Hassan Maishera
FLock announced on Thursday, August 29th, that it has partnered with io.net to develop the world’s first Proof of AI (PoAI) consensus mechanism for validating the integrity of nodes operating in a decentralized compute network.
In a press release shared with Cryptowisser, FLock explained that with PoAI, decentralized physical infrastructure networks (DePINs) can verify the integrity of DePIN nodes by completing compute-intensive AI training tasks.
PoAI is an AI-native Proof of Work, directing verification resources to meaningful AI tasks. This consensus mechanism allows nodes to earn block rewards from DePIN and AI training networks, in this case, both IO.net and FLock.io.
The mechanism also involves an engine that continuously provides challenges, aggregates responses, and supplies necessary stats (e.g., latency, score deviation, data correctness) to io.net nodes to compile judgments.
While commenting on this partnership, Jiahao Sun, Founder and CEO of FLock, said,
“AI engineers and end users alike need to trust the quality of the compute resources they are provided with, and Proof of AI is the key to achieving that. Compute underpins the entire AI development process, which is why we’re starting with that, and we are delighted to join forces with io.net, a true leader in its field.”
Decentralized AI ecosystem providers can use this mechanism to verify honest actors on their networks and ensure truthful and high-quality compute AI training inputs.
FLock explained that the PoAI service will create a flywheel connecting its flagship decentralized training platform with AI DePIN platforms. The team intends to extend PoAI’s verification capability beyond compute to include AI training and federated learning, with the possibility of a dedicated AI chain also under discussion.
io.net CEO and Co-founder Tory Green also computed that,
“The arrival of Proof of AI will assuredly lead to tremendous improvements in AI model training and inference over decentralized compute networks. I am confident GPU node operators, as well as the wider AI/ML developer community, will welcome Proof of AI with open arms – we certainly have.”
FLock Data Generation will leverage idling GPU resources to perform batch inference on LLMs requested by FLock Task Creator and Training Node.
This latest development comes two weeks after io.net appointed Tory Green as its new CEO. In his new role, Tory will strengthen the Business Development and Technical teams and appoint new leadership to prepare for io.net’s next stage of growth.
FLock.io is a decentralized AI training platform based on federated learning. The platform democratizes model creation, development, and alignment by incentivizing the community to contribute training data and model feedback.
Protocols and developers can use FLock to train models specific to their own use cases, such as transaction agents, AI companions, function call models, health analytics, etc.
Meanwhile, io.net deploys and manages on-demand, decentralized GPU clusters in the IO Network. IO Network is a decentralized physical infrastructure network (DePIN) of geo-distributed GPUs from multiple sources. Hundreds of thousands of GPUs are accessible today in IO Network, and this Internet of GPUs is specifically architected for low latency, high processing demand use cases like AI/ML ops and cloud gaming. io.net democratizes access to GPU compute capacity while reducing costs, expediting lead times, and expanding choice for engineers and businesses.
