The chapter explores the problem of verification in decentralized systems and proposes focusing on narrow niche use cases and expert protocols. It discusses the benefits of using different devices for economic value and mentions use cases in the crypto space. The chapter also delves into the challenges of training models on decentralized GPUs and highlights the need for optimal scheduling and framework agnosticism.
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/
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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