4 articles tagged with “rag”.
RAG is the technique that lets a language model answer using your own documents instead of only what it memorized in training. Here is how it works and why almost every serious AI app uses it.
Embeddings are how AI turns words into numbers that capture meaning — the quiet engine behind semantic search, recommendations, and RAG. Here is the concept without the math.
Perplexity answers questions with concise, cited summaries drawn from the live web — positioning itself between a search engine and a chatbot. Here is what it does and where it fits.
LangChain is the open-source framework that popularized chaining LLM calls, retrieval, and tools into full applications. Here is what it offers, and the trade-offs to weigh before building on it.