Jensen Huang on the smartest person he's ever met;

Is JD Vance seriously suggesting that immigrants have brought a culture of revolution and protest TO FRANCE? @jonstewart

When software shapes the car, what’s left for design? The human. See how we’re building the next generation of intelligent cars with @Stellantis. appliedintuition.com/blog/st…

Today, our team is excited to announce @InspiredCap Fund IV, $450M in new capital to back early-stage founders. There has never been a moment in history when more is possible. It takes just one person with exceptional ambition to take on the world’s problems and change billions of lives for the better.

Dreamlabs is better, faster, cheaper.

Today, Dream Labs is out of stealth. In February 2026, while we were at NVIDIA, @scott_e_reed @youliangtan @GeYunhao 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 👇

🔴 INSOLITE Quand deux touristes prennent leurs vacances à Paris au mauvais moment 🧳🧳

Real-to-sim-to-real, cross-embodiment, data rendering & augmentation — we’re taking a very similar path. Excited to see what Dreamlabs is building. Can’t wait to explore our own model, too.

Spoke to an early eng at @AppliedInt yesterday and they already built an internal version of this called Dana