An embedding is an idea in machine studying that refers to a selected illustration of textual content, photos, audio, or different data. Embeddings are designed to make knowledge consumable by ML fashions.
Nonetheless, storing embeddings presents a problem to conventional databases. Vector databases are designed to unravel this downside.
Pinecone has developed one of the outstanding vector databases that’s extensively used for ML and AI functions.
Marek Galovic is a software program engineer at Pinecone and works on the core database workforce. He joins the podcast right this moment to speak about how vector embeddings are created, engineering a vector database, unsolved challenges within the area, and extra.
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