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sota RAG in 2024

209,306 görüntüleme • 2 yıl önce •via X (Twitter)

10 Yorum

Eugene Yan profil fotoğrafı
Eugene Yan2 yıl önce

bm25 & np.array is all you need

saint profil fotoğrafı
saint2 yıl önce

>increase the value of k real

darren profil fotoğrafı
darren2 yıl önce

hacked together database? you mean np.array

Grant♟️ profil fotoğrafı
Grant♟️2 yıl önce

based

vish profil fotoğrafı
vish2 yıl önce

those in arena, they know instead of similarity searching the query with chunks, do a similarity search of fictional answer to chunks

Rani profil fotoğrafı
Rani2 yıl önce

ty for the laugh (lots of truths in this) I'm still learning, but I think it starts from the design of your vector DB though. Rather than stuffing everything in one db and using scuffed queries, trying to make 2 and 2 equal 5... It's asking more fundamental questions: -What are you querying? -What do you want to get? -How does this VDB fit into the larger application? -How can you re-organize, reformat, re-index your data to minimize the complexity of the retrieval task: aka, making distinct chunks more dissimilar to each other? -How can you optimize your queries? -Do you need to split the db into several smaller db with more targeted data? -Do you need a re-ranking system? Get a first batch of data, re-rank using a different/more precise query. Probably more efficient than having a single query trying to find a needle in a haystack, and flipping a coin each time. Of course, keeping in mind time, number of operations, handling failure cases, etc...

Michael P. Frank 💻🔜♻️ profil fotoğrafı
Michael P. Frank 💻🔜♻️2 yıl önce

That’s pretty hilarious 😂 My Telegram bots work like this, but they’re just a hobby project, not a mission-critical enterprise application, so it’s not like it matters lol

Hamel Husain profil fotoğrafı
Hamel Husain2 yıl önce

This is amazing

json profil fotoğrafı
json2 yıl önce

Bloody banger man

Grant♟️ profil fotoğrafı
Grant♟️2 yıl önce

Lolll pretty much

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