarching business strategy will ultimately move a company forward. But the key word here is “strategy.” Regular context-switching and unnecessary meetings mean there’s a great deal of brain power being misplaced within the working day.
Simply throwing more tech at the problem won’t help, and without a roadmap that offers a game plan, the more coordination cost of work you stand to create. Tools drafted to help alleviate the pressure on workers risk amplifying the number of pings interrupting their day, leading to greater feelings of pressure and anxiety. At a time when burnout in the workplace remains high, more must be done to help employees reset their burnout levels.
‘Tool fatigue’ is not just a sucker punch for your employees’ work-life balance, but their productivity too. This is why, in building a tech stack for the modern age , businesses should aim to reduce the number of tools in the process. This means there’s less context switching expected from your team, making it easier to stay focused and collaborative, and freeing them up from digital whiplash.
It can be a hard balance to strike. Teams become attached to their tech. But this is why change management is so crucial. In an uncertain macroeconomic environment, leaders need to confidently share, “I value your time and talent; we’re doing this to be more effective.” And then demonstrate to their teams, through first-hand experience, how enjoyable and productive the change can be.
The workplace has undergone a technological revolution that has changed how and where we all work. But the hard work doesn’t stop here.
The workplace is evolving every day and the same goes for technology. Business leaders must keep checking in and matching this evolution with the tools employees need to remain productive — akin to an ongoing temperature check. The pressure comes from the fact that it’s not just productivity that’s on the line, but the future of the workplace.
Anne Raimondi is COO and head of business at Asana.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The next-tech metaverse workplaces of tomorrow | VentureBeat"
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"https://venturebeat.com/virtual/the-next-tech-metaverse-workplaces-of-tomorrow"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The next-tech metaverse workplaces of tomorrow Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Are you ready for the next-tech workplace revolution of tomorrow? Maybe? Yes? Heck no? You aren’t alone. Many people are still reeling from previous COVID-19 workplace transformations.
Regardless of how you feel about it, the fact is, the next workplace revolution is coming faster than you might think and yes, the metaverse — in some fashion — will support the next medium for our employees to work in.t Tomorrow’s metaverse workplace offers an always-on, dynamic and more personalized than ever before “embodied” experience for employees. The lines between digital and physical work and personal lives will continue to blur, and the duality of technology will create new challenges that we haven’t even fathomed. The metaverse will also provide innovative ways to connect people, increase efficiencies and improve knowledge-sharing unlike anything we’ve seen before.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! And it’s already happening. Companies like Accenture are already reimagining how businesses can operate in a metaverse continuum and, because of COVID-19, deployed the technology at scale and even offered on-boarding of new employees in the metaverse. Companies will form new innovative partnerships to envision new business, like the Siemens and NVIDIA venture to build an industrial metaverse.
Skeptical? Remember the ‘new’ smartphones? I know some of you may be cringing at the thought of a metaverse-charged workplace ecosystem, viewing it as a fad that will fade, while others are smiling at the new marketplace opportunities that await your industry.
Let’s take a quick journey back in time. Recall when the first smartphones were launched. No keyboard and just a screen to interact with? Many thought that it was a trend that would never take hold. But in just a few years, that “trend” evolved to more than 6 billion people interacting with information and the internet, transforming business models and how employees work in most industries — and how they live.
Prior to the smartphone disrupting the way people engage, jobs revolved around the time people spent in the office, with no expectation of working when people weren’t physically at the office. The smartphone became an extension, driving new workplace policies for using them — for instance, Ford Motor Company even offered Bring Your Own Device initiatives — and the new always-connected workplace culture emerged.
These advancements redefined work from “a place you go for a set time in the day” to “cutting the tether to desks and freeing people to leverage innovative productivity tools and new virtual spaces to meet any time, any place, from anywhere.” This prompted the business digital transformation in the early 2010s and drove a major shift in how companies leverage technology to advance business opportunities, grow and sustain talent and determine where and when people worked.
Why you should prepare now Examining trends from the last major internet evolution, business leaders most likely have between 5 to 10 years to prepare for the next wave of digital change. This is given the current pace of the development, maturity and confluence of the seven prime technologies that form the metaverse: AI; blockchain; computing technology; augmented, virtual and mixed reality technologies; simulation and gaming technologies; next-generation communications networks; and sensing technology.
These technologies will enable the next human-centric internet transformation — the metaverse — and redefine how companies do business and how people work. The metaverse will likely see behavioral shifts comparable to the smartphone transformation in the mid-2010s that altered how people lived and worked, blending their digital and physical worlds in unimaginable ways.
The metaverse will offer a new lucrative marketplace for companies, employees, and consumers. Companies will need to develop new operating models, talent strategies, and infrastructures to support an evolutionary change at scale if they want to maintain a competitive talent and business advantage.
A McKinsey report assesses that by 2030, the metaverse could be worth $5 trillion , potentially offering a major new growth opportunity for many businesses in retail, financial services, technology, manufacturing and healthcare industries.
As we look to tomorrow, Deloitte experts assess that the metaverse will probably depend on consumer reaction and four key undetermined factors — standardization, market fragmentation, user interface and governance — likely leading to three potential scenarios for the metaverse by the early 2030s. These are: Low orbit: A specialty market for specific uses that will complement but not replace other technologies; Double star: A mainstream market for many applications but split among the next generation of leading platforms.
Big bang: The full migration of today’s internet and more into an immersive world in which most businesses and consumers operate.
Taking into consideration prior trends with technology advancements and workplace transformation, we can narrow the future metaverse workplace to at least two plausible outcomes: A specialized or common workplace in the next 3 to 5 years.
Specialized workplace for some Companies build specialized metaverse platforms to support specific users for specific tasks that will support other technologies. For example, a company may build a digital replica of its supply chain to better understand vulnerabilities, risks and opportunities.
There is limited adoption to specialized workers and it is not integrated into employees’ daily activities. For example, designers, architects and engineers could work in a metaverse workspace to conceptualize or virtually build cars, cities or infrastructures to better understand efficiencies and vulnerabilities prior to real-world fabrication.
Common workplace for many Companies develop dynamic metaverse workspaces to provide their entire workforce with new options to perform many business operations, collaborate and engage in proprietary and partitioned digital-physical ecosystems. This can provide employee efficiencies, offer greater workplace flexibility and create new business opportunities.
The common corporate metaverse will bridge the real and the virtual, with employees straddling both workspaces. For example, the entire workforce could have a shared presence at a town hall or training session by physically being in the space or digitally accessing it from anywhere by leveraging extended reality technology, a mobile device or a PC.
Greater collaboration, engagement Given that the development of the base technologies of the metaverse is in varying developmental stages, many technological factors, as well as social and business norms, could shift how the future unfolds.
However metaverse workplaces of tomorrow materialize, they will offer more blended digital and physical spaces that provide a shared and connected experience for people, regardless of when, how, or what device they use to engage with in their work. Some companies will shift to results-based work models where employee compensation focuses on results and performance, not the number of hours they work in the day.
The metaverse workplace will afford greater collaboration and engagement and more opportunities to gain insights for growth and development. It will also afford added support for well-being and belonging.
Companies will also see new workforce friction points and challenges arise that are akin to those seen with the adoption of the smartphone and the move to remote work during the pandemic. As with anything, there will be growing pains — as well as vast opportunities.
Kayla Lebovits is CEO and founder of Bundle Benefits.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The future of immersive work in the metaverse | VentureBeat"
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"https://venturebeat.com/virtual/the-future-of-immersive-work-in-the-metaverse"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages The future of immersive work in the metaverse Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The metaverse is coming, but what does this actually mean? Beyond virtual DJ sets and the unavoidable social media presence of Mark Zuckerberg’s avatar, headlines surrounding this corner of our digital future can often feel a little Black Mirror -esque.
The reality is that it will feel like an intangible prospect until we are all further involved in the metaverse and until it stretches beyond the reach of those directly building it. For now, its far-reaching applications remain mostly theoretical, so it’s difficult to envision the metaverse being as fully integrated into our daily lives as it promises to be.
When it comes to the world of work, our offices are becoming increasingly digital. The pandemic accelerated our journey towards a remote world of Zoom and Slack. Media narratives often proclaim that remote working is only going to increase and the metaverse will be the middleman between the workplace and the worker, with our offices living entirely in the cloud. This isn’t necessarily the case.
Hybrid working is now, quite clearly, the new norm — and it makes sense as to why. Beyond the joys of cutting commute times and costs and waving goodbye to the soggy pre-prepared sandwich for lunch, working from home can make us 9% more productive.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! For this reason, workers globally are demanding better hybrid policies from their companies. This does present the question: Are we heading for a working culture that is fully virtual? And is the metaverse the route to this? The benefits and pitfalls of VR in the workplace Clips and soundbites from Meta would have us believe that we are hurtling towards an entirely virtual working world, where 1-1s with your manager and quick coffees with colleagues take place in cafés and office spaces resemblant of The Sims , fully immersed through VR headsets.
In suitable instances, this virtual office does have its benefits in improving communication between employees working remotely, providing a space for interaction that is more natural and collaborative than video conferencing platforms and a more concrete community for tele c ommuters.
While perhaps the prospect of a VR office is neither good nor bad, it is also not set in stone.
The VR office is currently being tried and tested as a tool for remote work, and the results are mixed. An experiment at a German university found that, from a full week working entirely in VR, task load increased by 35%, frustration shot up by 42% and anxiety 19%. Therefore, it perhaps is not the most exciting prospect to imagine a world where we are so intensely immersed in the stresses of everyday business.
This being said, the role that technology will eventually play in our day-to-day work depends on how we choose to integrate it. We can, for instance, consider the HR and D&I benefits of incorporating AI and VR into recruitment.
VR interview training models could allow candidates to test their interview skills against AI and reduce inherent social biases when interviewing an avatar.
When done correctly, VR in the workplace can save employers time and money, allowing for further investment in salaries, benefits and training, and can also facilitate a more inclusive hiring process. This balance and the integration of these technologies doesn’t necessarily mean that the workplace has to live in the metaverse; businesses can integrate VR into their operations gradually and to an extent that best suits their needs.
Applications of VR in industries and businesses One only need look to a handful of examples to see how transformative VR is to certain fields. Medicine and healthcare, for instance, have made revolutionary discoveries using VR technology, enhancing surgery procedures and devising customized treatments through VR patient digital twins.
We have also seen the beginnings of a revolution in product development , with developers integrating the benefits of VR into their workflows, with the technology providing samples, tweaks and alternatives to products without the need for expensive and time-consuming physical mockups. This is one example of how integrating VR to a suitable extent can be hugely beneficial — the products delivered are still sold and mocked up physically, but VR can speed up the process and reduce costs along the way.
Additionally, companies that provide almost any form of training can enhance this with VR. This can make the costs of training up to 11 times cheaper and means trainees can retain 70% more information than from traditional classroom learning methods.
This new way of training can benefit a range of workers, from firefighters to retail assistants, making certain jobs and skills more achievable and accessible. In many cases, a blended learning balance between VR and in-person training has proven optimal, not too unlike the benefits of striking a balance between in-person and remote working.
More flexibility, availability VR innovation is also not a one-size-fits-all solution; platforms allow customers to adapt content and interactivity depending on their requirements. This, in turn, makes training across a variety of fields accessible to many learning styles and needs. By taking advantage of this flexibility, staff can comprehend the inner workings of VR themselves and create opportunities to see how the technology can solve problems unique to their workflow. Despite the skepticism of the ‘virtual office’, this will be crucial for companies in the future, not only for the end consumer but for processes and communication.
Companies need to consider the underlying technologies that will build this metaverse and anticipate the incorporation of these into their business models. Much like when businesses had to adapt to the growth of the internet, they now will need to incorporate a strategy for the metaverse in general.
Shiny new technology and the potential that this holds are both hugely exciting, but businesses will see the most success here when they have a measured and purposeful integration strategy.
Molding old and new working practices Bringing the metaverse to the world of work will be a challenge and needs to be done in the right way. While the hardware is developing quickly, it is understandable that many of us approach the subject with a degree of apprehension. We will need to find a middle ground to get the most out of the metaverse.
Enhancing technologies can clearly be incredibly useful: they can improve safety in a variety of fields, and make many features of work more accessible and efficient. These technologies will also be implemented increasingly into day-to-day business practices: For example, elevating customer service and sales experiences and processes. Fields such as fitness and medicine will no doubt also see revolutionary changes in the next decade through these technologies, which is something that we should be ready to embrace.
This does not mean, however, that companies should disregard the value of human-to-human interactions. While the metaverse is coming, this does not mean that with it we will see 8-hour work days in VR headsets, nor does it mean that all of our meetings will take place via avatars around virtual roundtables. The future of the workplace should still incorporate immersive technologies in training, entertainment and in research, and we would be foolish not to utilize such technologies to an extent.
The future of work lies in the middle ground here: In a working society that both makes the most of transformative technologies and does not disregard the value of the Zoom call or the in-person catch-up. Much like hybrid working, VR can aid us in the workplace with and without direct metaverse involvement. No one is exactly sure as to what this will look like, but with appropriate parameters and boundaries in place, the future of immersive work is certainly bright (and sometimes dons a VR headset).
Emma Ridderstad is CEO of Warpin.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Seeking to be hybrid work all-in-1 platform, Envoy acquires Worksphere | VentureBeat"
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"https://venturebeat.com/virtual/seeking-to-be-hybrid-work-all-in-1-platform-envoy-acquires-worksphere"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Seeking to be hybrid work all-in-1 platform, Envoy acquires Worksphere Share on Facebook Share on X Share on LinkedIn COVID-19 forced many organizations to adjust to the current realities of the global business landscape, resulting in a rapid transformation of the workplace. With the pandemic changing the scope of most businesses, remote and hybrid work are the “ new normal.
” The third edition of a study by McKinsey found 87% of people choose to work flexibly when they have the option to do so. Per a Cisco poll , 74% of surveyed employees say that hybrid working has improved family relationships. Undoubtedly, remote and hybrid have come to stay.
However, running a hybrid workplace is complicated and organizations are turning to workplace management solutions like Envoy to smooth out their business processes. In a previous interview with VentureBeat, Envoy founder and CEO Larry Gadea said Envoy’s customers came to the company in the aftermath of COVID-19, seeking to “reopen their businesses for essential workers, but in a safe way that would help people feel confident about coming back.” Founded in 2013 as a sign-in system for office reception desks, Envoy evolved and gained widespread prominence during the lockdown as enterprises sought new ways to keep working despite restrictions on gathering.
The pandemic has since wound down and Envoy is looking to move from a pandemic-boom organization to one that will continue to serve the wider industry now and beyond. To achieve this, Envoy today announced it has now added Worksphere — a platform that simplifies “the hybrid office” — to its rank of acquired platforms as it races to build a complete, end-to-end workplace management tool. This acquisition follows Envoy’s buy-over of desk reservation and scheduling startup, OfficeTogether earlier in August.
Envoy claims it enables workplace leaders to move faster — from streamlining processes that can get in the way of doing great work, to community building. Envoy helps save time and money by having everything needed in the same place, including visitor check-in, desk and room booking, mailroom management and real-time workplace data to make space decisions.
Shape-shifting into a hybrid work platform-for-all Announcing his delight at the strategic acquisition of the YC-backed, Seattle-based Worksphere in a blog post , Gadea said “like Envoy, the Worksphere team built a workplace management platform because they recognized the tremendous opportunity to innovate and challenge the status quo.” He noted the value alignment between the two organizations and how the acquisition will accelerate workplace hybrid work processes. The team at Worksphere is expected to work with Envoy on delivering products that will aid the future of work.
Gadea stated that Envoy has always had ambitious plans for the future, but it’s only by joining the collective experience and thoughtfulness of both teams that they can realize truly innovative products. “The Worksphere team will be key in our ability to scale thoughtful design to highly-complex enterprises and bring industry-leading reliability and customizability to every product we build.” This latest acquisition, according to the company’s press release, will position Envoy in the class of product-led enterprises that maintain relevance beyond the pandemic. Some of Envoy’s clients include big names like Slack, Stripe, Pinterest, Hulu and Mazda. On the list of Envoy’s competitors , according to G2, are The Receptionist, Traction Guest, Proxyclick, SwipedOn, Teem by iOFFICE and others. Since its inception, the company has raised $170.2 million in total funding to date.
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"Leveraging interactive design to maximize employee engagement | VentureBeat"
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"https://venturebeat.com/virtual/leveraging-interactive-design-to-maximize-employee-engagement"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Leveraging interactive design to maximize employee engagement Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Static workplaces are a thing of the past. Today’s workforce trends prioritize employee satisfaction and well-being — creating enjoyable, interactive work environments is at the forefront.
With more than 102 million Americans working in an office on a daily or part-time basis, the elements of the physical workspace cannot be ignored, as employee engagement and positive culture hang in the balance. With the right interactive design, organizations can better focus on their people and how they interact within the workspace for maximum collaboration and productivity.
While there are many considerations to a physical workspace, technology-driven design that sparks engagement promotes success and impacts every industry at every level. Employers who want meaningful collaboration at work need meaningful office elements to inspire and empower this mission. From tangible to intangible components, here are a few essential interactive design strategies to meet today’s workforce needs while pushing full speed into the future of work.
Activity-based workspaces According to a recent survey, 43% of workers are bored. Creating an activity-based workspace to cultivate engagement and innovation is an effective method to combat boredom and allow employees to have more flexibility and autonomy. Essentially, activity-based working allows employees to choose their setting based on the particular task at hand.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! For instance, an office with a designated “calm zone” offers a place for employees to recharge or quietly brainstorm. Shared office spaces have also been reimagined through the use of technology, such as with interactive digital jukeboxes that bring employees together through song. Ultimately, activity-based workplaces offer a variety of environmental elements, all within one office.
Interactive screens In today’s digital landscape, most workers are surrounded by screens, from smartphones to conference room projectors, and this spans across all industries.
For instance, a restaurant worker uses point-of-sale screens to place orders; a banker relies on computers for customer transactions; and a warehouse manager may use an iPad to record and track inventory. Screens are now the norm, but what if employers leveraged them to enhance productivity and boost workplace culture? For a collaborative workspace, smart rooms with interactive screens are essential. With dispersed teams and corporations that span the globe, conference rooms designed with interaction in mind are crucial.
Modern technology makes it possible to control screens from a simple mobile device, and the options to engage a team are endless. From real-time polls, attention-grabbing graphics, HD videos and virtual speakers who feel like they’re actually in the room, interactive screens are changing the way technology boosts engagement.
Additionally, screens as an employee perk have the power to unite, encourage and promote individual choice and diversity, which can improve workplace culture. Consider an interactive tool that plays shared music all from one in-office screen. The opportunities to dance, laugh and have conversations are endless.
Designs to promote well-being Employee well-being and engagement have a clear link. According to Gallup , a high level of well-being enhances the benefits of an engaged employee, meaning that the two factors work in tandem, producing results that drive workplace success. In fact, employees with high engagement and low well-being are 61% more likely to feel burnout “often” or “always.” When employers focus on both engagement and well-being, they can better retain happy employees. Research shows that engaged employees with high well-being are 59% less likely to seek a new job in the next 12 months.
So, to obtain this desirable blend, workspaces must be designed with both outcomes in mind — engagement and well-being. An interactive design can promote well-being through calm zones where workers can refresh. Simply having the choice to select the best space to complete a certain task or recharge brings satisfaction and instills a sense of true value. Sitting at the same desk next to the same people every day will wear down even the most motivated employee. Options and variety are ideal to maximize employee engagement.
Technology to enhance connections Human connection in the workplace is more important now than ever. In fact, 72% of workers said they experience loneliness on a monthly basis, and 55% report feeling loneliness weekly. The question is, has technology made the workforce a lonelier place? While tech tools support collaboration and dispersed teams, it’s time to ensure that the digital age is not driving workers into isolation. With the right strategy, technology should enhance human connections rather than diminish them. Individuals are seeking greater meaning at work, and 70% of employees say that their sense of purpose is heavily dependent on their work, according to McKinsey’s analysis.
To reach this level of purpose in the workplace, human bonds must be formed, and technology is the perfect tool to leverage.
To truly thrive in the digital landscape, whether in a hybrid or in-office setting, requires finding a perfect blend of technology and human touch. For instance, instead of supporting the use of isolating earbuds, encourage shared music and collaborative playlists at work, and rather than hosting a brainstorming session over Slack or email, gather in the conference room or at a local park. Technology must complement human interaction, and it takes intentionality to strike the right balance.
When driving engagement in the workplace, it’s important to consider how to best leverage interactive design. With activity-based workspaces, interactive screens, well-being at the forefront and employee-driven devices, employee engagement will have a healthy environment to grow. It’s up to businesses to invest in these workplace elements to boost culture, productivity and engagement.
Ross Honey is president and CEO of TouchTunes.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
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You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How tech leaders can reduce burnout and protect their most valuable employees | VentureBeat"
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"https://venturebeat.com/virtual/how-tech-leaders-can-reduce-burnout-protect-most-valuable-employees"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How tech leaders can reduce burnout and protect their most valuable employees Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
IT and cybersecurity professionals are often the unsung heroes of an organization — underfunded, overworked and short-staffed despite their importance in keeping sensitive business and customer data safe. It’s no wonder these employees are vulnerable to burnout — chronic workplace stress that results in mental and physical exhaustion. In fact, a recent survey found that almost half (47%) of cybersecurity incident responders say they’ve experienced burnout or extreme stress over the past 12 months.
Striving to achieve a better work-life balance is no new concept and this was only heightened following the pandemic. While employees may frequently see tips or messaging about what to do to reduce burnout (such as setting work-life boundaries or taking time off), in truth these actions can be much harder to put into practice at an individual level, and can be extremely difficult to manage and support from the leadership perspective. If not implemented into a company’s cultural core, ad hoc relief tactics may grant employees temporary release, but will never truly stop the cycle of chronic burnout. For leaders to ensure that balance becomes a workplace norm, leadership must start with stepping in and doing intentional, routine work from the top down.
The work-from-home movement also brought an increase in cyberattacks and data breaches — up 15.1% in 2021, according to one report.
Eliminating burnout among tech and cybersecurity professionals is not just good for company morale and employee retention, it is also essential to ensuring the overall safety of the organization. Here, I share my top recommendations for how leaders can reduce burnout in their organizations while balancing this effort with the essential work IT professionals handle.
The truth about PTO Many organizations recognize the importance of taking time off work to rest and recharge, and encourage their employees to take advantage of their paid time off (PTO), but talk only goes so far. If an IT administrator, for example, is completely underwater with responsibilities that are key to keeping a company up and running, they may not feel comfortable taking time off, or push it off until a time when they are less busy — a time that never arrives. Or, even worse, they are the only person on their team and there is no one to cover for them when they do request to take that time off.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! To circumvent this, I have instituted at many of the companies where I’ve had leadership positions the concept of “Down Days.” This is a program where different groups within a company have a required day to disconnect from work separate from their normal PTO. The intent is to have the employee do something just for them — whether they enjoy hiking, going to the movies, or gardening — and then upon return to work the next day, they can share with their team what they did. This serves to bring teams closer together and provide time off simply to rest, as opposed to taking time off for a specific reason (such as a doctor’s appointment or a sick day ).
I grew up and spent the start of my career in the UK, and I, like many, have noticed a major cultural difference in the way people take time off in the U.S. versus in Europe. People in Europe take full advantage of the time off they are given, but in the U.S., many in the IT industry will save up their PTO, allowing it to roll over to the next year and cashing out when they move on from the job. We as leaders need to change the concept of earned PTO and shift to flexible PTO that everyone is encouraged to take to ensure separation from work and relaxation.
Down Days and flexible PTO offer a good alternative to this mindset of hoarding PTO, and to policies that seek to solve this by requiring employees to use their PTO during a certain time frame or else lose it. While likely well-intentioned, such requirements only serve to create another kind of barrier for employees seeking to take time off.
Burnout prevention starts at the hiring stage Creating a culture of trust in your organization is one of the most important aspects of preventing burnout. Requiring your employees to stay on for long hours, or heavily monitoring their work, only adds more to their plate and wastes time. To allow employees to do their jobs effectively, and in a way in which they enjoy coming to work, leaders need to trust that their employees will get the work done.
This means hiring on the basis of values, rather than just skills. Skills can be taught, but if a person’s values do not align with those of the company, it will be difficult to maintain a workforce that you can trust and that embodies the energy of your corporate culture. I look for employees who are flexible, team players who leave egos behind. They need to have a fundamental sense of morality — that is, thinking in terms of making things better rather than just making money.
Once you employ these talented and smart people, your main job as a leader is to create an environment where they can excel. This means putting strategies in place to prevent overworking employees and placing a greater emphasis on output, rather than hours worked.
Be the change you want to see Creating a culture shift like this must start at the top. It really is the CEO’s responsibility to set an example and an expectation that reducing burnout is a priority.
Leaders can start on this journey by stepping back and building clarity around what’s most important to their company, or more specifically, to their unique teams. Everyone has an ever-expanding to-do list, and some tasks can feel tedious or pointless. It’s important to emphasize how tasks at every role map back to overall business goals. This can remind employees of their purpose and show how they are actively contributing to the company and creating impact from their work while pushing aside unneeded pressure on tasks that do not contribute to the overall vision.
Additionally, bringing IT professionals into wider company conversations will not only help your company to run more smoothly, but educate others in the company on what the IT team’s role is and why it is so essential. This will reduce the workload on these employees, making them more than just a dumping ground in the eyes of those not involved in IT.
Making burnout prevention a priority is essential to keeping your employees happy, healthy and productive, driving better results for your business and your team. Affording employees the time and mental headspace to contribute new ideas will help to retain them and drive their growth through the company. If the industry continues to take IT and cybersecurity professionals for granted, I have no doubt that innovation and security with suffer as a result.
David Bennett is a tech veteran and a seasoned channel executive with more than 30 years of IT channel leadership, currently as CEO of Object First , which aims to reduce ransomware and simplify data protection.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Anything but small: Micro events bring big benefits | VentureBeat"
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"https://venturebeat.com/virtual/anything-but-small-micro-events-bring-big-benefits"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Anything but small: Micro events bring big benefits Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
If you’re not telling your story through video, your competitor is. Video content has quickly become a primary communication channel with your target. And if you’re not speaking to your audience in the way they prefer to be spoken to, you’re already behind. But effective video content goes beyond what you see in a social stream.
Organizations are feeling the pressure to “get video right” for all of their content needs — including in the events space. While video became a must-have during the pandemic, it’s clear both hybrid and virtual-only events are here to stay.
Adding another layer of complexity to the events landscape is the shift away from only hosting one or two large events per year. Companies are beginning to supplement their key thought leadership initiatives with micro events, which can be webinars, live video broadcasts, networking opportunities, townhall-style or intimate, highly targeted events.
Facilitating ongoing engagement Micro events are condensed in size and scope (30-45 minutes is ideal), traditionally held virtually and executed multiple times per year, with the exact number varying by company and the objectives it’s looking to achieve.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The ultimate goal behind micro events is to facilitate an ongoing engagement model where you’re positioned to share, promote and leverage video content more consistently and increase engagement with your target through ongoing pulses of communication.
If an organization was solely dependent on a large event to communicate crucial and time-sensitive information, it could result in a missed opportunity to connect with its audience. Ongoing micro events, paired with consistent communication between events, allow you to be responsive and get ahead instead of simply keeping up.
Just as polished as in-person One of the biggest misconceptions is that a micro event means it can be less polished than a traditional event. Simply put, that is not the case. Just because an event is micro doesn’t mean you treat it as such. It needs to be executed with the same level of discipline and thoughtfulness as that of a traditional event.
That being said, the overall approach to creating content for a micro event versus a traditional one will be different.
In a virtual environment, it’s best to keep the content engaging, focused and to the point. Generally, having different speakers and/or new content every 10 minutes will keep the audience’s attention. Depending on the subject matter, this may not always be possible, but the goal should be to make the content on camera as energetic and entertaining as possible to keep your audience engaged.
How to make the move into micro events When a company is ready to get started with a micro events model, the inclination is to immediately solve the platform question — what tool are we going to use to deliver the content and event? But this should actually be the last step in the process.
First, you need to define what success looks like and develop a video content strategy that facilitates the desired behavior. That could mean driving more sales, increasing sign-ups or visiting a landing page.
Doing more video for the sake of doing video will no longer cut it — you need to determine what behavior you’re hoping to influence and how success maps to that. Establishing those key performance indicators (KPIs) will not only act as the framework for your micro events, but you’ll be able to adjust them accordingly after each event to help ensure that you’re tracking toward any overarching or larger goals for the business.
With the KPIs known, you can start to figure out what you want to say and who in the organization should say it. Conducting outreach to your key audience is helpful to learn what would be valuable to them. This can come from quick surveys , email and/or social media polls, or feedback you’ve heard from other events you’ve hosted.
The crowdsourced ideas and suggestions can become the themes for events throughout the year. If there isn’t time to gather input from your target, select a topic or two that you feel would be most helpful to them based on key insights or trending topics in the industry.
Stemming from those initial micro events, you can analyze your KPIs and event metrics and pivot as needed. Ideally, there should be a throughline between your events for connectivity, to build momentum and continue conversations from one event to the next.
Choosing the right hosting platform At this point, you can look at hosting platforms. KPIs plus the type of content you want to present should be the determining factors when assessing a tool.
For example, if the goal of your micro event is to facilitate a small, collaborative session among participants, a basic web conferencing tool is going to be an appropriate selection. If the event will follow a more traditional path — an individual presenter sharing information — a webcasting tool will provide more options for event management and engagement, such as polls, live Q&A and multi-streaming.
Knowing how you want your audience to interact with the content and the type of event experience you want to provide for attendees will help you pare down the choices much more quickly as you assess the various features and functionalities and rule out whether or not they can help meet your goals.
Keeping the momentum going post-event After all the prep and planning, your micro event goes off without a hitch and now you can rest easy, right? Actually, after an event, there’s still work to be done. The period in between events is arguably one of the most important parts. This is when you need to deliver a regular cadence of content stemming from the event. Content that either is new or has already been shared or dives deeper into the event’s subject matter does well because of its value add.
The follow-ups with additional content will allow you to glean feedback, keep your company top of mind and help foster an ongoing dialogue with your audience. Plus, you’ve already created an abundance of new video content, so repurposing it and continuing to leverage it throughout the year maximizes its value.
Behold the benefits of micro events That may seem like a lot to do, but the benefits are big. There are a lot of companies trying to capture the attention of your target daily. Micro events position your organization to provide relevant content consistently, increase visibility and foster meaningful connections with your target.
Through feedback and ongoing conversations, you’ll know what is (or isn’t) resonating and adjust content, event topics and even business goals quicker. Keeping your finger on the pulse in this way helps you work smarter, not harder, because you’re providing thoughtful, more proactive content that matters in the moment.
What’s important to remember is that people crave content, and in some way, shape or form, they will find what they’re looking for. The key is to make the content they find yours. Optimize the content for search with SEO keywords identified and included in content titles and descriptions.
Additionally, make sure the content is tagged with enough metadata so that if there is a lot to choose from in a resource center, the target can find exactly what they are looking for through filters and search fields.
Micro events are a way to get your thought leadership in front of the right people, at the right time and for the right purpose. While it might be a deviation from how your organization has approached video content and events in the past, micro events can have a sizeable impact on your business.
Donny Neufuss is director of business development and strategic partnerships at Sonic Foundry.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"4 key ways to empower your remote workforce | VentureBeat"
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"https://venturebeat.com/virtual/4-key-ways-to-empower-your-remote-workforce"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest 4 key ways to empower your remote workforce Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
According to the United States Bureau of Labor Statistics, the U.S. voluntary job abandonment rate at the end of May 2022 was 25 % higher than before the pandemic.
This is not a new phenomenon. Are some of your employees focused only on their tasks? Do they rarely want to take the initiative or help their colleagues? When deadlines pass, do they say, “That’s not my fault!” Remote employees often don’t feel attached to workplace culture. They can consider their workplace to be toxic. While trying to boost remote employee engagement, employers sometimes engage in “stalking” tactics. For instance, they observe whether employees always have a green light on their Slack during work hours. They may monitor employees’ screen time or count the hours spent on a laptop. Even worse, they can scan clicks per minute.
Instead, they should be empowering their remote workforce.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! ASQ defines employee empowerment as: “How organizations provide their employees with a certain degree of autonomy and control in their day-to-day activities. This can include engaging in process improvement, supporting the creation and management of new systems and tactics, and managing small departments with less senior management oversight.” Use time-measured goals If not measuring a worker’s time spent at work, monitoring if they are online, and asking to submit reports on what they are working on, then what? Measure their achievement and how they are meeting their objectives on a daily basis.
It is essential to make this measure transparent, time-limited, and visible throughout organizations. There are four main principles to create a bias for independent actions.
First, team members must be supported in setting up their daily processes and developing strategies to achieve their goals.
For that purpose, you may hold regular meetings with remote employees.
And when new employees are onboarded, talk with them and set goals for the next three months. For example, you might establish a $40,000 new MMR plan for a sales manager for the next three months. Make sure not to limit the employee in achieving that goal. Let them build their tactics and strategies and collaborate with any department that they need to, to achieve the goal.
For a customer-facing role, I like the results measurement that GitLab uses: identifying customers’ OKRs and KPIs , and measuring a variety of end-user performance metrics.
Setting long-term goals will provide employees with a clear understanding of what you are expecting from them, and at the same time, you will be able to monitor their performance in a less toxic way.
Empower employees to take independent actions and decisions. Don’t set limits on creativity. Remove hurdles and red tape. Set a time frame for reaching specific goals and create an enabling environment.
Create one knowledge source The second principle is inseparably linked to the first. Actions and new tactics must be informed to be empowered to work with a bias toward independence. To accomplish that, create one corporate knowledge source — a corporate Academy or University. Also, set up a platform to track employees’ performance and task completion and encourage them to create a dashboard with their tasks and deadlines.
Ensure that all employees working remotely and scattered in different countries use the same knowledge and task source.
Ask them to change the status when they start working on an assignment and when it is completed.
Ask employees to write down the ideas and strategies they want to implement in a task planner so everyone can see where the current task is, and who’s involved.
Also, manage the knowledge source so that employees can receive answers when they have questions. Plan for the unexpected, and prepare younger employees by empowering them to use extreme ownership.
For example, a customer contacts your technical support with a question. The employee handling the call is still a novice and needs to learn how to help them. Instead of Googling or postponing the problem to better times, they go to a corporate university and quickly find answers. Also, encourage employees to ask questions. Provide employees with links to thematic forums and contacts with their senior colleagues. Show that senior employees are always there, and happy to answer questions.
Use ROIs Once you’ve empowered the team with the bias toward independent tactics and strategy creation, start encouraging independent learning. Cultivate a focus on iteration. To track the efficiency of learning programs, use ROIs in training to measure whether a course or program offers value for the money. Plan how you will evaluate, whom to involve, the success criteria and how long it will take. Also, ask questions like, what are the desired outcomes? What is the current state? What changes have taken place that aided long-term change in learners? Encourage real-time achievements sharing Finally, consider the tactics you have in place for executing goals. I don’t monitor employees’ work screens in my company. Instead, I watch how they are moving toward their goals.
Ask them what they think are the best ways to achieve their goals. What do they do if something doesn’t work? For example, at my company, we have a monthly meeting where all departments share their results. When all members show their presentations and talk about leads and new clients, remote employees feel a team spirit.
Also, we have a Slack chat where employees share their goals for the current three months and what they have done in the past week to achieve those.
Your employees’ results are what really matter. Let’s stop monitoring remote employees’ engagement on Slack or comparing it to clicks they’ve made per day. Instead, let’s focus on results by setting the right goals measured in time, creating team spirit, and implementing learning measures. That’s what we can call empowering employees.
Vladimir Polo is CEO and founder of AcademyOcean.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"U.S. Army chooses Google Workspace to bring zero trust to the multicloud | VentureBeat"
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"https://venturebeat.com/security/u-s-army-chooses-google-workspace-to-bring-zero-trust-to-the-multicloud"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages U.S. Army chooses Google Workspace to bring zero trust to the multicloud Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Securing multicloud environments isn’t easy, especially for high-profile organizations like the U.S. Army. As the Russia-Ukraine war continues and offensive operations on both sides of the conflict escalate, nation state-sponsored cyberattacks remain a constant threat.
Yet in spite of this heightened threat landscape, the U.S. Army has the confidence to go all-in on remote working and collaboration.
Just last week, Google Cloud announced the U.S. Army’s new partnership with Google Public Sector that will provide 250,000 soldiers with Google Workspace , after Google achieved the Department of Defense’s (DoD) Impact Level 4 (IL4) authorization.
This decision is noteworthy because it highlights that enterprises don’t need to abandon digital collaboration tools to stay productive. By prioritizing tools that enable zero trust access controls, organizations can reliably secure their multicloud environments against even the most determined attackers.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Google Workspace secures the multicloud with zero trust The announcement comes after Google announced the launch of Google Public Sector (GPS) in June 2022. This new division is designed to help public-sector entities like federal, state and local governments and educational institutions accelerate their digital transformations.
For the U.S. Army, part of that process is making collaboration secure for personnel working in different remote locations and training bases. One core component of collaboration security via Google Workspace is zero trust.
“As the Biden Administration’s Executive Order on Improving the Nation’s Cybersecurity states, it’s important that the federal government adopts security best practices that advance toward a zero-trust architecture to keep pace with today’s increasingly sophisticated cyberthreat environment,” said Will Grannis, CEO of GPS.
“We offer products with the security ‘baked in’ the product so our customers don’t need costly add-ons. For example, Google Workspace leverages Google’s zero-trust technologies to provide a secure email, communication and collaboration solution and is part of a set of existing solutions by Google Cloud which can help accelerate any agency’s zero-trust efforts to protect against cyberattacks,” Grannis said.
The U.S. Army also confirmed that zero trust played an integral role in securing its multicloud environment. “The Army and DoD have committed to a multicloud strategy, and this decision reinforces the need for a cloud-based ecosystem to support the diverse needs of the DoD,” said a U.S. Army spokesperson.
“Google’s zero-trust capabilities align well with the DoD Zero-Trust reference architecture and enables the Army to further integrate the solution into our existing cloud-based cybersecurity environment for advanced threat detection, monitoring and risk management,” the spokesperson said.
Implications for enterprises This partnership between the U.S. Army and GPS has implications for the wider enterprise market, because it shows not simply that Google Workspace can protect regulated data but, more importantly, that collaboration can be made secure in hybrid and multicloud environments through zero trust.
Given that research shows 90% of organizations have already deployed multicloud architectures, zero trust has the potential to redefine cloud security in the future.
This is good news given that there’s no way to undo the remote-work revolution that took place during the COVID-19 pandemic. Today’s users and employees expect to be able to access applications whether they’re working in the office or at home, and multicloud environments play a key role in facilitating this.
Defining zero trust At its most basic, zero trust is about authenticating every user and device within and outside an organization’s network before they can access certain applications or resources. It’s a concept that applies as much to multicloud environments as it does to gated on-premises networks.
“Zero trust cares little about being deployed on-premises, in one cloud or in multiple clouds,” said Gartner VP analyst, Thomas Lintemuth. “The keys to zero trust are 1) identifying your applications, and 2) [determining] which users from which endpoints should have access. Once a basic zero-trust architecture is built, continue [adding] signals to increase the efficacy of the trust calculation.” Part of the challenge around implementing zero trust is that an organization has to not only authenticate users, but offer a robust user experience while doing so, or users won’t be able to access resources at the speed of business, and will become less productive.
In this environment, traditional solutions like VPNs simply aren’t effective or scalable at authenticating users. Organizations need to provide employees with user-friendly, high-performance solutions that can enable them to authenticate on their local devices. This is where Google Workspace and Office 365 come in.
Google Workspace vs. Office 365 Across the widespread ecosystem of collaboration tools, Google isn’t the only provider on the market to start leveraging zero trust to help enterprises secure remote environments. Microsoft Office 365 has its own array of zero-trust capabilities.
For instance, enterprises can use Office 365 alongside tools like Azure Active Directory’s Conditional Access with Microsoft Intune to control access to cloud applications and SaaS services. They can also be used to apply device access policies to determine what authentication steps the user needs to follow to log in.
It’s worth noting that collaboration providers like Slack have also begun experimenting with zero trust, incorporating identity and access controls including SAML-based single-sign on, two-factor authentication, user and group provisioning, and session management to reduce the risk of unauthorized access.
As the need to secure decentralized working environments increases, the zero-trust capabilities of Google Workspace and Office 365 are becoming ever more important differentiators in the collaboration market.
According to Statista , in the office suite market (defined as solution providers with software applications offering word processing, spreadsheets and databases), Google G Suite (now known as Google Workspace) holds 48% of the global market while Office 365 holds 46%.
Going forward, securing user access comes down to not only implementing a robust process for authenticating users and reducing the risk of breaches, but also offering a user-friendly login process that can keep up with the pace of business.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How to stop data leaks in Slack and SaaS apps, Metomic raises $20M | VentureBeat"
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"https://venturebeat.com/security/how-to-stop-data-leaks-in-slack-and-saas-apps-metomic-raises-20m"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages How to stop data leaks in Slack and SaaS apps, Metomic raises $20M Share on Facebook Share on X Share on LinkedIn Metomic cofounders Ben van Enckevort, CTO, and Rich Vibert, CEO.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Collaboration is a data security nightmare. The more accessible data is to employees working remotely, the greater the risk of it falling into the wrong hands. After all, today’s critical data assets aren’t just residing in tightly controlled on-premises servers, they’re often openly available in SaaS apps and collaboration tools like Slack.
However, a new breed of data security provider is emerging, looking to prevent data leakage from SaaS apps altogether. One such provider is Metomic , which today announced it has raised $20 million as part of a series A funding round led by Evolution Equity Partners. Metomic specializes in using artificial intelligence (AI) to detect data leaks in SaaS apps.
Metomic’s solution uses AI to identify data leakage risks in real time with no-code workflows that security teams can use to automate data policies across SaaS applications like Google Apps, Slack, Jira and Zendesk.
This “human firewall” approach means that if a user exposes a sensitive file, Metomic will generate a real-time notification to notify the compliance team about potential violations.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The cost of collaboration The announcement comes as SaaS apps have emerged at the heart of a number of high-profile data breaches, the most notable impacting Rockstar Games and Uber , where hackers used social engineering to gain access to both companies’ internal Slack channels.
One of the unfortunate realities of the hybrid work era is that SaaS apps are a honeypot of confidential information and intellectual property that cybercriminals can and will exploit if they have the opportunity to.
“With the growth of remote work, the volumes of sensitive data being shared via these tools continues to rise. It is incredibly easy for employees to share data on these apps every single day, leaving behind huge data risks in the natural course of day-to-day business,” said Richard Vibert, Metomic CEO and cofounder.
Augmenting these challenges is a lack of transparency over what types of sensitive information and IP are shared.
“Today, organizations don’t have the visibility to answer questions like ‘how much PII is in my Google Drive?’ In five years, the ability to answer this question — and more nuanced ones like ‘which U.S. employees have access to EU customer data?’ — will become table stakes,” Vibert said.
Metomic’s answer to these challenges is to provide a solution that enables security teams to create custom classifiers for what constitutes PII. Then the tool will use those classifiers to automatically identify sensitive data shared within the app, assign an AI-driven risk score, and redact it if it’s protected.
A look at the SaaS security market Metomic’s solution sits within the SaaS security market , which researchers valued at $8.2 billion in 2021, and estimate will reach $21 billion by 2028 as more organizations look to secure their attack surface against threat actors.
One of Metomic’s main competitors in the market is Wing Security , which raised $20 million in series A funding last year with a platform designed to discover SaaS apps, users and vulnerabilities.
Another key competitor is AppOmni , which offers inventorying for all installed third-party apps, as well as configuration management and threat detection for SaaS applications and identification of data leaks. Last year, AppOmni raised $70 million in series C funding.
The key differentiator, according to Vibert, is Metomic’s use of AI “to identify the risks that actually matter. And by making it easy for security teams to involve their workforce in quickly remediating and preventing sensitive data risks through real-time Slack notifications.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"With collaboration app for security teams, Balance Theory raises $3 million | VentureBeat"
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"https://venturebeat.com/security/collaboration-apps-security"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages With collaboration app for security teams, Balance Theory raises $3 million Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Collaboration apps are a staple of the remote working era, but they’re also open to compromise. It only takes one hacker to gain access to an employee’s login credentials to access workspaces full of confidential information and materials.
That’s why cybersecurity collaborative workspace provider Balance Theory , which today announced it has raised $3 million as part of a seed funding round led by DataTribe, has developed a collaboration tool for security teams.
Balance Theory’s solution provides users with a secure, encrypted platform to manage security workflows, processes, technical documentation and playbooks, in a single location with classification and redaction capabilities. It also integrates with existing collaboration tools like Slack and Microsoft Teams.
It’s an approach that enables board members, auditors, new hires and vendors to get a top-down perspective of the security team’s protections.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The need for secure collaborative workspaces The announcement comes as collaboration apps have increased risk for enterprises substantially.
One of the most notable examples of this occurred just a few months ago, when hackers breached Rockstar Games’ internal Slack channel, exfiltrated content, assets and source code from Grand Theft Auto VI, and released over 90 videos and images on GTAForums.
Collaboration apps are a prime target for cybercriminals because they know that these solutions contain a mountain of protected data and intellectual property that’s being discussed among employees. If an intruder successfully hacks a collaboration app, they have access to a central repository of high-value information.
However, Balance Theory isn’t just providing a protected collaboration environment, it’s also offering a place where security teams can optimize their processes without reliance on inefficient legacy solutions like spreadsheets.
“When asked the question: tell me the story of your cybersecurity program … most today respond with PowerPoints and Spreadsheets populated on the back of siloed, dispersed, and hard-to-assemble information,” said Greg Baker, CEO of Balance Theory.
“Balance Theory provides the space to solve the building, management and communication of all aspects of an enterprise cybersecurity team in one integrated secure and trusted platform,” said Baker.
Users can communicate through a live chat function using features like redaction to remove sensitive information, while security teams can implement public sharing controls and permissions management to determine who can access shared materials.
Cybersecurity providers target the collaboration tools market According to Baker, Balance Theory’s main competitors are legacy solutions for creating and managing cybersecurity programs. However, there are also a number of secure collaboration tools emerging for enterprises.
One vendor focusing on securing enterprise communications is Element , which offers a secure, end-to-end encrypted collaboration platform that’s also designed for security teams. Element’s solution provides single sign-on (SSO) and data loss prevention (DLP) capabilities to reduce the risk of data leaks.
Last year, Element raised $30 million in funding.
Other vendors, like Safeguard Cyber , are taking a different approach to collaboration security by offering a platform that offers visibility into communication channels like Microsoft Teams and Slack.
Safeguard Cyber’s solution enables security teams to detect social engineering attempts and malicious links across the collaboration apps they rely on every day. Safeguard Cyber most recently announced raising $45 million in funding in 2021.
