AI & ML
2 articles
9 min read
What Is RAG? Retrieval-Augmented Generation Explained
Retrieval-Augmented Generation (RAG) grounds an LLM's answers in information it pulls from an external knowledge source at query time, instead of relying on frozen training data. Here's what RAG is, how the indexing and retrieval pipelines actually work, and when to choose it over fine-tuning or long-context.
AI & ML
7 min read
How Speculative Decoding Speeds Up LLM Inference
Speculative decoding makes LLM inference 2-3x faster by letting a small draft model guess ahead and a large model verify the guesses in one parallel pass. A rejection-sampling step keeps the output mathematically identical to the slow path. Here's how it works, why it's lossless, and where it stops helping.
AI & ML