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Boston Dynamics has published a technical blog explaining how Atlas learned to lift and carry objects exceeding 100 pounds using reinforcement learning trained across millions of GPU-parallelized simulations, with the behavior developed within weeks of the robot’s public debut.
Sony’s Ace robotic arm has become the first autonomous system demonstrated to be competitive with elite human table tennis players, according to a study published in Nature, tracking a ball with 10-millisecond latency and winning matches against top-ranked opponents.
Toyota has introduced CUE7, the latest iteration of its basketball-shooting robot, featuring a significantly lighter frame, an inverted two-wheel base, and a hybrid control system combining reinforcement learning with model predictive control.
AGIBOT introduced Genie Sim 3.0, a unified platform combining simulation, data generation, and benchmarking to accelerate embodied AI development.
Boston Dynamics and the Robotics & AI Institute unveiled new footage showing the Atlas humanoid robot executing gymnastic-style movements, highlighting advances in whole-body control and simulation-to-reality learning as the company prepares for enterprise deployment.
Machine learning focuses on data-driven methods that enable systems to learn, adapt, and improve over time.