Turning machine learning research into products for industry
Turning machine learning research into products for industry


Reza Zadeh details three challenges on the way to building cutting-edge ML products, with a focus on computer vision, offering examples, recommendations, and lessons learned. 1) Since ML is all about approximation, it can be difficult to assess when a research result is good enough for the industry. 2) Building systems that scale ML models in production is a challenge on its own. Although a model may work in the lab, scaling it to millions of users may be impossible without further research. 3) Building good user interfaces for ML products is crucial. Since ML researchers often don’t have a background in user-focused design, they tend to underestimate the importance of good UX design.


Reza Bosagh Zadeh is Founder CEO at Matroid and an Adjunct Professor at Stanford University. His work focuses on Machine Learning, Distributed Computing, and Discrete Applied Mathematics. Reza received his PhD in Computational Mathematics from Stanford under the supervision of Gunnar Carlsson. His awards include a KDD Best Paper Award and the Gene Golub Outstanding Thesis Award. He has served on the Technical Advisory Boards of Microsoft and Databricks, and has been working on Artificial Intelligence since 2005, starting at age 18 when he worked in Google's AI research team.

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