Migrating vector embeddings in production without downtime
In the fast-moving world of AI, models evolve rapidly. What was state-of-the-art six months ago is now being surpassed by newer models. For a RAG syst…
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TiDB for AI Memory: Vector Search, HTAP, and Horizontal Scaling in One Database
Most AI applications today run on a fragmented stack. Pinecone stores your vectors. PostgreSQL holds your user data. Redis caches frequently accessed …
Embeddings Explained: The Secret Language AI Uses to Understand the World
If you've ever wondered how ChatGPT "knows" that king and queen are related, or how Spotify recommends songs you actually like, the answer is almost a…
"Backend Engineering for an AI Platform: The Infrastructure Decisions Nobody Talks About"
Video Explanation: https://youtu.be/1xL_Dtp7Ksg ) By Raghav Bansal | Backend Engineer & Memory Infrastructure Lead, Team FireFury EduRag Project |…
The “The Architecture Handbook for Milvus Vector Database” Book Review
A feedback and my thoughts on the “The Architecture Handbook for Milvus Vector Database” book. The image from the book cover produced by Packt Publica…