Exploring Machine Learning Models for Disasters and Insurable Risk

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This chapter discusses the experience of the hosts working with machine learning models for disaster and insurable risk, including the incorporation of additional data points like UFO sightings. They highlight the limitations of compute power and the value of nuanced private data sets, leading them to make a career-changing decision.

Ben Fielding and Harry Grieve are the Co-Founders of Gensyn - The Gensyn network is the Machine Learning Compute Protocol that unites all of the world’s compute into a global supercluster, accessible by anyone at any time Ben Fielding Twitter: ⁠https://twitter.com/fenbielding Harry Grieve Twitter: https://twitter.com/_grieve Gensyn's Website: ⁠https://twitter.com/gensynai Logan Jastremski's Twitter: @LoganJastremski Frictionless's Twitter: @_Frictionless_ Frictionless's Website: ⁠⁠https://frictionless.fund/⁠⁠ ___ Timecodes: 0:00 - Intro 1:10 - Founders Background 10:20 - Gensyn's Vision 15:20 - AI is the next industrial revolution 21:20 - Machine Learning and Training Compute 32:00 - Real World Limitations of Decentralized Compute 39:30 - Where does Compute come from? 50:50 - Decentralized Cost vs. Traditional Compute Clusters 55:15 - Owning your own AI 1:01:00 - Verification problem