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Gauge Equivariant CNNs, Generative Models, and the Future of AI with Max Welling - TWiML Talk #267
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Sam Charrington

· 1h 03m

PodcastThe TWIML AI Podcast

Gauge Equivariant CNNs, Generative Models, and the Future of AI with Max Welling - TWiML Talk #267

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Today we’re joined by Max Welling, research chair in machine learning at the University of Amsterdam, and VP of Technologies at Qualcomm, to discuss:  • Max’s research at Qualcomm AI Research and the University of Amsterdam, including his work on Bayesian deep learning, Graph CNNs and Gauge Equivariant CNNs, power efficiency for AI via compression, quantization, and compilation. • Max’s thoughts on the future of the AI industry, in particular, the relative importance of models, data and com

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This story was published by The TWIML AI Podcast and written by Sam Charrington. SyncAI.news shows a preview; the complete article is on the publisher's site.

Read the full story on twimlai.com

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