Will decentralized protocols become the future infrastructure of machine learning?

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AI and machine learning networks built on decentralized infrastructure could allow the onboarding of significant hardware resources worldwide.

Booming interest in artificial intelligence and machine learning has led to a shortage of hardware resources and exorbitant cloud service costs, but decentralized infrastructure could challenge the dependence on centralized players.

Grieve says the network holds significant potential as the internet changes to a more dynamic representation of information that will empower “self-sovereignty and computational liberty online.” “How can you peer with another device and train a machine learning model on that device where A), the device is untrusted? B), your training model can’t fit on that single device. And C, you want the achievable scale of the entire system and unit economic outcomes as good as AWS,” Grieve said.describes the protocol as “a layer-1 trustless protocol for deep learning computation.

“Satoshi gave people the right to their money again; they could generate it from a laptop. They could convert electricity into money. They could convert fiat into something harder.” This provides two potential major benefits for protocols like Gensyn, which could tap into a broad set of devices to contribute to its global supercluster. Grieve says:

 

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