Reaching 1B Context Length With RAG

Zyphra: https://www.zyphra.com/post/reaching-1b-context-length-with-rag

retrieval system enables LLMs to process up to 1 billion tokens efficiently on a standard CPU using a sparse graph-based approach. Outperforms RAG methods with dense embeddings or long-context transformers.

I’m impressed with the work Zyphra has been doing in the SSM space (most recently Zamba2-7B) so I’m eager to see more.

chungus raw prompt go in yum yum machine, make yummy portion prompt for llm come out.

Zyphra's ultra fast more general RAG search is yum yum machine

aichannel

prev founded rocketr.net, swish.id now exploring aiXcrypto identity ai. expired sprint car driver & energy data engineer. idol worship on shoni_eth.X

product @seedclub. i host S-TIER @ X Spaces & i interview crypto builders @ web3galaxybrain.com.

i'll post them in /six for now on we like to keep /ai a little more scientific

ofc post where you please. but do check out /aichannel where less scientific takes are allowed 

oh okay i tried /llm but this might be cool. can you add me as a member

yes you can join via the link on the channel description. i follow you so you should get in straight away. lmk if not!