Ring-Zero scales zero RL to one trillion parameters for emergent reasoning

Researchers have published a paper on arXiv titled "Ring-Zero," describing how zero-shot reinforcement learning can be scaled to one trillion parameters in a language model. The goal is to elicit emergent reasoning capabilities at unprecedented scale. The paper received 3 points on Hacker News with no comments yet.