Retrieval
topic on 3 shows · 6 statements across 6 episodes
Latent Space 
No Priors 
the MAD Podcast
6 statements about Retrieval, every show
Shah: Pure retrieval AI memory fails on non-literal questions
“Traditionally you have this retrieval thing that happens. So you get a question, you retrieve something, and an answer is generated based on that. But we think that it will not work for most non-literal questions, like find the best monitor for me. If I've nev…”
Massive context windows will not eliminate the need for RAG retrieval
“Like if you do have billion token context window model, you throw it all in there. It's still gonna be more expensive. The reason why retrieval is so important for us is because even if there is a model that's going to have these larger context windows, and ce…”
Kiela: Retrieval is the only way AI agents can handle proprietary data
“Really focused on retrieval because that's really the only way you get these agents to work on your data and your problems.”
Soldani: Local models beat closed models in retrieval applications
“There are some applications where local models just blow closed models out of the water. So, like, retrieval is a very clear example.”
Swyx: Enterprise ChatGPT implementations are just retrieval, not generative AI
“That is what people think generative AI is, but it's not super generative, really, it's just retrieval.”
Guo: Large context windows expand RAG trade-offs rather than killing retrieval
“I'm more of the belief that it just opens up the set of trade-offs you can make between retrieval, more sophisticated retrieval and model reasoning by having a larger context window versus saying, like, we don't need any ability to work with a specific data se…”