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] | p | Thanks to the DataTalks.Club for organizing this podcast. | [
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"tags/retrieval-augmented-generation"
] | 10,600 |
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[
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] | p | If you’re interested in a similar discussion, watch for the recording from the following event, organized by DeepRec.ai. | [
"tags",
"tags/retrieval-augmented-generation"
] | 10,602 |
[
"Retrieval Augmented Generation - Qdrant"
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"tags",
"tags/retrieval-augmented-generation"
] | 10,603 |
[
"Retrieval Augmented Generation - Qdrant",
"Further reading"
] | /tags/retrieval-augmented-generation/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > ul:nth-of-type(4) > li:nth-of-type(1) | [
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] | h2 | Navigating challenges and innovations in search technologies | [
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[
"Search - Qdrant",
"Navigating challenges and innovations in search technologies"
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[
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"Navigating challenges and innovations in search technologies"
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[
"Search - Qdrant",
"Navigating challenges and innovations in search technologies"
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"tags/search"
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[
"Search - Qdrant"
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[
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"More about RAG"
] | /tags/search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(4) | [
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[
"Search - Qdrant",
"More about RAG"
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"tags",
"tags/search"
] | 10,620 |
[
"Search - Qdrant",
"More about RAG"
] | /tags/search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > ul:nth-of-type(1) > li:nth-of-type(1) | [
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"tags",
"tags/search"
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[
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"More about RAG"
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] | li | Model evaluation(LLM) - Understanding the model at the domain-level for the given use case, supporting required context length and terminology/concept understanding. | [
"tags",
"tags/search"
] | 10,635 |
[
"Search - Qdrant",
"Podcast Discussion Recap"
] | /tags/search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > ul:nth-of-type(3) > li:nth-of-type(2) | [
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"tags",
"tags/search"
] | 10,636 |
[
"Search - Qdrant",
"Podcast Discussion Recap"
] | /tags/search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > ul:nth-of-type(3) > li:nth-of-type(3) | [
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"tags",
"tags/search"
] | 10,637 |
[
"Search - Qdrant",
"Podcast Discussion Recap"
] | /tags/search/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > ul:nth-of-type(3) > li:nth-of-type(4) | [
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"tags",
"tags/search"
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[
"Search - Qdrant"
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"tags",
"tags/search"
] | 10,644 |
[
"Search - Qdrant"
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] | p | Discussing core differences between search engines and databases, Andrey underlined the importance of application needs and scalability in database selection for vector search tasks. | [
"blog",
"blog/open-source-vector-search-engine-vector-database"
] | 10,651 |
[
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov - Qdrant",
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov"
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"blog",
"blog/open-source-vector-search-engine-vector-database"
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[
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[
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov - Qdrant",
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov"
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] | p | You can watch this episode on YouTube. | [
"blog",
"blog/open-source-vector-search-engine-vector-database"
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[
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov - Qdrant",
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov"
] | /blog/open-source-vector-search-engine-vector-database/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(4) | [
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] | p | This episode is part of the ML⇄DB Seminar Series (Machine Learning for Databases + Databases for Machine Learning) of the Carnegie Mellon University Database Research Group. | [
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"blog/open-source-vector-search-engine-vector-database"
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[
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov - Qdrant"
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[
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"blog/open-source-vector-search-engine-vector-database"
] | 10,670 |
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[
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"More Quotes from Andrey:"
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"blog/open-source-vector-search-engine-vector-database"
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[
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov - Qdrant",
"More Quotes from Andrey:"
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"blog",
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[
"Open Source Vector Search Engine and Vector Database - Andrey Vasnetsov - Qdrant",
"More Quotes from Andrey:"
] | /blog/open-source-vector-search-engine-vector-database/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(10) | [
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"More Quotes from Andrey:"
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[
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"tags/vector-search-engine"
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[
"Vector Search Engine - Qdrant"
] | /tags/vector-search-engine/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(2) | [
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"tags/vector-search-engine"
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[
"Vector Search Engine - Qdrant"
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] | p | He works on Open Source projects related to Vector Similarity Search and Similarity Learning. | [
"tags",
"tags/vector-search-engine"
] | 10,686 |
[
"Vector Search Engine - Qdrant"
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[
"Vector Search Engine - Qdrant"
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"tags",
"tags/vector-search-engine"
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[
"Vector Search Engine - Qdrant"
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"tags",
"tags/vector-search-engine"
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[
"Vector Search Engine - Qdrant"
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] | p | Dive into the intricacies of vector databases with Andrey as he unpacks Qdrant’s approach to combining filtering and vector search, revealing how in-place filtering during graph traversal optimizes precision without sacrificing search exactness, even when scaling to billions of vectors. | [
"tags",
"tags/vector-search-engine"
] | 10,691 |
[
"Vector Search Engine - Qdrant",
"Top Takeaways:"
] | /tags/vector-search-engine/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(6) | [
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[
"Vector Search Engine - Qdrant",
"Top Takeaways:"
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] | li | 🚅 Speed and Precision Tactics: Uncover the techniques for controlling search precision and speed by tweaking the beam size in HNSW indices. | [
"tags",
"tags/vector-search-engine"
] | 10,699 |
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