The convergence of artificial intelligence, digital twins, and accelerated computing is rapidly reshaping industrial design and production, allowing companies to optimize processes and innovate at an unprecedented pace. This shift, fueled by advancements in platforms like NVIDIA Omniverse and partnerships between tech giants, promises to drastically reduce development cycles and improve sustainability across diverse sectors.
Earlier this month, NVIDIA and Dassault Systèmes announced a strategic partnership designed to accelerate this transformation. The collaboration integrates Dassault Systèmes’ Virtual Twin platforms with NVIDIA’s accelerated computing, AI physics models, and Omniverse libraries. This synergy aims to empower engineers and designers with the tools to create and test virtual prototypes – or “digital twins” – that accurately mimic real-world performance, leading to faster innovation and more efficient product development.
At the heart of this evolution lies the concept of the digital twin – a virtual replica of a physical asset, process, or system. These twins, powered by AI and physics-based modeling, are no longer simply visual representations; they are dynamic simulations capable of predicting outcomes and optimizing performance. The ability to simulate complex scenarios before physical implementation is proving invaluable across industries, from automotive to aerospace and even food science.
Dassault Systèmes’ SIMULIA software is now leveraging NVIDIA CUDA-X and AI physics libraries to enhance the accuracy and speed of virtual twin simulations. This allows designers to instantly predict how a product will behave under various conditions, reducing the require for costly and time-consuming physical prototypes. NVIDIA, in turn, is adopting Dassault Systèmes’ model-based systems engineering technologies to accelerate the design and deployment of large-scale AI factories, further solidifying the link between virtual and physical worlds.
From Cars to Cheese: Real-World Applications of Digital Twins
The impact of these technologies is already being felt across a range of industries. Lucid Motors is utilizing digital twin technology, combined with AI physics models and tools from Dassault Systèmes, to accelerate innovation in electric vehicle design, and engineering. In the life sciences, researchers are employing virtual twins and the NVIDIA BioNeMo platform to expedite the discovery of new molecules, materials, and therapeutic solutions. The Bel Group, known for its Babybel cheese, is leveraging these technologies to develop sustainable and healthier food options, using virtual twins to study and optimize food protein structures.
The Bel Group’s application is particularly noteworthy. By using industry world models from Dassault Systèmes, the company can generate and study food proteins, creating non-dairy alternatives that complement their existing product line. This allows for faster and more efficient research and development, ultimately leading to more sustainable and innovative food products. Similarly, Omron is employing virtual twins and physical AI to enhance the design and deployment of automation technologies, driving advancements in digitally validated production processes.
In the aerospace sector, researchers at Wichita State University’s National Institute for Aviation Research are utilizing virtual twins and AI companions, powered by Dassault Systèmes’ Industry World Models and NVIDIA Nemotron open models, to accelerate the design, testing, and certification of aircraft. This demonstrates the potential of digital twins to streamline complex processes and improve safety in highly regulated industries.
The Power of Physics-Based World Models
A key component driving the advancement of digital twins is the development of physics-based Industry World Models. These models, created by Dassault Systèmes, are trained with extensive knowledge in fields like biology, physics, and material science. This allows them to accurately simulate real-world environments and scenarios, enabling teams to test industrial operations end-to-end, from supply chains to retail shelves, before implementing changes in the physical world. According to Pascal Daloz, CEO of Dassault Systèmes, “Knowledge is encoded in the living world,” and virtual twins allow us to “learn from life and…replicate it and scale it.”
These models aren’t limited to static simulations; they can also be used to analyze complex workflows, such as DNA sequencing and the strengthening of materials used in vehicle manufacturing. The ability to accurately predict and optimize these processes has the potential to revolutionize industries and drive significant improvements in efficiency and sustainability.
Learn More at NVIDIA GTC
Those interested in learning more about industrial AI and digital twins can register for NVIDIA GTC, taking place March 16-19 in San Jose. The conference will feature a keynote address from NVIDIA founder and CEO Jensen Huang on March 16 at 11 a.m. PT, as well as a dedicated industrial AI agenda with hands-on sessions, customer stories, and live demos. Attendees can also explore the world of OpenUSD with a special session focused on physical AI simulation and learn from Florence Hu-Aubigny, executive vice president of R&D at Dassault Systèmes, who will present on the transformative power of virtual twins. A livestream of the developer community will be available on March 18, offering opportunities for direct interaction with NVIDIA engineers.
The integration of industrial AI and digital twins represents a significant leap forward in the way products are designed, manufactured, and optimized. As these technologies continue to evolve, we can expect to see even more innovative applications emerge, driving efficiency, sustainability, and innovation across a wide range of industries. The ongoing development of platforms like NVIDIA Omniverse and the collaborative efforts of companies like NVIDIA and Dassault Systèmes are paving the way for a future where the virtual and physical worlds are seamlessly integrated, unlocking new possibilities for industrial advancement.
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