Machine Learning Street Talk (MLST)

Sara Hooker - The Hardware Lottery, Sparsity and Fairness


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Dr. Tim Scarfe, Yannic Kilcher and Sayak Paul chat with Sara Hooker from the Google Brain team! We discuss her recent hardware lottery paper, pruning / sparsity, bias mitigation and intepretability. 

The hardware lottery -- what causes inertia or friction in the marketplace of ideas? Is there a meritocracy of ideas or do the previous decisions we have made enslave us? Sara Hooker calls this a lottery because she feels that machine learning progress is entirely beholdant to the hardware and software landscape. Ideas succeed if they are compatible with the hardware and software at the time and also the existing inventions. The machine learning community is exceptional because the pace of innovation is fast and we operate largely in the open, this is largely because we don't build anything physical which is expensive, slow and the cost of being scooped is high. We get stuck in basins of attraction based on our technology decisions and it's expensive to jump outside of these basins. So is this story unique to hardware and AI algorithms or is it really just the story of all innovation? Every great innovation must wait for the right stepping stone to be in place before it can really happen. We are excited to bring you Sara Hooker to give her take. 

YouTube version (including TOC): https://youtu.be/sQFxbQ7ade0

Show notes; https://drive.google.com/file/d/1S_rHnhaoVX4Nzx_8e3ESQq4uSswASNo7/view?usp=sharing

Sara Hooker page; https://www.sarahooker.me



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Machine Learning Street Talk (MLST)By Machine Learning Street Talk (MLST)

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