DataFramed #255 Not Only Vector Databases: Putting Databases at the Heart of AI, with Andi Gutmans, VP and GM of Databases at Google
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Oct 24, 2024 
Andi Gutmans, VP and GM of Databases at Google, brings over 20 years of expertise in open-source and database technologies. He discusses the intertwining of generative AI and data, emphasizing how quality databases are crucial for AI success. Andi explores the evolution of cloud database solutions, innovative technologies like vector and graph databases, and their transformative potential for businesses. He also highlights practical AI applications in databases and the importance of strategic integration to enhance data-driven decision-making across organizations.
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Grounding GenAI
- Generative AI models, while powerful, can hallucinate.
- Grounding them with operational data ensures accuracy and relevance in enterprise applications.
Database Selection for GenAI
- Leverage existing databases for GenAI if they have basic capabilities like vector support.
- Prioritize integrating current data over adopting new database systems solely for GenAI.
Vector Embeddings and Semantic Search
- Vector embeddings enable semantic search by representing data numerically, capturing similarities like "King" and "Queen".
- This allows for similarity searches and enhances retrieval augmented generation (RAG) in GenAI.