00:00:00 Intro. Gaels's journey from physics to AI through coding, then health and social science applications.
00:06:17 Looking for impact. Are we using our energy to solve the best problems? How to estimate future impact?
00:12:18 How did the interacting with a wide variety of sciences changes you as an AI researcher? Out-of-the box. Empirical research.
00:13:19 Benchmarks. How they incorporate value and drive AI research. AI went from a mathematical to an empirical science. Fei-Fei Li and ImageNet.
00:19:07 The Autism Challenge: predict the condition from brain imaging. How to avoid fooling ourselves?
00:25:24 How did the medical community react? The clash between what is true and what is valuable.
00:27:15 How do you measure your scientific impact?
00:31:09 Scientific/technological and societal progress.
00:33:01 Recommender AI and the 2007 Netflix challenge.
00:35:14 How to deal with social media addiction.
00:42:06 Scikit-learn. The Toyota of AI. Origin story.
A well-designed tool for scientist is also useful for business.
00:47:03 Open source organizational structure. Ecosystem building.
00:55:57 Deep learning and scikit-learn.
00:59:37 Sociology ad psychology of scikit-learn.
01:09:57 How to bring science home. AI has become an ice breaker.
01:13:13 Gael's question: what excites me these days. Being seen; clarifying my thoughts through dialogs and writing; agency, RL, and putting AI in hardware we connect with; moving my body.
I, scientist blog: https://balazskegl.substack.com
Twitter: https://twitter.com/balazskegl
Artwork: DALL-E
Music: Bea Palya https://www.youtube.com/channel/UCBDp3qcFZdU1yoWIRpMSaZw
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