Maybe robots don't only need more robot data.

Humans already provide a gigantic record of interacting with the physical world. Why not learn from that ?

Dyna Robotics just proved robot prediction improves monotonically as human video pre-training reaches 1Mn hours.

They just launched Dyna-2, a world-action model pre-trained using 1 million hours of human video. The key breakthrough is a human-to-robot transfer scaling law.

More human video went in, better manipulation came out. And somehow, that improvement carried over to robots the model had never trained on.

At unseen customer sites, Dyna reports an 87% production pass rate for Dyna-2 versus 46% for Dyna-1 at identical post-training budgets.

So there is now an obvious next experiment: keep scaling.