FLock.io Launches Incentivized Beta for Decentralized AI Training Platform with Foundry as one of early Participants
Train.FLock.io Invites Users to Earn Rewards by Staking Tokens for AI Model Training
FLock.io announces the launch of train.flock.io, the web app for its decentralized AI training platform, now available as part of its incentivized beta program. This platform allows users to earn rewards by staking tokens to help train and fine-tune AI models.
Foundry, a leading node operator in decentralized AI, is participating in the FLock.io incentivized beta to provide valuable feedback. “Foundry is excited to participate in the FLock.io beta, operating both Training and Validator nodes. FLock.io’s focus on decentralizing and democratizing AI aligns perfectly with Foundry’s mission of empowering a decentralized infrastructure,” said Mike Colyer, Foundry CEO. “Our partnership with FLock.io marks a milestone in Foundry’s commitment to advancing decentralized AI for generations to come.”
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FLock.io’s new web app, train.flock.io, is a significant step towards decentralized AI training. By integrating private data with on-chain rewards, FLock.io ensures fair incentives and encourages open collaboration. The platform addresses the need for bespoke AI models from Web3 and Web2 projects while keeping data local by training models without exposing source data. This beta program marks a significant advancement in traceable contribution and on-chain incentivization for data owners, model developers, and compute providers. The goal is to develop specialized models for diverse communities, shaping the future of AI model training. FLock.io invites the public to participate in shaping the future of AI by executing tasks within the platform.
Jiahao Sun, Founder and CEO of FLock shared, “We’re excited to have Foundry onboard, significantly expanding our decentralized network and stability. Foundry’s strong support and early adoption greatly stimulate the decentralized AI community. With train.flock.io, we’re addressing the growing demand for custom AI models, empowering communities to create and train specialized models while ensuring top-notch data protection and security.”
Crypto incentives are central to driving momentum in open-source, decentralized, and composable AI development, providing a solution to the financial challenges often faced by traditional open-source projects. Participants stake $FML, FLock.io’s beta token, to engage in tasks. Developers can choose between running automated training/validation scripts or creating bespoke processes for better performance. This staking mechanism promotes good behavior, rewarding or penalizing users based on their actions. Blockchain ledger technology ensures the security and integrity of these processes, and FLock.io researchers recently highlighted the platform’s role in preventing malicious attacks in a paper published in the IEEE Transactions on Artificial Intelligence.
Users can engage with the FLock.io network as training nodes, validators, or delegators. Training nodes handle AI task training and stake tokens for task eligibility, with FLock.io providing a training script for a quick start. Validators run validation scripts to evaluate models submitted by training nodes, ensuring fair task distribution, with rewards based on FLock.io’s on-chain model consensus. Delegators delegate tokens to validators, enhancing the validation process and indirectly boosting the network’s efficiency and reward mechanism. Task creation is currently managed by the FLock.io team but will soon be open to public participation, allowing users to define desired models. These participants are coordinated by the on-chain rewards mechanism to produce a diverse range of AI models needed by communities, such as AI companions, crypto trading bots, and a Web3 search engine.
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