Digital twins allow engineers to test factory changes, train robots and assess infrastructure performance before implementing solutions in the real world. In an interview with Qazinform News Agency, Rev Lebaredian, NVIDIA ’s Vice President of Physical AI Simulation, discusses the opportunities these technologies offer Kazakhstan and why computing power alone is not enough to put them into practice.
You have spent more than 30 years working in computer graphics, from Hollywood studios to NVIDIA. How has the role of computer graphics changed with the rise of artificial intelligence, and what do you think is the biggest transformation still ahead? For much of my career, computer graphics was about creating virtual worlds that people could believe in.
With physical AI, those worlds become places where machines can learn. That makes the physics essential: a robot needs to understand what happens when it picks up an object, moves through a room or encounters something it hasn’t seen before. Simulation lets developers explore those interactions repeatedly, under conditions that would be expensive, difficult or dangerous to reproduce physically.
The biggest transformation ahead is AI moving into the physical world - helping machines perceive, reason and act. Decades of progress in graphics, physics simulation and accelerated computing are providing essential building blocks for that transition. NVIDIA Omniverse is designed to create and simulate physically accurate virtual worlds.
How close are we to a point where companies can test factories, robots, vehicles or entire cities virtually before deploying them in the real world? This is already happening. BMW Group uses NVIDIA Omniverse in its Virtual Factory to plan and test manufacturing changes.
BMW said previously that a production-line collision check that previously required almost four weeks of physical testing can now be simulated in three days. AI agents are now changing how we build and use these digital twins too. A great deal of engineering effort goes into preparing the data, connecting software and setting up simulations.
With NVIDIA Omniverse libraries and agent skills, developers can have agents help carry out that work and run experiments. An engineer could describe a goal - such as moving materials through a factory more efficiently - and have an agent help explore different layouts and compare the results.
The digital twin gives that agent a way to test the likely physical consequences of a proposed change. Engineers can explore more possibilities, check the results against physical tests and real-world measurements, and use that feedback to refine the digital twin and decide which changes to make.
What industries do you expect to benefit most from the combination of generative AI, Omniverse and simulation over the next five years - manufacturing, automotive, energy, construction, healthcare, or something else? Manufacturing, logistics and automotive are among the strongest near-term opportunities.
They involve complex physical systems, where changing a production line, introducing a robot or testing a vehicle can be expensive and time-consuming. Simulation lets engineers explore those changes virtually. Generative AI can help create more varied training scenarios, and AI agents can help coordinate design, simulation and optimization, making it easier to explore more options.