Fast and secure AI context with open source hybrid vector search (AIM207)

Here is a summary of the key takeaways from the video transcription, presented in a markdown format with sections for better readability:

Challenges in AI Adoption

  • Only 17% of companies are in production with AI use cases
  • Top concerns are data security, privacy, and data availability/quality
  • AI models can "hallucinate" and provide incorrect information, which is a huge problem for companies

Retrieval Augmented Generation (RAG) and Vector Search

  • RAG is a common solution to provide context to AI models
  • Vector search allows storing data in a multi-dimensional space and retrieving relevant documents
  • However, vector search is a proximity-based search and may not provide accurate results for specific requirements

Hybrid Search

  • Hybrid search combines vector search and traditional search techniques
  • Techniques include pre-filtering, post-filtering, and re-ranking
  • Each approach has its own pros and cons in terms of performance and semantic accuracy

Implementing Hybrid Search

  • Hybrid search is not limited to dedicated vector databases, but can be implemented in traditional databases like PostgreSQL
  • PostgreSQL has the ability to store embeddings and perform hybrid searches
  • Alloy DB and OpenSearch are other tools that provide hybrid search capabilities

Data Platform Considerations

  • AI requires data from various sources, so a comprehensive data platform is needed
  • Hevo provides a data platform that covers streaming, storage, and serving layers
  • The platform offers integration with various databases, search engines, and AI capabilities

Conclusion

  • For companies looking to move AI use cases into production, a secure and fast AI context is crucial
  • Hybrid search, combined with a comprehensive data platform, can address the challenges of data security, privacy, and availability
  • Hevo's data platform offers a solution to free data from various sources and make it ready for AI applications.

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