『Ep162: Improving Search for Generative AI Developers with DataStax and AWS』のカバーアート

Ep162: Improving Search for Generative AI Developers with DataStax and AWS

Ep162: Improving Search for Generative AI Developers with DataStax and AWS

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Learn how DataStax transformed customer feedback into a hybrid search solution that powers Fortune 500 companies through their partnership with AWS.

Topics Include:

  • AWS and DataStax discuss how quality data powers AI workloads and applications.
  • DataStax built on Apache Cassandra powers Starbucks, Netflix, and Uber at scale.
  • Their TIL app collects outside-in customer feedback to drive product development decisions.
  • Hybrid search and BM25 kept trending in customer requests for several months.
  • Customers wanted to go beyond pure vector search, not specifically BM25 itself.
  • Research showed hybrid search improves accuracy up to 40% over single methods.
  • ML-based re-rankers substantially outperform score-based ones despite added latency and cost.
  • DataStax repositioned their product as a knowledge layer above the data layer.
  • Developer-first design prioritizes simple interfaces and eliminates manual data modeling headaches.
  • Hybrid search API uses simple dollar-sign parameters and integrates with Langflow automatically.
  • AWS PrivateLink ensures security while Graviton processors boost efficiency and tenant density.
  • Graviton reduced total platform operating costs by 20-30% with higher throughput.


Participants:

  • Alejandro Cantarero – Field CTO, AI, DataStax
  • Ruskin Dantra - Senior ISV Solution Architect, AWS, Amazon Web Services


See how Amazon Web Services gives you the freedom to migrate, innovate, and scale your software company at https://aws.amazon.com/isv/

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