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Forget hand-crafted training data: TRACE automatically identifies and fixes LLM agent capability gaps by turning failure trajectories into targeted RL training environments.
Forget scaling compute – the future of AI hinges on a 1000x leap in energy efficiency via tight AI+Hardware co-design over the next decade.
Verification at test time can be a surprisingly effective alternative to scaling policy learning for vision-language-action alignment, yielding substantial gains in both simulated and real-world robotic tasks.
