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-WEBVTT
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- The following is a conversation with Kai Fu Li.
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- He's the chairman and CEO of Sinovation Ventures
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- that manages a $2 billion dual currency investment fund
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- with a focus on developing the next generation
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- of Chinese high tech companies.
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- He's the former president of Google China
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- and the founder of what is now called Microsoft Research
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- Asia, an institute that trained many
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- of the artificial intelligence leaders in China,
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- including CTOs or AI execs at Baidu, Tencent, Alibaba,
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- Lenovo, and Huawei.
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- He was named one of the 100 most influential people
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- in the world by Time Magazine.
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- He's the author of seven bestselling books in Chinese
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- and most recently, the New York Times bestseller called
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- AI Superpowers, China, Silicon Valley,
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- and the New World Order.
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- He has unparalleled experience in working across major tech
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- companies and governments on applications of AI.
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- And so he has a unique perspective
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- on global innovation in the future of AI
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- that I think is important to listen to and think about.
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- This is the Artificial Intelligence Podcast.
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- If you enjoy it, subscribe on YouTube and iTunes,
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- support it on Patreon, or simply connect with me on Twitter
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- at Lex Freedman.
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- And now, here's my conversation with Kaifu Li.
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- I immigrated from Russia to US when I was 13.
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- You immigrated to US at about the same age.
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- The Russian people, the American people, the Chinese people,
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- each have a certain soul, a spirit,
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- that permeates throughout the generations.
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- So maybe it's a little bit of a poetic question,
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- but could you describe your sense of what
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- defines the Chinese soul?
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- I think the Chinese soul of people today, right,
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- we're talking about people who have had centuries of burden
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- because of the poverty that the country has gone through
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- and suddenly shined with hope of prosperity
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- in the past 40 years as China opened up
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- and embraced market economy.
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- And undoubtedly, there are two sets of pressures
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- on the people, that of the tradition,
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- that of facing difficult situations,
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- and that of hope of wanting to be the first
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- to become successful and wealthy,
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- so that it's a very strong hunger and strong desire
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- and strong work ethic that drives China forward.
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- And is there roots to not just this generation,
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- but before, that's deeper than just
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- the new economic developments?
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- Is there something that's unique to China
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- that you could speak to that's in the people?
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- Yeah.
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- Well, the Chinese tradition is about excellence,
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- dedication, and results.
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- And the Chinese exams and study subjects in schools
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- have traditionally started from memorizing 10,000 characters,
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- not an easy task to start with.
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- And further by memorizing historic philosophers,
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- literature, poetry.
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- So it really is probably the strongest road
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- learning mechanism created to make sure people had good memory
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- and remembered things extremely well.
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- That, I think, at the same time suppresses
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- the breakthrough innovation.
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- And also enhances the speed execution get results.
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- And that, I think, characterizes the historic basis of China.
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- That's interesting, because there's echoes of that
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- in Russian education as well as rote memorization.
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- So you memorize a lot of poetry.
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- I mean, there's just an emphasis on perfection in all forms
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- that's not conducive to perhaps what you're speaking to,
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- which is creativity.
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- But you think that kind of education
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- holds back the innovative spirit that you
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- might see in the United States?
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- Well, it holds back the breakthrough innovative spirit
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- that we see in the United States.
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- But it does not hold back the valuable execution oriented,
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- result oriented value creating engines, which we see China
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- being very successful.
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- So is there a difference between a Chinese AI engineer
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- today and an American AI engineer perhaps rooted
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- in the culture that we just talked about or the education
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- or the very soul of the people or no?
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- And what would your advice be to each
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- if there's a difference?
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- Well, there's a lot that's similar,
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- because AI is about mastering sciences,
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- about using known technologies and trying new things.
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- But it's also about picking from many parts of possible networks
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- to use and different types of parameters to tune.
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- And that part is somewhat rote.
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- And it is also, as anyone who's built AI products,
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- can tell you a lot about cleansing the data.
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- Because AI runs better with more data.
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- And data is generally unstructured, errorful,
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- and unclean.
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- And the effort to clean the data is immense.
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- So I think the better part of the American AI engineering
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- process is to try new things, to do things people haven't done
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- before, and to use technology to solve most, if not all,
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- problems.
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- So to make the algorithm work despite not so great data,
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- find error tolerant ways to deal with the data.
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- The Chinese way would be to basically enumerate,
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- to the fullest extent, all the possible ways
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- by a lot of machines, try lots of different ways
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- to get it to work, and spend a lot of resources and money
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- and time cleaning up data.
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- That means the AI engineer may be writing data cleansing
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- algorithms, working with thousands of people
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- who label or correct or do things with the data.
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- That is the incredible hard work that
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- might lead to better results.
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- So the Chinese engineer would rely on and ask for more and more
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- data and find ways to cleanse them and make them work
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- in the system, and probably less time thinking
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- about new algorithms that can overcome data or other issues.
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- So where's your intuition?
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- What do you think the biggest impact the next 10 years
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- lies?
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- Is it in some breakthrough algorithms?
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- Or is it in just this at scale rigor, a rigorous approach
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- to data, cleaning data, organizing data
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- onto the same algorithms?
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- What do you think the big impact in the applied world is?
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- Well, if you're really in the company
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- and you have to deliver results, using known techniques
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- and enhancing data seems like the more expedient approach
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- that's very low risk and likely to generate
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- better and better results.
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- And that's why the Chinese approach has done quite well.
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- Now, there are a lot of more challenging startups
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- and problems, such as autonomous vehicles,
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- medical diagnosis, that existing algorithms probably
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- won't solve.
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- And that would put the Chinese approach more challenged
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- and give them more breakthrough innovation approach, more
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- of an edge on those kinds of problems.
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- So let me talk to that a little more.
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- So my intuition, personally, is that data
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- can take us extremely far.
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- So you brought up autonomous vehicles and medical diagnosis.
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- So your intuition is that huge amounts of data
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- might not be able to completely help us solve that problem.
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- Right.
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- So breaking that down further, autonomous vehicle,
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- I think huge amounts of data probably
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- will solve trucks driving on highways, which
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- will deliver significant value.
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- And China will probably lead in that.
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- And full L5 autonomous is likely to require new technologies
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- we don't yet know.
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- And that might require academia and great industrial research,
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- both innovating and working together.
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- And in that case, US has an advantage.
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- So the interesting question there is,
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- I don't know if you're familiar on the autonomous vehicle
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- space and the developments with Tesla and Elon Musk,
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- where they are, in fact, a full steam ahead
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- into this mysterious, complex world of full autonomy, L5,
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- L4, L5.
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- And they're trying to solve that purely with data.
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- So the same kind of thing that you're saying
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- is just for highway, which is what a lot of people
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- share your intuition, they're trying to solve with data.
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- It's just to linger on that moment further.
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- Do you think possible for them to achieve success
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- with simply just a huge amount of this training
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- on edge cases, on difficult cases in urban environments,
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- not just highway and so on?
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- I think they'll be very hard.
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- One could characterize Tesla's approach as kind
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- of a Chinese strength approach, gather all the data you can,
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- and hope that will overcome the problems.
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- But in autonomous driving, clearly a lot of the decisions
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- aren't merely solved by aggregating data
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- and having feedback loop.
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- There are things that are more akin to human thinking.
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- And how would those be integrated and built?
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- There has not yet been a lot of success
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- integrating human intelligence or, you know,
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- colored expert systems, if you will,
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- even though that's a taboo word with the machine learning.
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- And the integration of the two types of thinking
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- hasn't yet been demonstrated.
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- And the question is, how much can you
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- push a purely machine learning approach?
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- And of course, Tesla also has an additional constraint
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- that they don't have all the sensors.
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- I know that they think it's foolish to use LIDARS,
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- but that's clearly a one less, very valuable and reliable
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- source of input that they're foregoing, which
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- may also have consequences.
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- I think the advantage, of course,
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- is capturing data that no one has ever seen before.
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- And in some cases, such as computer vision and speech
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- recognition, I have seen Chinese companies accumulate data
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- that's not seen anywhere in the Western world,
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- and they have delivered superior results.
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- But then speech recognition and object recognition
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- are relatively suitable problems for deep learning
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- and don't have the potentially need for the human intelligence
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- analytical planning elements.
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- And the same on the speech recognition side,
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- your intuition that speech recognition and the machine
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- learning approaches to speech recognition
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- won't take us to a conversational system that
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- can pass the Turing test, which is maybe akin to what
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- driving is.
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- So it needs to have something more than just simply simple
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- language understanding, simple language generation.
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- Roughly right, I would say that based on purely machine
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- learning approaches, it's hard to imagine.
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- It could lead to a full conversational experience
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- across arbitrary domains, which is akin to L5.
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- I'm a little hesitant to use the word Turing test,
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- because the original definition was probably too easy.
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- We probably do that.
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- The spirit of the Turing test is what I was referring to.
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- Of course.
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- So you've had major leadership research positions
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- at Apple, Microsoft, Google.
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- So continuing on the discussion of America, Russia, Chinese soul
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- and culture and so on, what is the culture of Silicon
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- Valley in contrast to China and maybe US broadly?
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- And what is the unique culture of each of these three
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- major companies, in your view?
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- I think in aggregate, Silicon Valley companies,
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- we could probably include Microsoft in that,
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- even though they're not in the Valley,
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- is really dream big and have visionary goals
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- and believe that technology will conquer all
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- and also the self confidence and the self entitlement
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- that whatever they produce, the whole world should use
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- and must use.
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- And those are historically important, I think.
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- Steve Jobs's famous quote that he doesn't do focus groups.
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- He looks in the mirror and asks the person in the mirror,
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- what do you want?
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- And that really is an inspirational comment
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- that says the great company shouldn't just ask users
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- what they want, but develop something
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- that users will know they want when they see it,
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- but they could never come up with themselves.
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- I think that is probably the most exhilarating description
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- of what the essence of Silicon Valley is,
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- that this brilliant idea could cause you to build something
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- that couldn't come out of the focus groups or A.B. tests.
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- And iPhone would be an example of that.
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- No one in the age of BlackBerry would write down
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- they want an iPhone or multi touch, a browser,
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- might be another example.
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- No one would say they want that in the days of FTP,
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- but once they see it, they want it.
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- So I think that is what Silicon Valley is best at.
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- But it also came with a lot of success.
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- These products became global platforms,
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- and there were basically no competitors anywhere.
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- And that has also led to a belief
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- that these are the only things that one should do,
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- that companies should not tread on other companies territory,
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- so that a Groupon and a Yelp and an OpenTable
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- and the Grubhub would each feel,
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- okay, I'm not going to do the other companies business
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- because that would not be the pride of innovating
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- what each of these four companies have innovated.
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- But I think the Chinese approach is do whatever it takes to win.
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- And it's a winner take all market.
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- And in fact, in the internet space,
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- the market leader will get predominantly all the value
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- extracted out of the system.
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- And the system isn't just defined as one narrow category,
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- but gets broader and broader.
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- So it's amazing ambition for success and domination
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- of increasingly larger product categories
-
-15:11.760 --> 15:15.080
- leading to clear market winner status
-
-15:15.080 --> 15:19.120
- and the opportunity to extract tremendous value.
-
-15:19.120 --> 15:25.840
- And that develops a practical, result oriented,
-
-15:25.840 --> 15:31.520
- ultra ambitious winner take all gladiatorial mentality.
-
-15:31.520 --> 15:37.400
- And if what it takes is to build what the competitors built,
-
-15:37.400 --> 15:41.920
- essentially a copycat, that can be done without infringing laws.
-
-15:41.920 --> 15:46.280
- If what it takes is to satisfy a foreign country's need
-
-15:46.280 --> 15:48.480
- by forking the code base and building something
-
-15:48.480 --> 15:51.440
- that looks really ugly and different, they'll do it.
-
-15:51.440 --> 15:56.280
- So it's contrasted very sharply with the Silicon Valley approach.
-
-15:56.280 --> 16:00.080
- And I think the flexibility and the speed and execution
-
-16:00.080 --> 16:01.960
- has helped the Chinese approach.
-
-16:01.960 --> 16:05.040
- And I think the Silicon Valley approach
-
-16:05.040 --> 16:10.280
- is potentially challenged if every Chinese entrepreneur is
-
-16:10.280 --> 16:13.200
- learning from the whole world, US and China,
-
-16:13.200 --> 16:16.280
- and the American entrepreneurs only look internally
-
-16:16.280 --> 16:19.600
- and write off China as a copycat.
-
-16:19.600 --> 16:22.880
- And the second part of your question about the three
-
-16:22.880 --> 16:23.520
- companies.
-
-16:23.520 --> 16:26.000
- The unique elements of the three companies, perhaps.
-
-16:26.000 --> 16:26.840
- Yeah.