Baker argues that Balance Theory’s range of security measures differentiate it from competitors. “We are built securely with features such as encryption, redaction, classification and provenance to provide the most secure collaborative workspace on the market.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Tim Berners-Lee shares his vision of a collaborative web | VentureBeat"
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"https://venturebeat.com/programming-development/tim-berners-lee-shares-his-vision-of-a-collaborative-web"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Tim Berners-Lee shares his vision of a collaborative web Share on Facebook Share on X Share on LinkedIn Sir Tim Berners-Lee Tim Berners-Lee founded the web in the early 1990s as a tool for collaboration. But this initial vision was sidelined by read-only web browsers better suited for consuming content instead of collaboration.
Web2 has since brought us apps, mobile and the cloud. But data and authentication were tightly coupled to the apps for security reasons. As a result, the Web2 era was defined by a few big companies that use our data to lock us into their platforms.
Now Berners-Lee is working on a new data-sharing standard called Solid that could help deliver on the initial vision, and a company, Inrupt , to help commercialize this vision. He cautions that this new Web 3.0 vision for giving back control of our data differs wildly from current Web3 efforts built on less efficient blockchains.
Core features of Solid include support for the following: Global single sign-on.
Global access control.
Universal API centered around people instead of apps.
VentureBeat recently talked to Berners-Lee to learn more about his initial idea for the web, recent progress and vision for the future.
In the beginning, it was the read-write web Berners-Lee said he knew that the web was going to be significant from the beginning. “I wanted it to be a read-write web immediately,” he said. “I wanted to be able to collaborate with it and do GitHub-like things for my software team at CERN in 1990.” At the time, there were about 13 theoretical physicists at CERN, while the rest of the team were engineers. Berners-Lee looked for ways to make it easier for teams to work together from different offices.“They had to communicate using the internet, which was only becoming politically correct to use in projects,” he said.
The first browser-editor was built on a powerful NeXT Workstation. People could make links and add information to websites. The information could flow across the team to create a new equilibrium as knowledge was added, corrected or extended.
“Everybody in the team is in an equilibrium knowledge-wise, where this bit of web represents all of the work they have done,” he said.
Sidelined by Web 1.0 But this initial vision was sidelined by the massive popularity of less-capable browsers that could run on PCs and Macs, such as Mozilla, Netscape and Microsoft Internet Explorer.
“We did not actually get that [vision] because it took off as a publishing medium,” Berners-Lee said.
They also ran into other challenges in extending the work at CERN more broadly. While some of the collaborative capabilities worked in a tightly controlled environment like CERN, more work was required on single sign-on, authorization and fine-grained data-sharing to scale these ideas.
Berners-Lee was also disappointed at the content-generation tools used to create websites. His first read-write browser took a WYSIWYG (what you see is what you get) approach, whereas other HTML editors designed for publishing required a complex process of nesting labels more akin to programming than editing a collaborative document.
“It was amazing to find that people would write HTML files by hand,” he said. “I was not prepared to do that. I wanted to highlight something, make a link and save it back. I assumed that by 1989 this would be easy since we had Microsoft Word already doing this.” Laying the foundation Berners-Lee continued this research over the intervening years in the UK and later at MIT. He also incorporated these improvements into the Solid standard and helped found Inrupt to scale the adoption of the new infrastructure.
Berners-Lee has been using Solid to capture data from all aspects of his life in an editable and shareable way. He stores his bank statements, documents, photos, music, IoT data and exercise data on a Solid storage service on his Mac Mini. He’s most excited about how it could improve collaboration between individuals, the businesses they trust and governments — safely and securely.
Solid already supports government services, privacy-preserving medical research and new home improvement services that combine product manuals and energy management. This is just the beginning. Eventually, he believes Solid could have as profound, if not a more significant, impact as the first version of the web.
“We should have called the first one Web 0.3, and then we would be in a good place now,” he said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"You can now use your Slack account to sign into other apps, starting with Quip | VentureBeat"
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"https://venturebeat.com/mobile/you-can-now-use-your-slack-account-to-sign-into-other-apps-starting-with-quip"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages You can now use your Slack account to sign into other apps, starting with Quip Share on Facebook Share on X Share on LinkedIn Slack pillows on display during a company event.
Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
Slack is making it easier to sync up with all the third-party applications that are tied in with the productivity messaging service. The company announced the release of a “Sign in with Slack” button that performs the same function as Facebook Login or Twitter OAuth. The first partner is Quip , and the integration furthers the goal of having “happier, more productive teams.” With this new platform button, Slack is hoping to advance its goal of becoming the de facto platform for managing activity inside a company by making its service the hub for all communication. The feature uses OAuth 2.0 and includes new settings that developers can modify to control what information is needed to sign into third-party apps. Beyond Quip, only five other services have integrated the “Sign in with Slack” button so far: Figma, Kifi, OfficeVibe, Slackline, and Smooz.
This isn’t the first button Slack has deployed, as it has an “ Add to Slack ” feature that imports content directly into channels.
Launching the “Sign in to Slack” button, with its increased scope, is very much in line with Slack’s developer roadmap , which it has published for everyone to see on a Trello board and is aimed at strengthening Slack’s developer community.
“The Slack integration is special,” Quip CEO Bret Taylor declared. “We’re targeting a similar demographic: The team. There aren’t that many products with that focus. Google Apps is on the email domain while Evernote is focused on the individual. Slack and Quip are spiritually aligned.” Above: Create Quip Doc in Slack Just as with any Slack tie-in, administrators will need to enable Quip before individual employees can leverage this relationship. A document can be shared or referenced simply by using the /quip command line, or you can paste the link to the document right into Slack.
Since Quip’s workflow facilitates collaboration, any discussions that take place around the contents of the document — such as edits or questions — will appear in Slack channels. However, it’s entirely up to you to determine how tightly integrated you’d like the channels to be. And although Quip has some features that are redundant with Slack, such as its chat rooms feature , Taylor explained that when integrated with Slack, those capabilities are “suppressed.” While Quip’s chat room feature did initially draw comparisons to Slack, with this direct integration, Quip is making documents and spreadsheets created in its app more accessible, no matter how people are working.
Above: Using the /quip slash command in Slack “Slack is the most popular team chat software and we want documents to work really well with it,” Taylor said. And although he thinks of Quip and Slack as complementary, rather than competitive, he acknowledged that in the long-term, the two products may eventually compete in some areas.
The inclusion of a word processing service could be a welcome one for Slack, however, especially as it improves project collaboration. But the partnership between these two cloud-based services is also interesting because it’s a relationship between companies that have focused on the team, something Taylor called the “atomic unit of productivity.” Above: Quip Doc change updates in Slack This integration also represents how the modern workplace is changing, moving away from email as the foundation of working together. “Unlike restrictive legacy platforms, we’re purposefully open, conversation, and malleable,” the company wrote in a blog post. “Our platforms free up teams to do their best work without any of the pain.” Taylor shared that although Slack is the first integration, it won’t be the last. “We are thinking broadly about partnerships and integrations around expanding the utility and market for the product,” he said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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2,348 | 2,017 |
"Google launches Hangouts Chat, its Slack competitor | VentureBeat"
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"https://venturebeat.com/mobile/google-launches-its-slack-competitor-hangouts-chat"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Google launches Hangouts Chat, its Slack competitor Share on Facebook Share on X Share on LinkedIn Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
Google is getting back into the team collaboration space to take on Slack, Microsoft Teams, Workplace by Facebook, and Cisco Spark with a new service called Hangouts Chat. Available in a private beta, it blends private rooms for conversations and integrations not only with G Suite, but also third-party services. Hangouts Chat is a free service that comes as part of your G Suite subscription and is intended to help Google better appeal up-market at the enterprise.
Initially, there are 11 available integrations: Prosperworks, Box, Zendesk, Asana, Polly.ai, Freshdesk, Zapier, Zenefits, Xero, Smartsheets, and Intuit.
Using Google Hangouts is often about videoconferencing, but it’s also about collaboration in many different forms. Over the past few years, the company has evolved its strategy to one centered around team productivity and chat. “[It took] a lot of figuring out what the right thing to do for enterprise users was,” remarked Scott Johnston, director of product management for Google Drive. “There’s a critical component of bringing teams together, but you have got to make the right decisions that both make them more productive, but also let them have their lives and let them jump into face-to-face meetings when they need to elevate it from a chat.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! While we may use Hangouts as a place to converse, Google is following a route similar to Slack and establishing a platform to not only be a place to hold discussions, but to quickly jump into video calling when needed. Some of the available features include generating a simple, shareable web address that anyone can join without needing to download an app or plugin; providing a unique dial-in phone number for conference calls; supporting larger meeting sizes; having search that parses through all messages and rooms while filtering by individual or file type; featuring custom workflows; integrating with G Suite; and implementing data-loss prevention with administrative controls made for the enterprise.
Above: @Meet bot for Google Hangouts Chat Google has also produced a bot called @meet designed to schedule meetings on your behalf, perhaps similar to X.ai or what LinkedIn recently launched.
Having this automated program is worthwhile because it’ll be able to look at all internal calendars within a business’ G Suite account to find the ideal time for meetings and events, saving hours of needless back-and-forth to accommodate everyone. The @meet bot will be available for customers that sign up for the early adopter program version of G Suite.
This is just the first bot supported on Hangouts Chat. Google told VentureBeat that developers will be able to add their own once the service becomes generally available to the public.
Google Assistant isn’t currently available within this offering. When asked why, the company replied: “It’s a good question. Let’s say we’re thinking really hard about it.” What’s interesting is that Google is thinking about bots and automated programs right from the beginning instead of waiting. Whether developers flock to the platform or not remains a question, but being able to create a bot around the G Suite could be very appealing.
Google’s G Suite enterprise version launched in January and included all the usual refineries, including Gmail, Google Calendar, Google Docs/Sheets/Slides/Drive, Google Sites, Google Forms, and more — basically, all the core services any large business would need to operate. But one thing seemed to be missing, and that was a strong collaboration product a la Slack, Microsoft Teams, and others. The introduction of Hangouts Chat is intended to solve that problem by providing a full stack of resources for any company.
Hangouts Chat is a way to try to steer customers away from third-party services, since it’s an area where Google has been lacking until now. But this isn’t the first time the company has tried its hand at collaboration; it did have Google Wave in 2009 and its group sharing app Spaces , which will officially shut down on April 17 , likely to make room for Hangouts Chat.
While Slack currently may have the upper hand in terms of integrations, Google could have the leverage in selling to the enterprise, an area Slack only recently officially targeted with its enterprise grid offering.
But there doesn’t appear to be animosity between the two companies since Google does include a Drive integration with Slack.
Google’s initial support of bots along with video conferencing could also give it a stronger hand against other players including Facebook, Microsoft, and Cisco.
A Google spokesperson told us that the main value proposition of this new product centers around its “tight integration with G Suite and the introduction of the Hangouts platform, which allows for intelligence to be built in via bots and as well as third-party applications from other enterprise tools. Additionally, Hangouts Chat evolves the Hangouts experience in a way that can scale to enterprise-sized organizations. Rooms and Conversations make it possible for teams to work on entire projects in a productive way that keeps work moving forward, especially when teams can’t meet face-to-face.” While Hangouts Chat will be initially available to current G Suite customers eligible for participation, once it becomes publicly available, anyone with a Google Account will be able to use it similar to how they use Hangouts today.
A blog post has more detail.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Cevat Yerli created Room to blend video conferencing with 3D-animated scenes | VentureBeat"
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"https://venturebeat.com/games/cevat-yerli-created-room-for-3d-animated-video-conferencing"
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"Game Development View All Programming OS and Hosting Platforms Metaverse View All Virtual Environments and Technologies VR Headsets and Gadgets Virtual Reality Games Gaming Hardware View All Chipsets & Processing Units Headsets & Controllers Gaming PCs and Displays Consoles Gaming Business View All Game Publishing Game Monetization Mergers and Acquisitions Games Releases and Special Events Gaming Workplace Latest Games & Reviews View All PC/Console Games Mobile Games Gaming Events Game Culture Cevat Yerli created Room to blend video conferencing with 3D-animated scenes Share on Facebook Share on X Share on LinkedIn Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
Room is rolling out today as the latest collaboration tool combining video conferencing cameras with 3D-animated backgrounds. The social 3D communications engine was created by a team led by former Crytek game developer Cevat Yerli, who was behind the Far Cry, Crysis and Warface series of video games.
The rollout of Room (spelled ROOM by the company) is designed with the new reality of working in mind to make remote teamwork easier. The browser-based, one-click tool has been in open beta for creators, and a general rollout starting now.
Yerli is the latest game developer to try his hand at metaverse-like conferencing solutions. Last week, former VR game devs Alex Schwartz and Cy Wise of Absurd:joy launched their beta version of the collaboration tool Tangle. They were partly inspired by the success of game devs who created Slack and Discord. Both of those companies started out making games, but they both pivoted to make communications tools that have become extremely popular.
Room uses video capture from your webcam to take your live capture and place you in a 3D-animated scene. Your video is literally an overlay in a coffee shop or an auditorium or a theater. But what you’re seeing of the characters is live video.
Event GamesBeat at the Game Awards We invite you to join us in LA for GamesBeat at the Game Awards event this December 7. Reserve your spot now as space is limited! The tool combines video capture from your webcam to take video of your face and upper body. Then it places you in a 3D-animated scene. It’s actually video of you, cut out and pasted into an animated background. The trick is making the blending appear to be seamless.
I asked for more explanation on how it works, and the company said, “Room has purposefully arranged the camera setting in a way that when sitting at the table and looking around, people are placed with a specific fob on the camera path (which Room calls ‘table view’) so that people naturally integrate with the 3D background and the 2D effect is not visible. You do not have to sit at the table to be captured. You can freely move around. However, Room can only show of people what their camera video is providing in real time. The team is working on solutions for people who are walking around to be shown integrated into the 3D environment as well. This will be part of a future release and is still in R&D stage.” The opportunity is to produce something that is more joyful for employees to use in the metaverse age than the standard Zoom, Google Meet, Discord or Microsoft Teams. Meta is among the companies using solutions such as VR to take conferencing into the metaverse.
Yerli’s company isn’t pushing Room as a metaverse tool to be used to build virtual worlds. Rather, it is a communications tool that can support the metaverse strategies of other companies. It uses your camera to capture your reactions and converts them into expressions that your avatar can make. It does not require browser extensions.
Yerli will be in New York attending the Clinton Global Initiative and the Future Investment Initiative , where he’ll be debuting the product.
Luxembourg-based Room wants to make it easy to create lifelike or fantastical online meeting spaces using its proprietary social 3D communications engine, RealityOS. It replaces video camera calls with blended video and 3D animations that use lightweight data transfer so the communication happens at 60 frames per second, Yerli said in an interview with GamesBeat. That makes interaction more natural.
As tech giants grapple with arrangements to return to the office, retaining company culture is at an impasse. About 51% of senior leaders are worried that flexible work arrangements will make it difficult to maintain their organizations’ current culture, and the adoption of technology that supports and complements existing company cultures will be critical for future success, according to Mercer.
Research by INSEAD Knowledge found that a further 45% of workers said camaraderie and teamwork had declined since the start of the pandemic. Technology that bridges distance and creates a space for more uplifting and meaningful communication can result in better workdays and outcomes.
As part of the TMRW Foundation, founded by Yerli, Room uses real-time 3D, depth-of-field and real-time reflections that simulate a natural, first-person point of view where participants can freely move around the room and look at each other — just as they would in real life. The technology allows people to represent themselves realistically in 3D spaces and provides users with an experience that closely mirrors human nature, he said. Within the industry, Room features the highest level of social presence, Yerli said.
I tried out a demo of Room and it was pretty snappy. I didn’t see interaction delays like I normally do in video calls. When you look at the people in the room straight on, they look pretty realistic even though they are 3D animated. If you move to the side, you can see the characters are like cardboard cutouts. It would be more realistic if they were fully 3D animated, but this is how Room gets its speed.
Origins Yerli started thinking about the tech after his twins were born in 2011. For this application, the technology that Crytek created for 3D-animated games would not work. Most of the work has been done in the last three years.
“It requires a completely different architecture and a completely different approach,” he said. “It was all about how I would see the world through the eyes of my children when they grew up. It was about what that next internet would look like. Other people reference the metaverse. For me, it was about information first, then people, social media, and life. I saw it as an internet of life.” The idea is to share your life and the moments of life.
“The context defines what kind of transaction you do. If it’s a classroom, there is a learning transaction. If it’s shopping, there is a shopping transaction. For that smallest unit of life, contextual moments are shared. I was wondering how I could do this over the internet.” In contrast to his career in games, Yerli is pushing a mass market technology with Room, not a high-end 3D graphics solution for a limited number of users.
“With Crytek, I was trying to push the envelope of graphics with Nvidia, AMD and Intel. Now we are pushing the boundaries of what you can do within one click away within a few seconds,” Yerli said. “We want you to enter a space and create lifelong experiences. My vision is to upgrade 2D to 3D first before going to VR.” This approach also uses less processing power and so it’s better for the planet, said Stefanie Palomino, chief product officer of Room. Yerli said he thinks this lightweight approach will work better than selling a new generation of VR hardware to people. Yerli favors a 3D standard dubbed glTF right now.
Right now, about 16 people can participate in a Room meeting. The company is trying to push that upward over time.
“My whole life I have been pushing the high end. One thing I have learned is it is the masses that win the battle. We are always upholding that bar that it has to run on four billion devices,” Yerli said. “If I wanted to run on 20 million devices, then I would run on native apps and have complex avatars. That was my previous way of pushing tech for a limited audience. We want to make sure that we empower as many people as possible to connect from as many locations as possible.” Key features Room uses an immersive first-person perspective. It has real-time and AI-supported video presence in 3D, giving users physical depth and dimension. Participants are shown in the same shared space, giving them a realistic sense of presence and togetherness without the need for additional VR equipment.
It also features designer rooms that give shared context to meetings. Users have a wide range of Room options, including a hip New York coworking space, a cozy campfire in the woods, a Mediterranean beachfront, a Hollywood-style talk show set, an ethereal cloud room, and more. Each space has been with the help of interior decorators Claire Davies and Marcin Lubecki.
Room runs on RealityOS, a patent-protected social 3D communications platform. It is built with a new, browser-first 3D game engine core. The aim is to reduce video call fatigue and let users interact with objects and their peers in a natural and learned way.
It also has privacy protection, as users enter Room with the visual surroundings of their homes in the background automatically removed. All meetings are end-to-end encrypted. It is browser-ready and device-agnostic so users can access the platform by clicking a link within a web browser on any computer with a microphone and camera. No additional software downloads or VR headsets are required.
“We believe that digital spaces should be shaped by real life and with the presence of actual people, not anonymous avatars,” said Yerli. “Human nature is programmed to interact with others in a certain way. We close and deepen relationships face-to-face in shared spaces most of the time.” He added, “When we meet online, we should do it in one room and with our actual selves. We know how to bring people together in digital spaces. We think that the concept of Room will profoundly change the way people get together in the next phase of the internet. Not as a replacement for real life — but as the second-best option. We call it the Internet of Life.” Palomino said that creating the right culture and values remains important in the age of remote work.
“It is clear from the research that while remote working offers huge emotional and financial benefits to both organizations and individuals, without the right technology in place, there remains a significant risk to our culture of togetherness,” Palomino said. “Due to the recent and rapid virtualization of corporate interactions, we have pushed ourselves into these two-dimensional, flat spaces. Room has been designed to encourage people to interact in uplifting virtual 3D meetings, and ultimately support and enhance unique cultural norms.” The Founders Plan features access to all rooms including the exclusive Founder Room, lifetime founder status and price, early access to upcoming features, unlimited meeting time and more.
I wrote one of the first stories ever on Yerli and his brothers as they launched Far Cry. Yerli served as CEO of Crytek from 1999 to 2018. While the company thrived on creating memorable games with high-end 3D graphics — Far Cry, Crysis, Warface, and more — it had trouble keeping up with the financial requirements and development demands of modern gaming.
He founded the TMRW Foundation in 2017 with the mission to create, acquire, and propel ideas, digital technology, and applications of the next iteration of the internet that have a positive impact on society and the way we define presence, interact as people, and generate profits. It has a portfolio of 3D simulations, VR, AR, and AI-powered products. The largely self-funded company started in 2017 and it has about 100 people. It is unrelated to Crytek.
Palomino was the cofounder of Red Lab, a boutique consultancy started in 2015 to support clients in interactive, smart digital events and communications.
The memory palace Each Room is set up like a memory palace, a visualization technique that goes back to the ancient Romans and Greeks.
With it, you create 3D spaces around the cool moments that happen in life. The 2020 video game Twin Mirror used this technique to solve mysteries.
Yerli believes the memory palace approach of Room is unique among the plentiful competition.
“The technology for avatars is pretty far away from being real, inclusive, accessible, and scalable,” he said. “So we came up with a technique based on AI inferencing. We can provide a presence or social presence quality that is unseen before.” Yerli thinks this technique is more humanizing while enabling it to run in a browser that is only a click away.
“For me, the vision of the next internet is not so much about VR, it’s not so much about avatars, because often VR has a threshold, a technical barrier. And gamers don’t approve yet. The barrier is there, and the scale is not there. Our philosophy has been how can we build a foundation that can be operated by or clicked on and entered by four billion people. It has to be running on every browser, on any device. It has to be the most inclusive, the lowest lightweight engine.” Accessibility doesn’t mean it has to sacrifice quality, as Room adds reflection shadows and AI inferencing to make it more realistic.
“What we’re trying to do is humanize technology,” Yerli said.
GamesBeat's creed when covering the game industry is "where passion meets business." What does this mean? We want to tell you how the news matters to you -- not just as a decision-maker at a game studio, but also as a fan of games. Whether you read our articles, listen to our podcasts, or watch our videos, GamesBeat will help you learn about the industry and enjoy engaging with it.
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"Google Cloud pushes a strategy for broad openness | VentureBeat"
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"https://venturebeat.com/data-infrastructure/google-cloud-pushes-a-strategy-for-broad-openness"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Google Cloud pushes a strategy for broad openness Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
How will Google Cloud compete in the future? If the announcements from this year’s Google Cloud Next conference are an indication, the word “open” will be a big part of its strategy. The company wants to open up its tools so that partners and other companies can integrate their software with the Google Cloud platform.
Google also wants to open up its cloud at multiple different levels for both the users and the backends. The synergy, it hopes, will nurture more applications with better features that grow from a combination of Google’s prowess in building big platforms and its partners’ big ideas.
The Next conference is one of Google’s main events for its cloud customers. This year’s event includes a mixture of programs that help customers learn best practices for using the cloud machines while swapping advice with Google engineers and other customers. The conference this year is being held online with a few in-person events as the company experiments with returning to the norms from before the pandemic.
[ Follow VentureBeat’s ongoing Google Cloud Next 2022 coverage » ] VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Google also uses the conference to announce new products and ventures. This year, many of these revolve around ways the company is opening their platform to others and encouraging open practices at all levels. The data storage layer, the infrastructure layer and the application layer called Workspace are all announcing various new features and products that open up the cloud to users, partners and even competitors.
A new, more open Google Cloud platform “Virtually any company runs across multiple clouds and premises,” explained Gerrit Kazmaier, general manager of data analytics and Looker, two products of Google Cloud. ” Big data means data which is spread out on the Google Cloud platform, the other clouds and on-premises systems. The answer is not to have a single-point solution that you can independently deploy everywhere, The answer is that you need to develop a data architecture which actually connects all of that together.” Toward that end, Google is opening up some of the data storage layer to encourage others, including nominal competitors, to create deeper connections. Instead of just storing information through an API at arms length, Google would like users and partners to integrate their software to work seamlessly with its infrastructure.
Some of the announcements at Next suggest that Google’s new plan is to open up their cloud more and make it easier for others to add their own features on top of Google’s data storage foundation. The company is announcing new relationships both with smaller boutique firms that build applications on top of the cloud, as well as others that might be considered competitors.
Building industry data networks with Google’s BigQuery “Every business conversation I have in my role in the executive briefings revolves around asking how do we build industry data networks ? How can I connect my data with someone else’s data?” explained Kazmaier.
At the core of many of these announcements is the BigQuery database, a service that offers a highly scalable way to store large amounts of data. While it began as a simple storage option with a SQL-based interface, it’s grown over the years as Google integrated features for artificial intelligence (AI) and business reporting. Developers can now store data in one place and generate reports or train machine learning models with just a few extra commands.
Several hundred smaller firms, for instance, offer more specialized services that rely upon BigQuery or some other Google infrastructure for storage and support. Companies like Netpremacy , Pythian , Pluto 7 , and Cloud Ace are just some of the firms that fit into this niche. They effectively resell Google Cloud to their customers while adding value by adding features like better analytics or deeper understanding of AI.
The openness goes further. Google is announcing partnerships with companies like Elastic , Adobe and MongoDB.
While these might be considered competitors for some of Google’s databases, they will now be effectively using Google’s backend for some of their services. Developers may be writing data to an API that looks like an Elastic or MongoDB API, but it will eventually be stored in BigQuery.
The result could deliver the best of both worlds. The developers can continue to use the APIs for what they like best about Mongo or Elastic, but they’ll also get all of the features that are built into Google’s BigQuery.
In MongoDB’s case, BigQuery will be connecting with Atlas, a service it calls a “multicloud developer data platform” that includes both storage and data analysis. The tool gathers information from multiple sources and then helps analysis with a unified query engine.
“This is a big win for developers and very in line with MongoDB’s values,” explained Sahir Azam, the chief product officer at MongoDB. “Customers fear vendor lock-in because it removes flexibility. If they are fully locked in with one vendor, that provider can choose to increase prices and customers just have to deal with it because it’s even more costly to move their data to a different cloud.” Other improvements to Google’s office apps Some of the other announcements describe how Google is bringing the same kind of openness to other products. A collection of new APIs and SDKs for Google Workspace will enhance collaborative workflows. Google says it wants to make Workspace, its collection of office products, “the most open and extensible platform” for office work.
Google’s announcements detail numerous ways that it’s extending its various applications — and sometimes blurring the boundaries — all to make what it says will be a more immersive experience.
For instance, the Google Meet platform’s API will open up options for other software platforms, both outside and inside the space of the meetings. Other applications will be able to start up meetings. Some will even operate inside.
For example, Google says that users will soon be able to view and collaborate on Figma whiteboards and jam sessions, all within the meeting space. Several other companies like AODocs, Atlassian, Asana, Miro and Tableau are said to be planning to take advantage of these new options.
Google’s collection of announcements also includes a number of new options for hardware and data centers. It’s moving forward with plans for adding new data regions for Austria, Greece, Norway, South Africa and Sweden.
New, faster cloud machines The company is also rolling out a new cloud machine, the C3, built around a version of Intel’s Xeon processor that’s been enhanced with a custom ASIC. Developers can write custom logic for the chips that can dramatically improve some common operations. In the most extreme cases, the speed up from what they’re referring to as a “ Infrastructure Processing Unit ” or IPU could be multiple times faster but others may see more modest gains.
“Based on the initial performance data, running weather research and forecasting (WRF) on C3 clusters can deliver as much as 10x quicker time to results for about the same computational cost,” explained Michael Wilde, CEO, Parallel Works , a company that specializes in the kind of big parallel computational jobs that will benefit the most from the new option.
There is one exception to the theme of openness. Google is also announcing several new security initiatives and software options that they say will close the door even tighter against unauthorized intrusions. For instance, their cloud will enable users from different teams, organizations or businesses to set up shared spaces for data analysis. These options, called Confidential Spaces, extend their push to improve confidential collaboration.
The Google Cloud Next conference will run from October 11th to October 13th.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Dreamforce 2022: Salesforce aims to make sustainability accessible with Net Zero Marketplace | VentureBeat"
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"https://venturebeat.com/data-infrastructure/dreamforce-2022-salesforce-aims-to-make-sustainability-accessible-with-net-zero-marketplace"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Dreamforce 2022: Salesforce aims to make sustainability accessible with Net Zero Marketplace Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
At Dreamforce 2022, CRM platform provider Salesforce unveiled two new products focusing on carbon credit market transparency and productive services for teams to get more value from their digital HQ.
Dreamforce, which runs at the Moscone Center in San Francisco through Wednesday, is Salesforce’s annual event, which began in 2003.
Salesforce announced the Net Zero Marketplace, a platform that’s designed to enable simple and transparent carbon credit purchases, allowing organizations to accelerate climate-positive impact at scale, and three Slack tools designed to enhance productivity. enhancing productivity.
Net Zero Marketplace: A carbon credit platform Salesforce’s Net Zero Marketplace aims to connect buyers with ecopreneurs — environmentally focused entrepreneurs — in a trustworthy and transparent carbon credit platform to scale climate-positive impact.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! According to a report by McKinsey , the global voluntary carbon market is estimated to grow to $50B by 2030 as many organizations race to achieve their net-zero commitments. However, organizations may not always know where to begin or how to develop a carbon credit portfolio.
Furthermore, the process of obtaining carbon credits can be complicated, and buyers want to be confident that the carbon credit projects will have a positive impact. Salesforce intends to address such concerns through its Net Zero marketplace.
Built on Salesforce’s commerce cloud and powered by the company’s new real-time CRM Genie, the platform offers a catalog of third-party rated carbon credits. The Net Zero Marketplace also features a climate action hub where businesses or individuals can learn about the latest climate issues and connect with other ecopreneurs.
According to new Salesforce research on the sustainability talent gap , 8 in 10 global workers want to help their company operate sustainably, with 3 in 5 eager to incorporate sustainability into their current role.
Patrick Flynn , SVP, global head of sustainability at Salesforce, told VentureBeat that Salesforce recently added sustainability as its fifth core value and has been actively using carbon credits as a part of their own climate strategy for five-plus years.
“One must start with emission reduction plans that consider not only your own operations but also the entire value chain consequences, including initiatives to catalyze systemic emission reduction effects beyond your value chain,” said Flynn. “Empowering such efforts was one of our main reasons for creating the Net Zero Marketplace, which also greatly complements our Net Zero cloud.” Flynn said that the Net Zero Marketplace will enable individuals and organizations to collaborate on building better carbon credit portfolios and using carbon credits as a part of their overall climate action strategy.
The Net Zero Marketplace also eliminates the time-consuming process of finding and verifying a carbon credit’s quality by aggregating and publishing third-party ratings for projects not locked behind paywalls or account registrations. This level of transparency helps organizations determine which carbon credits are best for them.
“The unique part in this experience is that when anyone comes and learns about a project and learns about an ecopreneur, they will also be able to see a transparent pricing and third-party ratings, a key differentiator in our offering,” Nina Schoen , director of product management, Net Zero Cloud Salesforce told VentureBeat.
For organizations currently using Net Zero Cloud , Salesforce’s carbon accounting solution, the credits can be integrated into the platform and tracked against their current emissions. Buyers will also get updates on project progress, which encourages reinvestment.
New Slack innovations to enhance team productivity Salesforce also announced new Slack features at Dreamforce to make it more productive for teams to work together in their digital HQ, allowing them to pull in actionable data directly from Salesforce Customer 360.
Slack Canvas, which will be available next year, is a new tool that will enable teams to select, organize, and share critical resources. When combined with the new Slack platform and Customer 360, teams can integrate data from record systems into the canvas and automate business-critical workflows.
Building on its audio-first experience, Slack huddles will now offer teams lightweight video conferencing, multi-person screen sharing, message threads, and more to power live coworking sessions.
“The nature of work is changing, and most organizations today use Slack as a digital HQ for synchronous communication with their team,” said Tamar Yehoshua , chief product officer at Slack.
At Dreamforce, Yehoshua said that the new Slack tools will help organizations increase team productivity and get the most value from their tech stacks by connecting conversations, automation, and apps in one space.
With the Marketing Cloud for Slack integrations, teams can set up, execute and measure their campaigns directly in Slack. Powered by Marketing Cloud Account Engagement, marketing and sales teams can leverage real-time alerts and align within Slack channels to prioritize lead follow-up, analyze pipeline impact and iterate on campaigns instantly.
Once a campaign is live, teams can include in-flight campaign performance data using Marketing Cloud’s Intelligence Insights for Slack integration in the channel and canvas. This feature aims to provide marketers a custom view of the campaign’s performance data in one place for teams to monitor trends, align on strategy and shift investments.
The new Slack platform and huddle features will start rolling out today and will be generally available to all users in the coming weeks.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Slack launches private shared channels for more discreet conversations between businesses | VentureBeat"
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"https://venturebeat.com/business/slack-launches-private-shared-channels-for-more-discreet-conversations-between-businesses"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Slack launches private shared channels for more discreet conversations between businesses Share on Facebook Share on X Share on LinkedIn Slack logo cast on the wall of a building ahead of the company's launch event around its platform on December 15, 2015.
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Slack calls its channels for group chat and project management the workplace of the future, and today announced that channels shared between two companies can now be set to private. Even team administrators won’t be able to see files and conversations shared in private shared channels between specific employees or team members. Before today, shared channels were also visible to other team members.
Private shared channels may come in handy for limited company partnerships, or instances when a company works with consultants or external service providers. Private channels within a team or company were available before today to limit participation to specific people.
About one in three paying Slack customers have opted into the shared channels beta, a company spokesperson told VentureBeat in an interview. Slack first made the shared channels beta available last fall at Frontiers, its first developer conference.
Both teams in a private shared channel will be able to choose if they want the channel visible to their side’s other team members, product manager Sean Rose told VentureBeat in a phone interview.
“Each side controls the privacy levels so it could be public or private on either side without the other side necessarily dictating that we do that because the requirements from each side may be different,” he said. “Each team is going retain a copy of the data no matter what so they ultimately control the visibility of that even if they stop actively working together.” Private shared channels is one in a set of new features being rolled out today by the enterprise chat app. Also announced today is the ability for admins at companies using Enterprise Grid to deploy read-only channels — channels users are required to join so they can see messages sent by executives or certain team members, but lock them out from sending any messages in response.
Slack launched Enterprise Grid one year ago with features designed to give companies with tens of thousands of employees the ability to use Slack companywide. Enterprise Grid was launched to compete with Workplace by Facebook , Microsoft Teams , and other team collaboration offerings. Slack declined to share the current number of Enterprise Grid customers.
Also today, Slack team administrators have a new place to manage shared channels. Admins who are not a member of a private shared channel will be unable to view the channel name or the conversations that take place, but they may be able to stop sharing between teams.
The capacity to require every member of a Slack team to see certain messages has always been available with the #general channel, the one channel included in every Slack team, but the move today extends that ability to any channel for Enterprise Grid customers.
With each of the new features added today, Rose said, “the key idea is that we’re trying to take what we built with channels and meet our customers with the different use cases we’re seeing with them, because we believe this is the way people are going to be working in the future.” These expansions to shared channels comes ahead of other features likely on the way, such as shared channels for collaboration between Enterprise Grid customers and the ability for shared channels to include more than two teams.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Microsoft Teams opens conversations to outsiders with new guest access feature | VentureBeat"
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"https://venturebeat.com/business/microsoft-teams-opens-conversations-to-outsiders-with-new-guest-access-feature"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Microsoft Teams opens conversations to outsiders with new guest access feature Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Microsoft today announced that it’s rolling out guest access for Teams so companies using the collaboration software can now invite guests from outside their companies to join their conversations. Teams, which requires an Office 365 account and debuted last November to compete with Slack, HipChat, and other enterprise chat apps, is now used by more than 125,000 organizations.
Teams can now be found in 181 markets and is available in 25 languages.
Also announced today: Developers can now use Botkit to make bots for Microsoft Teams, and Teams now has integrations with GitHub and Atlassian software like Jira.
Guests in Teams can join video chat meetings or access the same bots, interactive tabs, and private chat conversations as any other Teams user.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “At its high level, collaboration doesn’t mean much until you can bring together all of the various people with the same richness and seamlessness you’ve come to expect from your toolset,” Microsoft Teams program manager Larry Waldman told VentureBeat in an interview at Microsoft offices in San Francisco. “A team is only as good as all the parts coming together, and guest access makes it more seamless to bringing all those parts together into one ecosystem in a natural way.” In giving Teams users the ability to grant guest access, Microsoft joins its biggest competitors, including Slack , HipChat , and Workplace by Facebook, who earlier this year made it possible for businesses to create groups for multiple companies.
“I think for sure you’ll see more in our roadmap of allowing companies to work together. This is our starting place for it,” Waldman said.
Guest access to Microsoft Teams can only be granted by administrators, who have the choice to limit guest access based on specific channels or even time of day.
To become a guest, users must initially have Azure Active Directory and Microsoft accounts. Later, Microsoft will make it possible to grant guest access to anyone with a Microsoft account.
“Take a big company of 10,000. You’re going to have organic creation of teams in most cases. It’s not usually locked down, but you do want central control over who is participating in these things. So by leveraging the overall Microsoft identity stack, not just can team admins see where the guests are participating, but central IT can also monitor,” Waldman said.
A “Guest” label will appear under each guest user’s name, and each channel with a guest will be labeled as well.
Among the 150,000 groups using Teams, an undisclosed number are in the education space.
Collaboration tools designed especially for classrooms were made available in May.
“So if I’m a school administrator, I can create a classroom team, I can create a professional learning environment team, there’s a few different types of teams that I can create, and those are essentially provisioned with a set of resources already at their fingertips,” Waldman said.
Since the launch of Teams last November, the chat app has added features like third-party cloud access, as well as third-party bots, like Polly and Zenefits.
The app became generally available in March. In May, developers gained the ability to publish Teams apps to the Office Store.
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"Slack remodels workplace apps and expands SaaS workflow actions | VentureBeat"
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"https://venturebeat.com/ai/slack-remodels-workplace-apps-and-expands-saas-workflow-actions"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Slack remodels workplace apps and expands SaaS workflow actions Share on Facebook Share on X Share on LinkedIn Slack logo at Slush 2018 conference in Helsinki, Finland Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Slack today introduced a range of upgrades that change how workplace apps function, further stepping away from the traditional bot to offer more advanced workplace apps capable of functioning with buttons and menus, even outside conversations in Slack channels.
App home is designed to act as a home page for apps, where updates can be shared without the need to send messages to a channel. One of the first apps to receive the App home feature is Google Calendar , which shows a stream of your upcoming meetings and lets you join a call, reschedule, or RSVP for an appointment.
Above: App home “It’s so much easier to use now than it was when this was just a stream of messages notifications saying you have a meeting in five minutes,” Slack director of developer relations Bear Douglas told VentureBeat in a phone interview.
There’s also modal windows, which can pop up within Slack to share detailed information for more complex uses cases that require receiving input from users across multiple steps.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! App home and modal windows are designed with Slack’s app design interface Block Kit and are available today. App home is available in open beta and will be generally available for app builders in the coming months.
Above: Slack modal windows Block Kit was made available for developers to quickly build apps in February and first introduced at the first Spec conference last year. Block Kit can make apps that display photos, use drop-down menus, collect data with cards, and utilize things like buttons and lists instead of completing tasks with words alone.
Changes to how Slack apps can function are scheduled to be announced today at Spec, Slack’s second annual developer conference in San Francisco. Slack’s App Directory may only contain 1,800 automated bots, but Slack dev platforms have been used to create 500,000 custom bots to share info or streamline workflows, from bots made to tell coworkers about each other’s birthdays to a bot HSBC uses to help new hires learn company acronyms and jargon.
Today most app interactions are seen in the bottom left in Slack, where you get messages from bots, but App Home will give developers and businesses making custom apps a way to serve up content in tabs and consolidate updates in a single stream.
Finally, to encourage app discovery, the Slack app will soon get a centrally located place to find SaaS integrations and apps, called the app launcher. Available in the coming months, the app launcher will share the most commonly used apps at launch but may expand to personalize recommendations based on the individual user.
Above: App launcher The first things users will see in the app launcher will be apps an administrator approved for an employee to use or apps that are already installed, addressing a pain point for average Slack users.
“They may not even be aware of the apps that are already in their team,” Douglas said.
Slack has a history of being slow to bring app discovery opportunities into the app , but the new App launcher may grow to include Personalized results based on your role within a company or industry.
“You can imagine in the future it might be something aligned to what your role in a company is so if you’re on the finance team here are the 5 apps that people tend to use,” she said.
Also new today: the expansion of Actions.
Actions first launched at Spec last year to make it easy to do things like create an Asana task or Zendesk ticket attached to any message within Slack, but actions are now being expanded to become prominently available and no longer require a connection to messages.
Administrators will be able to assign actions to specific channels, and admin control of default actions based on a person’s role within a company is a possibility in the future, Douglas said.
“Creating a task may come from a conversation you’re having with a colleague or it might come from something that just occurred to you while you’re talking to a colleague that has nothing to do with your conversation, and so we want to create a surface for people to start interacting with apps in that way,” she said.
Above: Actions from Anywhere Actions will also soon become available in the Slack search area so you can search “file an expense” or other tasks employees frequently need to do their jobs.
Actions from Anywhere is available in closed beta today and will be made generally available in the coming months.
In other recent Slack news, a revamped Salesforce app was recently introduced, and last week, Slack launched the Workflow Builder to make it easy to create a workflow or work from a pre-made template to do things like make a help desk request or praise a teammate.
Slack now has 12 million daily active users and 6 million paid users.
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"Pingpad relaunches as a Slack bot to help enterprise teams share knowledge | VentureBeat"
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"https://venturebeat.com/ai/pingpad-relaunches-as-a-slack-bot-to-help-enterprise-teams-share-knowledge"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Pingpad relaunches as a Slack bot to help enterprise teams share knowledge Share on Facebook Share on X Share on LinkedIn Are you looking to showcase your brand in front of the brightest minds of the gaming industry? Consider getting a custom GamesBeat sponsorship.
Learn more.
When Ross Mayfield launched Pingpad in September , the idea was to give people an app that combined collaboration and conversation in one. Focused on social productivity, the app blended real-time messaging with a Wiki-like product. However, in June, the company announced that it was discontinuing its app and would be pivoting toward a new direction, one focused on team collaboration in the enterprise.
Today, Pingpad has relaunched, and this time it has positioned itself within Slack. With the new product, the company wants to enable teams to not only share knowledge with each other but to also make better decisions and take appropriate actions.
The spirit behind the service has remained, but the overall user experience and interface have changed. Mayfield explained that Pingpad will create a real-time wiki or note for every Slack channel, and every time that note is updated, the respective channel will be notified.
Since its private beta program started, the company has discovered four cases in which Pingpad can be useful in this enterprise team setting. The first is as a primary area for teams to communicate — Pingpad will create a channel called #Teamsite, along with a corresponding wiki. This is the dashboard for all of your team’s information — such as contacts, passwords, tools, instructions, and more.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Another, fairly straightforward, use case centers around meeting notes.
Pingpad is also useful as a repository for documentation stored on Slack, so if you happen to have a #design or #QA channel, teams can use Pingpad to store best practices, instructions, brand guidelines, or tutorials that are necessary for teams to function.
Lastly, Mayfield sees this Slack bot as a glossary for team operations. He shared that it can be a place where teammates can find common vocabulary and answers to common questions. Pingpad also supports a Slack command that lets you @reply, along with “X is Y” to establish a definition or answer.
This relaunched service supports “Sign in with Slack” as well as slash commands.
In a Medium post , Mayfield explained why Pingpad opted to focus on Slack, citing the platform’s great APIs and the fact that it is a fast-growing enterprise company with more than 3 million daily active users.
He also noted that Slack’s business model is in alignment with what Mayfield’s team wants to do. He added that Slack doesn’t “want to do a Twitter,” meaning that Slack isn’t interested in rubbing developers the wrong way.
Pingpad’s Slack bot is free to use until you’ve hit 100 notes per team. From there, it’s assumed that you’re engaged and getting a lot of value out of the service. The company offers a premium subscription of $4 per user per month that provides an unlimited number of notes and enterprise-grade support.
There are some limitations as to how you can use Pingpad. You’ll be able to create new notes within Slack, but if you’re looking to edit them, it’ll have to be done on the desktop or mobile web. The company is still working on developing rich mobile apps.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"You can now make an AI clone of yourself — or anyone else, living or dead — with Delphi | VentureBeat"
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"https://venturebeat.com/ai/you-can-now-make-an-ai-clone-of-yourself-or-anyone-else-living-or-dead-with-delphi"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages You can now make an AI clone of yourself — or anyone else, living or dead — with Delphi Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
My favorite episode of the hit sci-fi/horror TV series Black Mirror is “Be Right Back,” which premiered 10 years ago now, and captured the alienating experience of a woman cloning her dead ex-boyfriend by using a service that analyzed his social media posts and texts to recreate his personality.
The episode seemed fantastical but just on the edge of plausible at the time in 2013 — after all, many of us were already leaving extensive digital communications trails with our smartphones and computers back then.
Today, it actually is possible, at least in digital form. A startup Delphi , founded in the US but named after the Ancient Greek fortune teller and dispenser of knowledge, is announcing $2.7M in funding and its new AI digital cloning service.
Simply upload as few as four documents containing your communications to it — and as many as thousands, including emails, chat transcripts, even YouTube videos or audio files such as podcasts or voicemails — and Delphi will create an AI chatbot that mimics, as closely as it can, your personality, manner of writing, or speaking, audibly, as of today, through a partnership with voice-cloning startup ElevenLabs.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! You can then deploy your AI clone on a website, in Slack, or even hook it up to a phone number to answer calls and engage in discussions with callers on your behalf.
Delphi also tries to recreate your unique thought processes in your clone, to the extent that it can provide what it thinks would be your response to a given prompt.
“We hope to be more optimistic than Black Mirror for sure,” said Dara Ladjevardian, founder and CEO of Delphi, in an exclusive interview with VentureBeat. “We hope to see the optimistic side of this technology rather than the fear side.” Some big name investors are optimistic about Delphi’s work: the new funding round was led by Keith Rabois , CEO of OpenStore and general partner at Founders Fund (the famed venture firm founded by controversial VC Peter Thiel, founder of intelligence software company Palantir , backer of the lawsuit that destroyed Gawker , and who made headlines discussing the promise that young blood transplants hold to reverse aging), and joined by Lux Capital, Xfund, MVP Ventures, and SaxeCap. Other angel investors who have backed Delphi include founders of AngelList, EightSleep, and Soylent.
Rabois has already cloned himself, as well, as seen in the screenshot below.
Clone anyone, from famous figures to loved ones Not interested in digitally cloning yourself? Delphi works on other people, too: for now, the company does not restrict a user’s ability to create clones of anyone they’d like, living or dead, without their permission.
Want to clone your ex and resume your relationship, at least the communication part of it? You can do it, provided you grab and upload samples of their writing or speaking.
Want to clone the late Steve Jobs or the still living Elon Musk? Delphi allows you to do this, too, if you extract data from the public internet, such as through interviews in news outlets or YouTube videos. Delphi has even already cloned “Oracle of Omaha” and legendary investor Warren Buffett for its internal use.
“If [Buffett] ever tells me, ‘Dara, take this down,’ I’m going to take it down, I’m going to respect him,” Ladjevardian said.
In fact, Delphi already has already used its AI software to clone a number of famous figures — Steve Jobs ; Jeff Bezos , Robert Oppenheimer ; Estée Lauder; philosophers including Socrates, Lao-Tzu, and Aristotle; all US presidents living and deceased; and others (Delphi’s website shows a collage of photos including magazine magnate Anna Wintour and former Chicago Bulls basketball player Michael Jordan).
While Delphi previously allowed early users access to converse with these clones in a chatbot format during a beta launch of its software, it appears they are no longer publicly available online.
