A technical explainer on knowledge cutoffs and parametric memory states that Allen-Zhu and Li (2024) measured a language model's knowledge capacity at about 2 bits per parameter when each fact appears…
A local embedding model, a second smaller model that converts text into vectors, is essential for retrieval-augmented generation (RAG) setups, as it retrieves relevant document chunks for the LLM. Acc…
An engineer argues that AI agents do not automatically need RAG pipelines to use organizational knowledge, advocating instead for a readable, searchable knowledge base with bounded tools. The piece, p…
A developer distinguishes between RAG (Retrieval-Augmented Generation) and agent memory, explaining that RAG is read-only retrieval from static corpora while agent memory involves read-write learning …