The impressive progress of Omniverse and digital twins | Nvidia GTC 24 panel

Driving back and forth between San Francisco and San Jose is never fun. But I’m glad I made the trek from the Game Developers Conference in SF to the Nvidia GTC 24 conference in SJ so I could moderate an interesting panel about the industrial metaverse.

The session was entitled “Digitalizing the world’s largest industries with OpenUSD and generative AI.” In a place full of 16,000 engineers and sprinkled with celebrities like Nvidia CEO Jensen Huang and CNBC’s Jim Kramer, I was glad to see we had a full house in the room.

Our panelists included Rev Lebaredian, vice president of Omniverse and simulation technology at Nvidia; Patrick Cozzi, CEO of Cesium, Joe Bohman, EVP of PLM products at Siemens Digital Industries Software; Andy Pratt, CVP of emerging technologies at Microsoft; Christine Osik, head of simulation at Amazon Robotics; Benjamin Chang, VP of global manufacturing at Wistron; and Paulina Chmielarz, industrial operations innovation director at Jaguar Land Rover (JLR).

Progress for digital twins

Our charter was to see how far and fast the world’s largest industries are racing to digitalizing their complex industrial and enterprise processes. After a few years of hearing about the benefits of digital twins and the Pixar-inspired Universal Scene Description (USD), they’re pretty sold on the idea and are racing to establish the OpenUSD standard. With standardized assets, enterprises will be able to collaborate and re-share their assets with each other to achieve greater efficiencies and productivity.

If you haven’t heard of digital twins, they have a clear use case, in contrast to the consumer version of the metaverse, which has fallen out of favor. With digital twins, a big company can design a virtual factory and perfect that design before it puts a shovel in the ground on the physical factory. Once that design is good, they make a twin of that design in the real world, with extreme precision.

That requires an accurate simulation so that the simulated digital factory matches the real world factory. And by outfitting the factory with sensors, the company can capture real world data that can be fed back into the virtual factory, improving its accuracy and saving tons of money by building things right the first time and then continuously updating them to keep up with changing missions and real world demands.

Our panelists did a good job talking about how far simulation has come and how far it has to go in closing the “SimToReal” gap. How much accuracy do enterprises and heavy industry companies require in their digital twins? It seems like the answer is the simulations must constantly get better.

VentureBeat: I’m Dean Takahashi, lead writer for GamesBeat at VentureBeat. I’m sure you think I got lost here coming to this enterprise and industrial session. It’s not a video game session, but I’ll try to sneak in a game reference every now and then. I’ve been covering tech for 35 years and games for about 27. It’s interesting to see the intersection between games and tech. This whole technology here is one example of that. We’ll start with introductions with Andy Pratt, from Microsoft.

Andy Pratt: I’m corporate vice president for emerging technology. I have gaming studios in my team as well, and so it’s a safe space. But the main team that I lead is around how we take advanced AI teams, software engineers, and we’re just focused on our customers and partners. How do we take this emerging technology and hit value at scale? To your point, we’re using game technology in heavy assets a lot just now.

Benjamin Chang: I’m from Wistron. We’re mainly a leading EMS provider. My major role would be process engineering and development, and also digital transformation for small factories.

Christine Osik: I’m from Amazon Robotics. I lead teams that are responsible for system operations in those robotics, and for simulation. We build everything from robotic work cell level emulators for development and testing, all the way to building full digital twins.

Joe Bohman: I’m head of PLM products at Siemens. Anybody that saw that boat in Jensen’s keynote, that really cool LNG carrier, that was us. Within PLM we provide a set of tools for our customers to help them design all sorts of great products that we use every day.

Patrick Cozzi: I’m CEO at Cesium. We enable software developers to build 3D experiences and simulations with geospatial data. Providing a global canvas for terrain, buildings, to allow folks to build their applications.

Paulina Chmielarz: I’m the director of photodigital and innovation at JLR. You might have seen in the keynote a small snippet of the Defender, or our famous Range Rovers. We digitalize manufacturing, supply chain, and procurement.

Rev Lebaredian: I lead the Omniverse and simulation team here at Nvidia. We’re building a collection of technologies to create simulations, so that our AIs can be born and raised inside these virtual worlds before we bring them out into the real world. You saw a bit of that in yesterday’s keynote. Jensen explained how the next wave of AI is going to be grounded in reality, in the physics of reality. Omniverse is that bridge for us.

VentureBeat: I’m going to start with a question for Paulina, Christine, and Benjamin. Each of you represents some of the world’s largest industries – automotive, supply chain, warehouse automation, and electronics manufacturing. What are industry technology requirements and priorities to help you with your digitalization efforts?

Chmielarz: I could categorize the priorities for us in three groups. The first, fundamental element is our infrastructure. The technical element of gearing up our factories and our operations with the correct baseline to use the systems. The second element is systems of record. Those big elements of data that we need, the transactions we need. Then all the technology on top of that, that really takes it to the next level. Those are the three big pieces of the story for us.

Osik: At Amazon, our fleet of robotics is essential in bringing better value for our customers. Speed, price, and selection, that’s what drives it. We have a range of priorities, but our first priority is making sure those robots are safe. We use simulations for that. We use digital twins for that. We also use digital twins in design to optimize flow through the buildings. Then we also have the operations. We need to get the same thing as Paulina. We have to collect all the metrics and data coming from the various buildings and distill them for the operators to operate their robotic solutions efficiently.

Chang: For Wistrom, we started our smart manufacturing initiative around 10 years ago. At