Today we’re joined by Kyle Story, computer vision engineer at Descartes Labs.
Kyle and I caught up after his recent talk at the Google Cloud Next Conference titled “How Computers See the Earth: A Machine Learning Approach to Understanding Satellite Imagery at Scale.” We discuss some of the interesting computer vision problems he’s worked on at Descartes, including custom object detectors and the company’s geovisual search engine, covering everything from the models they’ve developed and platform they’ve built, to the key challenges they’ve had to overcome in scaling them.
For the complete show notes, visit twimlai.com/talk/173.
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Constraint Active Search for Human-in-the-Loop Optimization with Gustavo Malkomes - #505
Fairness and Robustness in Federated Learning with Virginia Smith -#504
Scaling AI at H&M Group with Errol Koolmeister - #503
Evolving AI Systems Gracefully with Stefano Soatto - #502
ML Innovation in Healthcare with Suchi Saria - #501
Cross-Device AI Acceleration, Compilation & Execution with Jeff Gehlhaar - #500
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Deep Unsupervised Learning for Climate Informatics with Claire Monteleoni - #497
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Bringing AI Up to Speed with Autonomous Racing w/ Madhur Behl - #494
AI and Society: Past, Present and Future with Eric Horvitz - #493
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Data Science on AWS with Chris Fregly and Antje Barth - #490
Accelerating Distributed AI Applications at Qualcomm with Ziad Asghar - #489
Buy AND Build for Production Machine Learning with Nir Bar-Lev - #488
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