On the power of data flywheels in Physical AI @nvidia recently introduced Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, images, video, audio, and actions within a unified mixture-of-transformers architecture. One aspect I find particularly exciting is the data flywheel emerging between #Cosmos# 3 and #Alpamayo# 2. Cosmos 3 was trained using data generated and curated in part through the Alpamayo ecosystem. In turn, the next generation of Alpamayo will build on Cosmos 3's capabilities. This creates a virtuous cycle in which better models enable better data generation, and better data leads to even stronger models. Much of the attention in #AI# is naturally focused on model architectures and benchmark results. Yet, in robotics and autonomous systems, development processes matter just as much as models themselves. Robust data flywheels are increasingly becoming a defining characteristic of state-of-the-art robot autonomy stacks. Further reading: - Cosmos 3: - Alpamayo 2: Join me on June 16 at 9:00 AM PT for a livestream on Alpamayo 2 Super: The Open Reasoning Model for Robotaxis: We'll showcase brand-new elements of the open pipeline—from real-world fleet data to model training recipes to closed-loop development with simulation. If you're building toward L4 autonomy, I think you'll find it worthwhile. I'll be joined by @iamborisi @YurongYou @yan_wang_9 @MaxiIgl Looking forward to seeing you there. @NVIDIADRIVE @NVIDIAAI