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LLMs don’t know your PDF.
They don’t know your company wiki either. Or your research papers.

What they can do with RAG is look through your documents in the background and answer using what they find.

But how does that actually work? Here’s the basic idea behind RAG:
:blobcoffee: Chunking: The document is split into small, overlapping parts so the LLM can handle them. This keeps structure and context.
:blobcoffee: Embeddings & Search: Each part is turned into a vector (a numerical representation of meaning). Your question is also turned into a vector, and the system compares them to find the best matches.
:blobcoffee: Retriever + LLM: The top matches are sent to the LLM, which uses them to generate an answer based on that context.

#llm #largelanguagemodel #ai #ki #rag #tech #technology #vector #datascience #vectorsearch #vector #machinelearning



Josh Johnson: Trump VS MAGA? The Epstein Crashout Explained littlegreenfootballs.com/artic…


Democrats' 2026 Rallying Cry Is Staring Them in the Face (Lauren Egan/The Bulwark)

thebulwark.com/p/democrats-202…
memeorandum.com/250720/p65#a25…





A little late on this one. There is already a whole subreddit of people with AI “partners”
RE: bsky.app/profile/did:plc:iiofy…

in reply to Karen Attiah

This is already a thing and they are already “abusing” virtual women futurism.com/chatbot-abuse

Men Are Creating AI Girlfriend...




Queensland road toll climbs to 158 after 10 people killed in horror weekend byteseu.com/1212808/ #Australia #Brisbane




😀 I like when people boost posts into my time line because I find more people to follow who have unique and interesting ideas 💡

So please, Boost The Toots

Parcel the Posts 📩

#BoostTheToots
#Fediverse #Mastodon



Voix pour une confédération israélo-palestinienne





I share this @theonion.com headline whenever I talk with people about the importance of headlines. theonion.com/july-21-1969...

July 21, 1969