As for others cloning loved ones, exes, or impersonating famous people to deceive or commit crimes, Ladjevardian admitted to VentureBeat: “We have no guardrails against that, so that is something we’re going to have to figure out at scale.” Ladjevardian told VentureBeat that Delphi has already received a takedown request from notable physician and podcast host Peter Attia , and removed the unsanctioned AI clone of him accordingly.
The tech behind Delphi’s AI clones Delphi’s digital cloning software began with second-generation immigrant Ladjevardian’s earnest and heartfelt desire to reconnect with his deceased grandfather, who was an entrepreneur in Iran prior to the 1979 Iranian Revolution that radically changed the government from a secular monarchy into a theocracy.
When OpenAI released its GPT-3 large language model (LLM) in the summer of 2020, Ladjevardian was working as a software engineer at C3 AI , an enterprise-focused AI software application platform company with clients in government, oil, and gas.
“I was like, ‘wow, this is really going to change things,'” Ladjevardian recollected to VentureBeat. “So I should dedicate my life to this, because I think there’s going to be a lot of opportunities here.” Ladjevardian left his job at C3 AI and founded his first company, Friday, an AI-based shopping assistant that offered people product recommendations in a conversational format.
At the time, he was reading a book about his grandfather that he found illuminating, but Ladjevardian desperately wished he could actually converse with the man about his experiences, ask him questions, and lean on him as the mentor he’d never had growing up as a lonely, second-gen Iranian immigrant in Houston, Texas.
Taking GPT-3 and using open-source embeddings — the clusters of information that AI uses to form meanings and associations — “I created a clone of him using his book and kind of treated it as my own personal mentor as I was building out that startup,” Ladjevardian said.
The experiment worked, at least on a personal level: Ladjevardian sold the startup for a profit and moved to Miami to work for Rabois’ OpenStore, where he leaned on Rabois as a mentor and kept developing the idea and tech for digital AI clones that would ultimately lead to him creating Delphi.
Use cases and monetization Using AI to create clones as personal mentors is a nice idea for those looking for that kind of guidance in life, but how can it scale as a business? Ladjevardian and his employees at Delphi are convinced that there is a market for this kind of software, especially for those people who already make a living by imparting their knowledge to others — think coaches, influencers, creators, and business leaders.
“We’re focused on helping coaches, creators, experts, politicians, CEOs — people with high intellectual leverage — scale themselves and make themselves available to others,” Ladjevardian said.
Delphi is not publicly listing its pricing structures yet, as it is still tinkering and iterating with the best way to monetize its software, but Ladjevardian did say that the company is considering collecting monthly subscription payments for hosting people’s digital clones and how much usage they get out of their audience on those clones, such as how many messages the clone will send out. Adding voice capabilities and a dedicated phone would cost extra, in this scheme.
Already, over 100 individuals have created digital clones of themselves in Delphi’s private beta, including the Grammy-Award winning producer, Illmind , who’s clone offers text-based responses and general career and life guidance.
“We’re focused on capturing someone’s mind and relaying that through text and voice,” Ladjevardian explained.
Of course, Ladjevardian has also cloned himself and even had an audio conversation with his clone.
“I called myself and spoke to myself for 10 minutes and it was weirdly therapeutic,” he said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"What you need to know about Sakana AI | VentureBeat"
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"https://venturebeat.com/ai/what-you-need-to-know-about-sakana-ai-the-new-startup-from-a-transformer-paper-co-author"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages What you need to know about Sakana AI, the new startup from a Transformer paper coauthor Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The landscape of generative artificial intelligence (gen AI) is in a rapid state of evolution these days, not only with OpenAI , Meta , and Google competing directly on foundation models, but doing so while some of their biggest in-house talent leaves to launch their own gen AI startups.
Last month saw one of the biggest defections: Llion Jones, one of the co-authors on the seminal 2017 research paper “ Attention Is All You Need ,” which kickstarted the generative AI revolution by developing the architecture of the transformers used in leading large language models (LLMs), announced he’d left Google to found a new startup.
This week, we learned just what he is working on: Sakana AI , a new AI company based out of Tokyo.
Joining him as a co-founder of Sakana is David Ha, previously the head of research at Stability AI and a former Google Brain researcher.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Together at Sakana, they are pursuing a strikingly different model for AI: one of biomimicry, specifically looking to the collective intelligence in systems found in nature such as schools of fish and beehives, to design AI models that are flexible, reactive and economically efficient.
At Sakana AI, Jones’ vision is to capitalize on this technology to craft a trail-blazing generative AI model proficient in generating text, images, code and multimedia content.
So far, Sakana is keeping its backers close to the vest, declining to comment to Reuters on who is investing in the company.
New tech inspired by nature Sakana AI distinguishes itself with a novel approach that involves developing numerous smaller AI models that collaborate, much like a swarm, to deliver complex results.
This methodology challenges the dominant trend of constructing extensive AI systems.
Sakana AI is confident that its swarm-based approach, inspired by collective intelligence, can provide results on par with larger systems while being more economical and flexible.
“Ants move around and dynamically form a bridge by themselves, which might not be the strongest bridge, but they can do it right away and adapt to the environments,” Ha told Bloomberg in an interview.
“I think this sort of adaptation is one of the very powerful concepts that we see in natural algorithms.” The name Sakana was derived from a Japanese word for fish (さかな) meant to elicit “a school of fish coming together and forming a coherent entity from simple rules,” the two founders told The Financial Times.
Sakana AI’s decision to establish its base in Tokyo is a calculated move. With its advanced technical infrastructure and highly educated talent pool, Tokyo is primed to nurture the growth of AI startups and attract international expertise. Sakana plans to exploit these benefits to bolster its research and development activities, although the company has yet to set up office space for its new headquarters.
Will nimble startups be able to out-maneuver AI industry titans? The vision of Sakana AI transcends the creation of AI models, as Ha and Jones underscore the shortcomings of contemporary AI systems that often end up inflexible. Instead, they propose AI models that embody principles of evolutionary computing, inspired by the adaptability of nature. This approach could potentially resolve issues related to cost and security in AI systems.
The cofounders told CNBC they believed Google’s focus on a single type of generative AI technology, large language models, was a mistake “because that’s quite a restrictive framework,” Jones said.
The cofounders said they’ve been in talks about using LLMs, but haven’t made a final determination. However, Ha did not write them off: “I would be surprised if language models were not part of the future,” he told CNBC.
The transition of both Jones and Ha from Google to Sakana AI is a noteworthy development in the AI sector, especially in the realm of generative AI.
“It’s just a side effect of big company-itis,” Jones said in the CNBC interview. “I think the bureaucracy had built to the point where I just felt like I couldn’t get anything done.” Similarly, Ha sees challenges facing the current-gen AI leader, OpenAI. He said he views the use of the research he was part of at Google as less than innovative and expressed concern over the lack of development-sharing with the broader community.
By harnessing the swarm concept and evolutionary computing principles, Sakana AI aims to deliver flexible and cost-effective AI solutions.
With Tokyo shaping up as a nucleus for AI innovation, Sakana AI’s presence in the city will contribute significantly to generative AI’s future evolution, with the AI industry awaiting the transformation this collaboration proposes to usher in.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Meta releases Code Llama, a new LLM geared for programming | VentureBeat"
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"https://venturebeat.com/ai/meta-releases-code-llama-a-new-open-source-llm-geared-for-programming"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Meta releases Code Llama, a new open-source LLM geared for programming Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
True to the rumors and advance reports , Meta Platforms, the company formerly known as Facebook, today unveiled Code Llama , its new generative AI large language model (LLM) designed specifically for programming — and like the more general-purpose LLaMA 2 , it’s open source and licensed for commercial use.
Code Llama is “designed to support software engineers in all sectors — including research, industry, open source projects, NGOs, and businesses,” Meta says in its blog post announcing the models.
The tool immediately becomes a major rival to OpenAI’s Codex (powered by a modified GPT-3) , the Codex-powered Github Copilot from Microsoft , and other coding-specific LLM assistants such as Stack Overflow’s OverflowAI.
In its blog post, Meta explains that Code LlaMA is a “code-specialized” version of LLaMA 2 that can generate code, complete code, create developer notes and documentation, be used for debugging, and more. It supports Python, C++, Java, PHP, Typescript (Javascript), C# and Bash. You can read the full research paper from Meta about its performance here , which describes Code LlaMA as a “family” of LLMs for code.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Building on that analogy, the family includes three main members: a 7-billion, a 13-billion and a 34-billion parameter model, each trained on 500 billion tokens. The smaller models are designed to run on fewer GPUs (the 7-billion model can run on a single one), a beneficial attribute given the rumored scarcity in this critical piece of hardware at the moment , and Meta says both are faster than its 34-billion big model.
All models support up to 100,000 tokens for their prompts. This means “users can provide the model with more context from their codebase to make the generations more relevant,” according to Meta.
The LLaMA extended family also includes two fine-tuned models, one for Python and one for Instruct, the latter of which “has [been] fine-tuned to generate helpful and safe answers in natural language,” and therefore, Meta says, should be used when generating new code from natural language prompts. That is, it returns safer, more expected and perhaps less creative responses.
You can download Code LlaMA directly from Meta here and find the source code on Github here.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Hollywood writers' strike ends with first-ever protections against AI | VentureBeat"
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"https://venturebeat.com/ai/hollywood-writers-strike-ends-with-first-ever-protections-against-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Hollywood writers’ strike ends with first-ever protections against AI Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
One of the two major unions now striking in the film industry, the Writers Guild of America (WGA), has reached an agreement with the organization representing major studios, the Alliance of Motion Picture and Television Producers (AMPTP), and its leadership has voted to end the writers’ strike as of Wednesday, September 27, 2023 — 148 days after it began.
Among the concessions won by the writers are what writer and stand-up comic Adam Conover called “strong limitations on A.I.” in a post on X (formerly Twitter).
The WGA Contract 2023 website established by the union includes a summary of the new agreement, with the AI provisions under point 5 reading as follows: Artificial Intelligence VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! We have established regulations for the use of artificial intelligence (“AI”) on MBA-covered projects in the following ways: AI can’t write or rewrite literary material, and AI-generated material will not be considered source material under the MBA, meaning that AI-generated material can’t be used to undermine a writer’s credit or separated rights.
A writer can choose to use AI when performing writing services, if the company consents and provided that the writer follows applicable company policies, but the company can’t require the writer to use AI software (e.g., ChatGPT) when performing writing services.
The Company must disclose to the writer if any materials given to the writer have been generated by AI or incorporate AI-generated material.
The WGA reserves the right to assert that exploitation of writers’ material to train AI is prohibited by MBA or other law.
Overall, the prohibitions seem flexible enough to enable AI to be used when writing screenplays, but only under the control and volition of a human writer — though it remains to be seen in practice whether studios will privilege and elect to hire only those writers who are most receptive toward using AI.
Now it’s up to the Screen Actors Guild – American Federation of Television and Radio Artists (SAG-AFTRA) to settle its strike with the studios and establish its own principles around AI and 3D scanning. VentureBeat published a deep dive report on the technology’s history, present, and future outlook in Hollywood that you can read here.
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"Confessions of an AI deepfake propagandist | VentureBeat"
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"https://venturebeat.com/ai/confessions-of-an-ai-deepfake-propagandist-using-elevenlabs-to-clone-jill-bidens-voice"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Confessions of an AI deepfake propagandist: using ElevenLabs to clone Jill Biden’s voice Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
A recent deepfake video of First Lady of the United States Jill Biden , where she attacks her own husband’s —President Biden— political policies, highlights both the powerful speech potential and emerging challenges of advanced synthetic media technologies — especially in light of the pending and sure-to-be divisive 2024 U.S. general election.
Created by filmmaker and producer Kenneth Lurt, the video depicts Jill Biden delivering a speech critical of President Biden’s policy regarding the ongoing Israeli-Palestine conflict. Using machine learning (ML) techniques, Lurt was able to generate a realistic-sounding voice for Jill Biden delivering remarks attacking the president for supporting airstrikes in Gaza.
My name is Jill Biden and I want to tell you about my husband, Joe #palestine #CeasefireNOW pic.twitter.com/qfn8jjqtxN The video was posted to X (formerly Tw i tter) where it has 230,000 views at the time of this article’s publication, and Reddit’s r/Singularity subreddit where it received upwards of 1,500 upvotes, or community endorsements.
“The goal of using AI Jill Biden, was to create something absurd and cinematic enough to get folks to actually engage with the reality of what’s happening in Palestine. The drama of a radical first-lady calling out her own husband and standing up to the American empire — it’s too juicy to look away,” said Lurt in an exclusive interview with VentureBeat.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! To create this synthetic voice, Lurt used ElevenLabs, a voice and audio AI-focused startup that has trained its models on vast amounts of natural speech to clone voices. By intaking samples of Jill Biden’s authentic voice from interviews and appearances, the AI was able to generate an entirely new speech in her voice pattern and cadence.
Beyond the synthetic audio track, Lurt spliced together curated clips from Biden campaign footage, news reports on Palestine, and social media videos of suffering on the ground in Gaza. With selective editing and placement of the AI-generated speech over these real video segments, Lurt was able to craft a superficially plausible narrative.
AI is driving a new era of advertising, activism, and propaganda The use of AI and deepfake technology in political advertising is increasingly prevalent. Earlier this year, the RNC released an ad depicting generative imagery of a potential future Biden victory in 2024.
A few months later, the Never Back Down PAC launched their million dollar ad buy featuring an AI-generated version of Trump criticizing Gov. Reynolds of Iowa. This ad directly illustrated how synthetic media could be employed to either promote or attack candidates. Then in September 2023, satirist C3PMeme posted a fake video depicting Ron DeSantis announcing his withdrawal from the 2024 presidential race.
Though intended as satire, it showed how easy and convincing deepfakes had become – and the potential for both legitimate political expression as well as deliberate misinformation through manipulated media using emerging technologies.
These examples served as early tests of synthetic campaign advertising that some experts feared could proliferate and intensify misleading information flow in upcoming elections.
Notably, Lurt accomplished this synthesis with readily available and relatively inexpensive AI tools, requiring just a week of work utilizing his editing and filmmaking skills.
While he aimed to leave “breadcrumbs” indicating fiction for the discerning viewer, it could fool casual viewers.
Human effort and creativity remain key On the flip side, Lurt believes that most AI tools still offer limited quality and that human filmmaking skills are necessary to pull together something convincing.
“Most AI anything is boring and useless because it’s used as a cheap cheat code for creativity, talent, experience, and human passion,” Lurt explained.
He emphasized the pivotal role of post-production and filmmaking experience: “If I took away the script, the post-production, the real conflict, and just left the voice saying random things, the project would be nothing.” As Lurt highlighted: “The Jill Biden video took me a week. Other content has taken me a month. I can tell some AI to generate stuff quickly, but it’s the creative filmmaking that actually makes it feel believable.” Motivated by disruption According to Lurt, he wanted to “manifest a slightly better world” and draw widespread attention to the real human suffering occurring in Palestine through provocative and emotionally gripping storytelling.
Specifically, Lurt’s intent was to depict an alternate scenario where a “powerful hero” like Jill Biden would publicly condemn her husband’s policies and the ongoing violence. He hoped this absurd scenario, coupled with real footage of the destruction in Gaza, would force viewers to grapple with the harsh realities on the ground in a way that normal reporting had failed to accomplish.
To achieve widespread engagement, Lurt deliberately selected a premise—a dissident speech by the First Lady—that he perceived as too shocking and controversial to ignore. Using modern synthetic media techniques allowed him to actualize this provocative concept in a superficially plausible manner.
Lurt’s project demonstrates that synthetic media holds promise for novel discourse but also introduces challenges regarding truth, trust and accountability that societies must navigate. Regarding concerns over intentional misinformation, Lurt acknowledged both benefits and limits, stating “I hold every concern, and every defense of it, at the same time.” He reflected “We’ve been lied into wars plenty of times…that’s way more dangerous than anything I could ever make.” Rather than attributing the problem solely to information quality, Lurt emphasized “the real problem isn’t good or bad information; it’s power, who has it, and how they use it.” Lurt saw his role more aligned with satirical outlets like The Onion than disinformation campaigns. Ultimately, he acknowledged the challenges that generative content will bring, saying “I think that the concept of a shared reality is pretty much dead…I’m sure there are plenty of bad actors out there.” Mitigation without censorship Regulators and advocates have pursued various strategies to curb deepfake threats, though challenges remain. In August, the FEC took a step toward oversight by opening public comment on AI impersonations in political ads. However, Republican Commissioner Dickerson expressed doubts about FEC authority as Bloomberg Law reported , and partisanship may stall comprehensive proposed legislation.
Enterprises too face complex choices around content policies that could limit protected speech. Outright bans risk overreach and are challenging to implement, while inaction leaves workforces vulnerable. Targeted mitigation balancing education and responsibility offers a viable path forward.
Rather than reactionary restrictions, companies could promote media literacy training by highlighting technical manipulation signs. Pairing awareness of evolving techniques with skepticism of extraordinary claims empowers nuanced analysis of emerging synthetics without absolutes.
Warning against reliance on initial reactions alone and referencing fact-checkers when evaluating disputed claims instills resilient citizenship habits less prone to provocation. Such training stresses analysis over censorship to achieve resilience lawfully.
Informed participation, not preemptively restrictive stances, must remain the priority in this complex era. Many synthetic content examples still drive alternative perspectives through parody rather than outright deception calling for moderated, not reactionary, governance navigating opportunities and responsibilities in technological evolution.
As Lurt’s case illustrates, state regulation and the FEC’s role remains uncertain without mandates to oversee less regulated groups like PACs. Coordinated multi-stakeholder cooperation currently provides the optimal path to mitigating emerging threats systematically without overreaching into protected realms of political expression.
Whether one finds Lurt’s tactics appropriate or not, his explanations provide insights into his perspective on using synthetic multimedia to drive impactful political discourse in novel ways. It serves as a case study on both the promise and ethical dilemmas arising from advanced generative technologies.
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"Canva unveils AI Magic Studio and generative video with Runway | VentureBeat"
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"https://venturebeat.com/ai/canva-adds-generative-video-with-runway-and-new-ai-powered-magic-studio"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Canva adds generative video with Runway and new AI-powered Magic Studio Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Canva , the Australian online graphic design and multimedia company whose web-based platform is used by numerous media organizations worldwide to create graphics and multimedia (including VentureBeat), is celebrating its 10th anniversary with a sweeping update of numerous AI features, including offering a new generative video tool through a partnership with AI video startup Runway ML.
With Canva’s massive Magic Studio update announced today, users of the platform can access a feature called Magic Media that allows them to simply type text into a field or upload a still image. Then, Canva’s Runway integration will generate up to 18 seconds of video based on what the user provided. In the case of text, the video will be generated based on the words provided. In the case of a still image, the image will be used as the basis of the video and motion and camera movement applied.
“We believe that AI has incredible potential to supercharge the 99% of office workers who don’t have design training or access to professional design tools,” said Cameron Adams, Canva’s co-founder and Chief Product Officer, in an exclusive video call interview with VentureBeat ahead of the announcement.
In a post on X (formerly Twitter) , Runway co-founder and CEO Cristóbal Valenzuela wrote: “Excited to partner with Canva. Great things are coming.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Excited to partner with Canva. Great things are coming.
https://t.co/wf8rKq90qc In a blog post further elaborating on the team-up, Valenzuela wrote: “Runway’s mission is to ensure that anyone anywhere can tell their stories, just as Canva aims to empower the world to design. We believe that deep learning techniques applied to audiovisual content will forever change art, creativity, and design tools. This partnership is an exciting step toward furthering that mission by putting Gen-2 into the hands of Canva users so they can add the power of video to their designs.” An AI-assisted design studio But it’s not just generative video that Canva’s Magic Studio seeks to offer users.
Magic Studio is “the first all-in-one AI design platform in the market,” according to Adams, consisting of nine other major new AI features that build upon its existing AI-powered copyrighting assistant Magic Write (powered by OpenAI’s GPT-3) and text-to-image generative AI feature built atop the open source Stable Diffusion model introduced last year.
Among them are: Magic Switch: A one-click solution for turning a single design into multiple assets, such as a presentation into an executive summary, or whiteboard of ideas into a blog post. It also supports multilingual translations.
“You can go from that document you just created over to a video that you might send to your marketing team,” Adams said, displaying in a demo to VentureBeat how a visual sales report presentation could be turned into a longer text document and then finally, transformed into a video, all within seconds.
Magic Design: Start with a text prompt or still image and then this feature lets you select color schemes and builds new imagery and designs for you to choose from.
“Any idea that you put into that search box, it can generate a unique design for,” Adams said. “You can tailor it with your brand and get it perfectly customized.” Brand Voice: Type in guidelines and upload assets from your Brand Kit, and Canva’s AI writing and design features will follow them throughout all the other media you generate using the additional features listed here, including tone-of-voice and color schemes.
“It understands whether you want to be playful or whether your brand wants to be serious, or whether it wants to be enthusiastic or assertive or professional and it will be able to generate text appropriate to the brand itself,” Adams noted.
Text-to-Image with Multiple Styles: Now when you generate an image from text, Canva will give you many more options to choose from in different major art styles.
Magic Morph: Lets you tweak your lettering and shapes to make them shiny, puffy, 3D, or add other effects to help them stand out.
“If you want a big shiny green foil balloon, you can type that in as your prompt and it will automatically turn that shape into that exact style,” said Adams.
Magic Grab: Is like an auto-object selector an extractor that can isolate different objects within your image, similar to the functionality of Photoshop’s “Object Selection tool” or even the new object isolation feature available through Apple’s iOS Photos app.
“If you have a photo with a person in it…maybe you need a bit more space to add in text for social media posts you want to put out,” explained Adams by way of example. “Magic Grab enables this by understanding what’s in your photo, letting you grab the elements and move them across.” Magic Expand: As the name suggests, lets you “outfill” photos and images, expanding their area beyond the original borders using AI.
New AI apps on Canva’s Apps Marketplace: The company will allow selected third-party AI companies to offer their apps through its online storefront.
Security, indemnification, and paying creators to train AI on their designs Canva Shield is a new “enterprise-grade collection of robust safety, privacy and security controls” that allows IT administrators and design directors to encode rules for creating content in Canva through employee/team accounts, restricting certain results or content options.
Importantly for those enterprises intrigued but hesitant about AI due to underlying data copyright issues or misuses, Canva Shield offers “indemnification, providing additional peace of mind for organizations creating content with AI.” Finally, Canva is also introducing a new “Creator Compensation Program,” a $200 million fund that will pay Canva creators “who consent to having their content used to train the company’s proprietary AI models.” Canva also noted that it has seen massive success in its current embrace of AI, adding 65 million new monthly active users in the last year and nearly doubling its paying subscribers to 16 million.
The new Magic Studio features are now rolling out to all Canva paying subscribers.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Breaking down language walls: ElevenLabs launches multilingual text-to-speech for diverse audiences | VentureBeat"
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"https://venturebeat.com/ai/ai-startup-elevenlabs-launches-text-to-speech-model-supporting-30-languages"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Breaking down language walls: ElevenLabs launches multilingual text-to-speech for diverse audiences Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
ElevenLabs , a year-old startup that is leveraging the power of machine learning for voice cloning and synthesis, today announced the expansion of its platform with a new text-to-speech model that supports 30 languages.
The expansion marks the platform’s official exit from the beta phase, making it ready to use for enterprises and individuals looking to customize their content for audiences worldwide. It comes more than a month after ElevenLabs’ $19 million series A round that valued the company at nearly $100M.
“ElevenLabs was started with the dream of making all content universally accessible in any language and in any voice. With the release of Eleven Multilingual v2, we are one step closer to making this dream a reality and making human-quality AI voices available in every dialect,” Mati Staniszewski, CEO and cofounder of the company, said in a statement.
“Eventually we hope to cover even more languages and voices with the help of AI and eliminate the linguistic barriers to content,” he added.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Eleven Multilingual v2: How is it useful? ElevenLabs offers two main voice-focused AI products – Speech Synthesis and VoiceLab.
The former is a synthesis tool that generates natural-sounding speech from text inputs. The latter is an add-on of sorts that gives users the ability to clone their own voices or generate entirely new synthetic voices (by randomly sampling vocal parameters) for use with the synthesis tool.
Once a user creates their custom voice, they can plug it into the text-to-speech tool to convert any short or long-form content of their choice into their preferred speech – with no effort at all. As an alternative, they could also use a bunch of premade AI voices from the company or those created and shared publicly by the community.
In the early days, the synthesis tool started off with a model that produced speech just in English. Later, it was expanded to Eleven Multilingual version 1, which used text inputs and AI voices to generate speech in six languages: English, Polish, German, Spanish, French, Italian, Portuguese and Hindi.
Now, with the release of the Eleven Multilingual version 2, the offering can now synthesize speech in 30 more languages. This includes Korean, Dutch, Turkish, Swedish, Indonesian, Vietnamese, Filipino, Ukrainian, Greek, Czech, Finish, Romanian, Danish, Bulgarian, Malay, Hungarian, Norwegian, Slovak, Croatian, Classic Arabic and Tamil.
The move essentially means a person could clone their voice and use it to produce speech in dozens of languages targeting different markets.
According to ElevenLabs, the user has to enter the text in the language of their choice, select the voice they want (pre-made, synthetic or cloned) and adjust a few speech parameters. The model will automatically identify the written language and use the set parameters to generate speech in it. It also maintains the selected voice’s unique characteristics across all languages, including its original accent.
“Our model is able to understand the relations between words and adjust delivery based on context (‘contextual’ text-to-speech). Because there are no hardcoded voice features in the model, it can robustly predict thousands of voice characteristics while creating AI voices. This means the ElevenLabs model can take the text surrounding each generated utterance into account to maintain appropriate flow, rather than generating each utterance separately, which can create voices that sound robotic,” Staniszewski told VentureBeat.
Widespread applications of text-to-speech tool Since its launch in beta, ElevenLabs has seen interest from both enterprises and creators and claims to have registered more than a million users worldwide. The latest launch is expected to not only boost the user base of the platform but also the volume of content it generates on a daily basis.
“We have a number of enterprise clients using our products and their use cases are varied: from voicing characters in video games to voicing customer service avatars, and from recording audiobooks to creating content for the visually impaired,” Staniszewski explained.
Most recently, the company collaborated with ArXiv to publish all their papers with an audio version for additional accessibility. It also partnered with Storytel to enhance the options available for audiobooks – offering additional AI voices alongside human narrators. At some point in the future, the CEO expects it may also be able to make dubbing an entire movie into multiple languages completely seamless, while preserving the accents and emotions of the original actors.
More to come As part of this mission, ElevenLabs plans to expand its products with more languages and features, including a projects tool that will make it easier for users to structure and edit their long-form content. According to Staniszewski, it will add a “Google Docs” level of simplicity to generating speech from lengthier content.
“By the end of the year, we are also planning to release a beta version of our AI dubbing tool which will allow users to instantly convert speech from one language to another, all while preserving the original speakers’ voice,” he noted.
In this space of AI-powered voice and speech generation, ElevenLabs competes with players like MURF.AI , Play.ht and WellSaid Labs.
According to Market US , the global market for such tools stood at $1.2 billion in 2022 and is estimated to touch nearly $5 billion in 2032, with a CAGR of slightly above 15.40%.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"3D motion capture app Move AI raises $10M in seed funding | VentureBeat"
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"https://venturebeat.com/ai/3d-motion-capture-app-move-ai-raises-10m-in-seed-funding"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages 3D motion capture app Move AI raises $10M in seed funding Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
VentureBeat has written on multiple occasions about Move AI , the four-year-old, UK-based company that makes a smartphone app capable of generating 3D motion capture models from standard 2D video.
Now, the company that threatens to upend the longstanding traditional, expensive, and time-consuming method of 3D motion capture used for sports, film, TV, video games, and music videos — putting ping pong ball-like “markers” over a subject’s face or body and capturing them with specialized cameras — has gotten more funding to make its tech even better.
Today, Move AI announced it has raised $10 million in a seed round from Play Ventures, Warner Music Group, RKKVC, Level2 Ventures, and Animoca Brands.
The support from Warner Music Group signals interest from leading established brands in entertainment, and shows an obvious appetite for using Move AI’s markerless motion capture tech to create music videos and new music performance experiences (holograms, anyone?).
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “Our goal at Move AI is to democratise 3D animation,” said Move AI’s co-founder and CEO Tino Millar in a press release. “We are excited to use this funding round to double down on our efforts to reduce the cost of 3D animation and make it more accessible to creators.” Single-device motion capture coming up Move AI offers an iOS app that requires the user to place at least two smartphone cameras (and a maximum of six) around the subject, and an experimental mode that supports Android devices and other digital cameras.
However, about a month ago, Move AI changed the process for signing up for these offerings, according to an email from a spokesperson to VentureBeat: “We changed the sign-up process by removing the self-service option—where a customer could sign-up and start using the app without ever talking to a Move team member. Instead, new customers must first be onboarded by a Move team member before they can get started. Once a Move team member onboards a new customer, they are given access to the multi-camera web app and iOS app.” “We have moved to custom pricing plans, available here ,” through a new Move Pro subscription model, the spokesperson added.
Earlier in the summer, Move AI revealed exclusively to VentureBeat that it planned to offer a single-camera app in September 2023, and along with the funding announcement today, provided an update on that solution.
A new app, called “ Move One ,” is now accepting applications to its invitation-only beta testing mode, and Move AI is highlighting single-camera motion captures from initial users via social posts on its website. Move AI’s spokesperson told VentureBeat that customers of the prior multi-camera app are given Move One beta access upon request.
In its news release on the funding round, Move AI said that Move One’s “public launch will be later this year.” Implications for entertainment The implications of Move AI’s ascent for the entertainment industry are vast, especially coming on the heels of the end of the 2023 write r s’ strike , ongoing Hollywood actors’ strike , and recent strike authorization for video game performers (if a contract cannot be agreed upon).
As VentureBeat explored in our deep dive report on 3D scanning and AI usage in Hollywood , 3D scanning and AI technologies have largely been two separate branches in Hollywood until recently. Auteur directors such as James Cameron and David Fincher pioneered the use of 3D actor scanning in their films The Abyss and The Curious Case of Benjamin Button , respectively, but the technology has since spread to multiple vendors around the world.
However, those vendors have largely simply provided the hardware systems and basic software for capturing 3D models. They have not moved much into AI solutions yet, though one company, Digital Domain, provided VentureBeat with a document explaining that it was exploring generative AI as a way of creating fully “digital human” characters that could emote and perform without human actors serving as the basis for their behaviors (Digital Domain said this was likely to be used in non-entertainment industries, such as hospitality and customer service).
Yet Move AI is one of the leading consumer and “pro”-sumer facing companies seeking to bridge the gap, using its own proprietary AI models to take 2D video and convert it into 3D motion, a non-trivial task. Most other 2D-to-3D scanning apps and technologies, such as Neural Radiance Fields (NeRFs) and 3D Gaussian Splatting are usually limited to static scenes.
Indeed, Move AI had to develop an extensive “understanding [of] human motion in physics and statistics” in order to code its underlying algorithms, according to a previous comment from Millar to VentureBeat.
With Move AI, the cost of creating effects-driven films, video games, music videos, sports analysis, and other forms of art and entertainment is poised to drop dramatically, and to CEO Millar’s point, could open up creative potential for many amateurs and aspiring creators.
“We believe we can make it 100 to 1,000 times cheaper to do than with motion capture suits, while maintaining the quality, and making it much more accessible to people,” Millar previously told us.
Yet it could also be used by studios to undercut their talent by 3D scanning their work for a limited time and re-using it in perpetuity — something the actors’ union is currently standing firmly against — as well as to create unauthorized captures of individuals.
Either way, with more funding, it appears Move AI is going to make 3D motion capture even more accessible, likely putting it in the hands of many more people than ever before.
Updated Oct. 3 at 8:02 pm ET to include new information from a Move AI spokesperson regarding the changes to Move AI’s previous multi-camera app, and Move One app.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"JustCall launches AI-driven platform to improve call center ops via sentiment analysis | VentureBeat"
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"https://venturebeat.com/ai/justcall-launches-justcall-iq-enhance-call-center-operations-sentiment-analysis"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages JustCall launches AI-driven platform to improve call center ops via sentiment analysis Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
JustCall by SaaSLabs , a contact center software provider backed by Sequoia Capital , today unveiled JustCall iQ, an AI-driven conversational intelligence platform for small and medium-sized businesses (SMBs). The solution is designed to enhance the performance of call center sales teams, operations and customer support.
By harnessing the power of AI, JustCall iQ offers real-time coaching and sentiment analysis, aiming to allow call center agents to quickly achieve optimal performance. According to the company, its approach enables agents to achieve peak performance within days instead of the conventional months-long training methods.
JustCall said that the platform, facilitated by an AI bot, automatically records and transcribes all calls, delivering teams a transcript of their meetings. This streamlined process allows managers to conduct efficient call reviews without having to listen for the entire duration.
>>Don’t miss our special issue: Building the foundation for customer data quality.
<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! After analysis, the system assists sales teams in identifying crucial moments that contribute to successful or unsuccessful calls. This helps sales employees improve their pitches and convert potential leads, while support teams can use the insights to improve customer satisfaction and drive business growth.
“Our new offering is a tool that lets you record, transcribe and analyze calls to get useful information that can be used for improved onboarding, continuous training and coaching,” Gaurav Sharma, CEO and founder of JustCall, told VentureBeat. “Features such as AI-based performance scoring and sentiment analysis are great for agents and managers to improve win/call resolution rates, and our real-time agent assist bot offers prompts to agents to quickly address customer concerns as they happen.” The company claims that early adopters have experienced significant improvements, such as a 44% increase in closed-won rates, a 25% reduction in average handle time and a 32% boost in customer satisfaction.
Enhancing post-call insights through sentiment analysis Sharma emphasized his company’s commitment to eliminating guesswork in call analysis and providing valuable insights through post-call reports. These reports offer an overview of each call, including performance assessment, key takeaways, and actionable steps to reinforce successes and address challenges in future calls.
According to him, many businesses with call center managers remain entrenched in outdated call evaluation methods that depend on human monitoring. Not only does this prove costly, it results in many calls going unreviewed.
“Turnover rates for call center employees are high compared to other industries, and the work is stressful, dealing with angry customers, strict time limits and repetitive tasks,” Sharma told VentureBeat. “With JustCall iQ, we’re helping businesses improve customer experiences to capture the value of every call. We improve feedback and engagement and help guide agents with the right prompts as calls happen.” Sharma asserts that sentiment analysis offers a valuable opportunity for managers to accurately evaluate the effectiveness of their pitches and delivery in customer interactions. By employing emotion detection and language processing, customer sentiment analysis delves deep into customers’ emotions and reactions.
He said that admins and managers can use sentiment analysis to identify trends that inform their guidance and coaching of agents.
“The success of every customer interaction hinges on the real-time reactions and sentiments expressed by customers. Sentiment analysis is crucial in monitoring each call’s emotional quotient (EQ), focusing on vital parameters including fluency, empathy, satisfaction, interest levels, excitement levels, politeness and patience,” explained Sharma. “Organizations learn from precise and unbiased insights delivered after every call, eliminating the guesswork and need for manual data mining, which saves managers valuable time and ensures a more objective analysis of customer interactions.” The company said that online insurance provider Apollo Insurance has adopted the JustCall iQ platform to gain insights into its customer interactions. The platform enables Apollo to track metrics such as text volume, call duration, agent performance and the average communication count that results in conversions.
Likewise, Newity , a small business lender, has used JustCall iQ to improve operational efficiencies in its financial services business. Its sales and support teams use the platform’s real-time features, including agent assistance and real-time coaching, increasing their efficiency over a traditional QA team.
“Using the analytics has given them valuable insights into what’s happening with these calls and texts,” said Sharma. “Now they can route leads to the agents most likely to convert them to sales — which has helped them increase conversions significantly.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Business leaders concerned about generative AI adoption | VentureBeat"
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"https://venturebeat.com/ai/business-leaders-fret-about-generative-ai-despite-growing-adoption"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Business leaders fret about generative AI despite growing enterprise adoption: Study Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
A recent study conducted by IT solutions integrator Insight Enterprises and research company The Harris Poll has shed light on the increasing adoption of generative AI amongst businesses while also uncovering concerns about its implementation.
The study indicates that most business leaders from Fortune 500 companies (72%) plan to incorporate generative AI within the next three years to improve employee productivity.
However, approximately half of the respondents expressed reservations about the deployment of these technologies. The primary concerns cited were quality and control (51%) and safety and security risks (49%).
Furthermore, the study found that 90% of business leaders anticipate that adopting generative AI will impact specific organizational roles.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Data analysts and data scientists emerged as the roles leaders thought were most likely to be affected (44%), followed by software developers and testers (37%) and professionals in financial operations and communications roles (32% and 30%).
“As generative AI can assess millions of datasets and find patterns better than any human, it is extremely effective at identifying correlations in research data and making suggestions regarding potential paths for further research,” Matt Jackson, global CTO of Insight, told VentureBeat. “It can use those same capabilities to find patterns in code repositories and generate highly effective software.” Aiding employee productivity through generative AI According to the study, business leaders want to embrace generative AI primarily to enhance employee productivity and customer service.
Two-thirds (66%) of these leaders recognize the technology’s potential in improving customer service — with 44% keen on providing personalized customer experiences through gen AI.
“We’re seeing that business leaders, by and large, are excited by the potential of generative AI, primarily because it can drive both productivity improvements and increased customer engagement,” Insight’s Jackson told VentureBeat. “This data shows ample opportunity for internal and external stakeholders to leverage generative AI as a competitive advantage, helping them work ‘smarter,’ not ‘harder.’” The study reveals that around half of the business leaders (53%) anticipate gen AI’s assistance in research and development, while others expect it to automate software development.
Jackson asserts that generative AI and large language models (LLMs) will revolutionize business interactions and decision-making. He emphasized that the potential use cases for these technologies are virtually limitless, leading to a fundamental shift in the nature of work.
He said that generative AI aligns with the theory of “two types of innovation.” Sustained innovation benefits established industry leaders, while when disruptive innovation emerges it creates new markets and challenges existing businesses.
“This prompts us to inquire: Does this technology primarily serve as a ‘sustaining innovation,’ benefiting dominant hyper-scalers such as Microsoft, who already wield the requisite computing power and research capabilities? Or does it qualify as a ‘disruptive innovation,’ fostering opportunities for an entirely new ecosystem of companies?” Jackson said. “I predict that both scenarios will prove to be accurate. Nevertheless, these tools introduce captivating possibilities for company expansion, operational efficiency, and the creation of innovative products.” Lingering enterprise concerns around generative AI The study found that over a quarter of professionals (26%) express concerns about workforce displacement caused by implementing generative AI.
Respondents also cited specific concerns, including the potential limitation of human innovation (39%), budgetary constraints (38%), and compliance with legal and regulatory requirements (35%). Moreover, 38% expressed worries about human error due to lack of understanding of how to use the tool or accidental breaches of their organization’s data.
“Such data indicates that people are still central to decision-making and that we cannot become overly dependent on AI. It can help people become more productive, and it may help companies grow without the need to scale their workforce, but generative AI in its current form cannot replace a human’s creative potential,” said Jackson. “Regardless of industry, businesses are fueled by — and all about — people. Generative AI shouldn’t get in the way of that. People’s needs should be at the forefront of any decision-making surrounding generative AI.” Jackson emphasized the importance of business decision-makers carefully considering how to efficiently leverage this technology. He said that the initial step is to establish robust governance, and the stage entails developing secure and customized solutions across the entire enterprise.
“Businesses must create guardrails for testing and learning to minimize security risks. A policy framework that gets reviewed on an ongoing basis should help teammates understand the good the technology can achieve, as well as its limitations and drawbacks,” he said. “It’s encouraging to see that these practices are already in motion: Our research also found that 81% of business leaders say their company already has established or implemented policies/strategies around generative AI or are currently in the process of doing so.” Insight Enterprises and The Harris Poll conducted a targeted survey among 405 U.S. respondents aged 25 and above, all occupying full-time director-level positions or higher at companies with over 1,000 employees.
Insight said the survey results were measured for sampling precision using a credible Bayesian interval by The Harris Poll.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Vendict emerges with $9.5M in funding to automate security compliance with generative AI | VentureBeat"
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"https://venturebeat.com/security/vendict-emerges-with-9-5m-in-funding-to-automate-security-compliance-with-generative-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Vendict emerges with $9.5M in funding to automate security compliance with generative AI Share on Facebook Share on X Share on LinkedIn Credit:VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Today, enterprise software vendors must often fill out questionnaires proving they are compliant with the security requirements of the customers they seek to service — a highly manual, technical and time-consuming process.
Vendict wants to change all that. The Israeli startup is emerging from stealth today with $9.5 million in funding led by NFX, Disruptive AI and Cardumen Capital and joined by NewFund Capital, Tuesday Capital, Cyber Club London and Andy Ellis.
>> Follow all our VentureBeat Transform 2023 coverage << The company aims to streamline security compliance assessment by automating the filling out of questionnaires with generative AI -powered answers that use a vendor’s own data, saving them hundreds of work hours each month and accelerating the sales process for its clients.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! An AI fluent in security lingo? Vendict founders Udi Cohen, CEO, and Michael Keslassy, CTO, set out to create an AI model that excels in security language. This unique AI capability combines high-level security assessment expertise with cutting-edge AI innovation, a first in the governance, risk and compliance (GRC) landscape.
The company uses a combination of its own large language model (LLM) combined with other leading ones. “We use a proprietary pipeline that combines our own security-compliance-trained LLM and other proprietary models, along with Microsoft Azure rephrasing LLM,” Cohen told VentureBeat via email.
Not only does this novel AI model shorten security assessments from weeks to mere hours, it also continuously improves efficiency with every user interaction. Recognizing the integral role of natural language processing and generative AI in transforming security questionnaires and driving automation in compliance tasks, the Vendict team wants to redefine the GRC landscape.
Pro-grade responses Vendict’s innovative approach involves extracting data from an organization’s existing compliance information and using its generative AI stack to respond professionally and accurately to each question in a given questionnaire.
In addition to aiding in internal risk management, Vendict also provides internal audits, regulation tracking, and a centralized knowledge base for all compliance documentation.
With Vendict’s comprehensive vendor analysis, organizations can conduct swift end-to-end assessments based on industry, service criticality, and data sensitivity level. Vendict also guides businesses in improving their security compliance stance, thereby enabling them to venture into new markets.
Raul Zayat Galante, head of security at Orca Security, vouched for Vendict’s transformative power, stating, “We’ve been able to significantly reduce the time we spend on RFIs and security questionnaire responses … We highly recommend Vendict to any organization that wants to improve its RFI and security questionnaire response process.” Vendict’s Cohen expressed his vision for the future of security compliance, saying, “Vendict will generate security assessment reports to the buyers, based on the sellers’ documents, and the criticality of the vendor.” Through these innovations, Vendict wants to lead a paradigm shift in how security compliance is approached, making it less burdensome and easier than ever before.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Network, IAM, cloud are 2023's top cybersecurity spend priorities | VentureBeat"
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"https://venturebeat.com/security/network-iam-cloud-top-3-cybersecurity-spending-priorities-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Network, IAM and cloud are the top 3 cybersecurity spending priorities for 2023 Share on Facebook Share on X Share on LinkedIn Red Shield Cloud Computing Cybersecurity Technology 3D Rendering Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Attackers are so relentless at innovating new breach techniques that cyber-defenses implemented in 2022 have already weakened, with yet more severe attacks coming in 2024. Most cybersecurity leaders (71%) say their organizations have experienced three or more security incidents in the last year alone.
Ransomware breach attempts fell by 30% last year as attackers pivoted to new attack strategies that are proving more lucrative and less detectable. As attackers out-innovate the current generation of security platforms, total attack activity continues to grow, despite budgets growing too in an uncertain economic climate.
Scale Venture Partners ’ (SVP) Cybersecurity Perspectives 2023 report provides insights into the many challenges CISOs face. These include growing attack sophistication, talent shortages, geopolitical tensions and overworked security teams. The report found that CISOs are doubling down on network, IAM and cloud security to better protect against identity-based attacks.
CISOs battling identity theft Organizations’ growing reliance on multiple cloud services creates an attractive breach target for attackers, who use pretexting and social engineering to steal privileged access credentials. SVP’s survey found that 50% of security leaders say their cloud services accounts have been attacked in the last year. That’s consistent with CrowdStrike’s 2023 Global Threat Report.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! CrowdStrike found that exploitation of gaps in cloud infrastructure — most often the stealing of credentials, identities and data — grew 95% in 2022, with cases involving “cloud-conscious” threat actors tripling year-over-year. Attackers are seeking to modify authentication processes in order to attack identities.
“An especially popular tactic was the abuse of compromised credentials acquired via information stealers or purchased on the criminal underground, reflecting a growing interest in targeting identities that we also saw last year: Our 2022 report found 80% of cyberattacks leveraged identity-based techniques,” writes CrowdStrike cofounder and CEO George Kurtz.
Identities are under siege , and CISOs are prioritizing their spending in response. Getting identity and access management (IAM) under control is a challenging problem, especially when an organization relies on multiple cloud services, said Ariel Tseitlin , partner at SVP, in a recent interview with VentureBeat. The number of firms compromised by phishing attacks that stole employee credentials via cloud services rose 58%.
“Identity is where security is going … because there’s just so much more rich data there,” Tseitlin told VentureBeat. IAM jumped from eighth place to second in this year’s investment priorities ranking, reflecting increasing market concerns about identity security in multicloud tech stacks. Network security and cloud infrastructure security remain from last year’s survey, joining IAM as enterprises’ top three cybersecurity spending priorities in 2023. (Leading IAM providers include AWS Identity and Access Management , CrowdStrike, Delinea , Ericom , ForgeRock , Google Cloud Identity , IBM Cloud Identity, Microsoft Azure Active Directory , Palo Alto Networks and Zscaler.
) Enterprise cybersecurity budgets averaging a 20% increase Large enterprises are seeing a 20% average rise in security budgets, though mid-sized enterprises are averaging only a 5% increase. SVP’s survey of security leaders also found that security budgets for emerging technologies rose 18% this year, down 27% from 2022. That’s consistent with what many other surveys are seeing, including Ivanti’s State of Security Preparedness 2023 Report , which found that 71% of CISOs and security professionals predict their budgets will jump an average of 11% this year, well above the projected inflation rate.
Data, application, cloud and endpoint security are getting, on average, 10% of companies’ total cybersecurity budgets this year. Compared to last year, budgets for endpoint security, identity management and security awareness training are seeing the biggest increases.
Artificial Intelligence (AI) and machine learning (ML) security and software supply chain security were included for the first time in this year’s survey, accounting for 6% and 5% of budgets respectively.
A sure sign that boards of directors see cybersecurity spending as an investment that helps control risk is the increase in security budget per employee, rising to $3,653 this year, up 20% from $3,033 per employee last year.
Cybersecurity’s resilient budgets reflected in fast-growing revenue forecasts Organizations are reluctant to cut cybersecurity budgets for fear of falling too far behind as attackers use new technologies, including AI/ML , to launch attacks while weaponizing old vulnerabilities at the same time. SVP notes that CISOs are preparing for greater scrutiny of their spending decisions and longer decision-making timeframes , however.
