robotics

AI2 has released MolmoSpaces and MolmoBot, robotics models trained exclusively in simulation that transfer directly to real robots without manual real-world data collection or fine-tuning. The approach eliminates months of teleoperated demonstrations typically required for simulation-trained robots. Both systems are open-source.

AI2 is developing physical AI systems trained primarily on virtual simulation data rather than expensive real-world demonstrations. The approach, demonstrated through projects like MolmoBot, addresses the historical bottleneck of manually collecting hardware training data.

ABB and NVIDIA have partnered to deploy physical AI simulation in factory automation, addressing the critical sim-to-real gap that has limited intelligent robotics deployment. The approach uses digital physics simulation to train models that transfer reliably to actual factory floors, reducing production hurdles and securing measurable ROI.

World Labs, the AI startup founded by Fei-Fei Li, has raised $1 billion in new funding to develop spatial intelligence—AI systems capable of understanding and operating in three-dimensional physical environments. The capital will fund the development of world models, a class of AI architecture designed to reason about spatial relationships and physical interactions.