-
-16:26.840 --> 16:33.080
- I think Apple represents, while the user, please the user,
-
-16:33.080 --> 16:38.520
- and the essence of design and brand,
-
-16:38.520 --> 16:44.080
- and it's the one company and perhaps the only tech company
-
-16:44.080 --> 16:49.920
- that draws people with a strong, serious desire
-
-16:49.920 --> 16:53.560
- for the product and the willingness to pay a premium
-
-16:53.560 --> 16:57.160
- because of the halo effect of the brand, which
-
-16:57.160 --> 17:00.960
- came from the attention to detail and great respect
-
-17:00.960 --> 17:03.360
- for user needs.
-
-17:03.360 --> 17:09.200
- Microsoft represents a platform approach
-
-17:09.200 --> 17:14.280
- that builds giant products that become very strong modes
-
-17:14.280 --> 17:17.680
- that others can't do because it's
-
-17:17.680 --> 17:21.480
- well architected at the bottom level
-
-17:21.480 --> 17:26.640
- and the work is efficiently delegated to individuals
-
-17:26.640 --> 17:30.360
- and then the whole product is built
-
-17:30.360 --> 17:33.560
- by adding small parts that sum together.
-
-17:33.560 --> 17:37.760
- So it's probably the most effective high tech assembly
-
-17:37.760 --> 17:40.480
- line that builds a very difficult product
-
-17:40.480 --> 17:44.800
- that the whole process of doing that
-
-17:44.800 --> 17:50.800
- is kind of a differentiation and something competitors
-
-17:50.800 --> 17:52.480
- can't easily repeat.
-
-17:52.480 --> 17:54.800
- Are there elements of the Chinese approach
-
-17:54.800 --> 17:59.280
- in the way Microsoft went about assembling those little pieces
-
-17:59.280 --> 18:03.920
- and essentially dominating the market for a long time?
-
-18:03.920 --> 18:05.640
- Or do you see those as distinct?
-
-18:05.640 --> 18:08.240
- I think there are elements that are the same.
-
-18:08.240 --> 18:10.440
- I think the three American companies
-
-18:10.440 --> 18:13.880
- that had or have Chinese characteristics,
-
-18:13.880 --> 18:16.080
- and obviously as well as American characteristics,
-
-18:16.080 --> 18:20.400
- are Microsoft, Facebook, and Amazon.
-
-18:20.400 --> 18:21.720
- Yes, that's right, Amazon.
-
-18:21.720 --> 18:25.560
- Because these are companies that will tenaciously
-
-18:25.560 --> 18:31.320
- go after adjacent markets, build up strong product offering,
-
-18:31.320 --> 18:38.200
- and find ways to extract greater value from a sphere that's
-
-18:38.200 --> 18:39.960
- ever increasing.
-
-18:39.960 --> 18:43.520
- And they understand the value of the platforms.
-
-18:43.520 --> 18:45.600
- So that's the similarity.
-
-18:45.600 --> 18:53.760
- And then with Google, I think it's a genuinely value oriented
-
-18:53.760 --> 18:56.960
- company that does have a heart and soul
-
-18:56.960 --> 18:59.760
- and that wants to do great things for the world
-
-18:59.760 --> 19:06.040
- by connecting information and that has also
-
-19:06.040 --> 19:13.280
- very strong technology genes and wants to use technology
-
-19:13.280 --> 19:19.080
- and has found out of the box ways to use technology
-
-19:19.080 --> 19:23.680
- to deliver incredible value to the end user.
-
-19:23.680 --> 19:25.240
- We can look at Google, for example.
-
-19:25.240 --> 19:28.040
- You mentioned heart and soul.
-
-19:28.040 --> 19:31.840
- There seems to be an element where Google
-
-19:31.840 --> 19:34.840
- is after making the world better.
-
-19:34.840 --> 19:36.520
- There's a more positive view.
-
-19:36.520 --> 19:38.960
- I mean, they used to have the slogan, don't be evil.
-
-19:38.960 --> 19:43.120
- And Facebook a little bit more has a negative tend to it,
-
-19:43.120 --> 19:46.000
- at least in the perception of privacy and so on.
-
-19:46.000 --> 19:51.280
- Do you have a sense of how these different companies can
-
-19:51.280 --> 19:53.400
- achieve, because you've talked about how much
-
-19:53.400 --> 19:55.600
- we can make the world better in all these kinds of ways
-
-19:55.600 --> 19:59.360
- with AI, what is it about a company that can make,
-
-19:59.360 --> 20:03.200
- give it a heart and soul, gain the trust of the public,
-
-20:03.200 --> 20:08.000
- and just actually just not be evil and do good for the world?
-
-20:08.000 --> 20:09.000
- It's really hard.
-
-20:09.000 --> 20:13.120
- And I think Google has struggled with that.
-
-20:13.120 --> 20:15.160
- First, they don't do evil.
-
-20:15.160 --> 20:18.880
- Mantra is very dangerous, because every employee's
-
-20:18.880 --> 20:20.800
- definition of evil is different.
-
-20:20.800 --> 20:23.800
- And that has led to some difficult employee situations
-
-20:23.800 --> 20:25.240
- for them.
-
-20:25.240 --> 20:29.520
- So I don't necessarily think that's a good value statement.
-
-20:29.520 --> 20:31.840
- But just watching the kinds of things
-
-20:31.840 --> 20:36.440
- Google or its parent company Alphabet does in new areas
-
-20:36.440 --> 20:40.440
- like health care, like eradicating mosquitoes,
-
-20:40.440 --> 20:42.360
- things that are really not in the business
-
-20:42.360 --> 20:45.040
- of a internet tech company, I think
-
-20:45.040 --> 20:47.200
- that shows that there is a heart and soul
-
-20:47.200 --> 20:53.920
- and desire to do good and willingness to put in the resources
-
-20:53.920 --> 20:58.280
- to do something when they see it's good, they will pursue it.
-
-20:58.280 --> 21:00.640
- That doesn't necessarily mean it has
-
-21:00.640 --> 21:02.520
- all the trust of the users.
-
-21:02.520 --> 21:06.400
- I realize while most people would view Facebook
-
-21:06.400 --> 21:09.760
- as the primary target of their recent unhappiness
-
-21:09.760 --> 21:12.720
- about Silicon Valley companies, many would put Google
-
-21:12.720 --> 21:14.080
- in that category.
-
-21:14.080 --> 21:16.800
- And some have named Google's business practices
-
-21:16.800 --> 21:19.840
- as predatory also.
-
-21:19.840 --> 21:24.240
- So it's kind of difficult to have the two parts of a body.
-
-21:24.240 --> 21:28.080
- The brain wants to do what it's supposed to do for a shareholder,
-
-21:28.080 --> 21:29.280
- maximize profit.
-
-21:29.280 --> 21:30.880
- And then the heart and soul wants
-
-21:30.880 --> 21:36.120
- to do good things that may run against what the brain wants to do.
-
-21:36.120 --> 21:40.320
- So in this complex balancing that these companies have to do,
-
-21:40.320 --> 21:44.520
- you've mentioned that you're concerned about a future where
-
-21:44.520 --> 21:47.360
- too few companies like Google, Facebook, Amazon
-
-21:47.360 --> 21:51.560
- are controlling our data or are controlling too much
-
-21:51.560 --> 21:53.360
- of our digital lives.
-
-21:53.360 --> 21:55.400
- Can you elaborate on this concern?
-
-21:55.400 --> 21:58.640
- Perhaps do you have a better way forward?
-
-21:58.640 --> 22:05.000
- I think I'm hardly the most vocal complainer of this.
-
-22:05.000 --> 22:07.280
- There are a lot louder complainers out there.
-
-22:07.280 --> 22:11.840
- I do observe that having a lot of data
-
-22:11.840 --> 22:16.120
- does perpetuate their strength and limits
-
-22:16.120 --> 22:19.400
- competition in many spaces.
-
-22:19.400 --> 22:24.200
- But I also believe AI is much broader than the internet space.
-
-22:24.200 --> 22:26.280
- So the entrepreneurial opportunities
-
-22:26.280 --> 22:30.480
- still exists in using AI to empower
-
-22:30.480 --> 22:34.160
- financial, retail, manufacturing, education,
-
-22:34.160 --> 22:35.480
- applications.
-
-22:35.480 --> 22:39.800
- So I don't think it's quite a case of full monopolistic dominance
-
-22:39.800 --> 22:43.960
- that totally stifles innovation.
-
-22:43.960 --> 22:46.400
- But I do believe in their areas of strength
-
-22:46.400 --> 22:49.760
- it's hard to dislodge them.
-
-22:49.760 --> 22:53.280
- I don't know if I have a good solution.
-
-22:53.280 --> 22:57.160
- Probably the best solution is let the entrepreneurial VC
-
-22:57.160 --> 23:00.840
- ecosystem work well and find all the places that
-
-23:00.840 --> 23:04.200
- can create the next Google, the next Facebook.
-
-23:04.200 --> 23:08.560
- So there will always be increasing number of challengers.
-
-23:08.560 --> 23:11.360
- In some sense, that has happened a little bit.
-
-23:11.360 --> 23:15.760
- You see Uber, Airbnb having emerged despite the strength
-
-23:15.760 --> 23:19.040
- of the big three.
-
-23:19.040 --> 23:22.400
- And I think China as an environment
-
-23:22.400 --> 23:25.280
- may be more interesting for the emergence.
-
-23:25.280 --> 23:28.920
- Because if you look at companies between, let's say,
-
-23:28.920 --> 23:36.320
- $50 to $300 billion, China has emerged more of such companies
-
-23:36.320 --> 23:39.880
- than the US in the last three to four years.
-
-23:39.880 --> 23:42.120
- Because of the larger marketplace,
-
-23:42.120 --> 23:47.000
- because of the more fearless nature of the entrepreneurs.
-
-23:47.000 --> 23:50.840
- And the Chinese giants are just as powerful as American ones.
-
-23:50.840 --> 23:52.920
- Tencent Alibaba are very strong.
-
-23:52.920 --> 23:57.040
- But Bytes Dance has emerged worth $75 billion.
-
-23:57.040 --> 24:00.120
- And financial, while it's Alibaba affiliated,
-
-24:00.120 --> 24:03.920
- it's nevertheless independent and worth $150 billion.
-
-24:03.920 --> 24:08.280
- And so I do think if we start to extend
-
-24:08.280 --> 24:12.640
- to traditional businesses, we will see very valuable companies.
-
-24:12.640 --> 24:18.120
- So it's probably not the case that in five or 10 years,
-
-24:18.120 --> 24:20.920
- we'll still see the whole world with these five companies
-
-24:20.920 --> 24:22.680
- having such dominance.
-
-24:22.680 --> 24:26.040
- So you've mentioned a couple of times
-
-24:26.040 --> 24:27.840
- this fascinating world of entrepreneurship
-
-24:27.840 --> 24:31.080
- in China of the fearless nature of the entrepreneurs.
-
-24:31.080 --> 24:32.640
- So can you maybe talk a little bit
-
-24:32.640 --> 24:35.520
- about what it takes to be an entrepreneur in China?
-
-24:35.520 --> 24:38.240
- What are the strategies that are undertaken?
-
-24:38.240 --> 24:41.120
- What are the ways that you success?
-
-24:41.120 --> 24:43.960
- What is the dynamic of VCF funding,
-
-24:43.960 --> 24:46.480
- of the way the government helps companies, and so on?
-
-24:46.480 --> 24:49.520
- What are the interesting aspects here that are distinct from,
-
-24:49.520 --> 24:52.880
- that are different from the Silicon Valley world
-
-24:52.880 --> 24:55.240
- of entrepreneurship?
-
-24:55.240 --> 24:58.080
- Well, many of the listeners probably
-
-24:58.080 --> 25:03.000
- still would brand Chinese entrepreneur as copycats.
-
-25:03.000 --> 25:06.120
- And no doubt, 10 years ago, that would not
-
-25:06.120 --> 25:09.080
- be an inaccurate description.
-
-25:09.080 --> 25:12.320
- Back 10 years ago, an entrepreneur probably
-
-25:12.320 --> 25:14.840
- could not get funding if he or she could not
-
-25:14.840 --> 25:20.400
- describe what product he or she is copying from the US.
-
-25:20.400 --> 25:23.520
- The first question is, who has proven this business model,
-
-25:23.520 --> 25:27.200
- which is a nice way of asking, who are you copying?
-
-25:27.200 --> 25:29.520
- And that reason is understandable,
-
-25:29.520 --> 25:34.840
- because China had a much lower internet penetration
-
-25:34.840 --> 25:40.920
- and didn't have enough indigenous experience
-
-25:40.920 --> 25:43.200
- to build innovative products.
-
-25:43.200 --> 25:47.600
- And secondly, internet was emerging.
-
-25:47.600 --> 25:49.800
- Link startup was the way to do things,
-
-25:49.800 --> 25:52.920
- building a first minimally viable product,
-
-25:52.920 --> 25:55.320
- and then expanding was the right way to go.
