Polymath

Polymath provides world generation models and systems designed to automate the creation of reinforcement learning environments. As the focus of AI shifts towards autonomous agents capable of operating over extended periods, it becomes crucial for models to be trained in environments that mirror the real world. Currently, the generation of RL environments is limited by the need for human labor, with companies often employing contractors to manually create artifacts, a method that is costly and lacks scalability. Relying solely on human data is insufficient for achieving superintelligence. Polymath is developing core technology to enable automated environment generation, significantly reducing the need for human effort and eventually eliminating it. This innovation facilitates the creation of more complex and realistic worlds, enhancing the quality, scale, and diversity of tasks, which is vital for advancing RL scaling. The ultimate objective is to generate realistic, long-horizon environments from a simple text description, allowing for the creation of worlds with arbitrary complexity and scale. This capability is fundamental for training and evaluating autonomous, superintelligent AI agents.