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Search: it's vectors all the way down

Hosted by Doug Turnbull (Maven)

Wed, Aug 12, 2026

4:00 PM UTC (1 hour)

Virtual (Zoom)

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Build your own vector database
Doug Turnbull
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What you'll learn

The vector space model: from BM25 to metadata

How we've long thought of Information Retrieval as a "vector search" problem

The rise of dense vector databases

With the rise of RAG, how 2020s brought about an influx of dense vector databases and approaches

Why sparse vectors solutions are cool again

Why techniques like late interaction push the search world back towards sparse vector techniques

Why this topic matters

Want to be good at retrieval? Know your history. Search has had epochs. Approaches that come on the scene and perhaps evolve, but never die. The "vector space model" is as old as search. We're exiting one phase of Information Retrieval: a dense vector revolution brought on by the ubiquity of embeddings + vector databases. We're entering a new phase of sparse retrieval. And its all 'vectors'

You'll learn from

Doug Turnbull (Maven)

Led teams at Shopify, Reddit, Wikipedia

In 2012, Doug got bit by the search bug and he's still trying to keep up. From full-text search, to Learning to Rank models, to search agents that generate their own code, he knows the endless landscape first hand. Yet Doug wants to deeply understand the what / how / why, and help teams use these technologies practically, distinguishing hype from reality.

He’s led search at Reddit, Shopify, and Wikipedia, authored Relevant Search and AI Powered Search, and advised 100+ organizations over the years - all in pursuit of the same question: how does search actually work?

Previously at

Shopify.com
Reddit
LexisNexis
OpenSource Connections
See all products from Doug

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