Throughout the last three years, cybersecurity budgets have been among the most resilient across every size of organization. The aggregated effects of continued spending and what Gartner is hearing from its enterprise clients about planned purchases led the analysis company to predict that end-user spending on the information security and risk management market will grow to $188.1 billion this year and reach $288.5 billion in 2027. That’s a compound annual growth rate (CAGR) of 11.0% from 2022 to 2027.
Gartner’s latest forecasts [client access required], by selected enterprise information security and risk management markets, include the following, further reflecting how resilient budgeting is driving market growth: Application security is predicted to grow from $5.7 billion in revenue this year to $9.6 billion in 2027, attaining a 13.6% CAGR.
Cloud security is predicted to grow from $5.6 billion in revenue this year to $12.8 billion in 2023, attaining a 22.8% CAGR.
Data security is predicted to grow from $3.6 billion in 2023 to $6.1 billion in 2027, attaining a 13.6% CAGR.
Identity access management is predicted to grow from $16.1 billion in 2023 to $24.8 billion in 2027, attaining an 11.4% CAGR.
Enterprises look to AI/ML to close the talent gap Security leaders responding to PVC’s survey said finding and hiring cloud security experts is the most challenging role to fill. More than half of organizations (57%) said the biggest obstacle to achieving their desired security posture was insufficient security personnel, up 42% from last year. Security teams struggle with, among other things, too many alerts, too many false positives and too many tools.
AI/ML tools are helping security leaders fill the talent gap and scale their understaffed teams. Four out of five security leaders (79%) believe AI/ML will be “important” or “extremely important” for improving their security posture by 2024. More than 60% of cybersecurity leaders rely on cybersecurity tools with AI /ML-based capabilities to further offset talent shortages. And 62% of security leaders are using AI/ML-based tools to automate security processes.
Meanwhile, CISOs tell VentureBeat they are piloting generative AI -based platforms with ChatGPT capabilities to reduce SecOps workloads. Emerging from the initial pilots are ten use cases that show the potential to offload SecOp’s teams’ workloads.
Who owns a business’ identities, owns the business SVP’s study reflects how critical it is for every organization to get in control of IAM and have a solid strategy for hardening their every vulnerable threat surface. Identities are the most vulnerable security perimeter there is.
Attackers know gaps exist in cloud configurations, and by stealing privileged access credentials they can, in effect, take control of an entire business before anyone realizes it. That’s why IAM is critical to get right, and why it is seeing rapid growth. CISOs and CIOs continue collaborating toward the goal of closing cloud configuration gaps and strengthening network security.
And it all needs to start with identities — attackers’ primary target today.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Dropzone AI launches autonomous AI agent to investigate security alerts, raises $3.5M in seed funding | VentureBeat"
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"https://venturebeat.com/security/dropzone-ai-launches-autonomous-ai-agent-to-investigate-security-alerts-raises-3-5m-in-seed-funding"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Dropzone AI launches autonomous AI agent to investigate security alerts, raises $3.5M in seed funding Share on Facebook Share on X Share on LinkedIn Edward Wu, founder and CEO of Dropzone AI (Image Credit: Dropzone) Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Dropzone AI , a startup that aims to automate the tedious and time-consuming work of investigating security alerts, announced today that it has raised $3.5 million in seed funding from a group of investors led by Decibel Partners, a venture capital firm that focuses on early-stage enterprise software companies.
The company also announced the availability of its autonomous AI security agent, a software product that uses large language models (LLMs) to mimic the thought processes and techniques of expert security analysts. The agent can process and investigate every security alert from various sources and produce detailed reports and recommendations for human analysts.
“We have reached an inflection point where humans alone can’t keep up,” said Edward Wu, founder and CEO of Dropzone AI, in an exclusive interview with VentureBeat. “They need to be armed with an entirely new and better way to automate and enable their defensive forces.” Using LLMs to reinforce the frontlines of cybersecurity Wu said he started Dropzone AI because he observed that cyber-defenders are losing the technological arms race against attackers, who can leverage LLMs to improve their attacks. He also said that the acceleration of digitalization means that security teams need to deal with thousands of alerts every day from different security systems, such as endpoint detection and response (EDR), firewall, intrusion detection system (IDS), email, and cloud security solutions.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “Most teams are only able to fully research about 10% of daily events, leaving open the likely possibility of missing early warning signs of serious security breaches,” Wu said.
Wu told VentureBeat that his company’s solution can help security teams cope with the increasing volume and complexity of cyberattacks, and enable them to focus on higher-value security work. He said that his company’s AI agent does not rely on pre-programmed playbooks, which are difficult to write and maintain, but rather uses LLMs to reason and investigate alerts autonomously.
“Our approach sidesteps some of the traditional challenges that require terabytes of existing, well labeled, human-curated security data in order to train or build an AI system that works,” Wu said. “We use a slightly different approach that does not require a vast treasure trove of data to begin with, and that allows us to bootstrap our technology and kickstart the customer data network flywheel without spending years or tens of millions of dollars just gathering data.” Automating security alert investigation with AI Dropzone AI’s leading product is not just another chatbot system for security workers. Instead, it is being marketed as an autonomous alert investigation system that can conduct end-to-end investigations of security alerts autonomously and generate a comprehensive report with a recommended conclusion. “Our main product capability is the autonomous alert investigation capability, where you feed in alerts and the system goes about performing the investigation end-to-end autonomously,” Wu explained.
The company also offers a secondary chatbot capability, designed to handle ad hoc investigations and questions from the organization. Wu describes the chatbot as a “natural language interface” that allows analysts to focus on the information they want to know, acting as an assistant that navigates across different data sources to perform information retrieval.
“We are building autonomous agents. We don’t need human analysts to tell the system what to do. The system, from day one, already knows what to do and knows how to use different security tools and data sources,” Wu emphasized. This level of automation and intelligence is on an autonomous agent level, akin to Tesla’s full self-driving technology, compared to the cruise control-like functionality of the chatbots from other companies.
Wu also said that his company provides oversight and transparency to security teams that use his AI agent for alert investigation. He said that Dropzone AI’s autonomous agent does not necessarily replace human analysts, but rather assists them with the frontline work and produces detailed investigation reports that show the chain of evidence and reasoning behind their conclusions.
Wu said that his company is still in the early stage of development and is actively working with design partners to improve its technology. He also said that his company will have an online demo on its website where anyone can experience its AI agent. He said that the company will be in attendance at the Black Hat USA 2023 cybersecurity conference this week in Las Vegas.
Backed by cybersecurity veterans The seed funding round was led by Decibel Partners, joined by Pioneer Square Ventures Fund. Notable angel investors such as Oliver Friedrichs, CEO of Pangea Security and founder and former CEO of Phantom Cyber, Jon Oberheide cofounder and former CTO of Duo Security, and Jesse Rothstein, cofounder and CTO of ExtraHop, also participated in the round.
Jon Sakoda, founder of Decibel Partners, said in a statement that he was impressed by Wu’s vision and expertise in using AI to augment security operations teams.
“Cybersecurity teams need to update their defensive scheme with the best technology available, and Dropzone is an essential tool for every company that wants to rapidly augment its security operations team to face the increasing cyber threats of today’s world,” Sakoda said. “We are incredibly privileged to partner with Edward and to help him deliver on his vision of using AI to deploy autonomous reinforcements — this changes the game for cybersecurity teams and brings much-needed help to the front lines.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Designing for safety: 10 cybersecurity priorities for a zero-trust data center | VentureBeat"
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"https://venturebeat.com/security/designing-for-trust-top-10-cybersecurity-priorities-for-cios-in-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Designing for safety: 10 cybersecurity priorities for a zero-trust data center Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
This article is part of a VB special issue. Read the full series here: The future of the data center: Handling greater and greater demands.
Zero trust is the virtual shield data centers need to harden against increasingly complex, well-orchestrated data center attacks. Attackers are gaining access to data centers using stolen privileged access credentials and IDs , looking to exfiltrate as much customer data as possible.
Just to name two examples, attackers successfully obtained emails, passwords and other customer data from Shanghai-based GDS Holdings Ltd.
and Singapore-based ST Telemedia Global Data Centres , two of Asia’s largest data center operators.
Resecurity Inc.
recently provided an in-depth analysis of attackers’ strategies to infiltrate data centers, cloud service providers and managed service providers. Resecurity found that the most vulnerable threat vectors for data centers include customer support, customer service, and ticket management support portals running on data center servers. Attackers can gain enough control to steal thousands of customer records and exfiltrate a company’s most confidential data if not discovered.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The challenge for CIOs and CISOs is to deliver virtual shields that scale Designing for trust must start with the cornerstone of zero trust : the belief that the data center has already been breached, and further damage must be contained and stopped immediately. That’s because attackers are continuously fine-tuning their craft to find and exploit gaps in data center security architectures and tech stacks. These gaps often appear when long-standing on-premise security platforms are extended to the cloud without the correct configurations, leaving the systems vulnerable to breach.
CIOs and CISOs are teaming up to tackle the challenge of fast-tracking secure access service edge (SASE) and zero trust network access (ZTNA) initiatives in data centers to harden virtual shields against further attacks. CIOs tells VentureBeat that SASE improves enterprise security postures by providing ZTNA at scale while helping to consolidate data center and enterprise-wide security.
ZTNA needs to be on every CISO’s SASE roadmap.
Gartner predicts ZTNA will be the fastest-growing network security market segment worldwide. It’s forecast to achieve a 27.5% compound annual growth rate between 2021 and 2026, increasing from $633 million to $2.1 billion worldwide.
Esmond Kane, CISO of Steward Health , advises , “Understand that — at its core — SASE is zero trust. We’re talking about identity, authentication, access control and privilege. Start there and then build out.” CIOs and CISOs are seeing their roles overlap in cybersecurity , making shared ownership of data center security outcomes a must. At 19% of publicly-traded companies and 46% of private companies, the CISO currently has the double role of CISO and CIO, according to a survey of 650 security executives published earlier this year by Hitch Partners.
CIOs tell VentureBeat that their boards of directors consider getting data center security right to be integral to their risk management.
Eighty-eight percent of boards now view cybersecurity as a business risk.
Foundry’s State of the CIO Study 2023 found that security improvements are the most significant factor driving tech budget increases in 2023.
Top 10 cybersecurity priorities for 2023 There’s no shortage of cybersecurity weaknesses known to attackers, who seek to exploit them undetected. From the unsecured networks connecting data centers across an organization to the legacy systems relying on perimeter-based security, many data centers are breaches waiting to happen. Moving workloads to the cloud often expands the attack surface, with hybrid multicloud platforms among the riskiest and most challenging to secure. Enterprises getting the best results base their data center cybersecurity strategies on proven frameworks, with SASE and ZTNA the most prevalent.
1. Prioritize identity security first, using single sign-on (SSO) and multifactor authentication (MFA) “The best place to start is always around enforcing multifactor authentication,” Forrester senior analyst Andrew Hewitt told VentureBeat. Hewitt is the author of the report, The Future of Endpoint Management.
“This can go a long way toward ensuring that enterprise data is safe. From there, it’s enrolling devices and maintaining a solid compliance standard with the unified endpoint management (UEM) tool,” he added.
2. Make auditing access privileges, deleting obsolete accounts and reviewing admin rights part of the organization’s muscle memory According to Ivanti’s 2023 Cybersecurity Status Report , 45% of enterprises believe former employees and contractors still have active access to company systems and files due to inconsistent or nonexistent procedures for canceling access. De-provisioning is rarely done, and third-party apps still have access. “Large organizations often fail to account for the huge ecosystem of apps, platforms and third-party services that grant access well past an employee’s termination,” said Srinivas Mukkamala, chief product officer at Ivanti.
Leading IAM providers include AWS Identity and Access Management , CrowdStrike , Delinea , Ericom, ForgeRock, Ivanti, Google Cloud Identity , IBM Cloud Identity , Microsoft Azure Active Directory , Palo Alto Networks and Zscaler.
3. Consider replacing legacy IAM systems that can’t monitor identities, roles and privileged access credential activity early in your SASE and ZTNA roadmaps VentureBeat has learned from CISOs that legacy IAM systems long used to protect networks and data centers are having trouble keeping up with the vast numbers of new identities being generated today. An IAM that can track only some identity activity across roles, privileged access credential use, and endpoint used in real time is too risky. Legacy IAM systems have gaps that attackers exploit by offering bounties on the dark web for privileged credentials to financial services’ central accounting and finance systems, for example.
4. Microsegmentation can reduce data center lateral movement and attack surfaces when a breach happens Succeeding with an SASE framework supported by ZTNA needs to start with the assumption that the data center has already been breached. The goal is to stop lateral movement immediately and reduce the threat of attack surfaces leading to a breach.
The NIST zero-trust framework prioritizes microsegmentation alongside identity-based governance, authentication, and network and endpoint security management.
Airgap Networks , AlgoSec , ColorTokens , Illumio , Prisma Cloud and Zscaler Cloud Platform use microsegmentation to detect and stop intrusions and breach attempts early.
One of the most innovative is AirGap Networks, one of the top 20 zero-trust startups to watch in 2023 , which introduced its Airgap Zero Trust Firewall, or ZTFW, earlier this year. ZTFW prevents threats from spreading from IT to the core network and vice versa, even if higher network layers have been compromised. Airgap’s ZTFW defends critical business infrastructure and secures core networks by providing identity, agentless microsegmentation, and secure access for every connected endpoint.
Last month AirGap Networks acquired NetSpyGlass to enable Airgap ZTFW customers to better detect, locate and contain device anomalies in real time. “The greater the accuracy of asset discovery in these systems, the shorter the response time,” said Ritesh Agrawal, CEO and cofounder of Airgap Networks. “With the addition of NetSpyGlass, the Airgap ZTFW offers businesses the steering wheel to drive trust [in] their core network at speed and scale. It’s a game-changer for securing business-critical networks.” 5. Real-time asset management across all endpoints and data centers is table stakes CISOs use IT asset management systems and platforms to find and identify network equipment, endpoints, related assets, and contracts. Combining bot-based asset discovery with AI and ML algorithms improves IT asset management accuracy and monitoring.
Ivanti’s Neurons for Discovery combines bot-based asset discovery, AI and ML to create real-time service maps of network segments or an entire infrastructure. In addition, Ivanti updates configuration and asset management databases to receive real-time normalized hardware and software inventory and usage data. Other leading asset management providers include Absolute Software , Airgap Networks, Atlassian , CrowdStrike, BMC , ManageEngine , MicroFocus and ServiceNow.
6. Real-time telemetry data can extend endpoint lifecycles and catch intrusion attempts that might otherwise be missed Endpoint security requires real-time endpoint telemetry data to detect intrusions and breaches. This data is also helpful in identifying every endpoint’s hardware and software configuration at every level — file, process, registry, network connection and device data. Absolute Software, BitDefender , CrowdStrike, Cisco , Ivanti and Microsoft Defender for Endpoint , which secures endpoint data in Microsoft Azure, and other leading vendors use real-time telemetry data to generate endpoint analytics.
CrowdStrike, ThreatConnect, Deep Instinct and Orca Security calculate IOAs and IOCs using real-time telemetry. IOAs identify an attacker’s intent and goals regardless of malware or exploit. IOAs and IOCs provide forensics to prove a network breach.
Automating IOAs gives accurate, real-time data to understand attackers’ intent and stop intrusion attempts.
CrowdStrike launched the first AI-powered IOAs to protect endpoints using real-time telemetry data. The company told VentureBeat in a recent briefing that AI-powered IOAs work asynchronously with sensor-based machine learning and other sensor defense layers.
7. As data center endpoints take on more identities, they need audits and improvements to crucial digital certificate management Each network machine needs a unique identity to manage and secure machine-to-machine communications. More identities on endpoints make it harder to secure them all.
Key and digital certificate management must be prioritized. SSL, SSH keys, code-signing certificates, TLS, and authentication tokens assign digital identities. Cyberattackers bypass code-signed certificates or compromise SSL and TLS certificates to attack SSH keys. Data center security teams must ensure that every machine’s identity is accurate, reliable and trustworthy.
CheckPoint , Delinea, Fortinet , IBM Security , Ivanti, Keyfactor , Microsoft Security , Venafi and Zscaler are leading providers in this area.
8. Datacenter endpoints must identify an intrusion attempt and autonomously self-heal CISOs tell VentureBeat they are inheriting data centers located five or more time zones away. Sending staff to refresh endpoints isn’t feasible or financially prudent given the budget crunch many face. Many are evaluating and adopting self-healing endpoints that can capture and act on real-time telemetry data, rebuild themselves if breached, and can be programmed to brick themselves if necessary.
Closing the gaps between identity management and endpoint security is the future of zero trust. Michael Sentonas, CrowdStrike’s president, told VentureBeat in a recent interview that closing the gap between identities and endpoints is “one of the biggest challenges that people want to grapple with today. I mean, the hacking [demo] session that George and I did at RSA [2023] was to show some of the challenges with identity and the complexity. The reason why we connected the endpoint with identity and the data that the user is accessing is because it’s a critical problem. And if you can solve that, you can solve a big part of the cyber problem that an organization has.” Absolute Software, Akamai , Cisco, CrowdStrike, ESET , Cybereason Defense Platform , Ivanti, Malwarebytes , Microsoft, SentinelOne , Tanium , Trend Micro and many others vendors offer autonomously self-healing endpoints. Absolute Software is among the most unique in that it provides an undeletable digital tether to every PC-based endpoint to monitor and validate real-time data requests and transactions.
Absolute’s Resilience platform automatically repairs or reinstalls mission-critical applications and remote queries, remediating remote devices at scale. The platform can also discover sensitive data on endpoints and investigate and recover stolen devices. Absolute also turned its endpoint expertise into the industry’s first self-healing zero-trust platform.
9. Deploy risk-based conditional access for every data center threat surface, starting with endpoints Risk-based access for applications, endpoints and systems is enabled in least-privileged access sessions based on device type, settings, location and anomalous behaviors. Real-time risk scores are calculated by cybersecurity vendors using ML algorithms. “This ensures MFA (multifactor authentication) is triggered only when risk levels change — ensuring protection without loss of user productivity,” CrowdStrike’s Raina told VentureBeat. Leading vendors providing risk-based conditional access include CheckPoint, CrowdStrike, Fortinet, IBM Security, Ivanti, Microsoft Security, Venafi and Zscaler.
10. Data-driven, automated patch management reduces IT team workload CIOs tell VentureBeat that their IT teams are too overwhelmed with projects and urgent requests to work through the inventory of devices that need updates.
A data-driven approach is needed for large-scale patch management.
Leading banking, financial services and manufacturing companies, and CIOs and CISOs who run multiple data centers, are adopting AI- and ML-based systems to keep the thousands of devices across their data centers updated.
Leading vendors include Broadcom , CrowdStrike, Ivanti, SentinelOne , McAfee , Sophos , Trend Micro , VMWare Carbon Black and Cybereason.
Ivanti’s Neurons platform uses AI-based bots to find, identify and update all endpoint patches. Ivanti’s risk-based cloud patch management integrates the company’s vulnerability risk rating (VRR) to help SOC analysts prioritize risk. Ivanti discovered how to track service-level agreements (SLAs) and alert teams to devices nearing SLAs.
Data center cybersecurity is a business decision CIOs and CISOs need to partner to define a unified cybersecurity strategy to protect data centers, many of which are being protected with legacy perimeter-based systems today. Choosing an SASE-based strategy with ZTNA at its core is the direction many banking, insurance and financial services enterprises are going today. This approach is well suited for financial services, for example, which must keep certain systems on-premises for compliance requirements.
Attackers move faster than the most efficient IT, cybersecurity and SecOps teams do today. To protect their data centers, CIOs, CISOs and their teams must start by protecting identities first. The 10 priorities above are a roadmap to get started creating a hardened virtual shield that will reduce breaches and alleviate their severity. Breaches are coming; it’s a matter of minimizing the blast radius and reducing the losses they’ll create.
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"5 ways generative AI will help bring greater precision to cybersecurity | VentureBeat"
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"https://venturebeat.com/security/5-ways-generative-ai-will-help-bring-greater-precision-to-cybersecurity"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages 5 ways generative AI will help bring greater precision to cybersecurity Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Every cybersecurity vendor has a different vision of how generative AI will serve its customers, yet they all share a common direction. Generative AI brings a new focus on data accuracy, precision and real-time insights. DevOps, product engineering and product management are delivering new generative AI-based products in record time, looking to capitalize on the technology’s strengths.
All vendors realize generative AI is a double-edged sword, and each must provide guidance for reducing risks. Several have designed safeguards into their products, including Airgap Networks , CrowdStrike , Microsoft Security Copilot and Zscaler.
>>Don’t miss our special issue: Building the foundation for customer data quality.
<< Demand for generative AI-based cybersecurity platforms and solutions is predicted to grow at a compound annual growth rate of 22% between 2022 and 2023 and reach a market value of $11.2 billion in 2032 , up from $1.6 billion in 2022.
Canalys estimates that more than 70 % of businesses will have their cybersecurity operations supported by generative AI tools within the next five years.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Generative AI is dominating cybersecurity roadmaps and user events VentureBeat regularly gets briefings from cybersecurity vendors about their roadmaps. We’ve observed five ways generative AI has become the cornerstone of existing platform refreshes and new platform and app development. Zscaler’s Zenith Live 2023 event last week reflected what’s coming this year in generative AI products, both those under development and those ready for launch.
>>Follow VentureBeat’s ongoing generative AI coverage<< These cybersecurity vendors have announced generative AI products and services: Airgap Networks : One of the top 20 startups to watch in zero trust , AirGap Networks, with its Zero Trust Firewall ( ZTFW ) platform with ThreatGPT , reflects how quickly and completely DevOps teams are capitalizing on generative AI’s strengths to add value for prospects and customers. ThreatGPT uses graph databases and GPT-3 models to reveal cybersecurity insights. The company set up GPT-3 models to analyze natural language queries and identify security threats, while graph databases provide contextual intelligence on endpoint traffic relationships.
Cisco Security Cloud : Cisco announced a new series of generative AI products and services at its CISCO LIVE event earlier this month. Among the many announcements are new generative AI features added to Cisco’s Collaboration and Security portfolios, new generative AI-powered summarization features for the Cisco Webex platform, and new AI capabilities in Cisco Security Cloud designed to simplify policy management and improve the time to a threat response.
CrowdStrike : CrowdStrike’s deep AI and machine learning (ML) expertise is reflected in every aspect of its product and services strategy. From turning its XDR framework into a growth engine to the many new AI/ML-based products launched at its 2022 Fal.Con event , CrowdStrike’s ability to use AI/ML and now generative AI to reduce risks while delivering greater precision is noteworthy. Its latest product is Charlotte AI , a generative AI security analyst.
“If you look at CrowdStrike’s conception in 2011, one of the things that [CEO] George [Kurtz] talked about was that we couldn’t solve the security problem unless we used AI,” Michael Sentonas told VentureBeat during a recent interview.
“In the lead-up to going public as a company, he also talked about AI, and since we’ve gone public, every quarter when we talk to Wall Street, we talk about AI. We’ve been using AI as part of our efficacy and prevention models, and we leverage AI when we do threat hunting. It’s a core part of what we do.” Google Cloud Security AI Workbench: Sec-PaLM, Google’s security large language model (LLM), powers Google Cloud Security AI Workbench. One of its key goals is to provide an extensible platform that can flex and adapt in real time to enterprises’ rapidly changing workloads and requirements. Google announced that it is relying on partner plug-in integrations for threat intelligence, workflow, and future security features.
Microsoft Security Copilot : This is a GPT-4 implementation that adds generative AI to Microsoft’s in-house security suite. It detects breaches, connects threat signals and analyzes data using OpenAI’s GPT-4 generative AI and Microsoft’s security models.
Mostly AI: A synthetic data generation platform that relies on generative AI and is gaining rapid adoption across enterprises, educational institutions and government use cases, the Mostly AI platform can automatically learn new patterns, structures and variations from existing datasets. Customers also use the platform to generate realistic simulations and representative synthetic data at scale.
Palo Alto Networks : Palo Alto Networks’ CEO Nikesh Arora remarked on the company’s latest earnings call that the company sees “significant opportunity as we begin to embed generative AI into our products and workflows,” adding that the company intends to deploy a proprietary Palo Alto Networks security LLM in the coming year.
Recorded Future: Recorded Future trained OpenAI’s GPT model on more than 10 years of research insights ( including 40,000 analyst notes ) and 100 terabytes of text, images and technical data from the open web and dark web as well as a decade of expert insight from Insikt Group, to create written threat reports on demand. Recorded Future has integrated trained models with Intelligence Graph.
SecurityScorecard : SecurityScorecard’s AI-powered solution integrates with OpenAI’s GPT-4 to enable cybersecurity leaders to enter natural language queries and receive feedback on cyber-exposure and security gaps throughout their environment.
SentinelOne : SentinelOne’s threat-hunting platform uses generative AI and neural networks to detect and stop cyberattacks. The platform integrates multiple layers of AI technologies that enable real-time, autonomous enterprise-wide attack detection and response. SentinelOne’s platform is also designed to provide security teams the flexibility of asking complex threat and adversary-hunting questions while running operational commands.
Veracode : Veracode has launched a generative AI-based product called Veracode Fix that uses AI to make suggestions for making the software more secure. The product uses a GPT-based machine learning model trained on Veracode’s proprietary dataset to fix insecure code and reduce the work and time needed to fix flaws.
ZeroFox : ZeroFox has developed FoxGPT, a generative AI-based addition to its External Cybersecurity Platform. FoxGPT accelerates intelligence analysis and summarization across large datasets, identifying malicious content, phishing attacks and potential account takeovers. ZeroFox has continued to develop and add new machine learning capabilities to its platform, keeping pace with the rapid developments in the field.
Zscaler : Zscaler announced three generative AI projects in preview at its Zenith Live 2023 event last week. They include Security AutoPilot with Breach Prediction, Zscaler Navigator, and Multi-Modal DLP. Zscaler also made four new product announcements at the event: Zscaler Risk360 , Zero Trust Branch Connectivity , Zscaler Identity Threat Detection and Response (ITDR) , and ZSLogin which includes passwordless multifactor authentication, automated administrator identity management and centralized entitlement management.
Deepen Desai, Global CISO and VP of security research and operations, delivered a keynote titled “The Power of Zscaler Intelligence: Generative AI and a Holistic View of Risk” that provided an insightful look at how Zscaler plans to further capitalize on generative AI’s strengths. Desai told VentureBeat that Zscaler relies on customized large language models (LLMs) to predict breaches and ensure policies are set and executed accurately, with greater precision.
Five ways generative AI enhances cybersecurity precision Detecting anomalies faster than currently available technologies can, parsing logs and finding anomalous patterns in real time, triaging and responding to incidents and simulating attack patterns are a few of the many ways generative AI is already starting to revolutionize cybersecurity. Based on recent interviews with over a dozen cybersecurity leaders, including Airgap Networks’ CEO Ritesh Agrawal , CrowdStrike’s president Michael Sentonas , senior vice president of Ericom’s Cybersecurity Business Unit David Canellos and several others, we identified five areas where generative AI has the most significant impact on current and future product strategies: 1.
Real-time risk assessment and quantification Boards of directors and the C-level executives reporting to them have years of expertise in managing risk. Today’s accelerated, more complex risks create new challenges, however, and open up opportunities for CIOs and CISOs to advance their careers.
The ability to quantify cyber-risk and prioritize costs, expected returns, and outcomes from competing cybersecurity projects is a valuable skill set for any CIO or CISO today. The leading cybersecurity vendors see this as an opportunity to combine generative AI with their platforms and the telemetry data they capture daily to train models.
Zscaler’s launch of Risk360 is an example of the type of innovation cybersecurity vendors are pursuing with generative AI.
The greater CIOs’ and CISOs’ ability to quantify and control risk, the greater their potential to progress in their careers.
CrowdStrike ’s George Kurtz said during his Fal.Con keynote last year that he is “seeing more and more CISOs joining boards. I think this is a great opportunity for everyone here [at Fal.Con] to understand what impact they can have on a company. From a career perspective, being part of that boardroom and helping them on the journey is great. To keep business resilient and secure.” Leading vendors providing AI-based real-time risk assessment and quantification include Absolute Software, CrowdStrike, Ivanti, Trend Micro with its Trend Vision One™ platform, SAFE Security which launched its Cyber Risk Quantification (CRQ) solution, and Deloitte and its cyber-risk quantification services.
2.
Generative AI will revolutionize extended detection and response (XDR) Extended detection and response (XDR) platforms use APIs and an open architecture to aggregate and analyze telemetry data in real time. Vendors are also designing their XDR platforms to reduce application sprawl and remove cyberattack roadblocks, relying on generative AI to eliminate the data silos that have previously limited XDR’s latency and accuracy. Generative AI will also contextualize the massive amount of telemetry data available from endpoints, email repositories, networks and web-based apps. XDR platforms are an ideal use case for generative AI, as many rely on a single data lake. Leading XDR providers include CrowdStrike , Microsoft , Palo Alto Networks , Tehtris and Trend Micro.
3.
Improving endpoint resilience, self-healing capability and contextual intelligence Generative AI shows the potential to increase endpoints’ resiliency and self-healing capabilities. Analyzing the data that endpoints generate will yield greater contextual intelligence and insight that LLMs will use to learn and respond to attack patterns. By definition, a self-healing endpoint can turn itself off, recheck OS and application versioning, and reset to an optimized, secure configuration autonomously.
Endpoint data continues to be a significant source of innovation.
With generative AI being designed into the platforms of self-healing endpoint providers, the pace and scale of innovation will accelerate. Leading providers include Absolute Software , Akamai , BlackBerry , CrowdStrike , Cisco , Ivanti , Malwarebytes , McAfee and Microsoft 365.
Each of these providers takes a different approach to managing self-healing and resilience. Absolute’s approach is based on being embedded in the firmware of over 500 million endpoint devices that provide their customers’ security teams with real-time telemetry data on the health and behavior of critical security applications using proprietary application persistence technology. This creates a hardened, undeletable digital tether to every PC-based endpoint.
Absolute Software’s Resilience , the industry’s first self-healing zero-trust platform, is noteworthy for its asset management, device and application control, endpoint intelligence, incident reporting and compliance features, according to G2 Crowds’ crowdsourced ratings.
4.
Improving existing AI-based automated patch management techniques CISOs tell VentureBeat that an intrusion, a mission-critical system breach, or a theft of access credentials usually prompts patching.
Ivanti’s State of Security Preparedness 2023 Report found that 61% of external events, intrusion attempts or breaches restart patch management.
“Patching is not nearly as simple as it sounds,” said Dr. Srinivas Mukkamala, chief product officer at Ivanti, during a recent interview with VentureBeat. “Even well-staffed, well-funded IT and security teams experience prioritization challenges amidst other pressing demands. To reduce risk without increasing workload, organizations must implement a risk-based patch management solution and leverage automation to identify, prioritize and even address vulnerabilities without excess manual intervention.” What’s needed is a more generative AI-based approach that strengthens existing risk-based vulnerability management (RBVM) technologies. AI-based patch management systems can prioritize vulnerabilities by patch type, system and endpoint. Improving risk-based scoring accuracy is why vendors are fast-tracking generative AI improvements. Leading AI-based patch management systems interpret vulnerability assessment telemetry and prioritize risks by patch type, system and endpoint.
The GigaOm Radar for Patch Management Solutions Report analyzes the patch management landscape and provides insights into every provider’s strengths and weaknesses. Vendors included in the report are Atera, Automox, BMC Client Management Patch powered by Ivanti, Canonical, ConnectWise, Flexera, GFI, ITarian, Ivanti, Jamf, Kaseya, ManageEngine, N-able, NinjaOne, SecPod, SysWard, Syxsense and Tanium.
Ivanti’s Mukkamala also told VentureBeat that he envisions patch management becoming more automated, with AI copilots providing greater contextual intelligence and prediction accuracy. “With more than 160,000 vulnerabilities currently identified, it is no wonder that IT and security professionals overwhelmingly find patching overly complex and time-consuming. This is why organizations must utilize AI solutions … to assist teams in prioritizing, validating and applying patches.
“The future of security is offloading mundane and repetitive tasks suited for a machine to AI copilots so that IT and security teams can focus on strategic initiatives for the business.” 5.
Managing the use of generative AI tools, including AI-based chatbot services High on the priority list of CIOs and CISOs who regularly brief their boards on generative AI is the need for tools to manage and monitor models and chatbot services.
Airgap Networks , CrowdStrike , Cyberhaven , Microsoft Security Copilot , SentinelOne and Zscaler have announced they have tools available. Look for more cybersecurity vendors to create and fine-tune private LLMs that will need tools for fine-tuning and improving the accuracy and precision of model results. An example is how Zscaler focuses on prompt engineering today, as it previewed at its recent Zenith Live 2023 event.
The double-edged sword of generative AI in cybersecurity Interviews VentureBeat conducted with Zscaler’s senior management team and with customers including CIOs and CISOs at Zenith Live 2023 all point to a paradox they are facing: How can generative AI deliver exceptional productivity while risking the release of intellectual property and confidential company information into public models like OpenAI’s? The Zscaler team went after this issue early in their keynotes, with Syam Nair, chief technology officer, taking the lead on the topic.
Nair reassured the customers in the audience that bolstering its ZTX platform and relying on its LLMs, combined with the core of zero trust designed into the platform, was how the company plans on securing customers’ data and privacy. Nair explained to the audience how they could better ensure their data’s security: “This is where zero trust and the need for zero trust for AI applications comes into being.” Designing in zero trust, starting with identity, was a common theme at Zscaler Live 360. Zscaler is focused on capitalizing on its own LLMs’ real-time insights and versatility to strengthen zero trust across its platform.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Quantum leap: How quantum sensors are revolutionizing robotics | VentureBeat"
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"https://venturebeat.com/data-infrastructure/quantum-leap-how-quantum-sensors-are-revolutionizing-robotics"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Quantum leap: How quantum sensors are revolutionizing robotics Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The recent Ant-Man movie did a great job of putting quantum up in lights, but the future of quantum science shines even brighter than fiction. One application, quantum sensors, is already the basis of some of the most important systems and technologies in our world — global positioning systems (GPS) and magnetic resonance imaging (MRI) scanners are prime examples.
Quantum sensors and quantum AI are just the beginning: Robots are now getting the quantum sensor treatment too. Quantum sensors will supercharge the way robots work and how we apply them to important 21st-century challenges.
Why quantum sensors are a big deal Modern technology is full of sensors that measure heat, light, movement, pressure or other aspects of the physical environment. Quantum sensors add something new. They use the quantum properties of how particles behave at atomic scale to detect tiny movements or changes in gravitational, electric or magnetic fields.
Because they work at such a small scale, quantum sensors can measure light or other observable phenomena extremely accurately. It also means they can provide a highly precise and stable measurement, as they measure properties like the structure of atoms or spins of atomic particles, which never change.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! This accuracy and reliability make quantum sensors potentially very useful. By detecting important frequencies and tracking the interaction between the heart and brain or the spinal cord and brain, they could make the technology for scanning the human body more robust than today’s MRIs. Governments around the world are interested in quantum sensing for these benefits as well: Imagine being able to detect current stealth machinery or communicate without the need for a satellite.
Challenges of noisy data It’s important to mention, though, that sometimes being so precise and sensitive can be less useful. That’s because it results in a lot of noise in the data. Noisy data is a challenge that teams like our EY quantum data science team are tackling by implementing AI to separate insights from the noise.
In fact, combining quantum sensing with other technologies is a strategy with lots of potential. Quantum sensing and robotics is a good example. The tiny size of most quantum sensors, plus their high sensitivity, have already led to their use as tactile sensing elements in fiber optic cables for robotic arms — helping the robot arm to perceive its environment by detecting precise information about pressure, vibration, temperature or texture.
Other potential applications of this powerful combination are also emerging. For example, we are starting to see quantum sensors combined with mobile robots. Information about the environment detected by the sensors, such as small changes in temperature or magnetic fields, can enable the robot to make more precise movements and decisions, as well as gather valuable data for other purposes.
Mobile robots make great quantum sensor transporters We tested this ourselves by attaching a quantum sensor to Spot, a quadruped robot designed to move around and collect data. The quantum sensor we tested is designed to measure the type of light that influences plant growth, called photosynthetically active radiation (PAR). More precisely, the sensor measures the number of photosynthetically active photons at a particular location at a point in time to see how much PAR a plant in that location would receive.
Because the sensor is robust and reliable in environments like artificially lit greenhouses both underwater and underground, attaching it to mobile robots like Spot has valuable potential in agriculture, where monitoring and managing light is vital. It could also help model emerging large-scale bio-ecosystems, such as plantations in the desert or underground farms, to help use them address global food security.
We are already seeing pioneering research in this area, such as a Qatari project studying optimal growing strategies for very light-sensitive greenhouse plants like tomatoes, a project feeding into the country’s food security focus on locally grown rather than imported produce.
Great potential in pairing quantum sensors with mobile robots For a simple proof of concept, we attached our sensor to Spot with a standard GoPro mount and programmed the robot to move around our office garden so the sensor could take light measurements. Our first finding was that wintertime in Denmark is “not optimal” for our plants, unfortunately! Our second was to see first-hand why pairing quantum sensors with mobile robots has such potential. We saw particular value in the ability to program Spot to take regular measurements around the garden over time.
Beyond agricultural uses for robot-mounted PAR sensors like Spot’s, robots with quantum gravity sensors could transform our ability to map underground structures. By measuring differences in gravitational fields more precisely, these sensors could help reduce construction risks through more accurate mapping of tunnels, caves or sinkholes, as well as helping environmental scientists to model and predict patterns of magma flow or groundwater levels to manage eruption and flood risks.
Robots are also in line for a quantum sensor upgrade Getting quantum sensors into and around challenging environments isn’t the only benefit of the robot-quantum sensor pairing. Quantum sensors could also help robots navigate better. It’s critical for autonomous robots like Spot or self-driving cars to be able to navigate safely and accurately.
Here, too, quantum sensors look set to play a part. In December 2020, the SPIDAR project received UK government funding to develop quantum-based LiDAR systems for autonomous vehicles. By detecting single photons emitted by an object and using this to measure the detected object’s distance, SPIDAR will be able to sense how close an object is to a vehicle with far greater precision than existing 3D camera systems.
Compared to current LiDAR systems that measure laser beam travel time to and from objects with accuracy to the range of 100 milliseconds, quantum LiDAR like SPIDAR will measure photon travel time to the trillionths of a second. They will also be able to detect objects through fog or potentially around corners, which current LiDAR cannot do.
The quantum LiDAR upgrade certainly sounds like a positive move towards autonomous vehicles we can feel safe being in or alongside.
Away from every day road users, quantum sensors will also help robots like drones and autonomous military vehicles navigate in environments where GPS systems either don’t work or could be an exploitable weakness. These non-GPS PNT systems often use cold trapped ion quantum sensors that measure tiny changes in gravity and atomic acceleration. As the technology gets smaller and more rugged, experts believe these systems will have significant potential in commercial and defense industries.
The quantum and robot pairing doesn’t stop with sensors Our whistlestop tour of quantum sensors and robotics shows how much opportunity this combination will offer as the technology continues to develop. But what makes the quantum and robotics pairing even more exciting is its broader potential, particularly when you add AI into the mix.
AI technologies like computer vision and machine learning (ML) are vital to how autonomous mobile robots perceive and avoid obstacles and plan their activities within a particular environment. But making AI processors small and light enough to integrate within smaller robots is a big technical challenge. That’s because processes like machine vision require huge amounts of computing resources.
Experts believe quantum computing could overcome this challenge by running algorithms much faster, dramatically reducing the processing power required. Doing so could open up many more opportunities to take advantage of mobile robots.
This is just one example of quantum AI applied to robotics — others, such as quantum ML’s potential to help robots learn faster , are also being explored, and no doubt other fruitful pairings will follow.
All in all, it’s clear to us that quantum robotics is a dynamic field that innovators, scientists and governments are keen to expand. We are confident that quantum sensors and quantum AI are just the beginning. We will be watching closely as quantum robots take ever-bigger steps toward realizing their potential. As they do, they will join the raft of quantum applications taking quantum science well beyond the realms of fiction.
Jeff Wong is global chief innovation officer at EY.
Kristin Gilkes is global innovation quantum leader at EY.
The views reflected in this article are the views of the authors and do not necessarily reflect the views of the global EY organization or its member firms.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
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You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"ServiceNow partners with Nvidia and Accenture on 'AI Lighthouse' for rapid enterprise AI adoption | VentureBeat"
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"https://venturebeat.com/ai/servicenow-partners-with-nvidia-and-accenture-on-ai-lighthouse-for-rapid-enterprise-ai-adoption"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages ServiceNow partners with Nvidia and Accenture on ‘AI Lighthouse’ for rapid enterprise AI adoption Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Lighthouses are one of humanity’s most enchanting inventions — although they’ve been obsoleted as important seafaring navigation guides by boats equipped with global positioning system (GPS) receivers — remaining lighthouses still attract tourists, history buffs, photographers and other people seeking to connect with the past.
AI Lighthouse, on the other hand, seeks to illuminate the future for enterprises. The new software and consulting service offering unveiled today by low-code enterprise automation giant ServiceNow, in conjunction with partners Nvidia and Accenture, is designed to allow ServiceNow customers to quickly and securely adopt new generative AI tools — so they don’t get swept out to sea amid the wave of new products, services and investments.
The three partners each claim to offer a different benefit to customers who adopt AI Lighthouse: the ServiceNow enterprise automation platform and engine, Nvidia’s AI supercomputing and software and Accenture’s consulting and deployment services.
By combining these capabilities, the program aims to empower customers to collaborate as design partners in building and deploying custom gen AI large language models (LLMs) and applications to advance their business goals.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Moving at light(house) speed Essentially, the three partners are positioning the new AI Lighthouse program as a way for customer companies to get going with their own gen AI applications and sees meaningful results, fast, without having to go through a long, drawn-out assessment and procurement process. “Let us handle it,” is the prevailing message from the materials released about the program today.
“In collaboration with our visionary partners, ServiceNow, NVIDIA and Accenture are forming the market-leading blueprint for AI-first enterprise innovation,” ServiceNow Chairman and CEO Bill McDermott said in a press release. “We expect the AI Lighthouse customer program to inspire breakthrough ideas with massive ROI: ‘Return on Intelligence.’” Jensen Huang, founder and CEO of Nvidia, emphasized the demand for gen AI tools across industries, stating in the same release: “Industries are racing to add gen AI tools to their operations at a faster pace than in any previous technology shift. Nvidia, ServiceNow and Accenture are partnering to help customers lead their industries by deploying gen AI tools that harness their own invaluable knowledge to transform the applications they use every day.” Tools of the trade ServiceNow already offers various AI tools, including its Now Assist for Virtual Agent that uses natural language processing (NLP) to answer user questions 24/7, as well as “NLU Workbench,” a no-code method for creating and deploying new language models for a business, sentiment analysis to see how users feel about a certain product or service, regression that predicts resolution time for customer issues and more.
Meanwhile, Nvidia plugs into the AI Lighthouse program with its DGX AI supercomputers and DGX Cloud platforms and NeMo software, which it says will provide AI Lighthouse users with “full‑stack computing for model training and tuning,” leveraging the $1-trillion tech company ‘s massive technology base to get custom models or fine-tuned models up and running.
Finally, Accenture comes to the table with “design and engineering” services for apps within the ServiceNow platform, and just committed $3 billion of investment money towards AI.
What’s in the AI Lighthouse? Altogether, the AI Lighthouse program aims to deliver the following benefits to enterprise customers: Reduce Tedious Manual Work: The program intends to provide customer service professionals with overviews and insights that will help them solve problems faster, thereby reducing tedious manual work.
Promote Self-Service: AI Lighthouse seeks to deflect cases by empowering users — either internal employees or external customers — with self-service options and delivering engaging experiences through natural human language interactions.
Generate Content Automatically: The program will enable the automatic generation of content, including full “knowledge base” articles, essentially explainers on a topic or technology solution.
Increase Developer Productivity: AI Lighthouse aims to offer developers its own coding recommendations, putting it in line with Github Copilot X.
No pricing details for AI Lighthouse have yet been released publicly. We’ll update with more information when we receive it.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Fiverr launches Business Solutions and Neo AI matching algorithm | VentureBeat"
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"https://venturebeat.com/ai/fiverr-launches-business-solutions-and-neo-ai-matching-algorithm"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Fiverr launches Business Solutions and Neo AI matching algorithm Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Of all the businesses threatened by generative AI , you might conclude that Fiverr is among those in the crosshairs. The Israeli tech startup has become synonymous with its online marketplace of creative freelancers since launching in 2010, including artists, designers, videographers and more. But if more people are using gen AI tools to create content, shouldn’t that reduce the demand for the freelancers on Fiverr? Actually, Fiverr sees the moment as a tremendous opportunity. Earlier this year, VentureBeat reported how the company experienced a 1,400% increase in searches for professionals with AI-related skills on its marketplace. And today, Fiverr is announcing the launch of two new services — Fiverr Business Solutions and Fiverr Neo, both of which it hopes will leverage the sudden boom of interest in AI to further cement Fiverr’s place as the first stop when businesses need help with their creative projects.
Business time Fiverr Business Solutions is the new umbrella name for Fiverr’s existing offerings for mid-sized to large enterprise companies. It includes Fiverr Enterprise , “a SaaS platform which helps companies source, onboard, manage and pay your freelance talent legally and compliantly,” and which Fiverr acquired and rebranded from Stoke Talent.
Also in the lineup is “ Fiverr Certified ,” a service that launched in late June which allows software vendor companies to “identify, certify and promote” experts who are best equipped to help clients use their technology. Among the companies who are certifying experts in their products and services through Fiverr Certified are Amazon (specifically its Ads division), Monday.com and Stripe.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Finally, Fiverr Business Solutions also grants customers access to Fiverr Pro , the more premium offering of Fiverr that initially launched in 2017 , and is where freelancers on the platform have been “hand-vetted and carefully curated” by Fiverr itself. Fiverr Pro has been redesigned for “larger customers with more complex projects,” according to an email sent from Fiverr CEO Micha Kaufman to VentureBeat.
Pro also contains Fiverr’s Project Planning services, in which a Fiverr-trained human expert joins a customer’s project and helps manage it all the way through from inception to deliverables and payment. It features a new dashboard and has been upgraded with new payment options such as NetTerms.
The one for your company’s creative projects? But perhaps most important among the announcements today is Fiverr Neo, a new matching service that Fiverr says will allow its customers to find the right professional for their specific project needs rapidly, and more accurately than ever before.
Fiverr Neo does this by engaging the customer through a new hybrid chatbot/multiple choice interface that delivers human-like questions and responses and takes into account the customer’s specific project attributes and skills needed to deliver on it.
Fiverr Neo is powered by gen AI, specifically the kind of large language models (LLMs) that are in vogue everywhere these days thanks to the likes of OpenAI’s ChatGPT , Anthropic’s Claude 2 , Meta’s LLaMA 2 , and Google’s Bard , to name a few.
