Tagged
#embeddings
5 articles
Embeddings vs generation: two things models do
"Embeddings and generation are different jobs. Knowing which one your problem needs is the fastest way to a system that actually works."
Retrieval-augmented generation (RAG), from first principles
RAG is often explained as a stack of tools. Strip that away and it is one simple idea: let the model read the right material before it answers. Here is how it really works.
Choosing an embedding model for your project
Picking an embedding model is less about leaderboards than fit. Here is what actually decides whether retrieval works for your data and your budget.
Vector databases without the hype: what they do and when you need one
Vector databases became a buzzword overnight. Here is what they actually do, the problem they solve, and the honest signs you do or do not need one.
Build a simple RAG pipeline: a conceptual walkthrough
Retrieval-augmented generation, built up one stage at a time. No magic, no specific stack — just the shape of the pipeline and the decisions that matter.