-
-25:55.320 --> 25:59.480
- And the American successes have given a shortcut
-
-25:59.480 --> 26:02.840
- that if you build your minimally viable product based
-
-26:02.840 --> 26:05.040
- on an American product, it's guaranteed
-
-26:05.040 --> 26:06.720
- to be a decent starting point.
-
-26:06.720 --> 26:08.400
- Then you tweak it afterwards.
-
-26:08.400 --> 26:11.720
- So as long as there are no IP infringement, which,
-
-26:11.720 --> 26:15.080
- as far as I know, there hasn't been in the mobile and AI
-
-26:15.080 --> 26:19.360
- spaces, that's a much better shortcut.
-
-26:19.360 --> 26:23.720
- And I think Silicon Valley would view that as still not
-
-26:23.720 --> 26:29.200
- very honorable, because that's not your own idea to start with.
-
-26:29.200 --> 26:32.600
- But you can't really, at the same time,
-
-26:32.600 --> 26:35.160
- believe every idea must be your own
-
-26:35.160 --> 26:38.120
- and believe in the link startup methodology,
-
-26:38.120 --> 26:41.880
- because link startup is intended to try many, many things
-
-26:41.880 --> 26:44.240
- and then converge when that works.
-
-26:44.240 --> 26:46.720
- And it's meant to be iterated and changed.
-
-26:46.720 --> 26:51.240
- So finding a decent starting point without legal violations,
-
-26:51.240 --> 26:55.520
- there should be nothing morally dishonorable about that.
-
-26:55.520 --> 26:57.080
- So just a quick pause on that.
-
-26:57.080 --> 27:01.920
- It's fascinating that that's why is that not honorable, right?
-
-27:01.920 --> 27:04.680
- It's exactly as you formulated.
-
-27:04.680 --> 27:08.040
- It seems like a perfect start for business
-
-27:08.040 --> 27:12.440
- is to take a look at Amazon and say, OK,
-
-27:12.440 --> 27:14.560
- we'll do exactly what Amazon is doing.
-
-27:14.560 --> 27:16.800
- Let's start there in this particular market.
-
-27:16.800 --> 27:20.520
- And then let's out innovate them from that starting point.
-
-27:20.520 --> 27:22.200
- Yes. Come up with new ways.
-
-27:22.200 --> 27:26.520
- I mean, is it wrong to be, except the word copycat just
-
-27:26.520 --> 27:28.800
- sounds bad, but is it wrong to be a copycat?
-
-27:28.800 --> 27:31.640
- It just seems like a smart strategy.
-
-27:31.640 --> 27:35.800
- But yes, doesn't have a heroic nature to it
-
-27:35.800 --> 27:42.280
- that Steve Jobs, Elon Musk, sort of in something completely
-
-27:42.280 --> 27:43.880
- coming up with something completely new.
-
-27:43.880 --> 27:45.480
- Yeah, I like the way you describe it.
-
-27:45.480 --> 27:50.440
- It's a nonheroic, acceptable way to start the company.
-
-27:50.440 --> 27:52.840
- And maybe more expedient.
-
-27:52.840 --> 27:58.920
- So that's, I think, a baggage for Silicon Valley,
-
-27:58.920 --> 28:01.320
- that if it doesn't let go, then it
-
-28:01.320 --> 28:05.160
- may limit the ultimate ceiling of the company.
-
-28:05.160 --> 28:07.200
- Take Snapchat as an example.
-
-28:07.200 --> 28:09.840
- I think Evan's brilliant.
-
-28:09.840 --> 28:11.480
- He built a great product.
-
-28:11.480 --> 28:14.160
- But he's very proud that he wants
-
-28:14.160 --> 28:16.800
- to build his own features, not copy others.
-
-28:16.800 --> 28:21.000
- While Facebook was more willing to copy his features,
-
-28:21.000 --> 28:23.440
- and you see what happens in the competition.
-
-28:23.440 --> 28:27.440
- So I think putting that handcuff on the company
-
-28:27.440 --> 28:31.560
- would limit its ability to reach the maximum potential.
-
-28:31.560 --> 28:33.800
- So back to the Chinese environment,
-
-28:33.800 --> 28:38.400
- copying was merely a way to learn from the American masters.
-
-28:38.400 --> 28:43.480
- Just like if we learned to play piano or painting,
-
-28:43.480 --> 28:44.560
- you start by copying.
-
-28:44.560 --> 28:46.160
- You don't start by innovating when
-
-28:46.160 --> 28:48.200
- you don't have the basic skill sets.
-
-28:48.200 --> 28:51.040
- So very amazingly, the Chinese entrepreneurs
-
-28:51.040 --> 28:56.160
- about six years ago started to branch off
-
-28:56.160 --> 28:59.520
- with these lean startups built on American ideas
-
-28:59.520 --> 29:02.280
- to build better products than American products.
-
-29:02.280 --> 29:04.960
- But they did start from the American idea.
-
-29:04.960 --> 29:08.600
- And today, WeChat is better than WhatsApp.
-
-29:08.600 --> 29:10.520
- Weibo is better than Twitter.
-
-29:10.520 --> 29:12.920
- Zihu is better than Quora and so on.
-
-29:12.920 --> 29:17.000
- So that, I think, is Chinese entrepreneurs
-
-29:17.000 --> 29:18.480
- going to step two.
-
-29:18.480 --> 29:21.760
- And then step three is once these entrepreneurs have
-
-29:21.760 --> 29:23.720
- done one or two of these companies,
-
-29:23.720 --> 29:27.400
- they now look at the Chinese market and the opportunities
-
-29:27.400 --> 29:30.600
- and come up with ideas that didn't exist elsewhere.
-
-29:30.600 --> 29:36.320
- So products like and financial under which includes Alipay,
-
-29:36.320 --> 29:42.080
- which is mobile payments, and also the financial products
-
-29:42.080 --> 29:48.560
- for loans built on that, and also in education, VIP kid,
-
-29:48.560 --> 29:54.880
- and in social video, social network, TikTok,
-
-29:54.880 --> 29:58.640
- and in social eCommerce, Pinduoduo,
-
-29:58.640 --> 30:01.720
- and then in ride sharing, Mobike.
-
-30:01.720 --> 30:05.640
- These are all Chinese innovative products
-
-30:05.640 --> 30:08.720
- that now are being copied elsewhere.
-
-30:08.720 --> 30:13.040
- So an additional interesting observation
-
-30:13.040 --> 30:16.000
- is some of these products are built on unique Chinese
-
-30:16.000 --> 30:19.360
- demographics, which may not work in the US,
-
-30:19.360 --> 30:23.160
- but may work very well in Southeast Asia, Africa,
-
-30:23.160 --> 30:27.840
- and other developing worlds that are a few years behind China.
-
-30:27.840 --> 30:31.040
- And a few of these products maybe are universal
-
-30:31.040 --> 30:33.760
- and are getting traction even in the United States,
-
-30:33.760 --> 30:35.360
- such as TikTok.
-
-30:35.360 --> 30:42.080
- So this whole ecosystem is supported by VCs
-
-30:42.080 --> 30:44.920
- as a virtuous cycle, because a large market
-
-30:44.920 --> 30:49.400
- with innovative entrepreneurs will draw a lot of money
-
-30:49.400 --> 30:51.560
- and then invest in these companies.
-
-30:51.560 --> 30:54.480
- As the market gets larger and larger,
-
-30:54.480 --> 30:58.400
- China market is easily three, four times larger than the US.
-
-30:58.400 --> 31:01.120
- They will create greater value and greater returns
-
-31:01.120 --> 31:05.400
- for the VCs, thereby raising even more money.
-
-31:05.400 --> 31:10.000
- So at Sinovation Ventures, our first fund was $15 million.
-
-31:10.000 --> 31:12.040
- Our last fund was $500 million.
-
-31:12.040 --> 31:16.520
- So it reflects the valuation of the companies
-
-31:16.520 --> 31:19.840
- and our us going multi stage and things like that.
-
-31:19.840 --> 31:23.840
- It also has government support, but not
-
-31:23.840 --> 31:26.080
- in the way most Americans would think of it.
-
-31:26.080 --> 31:29.520
- The government actually leaves the entrepreneurial space
-
-31:29.520 --> 31:33.200
- as a private enterprise, so the self regulating.
-
-31:33.200 --> 31:36.200
- And the government would build infrastructures
-
-31:36.200 --> 31:39.320
- that would around it to make it work better.
-
-31:39.320 --> 31:41.960
- For example, the mass entrepreneur mass innovation
-
-31:41.960 --> 31:44.880
- plan builds 8,000 incubators.
-
-31:44.880 --> 31:48.360
- So the pipeline is very strong to the VCs
-
-31:48.360 --> 31:49.680
- for autonomous vehicles.
-
-31:49.680 --> 31:53.280
- The Chinese government is building smart highways
-
-31:53.280 --> 31:56.680
- with sensors, smart cities that separate pedestrians
-
-31:56.680 --> 32:01.560
- from cars that may allow initially an inferior autonomous
-
-32:01.560 --> 32:05.760
- vehicle company to launch a car without increasing,
-
-32:05.760 --> 32:11.520
- with lower casualty, because the roads or the city is smart.
-
-32:11.520 --> 32:13.800
- And the Chinese government at local levels
-
-32:13.800 --> 32:17.360
- would have these guiding funds acting as LPs,
-
-32:17.360 --> 32:19.400
- passive LPs to funds.
-
-32:19.400 --> 32:23.240
- And when the fund makes money, part of the money made
-
-32:23.240 --> 32:27.280
- is given back to the GPs and potentially other LPs
-
-32:27.280 --> 32:31.960
- to increase everybody's return at the expense
-
-32:31.960 --> 32:33.680
- of the government's return.
-
-32:33.680 --> 32:36.360
- So that's an interesting incentive
-
-32:36.360 --> 32:41.640
- that entrusts the task of choosing entrepreneurs to VCs
-
-32:41.640 --> 32:43.800
- who are better at it than the government
-
-32:43.800 --> 32:46.680
- by letting some of the profits move that way.
-
-32:46.680 --> 32:48.720
- So this is really fascinating, right?
-
-32:48.720 --> 32:51.800
- So I look at the Russian government as a case study
-
-32:51.800 --> 32:54.480
- where, let me put it this way, there
-
-32:54.480 --> 32:58.520
- is no such government driven, large scale
-
-32:58.520 --> 33:00.840
- support of entrepreneurship.
-
-33:00.840 --> 33:04.000
- And probably the same is true in the United States.
-
-33:04.000 --> 33:07.640
- But the entrepreneurs themselves kind of find a way.
-
-33:07.640 --> 33:11.680
- So maybe in a form of advice or explanation,
-
-33:11.680 --> 33:15.560
- how did the Chinese government arrive to be this way,
-
-33:15.560 --> 33:17.680
- so supportive on entrepreneurship,
-
-33:17.680 --> 33:21.520
- to be in this particular way so forward thinking
-
-33:21.520 --> 33:23.120
- at such a large scale?
-
-33:23.120 --> 33:28.280
- And also perhaps, how can we copy it in other countries?
-
-33:28.280 --> 33:29.800
- How can we encourage other governments,
-
-33:29.800 --> 33:31.600
- like even the United States government,
-
-33:31.600 --> 33:33.760
- to support infrastructure for autonomous vehicles
-
-33:33.760 --> 33:36.040
- in that same kind of way, perhaps?
-
-33:36.040 --> 33:36.680
- Yes.
-
-33:36.680 --> 33:44.440
- So these techniques are the result of several key things,
-
-33:44.440 --> 33:46.480
- some of which may be learnable, some of which
-
-33:46.480 --> 33:48.440
- may be very hard.
-
-33:48.440 --> 33:51.080
- One is just trial and error and watching
-
-33:51.080 --> 33:52.960
- what everyone else is doing.
-
-33:52.960 --> 33:54.960
- I think it's important to be humble and not
-
-33:54.960 --> 33:56.920
- feel like you know all the answers.
-
-33:56.920 --> 33:59.480
- The guiding funds idea came from Singapore,
-
-33:59.480 --> 34:01.440
- which came from Israel.
-
-34:01.440 --> 34:06.080
- And China made a few tweaks and turned it into a,
-
-34:06.080 --> 34:09.600
- because the Chinese cities and government officials kind
-
-34:09.600 --> 34:11.320
- of compete with each other.
-
-34:11.320 --> 34:14.640
- Because they all want to make their city more successful,
-
-34:14.640 --> 34:20.280
- so they can get the next level in their political career.
-
-34:20.280 --> 34:22.320
- And it's somewhat competitive.
-
-34:22.320 --> 34:25.200
- So the central government made it a bit of a competition.
-
-34:25.200 --> 34:26.840
- Everybody has a budget.
-
-34:26.840 --> 34:29.840
- They can put it on AI, or they can put it on bio,
-
-34:29.840 --> 34:32.200
- or they can put it on energy.
