GoKawiilOPAL package lets an AI agent rewrite optimizer code mid-training
A research project called Reactive Optimizers introduces an agent that monitors training dynamics in real time and rewrites the optimizer's source code during a single training run, rather than relying on a fixed recipe set before training begins. The team reports this approach matches or beats hand-tuned optimizer recipes on image and language tasks when no specific recipe exists for the task, and says the agent independently devised schedules and strategies to avoid loss spikes and overfitting. The method is available for testing via the OPAL package.