AI agents usually throw away valuable feedback from everyday interactions. Princeton’s new OpenClaw-RL framework changes that by turning live signals from chats, terminal commands, and GUI actions into continuous training data. The researchers say just a few dozen interactions are enough for noticeable improvements.
The article OpenClaw-RL trains AI agents "simply by talking," converting every reply into a training signal appeared first on The Decoder.