-
-34:32.200 --> 34:35.040
- And then whoever gets the results, the city shines,
-
-34:35.040 --> 34:38.000
- the people are better off, the mayor gets a promotion.
-
-34:38.000 --> 34:41.680
- So the tools is kind of almost like an entrepreneurial
-
-34:41.680 --> 34:44.840
- environment for local governments
-
-34:44.840 --> 34:47.480
- to see who can do a better job.
-
-34:47.480 --> 34:52.440
- And also, many of them tried different experiments.
-
-34:52.440 --> 34:58.440
- Some have given award to very smart researchers,
-
-34:58.440 --> 35:00.840
- just give them money and hope they'll start a company.
-
-35:00.840 --> 35:05.840
- Some have given money to academic research labs,
-
-35:05.840 --> 35:08.440
- maybe government research labs, to see
-
-35:08.440 --> 35:11.920
- if they can spin off some companies from the science
-
-35:11.920 --> 35:14.040
- lab or something like that.
-
-35:14.040 --> 35:17.080
- Some have tried to recruit overseas Chinese
-
-35:17.080 --> 35:18.960
- to come back and start companies.
-
-35:18.960 --> 35:20.960
- And they've had mixed results.
-
-35:20.960 --> 35:23.400
- The one that worked the best was the guiding funds.
-
-35:23.400 --> 35:25.840
- So it's almost like a lean startup idea
-
-35:25.840 --> 35:29.160
- where people try different things in what works, sticks,
-
-35:29.160 --> 35:30.600
- and everybody copies.
-
-35:30.600 --> 35:32.880
- So now every city has a guiding fund.
-
-35:32.880 --> 35:35.680
- So that's how that came about.
-
-35:35.680 --> 35:40.400
- The autonomous vehicle and the massive spending
-
-35:40.400 --> 35:46.080
- in highways and smart cities, that's a Chinese way.
-
-35:46.080 --> 35:49.480
- It's about building infrastructure to facilitate.
-
-35:49.480 --> 35:52.840
- It's a clear division of the government's responsibility
-
-35:52.840 --> 35:55.400
- from the market.
-
-35:55.400 --> 36:00.560
- The market should do everything in a private freeway.
-
-36:00.560 --> 36:02.920
- But there are things the market can't afford to do,
-
-36:02.920 --> 36:04.520
- like infrastructure.
-
-36:04.520 --> 36:08.000
- So the government always appropriates
-
-36:08.000 --> 36:12.000
- large amounts of money for infrastructure building.
-
-36:12.000 --> 36:16.880
- This happens with not only autonomous vehicle and AI,
-
-36:16.880 --> 36:20.840
- but happened with the 3G and 4G.
-
-36:20.840 --> 36:25.320
- You'll find that the Chinese wireless reception
-
-36:25.320 --> 36:28.760
- is better than the US, because massive spending that
-
-36:28.760 --> 36:30.720
- tries to cover the whole country.
-
-36:30.720 --> 36:34.360
- Whereas in the US, it may be a little spotty.
-
-36:34.360 --> 36:36.160
- It's a government driven, because I think
-
-36:36.160 --> 36:44.120
- they view the coverage of cell access and 3G, 4G access
-
-36:44.120 --> 36:47.080
- to be a governmental infrastructure spending,
-
-36:47.080 --> 36:49.880
- as opposed to capitalistic.
-
-36:49.880 --> 36:52.160
- So of course, the state or enterprise
-
-36:52.160 --> 36:55.000
- is also publicly traded, but they also
-
-36:55.000 --> 36:57.720
- carry a government responsibility
-
-36:57.720 --> 37:00.240
- to deliver infrastructure to all.
-
-37:00.240 --> 37:01.880
- So it's a different way of thinking
-
-37:01.880 --> 37:05.400
- that may be very hard to inject into Western countries
-
-37:05.400 --> 37:09.280
- to say starting tomorrow, bandwidth infrastructure
-
-37:09.280 --> 37:13.840
- and highways are going to be governmental spending
-
-37:13.840 --> 37:16.240
- with some characteristics.
-
-37:16.240 --> 37:18.240
- What's your sense, and sorry to interrupt,
-
-37:18.240 --> 37:21.680
- but because it's such a fascinating point,
-
-37:21.680 --> 37:25.600
- do you think on the autonomous vehicle space
-
-37:25.600 --> 37:30.120
- it's possible to solve the problem of full autonomy
-
-37:30.120 --> 37:34.040
- without significant investment in infrastructure?
-
-37:34.040 --> 37:36.400
- Well, that's really hard to speculate.
-
-37:36.400 --> 37:38.960
- I think it's not a yes, no question,
-
-37:38.960 --> 37:41.920
- but how long does it take question?
-
-37:41.920 --> 37:45.120
- 15 years, 30 years, 45 years.
-
-37:45.120 --> 37:48.960
- Clearly with infrastructure augmentation,
-
-37:48.960 --> 37:52.320
- where there's road, the city, or whole city planning,
-
-37:52.320 --> 37:56.440
- building a new city, I'm sure that will accelerate
-
-37:56.440 --> 37:59.040
- the day of the L5.
-
-37:59.040 --> 38:01.520
- I'm not knowledgeable enough, and it's
-
-38:01.520 --> 38:03.920
- hard to predict even when we're knowledgeable,
-
-38:03.920 --> 38:07.120
- because a lot of it is speculative.
-
-38:07.120 --> 38:09.800
- But in the US, I don't think people
-
-38:09.800 --> 38:13.240
- would consider building a new city the size of Chicago
-
-38:13.240 --> 38:15.920
- to make it the AI slash autonomous city.
-
-38:15.920 --> 38:18.840
- There are smaller ones being built, I'm aware of that.
-
-38:18.840 --> 38:21.280
- But is infrastructure spend really
-
-38:21.280 --> 38:23.720
- impossible for US or Western countries?
-
-38:23.720 --> 38:25.680
- I don't think so.
-
-38:25.680 --> 38:28.920
- The US highway system was built.
-
-38:28.920 --> 38:31.960
- Was that during President Eisenhower or Kennedy?
-
-38:31.960 --> 38:33.160
- Eisenhower, yeah.
-
-38:33.160 --> 38:38.960
- So maybe historians can study how the President Eisenhower
-
-38:38.960 --> 38:42.960
- get the resources to build this massive infrastructure that
-
-38:42.960 --> 38:47.560
- surely gave US a tremendous amount of prosperity
-
-38:47.560 --> 38:50.800
- over the next decade, if not century.
-
-38:50.800 --> 38:53.240
- If I may comment on that, then, it
-
-38:53.240 --> 38:54.880
- takes us to artificial intelligence
-
-38:54.880 --> 38:58.080
- a little bit, because in order to build infrastructure,
-
-38:58.080 --> 39:00.520
- it creates a lot of jobs.
-
-39:00.520 --> 39:02.840
- So I'll be actually interested if you
-
-39:02.840 --> 39:06.120
- would say that you're talking in your book about all kinds
-
-39:06.120 --> 39:08.960
- of jobs that could and could not be automated.
-
-39:08.960 --> 39:12.000
- I wonder if building infrastructure
-
-39:12.000 --> 39:15.720
- is one of the jobs that would not be easily automated,
-
-39:15.720 --> 39:18.160
- something you can think about, because I think you've mentioned
-
-39:18.160 --> 39:21.160
- somewhere in a talk, or that there
-
-39:21.160 --> 39:24.280
- might be, as jobs are being automated,
-
-39:24.280 --> 39:28.160
- a role for government to create jobs that can't be automated.
-
-39:28.160 --> 39:31.040
- Yes, I think that's a possibility.
-
-39:31.040 --> 39:34.280
- Back in the last financial crisis,
-
-39:34.280 --> 39:40.320
- China put a lot of money to basically give this economy
-
-39:40.320 --> 39:45.520
- a boost, and a lot of it went into infrastructure building.
-
-39:45.520 --> 39:49.920
- And I think that's a legitimate way, at the government level,
-
-39:49.920 --> 39:55.680
- to deal with the employment issues as well as build out
-
-39:55.680 --> 39:58.960
- the infrastructure, as long as the infrastructures are truly
-
-39:58.960 --> 40:03.160
- needed, and as long as there is an employment problem, which
-
-40:03.160 --> 40:04.960
- we don't know.
-
-40:04.960 --> 40:07.920
- So maybe taking a little step back,
-
-40:07.920 --> 40:12.840
- if you've been a leader and a researcher in AI
-
-40:12.840 --> 40:16.200
- for several decades, at least 30 years,
-
-40:16.200 --> 40:21.040
- so how has AI changed in the West and the East
-
-40:21.040 --> 40:23.120
- as you've observed, as you've been deep in it
-
-40:23.120 --> 40:25.120
- over the past 30 years?
-
-40:25.120 --> 40:28.520
- Well, AI began as the pursuit of understanding
-
-40:28.520 --> 40:34.160
- human intelligence, and the term itself represents that.
-
-40:34.160 --> 40:37.680
- But it kind of drifted into the one subarea that
-
-40:37.680 --> 40:40.880
- worked extremely well, which is machine intelligence.
-
-40:40.880 --> 40:45.080
- And that's actually more using pattern recognition techniques
-
-40:45.080 --> 40:51.280
- to basically do incredibly well on a limited domain,
-
-40:51.280 --> 40:54.840
- large amount of data, but relatively simple kinds
-
-40:54.840 --> 40:58.720
- of planning, tasks, and not very creative.
-
-40:58.720 --> 41:02.480
- So we didn't end up building human intelligence.
-
-41:02.480 --> 41:04.760
- We built a different machine that
-
-41:04.760 --> 41:08.040
- was a lot better than us, some problems,
-
-41:08.040 --> 41:11.840
- but nowhere close to us on other problems.
-
-41:11.840 --> 41:14.200
- So today, I think a lot of people still
-
-41:14.200 --> 41:18.080
- misunderstand when we say artificial intelligence
-
-41:18.080 --> 41:20.720
- and what various products can do.
-
-41:20.720 --> 41:24.160
- People still think it's about replicating human intelligence.
-
-41:24.160 --> 41:26.160
- But the products out there really
-
-41:26.160 --> 41:31.680
- are closer to having invented the internet or the spreadsheet
-
-41:31.680 --> 41:35.360
- or the database and getting broader adoption.
-
-41:35.360 --> 41:38.400
- And speaking further to the fears, near term fears
-
-41:38.400 --> 41:41.240
- that people have about AI, so you're commenting
-
-41:41.240 --> 41:45.680
- on the general intelligence that people
-
-41:45.680 --> 41:48.040
- in the popular culture from sci fi movies
-
-41:48.040 --> 41:50.920
- have a sense about AI, but there's practical fears
-
-41:50.920 --> 41:54.800
- about AI, the kind of narrow AI that you're talking about
-
-41:54.800 --> 41:57.280
- of automating particular kinds of jobs,
-
-41:57.280 --> 41:59.400
- and you talk about them in the book.
-
-41:59.400 --> 42:01.520
- So what are the kinds of jobs in your view
-
-42:01.520 --> 42:04.840
- that you see in the next five, 10 years beginning
-
-42:04.840 --> 42:09.240
- to be automated by AI systems algorithms?
-
-42:09.240 --> 42:13.000
- Yes, this is also maybe a little bit counterintuitive
-
-42:13.000 --> 42:15.440
- because it's the routine jobs that
-
-42:15.440 --> 42:18.360
- will be displaced the soonest.
-
-42:18.360 --> 42:23.120
- And they may not be displaced entirely, maybe 50%, 80%
-
-42:23.120 --> 42:26.320
- of a job, but when the workload drops by that much,
-
-42:26.320 --> 42:28.760
- employment will come down.
-
-42:28.760 --> 42:31.520
- And also another part of misunderstanding
-
-42:31.520 --> 42:35.720
- is most people think of AI replacing routine jobs,
-
-42:35.720 --> 42:38.760
- then they think of the assembly line, the workers.
-
-42:38.760 --> 42:40.960
- Well, that will have some effects,
-
-42:40.960 --> 42:44.600
- but it's actually the routine white collar workers that's
-
-42:44.600 --> 42:49.280
- easiest to replace because to replace a white collar worker,
-
-42:49.280 --> 42:50.720
- you just need software.
-
-42:50.720 --> 42:53.120
- To replace a blue collar worker,
-
-42:53.120 --> 42:57.200
- you need robotics, mechanical excellence,
-
-42:57.200 --> 43:01.880
- and the ability to deal with dexterity,
-
-43:01.880 --> 43:05.640
- and maybe even unknown environments, very, very difficult.
-
-43:05.640 --> 43:11.200
- So if we were to categorize the most dangerous white collar
-
-43:11.200 --> 43:15.600
- jobs, they would be things like back office,
-
-43:15.600 --> 43:20.800
- people who copy and paste and deal with simple computer
-
-43:20.800 --> 43:25.560
- programs and data, and maybe paper and OCR,
-
-43:25.560 --> 43:29.000
- and they don't make strategic decisions,
-
-43:29.000 --> 43:32.040
- they basically facilitate the process.
