Josh Bloom — The Link Between Astronomy and ML

Josh explains how astronomy and machine learning have informed each other, their current limitations, and where their intersection goes from here. (Read more: http://wandb.me/gd-josh-bloom)---Josh is a Professor of Astronomy and Chair of the Astronomy Department at UC Berkeley. His research interests include the intersection of machine learning and physics, time-domain transients events, artificial intelligence, and optical/infared instrumentation.---Follow Gradient Dissent on Twitter: https://twitter.com/weights_biases---0:00 Intro, sneak peek1:15 How astronomy has informed ML4:20 The big questions in astronomy today10:15 On dark matter and dark energy16:37 Finding life on other planets19:55 Driving advancements in astronomy27:05 Putting telescopes in space31:05 Why Josh started using ML in his research33:54 Crowdsourcing in astronomy36:20 How ML has (and hasn't) informed astronomy47:22 The next generation of cross-functional grad students50:50 How Josh started coding56:11 Incentives and maintaining research codebases1:00:01 ML4Science's tech stack1:02:11 Uncertainty quantification in a sensor-based world1:04:28 Why it's not good to always get an answer1:07:47 Outro