Deepu Talla, Vice President of Robotics and Edge AI, NVIDIA. (Image: Chitra Sethi)

In the rapidly evolving landscape of advanced manufacturing, the convergence of physical AI and high-fidelity simulation technologies is ushering in a transformative era of AI-powered automation. These innovations are not only enhancing precision, adaptability, and efficiency on the factory floor but could also play a pivotal role in reshoring efforts — bringing manufacturing capabilities back to the U.S.

“The ChatGPT moment of robotics is here,” according to Deepu Talla, Vice President of Robotics and Edge AI at NVIDIA, who presented the keynote titled “Industrial Autonomy in the Era of Physical AI” on May 13 at Automate 2025. Talla spoke about how NVIDIA’s vast ecosystem of industrial software, hardware, AI and robotics partners is helping accelerate this next wave of AI for industrial transformation.

Two technologies — physical AI and simulation — are reaching their tipping point. (Image: Chitra Sethi)

“There is incredible opportunity for reshoring to happen in North America and the only way it can happen is through industrial automation,” said Talla. He highlighted that there is a fundamental shift happening in the industry fueled by two technologies — physical AI and simulation — that are reaching their tipping point.

Physical AI, models that can understand and interact with our physical world, will embody every industrial facility. “Experts, all the way from researchers to companies are laser-focused on this, and the whole ecosystem is moving toward developing physical AI,” he said.

Simulation is now faster, safer, and cheaper. “Almost everyone is building and testing in simulation first. It has matured sufficiently that we can use it confidently whether it’s for single robot training or a fleet of robots. All of our partners are building and testing in simulation, significantly cutting time to development,” explained Tulla.

Tulla highlighted four major steps of autonomy: creating data, training AI, testing AI in simulation, and then deployment in real world. Within each of the steps, NVIDIA provides the computing infrastructure, workflows for developers, and acceleration libraries to speed up computing.

NVIDIA’s three-computer architecture is empowering the entire robotics ecosystem. (Image: Chitra Sethi)

“The manufacturing industry is experiencing a fundamental shift, with industrial automation and AI-powered robots increasingly changing how warehouses and factories operate worldwide,” said Talla. “NVIDIA’s three-computer architecture — enabling robot training, simulation, and accelerated runtime — is empowering the entire robotics ecosystem.”

Embodied AI systems, which refers to the integration of AI into physical systems, must be trained with real-world data — traditionally a complex and resource-intensive process. Each robot typically needs its own custom dataset due to differences in hardware, sensors and environments.

Synthetic data offers a powerful alternative. NVIDIA Isaac Lab 2.1 — the latest version of the open-source robot learning framework, announced at Automate — provides developers with tools to accelerate the robot training process using the NVIDIA Isaac GR00T Blueprint for synthetic motion generation. Built on NVIDIA Omniverse, a physical AI simulation platform, and NVIDIA Cosmos world foundation models, the blueprint provides a reference workflow for creating vast amounts of synthetic and robot manipulation data, making it easier and faster to train robots, like manipulators and humanoids, for a variety of tasks.

In addition to robots, manufacturers everywhere are increasingly turning to AI agents capable of analyzing and acting upon ever-growing video data. The NVIDIA AI Blueprint for video search and summarization (VSS), combines generative AI, large language models, vision language models and media management services to deploy visual AI agents that can optimize processes, such as visual inspection and assembly, and enhance worker safety in factories and warehouses.

The future is physical AI. According to Talla, physical AI will embody every industrial facility — from warehouse to factory — the robots that work alongside us within them, and the vehicles that transport manufactured goods around the world.

For more information, visit https://blogs.nvidia.com/blog/robotics-industrial-ai-automate/  .

Topics:
AR/AI Automation Robotics Software

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