-
-43:32.040 --> 43:34.680
- These software and paper systems don't work,
-
-43:34.680 --> 43:40.520
- so you have people dealing with new employee orientation,
-
-43:40.520 --> 43:45.400
- searching for past lawsuits and financial documents,
-
-43:45.400 --> 43:49.800
- and doing reference check, so basic searching and management
-
-43:49.800 --> 43:52.800
- of data that's the most in danger of being lost.
-
-43:52.800 --> 43:56.440
- In addition to the white collar repetitive work,
-
-43:56.440 --> 43:59.360
- a lot of simple interaction work can also
-
-43:59.360 --> 44:02.840
- be taken care of, such as tele sales, telemarketing,
-
-44:02.840 --> 44:07.280
- customer service, as well as many physical jobs
-
-44:07.280 --> 44:09.880
- that are in the same location and don't
-
-44:09.880 --> 44:12.240
- require a high degree of dexterity,
-
-44:12.240 --> 44:17.840
- so fruit picking, dishwashing, assembly line, inspection,
-
-44:17.840 --> 44:20.360
- our jobs in that category.
-
-44:20.360 --> 44:25.440
- So altogether, back office is a big part,
-
-44:25.440 --> 44:29.840
- and the other, the blue collar may be smaller initially,
-
-44:29.840 --> 44:32.560
- but over time, AI will get better.
-
-44:32.560 --> 44:36.880
- And when we start to get to over the next 15, 20 years,
-
-44:36.880 --> 44:39.120
- the ability to actually have the dexterity
-
-44:39.120 --> 44:42.600
- of doing assembly line, that's a huge chunk of jobs.
-
-44:42.600 --> 44:44.760
- And when autonomous vehicles start
-
-44:44.760 --> 44:47.400
- to work initially starting with truck drivers,
-
-44:47.400 --> 44:49.640
- but eventually to all drivers, that's
-
-44:49.640 --> 44:52.040
- another huge group of workers.
-
-44:52.040 --> 44:55.560
- So I see modest numbers in the next five years,
-
-44:55.560 --> 44:58.080
- but increasing rapidly after that.
-
-44:58.080 --> 45:01.240
- On the worry of the jobs that are in danger
-
-45:01.240 --> 45:04.320
- and the gradual loss of jobs, I'm not
-
-45:04.320 --> 45:06.680
- sure if you're familiar with Andrew Yang.
-
-45:06.680 --> 45:07.800
- Yes, I am.
-
-45:07.800 --> 45:10.560
- So there's a candidate for president of the United States
-
-45:10.560 --> 45:14.960
- whose platform, Andrew Yang, is based around, in part,
-
-45:14.960 --> 45:17.680
- around job loss due to automation,
-
-45:17.680 --> 45:21.120
- and also, in addition, the need, perhaps,
-
-45:21.120 --> 45:26.120
- of universal basic income to support jobs that are folks who
-
-45:26.120 --> 45:28.560
- lose their job due to automation and so on,
-
-45:28.560 --> 45:31.960
- and in general, support people under complex,
-
-45:31.960 --> 45:34.320
- unstable job market.
-
-45:34.320 --> 45:36.720
- So what are your thoughts about his concerns,
-
-45:36.720 --> 45:40.000
- him as a candidate, his ideas in general?
-
-45:40.000 --> 45:44.600
- I think his thinking is generally in the right direction,
-
-45:44.600 --> 45:48.440
- but his approach as a presidential candidate
-
-45:48.440 --> 45:52.240
- may be a little bit ahead at the time.
-
-45:52.240 --> 45:56.080
- I think the displacements will happen,
-
-45:56.080 --> 45:58.280
- but will they happen soon enough for people
-
-45:58.280 --> 46:00.480
- to agree to vote for him?
-
-46:00.480 --> 46:03.760
- The unemployment numbers are not very high yet.
-
-46:03.760 --> 46:07.600
- And I think he and I have the same challenge.
-
-46:07.600 --> 46:11.520
- If I want to theoretically convince people this is an issue
-
-46:11.520 --> 46:13.880
- and he wants to become the president,
-
-46:13.880 --> 46:17.760
- people have to see how can this be the case when
-
-46:17.760 --> 46:19.680
- unemployment numbers are low.
-
-46:19.680 --> 46:21.360
- So that is the challenge.
-
-46:21.360 --> 46:27.360
- And I think I do agree with him on the displacement issue,
-
-46:27.360 --> 46:32.280
- on universal basic income, at a very vanilla level.
-
-46:32.280 --> 46:36.800
- I don't agree with it because I think the main issue
-
-46:36.800 --> 46:38.320
- is retraining.
-
-46:38.320 --> 46:43.200
- So people need to be incented not by just giving a monthly
-
-46:43.200 --> 46:47.160
- $2,000 check or $1,000 check and do whatever they want
-
-46:47.160 --> 46:50.920
- because they don't have the know how
-
-46:50.920 --> 46:56.840
- to know what to retrain to go into what type of a job
-
-46:56.840 --> 46:58.640
- and guidance is needed.
-
-46:58.640 --> 47:01.720
- And retraining is needed because historically
-
-47:01.720 --> 47:05.080
- in technology revolutions, when routine jobs were displaced,
-
-47:05.080 --> 47:06.920
- new routine jobs came up.
-
-47:06.920 --> 47:09.400
- So there was always room for that.
-
-47:09.400 --> 47:12.640
- But with AI and automation, the whole point
-
-47:12.640 --> 47:15.320
- is replacing all routine jobs eventually.
-
-47:15.320 --> 47:17.840
- So there will be fewer and fewer routine jobs.
-
-47:17.840 --> 47:22.640
- And AI will create jobs, but it won't create routine jobs
-
-47:22.640 --> 47:24.840
- because if it creates routine jobs,
-
-47:24.840 --> 47:26.880
- why wouldn't AI just do it?
-
-47:26.880 --> 47:30.360
- So therefore, the people who are losing the jobs
-
-47:30.360 --> 47:32.280
- are losing routine jobs.
-
-47:32.280 --> 47:35.720
- The jobs that are becoming available are nonroutine jobs.
-
-47:35.720 --> 47:39.320
- So the social stipend needs to be put in place
-
-47:39.320 --> 47:42.040
- is for the routine workers who lost their jobs
-
-47:42.040 --> 47:46.120
- to be retrained maybe in six months, maybe in three years.
-
-47:46.120 --> 47:48.560
- Takes a while to retrain on the nonroutine job
-
-47:48.560 --> 47:51.360
- and then take on a job that will last
-
-47:51.360 --> 47:53.400
- for that person's lifetime.
-
-47:53.400 --> 47:56.160
- Now, having said that, if you look deeply
-
-47:56.160 --> 47:58.240
- into Andrew's document, he does cater for that.
-
-47:58.240 --> 48:03.240
- So I'm not disagreeing with what he's trying to do.
-
-48:03.280 --> 48:06.360
- But for simplification, sometimes he just says UBI,
-
-48:06.360 --> 48:08.760
- but simple UBI wouldn't work.
-
-48:08.760 --> 48:10.600
- And I think you've mentioned elsewhere
-
-48:10.600 --> 48:15.600
- that the goal isn't necessarily to give people enough money
-
-48:15.760 --> 48:19.120
- to survive or live or even to prosper.
-
-48:19.120 --> 48:22.800
- The point is to give them a job that gives them meaning.
-
-48:22.800 --> 48:25.600
- That meaning is extremely important.
-
-48:25.600 --> 48:28.600
- That our employment, at least in the United States
-
-48:28.600 --> 48:31.200
- and perhaps it cares across the world,
-
-48:31.200 --> 48:34.600
- provides something that's, forgive me for saying,
-
-48:34.600 --> 48:36.960
- greater than money, it provides meaning.
-
-48:38.400 --> 48:43.400
- So now what kind of jobs do you think can't be automated?
-
-48:44.840 --> 48:46.600
- You talk a little bit about creativity
-
-48:46.600 --> 48:48.200
- and compassion in your book.
-
-48:48.200 --> 48:50.720
- What aspects do you think it's difficult
-
-48:50.720 --> 48:52.320
- to automate for an AI system?
-
-48:52.320 --> 48:57.320
- Because an AI system is currently merely optimizing.
-
-48:57.360 --> 49:00.120
- It's not able to reason, plan,
-
-49:00.120 --> 49:02.920
- or think creatively or strategically.
-
-49:02.920 --> 49:05.320
- It's not able to deal with complex problems.
-
-49:05.320 --> 49:09.520
- It can't come up with a new problem and solve it.
-
-49:09.520 --> 49:12.320
- A human needs to find the problem
-
-49:12.320 --> 49:15.520
- and pose it as an optimization problem,
-
-49:15.520 --> 49:17.520
- then have the AI work at it.
-
-49:17.520 --> 49:21.320
- So an AI would have a very hard time
-
-49:21.320 --> 49:23.320
- discovering a new drug
-
-49:23.320 --> 49:26.320
- or discovering a new style of painting
-
-49:27.320 --> 49:30.320
- or dealing with complex tasks
-
-49:30.320 --> 49:32.320
- such as managing a company
-
-49:32.320 --> 49:35.320
- that isn't just about optimizing the bottom line,
-
-49:35.320 --> 49:39.320
- but also about employee satisfaction, corporate brand,
-
-49:39.320 --> 49:40.320
- and many, many other things.
-
-49:40.320 --> 49:44.320
- So that is one category of things.
-
-49:44.320 --> 49:48.320
- And because these things are challenging, creative, complex,
-
-49:48.320 --> 49:52.320
- doing them creates a higher degree of satisfaction
-
-49:52.320 --> 49:55.320
- and therefore appealing to our desire for working,
-
-49:55.320 --> 49:57.320
- which isn't just to make the money,
-
-49:57.320 --> 49:58.320
- make the ends meet,
-
-49:58.320 --> 50:00.320
- but also that we've accomplished something
-
-50:00.320 --> 50:03.320
- that others maybe can't do or can't do as well.
-
-50:04.320 --> 50:07.320
- Another type of job that is much numerous
-
-50:07.320 --> 50:09.320
- would be compassionate jobs,
-
-50:09.320 --> 50:14.320
- jobs that require compassion, empathy, human touch, human trust.
-
-50:14.320 --> 50:18.320
- AI can't do that because AI is cold, calculating,
-
-50:18.320 --> 50:22.320
- and even if it can fake that to some extent,
-
-50:22.320 --> 50:26.320
- it will make errors and that will make it look very silly.
-
-50:26.320 --> 50:29.320
- And also, I think even if AI did okay,
-
-50:29.320 --> 50:33.320
- people would want to interact with another person,
-
-50:33.320 --> 50:38.320
- whether it's for some kind of a service or a teacher or a doctor
-
-50:38.320 --> 50:41.320
- or a concierge or a masseuse or bartender.
-
-50:41.320 --> 50:46.320
- There are so many jobs where people just don't want to interact
-
-50:46.320 --> 50:49.320
- with a cold robot or software.
-
-50:50.320 --> 50:53.320
- I've had an entrepreneur who built an elderly care robot
-
-50:53.320 --> 50:58.320
- and they found that the elderly really only use it for customer service.
-
-50:58.320 --> 51:00.320
- But not to service the product,
-
-51:00.320 --> 51:05.320
- but they click on customer service and the video of a person comes up
-
-51:05.320 --> 51:07.320
- and then the person says,
-
-51:07.320 --> 51:11.320
- how come my daughter didn't call me? Let me show you a picture of her grandkids.
-
-51:11.320 --> 51:15.320
- So people earn for that, people people interaction.
-
-51:15.320 --> 51:19.320
- So even if robots improved, people just don't want it.
-
-51:19.320 --> 51:21.320
- And those jobs are going to be increasing
-
-51:21.320 --> 51:24.320
- because AI will create a lot of value,
-
-51:24.320 --> 51:29.320
- $16 trillion to the world in next 11 years according to PWC
-
-51:29.320 --> 51:34.320
- and that will give people money to enjoy services,
-
-51:34.320 --> 51:39.320
- whether it's eating a gourmet meal or tourism and traveling
-
-51:39.320 --> 51:41.320
- or having concierge services.
-
-51:41.320 --> 51:44.320
- The services revolving around, you know,
-
-51:44.320 --> 51:47.320
- every dollar of that $16 trillion will be tremendous.
-
-51:47.320 --> 51:52.320
- It will create more opportunities to service the people who did well
-
-51:52.320 --> 51:55.320
- through AI with things.
-
-51:55.320 --> 52:01.320
- But even at the same time, the entire society is very much short
-
-52:01.320 --> 52:05.320
- in need of many service oriented, compassionate oriented jobs.
-
-52:05.320 --> 52:10.320
- The best example is probably in healthcare services.
