[Robotics Industry] Recommended PC for "Newton Physics"
Transfer the skills learned by robots in a virtual environment (simulation) to the real world safely and quickly!!
NVIDIA Newton Physics is an open-source and high-speed GPU physics engine for robotics and simulation research, co-developed by NVIDIA, Google DeepMind, and Disney Research, and managed by the Linux Foundation. Announced in March 2025, it aims to safely and quickly transfer skills learned by robots in virtual environments (simulations) to real-world environments (sim-to-real). It requires NVIDIA's powerful GPUs to compute high-precision physical behaviors at high speed.
basic information
Newton fully supports GPU acceleration, making GPU performance the most important factor. The Newton physics engine enhances robot learning and development in collaboration with NVIDIA Isaac Lab. This is necessary because robots require real-time and highly accurate "physics calculations" to learn complex tasks quickly and safely through simulation. Therefore, this model is equipped with the NVIDIA RTX PRO 6000 Blackwell Max-Q W.E.
Price range
P6
Delivery Time
OTHER
Applications/Examples of results
- Reinforcement learning for robots: Training of humanoid and quadrupedal robots. - Bridging simulation to reality: Enhancing physical accuracy and applying learning outcomes from virtual spaces to real-world implementations. - Research on Physical AI: Improving robots' ability to understand and predict the physical properties of their environment.
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One of the current demands for AI is "physical AI," and I believe there are increasing opportunities to hear related terms such as "Omniverse" and "Isaac Sim." This time, I would like to unravel the current role and position of "Omniverse."
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[Exhibition Report] The Cutting Edge Where Physical Space and AI Intersect! The Evolution of Robotics Seen at the "Physical AI Exhibition"
On July 2, 2026, I visited the "Monozukuri World Physical AI Exhibition" being held at Tokyo Big Sight. The evolution of generative AI and reinforcement learning is breaking out of the digital world and exploring how to intelligently operate robots in the real world (physical). This exhibition was a very vibrant space that truly hinted at the next generation of manufacturing and the automation of R&D (research and development). I will report on the latest trends that particularly caught my eye on-site!
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