TL;DR: A Qwen3.6-based agent has been RL-trained to autonomously generate and submit full RL training jobs for other AI models, demonstrating meta-learning capabilities.
Summary: A Qwen3.6-35B-A3B agent was RL-trained to write complete training jobs, including environment, reward, dataset, and hyperparameters, for smaller Qwen models (0.6B or 1.7B). The agent received rewards based on the performance improvement of the models it trained on a hidden evaluation. This meta-learning system showed significant episode reward climb and transferability to held-out tasks.
Why it matters: This breakthrough in autonomous AI training could dramatically accelerate model development and optimization, reducing manual effort. AI builders should explore meta-learning frameworks to automate and scale their model training pipelines.
Source: reddit