-
-52:10.320 --> 52:15.320
- There's going to be 2 million new jobs, not counting replacement,
-
-52:15.320 --> 52:20.320
- just brand new incremental jobs in the next six years in healthcare services.
-
-52:20.320 --> 52:24.320
- That includes nurses orderly in the hospital,
-
-52:24.320 --> 52:29.320
- elderly care and also at home care.
-
-52:29.320 --> 52:31.320
- It's particularly lacking.
-
-52:31.320 --> 52:34.320
- And those jobs are not likely to be filled.
-
-52:34.320 --> 52:36.320
- So there's likely to be a shortage.
-
-52:36.320 --> 52:41.320
- And the reason they're not filled is simply because they don't pay very well
-
-52:41.320 --> 52:47.320
- and that the social status of these jobs are not very good.
-
-52:47.320 --> 52:52.320
- So they pay about half as much as a heavy equipment operator,
-
-52:52.320 --> 52:55.320
- which will be replaced a lot sooner.
-
-52:55.320 --> 52:59.320
- And they pay probably comparably to someone on the assembly line.
-
-52:59.320 --> 53:03.320
- And so if we're ignoring all the other issues
-
-53:03.320 --> 53:07.320
- and just think about satisfaction from one's job,
-
-53:07.320 --> 53:11.320
- someone repetitively doing the same manual action at an assembly line,
-
-53:11.320 --> 53:14.320
- that can't create a lot of job satisfaction.
-
-53:14.320 --> 53:17.320
- But someone taking care of a sick person
-
-53:17.320 --> 53:21.320
- and getting a hug and thank you from that person and the family,
-
-53:21.320 --> 53:24.320
- I think is quite satisfying.
-
-53:24.320 --> 53:28.320
- So if only we could fix the pay for service jobs,
-
-53:28.320 --> 53:33.320
- there are plenty of jobs that require some training or a lot of training
-
-53:33.320 --> 53:36.320
- for the people coming off the routine jobs to take.
-
-53:36.320 --> 53:43.320
- We can easily imagine someone who was maybe a cashier at the grocery store,
-
-53:43.320 --> 53:49.320
- at stores become automated, learns to become a nurse or at home care.
-
-53:49.320 --> 53:54.320
- Also, I do want to point out the blue collar jobs are going to stay around a bit longer,
-
-53:54.320 --> 53:57.320
- some of them quite a bit longer.
-
-53:57.320 --> 54:01.320
- AI cannot be told, go clean an arbitrary home.
-
-54:01.320 --> 54:03.320
- That's incredibly hard.
-
-54:03.320 --> 54:07.320
- Arguably is an L5 level of difficulty.
-
-54:07.320 --> 54:09.320
- And then AI cannot be a good plumber,
-
-54:09.320 --> 54:12.320
- because plumber is almost like a mini detective
-
-54:12.320 --> 54:15.320
- that has to figure out where the leak came from.
-
-54:15.320 --> 54:22.320
- So yet AI probably can be an assembly line and auto mechanic and so on.
-
-54:22.320 --> 54:26.320
- So one has to study which blue collar jobs are going away
-
-54:26.320 --> 54:30.320
- and facilitate retraining for the people to go into the ones that won't go away
-
-54:30.320 --> 54:32.320
- or maybe even will increase.
-
-54:32.320 --> 54:39.320
- I mean, it is fascinating that it's easier to build a world champion chess player
-
-54:39.320 --> 54:41.320
- than it is to build a mediocre plumber.
-
-54:41.320 --> 54:43.320
- Yes, very true.
-
-54:43.320 --> 54:47.320
- And to AI, and that goes counterintuitive to a lot of people's understanding
-
-54:47.320 --> 54:49.320
- of what artificial intelligence is.
-
-54:49.320 --> 54:53.320
- So it sounds, I mean, you're painting a pretty optimistic picture
-
-54:53.320 --> 54:56.320
- about retraining, about the number of jobs
-
-54:56.320 --> 55:01.320
- and actually the meaningful nature of those jobs once we automate repetitive tasks.
-
-55:01.320 --> 55:07.320
- So overall, are you optimistic about the future
-
-55:07.320 --> 55:11.320
- where much of the repetitive tasks are automated,
-
-55:11.320 --> 55:15.320
- that there is a lot of room for humans, for the compassionate,
-
-55:15.320 --> 55:19.320
- for the creative input that only humans can provide?
-
-55:19.320 --> 55:23.320
- I am optimistic if we start to take action.
-
-55:23.320 --> 55:27.320
- If we have no action in the next five years,
-
-55:27.320 --> 55:33.320
- I think it's going to be hard to deal with the devastating losses that will emerge.
-
-55:33.320 --> 55:39.320
- So if we start thinking about retraining, maybe with the low hanging fruits,
-
-55:39.320 --> 55:45.320
- explaining to vocational schools why they should train more plumbers than auto mechanics,
-
-55:45.320 --> 55:53.320
- maybe starting with some government subsidy for corporations to have more training positions.
-
-55:53.320 --> 55:57.320
- We start to explain to people why retraining is important.
-
-55:57.320 --> 56:00.320
- We start to think about what the future of education,
-
-56:00.320 --> 56:04.320
- how that needs to be tweaked for the era of AI.
-
-56:04.320 --> 56:06.320
- If we start to make incremental progress,
-
-56:06.320 --> 56:09.320
- and the greater number of people understand,
-
-56:09.320 --> 56:12.320
- then there's no reason to think we can't deal with this,
-
-56:12.320 --> 56:16.320
- because this technological revolution is arguably similar to
-
-56:16.320 --> 56:20.320
- what electricity, industrial revolutions, and internet brought about.
-
-56:20.320 --> 56:24.320
- Do you think there's a role for policy, for governments to step in
-
-56:24.320 --> 56:27.320
- to help with policy to create a better world?
-
-56:27.320 --> 56:32.320
- Absolutely, and the governments don't have to believe
-
-56:32.320 --> 56:39.320
- that unemployment will go up, and they don't have to believe automation will be this fast to do something.
-
-56:39.320 --> 56:42.320
- Revamping vocational school would be one example.
-
-56:42.320 --> 56:47.320
- Another is if there's a big gap in healthcare service employment,
-
-56:47.320 --> 56:54.320
- and we know that a country's population is growing older and more longevity living older,
-
-56:54.320 --> 56:59.320
- because people over 80 require five times as much care as those under 80,
-
-56:59.320 --> 57:04.320
- then it is a good time to incent training programs for elderly care,
-
-57:04.320 --> 57:07.320
- to find ways to improve the pay.
-
-57:07.320 --> 57:13.320
- Maybe one way would be to offer as part of Medicare or the equivalent program
-
-57:13.320 --> 57:18.320
- for people over 80 to be entitled to a few hours of elderly care at home,
-
-57:18.320 --> 57:21.320
- and then that might be reimbursable,
-
-57:21.320 --> 57:28.320
- and that will stimulate the service industry around the policy.
-
-57:28.320 --> 57:32.320
- Do you have concerns about large entities,
-
-57:32.320 --> 57:38.320
- whether it's governments or companies, controlling the future of AI development in general?
-
-57:38.320 --> 57:40.320
- So we talked about companies.
-
-57:40.320 --> 57:48.320
- Do you have a better sense that governments can better represent the interest of the people
-
-57:48.320 --> 57:54.320
- than companies, or do you believe companies are better at representing the interest of the people?
-
-57:54.320 --> 57:56.320
- Or is there no easy answer?
-
-57:56.320 --> 57:59.320
- I don't think there's an easy answer because it's a double edged sword.
-
-57:59.320 --> 58:06.320
- The companies and governments can provide better services with more access to data and more access to AI,
-
-58:06.320 --> 58:13.320
- but that also leads to greater power, which can lead to uncontrollable problems,
-
-58:13.320 --> 58:17.320
- whether it's monopoly or corruption in the government.
-
-58:17.320 --> 58:24.320
- So I think one has to be careful to look at how much data that companies and governments have,
-
-58:24.320 --> 58:29.320
- and some kind of checks and balances would be helpful.
-
-58:29.320 --> 58:33.320
- So again, I come from Russia.
-
-58:33.320 --> 58:36.320
- There's something called the Cold War.
-
-58:36.320 --> 58:40.320
- So let me ask a difficult question here, looking at conflict.
-
-58:40.320 --> 58:45.320
- Steven Pinker wrote a great book that conflict all over the world is decreasing in general.
-
-58:45.320 --> 58:51.320
- But do you have a sense that having written the book AI Superpowers,
-
-58:51.320 --> 58:57.320
- do you see a major international conflict potentially arising between major nations,
-
-58:57.320 --> 59:02.320
- whatever they are, whether it's Russia, China, European nations, United States,
-
-59:02.320 --> 59:09.320
- or others in the next 10, 20, 50 years around AI, around the digital space, cyber space?
-
-59:09.320 --> 59:12.320
- Do you worry about that?
-
-59:12.320 --> 59:19.320
- Is that something we need to think about and try to alleviate or prevent?
-
-59:19.320 --> 59:22.320
- I believe in greater engagement.
-
-59:22.320 --> 59:33.320
- A lot of the worries about more powerful AI are based on an arms race metaphor.
-
-59:33.320 --> 59:41.320
- And when you extrapolate into military kinds of scenarios,
-
-59:41.320 --> 59:48.320
- AI can automate autonomous weapons that needs to be controlled somehow.
-
-59:48.320 --> 59:57.320
- And autonomous decision making can lead to not enough time to fix international crises.
-
-59:57.320 --> 1:00:02.320
- So I actually believe a Cold War mentality would be very dangerous
-
-1:00:02.320 --> 1:00:07.320
- because should two countries rely on AI to make certain decisions
-
-1:00:07.320 --> 1:00:11.320
- and they don't even talk to each other, they do their own scenario planning,
-
-1:00:11.320 --> 1:00:14.320
- then something could easily go wrong.
-
-1:00:14.320 --> 1:00:24.320
- I think engagement, interaction, some protocols to avoid inadvertent disasters is actually needed.
-
-1:00:24.320 --> 1:00:28.320
- So it's natural for each country to want to be the best,
-
-1:00:28.320 --> 1:00:34.320
- whether it's in nuclear technologies or AI or bio.
-
-1:00:34.320 --> 1:00:40.320
- But I think it's important to realize if each country has a black box AI
-
-1:00:40.320 --> 1:00:48.320
- and don't talk to each other, that probably presents greater challenges to humanity
-
-1:00:48.320 --> 1:00:50.320
- than if they interacted.
-
-1:00:50.320 --> 1:00:56.320
- I think there can still be competition, but with some degree of protocol for interaction.
-
-1:00:56.320 --> 1:01:01.320
- Just like when there was a nuclear competition,
-
-1:01:01.320 --> 1:01:07.320
- there were some protocol for deterrence among US, Russia, and China.
-
-1:01:07.320 --> 1:01:10.320
- And I think that engagement is needed.
-
-1:01:10.320 --> 1:01:15.320
- So of course, we're still far from AI presenting that kind of danger.
-
-1:01:15.320 --> 1:01:22.320
- But what I worry the most about is the level of engagement seems to be coming down.
-
-1:01:22.320 --> 1:01:25.320
- The level of distrust seems to be going up,
-
-1:01:25.320 --> 1:01:32.320
- especially from the US towards other large countries such as China and Russia.
-
-1:01:32.320 --> 1:01:34.320
- Is there a way to make that better?
-
-1:01:34.320 --> 1:01:40.320
- So that's beautifully put, level of engagement and even just basic trust and communication
-
-1:01:40.320 --> 1:01:52.320
- as opposed to making artificial enemies out of particular countries.
-
-1:01:52.320 --> 1:02:01.320
- Do you have a sense how we can make it better, actionable items that as a society we can take on?
-
-1:02:01.320 --> 1:02:10.320
- I'm not an expert at geopolitics, but I would say that we look pretty foolish as humankind
-
-1:02:10.320 --> 1:02:19.320
- when we are faced with the opportunity to create $16 trillion for humanity.
-
-1:02:19.320 --> 1:02:29.320
- And yet we're not solving fundamental problems with parts of the world still in poverty.
-
-1:02:29.320 --> 1:02:34.320
- And for the first time, we have the resources to overcome poverty and hunger.
-
-1:02:34.320 --> 1:02:38.320
- We're not using it on that, but we're fueling competition among superpowers.
-
-1:02:38.320 --> 1:02:41.320
- And that's a very unfortunate thing.
-
-1:02:41.320 --> 1:02:54.320
- If we become utopian for a moment, imagine a benevolent world government that has this $16 trillion
-
-1:02:54.320 --> 1:03:02.320
- and maybe some AI to figure out how to use it to deal with diseases and problems and hate and things like that.
-
-1:03:02.320 --> 1:03:04.320
- World would be a lot better off.
-
-1:03:04.320 --> 1:03:07.320
- So what is wrong with the current world?
