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In this episode, Andy, Beth, Brian, Karl, and Jyunmi talk about vector embeddings and semantic search, unraveling their complexities and impacts on AI applications. They explore the mathematical foundations of vector embeddings, their role in enhancing semantic search capabilities, and their broader implications for AI technology.

Key Points Discussed:

Vector Embeddings Explained: Karl begins with a primer on vector embeddings, illustrating how words, concepts, and items

Vector Embeddings & Semantic Search

The Daily AI Show