Siemens and Nvidia partner to enable digital twin for the industrial metaverse
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The basic idea behind the concept of digital twins, is to help model aspects of the physical world in software.
According to a forecast from Fortune Business Insights, the market for digital twin technology and services will generate an estimated $8.9 billion in revenue in 2022, growing to $96 billion by 2029.
Industrial technology giant, Siemens, has long been modeling different elements of the real world in software, and it is now looking to advance its approach to enabling an industrial metaverse. To support its efforts, today, Siemens detailed an extended partnership with Nvidia to enable artificial intelligence (AI) digital twin capabilities.
The partnership will see Siemens industrial design and development technology integrated with the Nvidia Omniverse platform, which enables users to create photorealistic virtual simulations.
“The digital twin is the virtual representation of the real product and the value of that digital twin is how closely we can bring the virtual world and the real world together,” Tony Hemmelgarn, president and CEO of Siemens explained in a press briefing.
Hemmelgarn said that bringing Siemens technology together with Nvidia Omniverse will allow industrial organizations to make decisions faster.
One area where Nvidia Omniverse and Siemens will be able to help accelerate the decision-making process of industrial companies is with the elimination of physical prototypes. Hemmelgarn noted that in the past, automotive manufacturers often had to build costly prototypes in order to develop new vehicles.
In recent years, there has been a movement toward virtualization for automotive design, though it has typically involved the use of very specialized technology running in a specific location, often referred to as a ‘cave.’
Hemmelgarn said that with the Nvidia Omniverse, instead of automotive vendors needing a cave, the capability to visualize the new design can be opened up to a much wider audience. Omniverse doesn’t require a cave to run in any number of different locations, enabling a manufacturer to more quickly collaborate on an industrial effort.
“Siemens is number one in industrial automation and industrial software and because of this leadership position, we’re able to provide our customers with the most accurate, complete digital twin,” Hemmelgarn said. “However, with Nvidia, we can create this industrial Metaverse jointly taking the manufacturing process and the industrial automation process to a much more realistic level, leveraging AI capabilities.”
Nvidia is no stranger to partnership and actively works with vendors across multiple sectors. Rev Lebaredian, vice president of the Omniverse and simulation technology at Nvidia, commented during the press briefing that he’s particularly excited about the Siemens partnership.
“Siemens excels in the intersection of information technology and operational technology, and that’s something that we don’t do,” Lebaredian said. “There are things that we do, especially in the AI realm, and for real-time, that nobody else can do, and so the combination of these is truly unique.”
Photorealism is the key to bringing digital twins to life
Hemmelgarn noted that the idea of A digital twin is not a new concept, but it has changed in recent years. In his view, what has changed with digital twin technology is the comprehensive nature of the data that the digital twin encompasses and provides.
“The value of the digital twin is how closely your virtual world can represent your physical world,” Hemmelgarn said.
While Siemens had been building its own digital twins, Nvidia’s Omniverse takes the concept to a different level, thanks in no small part to its photorealism for images. For Hemmelgarn, integrating with Nvidia is all about making digital twins more lifelike, with real-time capabilities.
The idea of photorealism in the metaverse, should not be relegated to superficial things like entertainment, according to Lebaredian. He noted that in the modern era of AI, photorealism is critical for serious applications.
“One of the things that’s clear to us is that in order to build and create AI models we need to supply them with data, that’s essentially an encoding of the experience of the world around them,” Lebaredian said. “The only way we’re going to create truly intelligent AI is by first creating data that matches our real-world accurately, and a big part of that is how that world looks.”