A Fiverr spokesperson told VentureBeat via email that Fiverr Neo is using a “combination of in-house and 3rd party LLMs,” but did not go into specific details about which ones. However, a demo video on Fiverr’s website shows an icon with two four-pointed stars which looks nearly identical to the one used by Google Bard, and the interfaces are also very similar.
While Fiverr’s entire business model was based in some ways on search, “Neo is very different,” Kaufman said in an email to VentureBeat.
“It works with you to understand your requirements and preferences, then provides a very personalized and accurate matching experience,” Kaufman elaborated. “This can be particularly helpful for more complex projects that require multiple skills and expertise. Think of Neo as an expert with the depth of knowledge that makes it possible to pick a very specific selection of freelancers with the most relevant expertise, experience and availability to best meet the customer’s needs. It offers the customer the right amount of guidance, selection and control. It is a game changer in how talent matching is being done today.” Describing Neo with words only goes so far. Watching the video of it in action is in some ways much more illustrative and helpful, as it shows the user experience: A user clicks on the “Talk to Fiverr Neo” button, which begins a new chat window. Neo asks what the user needs help with, and then the user enters their need as a natural language prompt in the chat box.
Neo asks the user “what kind of vibe are you looking for?” and provides a number of suggested words to choose from. Neo surfaces the applicable freelance talent as miniature informational blurbs — similar to the Knowledge Panels on Google — along with their review average out of five stars and brief descriptions of their services and qualifications, and includes a button for the user to send them the project brief.
Then, once the freelancer accepts the assignment and turns it in — in the case of the example video, a screenplay or script — Neo continues the conversation and asks the user what kind of visual style they want it filmed or created in, again providing visual examples and descriptions.
Clearly, the goal is for Neo to help Fiverr customers move throughout their entire search and assignment process more smoothly, with an ever-present, AI assistant helping them out every step of the way.
Neo is available now for free on a wait-list basis in all regions where Fiverr does business. Users can sign up here.
With the launch of Fiverr Business Solutions and Fiverr Neo, the company seeks to futureproof its operations for the gen AI era, harnessing this category of technology to further improve its own services, while still maintaining its role as the predominant marketplace for trustworthy freelance human talent.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Acelab raises $5.3M to transform architecture with ML search | VentureBeat"
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"https://venturebeat.com/ai/acelab-raises-5-3m-to-transform-architecture-with-ml-powered-building-supplies-search"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Revolutionizing architecture: Acelab raises $5.3M to fuel supply search innovation Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
You’d be forgiven for thinking of architecture as a high-tech industry. Oh sure, there have been numerous advances to the age-old practice of designing buildings, especially since the advent of the personal computer, and longstanding computer-assisted design (CAD) software programs like Autodesk ‘s Revit and Graphisoft’s ArchiCAD make it far easier for architects to draft building blueprints, designs, floorplans, etc., including 3D models that the user can “walk through.” But one area of architecture has remained frustratingly old school: searching for the actual supplies needed, such as windows, doors, roofing, and insulation — as they are typically dispersed across the websites and paper media of many different manufacturers. Thankfully, that is changing fast, according to Vardhan Mehta, a Harvard Master’s-educated architect turned founder and CEO of the startup Acelab , which is today announcing a new $5.3 million funding round to continue building out its intelligent building supplies search platform for his fellow architects.
“With building products being in the hundreds of thousands, it’s simply impossible for any architect or contractor to know about all of them,” Mehta wrote to VentureBeat in an email. “But every construction project is atypical in nature – due to code requirements, budget constraints, project location or client needs. Acelab machine learning (ML) -powered search engine is the brain of the platform. It gathers all relevant info from the architect, collates it with our proprietary database, and returns the strongest fits through an easy-to-use interface.” The new funding round was led by Pillar VC, PJC and Draper Associates and joined by Alpaca, Steve Kaufer (Founder and former CEO of TripAdvisor), Erik Jarnryd (Former CEO of Harvey Building Products), Transcend Partners, Branagh Construction, Ken Lang, Klingenstein Fields and Westview PE Fund.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Architects turned ‘hackers’: the origins of Acelab “When I started working in architecture in 2017, I was surprised at how professional architects were still having to look through hundreds of manufacturers’ websites and brochures, and manually adding data on products to spreadsheets — they were kind of hacking their way through the problem,” Vardhan told VentureBeat in an exclusive video call interview.
Frustrated by this reality, Mehta and some of his fellow Harvard Master’s architecture students founded Acelab 2019 to provide a better solution. Together, they manually researched more than 39,000 products from hundreds of manufacturer websites and catalogs and combined them into a structured database. They further added 100,000 spec sheets from past architecture projects. Then, they worked with software engineers to develop their own machine learning (ML) search and recommendation engine, and provided a system for users to save, organize and share their building products search results.
The result is Acelab’s three-tiered platform, which is currently used by more than 8,000 architecture firms, and offers the following features: ProductAdvisor , a proprietary, ML algorithmic search engine that includes building products from every major manufacturer in the U.S. and includes searchable attributes such as relative cost, sustainability, aesthetics and more Project Workspace , a place where the architects and architecture firms who use Acelab Project can create lists of products for each project they are working on it and share it with colleagues, clients, building contractors, supplies manufacturers and other collaborators.
a Collaboration Portal that connects a full-time Acelab product expert or a manufacturer’s specialist with the architects to provide more in-depth information on product availability and costs. Users can “instantly request quotes from suppliers, and share recommendations among multiple stakeholders,” Mehta said.
But Acelab goes further than just functioning as a “Google for architects.” Acelab’s ProductAdvisor generates product recommendations based on its learnings from other users on the platform — highlighting those products that they most often selected and added to their Workspaces, depending on their architecture project requirements.
“We often play the role of influencer,” Mehta said. “We guide the customer to which products and supplies to use.” While users can’t order products directly from the platform itself (yet), they are only a click away from the manufacturers’ websites.
Acelab also employs a “data team” that manually canvasses building manufacturer websites and updates the product information on Acelab accordingly, though Mehta said the company has begun to automate some of this functionality.
“Typically, manufacturers revise their product lines every year or two,” Mehta said. “We do a manual refresh every 4-6 months.” Mehta said that while the platform was built to reduce hours and hours of research time for architects, allowing them to focus on actually designing and communicating with their clients and manufacturers, the manufacturers he had spoken to were similarly enthralled by it.
“In the last four years, I’ve probably interviewed 450 manufacturers,” Mehta said. “A big challenge has been, for them, they traditionally relied on trade shows and catalogs to get the word out about their products, which didn’t always result in a successful connection if the architect didn’t need them at that moment. But with Acelab, we are able to make the connection between the manufacturers and the architects exactly when the architects are seeking them out.” Acelab supports both residential construction, namely, homes and multifamily dwellings, and commercial construction products (offices, retail, hotels and convention centers).
Acelab’s blueprint for continued success Newly flush with investment, Acelab has big plans to continue evolving its platform and add more helpful features for architects.
One big ticket item on the product roadmap: procurement, allowing users to buy products directly, which Mehta says is coming in the next 12-18 months.
The company further intends to add “historic price codes of manufacturers as reported by users” to its product search results, according to Mehta, allowing users to see more precisely the cost of each item, rather than the current relative pricing indicator (between one and four dollar signs, signifying increasing cost).
Acelab is also looking at adding a new generative AI feature that would automatically create specification documents for an architecture project with all the relevant product information already included, so an architect wouldn’t have to add them all one by one. Once an architect reviews the gen AI-created spec sheets for accuracy and additional information, they could then turn it over to the building contractors and client.
“Architects are facing enormous pressure to find the right products due to higher interest rates, supply chain delays, and labor shortages,” Mehta concluded. “Acelab helps the entire construction ecosystem find the products they need, so they can deliver projects on budget and on time.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Netflix's AI legacy lives on: Outerbounds applies streaming giant's lessons to enterprise AI | VentureBeat"
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"https://venturebeat.com/ai/netflixs-ai-legacy-lives-on-outerbounds-applies-streaming-giants-lessons-to-enterprise-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Netflix’s AI legacy lives on: Outerbounds applies streaming giant’s lessons to enterprise AI Share on Facebook Share on X Share on LinkedIn Outerbounds , a machine learning infrastructure startup, today announced new product capabilities to help enterprises prepare for and adopt generative AI models like ChatGPT.
The company’s cofounders, CEO Ville Tuulos and CTO Savin Goyal, both former Netflix data scientists , aim to position Outerbounds as a leading provider of ML infrastructure as businesses increasingly look to leverage large language models (LLMs).
The new features added to the platform include GPU compute for generative AI use cases, bank-grade security and compliance, and workstation support for data scientists. These features aim to help customers ship data, ML, and AI projects faster, while retaining control over their data and models.
Tuulos explained the rationale of the new features in a recent interview with VentureBeat, stating, “The adoption of generative AI and LLMs should not be a quick fix or a gimmick. It should be tailored to enhance a company’s products in meaningful ways.” “Although AI is new and shiny and exciting today, in the long term AI isn’t an excuse to provide a subpar product experience,” he added. “The best companies will learn how to adapt and customize AI techniques to support their products in specific ways, not just as an easy chat add-on.” Leveraging its Netflix roots Since the startup launched in 2021, Outerbounds has been instrumental in the success of several businesses such as Trade Republic , Convoy and Wadhwani AI.
Notably, Trade Republic deployed a new ML-powered feature in just six weeks, leading to a direct uplift in product metrics, thanks to Outerbounds.
Outerbounds is built on Metaflow , an open-source framework that the founders of Outerbounds created at Netflix in 2019. Metaflow is currently used by hundreds of leading ML and data science organizations across industries, such as Netflix, Zillow, 23andMe, CNN Media Group and Dyson.
Tuulos said that Outerbounds has added a unique approach to MLOps and managing the ML lifecycle, one focused on the user experience rather than technical capabilities.
“Ever since the beginning, we have focused on the user experience,” Tuulos said. “Since the field is so new, many other solutions have focused on technical capabilities, with the UX as an afterthought. We have always believed that the technology will mature, and as always, ultimately it is the best user experience that wins.” Seamless integration and bank-grade security Despite the complexities of AI and ML , Outerbounds has been able to use its experience to navigate the immature and chaotic landscape. “Having a solid foundation for any AI project is critical,” said Tuulos, highlighting the need for data, compute, orchestration and versioning in any AI project.
Outerbounds cofounder and CTO, Savin Goyal, echoed Tuulos’s sentiments on the importance of building a solid AI foundation. He said, “ML and AI should meet the same security standards as all other infrastructure, if not more.” “We follow a cloud-prem deployment model,” Goyal added. “Everything runs on the customer’s cloud account with their own security policies and governance. We integrate with Snowflake, Databricks and open-source solutions.” Goyal also said that Outerbounds helps customers address challenges like model governance, transparency and bias that come with deploying generative AI models.
“Our view is that there can’t be — and there shouldn’t be — a single entity dictating what bias means and what is acceptable when it comes to gen AI. Each company should be responsible for these choices based on their understanding of the market — similar to how companies are responsible for their behavior today even without gen AI,” he said. “We give companies tools so they can customize and fine-tune gen AI to their own needs.” Human-centric approach to ML operations Outerbounds stands out in a crowded market with a unique approach to ML operations. “We are building a human-centric infrastructure that makes data scientists and data developers as productive as possible,” said Tuulos.
With the feature update, Outerbounds aims to solve the problem of data access, which Goyal sees as a “fundamental bottleneck.” He said, “How much time does it take for an individual to iterate through a variety of different iterations and hypotheses? If you’re spending 20 minutes to access the data that you need, it naturally breaks your flow state.” The features released today further align Outerbounds with its mission to make it easier for companies to adopt ML and AI in more parts of their business. The company envisages a future where AI and ML can be applied everywhere, and these new enhancements are a step towards realizing this vision.
As the field of AI continues to evolve, businesses are grappling with the complexities of implementation and governance. Outerbounds, with its new features, is positioning itself at the forefront of this transformation, offering solutions that are not only technologically sophisticated but also mindful of user experience and governance concerns. With its new offerings, Outerbounds is paving the way for broader and more effective use of AI and ML in the enterprise.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Meta AI Image Decoder recreates mental imagery from brain scans | VentureBeat"
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"https://venturebeat.com/ai/meta-recreates-mental-imagery-from-brain-scans-using-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Meta recreates mental imagery from brain scans using AI Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The computing interfaces of the not-too-distant future might move beyond touchscreens and keyboards — even past eyes and hand gestures, to the inside of our own minds.
Society is not quite there yet, but we are moving closer. Researchers at Meta Platforms, Inc., parent of Facebook, Instagram, WhatsApp and Oculus VR, today announced Image Decoder, a new deep learning application based on Meta’s open source foundation model DINOv2 that translates brain activity into highly accurate images of what the subject is looking at or thinking of nearly in realtime.
In other words, if a Meta researcher was sitting in a room and blocked from viewing the subject, even if the subject was on the other side of the world, the Image Decoder would allow the Meta researcher to see what the subject was looking at or imagining, based on their brain activity — provided the subject was at a neuroimaging facility and undergoing scanning from an MEG machine.
The researchers, who work at the Facebook Artificial Intelligence Research lab (FAIR) and PSL University in Paris, describe their work and the Image Decoder system in more detail in a new paper.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! In notes provided over email to VentureBeat by a spokesperson, Meta wrote that “his research strengthens Meta’s long-term research initiative to understand the foundations of human intelligence, identify its similarities as well as differences compared to current machine learning algorithms, and ultimately help to build AI systems with the potential to learn and reason like humans.
” How Meta’s Image Decoder works In their paper, Meta’s researchers describe the technology underpinning Image Decoder.
It is essentially combining two, hitherto, largely disparate fields: machine learning —specifically deep learning , wherein a computer learns by analyzing labeled data and then inspecting new data and attempting to correctly label it — and magnetoencephalogphy (MEG), a system that measures and records brain activity non-invasively, outside the head, using instruments that pick up on the tiny changes in the brain’s magnetic fields as a person thinks.
Meta Researchers trained a deep learning algorithm on 63,000 prior MEG results from four patients (two women and two mean with the mean age of 23) across 12 sessions, in which the patients saw 22,448 unique images, and 200 repeated images from that original pool.
The Meta team used DINOv2 , a self-supervised learning model designed to train other models and which was itself trained on scenery from forests of North America, and which Meta released publicly in April 2023.
The researchers instructed the Image Decoder algorithm to look at both this raw data and an image of what the person was actually seeing when their brain was producing that MEG activity.
In this way, by comparing the MEG data to the actual source image, the algorithm learned to decipher what specific shapes and colors were represented in the brain and how.
Promising results and ethical considerations While the Image Decoder system is far from perfect, the researchers were encouraged by the results, as it attained accuracy levels of 70% in its highest performing cases in terms of accurately retrieving or recreating an image based on the MEG data, seven times better than existing methods.
Some of the imagery that the Image Decoder successfully retrieved from a pool of potential images included pictures of broccoli, caterpillars, and audio speaker cabinets. It was less successful at decoding more complex and varied imagery, including tacos, guacamole, and beans.
“Overall, our findings outline a promising avenue for real-time decoding of visual representations in the lab and in the clinic,” the researchers write.
However, they noted that the technology poses “several ethical considerations,” as being able to look inside a person’s mind is a new level of invasiveness that technology has not yet attained on a large scale.
“Most notably,” among the ethical considerations the researchers put forth is “the necessity to preserve mental privacy,” though they don’t state exactly how this would be achieved.
The fact that this work is funded by a parent company that has already been fined billions for violating consumer privacy with its products is also a notable concern, though the researchers don’t directly address this elephant in the room.
But there are technological limitations that would prevent this technique from, for now, being used to read a person’s thoughts without their consent. Namely, the Image Decoder works best on concrete imagery of physical objects and sights a person has seen.
“By contrast, decoding accuracy considerably diminishes when individuals are tasked to imagine representations,” the researchers note.
In addition, “decoding performance seems to be severely compromised when participants are engaged in disruptive tasks, such 9 as counting backward (Tang et al., 2023). In other words, the subjects’ consent is not only a legal but also and primarily a technical requirement for brain decoding.” So, a person who was subjected to an Image Decoding of their brain activity without their consent could take it upon themselves to stop it by resorting to a technique such as counting backward — if they were aware of that option and the circumstances they were in.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Marvel criticized for AI use in 'Secret Invasion' opening credits | VentureBeat"
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"https://venturebeat.com/ai/marvel-criticized-for-using-ai-to-make-secret-invasion-opening-credits"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Marvel criticized for using AI to make ‘Secret Invasion’ opening credits Share on Facebook Share on X Share on LinkedIn Credit: Marvel/Disney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Marvel Studios has been a global entertainment juggernaut for the last 15 years, turning beloved but sometimes obscure comic book franchises into massive successes in film and TV.
But its latest TV series, Secret Invasion , debuting on the Disney+ streaming service and starring Samuel L. Jackson in his iconic role as former S.H.I.E.L.D director Nick Fury , has been met with an immediate backlash upon its premiere today, June 21, 2023 — over the use of AI to generate the imagery of the title cards in the opening sequence of each episode.
“Very disappointed that Marvel Studios decided to use AI for the opening credits of Secret Invasion,” tweeted a photographer with the handle “@HairyShortStack,” including screenshots of the title sequence showing a variety of eerie, green-tinged images of city skylines, explosions and deformed human figures resembling Nick Fury.
Very disappointed that Marvel Studios decided to use AI for the opening credits of Secret Invasion.
https://t.co/uojLB4TdOl pic.twitter.com/iSgA7qm4o7 Other Twitter users called the opening credits “ugly,” “disgusting” and “repulsive,” lamented the company’s treatment of human visual effects (VFX) artists and concluded that Marvel had chosen to use AI in this case to replace human artists.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! It’s so obvious now looking back that Marvel’s solution to their horrific treatment of VFX artists and subsequent bad results on screen, was going to be cutting them out all together where possible and shamefully replacing them with this ugly AI shit.
Horrifically predictable.
pic.twitter.com/e5SHR6Q5Ch Doesn’t surprise me in the least that Marvel would replace artists by typing “Samuel L. Jackson green alien dogshit” into an AI prompt. Just stunned by how hideous and repulsive this is.
https://t.co/X1EoEXs4GK This is the new #SecretInvasion title sequence… Big studios are taking a clear stance on AI issues for artists by using exploitative and morally very questionable AI tools for their current productions.
It is disgusting. ?1/ pic.twitter.com/m4O1RnP09s Even a former Marvel concept artist who claimed to have worked on the series itself, Jeff Simpson, joined in the dogpile, tweeting “Secret Invasion intro is AI generated. I’m devastated, I believe AI to be unethical, dangerous and designed solely to eliminate artists careers. Spent almost half a year working on this show and had a fantastic experience working with the most amazing people I ever met…” Secret Invasion intro is AI generated. I’m devastated, I believe AI to be unethical, dangerous and designed solely to eliminate artists careers. Spent almost half a year working on this show and had a fantastic experience working with the most amazing people I ever met… Human artists from Method Studios credited However, at least one Twitter user countered these objections by noting that Method Studios , a VFX and motion graphics subdivision of Company 3 , had been credited in the end credits as the creators of the Secret Invasion main title sequence, and that real human artists’ names were listed among the team that worked on the sequence.
Marvel has worked with Method Studios and Company 3 previously on such hit projects as Spider-Man: Far From Home and Avengers: Infinity War.
Method Studios also lists Top Gun: Maverick , Blade Runner 2049 and Elvis among the diverse set of Hollywood films for which it has helped create graphical elements.
In an interview with Polygon , Secret Invasion director and executive producer Ali Selim confirmed that Method Studios used AI to design the opening titles of the series, and stated that AI was chosen as a creative medium because it reflected some of the series’ themes — in which shapeshifting aliens called Skrulls masquerade as human beings, much like how AI can sometimes produce convincing impressions of humanity or human creativity.
Creative justification for using AI “When we reached out to the AI vendors, that was part of it — it just came right out of the shape-shifting, Skrull world identity, you know? Who did this? Who is this?” Selim told Polygon.
Selim did not elaborate on exactly which AI tools Method Studios deployed for this project, and the VFX production firm had not responded to the reporter’s questions at the time of the article’s publication.
VentureBeat also reached out to Marvel Studios and Method Studios and some of the artists credited with the title sequence to get more information on how it was designed and their reaction to the backlash on Twitter, and we will update if and when we hear back.
Strike context The use of AI to create Secret Invasion’s opening credits comes at a particularly fraught time period between major Hollywood studios and the creative community: As of the time of this article’s publication, the Writers Guild of America union representing Hollywood film and TV writers has been on strike for more than seven weeks over disputes about renewed contracts and residual payments in the streaming and AI era, with no immediate resolution in sight. SAG-AFTRA, the union representing film and TV actors, remains in negotiations with the studios over some of the same issues with authorization to strike if a resolution for their guild is not met by June 30 — nine days from now.
Meanwhile, it is worth pointing out that leading creatives within the massive Marvel moviemaking operation believe that it is inevitable AI will disrupt the filmmaking businesses. Joe Russo, co-director of several of Marvel’s most financially successful films including Avengers: Endgame , told the outlet Collider at a panel discussion earlier this year that he believed AI would be able to create a feature film within two years, and that he himself sat on the board of several AI companies.
“The value of it [AI] is the democratization of storytelling,” Russo was quoted as saying. “That’s incredibly valuable. That means that anyone in this room could tell a story, or make a game at scale, with the help of a photoreal engine or an engine and AI tools. That, I think, is what excites me about it most.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"How to navigate your engineering team through the generative AI hype | VentureBeat"
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"https://venturebeat.com/ai/how-to-navigate-your-engineering-team-through-the-generative-ai-hype"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How to navigate your engineering team through the generative AI hype Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In the last six months, AI, specifically generative AI , has been thrust into the mainstream by OpenAI’s launch of ChatGPT and DALL-E to the general public. For the first time, anyone with an internet connection can interact with an AI that feels smart and useful — not just a cool prototype that’s interesting.
With this elevation of AI from sci-fi toy to real-life tool has come a mixture of widely-publicized concerns (do we need to pause AI experiments ?) and excitement (four-day work week!). Behind closed doors, software companies are scrambling to get AI into their products, and engineering leaders already feel the pressure of higher expectations from the boardroom and customers.
As an engineering leader, you’ll need to prepare for the increasing demands placed on your team and make the most of the new technological advancements to outrun your competition. Following the strategies outlined below will set you and your team up for success.
Channel ideas into realistic projects Generative AI is nearing the Peak of Inflated Expectations in Gartner’s Hype Cycle.
Ideas are starting to flow. Your peers and the board will come to you with new projects they see as opportunities to ride the AI wave.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Whenever people think big about what’s possible and how technology can enable them, it’s a great thing for engineering! But here comes the hard part. Many ideas coming across your desk will be accompanied by a how , which may not be anchored in reality.
There may be an assumption that you can just plug a model from OpenAI into your application and, presto, high-quality automation. However, if you peel back the how and extract the what of the idea, you might discover realistic projects with strong stakeholder support. Skeptics who previously doubted automation was attainable for some tasks may now be willing to consider new possibilities, regardless of the underlying tool you choose to use.
Opportunities and challenges of generative AI The new-fangled AI capturing the headlines is really good at quickly generating text, code and images. For some applications, the potential time savings to humans is huge. Yet, it also has some serious weaknesses compared to existing technologies. Considering ChatGPT as an example: ChatGPT has no concept of “confidence level.” It doesn’t provide a way to differentiate between when there is a lot of evidence backing up its statements versus when it’s making a best guess from word associations. If that best guess is factually wrong, it still sounds surprisingly realistic, making ChatGPTs mistakes even more dangerous.
ChatGPT doesn’t have access to “live” information. It can’t even tell you anything about the past several months.
ChatGPT is ignorant of domain-specific terminology and concepts that aren’t publicly available for it to scrape from the web. It might associate your internal company project names and acronyms with unrelated concepts from obscure corners of the internet.
But technology has answers: Bayesian machine learning (ML) models (and plenty of classical statistics tools) include confidence bounds for reasoning about the likelihood of errors.
Modern streaming architectures allow data to be processed with very low latency, whether for updating information retrieval systems or machine learning models.
GPT models (and other pre-trained models from sources like HuggingFace ) can be “fine-tuned” with domain-specific examples. This can dramatically improve results, but it also takes time and effort to curate a meaningful dataset for tuning.
As an engineering leader, you know your business and how to extract requirements from your stakeholders. What you need next, if you don’t already have it, is confidence in evaluating which tool is a good fit for those requirements. ML tools, which include a range of techniques from simple regression models to the large language models (LLMs) behind the latest “AI” buzz, now need to be options in that toolbox you feel confident evaluating.
Evaluating potential machine learning projects Not every engineering organization needs a team dedicated to ML or data science. But before long, every engineering organization will need someone who can cut through the buzz and articulate what ML can and cannot do for their business. That judgment comes from experience working on successful and failed data projects. If you can’t name this person on your team, I suggest you find them! In the interim, as you talk to stakeholders and set expectations for their dream projects, go through this checklist: Has a simpler approach, like a rules-based algorithm, already been tried for this problem? What specifically did that simpler approach not achieve that ML might? It’s tempting to think that a “smart” algorithm will solve a problem better and with less effort than a dozen “if” statements hand-crafted from interviewing a domain expert. That’s almost certainly not the case when considering the overhead of maintaining a learned model in production. When a rules-based approach is intractable or prohibitively expensive, it is time to seriously consider ML.
Can a human provide several specific examples of what a successful ML algorithm would output? If a stakeholder hopes to find some nebulous “insights” or “anomalies” in a data set but can’t give specific examples, that’s a red flag. Any data scientist can discover statistical outliers but don’t expect them to be useful.
Is high-quality data readily available? Garbage-in, garbage-out, as they say. Data hygiene and data architecture projects might be prerequisites to an ML project.
Is there an analogous problem with a documented ML solution? If not, it doesn’t mean ML can’t help, but you should be prepared for a longer research cycle, needing deeper ML expertise on the team and the potential for ultimate failure.
Has ‘good enough’ been precisely defined? For most use cases, an ML model can never be 100% accurate. Without clear guidance to the contrary, an engineering team can easily waste time inching closer to the elusive 100%, with each percentage point of improvement being more time-consuming than the last.
In conclusion Start evaluating any proposal to introduce a new ML model into production with a healthy dose of skepticism, just like you would a proposal to add a new data store to your production stack. Effective gatekeeping will ensure ML becomes a useful tool in your team’s repertoire, not something stakeholders perceive as a boondoggle.
The Hype Cycle’s dreaded Trough of Disillusionment is inevitable. Its depth, though, is controlled by the expectations you set and the value you deliver. Channel new ideas from around your company into realistic projects — with or without AI — and upskill your team so you can quickly recognize and capitalize on the new opportunities advances in ML are creating.
Stephen Kappel is head of data at Code Climate.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"How ChatGPT could replace IT network engineers | VentureBeat"
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"https://venturebeat.com/ai/how-chatgpt-could-replace-it-network-engineers"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest How ChatGPT could replace IT network engineers Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Modern IT networks are complex combinations of firewalls, routers, switches, servers, workstations and other devices. What’s more, nearly all environments are now on-premise/cloud hybrids and are constantly under attack by threat actors. The intrepid souls that design, implement and manage these technical monstrosities are called network engineers, and I am one.
Although other passions have taken me from that world into another as a start-up founder, a constant stream of breathless predictions of a world without the need for humans in the age of AI prompted me to investigate, at least cursorily, whether ChatGPT could be used an effective tool to either assist or eventually replace those like me.
Here’s what I found out.
I started by getting the opinion of the best source I could think of about how ChatGPT could add value to network engineers: ChatGPT. It didn’t disappoint and generated a list of three areas it determined it could help: VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Configuration management Troubleshooting Documentation I then developed a set of prompts — admittedly not optimized — to determine whether or not the tool could, in fact, be an asset to network engineers in one or more of these areas.
Configuration management To test ChatGPT’s ability to add value in configuration management, I submitted the following prompts: Can you generate a complete example configuration for a Cisco router with the purpose of starting an internet exchange from scratch? What about Juniper? Can you create a Jinja template for each vendor? The ChatGPT results are extensive, so space — and my respect for the boredom limits of those reading this — limits an exhaustive reproduction of them here, but I have posted the complete transcript of all of the ChatGPT prompts and results on GitHub for those searching for a non-pharmaceutical substitute for Ambien.
So, in the case of configuration management, ChatGPT performed fairly well on basic configuration tasks, and I concluded that it is aware of vendor-specific syntax and can generate configurations. However, the configurations generated by the system should be carefully inspected for accuracy. The generic prompts I tested would be akin to building a quick lab, a task most young networking engineers find tiresome at a minimum and clearly a chore that can be handled by the technology (with, again, some human oversight).
Troubleshooting To test ChatGPT’s prowess at troubleshooting network engineering challenges, I turned to Reddit, and specifically the /r/networking subreddit to find real-world questions posed by network engineers to their peers. I pulled a few questions from the thread and proposed them to ChatGPT without optimizing the prompt, and the chatbot handled the easier questions well, while it struggled with the more difficult challenges.
Notably, I specifically asked a question that required knowledge of STP, or the Spanning Tree Protocol, a switch capability responsible for identifying redundant links that could result in unwanted loops. Frankly, my opinion is that ChatGPT understands STP better than many networking professionals I’ve interviewed over the years.
At present, ChatGPT can’t replace experienced networking professionals for even slightly complex issues, but it wouldn’t be alarmist to suggest that it might result in the obsolescence of many subreddits and Stack Overflow threads in the coming years.
Automating documentation This was the area of highest deficiency for ChatGPT. The chatbot initially assured me that it could generate networking diagrams. Knowing it is a text-based tool, I was obviously skeptical, a prejudice that was confirmed when I asked it to generate a diagram and it explained to me that it doesn’t have graphical capability.
Further prompting for network documentation led to the realization — confirmed by ChatGPT — that I needed to provide a detailed network description for it to provide a network description, clearly not a value add. Thus, in the case of automating documentation, the chatbot not only failed, but was guilty of generating lies and deception (so perhaps it’s closer to demonstrating human characteristics than we think). In fairness to AI in general, there are AI applications capable of generating images, and it’s very possible one of those may be capable of producing a usable network diagram.
I then asked ChatGPT if it could generate a network description based on a router configuration file, and it provided a decent summary of what’s configured until it apparently reached the limits of its computational commitment to my prompt, a limit likely implemented by its designers. It is, after all, a free tool, and resources are expensive, especially for an organization burning meaningful cash these days.
Conclusions A few of the challenges I encountered in my brief experiment when using ChatGPT for network engineering include: Ensuring accuracy and consistency Handling edge cases and exceptions Integration with existing systems and processes My guess is these issues are not unique either to ChatGPT or AI applications generally, and some cursory research may explain why. Cornell researchers have been studying large language models (LLMs) for some time and “draw a distinction between formal competence — the knowledge of linguistic rules and patterns — and functional competence, a set of skills required to use language in real-world situations.” Also from some of their research summaries: “Too often, people mistake coherent text generation for thought or even sentience. We call this a “good at language = good at thought” fallacy. Similarly, criticisms directed at LLMs center on their inability to think (or do math or maintain a coherent worldview) and sometimes overlook their impressive advances in language learning. We call this a “bad at thought = bad at language” fallacy.
This analysis is consistent with my experience preparing this article: Specificity reigns supreme when it comes to putting ChatGPT to work. Large, open-ended prompts on complex topics highlight a lack of “functional competence” in the chatbot, but that reality doesn’t neutralize its impressive capabilities when employed for specific tasks by an individual skilled in using it properly.
So, can ChatGPT replace network engineers? Not yet.
Mike Starr is the CEO and founder of trackd.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Google Cloud expands AI offerings with new tools, programs and partnerships | VentureBeat"
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"https://venturebeat.com/ai/google-cloud-expands-ai-offerings-with-new-tools-programs-and-partnerships"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Google Cloud expands AI offerings with new tools, programs and partnerships Share on Facebook Share on X Share on LinkedIn Composite Image: Google / VentureBeat Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Google Cloud is making another major push into generative AI with a slew of new tools, services and programs announced today aimed at helping businesses adopt and use the emerging technology.
The initiative includes expanded access to Google’s generative AI products like Vertex AI and Duet AI , new educational programs and consulting services, blueprints for specific use cases and expanding partnerships with companies like DataStax, Neo4j, Twilio and Typeface.
The company announced it’s making its Vertex AI platform more widely available, providing access to over 60 machine learning models that can generate images, translate between languages, summarize text and more. It also unveiled a new consulting service to help companies deploy generative AI and “activation packages” with sample AI applications for tasks like improving developer efficiency or speeding up content creation in marketing departments.
>>Follow VentureBeat’s ongoing generative AI coverage<< VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Google’s latest push into generative AI for business users comes as the technology is seeing wider interest and adoption. Tools like the company’s language model PaLM 2 can generate paragraphs of coherent text, while image generation software Imagen lets users create photorealistic pictures from scratch. But developing and deploying these complex AI systems requires significant expertise and resources, which Google is aiming to provide through its cloud services and partnerships.
Google Cloud generative AI goes live Vertex AI, Google’s machine learning platform, now provides full support for developing and deploying generative AI systems according to customers’ needs. Its Model Garden feature offers access to over 60 pre-trained AI models from Google and its partners that can translate between languages, summarize blocks of text, generate photorealistic images from descriptions and more.
Google believes its cloud services and partnerships can provide the expertise and resources needed to help mainstream businesses benefit from generative AI. The new availability of generative models and tools in Vertex AI points to an expanding role for artificial intelligence in office software and business automation.
A new offering called Generative AI Studio provides tools for customizing, improving and governing AI models in production use. This aims to give businesses more control and oversight of AI systems that directly impact their work and customers.
Google also said the enterprise version of Duet AI for Google Workspace, its office productivity suite, is now available for pre-order after months of testing. Duet AI uses generative models and other AI throughout Google’s collaboration apps to assist with tasks like writing documents, creating data visualizations and improving productivity in meetings.
The announcements highlight Google’s broad strategy to infuse artificial intelligence throughout its software and services for business customers. By baking AI into platforms for developing software, creating marketing content and enhancing office productivity, Google sees an opportunity to drive more enterprise use of its cloud technologies.
New AI consulting and educational offerings Google Cloud Consulting , the company’s professional services group, also launched several free learning programs covering generative AI for business executives, software developers and Google Cloud customers. And it introduced four new consulting services focused on deploying generative AI for automating search, summarizing documents, streamlining business processes and generating personalized content.
The consulting offerings suggest that even as Google makes powerful AI systems more widely available, many companies still require hands-on guidance and support to fully benefit from the technology. Generative models in particular often need to be fine-tuned for specific customer needs and use cases. The learning programs aim to build up knowledge about generative AI and machine learning both broadly and for strategic business uses.
In addition, Google released the first set of “blueprints” demonstrating how to apply generative AI for tasks like improving productivity in software engineering, accelerating marketing content creation and enhancing customer experience in industries such as finance, retail, healthcare and media. These provide a starting point for enterprises to build customized AI solutions, with Google and consulting partners on hand to advise them.
The announcements highlight Google’s ambition to drive enterprise adoption of advanced and complex AI systems through its cloud business. By providing both technological and human resources to help companies deploy machine learning for strategic needs, Google sees an opportunity to further compete with top cloud rivals like Amazon and Microsoft.
Traditional companies looking to use emerging technologies often face challenges finding and building internal expertise. Google’s moves suggest that its cloud business, which accounted for $26.28 billion in revenue last year, aims to provide not just access to AI and other technologies but also the guidance on how to adopt them.
Google Cloud expands AI ecosystem partnerships Google announced an expansion of several key partnerships as well, highlighting the company’s strategy to advance enterprise AI use through collaboration rather than competition.
Google said consulting firm partnerships with Deloitte, Capgemini and others will train over 150,000 people on Google’s AI platforms and tools, especially its generative models for tasks like generating images or summarizing text.
The company also released new “activation packages” providing templates for common AI applications such as improving search within organizations or accelerating marketing content creation. Google’s consulting arm will offer services to help companies apply AI for uncovering data patterns, summarizing information, streamlining business processes and generating personalized content tailored to customers.
The announcements signal Google’s belief that partnerships and expertise from outside firms will drive wider use of AI in traditional companies. By collaborating with large consultancies and technology providers, Google can extend its reach into new industries. The deployment partnerships also aim to demonstrate practical use cases of Google’s AI systems for enterprise customers.
The focus on partnerships and customer alliances contrasts with the strategies of Google’s largest cloud competitors, Amazon and Microsoft, which have built out their own large professional service groups to drive enterprise deals and technology implementations. By working with outside firms, Google can bring specialized expertise to new industries and use cases without building that knowledge in-house. The approach also allows Google to promote its AI and cloud services to the clients of major companies.
Still, Google continues to invest in expanding its own cloud consulting practice. The group now has thousands of employees working with customers on integrating Google’s technologies, highlighting the mix of internal and external resources the company aims to provide for enterprise AI adoption. The latest announcements suggest that blend may prove an advantage as complex tools like machine learning become more widely available.
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"Don't quit your day job: Generative AI and the end of programming | VentureBeat"
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"https://venturebeat.com/ai/dont-quit-your-day-job-generative-ai-and-the-end-of-programming"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Don’t quit your day job: Generative AI and the end of programming Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
There’s a lot of angst about software developers “losing their jobs” to AI, being replaced by a more intelligent version of ChatGPT , GitHub’s Copilot, Google’s foundation model Codey, or something similar.
AI startup founder Matt Welsh has been talking and writing about the end of programming.
He’s asking whether large language models (LLMs) eliminate programming as we know it, and he’s excited that the answer is “yes”: Eventually, if not in the immediate future.
But what does this mean in practice? What does this mean for people who earn their living from writing software? The value in new programming skills Some companies will certainly value AI as a tool for replacing human effort rather than for augmenting human capabilities.
Programmers who work for those companies risk losing their jobs to AI. If you work for one of those organizations, I’m sorry for you, but it’s really an opportunity.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Despite the well-publicized layoffs, the job market for programmers is great, it’s likely to remain great, and you’re probably better off finding an employer who doesn’t see you as an expense to be minimized. It’s time to learn some new skills and find an employer who really values you.
But the number of programmers who are “replaced by AI” will be small. Here’s why, and here’s how the use of AI will change the discipline as a whole. I did a very non-scientific study of the amount of time programmers actually spend writing code.
OK, I just typed “How much of a software developer’s time is spent coding” into the search bar and looked at the top few articles, which gave percentages ranging from 10% to 40%. My own sense, from talking to and observing many people over the years, falls into the lower end of that range: 15% to 20%.
Time for “the rest of the job” ChatGPT won’t make the 20% of time programmers spend writing code disappear completely. You still have to write prompts, and we’re all in the process of learning that if you want ChatGPT to do a good job, the prompts have to be very detailed.
How much time and effort does that save? I’ve seen estimates as high as 80%, but I don’t believe them; I think 25% to 50% is more reasonable. If 20% of your time is spent coding, and AI-based code generation makes you 50% more efficient, then you’re really only getting about 10% of your time back.
You can use it to produce more code — I’ve yet to see a programmer who was underworked, or who wasn’t up against an impossible delivery date. Or you can spend more time on the “rest of the job,” the 80% of your time that wasn’t spent writing code.
Some of that time is spent in pointless meetings, but much of “the rest of the job” is understanding the user’s needs, designing, testing, debugging, reviewing code, finding out what the user really needs (that they didn’t tell you the first time), refining the design, building an effective user interface, auditing for security and so on. It’s a lengthy list.
Programmers needed: AI lacks design skills That “rest of the job” (particularly the “user’s needs” part) is something our industry has never been particularly good at. Design — of the software itself, the user interfaces and the data representation — is certainly not going away and isn’t something the current generation of AI is very good at.
We’ve come a long way, but I don’t know anyone who hasn’t had to rescue code that was best described as a “seething mass of bits.” Testing and debugging — well, if you’ve played with ChatGPT much, you know that testing and debugging won’t disappear. AIs generate incorrect code, and that’s not going to end soon.
Security auditing will only become more important, not less; it’s very hard for a programmer to understand the security implications of code they didn’t write. Spending more time on these things — and leaving the details of pushing out lines of code to an AI — will surely improve the quality of the products we deliver.
Prompting a different form of programming Now, let’s take a really long-term view. Let’s assume that Welsh is right and that programming as we know it will disappear — not tomorrow, but sometime in the next 20 years. Does it really disappear? A couple of weeks ago, I showed Tim O’Reilly some of my experiments with Ethan and Lilach Mollick’s prompts for using AI in the classroom.
His reaction was: “This prompt is really programming.” He’s right.
Writing a detailed prompt really is just a different form of programming. You’re still telling a computer what you want it to do, step by step. And I realized that after spending 20 years complaining that programming hasn’t changed significantly since the 1970s, ChatGPT has suddenly taken that next step.
It isn’t a step towards some new paradigm, whether functional, object-oriented or hyperdimensional. I expected the next step in programming languages to be visual, but it isn’t that either. It’s a step towards a new kind of programming that doesn’t require a formally defined syntax or semantics. Programming without virtual punch cards. Programming that doesn’t require you to spend half your time looking up the names and parameters of library functions that you’ve forgotten about.
Understanding problems in depth — not counting lines of code In the best of all possible words, that might bring the time spent actually writing code down to zero or close to it. But that best case only saves 20% of a programmer’s time. Furthermore, it doesn’t really eliminate programming. It changes it — possibly making programmers more efficient and definitely giving programmers more time to talk to users, understand the problems they face and design good, secure systems for solving those problems.
Counting lines of code is less important than understanding problems in depth and figuring out how to solve them — but that’s nothing new. Twenty years ago, the Agile Manifesto pointed in this direction, valuing: Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan AI incorporated: Programmers working directly with customers Despite 23 years of “agile practices,” customer collaboration has always been shortchanged. Without engaging with customers and users, Agile quickly collapses to a set of rituals. Will freeing programmers from syntax actually yield more time to collaborate with customers and respond to change? To prepare for this future, programmers will need to learn more about working directly with customers and designing software that meets their needs. That’s an opportunity, not a disaster. Programmers have labored too long under the stigma of being neckbeards who can’t and shouldn’t be allowed to talk to humans. It’s time to reject that stereotype and build software as if people mattered.
AI isn’t something to be feared. Writing about OpenAI’s new Code Interpreter plug-in (gradually rolling out now), Ethan Mollick says , “My time becomes more valuable, not less, as I can concentrate on what is important, rather than the rote.” AI is something to be learned, tested and incorporated into programming practices so that programmers can spend more time on what’s really important: Understanding and solving problems. The endpoint of this revolution won’t be an unemployment line; it will be better software. The only thing to be feared is failing to make that transition.
Programming isn’t going to go away. It’s going to change, and those changes will be for the better.
Mike Loukides is VP of emerging tech content at O’Reilly Media.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"CodeSignal's AI strategy: CEO Tigran Sloyan addresses evolving skills gap | VentureBeat"
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"https://venturebeat.com/ai/codesignal-ai-strategy-ceo-tigran-sloyan-addresses-evolving-skills-gap"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages CodeSignal’s AI strategy: CEO Tigran Sloyan addresses evolving skills gap Share on Facebook Share on X Share on LinkedIn Image Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
CodeSignal , a San Francisco-based startup that provides coding assessments for technical recruiting, announced today several major platform upgrades leveraging artificial intelligence (AI) to better evaluate software engineering candidates.
The company rolled out several new features including AI-powered analysis to detect cheating, benchmarking data to compare candidates and an AI assistant to allow appropriate use of generative AI during coding tests.
Tigran Sloyan, the cofounder and CEO of CodeSignal, provided valuable insights into the future of AI in recruitment and skills development in a recent interview with VentureBeat. His commentary revealed the company’s plans to leverage AI to help companies adapt to the rapid emergence of new skill sets and to assist individuals in navigating this changing landscape “We’re a skills platform. Everything revolves around skills. [Employees] need to understand skills, they need to discover skills, they need to develop skills,” Sloyan said regarding the future of employment. “It’s going to become such a top of mind thing for all Fortune 500s.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “On one side, we have customers who want to detect AI usage because they aren’t ready to embrace it yet,” he added. “On the flip side, we have companies who want candidates to use AI to showcase skills. So we built both AI detection and enablement.” AI in technical recruitment CodeSignal has been transforming recruitment processes by focusing not only on whether a candidate can do the job but also how they achieve it. Sloyan compared this approach to judging the quality of a physical building, stating, “Just because a building stands doesn’t mean it’s well built, or that it will stand the test of time.” In the context of software development , he explained that “evaluating how somebody got something done used to be very difficult, because it requires a human level intelligence.” But now, through gen AI, CodeSignal can make nuanced decisions similar to those of an experienced interviewer.
This focus on the qualitative aspects of a candidate’s skills is a response to the rapid evolution and creation of new skill sets driven by technological advancements. Sloyan noted the strikingly short period for job categories to be born and become prominent, citing mobile developers and cloud engineers as examples.
“Organizations who cannot adapt to that change are not going to be able to survive,” Sloyan warned. The new reality of the job market, according to him, is that “ new skills will be born, will become dominant and will become absolutely necessary.” Bridging the skills gap As for CodeSignal’s future, Sloyan envisions the platform as a vital resource for navigating this terrain of rapidly emerging skills. “I want us to be able to both help the individual go through this transition of learning and acquiring new skills and demonstrating those skills, as well as helping companies not get stuck in an ever-widening skills gap.” CodeSignal’s approach to this challenge will be closely watched in an industry grappling with the dual reality of skill obsolescence and creation. As Sloyan pointed out, while technology might automate certain skills, it also presents an array of new skills that individuals can acquire. This adaptive capability will be pivotal for both businesses and individuals in the future of work.
Given this vision, it’s clear that CodeSignal is positioning itself as a key player in the future of recruitment and skills development. By leveraging the power of AI and maintaining a keen focus on the qualitative aspects of skills, CodeSignal is poised to address the skills gap and help both individuals and companies adapt to the ever-changing job market.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"UBS projects 61% compound annual growth rate for AI demand between 2022 and 2027 | VentureBeat"
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"https://venturebeat.com/ai/ubs-projects-61-compound-annual-growth-rate-for-ai-between-2022-and-2027"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages UBS projects 61% compound annual growth rate for AI demand between 2022 and 2027 Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In an analyst note on Tuesday, the financial services arm of Swiss banking giant UBS raised its guidance for long-term AI end-demand forecast from 20% compound annual growth rate (CAGR) from 2020 to 2025 to 61% CAGR between 2022 to 2027.
“We don’t think AI is a bubble given clear use cases and solid long-term visibility, but recommend investors consider companies with clear monetization trends,” wrote Solita Marcelli, the global wealth management chief investment officer Americas of UBS Financial Services.
The report is an acknowledgment of the huge financial potential of the emerging sector surrounding generative AI and related technology.
So far, the total global tech market capitalization has grown by $6 trillion year-over-year, of which AI-related enterprises contributed $2 trillion, according to the UBS note.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Current focus on infrastructure; apps and data in long term UBS predicts that global AI demand will grow from $28 billion in 2022 to $300 billion in 2027. The note identified two main components of the AI sector: an infrastructure layer as well as an application and data layer.
