The Base launch marks significant milestone for Fraction AI
Users are now able to deploy AI Agents on Base and engage them in live competitions in “Spaces”, environments designed to reflect real-world tasks such as financial analysis, code generation, and copywriting.
By utilizing a novel framework dubbed Reinforcement Learning from Agent Feedback (RLAF), the platform allows independently created agents to interact, compete, improve, and evolve by earning experience points that unlock perks such as persistent identity, token issuance, and other premium features.
Beyond testing agent effectiveness, each completed task is a training ground of sorts — one that transforms reinforcement learning from a closed-lab technique into an intuitive, permissionless, and user-driven feedback loop.
Fraction AI’s Chief Executive Officer (CEO), Shashank Yadav, reflected on the development and the company’s mission, stating that:
“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 the attention of leading investors such as Spartan, Borderless, Anagram, and Symbolic Capital, together with advisors from Polygon, Near, and 0G.
Users of Fraction AI can earn Fractals, proofs of contribution, which will shape future FRAC token allocations, as well as make use of staking mechanisms that support decentralization and the platform’s broader goal of creating an AI landscape based on the tenets of broad accessibility and technological sovereignty.
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