Researchers unveil AI swarm training without assigned roles

Groups of language models reportedly learned to communicate and coordinate without prescribed roles through cooperative reinforcement-learning post-training. Reported gains include better token efficiency and task success than compute-balanced baselines, plus learned protocols generalizing to swarms up to three times larger. The approach also reportedly outperformed single-agent best-of-N sampling. The announcements do not detail the models, benchmarks or absolute results.