Today, it said, most of the spending is found in the infrastructure component, with concentration on building and training huge data sets. But in the medium and long term, the application and data will be the larger segment with the increasing use of innovative deployments of gen AI technologies like copilots, imagery and big data analytics.
“We see significant opportunities over the next few quarters, such as in the integration of AI “copilots” in office productivity software, rising demand for big data analytics, and AI integration in image/video and other enterprise applications,” said Marcelli.
Applications vs. infrastructure UBS analysts laid out how they expect the applications and data segment to bring $170 billion in revenues, compared to $130 billion for the infrastructure layer, in 2027. Those are CAGRs of 139% and 38%, respectively.
In short, UBS thinks investors should be paying extra attention to the companies in the AI software ecosystem, as today’s infrastructure-adjacent semiconductor and hardware businesses, such as Nvidia , continue to have high valuations.
“Given the rich valuations, we are waiting for a pullback to turn positive on the segment again,” the note read. “Meanwhile, we think the risk-reward is more attractive for software stocks, which, in our view, are well positioned to ride the broadening AI demand trends.” Some companies have set out to capture both verticals. Nvidia recently announced the wide-accessibility of its cloud-based AI supercomputing software service, DGX Cloud , which will be powered by thousands of virtual Nvidia GPUs.
“With DGX Cloud, now any organization can remotely access their own AI supercomputer for training large complex LLM and other generative AI models from the convenience of their browser, without having to operate a supercomputing data center,” Tony Paikeday, senior director for DGX Platforms at Nvidia, told VentureBeat.
The money keeps flowing into AI Investment into AI-based companies continues to be strong. Last week, German enterprise software giant SAP announced it directly invested in three AI startups: Cohere , Anthropic (maker of the Claude 2 LLM service ) and Aleph Alpha.
Previously, SAP-backed Sapphire Ventures announced a $1 billion commitment to gen AI startups. All of this activity follows Microsoft’s $10 billion bet on OpenAI in January 2023.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"SAP invests directly in three AI startups: Cohere, Anthropic and Aleph Alpha | VentureBeat"
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"https://venturebeat.com/ai/sap-invests-directly-in-three-ai-startups-cohere-anthropic-and-aleph-alpha"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages SAP invests directly in three AI startups: Cohere, Anthropic and Aleph Alpha Share on Facebook Share on X Share on LinkedIn Credit: VentureBeat made with Midjourney Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
German enterprise software giant SAP is putting skin into the AI game.
The company today announced it has directly invested in three AI startups: Cohere , Anthropic (maker of the Claude 2 LLM service ) and Aleph Alpha.
While the company did not specify dollar amounts, a spokesperson told VentureBeat that the investments “are a signal of SAP’s commitment to offering valuable generative AI scenarios built into our portfolio of business applications, which are used every day by the world’s leading brands. As we continue to innovate, we are committed to using the best, responsible AI technology and tools in the market.” The news follows a more precise dollar investment from SAP-backed Sapphire Ventures, which announced a staggering $1 billion commitment to gen AI startups last week.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Why SAP needs to be a leader in enterprise AI SAP is the third largest software company in the world in terms of annual revenue, behind only Microsoft and Oracle, and the largest outside of the U.S. Its enterprise resource planning (ERP) software — the stack that knits together a company’s supply chain and operational applications — is used by such notable brands as oil megacorp ExxonMobil and drug maker Novartis. One of its more recognizable apps is the travel and business expense filing software Concur.
SAP says it already has 26,000 customers around the world using its existing SAP Business AI, which predated the investment announcement, showing the appetite for these types of services.
As such, applying generative AI to it could have a tremendous impact for businesses and their customers around the globe. In fact, while VentureBeat does not offer investment advice, Bank of America analyst Frederic Boulan named SAP one of the top 10 stocks to invest in for generative AI gains , citing the fact that “huge quantities of data about a company’s operations are held within a company’s ERP system which makes the software vital in any generative AI integration.” In other words: SAP already has a treasure trove of data from all of its many global customers, and should it decide to offer gen AI services to those customers in conjunction with or through existing SAP offerings, it stands to reason that SAP could make a huge impact on both the customer side and its own bottom line.
SAP customers begin AI pilots ‘immediately’ “Pilots and proof of concepts (PoCs) are underway with customers, so any customer who is interested can get started immediately with SAP,” SAP’s spokesperson told VentureBeat in an emailed statement.
As for why SAP chose these three gen AI startups to invest in over any others: “All three companies — Aleph Alpha (Germany), Anthropic (U.S.) and Cohere (Canada) are each recognized for industry leadership, innovation, and a unique vision for advancing AI and the potential to transform industries. And with our overarching approach to foster an open ecosystem of Business AI, we believe that SAP should give customers choice and are proud to invest in each of them.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Immuta updates its Data Security Platform for Databricks to strengthen AI workload protection | VentureBeat"
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"https://venturebeat.com/ai/immuta-updates-its-data-security-platform-for-databricks-to-strengthen-ai-workload-protection"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Immuta updates its Data Security Platform for Databricks to strengthen AI workload protection Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Data security provider Immuta announced significant enhancements to its Data Security Platform for Databricks to empower data teams to leverage Immuta’s platform capabilities. These updates aim to unlock data value, reduce costs, accelerate innovation and maintain robust data security.
Key updates include native integration with Databricks Unity Catalog , which connects customers with Immuta’s latest platform features such as localized sensitive data discovery, improved security and access control for artificial intelligence (AI) workloads and enhanced data security posture management.
The company said it distinguishes itself from competitors by offering a comprehensive platform instead of a mere point solution. This platform comprises three main product modules: Discover, Secure and Detect.
Discover facilitates the discovery of sensitive data and automates the capture of schema changes. On the other hand, Secure maps high-level data access policies to data warehouse policies and enforces access control. Lastly, Detect enables user and activity monitoring, behavior analytics, and risk scoring, empowering organizations to proactively identify and address issues such as insider threats.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “Our comprehensive solution for data security covers the breadth of what most organizations need to protect their data according to NIST standards, including sensitive data discovery, data access control and data access monitoring and detection,” Immuta chief product officer Mo Plassnig told VentureBeat.
Leveraging attribute-based access control The company claims that its approach to access control, which it calls attribute-based access control (ABAC), surpasses the traditional role-based access control (RBAC) in terms of effectiveness and efficiency.
According to a recent GigaOm report , leveraging ABAC reduces policy burdens by 93 times, resulting in potential savings of approximately $500,000 in time and opportunity costs for organizations.
“Our patented approach to sensitive data discovery allows data to be classified for security purposes without leaving the database, ultimately creating more effective data policies to meet stringent data localization regulations,” said Plassnig. “Additionally, we maximize value and speed and enable data security posture management and risk remediation above policy thresholds. “ Enabling secure AI data migration to the cloud Immuta said the growing trend of migrating data to the cloud presents a greater challenge in securing and protecting it, which can impede data migration initiatives. The company’s new integration with Databricks effectively handles the intricate aspects of data security management.
The company asserts that this integration will empower mutual customers to concentrate on extracting value from their data with enhanced efficiency. By leveraging the functionalities of Databricks Unity Catalog, including row filtering and column masking capabilities, Immuta offers a solution encompassing data discovery, security, access control and monitoring.
“Our new native integration with Databricks Unity Catalog enables joint customers to overcome boundaries to granularity and manageability, including implementing robust access controls and permissions to restrict unauthorized access to the data and continuous monitoring of the security posture of the lakehouse platform,” Plassnig told VentureBeat.
Necessary controls during model training Immuta emphasized its commitment to preventing the inclusion of sensitive data in models by implementing necessary controls during the model training process. Furthermore, by integrating more deeply, the company helps to ensure that AI workloads maintain compliance with regulations like GDPR , HIPAA and industry-specific standards.
The updated platform now offers customizable tools to reduce false positives and increase relevance and the value of results.
“Too many false positives leading to a higher than desired noise-to-signal ratio is the number one complaint for the companies we have spoken with who have wanted a more automated solution for SDD (sensitive data discovery),” Immuta VP of product management Matt DiAntonio told VentureBeat. “Teams are looking to use the results of their SDD tool to build out data security practices that up the ante and make accuracy very important. Immuta has taken that concern seriously by building an experience that gives data teams the tools they need to trust the results fully.” DiAntonio emphasized the importance of data producers embracing intelligent systems capable of scaling across large, geographically dispersed organizations to keep pace with innovation.
Monitoring key components in the data supply chain DiAntonio highlighted the unique capabilities of the platform’s Detect Activity Monitoring feature that enables the monitoring of key components, including individuals, tags and data sources that play a vital role in the data supply chain within the business.
To accomplish this, Immuta Detect consolidates data access logs, enabling data and security teams to consistently monitor and analyze user behavior and changes in data access entitlements. This monitoring encompasses source, query and user activity and provides valuable insights into security configuration and data classification changes.
(Come learn more about data and AI in the enterprise at VB Transform on July 11 & 12 in San Francisco, our networking event for enterprise technology decision makers.) Additionally, the Detect feature automatically assigns scores to data based on its sensitivity and protection measures, such as data masking or stated access purposes. This allows data and security teams to prioritize risks and receive real-time alerts regarding potential security incidents.
“Our Detect module can offer much value to teams looking to move fast,” DiAntonio added. “Many companies we spoke with struggled with the ‘black box’ phenomenon around their cloud data. They didn’t know what was going on within their organization around the production and usage of data. Immuta solves that by providing the essential views with data teams feeling informed without being overwhelmed.” What’s next for Immuta? Plassnig said that the increasing challenges associated with data migration have generated a need for cloud data management and security solutions.
Immuta strives to encourage corporate investors to establish partnerships with data security leaders. The objective is to give investors enhanced control and visibility over their data and assets.
“With better data security and simpler operations, organizations can get the right data to the right people so they can build more data products, collaborate, share data and create new revenue streams,” said Plassnig. “Immuta is taking a stand by helping organizations unlock value from their data by providing an integrated platform for sensitive data discovery, security and access control, and activity monitoring.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Rubrik looks to protect sensitive cloud-based data from ransomware attacks | VentureBeat"
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"https://venturebeat.com/security/rubrik-looks-to-protect-sensitive-cloud-based-data-from-ransomware-attacks"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Rubrik looks to protect sensitive cloud-based data from ransomware attacks Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Today, zero-trust data security provider Rubrik announced the launch of Rubrik Cloud Vault, a managed secure data service. The service is designed to protect sensitive data by isolating the vault from the rest of the organization’s cloud environment to reduce the risk of data being modified, deleted, or encrypted during a ransomware attack.
Essentially, Rubrik Cloud Vault is designed to provide organizations with access to Azure Storage and Zero Trust Data Security from Microsoft to offer a data protection and disaster recovery solution that they can use to store data securely in cloud and hybrid cloud environments.
The announcement comes after Microsoft’s recent equity investment in Rubrik in August of this year, which began a strategic agreement between the two companies to build zero-trust data protection solutions for Microsoft Azure customers. Rubrik Cloud Vault is set to launch early next year on the Azure Marketplace.
Getting to grips with ransomware Ransomware has emerged as a significant threat to enterprises. This year alone, attackers infected IT management provider Kaseya’s systems to encrypt the computers of 1,500 businesses, while Colonial Pipeline had to pay a $5 million ransom to get access to its systems.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! While these are high-profile examples, these attacks are expensive across the board, with the average attack costing $4.24 million.
The high cost of these attacks is a key reason why Rubrik and Microsoft are collaborating to reduce the likelihood of attackers being able to encrypt this information in the first place.
“Ransomware attacks pose an increased danger to every business around the world, regardless of industry,” said Dan Rogers, president of Rubrik. “This is a key milestone in our commitment to integrate Rubrik Data Security capabilities with Microsoft products to deliver zero trust data security to global enterprise customers.” Zero-trust data protection Rubrik Cloud Vault offers organizations a location to store data securely in the cloud under the protection of encryption, with multi-factor authentication and role-based controls that prevent unauthorized users from accessing sensitive business data.
With more employees working from home throughout the COVID-19 pandemic, a zero-trust approach is critical for reducing the likelihood of an attacker being able to obtain initial access to data and encrypting it. At the same time, in the event that an attacker does break into the vault, the solution provides organizations with instantly recoverable copies of their data that they can use to quickly restore critical data assets before they experience prolonged downtime.
While this doesn’t entirely prevent double extortion attempts, where attackers threaten to leak hacked data, it does provide more security against traditional ransomware-style attacks.
The ‘Azure data protection’ provider Rubrik was formed in 2014, and the cloud data management company now has more than 1,600 employees in over 18 countries, maintaining a customer base of over 3,200. Some of Rubrik’s top competitors in cloud data management solutions include Veeam Software Backup & Replication , Cohesity DataProtect , and Commvault Backup and Recovery.
Veeam offers a suite of data protection and backup solutions, including Veeam Software Backup & Replication, that are designed to back up physical and virtual workloads. The company has had a strong year so far, growing 25% in Q1, claiming to have 82% of the Fortune 500 as customers, and releasing a new backup platform for Google Cloud to add to its existing backup and disaster recovery solutions.
Cohesity recently announced the launch of a data security and governance service called DataGovern, which uses artificial intelligence to detect the kinds of anomalous access to data that come before ransomware attacks, and Project Fort Knox, which enables organizations to back up copies of their data in a secure vault. Cohesity has an annual run rate of over $300 million and claims it has 25% of the Fortune 500 as customers.
As more providers develop secure data backup and disaster recovery solutions to combat ransomware, Rubrik said it is attempting to differentiate itself by building an Azure-specific solution that offers organizations a zero-trust approach to cybersecurity.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Atlassian announces new DevSecOps feature for Jira to bolster security prioritization | VentureBeat"
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"https://venturebeat.com/security/atlassian-unveils-devsecops-feature-jira-software-security-prioritization"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Atlassian announces new DevSecOps feature for Jira to bolster security prioritization Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Collaborative software provider Atlassian today unveiled a groundbreaking feature for its renowned development issue-tracking software, Jira.
The “Security in Jira” feature allows users to integrate popular security tools in Jira’s Security tab. With this feature the company seeks to revolutionize how organizations prioritize security by granting software teams improved visibility into crucial security issues.
The company has partnered with other developer security companies — Snyk , Mend , Lacework , Stackhawk and JFrog — to empower teams to address security concerns more efficiently and earlier in the software development lifecycle. This collaborative effort aims to enable organizations to tackle security challenges proactively and enhance their overall software development processes.
“Our goal with Security in Jira is to make security a native part of the agile planning rituals central to excellent software teams. With the Security tab, we’re shifting security left while increasing transparency across tools and teams so Jira Software’s more than 100,000 customers will now be able to more easily and effectively address vulnerabilities,” Suzie Prince, head of product for DevOps at Atlassian, told VentureBeat.
Atlassian believes that with popular security tools integrated into Jira Software’s Security tab, development teams will be able to streamline their workflows and address vulnerabilities with greater agility.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! According to Prince, software teams should prioritize security as it is no longer limited to developers alone.
“We want to make it easy for anyone in the software team to access and understand their product’s security posture,” said Prince. “Our new feature allows teams to understand the importance of each vulnerability, so they can prioritize mission-critical solutions sooner and reduce the risk of each release. This also helps increase developer efficiency by minimizing ad hoc interruptions.” Starting today, the new security capabilities will be accessible to all Jira Software Cloud users.
The company told VentureBeat that users will have the option to enable the security tab and effortlessly integrate their existing tools, allowing them to explore this robust integration.
Mitigating data breaches with new DevSecOps features Atlassian believes securing software has become a daunting task due to the dynamic nature of the development process and the proliferation of new technologies. Teams often struggle to comprehensively address each potential attack vector, given the numerous vulnerabilities present in the code.
The company’s internal research identified the emergence of powerful security tools, each specializing in a specific aspect of the software development process. Organizations use multiple security tools, averaging over nine per enterprise.
The company stated that this fragmented approach results in vulnerabilities scattered across various tools, leading to inefficiencies and an increased likelihood of development teams making errors. Recognizing the need for a centralized solution, Atlassian introduced “Security in Jira” to bring together leading security tools within Jira Software.
“Our goal is to simplify security management with Jira Software as the mission control center. We want teams to use their preferred security tools, and have intentionally partnered with vendors that provide services for each stage of the software development lifecycle — from code to runtime,” Atlassian’s Prince told VentureBeat. “By bringing security insights directly into Jira Software, we’re streamlining security software rituals and minimizing context switching, so developers can spend less time clicking between apps and more time shipping high-quality, secure code.” Prince said that the new feature retrieves data from a company’s preferred security vendor(s) to offer a comprehensive overview of vulnerabilities impacting their product, from the code level to runtime. These vulnerabilities are then automatically linked to Jira issues and incorporated into the team’s sprints, enabling them to quickly address them with the necessary context.
“Until today, teams often needed to manually copy and paste vulnerability data from many tools into Jira Software to triage or write custom code to funnel vulnerabilities automatically into Jira Software. With Security in Jira, we have removed this busywork from teams and enabled a more reliable and refined triaging experience,” she explained.
Atlassian said that users will also be able to filter and prioritize vulnerabilities based on severity, allowing them to stack rank the vulnerabilities accordingly. Furthermore, users can set up automations to prioritize the most severe vulnerabilities. Once activated, Jira automation can generate a Jira issue and seamlessly add it to a team’s backlog or sprint board, automatically assigning a due date and owner.
“With Jira Software as the single source of truth, developers can address the highest-priority vulnerabilities faster and accelerate development velocity while reducing the risk of each release,” said Prince. “Our goal is to reduce complexity and friction and help developers understand the most critical vulnerabilities to address them quickly and earlier. The security tab in Jira automatically brings all vulnerabilities into one single pane, so developers can prioritize the most urgent vulnerabilities in one place with the assurance that they aren’t missing anything.” Crafted according to industrial security needs In private beta preview of the new capability for customers, software teams were enthusiastic about eliminating the time-consuming task of manually copying and pasting vulnerabilities into issues in Jira Software, the company said.
It also noted that customers were excited about the enhanced visibility of vulnerabilities and security for all software team members.
“They were pleased that Atlassian is taking a proactive and visible approach to integrating security within Jira Software, ensuring that security remains a top priority throughout the software development lifecycle,” added Prince. “With Security in Jira, we believe that a team’s vulnerabilities will go directly into their backlog to improve and help simplify their sprint planning.” She emphasized that while automations are crucial in expediting development velocity, their effectiveness relies on a well-maintained toolchain. Therefore, she recommends that teams should regularly synchronize the configuration between Jira Software and their security tools to consistently incorporate the latest vulnerabilities.
“To operationalize this practice, teams need to identify a toolchain manager to ensure they’re connected and to maximize the effectiveness of their integrations,” said Prince. “One of the challenges of standalone security tools is that only developers have visibility. A best practice is to review vulnerabilities within Jira Software as a team, to reduce silos and prioritize security across the entire software development lifecycle.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Report: 85% of financial leaders are preparing for possible recession and economic disruption in 2023 | VentureBeat"
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"https://venturebeat.com/enterprise-analytics/report-85-of-financial-leaders-are-preparing-for-possible-recession-and-economic-disruption-in-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Report: 85% of financial leaders are preparing for possible recession and economic disruption in 2023 Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
OneStream , a leader in corporate performance management (CPM) solutions, recently commissioned a report through Hanover Research to survey finance leaders across North America on responses to economic challenges and budget priorities for the upcoming year.
The findings revealed that ongoing global disruption continues to impact financial planning. In fact, 85% of financial leaders are reforecasting in preparation for an impending recession and nearly half (47%) identified economic disruption as the largest threat to business in 2023.
The looming recession will make hiring plans conservative in 2023, especially in accounting and finance departments. Finance leaders will need to invest in more automation and digital technology to increase productivity with the current talent shortage. Most leaders (57%) are planning to invest more in cloud-based planning and reporting solutions in 2023, while almost half (48%) will invest more in predictive analytics.
Sixty-one percent already use cloud-based planning and reporting solutions, and 37% utilize predictive analytics.
Meanwhile, only 37% of companies will invest more in machine learning (ML). With AutoML technology poised to reduce the barriers to adoption of machine learning, and although cost is still an obstacle, almost half (48%) of all financial decision-makers say their organizations plan to investigate AutoML solutions. In fact, one-quarter (28%) have already adopted AutoML solutions.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! When asked about the top use cases for artificial intelligence (AI) and ML technology, 48% see financial reporting as the top opportunity. Finance leaders see sales and revenue forecasting (41%), demand planning (39%), and sales and marketing optimization (39%) as additional opportunities for these technologies.
However, for businesses facing technical and security issues, almost half (49%) say there’s a lack of trust in new technology solutions, which is deterring new investments.
The study, conducted in September 2022, sourced insights from 657 finance decision-makers (management to C-suite) in the United States, Canada and Mexico. Respondents are employed by companies across numerous industries and varying revenues, with 34% employed by companies with more than $1 billion in annual revenue.
Read the full report from OneStream.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"OVH datacenter disaster shows why recovery plans and backups are vital | VentureBeat"
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"https://venturebeat.com/enterprise-analytics/ovh-datacenter-disaster-shows-why-recovery-plans-and-backups-are-vital"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages OVH datacenter disaster shows why recovery plans and backups are vital Share on Facebook Share on X Share on LinkedIn A picture taken on March 10, 2021 shows a view of a cloud data center of French Internet Service Provider OVH after the building was damaged in a fire in Strasbourg, eastern France.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
European cloud computing giant OVH announced today that a major fire destroyed one of its Strasbourg datacenters and damaged another, while the company also shut down two other datacenters located at the site as a precautionary measure. Nobody was reported to have been injured.
While AWS, Azure, and Google Cloud usually garner most of the limelight in the cloud computing realm, OVH is one of the bigger ones outside the “big three” with 27 datacenters globally, 15 of which are in Europe. Today’s disaster, which was thought to have taken more than 3.5 million websites offline, comes during a major period of activity for France-based OVH, after it recently announced a partnership with Atos to offer fully EU-made cloud services in an industry dominated by Amazon, Microsoft, and Google. And just this week, OVH revealed that it was in the early planning stages of going public.
Recovery In the wake of the fire which broke out around midnight local time today, OVH founder and chairman Oktave Klaba took to Twitter to recommend that its customers activate their disaster recovery plan.
We have a major incident on SBG2. The fire declared in the building. Firefighters were immediately on the scene but could not control the fire in SBG2. The whole site has been isolated which impacts all services in SGB1-4. We recommend to activate your Disaster Recovery Plan.
— Octave Klaba (@olesovhcom) March 10, 2021 VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! However, it soon became apparent that not all companies had a sufficient disaster recovery plan in place, with French government bodies and some banks still offline at the time of writing , more than 15 hours later.
Above: Algeria’s Trust Bank was still offline more than 15 hours after the fire first started.
Moreover, Facepunch Studios, the game studio behind Rust , confirmed that even after it was back online that it would not be able to restore any data.
Update: We've confirmed a total loss of the affected EU servers during the OVH data centre fire. We're now exploring replacing the affected servers.
Data will be unable to be restored.
— Rust (@playrust) March 10, 2021 And that, perhaps, is one of the biggest lessons businesses can glean from the events that unfolded in Strasbourg today. Despite all the benefits that cloud computing brings to the table, companies are still putting all their trust in a third-party’s infrastructure, which is why having a robust disaster recovery plan — including data backups — is so important.
OVH, which also provides email and internet hosting services, said that it plans to restart two of the unaffected datacenters by this coming Monday (March 15).
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"Microsoft makes Azure Site Recovery available to all, offers free on-premises replication for 1 month | VentureBeat"
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"https://venturebeat.com/dev/microsoft-makes-azure-site-recovery-available-to-all-offers-free-on-premises-replication-for-1-month"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Microsoft makes Azure Site Recovery available to all, offers free on-premises replication for 1 month Share on Facebook Share on X Share on LinkedIn A remnant of the time when Microsoft's public cloud, Azure, carried the Windows moniker in its name hangs in building 42 on the Microsoft campus in Redmond, Wash.
Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Microsoft today announced that its Azure Site Recovery service — for backing up companies workloads in the Microsoft public cloud in order to keep them available in the event of a disaster — is now generally available.
Microsoft launched a preview of Azure Site Recovery in June 2014. The service previously went by the name Hyper-V Recovery Manager. In March Microsoft said Azure Site Recovery could handle backup of VMware workloads and physical servers.
And now that the service is generally available, Microsoft really wants companies to try it out — so it’s making a compelling offer.
“Customers can replicate on-premises workloads to Azure with Azure Site Recovery for 31 days at no charge, effectively making migration to Azure free,” Microsoft cloud and enterprise program manager Abhishek Hemrajani wrote in a blog post on the news today.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Disaster recovery is far from the hippest thing that you can do in a public cloud, but it’s important — companies are willing to shell out good money to assure themselves that their applications and data keep running no matter what. VMware itself has a disaster recovery service in its vCloud Air public cloud. Amazon Web Services, the leading public cloud, and Google Cloud Platform do not offer dedicated disaster recovery services. Now that Azure Site Recovery is generally available, that may change soon.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
All rights reserved.
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"Why data management matters: Turning analytics insights into income | VentureBeat"
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"https://venturebeat.com/data-infrastructure/cracking-code-data-management-analytics-propel-revenue-foster-consumer-loyalty"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Why data management matters: Turning analytics insights into income Share on Facebook Share on X Share on LinkedIn Illustration by: Leandro Stavorengo Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
This article is part of a VB special issue. Read the full series here: Building the foundation for customer data quality.
In the era of digital technology expansion, companies are accumulating large volumes of data on consumers’ activities both online and offline. At the same time, recognition of customer data’s immense value and potential to drive revenue growth is rising as companies realize that without the appropriate data — and data management — initiatives risk falling short of their potential.
Delivering a comprehensive customer experience holds immense importance. It plays a crucial role in acquiring new customers and retaining existing ones in today’s crowded digital landscape. In a world of increased globalization and an abundance of choices, customer experience assumes even greater significance.
According to Salesforce’s Connected Customer report, 88% of customers say their experience with the company is as important as its products or services. Meanwhile, 8 in 10 business leaders say data is critical in decision-making at their organization.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Consequently, business leaders are prioritizing data-driven decision-making, aiming to deliver an exceptional customer experience that establishes a competitive advantage.
But to meet and surpass evolving customer expectations while optimizing return on investment (ROI), brands must possess high-quality data for their marketing and advertising efforts.
“Gathering the right customer data increases a company’s ability to be built to deliver tailored products to customers as opposed to producing generic inventory. Companies today need a hybrid approach,” Nathan Saegesser, principal and head of data and analytics at KPMG’s deal advisory and strategy practice, told VentureBeat. “Having a wide range of well-processed data empowers companies to have a greater understanding of their clients, and they can use this information to provide a better product or service to drive sales.” Achieving personalization necessitates having the right customer data, including a comprehensive understanding of the customer’s location and their interactions with the organization or brand, and in particular a real-time view of customer behavior.
To address modern data management challenges, companies are incorporating AI into their customer data management strategies. This proactive approach empowers them to foster authentic interactions and develop hyper-personalized experiences that align with customers’ evolving demands.
Companies can now provide personalized recommendations and deliver relevant content through the use of sophisticated algorithms. This not only improves customer satisfaction but increases sales and reduces customer churn.
The essence of effective data management for mapping the customer journey Traditionally, organizations have relied on customer segmentation as part of their marketing strategy to ensure customers receive relevant communications and offers. However, they often struggle to achieve deeper levels of personalization using this tried-and-true method. While increasing segmentation efforts may seem like a viable approach, it does not necessarily yield the best return on investment (ROI) or maximize program effectiveness.
The key to optimizing a customer’s journey lies in data. Unfortunately, the era of one-size-fits-all mass emails is long gone.
“We found that fewer than 10 % of organizations have reached advanced maturity on their insights-driven capabilities,” Kim Herrington, senior analyst at Forrester , told VentureBeat. “The underlying goal of becoming insights-driven is shared by chief data officers (CDOs) and chief executive officers (CEOs) — to help employees make smarter business decisions faster. To do this, employees must be able to move from knowledge seeker to insights, to action.” One of the main challenges that brands encounter today is developing and implementing a comprehensive strategy for gathering and organizing data — data that, traditionally, has remained highly compartmentalized.
Data is often dispersed across spreadsheets and platforms, and there is a growing discussion around the complexities associated with data, including its vast volume and lack of organization, which presents challenges for enterprises and their teams.
“More data isn’t necessarily better — unless it’s connected and easily accessible,” said Claire Gribbin, head of SMB Worldwide at Amazon Web Services. Gribbin emphasized the significance of a unified data infrastructure in enabling businesses to effectively collect, store and access data.
“A well-planned data strategy, coupled with unified and clean data, has the potential to generate measurable value and drive tangible improvements for a business,” Gribbin added.
According to Raj De Datta, co-founder and CEO of commerce experience platform Bloomreach , organizations should begin by thoroughly understanding the various types of data they already collect and their respective sources. He said that typically, companies have distinct silos of customer data. This necessitates adoption of a customer data platform to consolidate all this data into a unified location.
“This not only helps with more efficient collection and storage, but it also makes it easier to analyze that data for more customer insights,” said De Datta. “With GDPR and other compliance regulations, third-party data is becoming increasingly difficult to use. Making more of an investment into collecting zero-party and first-party data will allow businesses to give consumers the option to reveal data about themselves in return for value — an exchange that’s ideal for both parties.” Likewise, Chris Comstock, chief growth officer at marketing data analytics platform Claravine , said that a strong customer data strategy can help build a trusted relationship with your customers and make them loyal customers for life.
However, to fully embrace the potential for data standards to alleviate common procedural issues, he suggests that companies should first align on and apply the right data naming conventions and taxonomies.
“Where companies tend to misstep is by trying to achieve high-quality data outputs by increasing the amount of time put into adding inputs. However, if the inputs aren’t consistent across datasets, then the conclusions drawn on the other side won’t be trustworthy, and thus [will be] unusable,” said Comstock. “In cases like this, it is a better allocation of resources to devote time to standardizing data across all aspects of the business as opposed to focusing twice as hard on fixing faulty outcomes.” Comstock emphasized that data consistency is crucial across all industries. Inconsistent or non-standardized data can result in unclear and unhelpful conclusions, which can lead to major problems.
“Without proper data standards to ensure coherence among a brand’s first-party data, marketers may find themselves starting over from the beginning,” he warned.
Driving customer loyalty through hyper-personalized experiences Behavioral data can help predict customers’ purchasing decisions. Real-time access to these behavioral insights also enables businesses to identify customers who are at high risk of churn. By combining effective data management with business intelligence (BI), companies can reduce churn rates and better understand how customers engage with their products.
Companies are increasingly adopting AI-powered hyper-personalization techniques to achieve exceptional results and deliver seamless omnichannel experiences. This approach enhances their BI capabilities and enables them to personalize their marketing efforts to the individual level by using carefully collected customer data.
“Customers get frustrated by offers and emails they get that aren’t specific to their needs, and if unchecked, such inbounds can lead to damaged brand reputations and long-term sales impacts. A client-centric personalization approach driven by AI can increase customer loyalty,” said Claravine’s Comstock. “New customers can be difficult and costly to find, so customer-centric approaches are the key to reducing churn; by offering superior service, personalized product offers and an all-around great experience.” By harnessing the power of AI, companies can optimize their targeting strategies and tailor their messaging to each customer’s unique preferences and behaviors, in turn enhancing customer loyalty to the brand.
“At Walmart, we use a predictive basket algorithm driven by deep learning models to predict a complete order containing multiple items for a repeat customer, along with the reorder quantity,” Mangalakumar Vanmanthai, VP of data and customer analytics engineering at Walmart Global Tech, told VentureBeat. “This is displayed for online customers on the Walmart.com homepage and app. These recommendations and substitutions are personalized as needed using high dimensional neural embeddings of customer behavior.
“By combining customer data science technology with customer behavior, we aim to create delightful experiences whether customers are shopping with us in our stores or online — ultimately increasing customer lifetime value.” Vanmanthai further explained that Walmart utilizes Smart Substitutions, one of Walmart Global Tech’s specialized recommendation algorithms. This algorithm assists store associates and customers in making improved item substitutions, taking into account their personalized preferences as well as the preferences of similar customers.
“It is built on a graph convolutional neural network that is trained using historical data pertaining to substitution acceptance and semantic models of the catalog,” said Vanmanthai. “After Smart Substitutions was introduced , we found that our customer acceptance of item substitutions has increased to over 95%.” Aaron Lee, CEO and founder of Smith.
ai , a platform providing AI-driven virtual agents, believes that advanced analytics tools and machine learning algorithms are key in making sense of the vast amounts of customer data. He said that Smith.ai utilizes technologies like generative AI and natural language processing (NLP) to scan customer data, which has helped the company identify customer sentiments and understand their pain points.
“Using AI has allowed us to provide better support and anticipate future requirements. By understanding each of our customers’ unique situations, we offer more tailored and suitable solutions,” explained Lee.
Lee highlighted a notable example of gaining insights from customer data during the COVID-19 pandemic. As a result, the company actively identified decreases in call volumes and proactively provided customers with smaller plans and flexible payment options.
“Our customers responded positively to this proactive approach, which greatly contributed to post-COVID customer loyalty,” said Lee.
He further emphasized the potential of data-driven strategies, where companies can use accurate and timely data to determine customer renewal timing, utilization patterns and product satisfaction. With this information, businesses can reach out to customers with targeted promotions and discounts, minimizing customer attrition and boosting revenue.
Key considerations for driving revenue through data management Pedro Arellano, senior vice president and general manager of Tableau at Salesforce, told VentureBeat that the challenge businesses encounter today lies not in collecting data but in comprehending its significance. To optimize the efficiency of data collection, storage and analysis, he advises organizations to align their data management strategy with their business objectives.
Arellano emphasized that approaching data management from a business perspective can provide clarity on the appropriate processes, tools and governance required. This alignment ultimately leads to improved revenue generation, saving valuable time and resources along the way.
“The right tools — from software and hardware to platforms and tech solutions — are essential to building a data management strategy. The technology that fits an organization will help it manage the data within its existing analytics environment and streamline processes so people have access to the information they need when and where they need it directly in the flow of work,” he said.
“Other big challenges in using data effectively often come down to data literacy — data owners aren’t always data experts,” explained Arellano. “Businesses must invest in the training that employees need [in order] to do their work and become data-driven decision-makers, and ensure everyone understands the company’s data management strategy.” Arellano also predicts that generative AI will revolutionize work processes, and says it has already proven effective in alleviating pain points and eliminating operational bottlenecks across various industries. However, he highlighted the importance of establishing robust data governance architecture when adopting such technologies.
“ Robust data governance programs can empower businesses and IT teams to interact with data — from making faster, smarter data-driven decisions to data security. Every benefit of having actionable insights comes from having sound data governance,” he said. “Businesses must invest in developing and communicating policies for proper data usage regarding data quality, security, privacy and transparency.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Cloudburst: Hard lessons learned from the OVH datacenter blaze | VentureBeat"
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"https://venturebeat.com/business/cloudburst-hard-lessons-learned-from-the-ovh-datacenter-blaze"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Analysis Cloudburst: Hard lessons learned from the OVH datacenter blaze Share on Facebook Share on X Share on LinkedIn Conceptual image of numbers and flames Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
In every tabletop disaster-recovery exercise in every enterprise IT shop, there’s a moment when attention grudgingly shifts from high-profile threats — malicious intrusion, data theft, ransomware — to more mundane (and seemingly less likely) threats, like natural disasters, accidents, and low-tech turmoil.
What hurricanes, explosions, earthquakes, fires, and floods lack in cybersecurity panache, they often make up for in ferocity. The history is clear: CIOs need to put more emphasis on force majeure — an act of God or moment of mayhem that threatens data availability at scale — when making their plans.
On Christmas Day 2020, a bomb packed into an RV decimated a section of downtown Nashville, Tennessee. The collateral damage included a crippled AT&T transmission facility, which disrupted communications and network traffic across three states and grounded flights at Nashville International Airport. Outages for business clients and their customers lasted through the rest of the holiday season.
This week brought even more stark evidence of the disruptive power of calamity. One of Europe’s largest cloud hosting firms, OVH Groupe SAS, better known as OVHCloud, suffered a catastrophic fire at its facility in Strasbourg, France.
The blaze in a cluster of boxy, nondescript structures — actually stacks of shipping containers repurposed to save on construction costs — completely destroyed one of OVH’s four datacenters at the site and heavily damaged another.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! OVH officials were quick to sound the alarm, with founder and chair Octave Klaba warning that it could take weeks for the firm to fully recover and urging clients to implement their own data recovery plans.
Assuming they had them.
Many did not.
Scarcely protected data remains a significant problem for businesses of all stripes and sizes. In 2018, Riverbank IT Management in the U.K. found that 46% of SMEs (small and mid-size enterprises) had no plan in place for backup and recovery. Most companies (95%) failed to account for all of their data, on-premises and in the cloud, in whatever backup plans they did have.
The results of such indiscretion are costly. According to Gartner, data-driven downtime costs the average company $300,000 per hour — that’s $5,600 every minute. The destruction at the OVH facility on the banks of the Rhine near the German border took down 3.6 million websites, from government agencies to financial institutions to computer gaming companies, many of which remain dark as of this writing. Affected complained on blogs and social media that years’ worth of data was lost for good in the OVH conflagration. The final financial tally will be staggering.
“Not all data catastrophes are caused by a hoodie-wearing, Eastern European hacker,” said Kenneth R. van Wyk, president and principal consultant at KRvW Associates, a security consultancy and training company in Alexandria, Virginia. “Some are caused by the most mundane circumstances.” “Sure, we need to consider modern security threats like ransomware, [but] let’s never forget the power of a backhoe ripping through a fiber optic line feeding a business-critical datacenter.” “It’s about a mindset of always expecting the worst,” van Wyk said. “Security professionals look at systems and immediately ask ‘What could go wrong?’ Every business owner should do the same.” In this age of ubiquitous cloud migration and digital transformation, what can IT leadership do to gird the organization against hazards large and small? The answer lies within the realm of business continuity and disaster recovery (BCDR). This well-codified discipline in information security is a critical, but often missing, piece in enterprise risk management and mitigation. Most organizations understand the basic rules of engagement when it comes to BCDR, but security experts agree that execution often lacks rigor and commitment.
“As a CIO, I’d immediately ask, ‘Have we truly tested our backups and recovery capability?'” said cloud security specialist Dave Shackleford, founder and principal consultant at Voodoo Security in Roswell, Georgia. “Whether cloud-based or not, too many organizations turn disaster recovery and business continuity planning and testing into ‘paper exercises’ without really ensuring they’re effective.” For organizations looking to protect key digital assets, what Shackleford deems an effective BCDR approach begins with a few time-tested best practices.
Start with the provider Ask about redundancy and geographic resilience — and get it in writing. Losing two cloud datacenters will always result in disruption and downtime, even for a host like OVH with 300,000 servers in 14 facilities across Europe and 27 worldwide. But how painful and protracted that loss is will largely depend on the robustness of the hosting company’s own backup and fail-over protocols.
The assurances, as spelled out in the service-level agreement (SLA), must also go beyond data processing and storage. A big part of Roubaix-based OVH’s troubles stemmed from the failure of backup power supplies that damaged its own custom-built servers — even in areas unaffected by the actual fire.
Look for items in the SLA that address not only the service guarantee but also the eligibility for compensation and level of compensation offered. Offering “five-nines” availability is great, but the host should also demonstrate a commitment to diverse transit connections; multiple sources of power; redundant networking devices; and multiple, discrete storage assets on the backend.
Get your own house in order Holding your cloud host accountable is a solid start, but it’s important to remember that, as the OVH experience casts in stark relief, enterprise-grade cloud is not some mythical realm of infinite resources and eternal uptime. Moving important digital assets to the cloud means swapping your own infrastructure for that of another, for-profit vendor partner.
The first requirement for cloud migration is to establish a framework for determining the wisdom and efficacy of making such a move to the cloud in the first place. Then there needs to be a comprehensive plan in place to protect everything the organization holds dear.
“Inventory all your critical assets,” van Wyk suggests. “Ask how much it would cost you if any of them were unavailable, for any reason, for an hour, a day, a week. Ask how you would restore your business if everything in your inventory vaporized. What would the downtime be? Can you afford that? What is your Plan B?” The Cloud Security Alliance offers excellent guidance when preparing, analyzing, and justifying cloud projects with an eye toward risk, particularly with its Cloud Controls Matrix (CCM).
If third-party hosting is warranted, it should be guided by formal policy that covers issues such as: Definitions for systems, data types, and classification tiers that can be accounted for in a risk assessment Graduated internal policies and standards attached to each classification tier Application and security requirements Specific compliance/regulatory requirements And a BCDR plan that covers all assets entrusted to all third-party providers Create fireproof backup Understand that failures are going to happen. Backup and recovery is so fundamental to the security triad of data confidentiality, integrity, and availability (CIA) that it enjoys its own domain in the NIST Cybersecurity Framework.
NIST’s CSF encourages organizations to ensure that “recovery processes and procedures are executed and maintained to ensure timely restoration of systems or assets affected by cybersecurity incidents.” There’s a lot going on in that sentence, to be sure.
Developing a robust approach to recovery that can satisfy NIST and withstand a catastrophic event like the OVH fire takes more than scheduling some automated backups and hoping for the best.
Van Wyk said it’s a good idea to take extra precautions with your vital business data and processing and ensure you will actually be able to use your backup plans in different emergency scenarios.
Whether organizations’ crown jewels live on-premises, in a hybrid environment, or solely in the cloud, a mature and pragmatic BCDR approach should include: Making it formal.
A real, effective disaster-recovery plan must be documented. Putting the plan in writing, to include the who, what, where, when, and how of it all helps organizations quantify required actions for preventing, detecting, reacting to, and solving data-loss events.
Quantifying data at risk.
Formal BCDR documentation is the best place to ensconce a detailed data-classification schema and a backup-specific risk register, to include a realistic rundown of threats facing the organization, the consequences of lost data of various types, and a menu of mitigations.
Drafting some all-stars.
A mature BCDR approach requires more than policies and processes; it demands a dedicated group of stakeholders responsible for various parts of the plan. A well-rounded disaster recovery team should represent diverse areas of the business who can assess the damage, kick-start recovery plans, and help keep disaster-recovery plans updated These are the folks who know what to do when trouble strikes.
Counting on communications.
A significant part of the NIST guidance on recovery demands that “restoration activities are coordinated with internal and external parties, such as coordinating centers, internet service providers, owners of attacking systems, victims, and vendors.” This requires thoughtful, advance planning to ensure communications remain open to employees, customers, law enforcement, emergency personnel, and even the media. The heat of the moment is no time to be scrambling for contact info.
Testing for efficacy.
Formal incident recovery exercises and tests at regular intervals are critical to BCDR success, as many of the OVH discovered to their horror. Crunch time is not the time to figure out if backups can successfully be put into production in a reasonable period. Sensible practice runs should include realistic objectives, with specific roles and responsibilities, for stress-testing the organization’s recovery capabilities.
Keeping it fresh.
BCDR plans should be reviewed annually to ensure they remain relevant and practical. Moreover, every trial run, every exercise, and every data-loss incident, no matter how small, is an excellent opportunity to examine lessons learned and make pragmatic improvements.
No BCDR plan can ward off all chaos and guarantee perfect protection. But as the OVH incident demonstrates, half-hearted policies and incomplete protocols are about as effective as no plan at all. Establishing a solid BCDR posture requires meaningful investment in resources, time, and capital. The payoff comes when the lights flicker back on and rebooted systems go back online, data intact and none the worse for the experience.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Backup firm Druva protects data in the cloud with $147M in new funding | VentureBeat"
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"https://venturebeat.com/business/backup-firm-druva-protects-data-in-the-cloud-with-147m-in-new-funding"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Backup firm Druva protects data in the cloud with $147M in new funding Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Druva , a cloud data protection and backup startup based in Sunnyvale, California, today announced it has raised $147 million, pushing the company’s valuation to over $2 billion post-money. Druva says the capital will bolster a range of initiatives spanning product development and geographic expansion, as well as hiring, delivery, and customer support.
Enterprises are managing nearly 40% more data than a year ago, and the stakes have arguably never been higher. Gartner predicts that at least 75% of IT operations will face one or more cyberattacks by 2025, and the University of Texas found 94% of companies suffering from a catastrophic data loss do not survive. Those statistics are more alarming in light of high-profile outages like that of OVHCloud earlier this year , an attack that took down 3.6 million websites ranging from government agencies to financial institutions and computer gaming companies.
Druva’s mission Druva, which was founded in 2008 by Jaspreet Singh, Milind Borate, and Ramani Kothandaraman, provides software-as-a-service-based data protection and management products for over 4,000 organizations, including Zoom, NASA, and Pfizer. In 2008, Singh, Borate, and Kothandaraman, who met working together at Veritas Software, formally launched Druva in Pune, India. (In Sanskrit, “druva” translates to “North Star.”) The company initially focused on providing management software to financial companies before shifting to general enterprise data management.
In 2018, Druva acquired Letterkenny-based CloudRanger, a backup and disaster recovery company. The following year, Druva purchased CloudLanes to supplement its on-premises to cloud performance.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Today, Druva offers services that aggregate enterprise data from endpoints, datacenters, and cloud workloads for backup and restore, disaster recovery, archival and retention, compliance monitoring, data forensics, and other uses. For example, Druva’s InSync product supports data backup on endpoint devices like laptops, smartphones, and tablets, in addition to platforms such as G Suite and Office 365. Druva Phoenix is the company’s solution for physical and virtual file servers, while Druva CloudRanger addresses Amazon Web Services (AWS) environments and workloads. All of Druva’s offerings run on the Druva Cloud Platform, a cloud-native backup platform built on AWS that provides a centralized backup repository.
Customer momentum Druva occupies a data backup and recovery market anticipated to be worth $11.59 billion by 2022, according to Markets and Markets. It competes to a degree with San Francisco-based Rubrik, which has raised hundreds of millions in venture capital for its live data access and recovery offerings. There’s also Cohesity and Clumio, which raked in $51 million for its cloud-hosted backup and recovery tools, as well as data recovery companies Veeam, Acronis, and HYCU.
But Druva, which has over 800 employees, believes it can continue to stand out in a crowded field. In December 2019, the company surpassed $100 million in annual recurring revenue, and it claims to have grown since then, with a 26% uptick in a customer base of thousands of companies over the last year. In March, Druva crossed 2.5 billion annual backups, experiencing a 40% increase in daily backup activity over the last 12 months alone. Singh says the platform now performs over 7 million backups per day.
“The global pandemic and unprecedented events of 2020 have ushered in a generational cloud transformation for businesses, with data’s increasing value at the heart of it,” Singh told VentureBeat via email. “Businesses today need a new approach to data protection, which can be deployed from anywhere, protect data everywhere, and securely scale on-demand. Only solutions built natively in the cloud are able to deliver all this functionality.” Caisse de dépôt et placement du Québec led Druva’s latest round of fundraising, with a significant investment by Neuberger Berman. It brings the company’s total raised to date to $475 million, following a $130 million series G round in June 2019.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Stravito launches generative AI tool for enterprise search and knowledge management | VentureBeat"
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"https://venturebeat.com/ai/stravito-launches-generative-ai-tool-enterprise-search-knowledge-management"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Stravito launches generative AI tool for enterprise search and knowledge management Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Stravito , an enterprise insights company, is introducing proprietary generative AI capabilities on its platform to streamline enterprise knowledge management. The aim is to optimize the search experience by delivering transparent answers, complemented by clickable links to source documents for fact-checking.
