HTC Seminar #26 - Abstraction and Reasoning in AI systems: Modern Perspectives

 Todays's seminar was alluded to in yesterday's HTC Deep Learning Update.  "Abstraction and Reasoning in AI systems: Modern Perspectives", by Francois Chollet, Melanie Mitchell, Christian Szegedy.  It was presented at the most recent NeurlPS conference this month.

You can watch the presentation and associated slides on SlidesLive here.

If you read the HTC blog it should be obvious why i'm jazzed about this particular talk and associated paper.  It's a big affirmation to the notion that what deep learning networks do is manifold learning.  They approximate the nonlinear functional transformation to get from the input super high dimensional space to the internal manifold that the perceptual information in the input data live on.


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