{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"Channel Gating for Cheaper and More Accurate Neural Nets with Babak Ehteshami Bejnordi - #385","description":"Today we\u2019re joined by Babak Ehteshami Bejnordi, a Research Scientist at Qualcomm. Babak works closely with former guest Max Welling and is currently focused on conditional computation, which is the main driver for today\u2019s conversation. We dig into a few papers in great detail including one from this year\u2019s CVPR conference, Conditional Channel Gated Networks for Task-Aware Continual Learning.&amp;nbsp; We also discuss the paper TimeGate: Conditional Gating of Segments in Long-range Activities, and another paper from this year\u2019s ICLR conference, Batch-Shaping for Learning Conditional Channel Gated Networks. We cover how gates are used to drive efficiency and accuracy, while decreasing model size, how this research manifests into actual products, and more!&amp;nbsp; For more information on the episode, visit twimlai.com\/talk\/385. To follow along with the CVPR 2020 Series, visit twimlai.com\/cvpr20.&amp;nbsp; Thanks to Qualcomm for sponsoring today\u2019s episode and the CVPR 2020 Series! ","author_name":"The TWIML AI Podcast (formerly This Week in Machine Learning &amp; Artificial Intelligence)","author_url":"https:\/\/twimlai.com","html":"<iframe title=\"Libsyn Player\" style=\"border: none\" src=\"\/\/html5-player.libsyn.com\/embed\/episode\/id\/14923121\/height\/90\/theme\/custom\/thumbnail\/yes\/direction\/forward\/render-playlist\/no\/custom-color\/3e85b1\/\" height=\"90\" width=\"600\" scrolling=\"no\"  allowfullscreen webkitallowfullscreen mozallowfullscreen oallowfullscreen msallowfullscreen><\/iframe>","thumbnail_url":"https:\/\/assets.libsyn.com\/secure\/content\/76450997"}