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How Hambrecht Uses Machine Learning to Up its Venture Hit Rate 3X

Writer: Thomas Thurston
Thomas Thurston
Sep 30, 2019
1 min read

Updated: Jun 20, 2023

Venture capital is a “hit business.” The relatively few hits pay for the flops. And it’s the tantalizing possibility of a mega-hit that animates the industry, that keeps investors dreaming, prospecting and writing checks. For venture capitalists, it’s the hits and the mega-hits that make the high flop rate tolerable.

But is frequent venture failure inescapable? Could a probabilistic approach based on big data, machine learning and advanced computing do better?


Thomas Thurston, a data scientist and CTO of venture firm W.R. Hambrecht, is someone who “look(s) at things the way they are, and asks(s) why?”* Speaking in New York recently at Tabor Communications’ HPC & AI on Wall Street conference, Thurston discussed his data-driven, decade-plus quest to take on the venture industry’s immutable laws – not only its high flop rate but also its approach to investment discovery and assessment.


As bottlenecks move, so does opportunity. Finding them can change where capital is most useful, whether the goal is creating economic value or making progress on something that matters.

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