While AI has achieved breakthroughs in mathematics and cybersecurity, robotics remains fundamentally harder to solve due to three factors: the massive input/output data requirements from continuous high-dimensional sensor streams, the difficulty of defining verifiable reward functions in noisy real-world environments, and the constraint that robotic actions operate at the speed of atoms rather than bits, making iteration costly and irreversible.
A reverse-engineered model mimics Jev, TypeSafe's commercial system for selecting from multiple text options in a single pass. The repository includes implementations for Doom and chess games, with training and evaluation tools using attention-based scoring across option-context pairs.