Joel Jang
@jang_yoel • 4,182 subscribers
Co-founder & CEO of @dreamlabs_ai
Videos
Today, Dream Labs is out of stealth. In February 2026, while we were at NVIDIA, Scott Reed youliang Yunhao Ge and I started calling a new kind of robot model a World Action Model, one that learns how the world moves from video, then uses that to decide how to act. Today, we’re releasing Dream-1 through a public API that anyone in the world can use. When you rent a car you’ve never driven, you don’t learn to drive all over again. Within a few minutes, it feels like your own. Robots should work the same way: a good model should be able to pick up a new robot and get to work, without being retrained from scratch. That’s what we’ve spent the last 6 months on, and it’s what Dream-1 does. It controls bimanual robots with parallel grippers it has never seen before, zero-shot, on unseen tasks in unseen environments. Generalization has been my North Star in robotics: first by distilling video world models into VLAs (DreamGen), then by learning to act from those world models directly (DreamZero), and now by transferring across robots (Dream-1). I’ve come to believe it’s the only direction that lasts. Pushing a narrow model from 90% to 99.9% on a single task is real work, but much of it gets washed away once a model that generalizes arrives. Since the start of the company we’ve stayed single-minded about generalization.That focus is what got Dream-1 to control robots it was never trained on, on tasks it was never shown. And it’s what makes a public API possible at all: a model that only does one task on one robot can’t serve millions of users. Dream-1 is still a research beta, and it will make mistakes. But it already drives cars it’s never seen. Generalization wins in the end, and the end is closer than it looks. Here’s Dream-1 taking the wheel of a robot it’s never seen. Full details 👇
Joel Jang34,836 Aufrufe • vor 10 Tagen
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