Tag
embeddings
Embeddings turn text, speech, or code into vectors that systems can compare for semantic search, retrieval-augmented generation, similarity matching, and vector databases. They also shape tasks like token initialization, ASR evaluation, and context retrieval in tools such as Redis Vector Search.
3 articles
AI Agent/May 5
How to Build a RAG Pipeline in 5 Steps
Build a retrieval-augmented generation pipeline that grounds AI answers in your own data.
Tools & Apps/Apr 14
Redis Vector Search: Quick Start Guide Explained
Redis can store vectors, metadata, and search them with semantic queries. This guide shows the setup, indexing, and KNN search path.
Blockchain & Web3/Apr 3
A Better Way to Seed New LM Tokens
GTI grounds new vocabulary tokens before fine-tuning, aiming to preserve distinctions that mean initialization tends to collapse.