While Dropbox and Box have recently introduced similar offerings that enable users to conduct general keyword searches within documents and ask questions about the content, Stravito said it sets itself apart by providing information from multiple relevant sources.
Instead of offering a single answer per document, Stravito’s answer engine delivers a comprehensive analysis. Moreover, the company claims that its answer engine is adept at handling complex datasets, even when they present conflicting information. For instance, the engine will identify and highlight the discrepancies if different sources provide varying numbers.
“Our solution is designed to help users avoid bias by providing context, and it doesn’t just share binary yes/no answers, but will share additional details — suggesting more questions for followup searches,” Thor Olof Philogène, CEO and founder at Stravito, told VentureBeat. “The answers are generated based on proprietary knowledge, not on unverified internet data, and customers’ sensitive information stays within the trusted enterprise cloud environment.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Enhancing traditional search through generative AI The company said that its generative AI uses a client company’s internal knowledge base to generate answers. The tool will explicitly communicate if the platform lacks relevant knowledge to address a question. However, the user may still receive related context and existing information from the knowledge base.
>>Follow VentureBeat’s ongoing generative AI coverage<< According to Philogène, although generative AI is exciting and promising, human intervention remains crucial. He emphasized that the summarized answers the AI generates should serve as a starting point, enabling users to quickly grasp key points, rather than being treated as the ultimate answer to a question.
“Direct links to source documents make it easy to fact-check as well as to dig deeper and uncover important nuances in the data,” Philogène told VentureBeat. “That’s why Stravito’s AI capabilities not only provide links to the sources but also explicitly highlight the exact paragraphs that were used to generate the answer.” He said that in the realm of consumer insights and market research, the quality of answers depends heavily on the questions asked.
“While formulating the right question is a valuable skill, not all business stakeholders possess it, despite researchers investing significant time in developing this expertise,” explained Philogène. “Our AI’s recommended questions aim to solve both of these challenges: motivate users to continue exploration and learn more, but also help them ask better questions to get more concrete and helpful answers for further decision-making.” Philogène said that his company strongly focuses on trustworthiness, data privacy , and security aligned with strict enterprise requirements, as the platform runs on enterprise cloud solutions with an SOC 2 Type II report.
“The agreements we have in place cover confidentiality, data ownership and intellectual property (so that no service provider will use customer content to train their model). As an ISO 27001-certified organization, we ensure high data privacy and security for our new generative AI features just like for the rest of our platform,” he said.
What’s next for Stravito? The company said it would continue to develop generative AI capabilities based on customer feedback and needs, and plans to introduce several enhancements to the platform, including source control that allows users to exclude unwanted documents from generating answers. Furthermore, Stravito aims to integrate generative AI into existing workflows, such as Scrapbooks.
The company is exploring other areas in which to expand. These include providing concise one-page summaries for uploaded research, streamlining the desk research process through new production capabilities, and creating auto-generated summaries tailored to each user’s preferences.
“In the near future, AI-based communication will let us have meaningful talks and get personalized help from virtual assistants. At the same time, both new interfaces (from vendors) and new skills (from users) will be needed to make this cooperation seamless and effective,” said Philogène. ”At Stravito, we are very excited about the developments in generative AI and look forward to the groundbreaking developments we believe will happen in the market in the coming months and years.” >>Don’t miss our special issue: Building the foundation for customer data quality.
<< VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
Discover our Briefings.
The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Red Hat unveils Ansible Lightspeed to empower AI-driven IT automation | VentureBeat"
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"https://venturebeat.com/ai/red-hat-unveils-ansible-lightspeed-to-empower-ai-driven-it-automation"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Red Hat unveils Ansible Lightspeed to empower AI-driven IT automation Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Open-source solutions firm Red Hat today unveiled Ansible Lightspeed, a generative AI service integrated with IBM Watson Code Assistant.
The company’s latest offering seeks to drive extensive utilization of Ansible automation within organizations, streamlining task automation for beginners while freeing experienced automators from the arduous task of creating low-level tasks.
Red Hat utilizes natural language processing (NLP) to integrate the service with Watson Code Assistant, which is set to be available in the near future. Ansible Lightspeed allows users to rapidly construct automation code by harnessing IBM’s foundation models. According to the company, this integration offers a valuable solution for enterprises, as it addresses the skills gap and enhances efficiency, thereby expediting the time-to-value of automation.
Continuous feedback By allowing users to input simple English prompts, the service facilitates the translation of domain expertise into YAML code to create or modify Ansible Playbooks. Furthermore, users can actively contribute to the model’s training by providing valuable feedback and ensuring continuous enhancements.
“Organizations looking to modernize have a key challenge: An automation skills gap,” Tom Anderson, VP and GM of Ansible told VentureBeat. “ Generative AI has the potential to make experienced automation talent more productive and expand the aperture of who can create usable automation content.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! How? By making it easier for automation domain experts to translate their expertise into working automation code, he said. “Users can use natural language prompts to get code recommendations for generating tasks, which are the building blocks of Ansible Playbooks,” said Anderson.
The company says this new tool empowers domain experts to effectively translate their process knowledge and objectives into code. Furthermore, it caters to users who have a deep understanding of what needs to be accomplished but lack the YAML proficiency to craft compliant and efficient playbooks independently.
Moreover, the tool harnesses the vast repository of Ansible subject matter expertise within the Ansible Lightspeed foundation model. This allows users to explore new automation domains.
Leveraging natural language models to streamline automation Anderson told VentureBeat that the foundation model optimized for NLP is the cornerstone of the collaboration between Red Hat and IBM, distinguishing Ansible Lightspeed from other tools.
“The foundation model is trained with data from Ansible Galaxy, a huge open-source repository of Ansible content covering a plethora of use cases and vertical applications of Ansible technology,” said Anderson. “In addition to the data from Ansible Galaxy, the model has been (and continues to be) fine-tuned with additional Red Hat and IBM IT automation subject matter expertise.” He said he believes that IT automation is a key driver of operational efficiency and frees teams up to focus on innovation. But, standing up automated workflows can be complicated and time-consuming. Ansible Lightspeed can boost the efficiency of an organization’s automation efforts and improve ROI and time to value.
“Writing quality automation code takes time and resources,” said Anderson. “Ansible Lightspeed can help developers and operations teams produce better automation code much more quickly. Again, Ansible Lightspeed isn’t intended to be a silver bullet. But it is a true enhancement to the creation experience.” He added that users can access the service directly in their code editor for a “real-time productivity boost” to their existing workflows. “How much time you’re saving depends on the complexity of the playbooks you’re developing, but when you’re trimming a task from 30 to 60 minutes to 5 or 10 minutes, multiple times a day, it adds up,” he said.
Leveraging IBM Research LLM According to the company, the development of the tool involved leveraging a large language model (LLM) derived from IBM Research. IBM contributed its expertise in the field of LLM, while Red Hat contributed their specific domain knowledge to train the model using publicly available Ansible automation content.
This collaborative effort also included post-recommendation training based on subject matter expertise, highlighting the combined strengths of Red Hat’s domain expertise and IBM’s proficiency in LLMs, foundation models and AI.
“This uses generative AI from IBM’s foundation model trained on a specific domain (Ansible), to help people create automation faster,” Anderson explained. “Existing subject matter experts will be much more efficient by filling out a lot of the repetitive pieces of code as they’re creating an automation playbook, which is ultimately YAML code. This accelerates their ability to generate that a lot faster. Ansible Lightspeed makes existing subject matter experts far more efficient by doing a lot of the work for them.” Anderson added that IBM’s CIO team actively participated as early testers of Ansible Lightspeed with IBM Watson Code Assistant, resulting in notable productivity improvements.
Seamless accessibility tailored to IT environments In addition, during the pilot phase, the preview version of Watson Code Assistant proved instrumental in assisting IBM CIO teams in generating approximately 60% of their accurate code while adopting the Ansible automation platform.
The tool offers users accessibility through the Ansible VSCode extension, enabling them to interact directly with the AI within their code editor. Users can prompt the AI, evaluate suggestions, and make modifications or accept/reject them, with the convenience of incorporating the generated code into an Ansible Playbook.
In addition, Ansible Lightspeed operates within the user’s IT environment, acquiring knowledge and providing recommendations for variables and settings tailored to meet specific requirements.
Additionally, the tool boasts pre- and post-processing capabilities, ensuring all code recommendations align with recognized best practices in Ansible and automation. This feature enables users to confidently leverage generative AI, knowing that the suggestions adhere to established guidelines and standards.
“All generated code recommendations are backed by “content source matching,'” said Anderson. “That means that users can see the specific URL and path of where the code was pulled from, a description of the data source, the license under which the code is covered and the type of Ansible content it is. All Ansible Galaxy users will have the choice to opt out of having their code used as data to train the Ansible Lightspeed foundation model.” The promising future of automation empowered by generative AI Anderson said Red Hat recognizes the potential of foundational models to deliver significant business value.
Data scientists and developers can enhance accuracy by adapting these models to specific use cases like writing automation code.
However, the initial training of these models demands considerable infrastructure and resources including specialized tools and platforms, even before addressing serving, tuning and management.
These are challenges that Red Hat OpenShift AI can help address by providing a foundation that is already familiar to the enterprise IT organizations that need to manage AI infrastructure, and can still meet needs of data scientists and app developers, said Anderson.
“We do see domain-specific AI being a key factor in future adoption — taking a model and shaping it to meet a specific need for an organization is incredibly valuable,” he said. “This helps create unique AI-enabled applications, and with a foundation like OpenShift AI, you can run it on a manageable, scalable platform that still fuels further innovation.” He explained that the company aims to broaden the accessibility of AI to enterprises across the hybrid cloud.
“This could [include] organizations that want to use foundational models in-house but need a platform that they can use, or it could be a business that just wants to reap the benefits of an AI-driven application without managing any of the plumbing,” he added. “Red Hat’s goal is to support both of these paths via open standards-based approaches and bring customers choice — choice in tooling, choice in deployment method and choice in how they consume the final product.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Kumo gets deep learning into Snowflake Data Cloud via Snowpark | VentureBeat"
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"https://venturebeat.com/ai/kumo-empowers-deep-learning-in-snowflake-data-cloud-through-snowpark-container-services"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Kumo empowers deep learning in Snowflake Data Cloud through Snowpark Container Services Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Kumo , a deep learning platform for relational data, announced today at Snowflake Summit 2023 its integration of deep learning capabilities directly into the Snowflake Data Cloud through Snowpark Container Services.
Snowflake’s recently introduced Snowpark Container Services expands the functionality of Snowpark , which allows developers to write code in their preferred language and run that code directly on Snowflake. This Container Services update allows organizations to run third-party software and full-stack applications within their Snowflake accounts.
According to Snowflake, with this integration customers can maximize their data potential by using cutting-edge tools while maintaining data security and eliminating the need for data movement.
Moreover, Snowpark Container Services includes GPU support, which gives data science and machine learning teams a way to accelerate development and bridge the gap between model deployment and consistent data security and governance throughout the AI/ML lifecycle.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Kumo is one of the early adopters of Snowpark Container Services, using the technology to deploy advanced neural networks for enterprises.
Kumo’s predictive AI platform employs graph neural network (GNN) technology, empowering developers, data scientists, analysts and business owners to create and implement highly accurate predictions in production.
Graph neural networks and AI Traditional machine learning requires extracting data from a data warehouse or lake, followed by manual feature development and tuning. The new integration, now available in private preview, lets joint users operate directly on raw Snowflake tables; generate predictions; and store the results as additional tables within Snowflake.
“The new integration will run Kumo’s AI services directly on relational tables over the cloud without the intermediate steps found in traditional machine learning, such as training set generation and feature engineering, by using graph neural network technology,” Vanja Josifovski, co-founder and CEO of Kumo, told VentureBeat.
Josifovski highlighted that users can create and execute a query that offers predictions, mirroring the process of querying past data for analysis, all without the need to export data from their Snowflake environment.
The announcement follows a recent collaboration between Nvidia and Snowflake that allows customers to customize their generative AI models through the cloud to suit their specific enterprise requirements.
The integration enables organizations to develop generative AI applications using their proprietary data within Snowflake’s Data Cloud environment, eliminating the need to transfer data externally.
Facilitating deep learning-based predictive analytics over the cloud According to Kumo’s Josifovski, Snowpark Container Services will allow customers to directly utilize Kumo’s predictive AI service within Snowflake for conducting graph learning predictions on their enterprise data.
(Come learn more about data and AI in the enterprise at VB Transform on July 11 & 12 in San Francisco, our networking event for enterprise technology decision makers.) “An age-old question regarding machine learning and data warehousing has been around where the ML processing runs. By changing the paradigm to run the ML processing in the Snowflake Data Cloud, our companies allow users to expand the use of machine learning and predictions to everyone who has access to the Data Cloud,” Josifovski told VentureBeat. “This is done under a single security program which is much more simplified than operating under multiple security programs.” Modern AI methods heavily depend on linear algebra calculations, which are highly compatible with GPU processing. Previously, to utilize GPUs, Kumo had to extract the data from the customer’s account and process it externally. With this integration, all data processing occurs directly within the customer’s Snowflake account, including GPU processing.
“The approach of not needing a training set and feature engineering shortens the AI/ML lifecycle significantly,” he added. “We aim to relieve data scientists from repetitive and tedious tasks, to focus on higher-level tasks of defining the right predictive task, evaluating the results and finding the best way to obtain business value from the predictions.” The company introduced a distinctive feature through this offering: deep learning-driven relational data GNNs.
These deep learning-driven GNNs can learn from the graph and associated attributes, which are determined by non-key columns of the data. Once a graph is constructed, multiple AI/ML tasks can be efficiently trained on the same graph without creating separate training sets or numerous engineered features.
Kumo also offers a scalable and innovative autoML algorithm that alleviates the burdensome process of hyperparameter tuning.
“While GNNs are very effective for a wide range of predictive problems, they are also hard to implement, scale and make efficient. Kumo’s AI platform eliminates the need for graph creation, which requires familiarity with GNNs and optimization task creation. To specify the AI/ML task, Kumo has implemented a predictive query language,” said Josifovski.
Streamlining predictive analytics for citizen developers Josifovski says that predictive AI/ML currently requires highly skilled specialists with narrow expertise. The lifecycle involves experimenting with features, necessitating substantial infrastructure support for training and inference (scoring).
He explained that the objective of the new integration is to offer users a streamlined workflow, irrespective of their proficiency in data science.
They can then easily apply predictive graph learning in diverse business domains like customer acquisition, loyalty, retention, personalization and fraud detection. His company asserts that an entire AI-based analysis can be completed in a few hours.
“Kumo allows users to run queries over the relational data without requiring a deep understanding of AI/ML concepts, while providing control of the training and inference for skilled data scientists,” said Josifovski. “This way, the platform allows a wide range of users to use it, similarly to how data warehouses are used today for analytics.” Additionally, Kumo highlighted that the native integration with Snowflake facilitates the installation and usage of the product without requiring security and legal privacy reviews. This reduces barriers and significantly shortens the time to achieve value.
The company is confident that this will expedite experimentation and deployment of detailed predictions, enabling and improving practices such as customer acquisition, personalization, entity resolution and other predictive tasks.
“In enterprises, many teams issue SQL queries over a data warehouse to obtain analytics that professionals then consume to chart future actions,” Josifovski told VentureBeat. “Kumo will allow users to obtain actionable predictions in an automated manner, without requiring professional interpretation.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"IBM expands Adobe partnership to accelerate content supply chains with generative AI | VentureBeat"
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"https://venturebeat.com/ai/ibm-expands-adobe-partnership-accelerate-content-supply-chains-generative-ai"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages IBM expands Adobe partnership to accelerate content supply chains with generative AI Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
IBM and Adobe are joining forces to enhance content supply chains using AI technology. IBM announced that it will expand its existing collaboration with Adobe to leverage Adobe Sensei GenAI services and Adobe Firefly , a suite of creative generative AI models (currently in beta). Additionally, IBM Consulting will introduce a new range of Adobe consulting services to assist clients in navigating the complex generative AI landscape.
IBM said that this collaborative effort will specifically concentrate on helping clients create personalized customer experiences, develop rich customer personas, and design customized journeys through generative AI.
“To effectively leverage these enhanced capabilities, embedding the required process steps within Adobe’s Workfront technologies will deliver the collaboration and speed desired while ensuring visibility, governance, and brand integrity,” Matt Candy, global managing partner, IBM iX customer and experience transformation at IBM Consulting, told VentureBeat.
IBM says that brands will now be able to launch campaigns, experiences and products faster and with more confidence and precision, maximizing their impact on the business.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! The companies have set their sights on establishing an integrated content supply chain ecosystem that enhances efficiency, automates tasks and improves visibility for stakeholders involved in design and creative projects. They will harness Adobe’s AI-accelerated Content Supply Chain solution and IBM’s consulting services to achieve this goal.
Under this expanded partnership, Adobe’s enterprise customers will gain access to IBM Consulting’s team of experts, consisting of 21,000 experienced data and AI consultants. These experts will assist clients implement generative AI models into the design and creative process.
“Our global experts are certified in Adobe technologies [and] deeply understand Adobe’s tools to help our clients maximize the technology and workflows while also helping to ensure [that] transparency and explainability are embedded into their creative process,” IBM’s Candy told VentureBeat. “We will also help integrate Adobe’s AI-accelerated Content Supply Chain solution with our clients’ proprietary customer data, brand guidelines and IP, so organizations don’t have to worry if they are using the right content and [whether] it is consistent with the brand.” The services provided will include the use of Firefly, initially focused on generating images and text effects, and Sensei GenAI services, which function as a copilot for marketers embedded in Adobe’s enterprise applications.
Streamlining content workflows through generative AI IBM said that its expanded partnership with Adobe aims to capitalize on the growing momentum in AI adoption, enabling brands to create highly personalized customer experiences that drive growth and productivity. With a focus on trust, transparency and brand consistency, the company said that the partnership seeks to redefine the possibilities of AI-powered experiences while elevating business decisions.
>>Follow VentureBeat’s ongoing generative AI coverage<< IBM’s Candy stated that IBM Consulting is collaborating closely with Adobe clients to assist them in preparing their internal data sources and structures. Additionally, they are helping clients identify suitable use cases, estimate the impact on value, and evaluate and recommend technologies to adopt.
“We are assisting our clients in training and customizing foundational models (FMs) and LLMs using both company and customer datasets,” he said. “We prioritize establishing guardrails to address bias and maintain a brand voice.” Candy emphasized that IBM’s consultants have the expertise to use the complete generative AI technology stack, encompassing foundation models and over 50 domain-specific classical machine learning accelerators. This comprehensive range of tools enables them to expedite progress for clients.
“We use our unique IBM Garage method to co-create with clients and work together to build their ideas and bring them to enterprise scale,” he explained. “For example, we work with clients to develop prioritized AI use cases, define the technology roadmap, assets and tools to support those use cases, and develop the human-centric design and operating model needed to bring the use cases up to enterprise scale.” IBM’s long-term vision for AI IBM stated that its marketing transformation journey had laid the foundation for introducing these new services. The company has actively supported Adobe in enhancing its marketing team’s work management as part of its collaboration.
The expanded collaboration is built upon a strategic partnership of 20 years, which has encompassed technology and services. Notably, Adobe embraced Red Hat OpenShift, IBM AI and Sterling software as a result of this partnership.
The company highlighted that through its global client engagements, it has witnessed a shift in business approach from “plus AI” to “AI-first.” This transition signifies that AI is now deeply integrated into enterprises’ core operations.
IBM said it is actively reimagining work processes and fundamentally transforming tasks by leveraging AI technologies such as foundation models and generative AI.
“We’re helping clients around the globe and in every industry to embed AI in the ‘heartbeat’ processes of the enterprise,” said Candy. “Our experience tells us that getting to value for AI in business takes a deep understanding of the complexities involved in an enterprise and a human-centered, principled approach to using AI — and that won’t change anytime soon.” >>Don’t miss our special issue: Building the foundation for customer data quality.
<< VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Envoy unveils workplace occupancy analytics solution to empower informed decision-making | VentureBeat"
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"https://venturebeat.com/ai/envoy-unveils-workplace-occupancy-analytics-solution-to-empower-informed-decision-making"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Envoy unveils workplace occupancy analytics solution to empower informed decision-making Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
San Francisco-based workplace platform Envoy today announced the launch of Envoy Workplace , a unified workplace occupancy analytics tool. This captures data from various sources, such as door access scans, WiFi usage and employee sign-ins, providing organizations with an accurate depiction of workplace activities. Envoy claims that Workplace empowers organizations to gain insights into on-site teams and workspace utilization across all locations, facilitating informed decision-making.
According to the company, the tool is the sole fully-integrated solution in the market, combining all the necessary components to manage and optimize workplaces for better experiences. In addition, the analytics tool addresses the most persistent obstacles to creating excellent workplaces, such as fragmented data, space inefficiency and poor employee experience.
Users can conveniently access unified analytics , desk and room booking capabilities, and seamless delivery management in one centralized location.
“Envoy Workplace will be critical in empowering companies to confidently make the bold decisions necessary for survival,” Envoy founder and CEO Larry Gadea told VentureBeat. “Workplace provides companies with a real-time pulse on their space utilization with accuracy never-before-seen. Envoy Workplace aggregates door access data, WiFi data and other passive signals to give a unified, big-picture view of the office.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Hybrid awareness The tool provides hybrid-aware automatic scheduling of desks, automatic resizing of meeting rooms based on attendance and a centralized app to view coworkers’ seats, among other features. The company emphasized that it is designed to focus on employee experience, productivity and modernizing outdated practices.
“Every other solution uses one source of end data,” said Gadea. “For example, some use employee sign-ins, some building badge swipes, but we’re the only ones using multiple signals for the greatest accuracy. Since we pull from multiple sources passively, we have redundancy — so we deliver the most accurate, reliable picture of what’s happening in the workplace: Which teams are on site, and how they’re using their space at each location.” The platform links to more than 100 frequently used workplace tools and data streams. It consolidates the information and functionality of all these tools to assist customers in automating tasks and obtaining actionable insights on enhancing their workplace.
Enhancing workplaces through real-time analytics Envoy’s occupancy analytics system captures data from various sources, including door access badge scans, WiFi connections, desk and meeting room check-ins and employee app sign-ins. The tool operates by providing accurate and timely insights into global occupancy, as well as desk and meeting room utilization, for effective planning and decision-making.
The company believes that this system will assist organizations in identifying opportunities to optimize efficiency by either expanding or reducing resources to align with the number of individuals entering the workspace.
Moreover, it allows for measuring the long-term effects of return-to-office policies and strategies by analyzing attendance data categorized by time, team or department.
The system also includes pre-configured reports that can be exported and shared with executives and stakeholders, delivering detailed responses to critical questions.
“Envoy’s analytics takes the guesswork out of workplace planning,” said Gadea. “What we’re doing is giving leaders reliable occupancy and space usage data to understand how people use desks, rooms and team neighborhoods. We’re helping our customers build a cost-efficient, productive work environment based on how people use their space by providing them with the information they need to make informed space planning and management decisions and to make the most of their workplace budget.” Image Source: Envoy Streamlining workplace insights for decision-makers According to Gadea, leaders can better understand future expectations by utilizing precise historical trends segmented by the day of the week or frequency. Assessing and appropriately adjusting office footprints is the most prevalent scenario.
“Looking at occupancy over a period of time, you can better predict what type of resources you might need, like snacks, lunch or reception coverage,” said Gadea. “By optimizing usage of resources like desks or meeting rooms, you can compare how many desks and rooms are being used on an average day, then right-size the ratio based on those insights.” Gadea highlighted that companies have transitioned to distributed and smaller offices. As a result, obtaining a comprehensive and standardized understanding of space, untouched by regional, team and industry biases has become increasingly challenging.
Portfolio aggregation capabilities The platform’s portfolio aggregation feature will benefit the facilities staff and ensure an exceptional roaming experience for out-of-city or remote employee visits, said Gadea.
“Our global occupancy analytics gives a bird’s eye view into utilization and key occupancy stats across every location in your portfolio,” Gadea added. “Our approach allows us to unify the different tech stacks across locations so that our customers get standardized data from our analytics.” Furthermore, he said: “Whether workplace leaders manage one location or 500, they can access a global view to see how occupancy trends differ across locations. Automatically compiling the data saves the time and hassle of manually pulling data for each location.” Data-driven planning The app empowers employees to be more effective and workplace managers to make data-driven decisions, said Gadea. Envoy has has been developing first-party products for years, he said, which allows them to unify and aggregate information to provide more accurate data.
“In the past, analysts on the finance and workplace teams needed to manually combine everything in Tableau, Excel and other tools,” said Gadea. “Not only was it labor-intensive, but it was error-prone and tricky because of deduplication and redundancy.” He added: “We’ve made the workplace admin’s job much easier. Getting executives and other stakeholders the reports they need to drive important workplace decisions is no longer a major inconvenience. With Envoy, it takes minutes to get accurate data. The information is available on-demand and not dependent on a manual process or analyst bandwidth.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Bluesky helps optimize cloud workloads with cost governance algorithms | VentureBeat"
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"https://venturebeat.com/ai/bluesky-helps-curb-machine-learning-costs-with-cost-governance-algorithms"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Bluesky helps optimize cloud workloads with cost governance algorithms Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Query optimization isn’t necessarily new. Cost governance in the cloud to identify and control expenses for queries isn’t new, either. What is new, however, is Bluesky , a cloud-based workload optimization vendor, focused on Snowflake , that launched earlier this month to help organizations achieve these objectives.
One of the critical elements in the company’s approach is “the algorithms that we created ourselves, based on each of our past 15 years’ experience tuning workloads at Google, Uber, and so on,” said Mingsheng Hong , Bluesky CEO.
Hong is the former head of engineering for Google’s machine learning runtime capabilities, a role in which he worked extensively with TensorFlow. Bluesky was cofounded by Hong and CTO Zheng Shao, a former distinguished engineer at Uber, where he specialized in big data architecture and cost reduction.
The algorithms Hong referenced analyze queries at scale, predominantly in cloud settings, and determine how to optimize their workloads, thereby decreasing their costs. “Individual queries rarely have business value,” Hong observed. “It’s a combination of them that together achieve certain business goals, like transforming data and providing business insights.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! What’s particularly interesting is Bluesky combines both statistical and symbolic artificial intelligence (AI) approaches for this task, tangibly illustrating that their fusion may influence AI’s future in the enterprise.
Cost governance of queries There are several ways in which Bluesky reinforces cost governance by optimizing the amount of time and resources dedicated to querying popular cloud sources. The solution can curb query redundancy via incremental materialization, a useful function for recurring queries in set increments, like hourly, daily or weekly.
According to Hong, when analyzing monthly revenue figures, for example, this capability enables systems to “materialize the prior computation and only compute the incremental part,” or the delta since the last computation. When applied at scale, this feature can conserve a considerable amount of fiscal and IT resources.
Tuning recommendations Bluesky delivers a detailed amount of visibility into query patterns and their consumption. The solution offers an ongoing list of the most expensive query patterns, as well as other techniques to “show people how much they’re spending,” Hong said. “We break it down to individual users, teams, projects, call centers and so on, so everybody knows how much everybody else is spending.” Bluesky incorporates algorithms that involve statistical and non-statistical AI approaches for profile-driven, query cost attribution. Query profiles are based on how much time, CPU and memory that specific queries require. The algorithms employ this information to reduce the use of such resources for queries via tuning recommendations for modifying the query code, data layout and more. “Optimization is not just the compute,” Hong noted. “Also, we organize the storage: the table indices, how you lay out the tables, and then there are warehouse settings and system settings that we tweak.” Rules and supervised machine learning Significantly, the algorithms providing such recommendations and analyzing the factors Hong mentioned involve rules-based approaches and machine learning. As such, they combine AI’s classic knowledge-representation foundation with its statistical one. There are abundant use cases of such a tandem (termed neuro-symbolic AI) for natural language technologies. Gartner has referred to the inclusion of both of these forms of AI as part of a broader composite AI movement. According to Hong, rules are a natural fit for query optimization.
“This is like query optimization starting with rules and you enrich them with the cost model,” he reflected. “There are cases where trying to run a filter is always a good idea. So that’s a good rule. To eliminate a full table scan, that’s always good. That’s a rule.” Supervised learning is added when implementing rules based on cost conditions or the cost model. For instance, eliminating queries with a poor ROI is a useful rule. Supervised learning techniques can ascertain which queries fit this classification by scrutinizing the past week’s worth of queries, for example, before eliminating them via rules. “If a query is failing more than 98% of the time over the last seven days, you can put such a query pattern into a penalty box,” Hong remarked.
Curbing costs The need to lower enterprise costs, particularly as they apply to multicloud and hybrid cloud settings, will surely increase over the coming years. Cost governance and workload optimization methods that optimize queries are helpful for understanding where costs are increasing and how to reduce them. Relying on automation that uses both statistical and non-statistical AI to identify these areas, while offering suggestions for rectifying these issues, may be a harbinger of where enterprise AI is going VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Why privacy-preserving synthetic data is a key tool for businesses | VentureBeat"
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"https://venturebeat.com/programming-development/why-privacy-preserving-synthetic-data-is-a-key-tool-for-businesses"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Why privacy-preserving synthetic data is a key tool for businesses Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The tangible world we were born into is steadily becoming more homogenized with the digital world we’ve created. Gone are the days when your most sensitive information, like your Social Security number or bank account details, were merely locked in a safe in your bedroom closet. Now, private data can become vulnerable if not properly cared for.
This is the issue we face today in the landscape populated by career hackers whose full-time jobs are picking into your data streams and stealing your identity, money or proprietary information.
Although digitization has helped us make great strides, it also presents new issues related to privacy and security, even for data that isn’t wholly “real.” In fact, the advent of synthetic data to inform AI processes and streamline workflows has been a huge leap in many verticals. But synthetic data, much like real data, isn’t as generalized as you might think.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! What is synthetic data, and why is it useful? Synthetic data is, as it sounds, made of information produced by patterns of real data. It’s a statistical prediction from real data that can be generated en masse. Its primary application is to inform AI technologies so they can perform their functions more efficiently.
Like any pattern, AI can discern real happenings and generate data based on historical data. The Fibonacci sequence is a classic mathematical pattern where each number in the sequence adds the prior two numbers in the sequence together to derive the next number. For example, if I give you the sequence “1,1,2,3,5,8” a trained algorithm could intuit the next numbers in the sequence based on parameters that I’ve set.
This is effectively a simplified and abstract example of synthetic data. If the parameter is that each following number must equal the sum of the previous two numbers, then the algorithm should render “13, 21, 34” and so on. The last phrase of numbers is the synthetic data inferred by the AI.
Businesses can collect limited but potent data about their audience and customers and establish their own parameters to build synthetic data. That data can inform any AI-driven business activities, such as improving sales technology and boosting satisfaction with product feature demands. It can even help engineers anticipate future flaws with machinery or programs.
There are countless applications for synthetic data, and it can often be more useful than the real data it originated from.
If it’s fake data, it must be safe, right? Not quite. As cleverly as synthetic data is created, it can just as easily be reverse-engineered to extract personal data from the real-world samples used to make it. This can, unfortunately, become the doorway hackers need to find, manipulate and collect the personal information of user samples.
This is where the issue of securing synthetic data comes into play, particularly for data stored in the cloud.
There are many risks associated with cloud computing, all of which can pose a threat to the data that originates a synthesized data set. If an API is tampered with or human error causes data to be lost, all sensitive information that originated from the synthesized data can be stolen or abused by a bad actor. Protecting your storage systems is paramount to preserve not only proprietary data and systems, but also personal data contained therein.
The important observation to note is that even practical methods of anonymizing data don’t guarantee a user’s privacy. There is always the possibility of a loophole or some unforeseen hole where hackers can gain access to that information.
Practical steps to improve synthetic data privacy Many data sources that companies use may contain identifying personal data that could compromise the users’ privacy. That’s why data users should implement structures to remove personal data from their data sets, as this will reduce the risk of exposing sensitive data to ill-tempered hackers.
Differentiated data sets are a mode of collecting users’ real data and meshing it with “noise” to create anonymous synthesized data. This interaction assumes the real data and creates interactions that are similar to, but ultimately different from, the original input. The goal is to create new data that resembles the input without compromising the possessor of the real data.
You can further secure synthetic data through proper security maintenance of company documents and accounts. Utilizing password protection on PDFs can prevent unauthorized users from accessing the private data or sensitive information they contain. Additionally, company accounts and cloud data banks can be secured with two-factor authentication to minimize the risk of data being improperly accessed. These steps may be simple, but they’re important best practices that can go a long way in protecting all kinds of data.
Putting it all together Synthetic data can be an incredibly useful tool in helping data analysts and AI arrive at informed decisions. It can fill in gaps and help predict future outcomes if properly configured from the onset.
It does, however, require a bit of tact so as to not compromise real personal data. The painful reality is that many companies already disregard many precautionary measures and will eagerly sell private data to third-party vendors, some of which could be compromised by malicious actors.
That’s why business owners that plan to develop and utilize synthesized data should set up the proper boundaries to secure private user data ahead of time to minimize the risks of sensitive data leakages.
Consider the risks involved when synthesizing your data to remain as ethical as possible when factoring in private user data and maximize its seemingly limitless potential.
Charlie Fletcher is a freelance writer covering tech and business.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The quandary of Kubernetes: How Rafay is helping curb cloud spending | VentureBeat"
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"https://venturebeat.com/programming-development/the-quandary-of-kubernetes-how-rafay-is-helping-curb-cloud-spending"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages The quandary of Kubernetes: How Rafay is helping curb cloud spending Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Kubernetes is experiencing record growth — according to one survey, 96% of organizations are using or evaluating the open-source container orchestration system.
But ever-expanding Kubernetes environments result in growing clusters, application teams and infrastructure. In turn, this translates to increased spending, as well as difficulty in understanding just where and how that spending is occurring.
“Without controls or limits, an individual application team can overprovision resources for their application, without knowing the full cost impact of utilizing these resources, resulting in wasted spend,” said Mohan Atreya, SVP of product and solutions at Rafay.
To help mitigate this, Rafay — a Kubernetes management and operations platform — today launched Cost Management Service, a new tool intended to provide real-time visibility and allocation of Kubernetes cloud costs.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! When organizations attempt to do it on their own, “Kubernetes cloud cost management across multiple clusters, application teams and infrastructure is a challenging ambition,” said Atreya.
Increased use, complexity Originally designed by Google, Kubernetes automates software deployment, scaling and management in hybrid and multi-cloud environments.
One of its many advantages is that its workloads can operate in single clouds, private data centers or across multiple cloud environments, said Atreya. This allows organizations to use it to deploy and manage applications in a more agile, scalable way, while simultaneously avoiding cloud vendor lock-in.
Since Kubernetes also provides container integrations and access to different cloud providers, processes are more efficient for devops and platform teams, said Atreya. It is reliable because, if one node in a multi-node cluster fails, an application is redistributed to others without disrupting users of the application.
Furthermore, Kubernetes provides self-healing capabilities and will automatically restart, reschedule or replace an application (or parts of an application) when it fails. And, its autoscaling capabilities allow applications to scale up and down based on actual demand.
“This positively impacts end-user performance, along with budget management,” said Atreya.
But this benefit is only so long as cluster environments are appropriately managed — which, oftentimes, they aren’t, he pointed out.
Cloud cost optimization Today, 81% of organizations are using multi-cloud infrastructures (or will be soon). At the same time, 94% are overspending in the cloud.
Kubernetes’ resource consumption and spending only contribute to this, said Atreya.
Organizations aim to save money by having multiple application and business teams run Kubernetes workloads in the same clusters, he said. But this is ultimately counterintuitive, as it creates a challenge in viewing total cloud spend, evaluating what resources each team is using, and reporting how spend is allocated across departments.
Rafay — which competes with Mirantis Kubernetes Engine, Google Kubernetes Engine, Portainer and D2iQ, among others — has integrated its new cost management service into its existing Kubernetes Operations Platform (KOP).
The new tool provides organizations the ability to accomplish the following: – View and access cost metrics based on roles by pre-integrating with RBAC (application, FinOps and platform see cost metrics upon login).
– Optimize cloud budget by appropriately billing internal teams based on their resource consumption of shared resources.
– Create custom dashboards to view aggregated cost metrics for different internal groups and departments.
– Configure and implement cost management on a fleet of Kubernetes clusters with a single click.
Cost management: A team sport For example, Atreya pointed out, one Rafay customer — a large, global real estate services firm — has standardized on Rafay’s platform to provide application teams a self-service experience. The firm’s strategy is to empower various business units and application teams to select from several deployment options for Kubernetes infrastructure through a centralized platform and provide them visibility into associated costs.
“This level of transparency and flexibility allows the application teams to select the most optimal option, balancing application requirements and their budgets,” said Atreya.
Ultimately, application teams that have visibility into resource utilization metrics as well as associated infrastructure costs are better prepared to make decisions on cost-saving strategies (such as resource requests tuning or cluster sharing), he said.
Organizations should provide incentives to help application teams transition from treating cost management as good hygiene, rather than a burden. For example, Rafay has seen organizations implement internal awards for the most cost-effective application in their portfolio.
Platform teams should also provide well-documented, easy-to-use internal frameworks and best practices that application teams can use without much effort. For instance, a simple application onboarding questionnaire that recommends ideal approaches — such as “namespace on a shared cluster,” “workspace with multiple namespaces on a shared cluster,” or “dedicated cluster.” Rather than limiting access to cost data to a central team that then periodically disseminates this downstream, “it is more effective to democratize access and visibility to cost data,” said Atreya.
“Cost management is a team sport,” said Atreya. “Therefore, it is important to have the application teams be active participants in the process.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"The power and possibilities of no-code: Creatio releases first vendor-agnostic playbook | VentureBeat"
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"https://venturebeat.com/programming-development/the-power-and-possibilities-of-no-code-creatio-releases-first-vendor-agnostic-playbook"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages The power and possibilities of no-code: Creatio releases first vendor-agnostic playbook Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
There’s no question that there’s a dearth of technical talent : Tech leaders and experts are constantly decrying the situation and warning of dire long-term results. At the same time, becoming a developer takes important training, not to mention general interest in, and inclination to, the discipline.
The emerging solution to these swirling factors (according to some, at least): Drag-and-drop no-code tools that enable users with no technical knowledge whatsoever to design and quickly deliver custom apps.
“No-code is an amazing way to accelerate automation inside your organization,” said Katherine Kostereva, CEO of no-code platform Creatio.
To foster more widespread no-code use, Creatio today announced the vendor-agnostic “No-Code Playbook,” co-authored by Kostereva and product management expert Burley Kawasaki. The company will officially release the playbook in a live event today (at 10 a.m. ET) featuring a discussion with Silicon Valley pioneer Steve Wozniak.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! “We wrote the book to address the unique nature of no-code development so that organizations can maximize their business outcomes while adopting it,” said Kostereva.
Demand for apps, but not enough developers According to Grid Dynamics , the world is currently short 40 million skilled tech workers. The staff augmentation firm estimates that dearth to exceed 85 million by 2030.
Similarly, in a survey of more than 1,000 C-suite executives conducted by Harris Poll on behalf of Stripe2, 61% said they believed access to developer talent is a threat to the success of their business — an even bigger threat than lack of access to capital. Furthermore, the survey found that developers spend 42% of their time maintaining and debugging existing code, further reducing their ability to put energy into sources of new software innovation or differentiation.
These factors have led to an explosion in the number of no-code tools like Creatio’s: According to Emergen Research , the global no-code development platforms market size was $12.2 billion in 2020 and is expected to reach $68.1 billion by 2028, representing a compound annual growth rate (CAGR) of more than 24%.
Big players including Microsoft and Salesforce offer no-code platforms; other, more specialized companies vying in the space include Appy Pie, Quickbase, Zoho, Airtable and AppSheet.
No-code, explained With no-code tools, work is initially done “under the hood,” so to speak, by traditional developers, explained Kostereva.
Down the line, non-developers can participate in the application development process through visual drag-and-drop tools. Users compose the forms, workflows and data needed to build an application without needing to understand a programming language or having formal software development training.
The benefits? Apps are faster to start and finish, alignment is improved and agility is increased, according to Kostereva.
Ultimately, she compared the level of no-code disruption to the introduction of cloud computing in the early 2010s.
Millions of knowledge workers around the world — in sales, marketing, production or finance, for example — are leveraging no-code, thus decreasing dependency on technical resources, she said.
“Digital transformation is at the forefront of the C-suite agenda, and enterprises around the globe are seeking new ways to keep up with business automation demands,” said Kostereva. “The no-code approach enables organizations to significantly accelerate time-to-market and increase alignment between business and IT.” But first, debunking myths Much as there is much excitement around no-code — and the lauding of its benefits — there are misperceptions, too.
Most notably, said Kostereva: No-code can’t be used in large organizations. But “this is a stereotype, a myth.” While it is most definitely helpful for small organizations in areas of website creation and approval processes, she said there are many examples of larger organizations using no-code to automate very complex workflows.
“Not all mission-critical scenarios demand professional developers,” wrote Kostereva and Kawasaki. “An application’s level of business criticality has more to do with the selection of the business process and domain.” Another concern is that no-code tooling will put software developers out of work. “This is definitely so far from being true,” she said. There is already a much-lamented shortage; this will help augment developers’ work and close talent gaps.
There is also the inaccurate misperception that no-code is different from low-code, which does require at least some coding knowledge. No-code doesn’t require any, and it can be used alongside low-code tools and traditional coding.
“You can very, very quickly change your workflow automation,” said Kostereva.
Whereas traditional development might take years, no-code can push out applications almost immediately.
“That’s the value that we wanted to bring to the world — explain that you can do it really fast,” she said. “We see how much value no-code brings to people and organizations. The whole idea is to explain how to use no-code tech correctly to automate processes.” No-code in use “The No-Code Playbook” is focused on enterprise automation, explained Kostereva. While there are many no-code tools for simple processes, real disruption comes with large organizations that have sophisticated demands.
“They get a lot of value of no-code as a methodology,” she said.
The book emphasizes design, go-live and everyday delivery and is based on three principles: Use no-code to gather requirements and prototype on the fly.
Everything that can be developed with no-code, should be developed with no-code. Or, as Kostereva emphasized: “Don’t custom code, do it with no-code.” Deliver to end-users as fast as you can.
The no-code lifecycle The book includes a step-by-step description of the no-code lifecycle: “design,” “go live” and “everyday delivery.” It also helps organizations apply the right deployment strategy. These include: Do-it-yourself: The simplest delivery model, where primary roles of the no-code project are contained within a team sitting inside a single business unit.
Center of excellence: Typically owned and led by a single overall cross-functional leader. Skilled knowledge workers are missioned with maximizing efficiency through consistent definition and adoption of best practices across the organization.
Fusion-team delivery: A multidisciplinary team where members from the business side collaborate with IT. Typically, this model is used when there are greater technical requirements and complexity requiring software developers to build some components of no-code applications.
Also included in the playbook are several tools for assessing application complexity; there is also a no-code governance model and description of no-code project roles.
Kostereva underscored the fact that the book is vendor agnostic. The ultimate goals are to advance the industry, standardize best practices and increase the adoption of no-code technologies across midsize and enterprise-level organizations.
“We are truly passionate about creating a community around no-code,” she said.
The electronic version of the book will be available on Amazon and via the Creatio website; the printed version will be available later this year.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"The hottest IT skills for 2023 – even in a recession | VentureBeat"
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"https://venturebeat.com/programming-development/the-hottest-it-skills-for-2023-even-in-a-recession"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages The hottest IT skills for 2023 – even in a recession Share on Facebook Share on X Share on LinkedIn Photo by Christina Morillo: https://www.pexels.com/photo/woman-sitting-while-operating-macbook-pro-1181676/ Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
“It was the best of times, it was the worst of times,” wrote Charles Dickens in his 1859 novel “A Tale of Two Cities.” If he’d been writing today, that statement could very much apply to today’s IT personnel and hiring landscape.
For many of the hundreds of thousands who’ve been laid off by tech companies recently, this might well be considered the worst of times — especially with a recession looming. Yet there are plenty among them, and others in the workforce, who could consider this the best of times. Why? Because they possess the most in-demand skillsets and certifications. Despite the layoffs, cutbacks, tightening pursestrings, and general doom and gloom presented in the media, these IT professionals can look forward to higher pay, plenty of offers, perpetual headhunting inquiries and even the occasional bidding war for their talents.
Below are some of the hottest skills and certifications in IT, in no particular order.
Filling the IT skills gap First, Foote Partners ’ IT Skills Demand and Pay Trends Report provides a list of the rising stars among IT skills and certifications. Many of the top skills are in cybersecurity.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Security auditing With the market value of this skill rising by almost 20% in the last six months, security auditing is very much in demand. Cyber-insurers have gotten stingy about whom they offer policies to and what those policies cover. They are interrogating businesses about their policies, practices and tools. Security audits are one way they can find out what is going on. But organizations are using them too. Bringing in outside eyes helps them find blind spots.
>>Don’t miss our special issue: Zero trust: The new security paradigm.
<< “A security audit will provide a roadmap of an organization’s main information security weaknesses, and identify where it is meeting the criteria the organization has set out to follow and where it isn’t,” said David Foote, chief analyst at Foote Partners. “Security audits are crucial to developing risk assessment plans and migration strategies for organizations, and that always deals with individuals’ sensitive and confidential information — all of which are hot issues these days.” Azure Key Vault These Azure skills have risen in market by 19% in the third quarter of 2022. Azure Key Vault is a cloud service for securely storing and accessing secrets (anything you want to tightly control access to, such as API keys, passwords, certificates and cryptographic keys).
Cryptography Cryptographic skills, which encompass areas such as encryption, VPN and SSL/TLS, are very much in demand. They jumped 20% in market value over the last six months.
Identity and access management (IAM) IAM is up 6% over six months. This field has risen in importance steadily since the COVID-19 pandemic made physical boundaries less relevant. With so many remote workers being given greater access to internal systems, identity and access problems have become a serious concern. Those who can fix such issues and implement comprehensive IAM solutions have plenty of work opportunities.
Risk analytics Digital risk analytics is growing in popularity as a niche of business intelligence (BI) development because of increased interest among risk-management professionals. It is up about 6% over the last half year. “This discipline has vastly improved the way risk managers evaluate potential scenarios and predict risk-laden events,” said Foote.
Penetration testing Penetration testing (pen testing) has gained 21.4% in market value over six months. The more distributed denial of service (DDOS), phishing and ransomware attacks that occur, the more organizations want to bring in ethical hackers to identify, update and replace the parts of their systems that are susceptible to modern hacking techniques.
“While cybercriminals and hacktivists are increasing in numbers and deepening their skillsets, the ‘good guys’ are struggling to keep pace,” said Foote.
According to Skillsoft’s 2022 IT Skills and Salary Report , the top three most challenging areas to find qualified talent are cloud computing, data analytics/big data/data science and cybersecurity.
