
#3 Duncan Blythe on AI Inside Your Database, Real-Time AI, Declarative ML/AI
How AI Is Built
Challenges and Considerations in Computing Embeddings for Data Storage
The chapter delves into the challenges and considerations of calculating embeddings in data storage, emphasizing timing and synchronization for optimal performance. It highlights the benefits of computing similarities between vectors using LanceDB and discusses the integration of AI with databases for applications like search engines. Additionally, it explores the flexibility in choosing computational aspects of AI and the importance of operational requirements in AI development.
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