

#187 The Power of Vector Databases and Semantic Search with Elan Dekel, VP of Product at Pinecone
14 snips Mar 11, 2024
Elan Dekel, VP of Product at Pinecone, brings extensive experience from Google to discuss the evolution of vector databases. He emphasizes their role in combating AI hallucinations and improving accuracy in applications like chatbots. The conversation dives into the advantages of semantic search over traditional methods, successful implementations in various sectors, and innovative uses of vector databases. Elan also touches on infrastructure needs for generative AI, emerging job roles within the field, and the democratization of AI technology for non-technical users.
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LLM Hallucinations
- Large language models (LLMs) hallucinate when asked questions outside their training data.
- They confidently generate realistic-sounding answers that are often made up.
Vector Databases
- Vector databases handle vector embeddings, which represent the semantic meaning of data like text or images.
- Traditional SQL databases aren't designed for this type of search.
Semantic Search
- Semantic search understands the meaning of search queries, handling misspellings and synonyms.
- It offers Google-like search quality without extensive manual effort.