“This year’s list is notable first by what topics continue to be hot this year — cloud foremost, supplemented by a couple of key certifications in cybersecurity and data,” says Zach Sims, general manager, tech & dev, Skillsoft. “Not surprising, given how nearly every company in every industry of every size in every geography is relying upon cloud computing to power their technology strategy.” Cybersecurity Foote Partners named some of the specific areas of cybersecurity with the biggest recent hikes in market value. But that doesn’t mean there aren’t plenty of other areas of cybersecurity desperate for competent and experienced personnel. These include application security, network security, cloud security, intrusion detection, security controls and frameworks, incident response and threat detection/modeling/ management.
Projections about the need for cybersecurity talent are bullish. Between April 2021 and April 2022, employers posted almost three quarters of a million cybersecurity openings.
Government data projects a 35% surge in cybersecurity jobs between 2021 and 2031 — more than double the expected rise in demand for general IT jobs.
Cloud computing Anyone skilled in Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), Wasabi or other cloud services such as Salesforce will have no shortage of job openings in 2023. With Microsoft Azure cloud deployments expanding by 33% year over year, and other cloud platforms experiencing similar growth, organizations are screaming for more cloud developers, engineers, architecture specialists, cloud migration skills, application programming interface (API) management skills, cloud database skills and more.
“Cloud skills are clearly in high demand,” said Foote.
Data analytics/big data/data science Both Skillsoft and Foote Partners identified data analytics, big data and date science as rich in possibilities for anyone keen to find a lucrative career path. It’s also replete with avenues and niches. Depending on the platform, the programming language, the application or the industry, data analytics and data science skills are sought after to varying degrees. Data science positions are expected to grow by 28% by 2026, with salaries ranging between roughly $125,000 and $150,000.
Those proficient in statistics, economics, information systems, computer science and programming, and who can take care of data wrangling, data intuition, querying, social media mining and data visualization should be able to pick and choose their employers. Beyond data science skills, those who can extract SQL, Excel and other data and subject it to analysis will compete well in the job market.
Artificial intelligence Those with AI skills in addition to other specialties are likely to be inundated. Last year, some 33% of IT job postings asked for AI skills. The World Economic Forum’s Future of Jobs Report predicts 97 million new AI-related jobs will be created between 2021 and 2025. Salaries are rising accordingly. Those well trained and experienced can command average salaries around $150,000.
But AI is a wide and varied subject. It takes in many skills, including machine learning, data science, algorithms, math, statistics, analytics and a variety of programming disciplines such as Python, C++, R and Java. AI applications often make heavy use of machine learning (ML), which is another in-demand skill, centered around the harnessing of algorithms that can learn without being programmed to do so. ML engineers are among the top five fastest growing jobs in the U.S. over the past five years.
A study by application development firm Reign found that the U.S. witnessed a 21% increase in AI jobs, plus a 27% increase in AI job-related wages, over the past decade.
“The demand for workers who can develop AI technology is increasing, as are the effects of AI on workers around the world,” said Felipe Silberstein, head of platform strategy at Apply Digital.
“Jobs requesting AI or machine learning skills are expected to increase by 71% in the next five years.” Devops Devops has been a buzzword over the last couple of years. Nevertheless, devops specialization is a hot skill. Residing in the interface between software development and operations as a way to shorten development cycles, devops personnel need to be knowledgeable in continuous integration, testing, microservices and infrastructure as code, as well as programming.
Beyond devops as a whole, software development will provide abundant openings in the coming decade for those skilled in JavaScript, Python, Go, Java, Kotlin, PHP, C#, Swift, R, Ruby, C and C++, and in programming tasks related to containers and Kubernetes.
Further hot skills IT in general provides plenty of channels for employment beyond those listed above. These include product and project management, as well as a variety of networking specialties: cloud, wireless, edge, software-defined networking (SDN), secure access service edge (SASE), zero trust network access (ZTNA) and software-defined wide area network (SD-WAN).
Hot certifications Those possessing certain IT certifications can demand quite a premium in the job market. Anyone wishing to move up the career ladder is advised to plot a course that includes one or more of the following certifications, listed by Global Knowledge as the top paying certs for 2022: Google Certified Data Engineer Google Certified Professional Cloud Architect Amazon Web Services (AWS) Certified Solutions Architect (Associate) Certified in Risk and Information Systems Control (CRISC) Certified Information Systems Security Professional (CISSP) Certified Information Security Manager (CISM) Their average salary for those with these certifications is more than $150,000 per year. These certs can open doors to positions such as CIO, CTO, CISO, IT manager, security manager and chief architect, as well as plenty of positions requiring cloud skills.
These certifications also scored well in the most recent salary survey from Skillsoft.
But AWS Certified Solutions Architect (Professional) rose to the top spot.
To that list, Foote Partners adds the following, based on pay that’s well above average and the most gain in market value in the past six months: GIAC Certified Forensics Analyst (GCFA) Information System Security Engineering Professional (designed for those already completing CISSP and requiring two years of practical experience developing highly secure systems) AWS Certified Security Specialty OKTA Certified Professional (specialist in ID management) — rose 57.1% in market value in six months Certificate of Cloud Security Knowledge (CCSK) Other worthwhile certs that can bring a bump in paycheck include: Cisco CCNA certification CompTIA’s Network+, Security+ or CySA+ credentials ISACA’s CISM certification AWS Certified Security — Specialty PMP: Project Management Professional Nutanix Certified Professional — Multicloud Infrastructure (NCP-MCI) Microsoft Certified Azure Solutions Architect Expert Google Cloud — Cloud Digital Leader CISA — Certified Information Systems Auditor AWS Certified Big Data — Specialty VCP-DCV 2022 — VMware Certified Professional — DataCenter Virtualization 2022 AWS Certified Cloud Practitioner CCNP Enterprise “Learning is the catalyst for mutually beneficial growth for employees and employers, especially as organizations struggle to retain technical talent and keep pace with innovation,” said Sims of Skillsoft. “Companies that create cultures of learning and talent development will be most successful in recruiting and retaining ambitious individuals with the right skills and certifications to make an impact.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The best strategies for attracting developer talent | VentureBeat"
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"https://venturebeat.com/programming-development/the-best-strategies-for-attracting-developer-talent"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The best strategies for attracting developer talent Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
The last few years have been a period of substantial change and disruption for every industry, including businesses in tech. Many are struggling to hire the talent they need. In an industry where constant innovation is required to stay competitive, the lack of skilled workers in technology is proving costly, with 65% of CIOs claiming that the inability to hire is damaging their business.
When hiring developer talent, recruiters and businesses need to reassess their preconceived assumptions about what makes an effective developer.
Headhunters must cut through the myths, fables and misconceptions constructed around an archetypal but fictional developer. Not until this is done can the talent shortage be put in order.
Recognizing developer differences To be able to attract developer talent , it’s crucial to recognize the differences between developers and identify their skill sets and areas of improvement. No two developers are the same. Great developers come from various backgrounds and find their way into their careers through multiple paths. While some developers have been coding since they were children, others may have come to coding later in life after discovering a passion and skill for it. Others may have only found an aptitude for coding through chance or circumstance. All developers share a professional interest, but beyond that, their backgrounds and lives may diverge significantly. This variety is excellent for the industry, but businesses looking to hire developer talent must be aware of and account for those coming from different life paths.
This diversity not only applies to finding a passion, but also to qualifications and degrees. In most industries, the qualifications held by colleagues are broadly comparable; in software development , the same cannot be said. Although most developers do possess a degree of some type — and the subject of this can vary widely — it is not the case for everyone. Nor should it be a requirement when attempting to recruit candidates.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Although it is not the usual career route for software developers, some people join the industry as a second career. People who come to a career in software development after pursuing different paths often have innovative takes and can be just as valuable to an organization as lifelong developers.
Therefore, the qualifications, skills and aptitudes of people in development are a broad church and not uniform. This is incredibly positive for the industry. A range of backgrounds and life skills bring different insights and skills critical for innovative thinking. Businesses, therefore, should not constrain themselves to narrow recruitment criteria when seeking to attract developers.
Soft skills to look for in developers We’ve all seen it. The stock image of developers as the lonely computer whizz, tapping away on a keyboard from a dark basement. But this couldn’t be further from the truth. Life as a developer means a work-life of intense collaboration, discussion and teamwork, and recruiters need to take this into consideration.
To tackle the most complex of projects, developers must be able to collaborate and consult one another, bouncing ideas off each other and tapping into their whole team’s skill sets. Only through teamwork can you achieve the best outcomes. Therefore, every developer must have the ability to collaborate and work effectively as part of a team.
The best developers are those who can learn from others around them, absorbing everything they have to offer. Cooperation is also highly beneficial for overcoming the most challenging problems that developers face. A broad range of insights and experience, freely given through exchanging ideas, is essential to tackle complex problems. The tools utilized by developers help facilitate the free discussion of ideas and solutions.
Developers are by no means all unsociable and introverted. As in any walk of life, their personalities run the gamut from highly sociable to introverted. Developers tend to be very successful problem solvers who are efficient at collaboration.
Emotional intelligence and a strong work ethic are vital skills for developers. Being inquisitive and challenging yourself to learn skills are important traits that anyone who is a successful developer will possess.
The future of hiring developer talent With many businesses motivated to accelerate their digital transformations and the Great Resignation ongoing throughout the global job market, organizations should open their eyes to the possibilities and benefits of different hiring strategies. Qualified tech workers and would-be developers will have their pick of exciting and successful businesses to choose from. While this means that opportunities for people contemplating entering a career as a developer are becoming more attractive than ever, it is becoming more competitive than ever to hire them.
The global war for talent means that software developers and those who wish to work in the tech industry, in general, are in high demand. Highly talented and motivated employees can differentiate between a successful and a failing business. Organizations that can challenge misconceptions around a career as a developer and incorporate the realities of developer careers into their recruitment strategies will be best placed to attract the best talent.
Anna Richardson is vice president of HR at Aiven.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"The art of the possible with Web3 interoperability | VentureBeat"
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"https://venturebeat.com/programming-development/the-art-of-the-possible-with-web3-interoperability"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest The art of the possible with Web3 interoperability Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
While the Web3 industry is still emerging, the catalyst that will kick this revolution into high gear is hidden in the tech stack. Key improvements in Web3 interoperability will unlock new use cases and upgrade the fundamental systems we rely on every day. And with time, blockchain interoperability is bound to impact every sector across the globe.
What is interoperability? Interoperability, put simply, is the ability to move something from one system to another. This could mean something as simple as texting an iPhone from an Android phone, or something more complex like transferring a token across blockchains.
A seemingly intuitive action like money transfer is surprisingly intricate: We rely on interoperability not only to send currency from one system to another, but to ensure protection against double spending: A flaw in which the initial system sending an asset keeps a copy for use.
In the Web3 terrain, it’s difficult to find an area unaffected by interoperability. The fundamental networking concept is baked into the code of every project, from Binance to OpenSea. Upgrading Web3 interoperability is like updating the engine in a car; improving this key fundamental will bolster everything built on top of it.
Real world example: Building gamers a truly open world Real world examples abound, but before we move into more long-term and visionary use cases, let’s start with a couple of tangible examples that are especially ripe for innovation through interoperability. Two sectors with enormous potential include gaming and identity verification.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! We’ll begin with gaming. As one of the most popular and profitable sectors of the entertainment industry, gaming is known for its cutting-edge tech and unbridled creativity. The gaming industry has exploded in popularity, with a market size expected to reach $435 billion by 2028. Developers have built intricate open worlds, limitless canvases of self-expression and compelling social experiences — constantly expanding the borders of this ever-evolving medium.
Despite sitting on the bleeding edge of tech, however, gaming is limited by a stark lack of interoperability across projects. Today, even the most enthralling experiences and well-funded projects are still siloed isolated escapades — even the best open worlds aren’t actually that “open.” One of the most notable limitations in gaming is the lack of a persistent digital identity. Gamers work tirelessly to develop their online presence — they take care to customize everything about their in-game character, work tirelessly to earn in-game currency and steadily build up their reputation within their community — but their entire identity disappears the second they venture from one game to another.
Fostering developer freedom Some games such as Roblox have already begun addressing these issues. Roblox is designed as a platform for game developers to launch their projects. Using a central hub, players are able to seamlessly jump from project to project without ever leaving the Roblox platform. Projects across the platform use the same Roblox-sanctioned digital currency and players keep their wealth and identity across every project they load up.
However, to accomplish this level of interoperability, Roblox was forced to make sacrifices in developer freedom and game design. All Roblox projects must be built with Roblox-mandated tools, including a coding language and rendering engine — leaving developers with little freedom when it comes to art style and advanced game design.
Other projects have embraced designs that preserve developer freedom, but these too come with trade-offs. Take a game like Decentraland. This Web3 native game tokenizes many in-game assets, allowing them to exist outside the confines of the game just like a crypto token or NFT.
This hands-off approach doesn’t limit developers. Anyone is free to interpret the tokens however they’d like. But transferring Decentraland tokens are complex, typically involving wallets, gas fees and — most critically — cross-chain bridges.
Bridges in particular are notorious for falling victim to high-profile attacks. This year alone, more than $2 billion has been stolen in cross-chain bridge hacks. This means that to move assets across games, players often have to take on the risk that their account is drained in a hack — which would mean losing their identity and all the assets they have worked so hard to earn.
A more secure and robust interoperability standard is needed to ensure safe transfers and to streamline the process. Ideally, it should be as simple as loading up a Roblox game, not as complex as a science project.
On the horizon: Solving a growing identity crisis Another real world example ripe for further innovation through interoperability is identity verification. The ability to prove your identity is crucial to a functioning civilization and economy. Having a formal way to identify ourselves, our ideas and our material possessions is what allows us to exchange and create global markets. But currently, identity verification infrastructure is highly limited.
While global standards — passports, for example — exist, these records are maintained strictly by governments and are extremely limited in the details they contain. Take a moment to consider the many elements of your identity (school transcripts, diplomas, certifications, work experience); none can be encoded into a passport. In fact, they’re all managed by various parties: Your diploma can only be verified by your university; your work experience by your employer. We rely on a confusingly tangled web of identity verification that makes due diligence inefficient and allows fraud to fester.
On top of this, a large portion of the world lacks any means of identity verification altogether. A stunning 1.1 billion people around the world have no means of proving their first and last name, date of birth or nationality. This leads to great difficulty in opening a bank account, voting in an election, getting a job and ultimately participating as an integrated member of society.
Advancements in identity management Blockchain technology can be leveraged to improve management and storage of digital identities, providing unified and tamper-proof infrastructure that provides security and authentication through cryptography.
Blockchain brings exciting advancements to identity management by way of an interoperable and verifiable way to unify identity information such as attributes, claims, attestations and credentials. For example, an identity can include memberships, certifications, qualifications and even co-worker acknowledgments.
Even more powerful is the potential to preserve this data’s privacy while verifying the accuracy using a cryptography concept called “zero-knowledge proofs.” Specifically, zero-knowledge proofs can be used to verify identity tokens (or just owner-approved portions) and prove that they’re accurate while maintaining privacy.
Already, great progress has been made in making digital identity solutions a reality. Soulbound tokens — which can never be transferred to another user — can be used to represent certifications, experience, memberships and degrees, and can be verified in the blink of an eye. In addition, digital cryptography is cheap, particularly when compared to the physical security measures built into IDs and Passports. And, it will likely extend access to low-income demographics that have long been ignored.
However, all of this functionality is moot without the means to easily share and verify soulbound tokens across various platforms. Tools like passports are useful because they can be verified by countries across the globe — the product of a robust universal standard agreed upon by scores of independent governments.
In the same vein, it’s important to establish a protocol to ensure that Soulbound tokens and any other tokenized identity solutions are easily interoperable across an increasingly heterogeneous Web3 ecosystem.
Looking forward: Visionary use cases The benefits and potentials of Web3 interoperability are especially tangible in gaming and identity verification, but their reach extends across a broad swath of industries relying on antiquated systems and communication standards. Moving beyond near-term use cases, there are compelling visions and new areas of disruption on the horizon. Realms like voting are ripe for disruption, and blockchain-based voting may not be too far off.
Because blockchain is decentralized and can be anonymized, it comprises all of the essentials for making shared, fair and democratic decisions. Plus there is no possibility for manipulation, recording errors or tampering.
Along with voting, many have speculated about the enormous potential that interoperable blockchain technology holds for improving the healthcare industry, specifically for revolutionizing the way that medical records are stored, recorded, owned, and shared. Of course, this needs to be done in a way that preserves privacy and provides absolute security, and there are various compliance-related requirements that will need to be carefully considered.
As we move into the future and Web3 development continues at lightning speed — venturing out in new directions and bringing unpredictable new use cases into the fold — it’s important not to lose sight of the bigger picture.
Web3 projects must evolve to be accessible and universally intertwined, not hidden away in isolated silos. Robust interoperability is the key ingredient that transforms a neat proof of concept into an indispensable tool with real world utility.
Theo Gauthier is CEO of Toposware.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Stability AI launches StableCode, an LLM for code generation | VentureBeat"
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"https://venturebeat.com/programming-development/stability-ai-launches-stablecode-an-llm-for-code-generation"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Stability AI launches StableCode, an LLM for code generation Share on Facebook Share on X Share on LinkedIn Stable Code completing a relatively complex Python file using the Pytorch deep learning library (gray text shows Stable Code’s prediction) Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
Stability AI is well known for its Stable Diffusion text-to-image generation model, but that’s not all the generative AI startup is interested in developing. Stability AI is now getting into code generation too.
Today Stability AI announced the first public release of StableCode, its new open large language model (LLM) designed to help users generate programming language code. StableCode is being made available at three different levels: a base model for general use cases, an instruction model, and a long-context-window model that can support up to 16,000 tokens.
The StableCode model benefits from an initial set of programming language data from the open-source BigCode project, with additional filtering and fine-tuning from Stability AI. Initially, StableCode will support development in the Python, Go, Java, JavaScript, C, markdown and C++ programming languages.
“What we would like to do with this kind of model is to do a similar thing as we did for Stable Diffusion, which helped everyone in the world to become an artist,” Christian Laforte, head of research at Stability AI, told VentureBeat in an exclusive interview. “We’d like to do the same thing with the StableCode model: basically allow anyone that has good ideas [and] maybe has a problem, to be able to write a program that would just fix that problem.” VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! StableCode: Built on BigCode and big ideas Training any LLM relies on data, and for StableCode, that data comes from the BigCode project. Using BigCode as the base for an LLM generative AI code tool is not a new idea.
HuggingFace and ServiceNow launched the open StarCoder LLM back in May, which is fundamentally based on BigCode.
Nathan Cooper, lead research scientist at Stability AI, explained to VentureBeat in an exclusive interview that the training for StableCode involved significant filtering and cleaning of the BigCode data.
“We love BigCode, they do amazing work around data governance, model governance and model training,” Cooper said. “We took their datasets and we applied additional filters for quality and also for constructing the large-context-window version of the model, and then we trained it on our cluster.” Cooper said that Stability AI also executed a number of training steps beyond what is in the core BigCode model. Those steps included successive training on specific programming languages.
“It follows a very similar approach [to what’s] done in the natural language domain, where you start off with pre-training a generalist model and then you fine-tune it on a special set of tasks, or in this case languages,” Cooper said.
StableCode’s longer token length a game changer for code generation Looking beyond its BigCode foundation, StableCode’s long-context version could offer significant benefits to users.
StableCode’s long-context-window version has a context window of 16,000 tokens, which Stability AI claims is larger than any other model. Cooper explained that the longer context window enables the use of more specialized and complex code generation prompts. It also means that a user can have StableCode look at a medium-sized code base that includes multiple files, to help understand and generate new code.
“You can use this longer context window to let the model know more about your code base, and what other functions are defined in other files,” Cooper said. “So that when it does suggest code, it can be more tailor-made to your code base and to your needs.” Roping in better code generation with rotary position embedding (RoPE) StableCode, like all modern generative AI models, is based on a transformer neural network.
Rather than using the ALiBi (Attention with Linear Biases) approach to position outputs in a transformer model — the approach used by StarCoder for its open generative AI model for coding — StableCode is using an approach known as rotary position embedding (RoPE ).
Cooper said that the ALiBi approach in transformer models tends to weigh current tokens more than past tokens. In his view, that’s not an ideal approach for code, since unlike natural language, code doesn’t have a set narrative structure with a beginning, middle and end. Code functions can be defined for any point in an application flow.
“I don’t think that coding lends itself to this idea of weighing the present more important than the past, so we use … RoPE, [which] does not have this sort of bias where you’re weighing the present more than the past.” It’s still early for StableCode, and the goal with the initial release is to see how developers will receive and use the model.
“We are going to be interfacing and working with the community to see what cool directions they come up with, and explore the generative developer space,” Cooper said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"Netlify releases Jamstack report, with serverless computing and remote work scoring high marks | VentureBeat"
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"https://venturebeat.com/programming-development/netlify-releases-jamstack-report-with-serverless-computing-and-remote-work-scoring-high-marks"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Netlify releases Jamstack report, with serverless computing and remote work scoring high marks Share on Facebook Share on X Share on LinkedIn Serverless computing is the norm, edge experimentation is growing and Web3 remains hype.
These are some of the key findings in Netlify’s third annual Jamstack Community Survey , which gauges developer sentiment.
“We love data,” said Matt Biilmann, CEO and cofounder of Netlify.
“The survey highlights the trends of the community, for the community.” As he explained, the survey is designed to help developers learn from their peers, as well as to help businesses better gauge developer needs and preferences. Netlify will discuss the full findings at Jamstack Conf on November 7 and 8.
“We believe it’s hugely important to stay on top of trends in the Jamstack because these are the people building the future of the modern web,” said Biilmann.
Serverless computing unlocking impactful work Jamstack is a composable web development architecture that allows developers to create reusable components to more quickly and easily build apps and distribute to a global edge network.
“The Jamstack ecosystem is rapidly evolving as more and more businesses are adopting composable architectures and developers are moving away from traditional monolithic websites and apps,” said Biilmann.
Notably, Netlify’s survey of the Jamstack community found that the serverless cloud-native development model is officially mainstream: 70% of developers report using it, up from 46% last year. Meanwhile, 47% of developers are experimenting with edge dynamic sites.
Biilmann pointed out that when serverless technologies become integrated into platforms, web developers can focus on building user experiences, rather than doing tedious devops work, managing infrastructure or instrumenting for core observability.
“It increases developer productivity and frees up time to focus on the most impactful work,” he said.
React still favorite; the great TypeScript migration continues When it comes to application building, React continues to be the overwhelming favorite (71%), followed by Next.js. Nearly 1 in 2 developers (47%) said they built sites with Next.js in the last year.
Still, newer entrants like Astro (11%) and SolidJS (6%) have had strong starts, and Remix (10%) and Sveltekit (15%) grew strongly year over year, according to the report. And, Vite saw an 18% increase since last year.
Also, the so-called “great TypeScript migration” continues, with the use of the language growing 110% in the last two years.
Nearly a quarter of developers say TypeScript is their primary programming language. Still, 96% of developers use JavaScript (even if it isn’t their primary choice), per the report.
When it comes to CMS preference, meanwhile, WordPress is used by 37% of developers, even though many report that their satisfaction with it is lower than alternatives. At the same time, WordPress as a stand-alone CMS is losing share, and using WordPress as a headless API to power a Jamstack site is at 22%. Newcomer Storyblok, meanwhile, is used by 9% of developers.
“More and more developers realize the potential of headless architecture in building and deploying better web experiences,” said Dominik Angerer, CEO and founder of Storyblok.
At the same time, he said, a content team utilizing the power of Jamstack with a headless CMS “gets the content tools they need and love for creating great experiences on the frontend.” Netlify reports Web3 still just a concept to developers Interestingly, developers aren’t buying into the incredible hype of Web3.
When asked about their attitude to Web3 in general, 42% of developers either don’t know what Web3 is or don’t care about it, while 31% felt negatively about it, according to the survey.
Also, while 7% to 10% of developers have tried technologies like cryptocurrencies and NFTs, only 3% report using these technologies regularly.
“Now that the storm has died down, we’ll get a better sense of what the underlying ideas of self-owned data and identity can really bring to the web,”’ said Biilmann. “The amount of active developers on the most popular Web3 platforms was always low compared to the hype around the sector.” Remote work not just the norm: It’s expected Not surprisingly given the pandemic, remote work has become the new normal. Remarkably, according to the survey, 55% of developers said they would even quit their jobs if forced to return to an office. Also, developers aren’t hesitant to job hop.
Biilmann pointed out that Netlify was a remote company before the pandemic and called web development well-suited for remote work.
“But it was interesting to see just how committed developers are to remote work, even in a year where offices began reopening,” he said.
Per the survey: 83% of developers are working remotely more than half of the time.
76% have maintained or increased their frequency of working remotely over the last year.
33% have changed jobs in the last year, with the most cited reasons being remote work flexibility, career growth opportunities and compensation.
The fact that flexible working policies are often more important to developers than compensation “shows how drastically the workforce has changed in the past few years,” said Biilmann.
Ultimately, he noted, “I’m constantly inspired by the creativity happening across the Jamstack ecosystem, and the survey findings show that the pace of innovation isn’t slowing down anytime soon.” VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Kubernetes Gateway API reality check: Ingress controller is still needed | VentureBeat"
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"https://venturebeat.com/programming-development/kubernetes-gateway-api-reality-check-ingress-controller-is-still-needed"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Kubernetes Gateway API reality check: Ingress controller is still needed Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
No doubt the new Kubernetes excitement is the Gateway API. One of the more significant changes in the Kubernetes project, the Gateway API is sorely needed. More granular and robust control over Kubernetes service networking better addresses the growing number of use cases and roles within the cloud-native paradigm.
Shared architecture — at all scales — requires flexible, scalable and extensible means to manage, observe and secure that infrastructure. The Gateway API is designed for those tasks. Once fully matured, it will help developers, SREs, platform teams, architects and CTOs by making Kubernetes infrastructure tooling and governance more modular and less bespoke.
But let’s be sure the hype does not get ahead of today’s needs.
The past and future Kubernetes gateway API There remains a gap between present and future states of Ingress control in Kubernetes. This has led to a common misconception that the Gateway API will replace the Kubernetes Ingress Controller (KIC) in the near term or make it less useful over the longer term. This view is incorrect for multiple reasons.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Ingress controllers are now embedded in the functional architecture of most Kubernetes deployments. They have become de facto. At some point, the Gateway API will be sufficiently mature to replace all functionality of the Ingress API and even the implementation-specific annotations and custom resources that many of the Ingress implementations use, but that day remains far off.
Today, most IT organizations are still either in the early adoption or the testing stage with Kubernetes. For many, just getting comfortable with the new architecture, networking constructs, and application and service management requirements requires considerable internal education and digestion.
Gateway API and Ingress controllers are not mutually exclusive As we’ve done at NGINX, other Ingress maintainers will presumably implement the Gateway API in their products to take advantage of the new functionality and stay current with the Kubernetes API and project. Just as RESTful APIs are useful for many tasks, the Kubernetes API underpins many products and services, all built on the foundation of its powerful container orchestration engine.
The Gateway API is designed to be a universal component layer for managing service connectivity and behaviors within Kubernetes. It is expressive and extensible, making it useful for many roles, from DevOps to security to NetOps.
As a team that has invested considerable resources into an open source Ingress controller, NGINX could have chosen to integrate the Gateway API into our existing work. Instead, we elected to leverage the Gateway API as a standalone, more open-ended project. We chose this path so as not to project the existing constraints of our Ingress controller implementation onto ways we might hope to use the Gateway API or NGINX in the future. With fewer constraints, it is easier to fail faster or to explore new designs and concepts. Like most cloud-native technology, the Gateway API construct is designed for loose coupling and modularity — even more so than the Ingress controller, in fact.
We are also hopeful that some of our new work around the Gateway API is taken back into the open-source community. We have been present in the Kubernetes community for quite some time and are increasing our open-source efforts around the Gateway API.
It could be interpreted that the evolving API provides an invaluable insertion point and opportunity for a “do-over” on service networking. But that does not mean that everyone is quick to toss out years of investment in other projects. Ingress will continue to be important as Gateway API matures and develops, and the two are not mutually exclusive.
Plan for a hybrid future Does it sound like we think the Kubernetes world should have its Gateway API cake and eat its Ingress controller too? Well, we do. Guilty as charged. Bottom line: We believe Kubernetes is a big tent with plenty of room for both new constructs and older categories. Improving on existing Ingress controllers —which were tethered to a limited annotation capability that induced complexity and reduced modularity — remains critical for organizations for the foreseeable future.
Yes, the Gateway API will help us improve Ingress controllers and unleash innovation, but it’s an API, not a product category. This new API is not a magic wand nor a silver bullet. Smart teams are planning for this hybrid future, learning about the improvements the Gateway API will bring while continuing to plan around ongoing Ingress controller improvement. The beauty of this hybrid reality is that everyone can run clusters in the way they know and desire. Every team gets what they want and need.
Brian Ehlert is director of product management at NGINX.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"It’s 2023: Do you know if your Kubernetes environments are safe? | VentureBeat"
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"https://venturebeat.com/programming-development/its-2023-do-you-know-if-your-kubernetes-environments-are-safe"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest It’s 2023: Do you know if your Kubernetes environments are safe? Share on Facebook Share on X Share on LinkedIn Are you ready to bring more awareness to your brand? Consider becoming a sponsor for The AI Impact Tour. Learn more about the opportunities here.
“Kubernetes” is a word that businesses are hearing more and more, but most outside the IT and security space probably don’t have a clear understanding of what it means. The word itself is Greek for “helmsman” or “pilot,” which actually provides a decent sense of what Kubernetes is about.
Essentially, Kubernetes is an open-source system used to automate software deployment — one that’s very good at managing and scaling containerized applications. It steers the ship, so to speak, for software developers operating at the scale today’s technology landscape demands.
That might sound technical, and it is. But as Kubernetes adoption increases, business leaders will need a more complete understanding of how it’s used within their organization. Those outside the development team may not even be aware that Kubernetes is used at all, which poses a significant problem. As it becomes more popular, cybercriminals are turning their attention to Kubernetes — and organizations without a thorough understanding of Kubernetes risk leaving a significant portion of their environment unprotected.
Why Kubernetes is on the rise Kubernetes has become the de-facto standard for automating scaling, deployment and management of containerized applications. There are a number of factors driving its adoption, but it mostly boils down to enabling developers. The simplest explanation of how Kubernetes operates is that instead of developers deploying code directly onto a server, they can instead bundle up code in a container, which can then be deployed just about anywhere.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! Kubernetes is like a head chef, making sure everyone in the kitchen is in the right place, doing what they’re supposed to be doing. This abstracts typical developer concerns, such as disk space or how many copies of an application they might need. Instead, all they need to think about is whether their Kubernetes cluster has enough resources to operate.
In the past, developers would typically build a monolithic application with a massive code base and deploy it directly to enormous servers. This works for a while, but as the business grows, the demands on that server would increase — and ultimately, it’s only possible to throw so much CPU and memory at a problem.
Servers have limits, after all. This makes it easy to see why Kubernetes has become popular: It allows businesses to scale horizontally. Rather than scaling vertically (by buying increasingly powerful servers), they can simply add more instances of an application as needed. This creates a different paradigm for scaling the business — one that is incredibly valuable, particularly for startups.
It’s also worth noting that Kubernetes introduces a layer of abstraction between developers writing code and that code being deployed and running. It means developers can focus on writing code and Kubernetes can take care of scaling it and managing upkeep. In the past, this would require a dedicated team of employees watching those applications, monitoring for outages, and adding more memory, servers, or CPU when necessary. Kubernetes eases that pain — which is just another reason it has become extremely popular.
Building Kubernetes awareness While Kubernetes is great for developers, there are also challenges — particularly where security is concerned. Since Kubernetes is still (relatively) new, it can be difficult to find security professionals with Kubernetes expertise.
These experts are in understandably high demand at the moment, which means it can be a challenge for small companies and startups to bring them in. That said, as Kubernetes becomes more widespread, that knowledge base will grow — and there are partners and services businesses can turn to if they can’t attract the necessary expertise themselves.
It’s important for organizations to think of Kubernetes as an extension of their existing infrastructure. It requires the same levels of control, monitoring and response that a traditional development environment would have. Like all cybersecurity, protecting Kubernetes is more of a journey than a destination, but it’s important to start implementing controls as early as possible.
Organizations should take stock of where they are from a security perspective versus where they’d like to be, then start thinking about necessary steps to get there. This can be intimidating — some businesses spend years building their security infrastructure, and this can feel like starting from scratch — but it doesn’t have to be.
Taking the first steps toward Kubernetes security First — and perhaps most importantly — one of the biggest mistakes organizations make when it comes to Kubernetes security is assuming they can simply buy a product that will take care of the problem for them. This is almost never the case when it comes to security. All security tools require a mature understanding of how they will be deployed, how they will be used and maintained, and what expected outcomes they will produce. Nice as it would be, there isn’t a single product that simply “solves security” for all Kubernetes environments.
Instead, the best first step is to engage with the engineers and DevOps teams actually using Kubernetes. No one is better positioned to explain not just their goals, but the potential risks associated with them. Bringing the development and security teams together to discuss where existing vulnerabilities may lie — and how they can be accounted for without compromising productivity — is critical. These insights can help identify which solutions are needed, leading to better purchasing decisions and more effective controls. When done correctly, security can be built into the Kubernetes environment from the start.
A daunting but necessary task Securing Kubernetes can be a daunting task, but it’s one today’s organizations will need to engage with sooner rather than later. As a growing number of developers turn to Kubernetes to enable more straightforward, scalable software development, protecting Kubernetes environments will only become more critical.
Business leaders can get a jump start by having conversations with developers and engineers, educating themselves on the basic principles behind Kubernetes , and working to gain a more complete picture of the potential risks and challenges involved. Simply put, it’s 2023 — Kubernetes is only going to become more ubiquitous, and it’s important to know that your environments are safe.
Dan Whalen is a senior manager of R&D at Expel.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
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"Intel CTO wants developers to build once, then run on any GPU | VentureBeat"
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"https://venturebeat.com/programming-development/intel-cto-wants-developers-to-build-once-run-on-any-gpu"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Intel CTO wants developers to build once, then run on any GPU Share on Facebook Share on X Share on LinkedIn Over two decades ago, the Java programming language, originally developed by Sun Microsystems, offered developers the promise of being able to build an application once and then have it run on any operating system.
Greg Lavender, CTO of Intel , remembers the original promise of Java better than most, as he spent over a decade working at Sun. Instead of needing to build applications for different hardware and operating systems, the promise of Java was more uniform and streamlined development.
The ability to build once and run anywhere, however, is not uniform across the computing landscape in 2022. It’s a situation that Intel is looking to help change, at least when it comes to accelerated computing and the use of GPUs.
The need for a uniform, Java-like language for GPUs “Today in the accelerated computing and GPU world, you can use CUDA and then you can only run on an Nvidia GPU , or you can go use AMD’s CUDA equivalent running on an AMD GPU,” Lavender told VentureBeat. “You can’t use CUDA to program an Intel GPU, so what do you use?” That’s where Intel is contributing heavily to the open-source SYCL specification (SYCL is pronounced like “sickle”) that aims to do for GPU and accelerated computing what Java did decades ago for application development. Intel’s investment in SYCL is not entirely selfless and isn’t just about supporting an open-source effort; it’s also about helping to steer more development toward its recently released consumer and data center GPUs.
SYCL is an approach for data parallel programming in the C++ language and, according to Lavender, it looks a lot like CUDA.
Intel supports standardization for one code to rule them all To date, SYCL development has been managed by the Khronos Group , which is a multi-stakeholder organization that is helping to build out standards for parallel computing, virtual reality and 3D graphics. On June 1, Intel acquired Scottish development firm Codeplay Software , which is one of the leading contributors to the SYCL specification.
“We should have an open programming language with extensions to C++ that are being standardized, that can run on Intel, AMD and Nvidia GPUs without changing your code,” Lavender said.
Automated tool for converting CUDA into SYCL Lavender is also a realist and he knows that there is a lot of code already written specifically for CUDA. That’s why Intel developers built an open-source tool called SYCLomatic , which aims to migrate CUDA code into SYCL. Lavender claimed that SYCLomatic today has coverage for approximately 95% of all the functionality that is present in CUDA. He noted that the 5% SYCLomatic doesn’t cover are capabilities that are specific to Nvidia hardware.
With SYCL, Lavender said that there are code libraries that developers can use that are device independent. The way that works is code is written by a developer once, and then SYCL can compile the code to work with whatever architecture is needed, be it for an Nvidia, AMD or Intel GPU.
Looking forward, Lavender said that he’s hopeful that SYCL can become a Linux Foundation project, to further enable participation and growth of the open-source effort. Intel and Nvidia are both members of the Linux Foundation supporting multiple efforts. Among the projects where Intel and Nvidia are both members today is the Open Programmable Infrastructure (OPI) project , which is all about providing an open standard for infrastructure programming units (IPUs) and data processing units (DPUs).
“We should have write once, run everywhere for accelerated computing, and then let the market decide which GPU they want to use, and level the playing field,” Lavender said.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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"In shadow of ChatGPT, diverse Nvidia technology grows at GTC 2023 | VentureBeat"
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"https://venturebeat.com/programming-development/in-shadow-of-chatgpt-diverse-nvidia-technology-grows-at-gtc-2023"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages In shadow of ChatGPT, diverse Nvidia technology grows at GTC 2023 Share on Facebook Share on X Share on LinkedIn Nvidia's Earth-2 will be a digital twin of the planet.
It was hard to discern amid the ChatGPT news that dominated at last week’s Nvidia GTC 2023 event, but it’s worth noting that Nvidia technology continues to push forward a broad array of initiatives.
Technical sessions and product announcements in radar design simulation, streaming sensor array data processing and computational lithography don’t fit in the spirited ChatGPT chorus, but some of these announcements may prove equally important in the long term.
>>Follow VentureBeat’s ongoing Nvidia GTC spring 2023 coverage<< Even as he evangelizes ChatGPT , Nvidia CEO Jensen Huang continues to show enthusiasm for a range of undertakings under the banner of “accelerated computing.” Pedal-to-the-metal for accelerated computing Steady progress has held Nvidia in good stead as it expanded GPU technology from graphics cards and video games to crypto-mining and supercomputing, and now, enterprise AI.
Even at its inception in the 1990s, Nvidia proclaimed that its GPU technology had applications beyond graphics processing. That was somewhat retro at the time, as standalone floating-point coprocessors were being added to CPUs. All along, Nvidia’s mission has been to accelerate computing.
The company was careful to nurture products that could be used in the near term, but also to seed long-term uses. Nvidia had to continually create software that eased such evolution. A very notable case is the CUDA programming platform.
That paid off as industry began to pursue AI and deep learning , where GPUs’ very high memory bandwidth thrived. On the hardware front, Nvidia chips have a significant lead in AI in the data center. Despite a slew of specialized ASICs, little has curbed general GPU enthusiasm in deep learning.
Nvidia continues to spice up its product line. In the shadow of varied ChatGPT advances at GTC, Nvidia’s notable announcements included: Open-sourcing its Modulus framework Nvidia is making its Modulus framework available for use with physics-ML under the simple Apache 2.0 license. This can advance efforts to combine physical modeling and numerical simulation.
Why is that important? In recent years Nvidia Modulus has forged a family of neural operators, which now include physics-informed neural networks.
Success with physics-ML could translate into better results in modeling physical systems. That would lead to better fidelity, for example, for digital twins across industries, or avatars across metaverses.
cuLitho: a software library to speed computational lithography workloads Speeding up computational lithography is important as the late Gordon Moore’s Law runs its course. Circuit features are now ultra-small, and it is an incredibly complex job to calculate precise manipulation of mask patterns used to draw them on silicon wafers.
The cuLitho library runs on GPUs and increases speed of nanoscale computational lithography to 40 times greater than today’s alternatives, according to the company. Nvidia foresees dramatic speed-ups in the work of semiconductor fabs with cuLitho.
A quantum-classical computing platform Nvidia together with Tel Aviv-based Quantum Machines announced a platform that will match an OPX+ quantum control system with a Nvidia Grace Hopper system. The goal is to create a system that can scale from a few-qubit rig to a quantum-accelerated supercomputer.
Quantum-classical computing would fill a gap as quantum computing advocates work to extend coherence times, improve error correction and scale-up qubit counts.
A payback on these efforts will be hard won. In the case of quantum computing, Nvidia’s Huang was pretty clear that he sees full-fledged adaptations as a longer-term goal.
Quantum computing is “solidly a decade and two decades away to have … broadly useful quantum systems,” he said at a GTC press conference.
Nvidia and the next computer overlord Huang is not alone in his prediction that true quantum computing is 10 years off of more. That is not altogether surprising given Nvidia’s post on the farthest frontier of classical computing today.
Since Nvidia is focused on accelerated computing, it seems in a position to embrace quantum computing if and when it outpaces GPU-based machines.
For me, it’s not hard to picture Huang echoing game-show king Ken Jennings’s bemused words when Watson won their Jeopardy match: “I for one welcome our new computer overlords.” After all, speeding computation is the true quest.
VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.
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The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! VentureBeat Homepage Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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"Identifying and differentiating quantum talent for future success | VentureBeat"
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"https://venturebeat.com/programming-development/identifying-and-differentiating-quantum-talent-for-future-success"
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"Artificial Intelligence View All AI, ML and Deep Learning Auto ML Data Labelling Synthetic Data Conversational AI NLP Text-to-Speech Security View All Data Security and Privacy Network Security and Privacy Software Security Computer Hardware Security Cloud and Data Storage Security Data Infrastructure View All Data Science Data Management Data Storage and Cloud Big Data and Analytics Data Networks Automation View All Industrial Automation Business Process Automation Development Automation Robotic Process Automation Test Automation Enterprise Analytics View All Business Intelligence Disaster Recovery Business Continuity Statistical Analysis Predictive Analysis More Data Decision Makers Virtual Communication Team Collaboration UCaaS Virtual Reality Collaboration Virtual Employee Experience Programming & Development Product Development Application Development Test Management Development Languages Guest Identifying and differentiating quantum talent for future success Share on Facebook Share on X Share on LinkedIn Quantum computer. Conceptual computer artwork of electronic circuitry with blue light passing through it, representing how data may be controlled and stored in a quantum computer.
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In August, President Biden signed the CHIPS and Science Act of 2022 , authorizing new investments in quantum information science and technology (QIST).
This new legislation builds on decades of accelerated investments to encourage new discoveries and harness new technologies to ensure U.S. economic and national security. The Act authorizes activities that will accelerate the discovery of quantum applications, grow the quantum workforce and enable cutting-edge research and development.
Greater investment in quantum technology will create an increased demand for what is already a small talent pool. Organizations will need to have a firm understanding of how QIST affects their mission to hire or upskill the right technologists to further their strategic priorities.
QIST has the potential to revolutionize every major industry, but the field is still nascent, and until industry standards and norms are further developed, it can be easy to miss important differences among the principal subsets of quantum technology.
Quantum sensing, computing and communications require different expertise, and an organization may not need experts in all three areas. Similarly, a single quantum scientist won’t be equally suited to roles across the three technology clusters.
VB Event The AI Impact Tour Connect with the enterprise AI community at VentureBeat’s AI Impact Tour coming to a city near you! With that in mind, organizations must carefully align personnel and projects to enable the full potential of quantum technologies.
Distinguishing QIST expertise Harnessing the transformative potential of quantum technology requires a breadth and depth of talent that is challenging to recruit and retain. To capitalize on QIST’s potential, leaders must accurately manage the expertise their organizations need for strategic planning and R&D, while building hiring pipelines that enable them to scale.
Furthermore, building a team that is capable of operationalizing the technology requires input from experts in the fields of the target application. For example, to create a quantum financial solution to predict a market crash, an organization would need to pair a quantum scientist with an expert in financial data and modeling.
We can learn several lessons from implementing artificial intelligence (AI) teams. Due to the diversity of expertise under the AI umbrella, it’s no longer sufficient to simply recruit an “AI expert.” Rather, recruitment language has evolved to differentiate AI specialties — between computer vision, natural language processing (NLP) and reinforcement learning, for example — to better facilitate connections between people and applications.
As QIST continues to mature, leaders must learn to distinguish quantum expertise with similar specificity. Ultimately, the ideal team will be composed based on the unique mission of the particular agency or organization.
Developing upskilling initiatives and strategic partnerships As we navigate this quantum talent shortage, leaders should focus on two key efforts: upskilling endeavors and strategic partnerships.
Upskilling may not be viable to produce quantum specialists without the right pre-existing skills, but it can prepare other subject matter experts to contribute to quantum problems. Effective upskilling initiatives focus on the foundational information mission experts need to identify quantum-relevant problems and engage quantum solutions.
These initiatives should go hand in hand with internal networking — organizations should aim to train their workforce to recognize opportunities where quantum technology could drive mission-critical impacts. As the goals and needs of the field continue to develop, organizations must build forecasting into their strategy to make sure the teams they are building are diverse and interdisciplinary enough to pivot as the application areas of quantum evolve.
This approach to upskilling can be extrapolated to external partnerships. It’s a tall order for any organization to recruit and retain the diversity of quantum expertise they will likely need to fully optimize their use of the technology over time. In-house talent investments won’t make sense for every organization, and it can be beneficial to consider outside partners who understand the probable time horizons for realizing different quantum applications.
With the ability to pool quantum expertise, organizations will be better prepared to identify critical use cases and mission applications for QIST in both the short and long terms. In short, external partnerships will enable organizations to maximize the benefits of QIST adoption potential without overextending their in-house expertise.
Tying quantum together with talent and technology in lockstep While quantum technology will continue to develop at its own pace, there must be a consistent, clear connection between in-house QIST research and how it will impact business goals. Organizations will need to remain grounded in their missions and clarify how their talent needs are aligned to their priorities. CISOs, CTOs and other senior leaders must start preparing today to leverage QIST as it scales to upend technology norms across sectors and industries.
QIST is not a quick fix. Rather, the many applications of quantum technology — current and future — represent advances to solving specific types of problems. Some applications are on a longer timeline, while others require immediate attention.
For example, post-quantum cryptography (PQC) is an advanced encryption approach that every government and commercial enterprise must adopt soon to ensure ongoing digital security.
With early support from trusted advisors and partners, leaders can identify which quantum skillsets correspond to their mission-critical use cases and ensure access to the right talent.
Jordan Kenyon is senior lead scientist at Booz Allen. JD Dulny is director at Booz Allen.
DataDecisionMakers Welcome to the VentureBeat community! DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.
If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.
You might even consider contributing an article of your own! Read More From DataDecisionMakers The AI Impact Tour Join us for an evening full of networking and insights at VentureBeat's AI Impact Tour, coming to San Francisco, New York, and Los Angeles! DataDecisionMakers Follow us on Facebook Follow us on X Follow us on LinkedIn Follow us on RSS Press Releases Contact Us Advertise Share a News Tip Contribute to DataDecisionMakers Careers Privacy Policy Terms of Service Do Not Sell My Personal Information © 2023 VentureBeat.
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Subsets and Splits
Wired Articles Filtered
Retrieves up to 100 entries from the train dataset where the URL contains 'wired' but the text does not contain 'Menu', providing basic filtering of the data.