-
-1:03:07.320 --> 1:03:13.320
- I think the people with more skill than I should think about this.
-
-1:03:13.320 --> 1:03:19.320
- And then the geopolitics issue with superpower competition is one side of the issue.
-
-1:03:19.320 --> 1:03:29.320
- There's another side which I worry maybe even more, which is as the $16 trillion all gets made by U.S. and China
-
-1:03:29.320 --> 1:03:34.320
- and a few of the other developed countries, the poorer country will get nothing
-
-1:03:34.320 --> 1:03:42.320
- because they don't have technology and the wealth disparity and inequality will increase.
-
-1:03:42.320 --> 1:03:50.320
- So a poorer country with a large population will not only benefit from the AI boom or other technology booms
-
-1:03:50.320 --> 1:03:57.320
- but they will have their workers who previously had hoped they could do the China model and do outsource manufacturing
-
-1:03:57.320 --> 1:04:02.320
- or the India model so they could do the outsource process or call center
-
-1:04:02.320 --> 1:04:05.320
- while all those jobs are going to be gone in 10 or 15 years.
-
-1:04:05.320 --> 1:04:14.320
- So the individual citizen may be a net liability, I mean financially speaking, to a poorer country
-
-1:04:14.320 --> 1:04:19.320
- and not an asset to claw itself out of poverty.
-
-1:04:19.320 --> 1:04:29.320
- So in that kind of situation, these large countries with not much tech are going to be facing a downward spiral
-
-1:04:29.320 --> 1:04:37.320
- and it's unclear what could be done and then when we look back and say there's $16 trillion being created
-
-1:04:37.320 --> 1:04:43.320
- and it's all being kept by U.S. China and other developed countries, it just doesn't feel right.
-
-1:04:43.320 --> 1:04:50.320
- So I hope people who know about geopolitics can find solutions that's beyond my expertise.
-
-1:04:50.320 --> 1:04:54.320
- So different countries that we've talked about have different value systems.
-
-1:04:54.320 --> 1:05:02.320
- If you look at the United States to an almost extreme degree, there is an absolute desire for freedom of speech.
-
-1:05:02.320 --> 1:05:14.320
- If you look at a country where I was raised, that desire just amongst the people is not as elevated as it is to basically fundamental level
-
-1:05:14.320 --> 1:05:17.320
- to the essence of what it means to be America, right?
-
-1:05:17.320 --> 1:05:20.320
- And the same is true with China, there's different value systems.
-
-1:05:20.320 --> 1:05:30.320
- There is some censorship of internet content that China and Russia and many other countries undertake.
-
-1:05:30.320 --> 1:05:40.320
- Do you see that having effects on innovation, other aspects of some of the tech stuff, AI development we talked about
-
-1:05:40.320 --> 1:05:52.320
- and maybe from another angle, do you see that changing in different ways over the next 10 years, 20 years, 50 years as China continues to grow
-
-1:05:52.320 --> 1:05:55.320
- as it does now in its tech innovation?
-
-1:05:55.320 --> 1:06:08.320
- There's a common belief that full freedom of speech and expression is correlated with creativity, which is correlated with entrepreneurial success.
-
-1:06:08.320 --> 1:06:15.320
- I think empirically we have seen that is not true and China has been successful.
-
-1:06:15.320 --> 1:06:25.320
- That's not to say the fundamental values are not right or not the best, but it's just that perfect correlation isn't there.
-
-1:06:25.320 --> 1:06:36.320
- It's hard to read the tea leaves on opening up or not in any country and I've not been very good at that in my past predictions.
-
-1:06:36.320 --> 1:06:46.320
- But I do believe every country shares some fundamental value, a lot of fundamental values for the long term.
-
-1:06:46.320 --> 1:07:02.320
- So, you know, China is drafting its privacy policy for individual citizens and they don't look that different from the American or European ones.
-
-1:07:02.320 --> 1:07:13.320
- So, people do want to protect their privacy and have the opportunity to express and I think the fundamental values are there.
-
-1:07:13.320 --> 1:07:21.320
- The question is in the execution and timing, how soon or when will that start to open up?
-
-1:07:21.320 --> 1:07:31.320
- So, as long as each government knows, ultimately people want that kind of protection, there should be a plan to move towards that.
-
-1:07:31.320 --> 1:07:35.320
- As to when or how, again, I'm not an expert.
-
-1:07:35.320 --> 1:07:38.320
- On the point of privacy to me, it's really interesting.
-
-1:07:38.320 --> 1:07:44.320
- So, AI needs data to create a personalized awesome experience.
-
-1:07:44.320 --> 1:07:47.320
- I'm just speaking generally in terms of products.
-
-1:07:47.320 --> 1:07:53.320
- And then we have currently, depending on the age and depending on the demographics of who we're talking about,
-
-1:07:53.320 --> 1:07:58.320
- some people are more or less concerned about the amount of data they hand over.
-
-1:07:58.320 --> 1:08:03.320
- So, in your view, how do we get this balance right?
-
-1:08:03.320 --> 1:08:09.320
- That we provide an amazing experience to people that use products.
-
-1:08:09.320 --> 1:08:15.320
- You look at Facebook, you know, the more Facebook knows about you, yes, it's scary to say.
-
-1:08:15.320 --> 1:08:20.320
- The better it can probably, a better experience it can probably create.
-
-1:08:20.320 --> 1:08:24.320
- So, in your view, how do we get that balance right?
-
-1:08:24.320 --> 1:08:38.320
- Yes, I think a lot of people have a misunderstanding that it's okay and possible to just rip all the data out from a provider and give it back to you.
-
-1:08:38.320 --> 1:08:43.320
- So, you can deny them access to further data and still enjoy the services we have.
-
-1:08:43.320 --> 1:08:48.320
- If we take back all the data, all the services will give us nonsense.
-
-1:08:48.320 --> 1:08:57.320
- We'll no longer be able to use products that function well in terms of, you know, right ranking, right products, right user experience.
-
-1:08:57.320 --> 1:09:04.320
- So, yet I do understand we don't want to permit misuse of the data.
-
-1:09:04.320 --> 1:09:16.320
- From legal policy standpoint, I think there can be severe punishment for those who have egregious misuse of the data.
-
-1:09:16.320 --> 1:09:19.320
- That's, I think, a good first step.
-
-1:09:19.320 --> 1:09:27.320
- Actually, China on this aspect has very strong laws about people who sell or give data to other companies.
-
-1:09:27.320 --> 1:09:40.320
- And that over the past few years, since that law came into effect, pretty much eradicated the illegal distribution sharing of data.
-
-1:09:40.320 --> 1:09:52.320
- Additionally, I think giving, I think technology is often a very good way to solve technology misuse.
-
-1:09:52.320 --> 1:09:58.320
- So, can we come up with new technologies that will let us have our cake and eat it too?
-
-1:09:58.320 --> 1:10:07.320
- People are looking into homomorphic encryption, which is letting you keep the data, have it encrypted and train encrypted data.
-
-1:10:07.320 --> 1:10:13.320
- Of course, we haven't solved that one yet, but that kind of direction may be worth pursuing.
-
-1:10:13.320 --> 1:10:22.320
- Also federated learning, which would allow one hospital to train on its hospitals patient data fully because they have a license for that.
-
-1:10:22.320 --> 1:10:28.320
- And then hospitals would then share their models, not data, but models to create a supra AI.
-
-1:10:28.320 --> 1:10:30.320
- And that also maybe has some promise.
-
-1:10:30.320 --> 1:10:39.320
- So I would want to encourage us to be open minded and think of this as not just the policy binary yes no,
-
-1:10:39.320 --> 1:10:48.320
- but letting the technologists try to find solutions to let us have our cake and eat it too, or have most of our cake and eat most of it too.
-
-1:10:48.320 --> 1:10:55.320
- Finally, I think giving each end user a choice is important and having transparency is important.
-
-1:10:55.320 --> 1:11:04.320
- Also, I think that's universal, but the choice you give to the user should not be at a granular level that the user cannot understand.
-
-1:11:04.320 --> 1:11:12.320
- GDPR today causes all these pop ups of yes, no, will you give this site this right to use this part of your data?
-
-1:11:12.320 --> 1:11:20.320
- I don't think any user understands what they're saying yes or no to, and I suspect most are just saying yes because they don't understand it.
-
-1:11:20.320 --> 1:11:30.320
- So while GDPR in its current implementation has lived up to its promise of transparency and user choice,
-
-1:11:30.320 --> 1:11:39.320
- it implemented it in such a way that really didn't deliver the spirit of GDPR.
-
-1:11:39.320 --> 1:11:41.320
- It fit the letter, but not the spirit.
-
-1:11:41.320 --> 1:11:50.320
- So again, I think we need to think about is there a way to fit the spirit of GDPR by using some kind of technology?
-
-1:11:50.320 --> 1:11:52.320
- Can we have a slider?
-
-1:11:52.320 --> 1:12:01.320
- That's an AI trying to figure out how much you want to slide between perfect protection security of your personal data
-
-1:12:01.320 --> 1:12:07.320
- versus high degree of convenience with some risks of not having full privacy.
-
-1:12:07.320 --> 1:12:11.320
- Each user should have some preference and that gives you the user choice,
-
-1:12:11.320 --> 1:12:18.320
- but maybe we should turn the problem on its head and ask can there be an AI algorithm that can customize this
-
-1:12:18.320 --> 1:12:24.320
- because we can understand the slider, but we sure cannot understand every pop up question.
-
-1:12:24.320 --> 1:12:30.320
- And I think getting that right requires getting the balance between what we talked about earlier,
-
-1:12:30.320 --> 1:12:36.320
- which is heart and soul versus profit driven decisions and strategy.
-
-1:12:36.320 --> 1:12:45.320
- I think from my perspective, the best way to make a lot of money in the long term is to keep your heart and soul intact.
-
-1:12:45.320 --> 1:12:53.320
- I think getting that slider right in the short term may feel like you'll be sacrificing profit,
-
-1:12:53.320 --> 1:12:59.320
- but in the long term, you'll be getting user trust and providing a great experience.
-
-1:12:59.320 --> 1:13:01.320
- Do you share that kind of view in general?
-
-1:13:01.320 --> 1:13:11.320
- Yes, absolutely. I sure would hope there is a way we can do long term projects that really do the right thing.
-
-1:13:11.320 --> 1:13:16.320
- I think a lot of people who embrace GDPR, their hearts in the right place.
-
-1:13:16.320 --> 1:13:20.320
- I think they just need to figure out how to build a solution.
-
-1:13:20.320 --> 1:13:24.320
- I've heard utopians talk about solutions that get me excited,
-
-1:13:24.320 --> 1:13:29.320
- but not sure how in the current funding environment they can get started, right?
-
-1:13:29.320 --> 1:13:37.320
- People talk about, imagine this crowdsourced data collection that we all trust,
-
-1:13:37.320 --> 1:13:45.320
- and then we have these agents that we ask them to ask the trusted agent.
-
-1:13:45.320 --> 1:13:48.320
- That agent only, that platform.
-
-1:13:48.320 --> 1:14:02.320
- A trusted joint platform that we all believe is trustworthy that can give us all the close loop personal suggestions
-
-1:14:02.320 --> 1:14:07.320
- by the new social network, new search engine, new ecommerce engine
-
-1:14:07.320 --> 1:14:12.320
- that has access to even more of our data, but not directly but indirectly.
-
-1:14:12.320 --> 1:14:18.320
- I think that general concept of licensing to some trusted engine
-
-1:14:18.320 --> 1:14:22.320
- and finding a way to trust that engine seems like a great idea,
-
-1:14:22.320 --> 1:14:27.320
- but if you think how long it's going to take to implement and tweak and develop it right,
-
-1:14:27.320 --> 1:14:31.320
- as well as to collect all the trust and the data from the people,
-
-1:14:31.320 --> 1:14:34.320
- it's beyond the current cycle of venture capital.
-
-1:14:34.320 --> 1:14:37.320
- How do you do that is a big question.
-
-1:14:37.320 --> 1:14:44.320
- You've recently had a fight with cancer, stage 4 lymphoma,
-
-1:14:44.320 --> 1:14:54.320
- and in a sort of deep personal level, what did it feel like in the darker moments to face your own mortality?
-
-1:14:54.320 --> 1:14:57.320
- Well, I've been the workaholic my whole life,
-
-1:14:57.320 --> 1:15:04.320
- and I've basically worked 9.96, 9am to 9pm, 6 days a week, roughly.
-
-1:15:04.320 --> 1:15:10.320
- And I didn't really pay a lot of attention to my family, friends, and people who loved me,
-
-1:15:10.320 --> 1:15:14.320
- and my life revolved around optimizing for work.
-
-1:15:14.320 --> 1:15:25.320
- While my work was not routine, my optimization really made my life basically a very mechanical process.
-
-1:15:25.320 --> 1:15:36.320
- But I got a lot of highs out of it because of accomplishments that I thought were really important and dear and the highest priority to me.
