AI with AI
Episode 2.24: Black Hole Watson
Andy and Dave discuss the first image of a black hole, and its link to machine learning -- with research from Katie Bouman while she was at MIT, developing Continuous High-resolution Image Reconstruction using Patch priors (CHIRP), as a way to stitch together different sources to create a continuous whole. Next, Andy and Dave discuss research from the Sorbonne and IST Austria that tries to deduce the reward function of a recurrent neural network by assuming the neurons are agents. And research from Hopfield and Krotov examines a way to approach neural network learning in a more “plausible” biological fashion, with a more physically local method of plasticity. In reports, the European Commission releases its 41-page report on Ethics Guidelines for Trustworthy AI. Elizabeth Holm publishes a short paper in defense of the black box. A paper in IEEE Spectrum examines the actual health care products (compared to the partnerships and promises) of IBM Watson. Sean Luke publishes the second edition of The Essentials of Metaheuristics. And the video of the week is a 2016 TED Talk by Katie Bouman on the development of the software that combines the data collected by individual telescopes.