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"text": "I made Physical AutoResearch sound simple (conceptually), but it took a village to pull off and lots of design thinking into the robot /loopcraft. The hardest part is everything we need to setup *before* pressing Enter. Here's a behind-the-scene tour:\n\n1. Safety harness\n\nLetting 8 robots run unattended overnight means safety has to be more than a hint in the system prompt. ENPIRE hardwires it in 2 layers: (1) hard kinematic limit that trips an immediate task failure and auto-resets as soon as a robot leaves its safety envelope, and (2) a torque-limited compliant gripper so a bad contact or misaligned insertion ends in a safe stall, instead of crushing the robot or the object at hand. \n\nWe make safety more conservative than usual so humans can sleep tight. In reality, we still need a few human operators to watch over the \"robots of loving grace\". \n\n2. Definition of /done\n\nAn agent that can edit its own reward will game it for sure. ENPIRE fixes the goalposts before the fleet can move them. Here's the recipe:\n\nCollect a few minutes of success & failure demos\n-> Ask agent to write code using computer vision tools to classify success and measure against groundtruth\n-> Agent hill-climbs on classifier until reliably good\n-> This classifier becomes the real-time reward function that directly computes on sensor streams \n-> *Freeze* the reward function before AutoResearch. It's sacred, enshrined in a Gym env that no one can touch.\n\n3. System telemetry design\n\nRobot-seconds is by far the scarcest resource, followed by GPU-seconds, and finally tokens. We instrument all three and surface them to ENPIRE for live resource awareness rather than letting it hill-climb in a vacuum. \n\nWe define:\n- Mean Robot Utilization (\"MRU\"): the fraction of wall-clock time when the robot is actively executing an experiment. Otherwise the hardware is sitting idle and waiting for the next code commit.\n- Mean Token Utilization (\"MTU\"): tokens consumed per minute, our proxy for how hard the agent is actually thinking. A low MTU means the agent is stalled, waiting on a robot rollout to finish instead of doing research.\n- GPU utilization: fraction of wall-clock time when GPU is active. \n\n... and evaluate on two budget-to-outcome metrics:\n\n1. Tokens-to-Success: token budget the fleet burns to complete /goal.\n2. Time-to-Success: wall-clock time to /goal",
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