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New open models, physics engines and benchmarks let robots train for precise manipulation in realistic virtual worlds before attempting the same tasks on real factory floors.

Berkeley and NVIDIA researchers say AI agents that generate, test and refine robot-control programs in simulation could ease the data and engineering bottlenecks holding robotics back.

An automated biology laboratory coordinates more than 20 instrument types, executes parallel protocols and stores digital information in DNA, while people handle maintenance.

From frozen models to mind children: learning, bodies, and experience. Continual learning, embodiment, and why frozen AI weights may not settle the question of machine consciousness.

Zhang Yunhan, founder of Chinese robot brain startup Spirit AI, predicts humanoid robots will handle most general-purpose tasks from verbal instructions by 2027. The Beijing-based company, known for partnerships with Xiaomi and Qualcomm, sees this as a ChatGPT-like moment for embodied AI, though practical household applications remain further out.

A biotech startup connected an AI agent to lab equipment and let it carry out a brain injection on a living mouse, with human safeguards in place.

University of Nottingham researchers have built a robotic laboratory guided by artificial intelligence that can prepare and test candidate materials for heat-resistant coatings on its own.

Elon Musk's companies are advancing an unusually broad slate of technology initiatives in 2026, spanning brain-computer interfaces, humanoid robots, autonomous vehicles, semiconductor manufacturing, and AI infrastructure.

Researchers at Seoul National University have developed Dynin-Robotics, a single AI model that combines language understanding, visual prediction, and robot control. In tests on a real robot, it achieved a 78.4% success rate, outperforming models from NVIDIA and Physical Intelligence.