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Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared…
Microsoft ResearchPublished Sep 24, 2026
Official source · Microsoft ResearchVerified Oct 10, 2026
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic applications.
Google DeepMindPublished Jul 30, 2026
Official source · Google DeepMind BlogVerified Sep 6, 2026
AI has the potential to help solve some of the world’s biggest challenges — not just in the digital realm, but in the physical world, too. Robotics is one of the most exciting frontiers of AI, where advances in language, vision and action models can help create intelligent machines that interact with the real world in…
Google DeepMindPublished Jun 9, 2026
Official source · Google DeepMind BlogVerified Sep 6, 2026
The bottleneck isn’t the model. It’s the data. Robot learning has a supply problem. We have capable policy architectures (transformer-based VLAs, diffusion and flow-matching policies, and even world models) and the GPUs to train them. What we lack is large, diverse, real-world manipulation data.
Hugging FacePublished Jul 21, 2026
Cross-checked · Hugging Face BlogVerified Sep 4, 2026
World foundation models offer a different path. Instead of manually authoring every object and physical interaction, they learn visual dynamics directly from synchronized video and robot kinematics. NVIDIA's Cosmos-H-Surgical-Simulator demonstrated this approach by generating future surgical video from an initial scen…
Hugging FacePublished Jul 27, 2026
Cross-checked · Hugging Face BlogVerified Sep 9, 2026