Collective Intelligence: What AI Teams get wrong about Vector Databases
Welcome to Collective Intelligence!
Collective Intelligence is a global learning space that gives our community direct access to education at the frontier of AI. From mastering cutting-edge skills to exploring the ideas shaping tomorrow, you’ll engage with leading educators, innovators, and builders at the forefront of what’s next.
What You'll Learn
How vector databases differ — the tradeoffs between scale, functionality, and performance
Hidden features you’ll wish you had — what separates toy projects from production-grade applications
Beyond similarity search — why vector DBs are more than “giant similarity machines” and which features truly matter
From vector to hybrid and full text — how decades of information retrieval research can supercharge your AI solutions
Why This Topic Matters
In AI, context is king — and context doesn’t exist without retrieval. The type of retrieval you choose, along with the features and functionality of your vector database, can make or break your application. In this talk, we’ll explore how to evaluate different vector DBs, what to look for (and what to avoid), and how to build systems that are robust, scalable, and future-proof.
Learn from Doug Turnbull
Doug Turnbull is a leading consultant in search technology and relevance engineering, and a Maven instructor on AI-powered search. He has built hybrid systems that combine lexical and vector retrieval and developed LLM-driven quality programs for e-commerce. Previously, he spearheaded machine-learning-powered search at Reddit and led relevance initiatives at Shopify.
With hands-on experience across Pinecone, Weaviate, Elasticsearch, OpenSearch, Vespa, and Turbopuffer, Doug brings practical, hard-earned insights on when—and why—to reach for each tool.
Event Details
Thursday, September 4
10:00 AM – 11:00 AM PT
Live on Roam
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