Relying on human prejudgement in this manner usually leads to an impenetrable ceiling on the agent’s performance: the agent cannot discover better strate-gies that are underappreciated by the human rater. To discover new ideas that go far beyond existing human knowledge, it is instead necessary to use grounded rewards: signals that arise from the... See more

Agents in the era of experience will act autonomously in the real world. LLMs in the era of human data focused primarily on human-privileged actions and observations that output text to a user, and input text from the user back into the agent. This differs markedly from natural intelligence, in which an animal interacts with its environment through... See more

To progress significantly further, a new source of data is required. This data must be generated in a way that continually improves as the agent becomes stronger; any static procedure for synthetically generating data will quickly become outstripped. This can be achieved by allowing agents to learn continually from their own experience , i.e., data... See more