Data is the source of intelligence for foundation models. The scaling of language models has shown that model capability ...
Robots are increasingly expected to operate beyond structured laboratories, where they must interpret incomplete sensory ...
Need to separate bolts that arrive in a mixed batch onsite? Hexagon's Aeon robot can do that. Aeon's human friend is 'seeing' items in front of it with head-mounted cameras through NVIDIA Omniverse.
Interesting Engineering on MSN
US firm builds 90,000-sq-ft robot park to advance humanoid robots with real-world training
Texas-based humanoid robotics company Apptronik has opened Robot Park, a nearly 90,000-square-foot training and ...
4D were impressed with Loop Technology’s advanced system knowledge and capability with Robotic Integration, and ability to offer Robotmaster as an advanced OLP system to their existing robot ...
Robot skill library ASPIRE — released June 29 by NVIDIA and collaborators — gives robots persistent memory by storing every debugging fix as a named, reusable code pattern. It pushed bimanual handover ...
Three AI coding agents, including Claude Code and Codex, trained on real hardware, achieving 99% success on tasks like GPU installation and pin sorting.
TechCrunch on MSN
Collecting robot training data is dirty, unglamorous work. Some AI labs are already paying XDOF to do it.
If physical AI is going to match the accomplishments of LLMs, there's a data problem that needs to be solved.
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