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Are Vector DBs the Future Data Platform for AI? with Ed Anuff - #664
Manage episode 392138979 series 2355587
Контент предоставлен TWIML and Sam Charrington. Весь контент подкастов, включая эпизоды, графику и описания подкастов, загружается и предоставляется непосредственно компанией TWIML and Sam Charrington или ее партнером по платформе подкастов. Если вы считаете, что кто-то использует вашу работу, защищенную авторским правом, без вашего разрешения, вы можете выполнить процедуру, описанную здесь https://ru.player.fm/legal.
Today we’re joined by Ed Anuff, chief product officer at DataStax. In our conversation, we discuss Ed’s insights on RAG, vector databases, embedding models, and more. We dig into the underpinnings of modern vector databases (like HNSW and DiskANN) that allow them to efficiently handle massive and unstructured data sets, and discuss how they help users serve up relevant results for RAG, AI assistants, and other use cases. We also discuss embedding models and their role in vector comparisons and database retrieval as well as the potential for GPU usage to enhance vector database performance.
The complete show notes for this episode can be found at twimlai.com/go/664.
702 эпизодов
Are Vector DBs the Future Data Platform for AI? with Ed Anuff - #664
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Manage episode 392138979 series 2355587
Контент предоставлен TWIML and Sam Charrington. Весь контент подкастов, включая эпизоды, графику и описания подкастов, загружается и предоставляется непосредственно компанией TWIML and Sam Charrington или ее партнером по платформе подкастов. Если вы считаете, что кто-то использует вашу работу, защищенную авторским правом, без вашего разрешения, вы можете выполнить процедуру, описанную здесь https://ru.player.fm/legal.
Today we’re joined by Ed Anuff, chief product officer at DataStax. In our conversation, we discuss Ed’s insights on RAG, vector databases, embedding models, and more. We dig into the underpinnings of modern vector databases (like HNSW and DiskANN) that allow them to efficiently handle massive and unstructured data sets, and discuss how they help users serve up relevant results for RAG, AI assistants, and other use cases. We also discuss embedding models and their role in vector comparisons and database retrieval as well as the potential for GPU usage to enhance vector database performance.
The complete show notes for this episode can be found at twimlai.com/go/664.
702 эпизодов
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Похожие на The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Hungry for Technology Talk? Get All You Can Eat at the Android Buffet
…
continue reading
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…
continue reading
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…
continue reading
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…
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…
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…
continue reading
Why do only 10% of companies succeed with AI? In this series by MIT SMR and BCG, we talk to the leaders who've achieved big wins with AI in their companies and learn how they did it. Hear what gets experts from companies like NASA, Shopify, and others excited to do their jobs every day and what they consider the keys to their success.
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continue reading
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