Over 100,000 GPUs from data centers and private clusters are set to plug into a new decentralized physical infrastructure network (DePIN) beta launched by io.net.
As Cointelegraph previously reported, the startup has developed a decentralized network that sources GPU computing power from various geographically diverse data centers, cryptocurrency miners and decentralized storage providers to power machine learning and AI computing.
The company announced the launch of its beta platform during the Solana Breakpoint conference in Amsterdam, which coincided with a newly formed partnership with Render Network.
Tory Green, chief operating officer of io.net, spoke exclusively to Cointelegraph after a keynote speech alongside business development head Angela Yi. The pair outlined the critical differentiators between io.net’s DePIN and the broader cloud and GPU computing market.
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Green identifies cloud providers like AWS and Azure as entities that own their supplies of GPUs and rent them out. Meanwhile, peer-to-peer GPU aggregators were created to solve GPU shortages, but “quickly ran into the same problems” as the exec explained.
Proud to present @ionet_official at @Solana #Breakpoint2023 yesterday!
Whether you’re a GPU provider or an ML engineer – tune in for the live demonstration of the platform and join https://t.co/WLXlHkv6f1 now.
Watch the full video pic.twitter.com/E1XsgJLJNu
— io.net (@ionet_official) November 4, 2023
The wider Web2 industry continues to look to tap into GPU computing from underutilized sources. Still, Green contends that none of these existing infrastructure providers cluster GPUs in the same way that io.net founder Ahmad Shadid has pioneered.
“The problem is that they don’t really cluster. They’re primarily single instance and while they do have a cluster option on their websites, it’s likely that a salesperson is going to call up all of their different data centers to see what’s available,” Green adds.
Meanwhile, Web3 firms like Render, Filecoin and Storj have decentralized services not focused on machine learning. This is part of io.net’s potential benefit to the Web3 space as a primer for these services to tap into the space.
Green points to AI-focused solutions like Akash network, which clusters an average of 8 to 32 GPUs, as well as GenSyn, as the closest service providers in terms of functionality. The latter platform is building its own…
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