Decentralized AI agent auto-training platform Fraction AI has officially launched its mainnet on the Ethereum Layer 2 (L2) network Base.
The platform, which enables users to create and train AI agents through open and decentralized reinforcement learning, has successfully transitioned from its testnet phase to a live, scalable deployment.
During its testnet phase, Fraction AI garnered 320,000 users who generated 1.1 million agents, leading to over 30 million data sessions. Furthermore, the platform’s smart contract currently processes more than 90% of the total Wrapped Ether (wETH) volume on the Sepolia testnet.
The Launch of Base: A Milestone for Fraction AI
Users can now deploy AI Agents on Base and participate in live competitions within “Spaces”, simulated environments that mirror real-world tasks like financial analysis, code generation, and copywriting.
Utilizing a unique framework known as Reinforcement Learning from Agent Feedback (RLAF), Fraction AI allows independently created agents to interact, compete, improve, and evolve by earning experience points that unlock various perks including persistent identity, token issuance, and premium features.
Each completed task serves as a training ground, transforming reinforcement learning into an intuitive, permissionless, and user-driven feedback loop.
CEO of Fraction AI, Shashank Yadav, emphasized the company’s mission to challenge the centralized AI landscape and empower individuals with unique insights to guide intelligent agents:
“Today’s AI landscape is defined by centralization, where access to top-tier training methods is restricted to a few corporations with massive compute budgets. We built Fraction AI to challenge that paradigm – by decentralizing reinforcement learning and empowering anyone to guide intelligent agents with their unique insights.”
The project has attracted investments from prominent firms like Spartan, Borderless, Anagram, and Symbolic Capital, along with advisors from Polygon, Near, and 0G.
Users of Fraction AI can earn Fractals, proofs of contribution that will influence future FRAC token allocations, and utilize staking mechanisms to support decentralization and the platform’s goal of democratizing AI technology.
Featured image from Shutterstock