-
-1:15:36.320 --> 1:15:41.320
- But when I faced mortality and the possible death in matter of months,
-
-1:15:41.320 --> 1:15:45.320
- I suddenly realized that this really meant nothing to me,
-
-1:15:45.320 --> 1:15:48.320
- that I didn't feel like working for another minute,
-
-1:15:48.320 --> 1:15:54.320
- that if I had 6 months left in my life, I would spend it all with my loved ones.
-
-1:15:54.320 --> 1:16:02.320
- And thanking them, giving them love back, and apologizing to them that I lived my life the wrong way.
-
-1:16:02.320 --> 1:16:11.320
- So that moment of reckoning caused me to really rethink that why we exist in this world
-
-1:16:11.320 --> 1:16:22.320
- is something that we might be too much shaped by the society to think that success and accomplishments is why we live.
-
-1:16:22.320 --> 1:16:29.320
- And while that can get you periodic successes and satisfaction,
-
-1:16:29.320 --> 1:16:35.320
- it's really in them facing death, you see what's truly important to you.
-
-1:16:35.320 --> 1:16:41.320
- So as a result of going through the challenges with cancer,
-
-1:16:41.320 --> 1:16:45.320
- I've resolved to live a more balanced lifestyle.
-
-1:16:45.320 --> 1:16:48.320
- I'm now in remission, knock on wood,
-
-1:16:48.320 --> 1:16:52.320
- and I'm spending more time with my family.
-
-1:16:52.320 --> 1:16:54.320
- My wife travels with me.
-
-1:16:54.320 --> 1:16:57.320
- When my kids need me, I spend more time with them.
-
-1:16:57.320 --> 1:17:02.320
- And before, I used to prioritize everything around work.
-
-1:17:02.320 --> 1:17:05.320
- When I had a little bit of time, I would dole it out to my family.
-
-1:17:05.320 --> 1:17:09.320
- Now, when my family needs something, really needs something,
-
-1:17:09.320 --> 1:17:12.320
- I drop everything at work and go to them.
-
-1:17:12.320 --> 1:17:15.320
- And then in the time remaining, I allocate to work.
-
-1:17:15.320 --> 1:17:18.320
- But one's family is very understanding.
-
-1:17:18.320 --> 1:17:22.320
- It's not like they will take 50 hours a week from me.
-
-1:17:22.320 --> 1:17:26.320
- So I'm actually able to still work pretty hard,
-
-1:17:26.320 --> 1:17:28.320
- maybe 10 hours less per week.
-
-1:17:28.320 --> 1:17:35.320
- So I realize the most important thing in my life is really love and the people I love.
-
-1:17:35.320 --> 1:17:38.320
- And I give that the highest priority.
-
-1:17:38.320 --> 1:17:40.320
- It isn't the only thing I do.
-
-1:17:40.320 --> 1:17:45.320
- But when that is needed, I put that at the top priority.
-
-1:17:45.320 --> 1:17:49.320
- And I feel much better and I feel much more balanced.
-
-1:17:49.320 --> 1:17:56.320
- And I think this also gives a hint as to a life of routine work,
-
-1:17:56.320 --> 1:17:58.320
- a life of pursuit of numbers.
-
-1:17:58.320 --> 1:18:03.320
- While my job was not routine, it wasn't pursuit of numbers.
-
-1:18:03.320 --> 1:18:05.320
- Pursuit of, can I make more money?
-
-1:18:05.320 --> 1:18:07.320
- Can I fund more great companies?
-
-1:18:07.320 --> 1:18:09.320
- Can I raise more money?
-
-1:18:09.320 --> 1:18:13.320
- Can I make sure our VC is ranked higher and higher every year?
-
-1:18:13.320 --> 1:18:20.320
- This competitive nature of driving for bigger numbers and better numbers
-
-1:18:20.320 --> 1:18:27.320
- became an endless pursuit of that's mechanical.
-
-1:18:27.320 --> 1:18:31.320
- And bigger numbers really didn't make me happier.
-
-1:18:31.320 --> 1:18:36.320
- And faced with death, I realized bigger numbers really meant nothing.
-
-1:18:36.320 --> 1:18:42.320
- And what was important is that people who have given their heart and their love to me
-
-1:18:42.320 --> 1:18:45.320
- deserve for me to do the same.
-
-1:18:45.320 --> 1:18:52.320
- So there's deep profound truth in that, that everyone should hear and internalize.
-
-1:18:52.320 --> 1:18:56.320
- And that's really powerful for you to say that.
-
-1:18:56.320 --> 1:19:02.320
- I have to ask sort of a difficult question here.
-
-1:19:02.320 --> 1:19:07.320
- So I've competed in sports my whole life, looking historically.
-
-1:19:07.320 --> 1:19:14.320
- I'd like to challenge some aspect of that a little bit on the point of hard work.
-
-1:19:14.320 --> 1:19:20.320
- That it feels that there are certain aspects that is the greatest,
-
-1:19:20.320 --> 1:19:26.320
- the most beautiful aspects of human nature, is the ability to become obsessed,
-
-1:19:26.320 --> 1:19:33.320
- of becoming extremely passionate to the point where, yes, flaws are revealed
-
-1:19:33.320 --> 1:19:36.320
- and just giving yourself fully to a task.
-
-1:19:36.320 --> 1:19:41.320
- That is, in another sense, you mentioned love being important,
-
-1:19:41.320 --> 1:19:47.320
- but in another sense, this kind of obsession, this pure exhibition of passion and hard work
-
-1:19:47.320 --> 1:19:50.320
- is truly what it means to be human.
-
-1:19:50.320 --> 1:19:53.320
- What lessons should we take that's deeper?
-
-1:19:53.320 --> 1:19:55.320
- Because you've accomplished incredible things.
-
-1:19:55.320 --> 1:19:57.320
- Like chasing numbers.
-
-1:19:57.320 --> 1:20:01.320
- But really, there's some incredible work there.
-
-1:20:01.320 --> 1:20:07.320
- So how do you think about that when you look back in your 20s, your 30s?
-
-1:20:07.320 --> 1:20:10.320
- What would you do differently?
-
-1:20:10.320 --> 1:20:16.320
- Would you really take back some of the incredible hard work?
-
-1:20:16.320 --> 1:20:17.320
- I would.
-
-1:20:17.320 --> 1:20:20.320
- But it's in percentages, right?
-
-1:20:20.320 --> 1:20:22.320
- We're both now computer scientists.
-
-1:20:22.320 --> 1:20:27.320
- So I think when one balances one's life, when one is younger,
-
-1:20:27.320 --> 1:20:33.320
- you might give a smaller percentage to family, but you would still give them high priority.
-
-1:20:33.320 --> 1:20:38.320
- And when you get older, you would give a larger percentage to them and still the high priority.
-
-1:20:38.320 --> 1:20:43.320
- And when you're near retirement, you give most of it to them and the highest priority.
-
-1:20:43.320 --> 1:20:50.320
- So I think the key point is not that we would work 20 hours less for the whole life
-
-1:20:50.320 --> 1:20:56.320
- and just spend it aimlessly with the family, but that when the family has a need,
-
-1:20:56.320 --> 1:21:02.320
- when your wife is having a baby, when your daughter has a birthday,
-
-1:21:02.320 --> 1:21:07.320
- or when they're depressed, or when they're celebrating something,
-
-1:21:07.320 --> 1:21:11.320
- or when they have a get together, or when we have family time,
-
-1:21:11.320 --> 1:21:18.320
- that is important for us to put down our phone and PC and be 100% with them.
-
-1:21:18.320 --> 1:21:26.320
- And that priority on the things that really matter isn't going to be so taxing
-
-1:21:26.320 --> 1:21:32.320
- that it would eliminate or even dramatically reduce our accomplishments.
-
-1:21:32.320 --> 1:21:36.320
- It might have some impact, but it might also have other impact
-
-1:21:36.320 --> 1:21:39.320
- because if you have a happier family, maybe you fight less.
-
-1:21:39.320 --> 1:21:45.320
- If you fight less, you don't spend time taking care of all the aftermath of a fight.
-
-1:21:45.320 --> 1:21:46.320
- That's right.
-
-1:21:46.320 --> 1:21:48.320
- And I'm sure that it would take more time.
-
-1:21:48.320 --> 1:21:53.320
- And if it did, I'd be willing to take that reduction.
-
-1:21:53.320 --> 1:21:56.320
- And it's not a dramatic number, but it's a number
-
-1:21:56.320 --> 1:22:00.320
- that I think would give me a greater degree of happiness
-
-1:22:00.320 --> 1:22:03.320
- and knowing that I've done the right thing
-
-1:22:03.320 --> 1:22:10.320
- and still have plenty of hours to get the success that I want to get.
-
-1:22:10.320 --> 1:22:14.320
- So given the many successful companies that you've launched
-
-1:22:14.320 --> 1:22:17.320
- and much success throughout your career,
-
-1:22:17.320 --> 1:22:25.320
- what advice would you give to young people today looking,
-
-1:22:25.320 --> 1:22:28.320
- or it doesn't have to be young, but people today looking to launch
-
-1:22:28.320 --> 1:22:35.320
- and to create the next $1 billion tech startup, or even AI based startup?
-
-1:22:35.320 --> 1:22:42.320
- I would suggest that people understand technology waves move quickly.
-
-1:22:42.320 --> 1:22:45.320
- What worked two years ago may not work today.
-
-1:22:45.320 --> 1:22:49.320
- And that is very much a case in point for AI.
-
-1:22:49.320 --> 1:22:53.320
- I think two years ago, or maybe three years ago,
-
-1:22:53.320 --> 1:22:57.320
- you certainly could say I have a couple of super smart PhDs
-
-1:22:57.320 --> 1:22:59.320
- and we're not sure what we're going to do,
-
-1:22:59.320 --> 1:23:04.320
- but here's how we're going to start and get funding for a very high valuation.
-
-1:23:04.320 --> 1:23:11.320
- Those days are over because AI is going from rocket science towards mainstream.
-
-1:23:11.320 --> 1:23:14.320
- Not yet commodity, but more mainstream.
-
-1:23:14.320 --> 1:23:20.320
- So first, the creation of any company to eventual capitalist
-
-1:23:20.320 --> 1:23:25.320
- has to be creation of business value and monetary value.
-
-1:23:25.320 --> 1:23:29.320
- And when you have a very scarce commodity,
-
-1:23:29.320 --> 1:23:34.320
- VCs may be willing to accept greater uncertainty.
-
-1:23:34.320 --> 1:23:40.320
- But now the number of people who have the equivalent of PhD three years ago
-
-1:23:40.320 --> 1:23:43.320
- because that can be learned more quickly.
-
-1:23:43.320 --> 1:23:45.320
- Platforms are emerging.
-
-1:23:45.320 --> 1:23:51.320
- The cost to become an AI engineer is much lower and there are many more AI engineers.
-
-1:23:51.320 --> 1:23:53.320
- So the market is different.
-
-1:23:53.320 --> 1:23:57.320
- So I would suggest someone who wants to build an AI company
-
-1:23:57.320 --> 1:24:01.320
- be thinking about the normal business questions.
-
-1:24:01.320 --> 1:24:05.320
- What customer cases are you trying to address?
-
-1:24:05.320 --> 1:24:08.320
- What kind of pain are you trying to address?
-
-1:24:08.320 --> 1:24:10.320
- How does that translate to value?
-
-1:24:10.320 --> 1:24:16.320
- How will you extract value and get paid through what channel?
-
-1:24:16.320 --> 1:24:19.320
- And how much business value will get created?
-
-1:24:19.320 --> 1:24:26.320
- That today needs to be thought about much earlier up front than it did three years ago.
-
-1:24:26.320 --> 1:24:30.320
- The scarcity question of AI talent has changed.
-
-1:24:30.320 --> 1:24:32.320
- The number of AI talent has changed.
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-1:24:32.320 --> 1:24:41.320
- So now you need not just AI but also understanding of business customer and the marketplace.
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-1:24:41.320 --> 1:24:49.320
- So I also think you should have a more reasonable evaluation expectation
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- and growth expectation.
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- There's going to be more competition.
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- But the good news though is that AI technologies are now more available in open source.
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- TensorFlow, PyTorch and such tools are much easier to use.
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- So you should be able to experiment and get results iteratively faster than before.
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-1:25:13.320 --> 1:25:18.320
- So take more of a business mindset to this.
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- Think less of this as a laboratory taken into a company because we've gone beyond that stage.
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- The only exception is if you truly have a breakthrough in some technology that really no one has,
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- then the old way still works.
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- But I think that's harder and harder now.
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- So I know you believe as many do that we're far from creating an artificial general intelligence system.
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- But say once we do and you get to ask her one question, what would that question be?
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- What is it that differentiates you and me?
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- Beautifully put, Kaifu, thank you so much for your time today.
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- Thank you.
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