FLock.io, a pioneer in decentralized AI model development and training, has raised $3 million in a funding round led by Digital Currency Group (DCG), with participation from Faction, Animoca Brands, Fenbushi Capital, OKJ, GnosisVC, Bas1s Ventures, A41, and GSR. This latest round brings the company’s total funding to $11 million, reinforcing its mission to democratize AI model development and accelerate the growth of its collaborative decentralized AI training platform.
The funding follows a recent grant from the Ethereum Foundation to research blockchain-based incentive mechanisms for federated AI training, solidifying FLock’s position as a leader in decentralized AI innovation. The new capital will be used to scale FLock’s platform, advance its federated learning capabilities, and prepare for a mainnet launch. The platform enables secure, collaborative AI model development by integrating blockchain technology with federated learning, ensuring privacy and equitable rewards for contributors.
Jiahao Sun, Founder and CEO of FLock.io., said FLock is driving a paradigm shift in AI development by championing decentralized, community-driven models. He emphasized that the support from DCG and other investors underscores the growing importance of decentralized AI in enabling developers to participate democratically in the AI ecosystem through shared governance and fair rewards.
Anna Bertha, an investor at DCG, stated that FLock aligns with DCG’s vision of making technology accessible to all. She noted that FLock’s innovative platform democratizes AI training, rewards contributors equitably, and fosters open collaboration — critical elements in the evolution of AI.
Currently, FLock hosts over 30 active AI models spanning Web2 and Web3 use cases, with participation from more than 1,500 training and validation nodes worldwide. Contributors from communities like Numerai, Kaggle, Foundry, and Tensorplex have collectively created over 19,000 models using the platform.
FLock.io is a decentralized platform that integrates federated learning with blockchain technology to enable secure, collaborative AI model development. It empowers contributors with equitable incentives, fosters open innovation, and ensures privacy in model training without exposing source data.
