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In depth explanation + examples of why sometimes you don't need rag (especially with gemini 2.0)

34,228 просмотров • 1 год назад •via X (Twitter)

Комментарии: 11

Фото профиля Sully
Sully1 год назад

video up on youtube too

Фото профиля Aly Khairy
Aly Khairy1 год назад

It's simpler, but still costs a lot more. Maybe break down 1 query into several prompts like "is management optimistic about iphone sales next Q" and feed that to a "risks"prmpr and an "mda" prmpt, retrieve more chunks then feed those chunks to Gemini to get a more rounded answer

Фото профиля Sully
Sully1 год назад

Would you rather pay more and have a accurate answer ? I think the cost equation starts to matter less and less

Фото профиля Sohail Hosseini
Sohail Hosseini1 год назад

Thanks for sharing!

Фото профиля Raduan Al-Shedivat
Raduan Al-Shedivat1 год назад

amazing explainer video, Sully. one thing that you've missed, which is HUGE: **context caching**[1]. basically, now you can send this whole 50k transcript, cache it for subsequent calls, and never ever bother breaking this down for RAG, even for long conversations, because this whole thing will get cached. I am switching most of my LLM use to Gemini after this. [1]:

Фото профиля Sully
Sully1 год назад

Agreed I didn’t even mentioned which makes it way cheaper I will say googles caching needs work

Фото профиля D33PS33K
D33PS33K1 год назад

KAG vs RAG

Фото профиля David
David1 год назад

great video, i just don't understand how google was able to achieve this without crazy hallucinations

Фото профиля Derek Cheung
Derek Cheung1 год назад

Thanks Sully! Great work

Фото профиля Nate Pratt
Nate Pratt1 год назад

im extracting information from bank statments and need it REALLY accurate what would you recommend?

Фото профиля Sully
Sully1 год назад

Gemini

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