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"you actually optimize your rag"
Building Production-Ready RAG Applications: Jerry Liu
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AI Engineer: model once you've defined your evalve benchmark now you want to think about how do you actually optimize your rag…
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you actually optimize your rag
Building Production-Ready RAG Applications: Jerry Liu
8:17
you actually optimize your rag systems so I sent a teaser on this slide
Building Production-Ready RAG Applications: Jerry Liu
8:19
you actually retrieve from a vector database and how do you synthesize that with an
Building Production-Ready RAG Applications: Jerry Liu
2:19
you synthesize that with an L1 so that's basically the key stack
Building Production-Ready RAG Applications: Jerry Liu
2:21
these challenges with naive rag
Building Production-Ready RAG Applications: Jerry Liu
2:56
you use llms for for
Building Production-Ready RAG Applications: Jerry Liu
14:35
you incorporate agents towards
Building Production-Ready RAG Applications: Jerry Liu
9:38
you actually get language models to
Building Production-Ready RAG Applications: Jerry Liu
0:49
similar elements from your vector database
Building Production-Ready RAG Applications: Jerry Liu
4:39
you use llms for for reasoning as opposed to just synthesis
Building Production-Ready RAG Applications: Jerry Liu
14:37
you actually properly evaluate
Building Production-Ready RAG Applications: Jerry Liu
8:07
you actually fine-tune
Building Production-Ready RAG Applications: Jerry Liu
9:46
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you actually optimize your ragyou actually optimize your rag systems so I sent a teaser on this slideyou actually retrieve from a vector database and how do you synthesize that with anyou synthesize that with an L1 so that's basically the key stackthese challenges with naive ragyou use llms for foryou incorporate agents towardsyou actually get language models tosimilar elements from your vector databaseyou use llms for for reasoning as opposed to just synthesis
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"you actually optimize your rag"
Building Production-Ready RAG Applications: Jerry Liu
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