Affine is an incentivized RL environment that pays miners who make incremental improvements on a set of tasks. Learn how we are commoditizing reasoning and breaking the intelligence sound barrier.
Deep dive into how Affine uses Pareto dominance to evaluate and reward miners. Why winners-take-all creates the right incentives for model improvement.
A comprehensive guide to setting up your environment, pulling models, training improvements with RL, and deploying to Chutes for rewards.
How we built a clean, lightweight container management system with support for local and remote Docker deployments, environment caching, and type-safe definitions.
Exploring how directed incentives for reinforcement learning have never been achieved before, and why this unlocks rapid advancement in intelligence.