In episode 34 of The Gradient Podcast, Daniel Bashir speaks to Sara Hooker.
Sara (@sarahookr) leads Cohere for AI and is a former Research Scientist at Google. Sara founded a Bay Area non-profit called Delta Analytics, which works with non-profits and communities to build technical capacity. She is also one of the co-founders of the Trustworthy ML Initiative, an active participant of the ML Collective research group, and a host of the underrated ML podcast.
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Sections:
(00:00) Intro
(02:20) Podcasting gripe-fest
(06:00) Sara’s journey: from economics to AI
(09:15) Economics vs. AI research
(12:45) The Hardware Lottery
(19:15) Towards better hardware benchmarks
(26:00) Getting away from the hardware lottery
(32:30) The myth of compact, interpretable, robust, performant DNNs
(35:15) Top-line metrics vs. disaggregated metrics
(39:20) Solving memorization in the data pipeline, noisy examples
(45:35) Cohere For AI
Episode Links:
Sara Hooker: Cohere For AI, the Hardware Lottery, and DL Tradeoffs