Robot Demos Are Easy. Reliability Is Hard — Jason Ma, Dyna Robotics

A generalist robot that succeeds 80 to 90% of the time makes a great video but a poor product.

Jason Ma, co-founder and CTO of Dyna Robotics, shows how Dyna got its model, Dyna-1, to a 99.4% success rate folding restaurant napkins for 24 hours straight, including recovering after it pulled over the whole stack. The key is a reward model that watches the robot and scores its progress. When the score dips, the robot is making a mistake, so the team can collect targeted recovery data and fine-tune again in a human-in-the-loop active-learning cycle. Ma also covers Dyna's pre-training data pyramid of more than 200,000 hours, and its architecture that pairs a reasoning model with a world action model. He shows deployments in restaurants and a Sacramento laundromat, and a robot folding T-shirts for three days straight at CoRL in Korea with no site-specific data.

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