Dassault Systèmes and NVIDIA Partner to Build Industrial AI Platform Powering Virtual Twins

March 1, 2026

Dassault Systèmes and NVIDIA have announced a long-term strategic partnership to establish a shared industrial architecture for mission-critical artificial intelligence across industries.

Combining Dassault Systèmes’ Virtual Twin technologies with NVIDIA AI infrastructure, open models and accelerated software libraries will establish science-validated industry World Models, and new ways of working through skilled virtual companions on the agentic 3DEXPERIENCE platform, that empower professionals with new expertise.

“We are entering an era where artificial intelligence does not just predict or generate, but understands the real world. When AI is grounded in science, physics and validated industrial knowledge, it becomes a force multiplier for human ingenuity,” said Pascal Daloz, CEO of Dassault Systèmes. “Together with NVIDIA, we are building industry World Models that unite Virtual Twins and accelerated computing to help industry design, simulate and operate complex systems in biology, materials science, engineering and manufacturing with confidence. This partnership establishes a new foundation for industrial AI, one that is trustworthy by design and capable of scaling innovation across the generative economy.”

The new partnership between the two companies will see shared industrial AI architecture combining virtual twins and AI infrastructure deployable at scale. Science-validated world models position industrial AI as a mission-critical system of record, not a point solution. Platform accelerated by NVIDIA, grounded in science by Dassault Systèmes, expands long-term value creation across biology, materials science, engineering and manufacturing through a new way of working: skilled virtual companions. (Image: Dassault Systèmes)

“Physical AI is the next frontier of artificial intelligence, grounded in the laws of the physical world,” said Jensen Huang, founder and CEO of NVIDIA. “Together with Dassault Systèmes, we’re uniting decades of industrial leadership with NVIDIA’s AI and Omniverse platforms to transform how millions of researchers, designers and engineers build the world’s largest industries.”

Dassault Systèmes and NVIDIA Partner to Accelerate Every Industry

Dassault Systèmes, with its OUTSCALE brand, is deploying AI factories as part of its sustainable and sovereign cloud strategy. OUTSCALE AI factories will harness the latest NVIDIA AI infrastructure on three continents, bringing additional capabilities to operate AI models in the 3DEXPERIENCE platform, while guaranteeing data privacy, intellectual property protection and sovereignty of Dassault Systèmes’ customers.

NVIDIA is adopting Dassault Systèmes model-based systems engineering (MBSE) to design AI factories , starting with the NVIDIA Rubin platform and integrating into the NVIDIA Omniverse™ DSX Blueprint for large-scale AI factory deployment.

Aerospace and defense users already make up one of the largest segments of Dassault Systèmes’ virtual twins and other simulation and design platforms. The partnership will allow aerospace and defense users to unlock new levels of design and simulation innovation. (Image: Dassault Systèmes)

This infrastructure will power Dassault Systèmes’ industrial Virtual Twins using NVIDIA open models and libraries, unlocking new opportunities across biology, materials science, engineering and manufacturing:

Advancing Biology and Materials Research: The NVIDIA BioNeMo™platform combined with BIOVIA science-validated world models will accelerate the discovery of new molecules and next-generation materials.
AI-Driven Design and Engineering: SIMULIA AI-based Virtual Twin Physics Behavior leveraging NVIDIA CUDA-X™ libraries and AI physics libraries empowers designers and engineers to accurately and instantly predict outcomes.
Virtual Twins for Every Factory: NVIDIA Omniverse physical AI libraries integrated into the DELMIA Virtual Twin of global production systems enable autonomous, software-defined production systems.
Virtual Companions Supercharge Dassault Systèmes’ Users: The 3DEXPERIENCE agentic platform, combining NVIDIA AI technologies and NVIDIA Nemotron™ open models with Dassault Systèmes’ Industry World Models, powers Virtual Companions to tap into deep industrial context, delivering trusted, actionable intelligence with industrial-scale efficiency.

The partnership elevates the existing collaboration between Dassault Systèmes and NVIDIA to a shared long-term vision for how industrial AI will be built, validated and deployed at scale, through a unique combination of Dassault Systèmes’ Virtual Twin Factories and NVIDIA’s AI technologies for all industries.

Global Leaders Build the Future of Industry With Dassault Systèmes and NVIDIA

“Bel Group is building a sustainable food future through responsible formulation and packaging. Through the NVIDIA-Dassault Systèmes collaboration, we gain the computational power to model and optimize our products at scale-accelerating innovation while delivering on our sustainability commitments,” said Cécile Béliot, CEO of Bel Group.

“To address the growing complexity of modern manufacturing, the industry must move toward fully autonomous and digitally validated production systems,” said Motohiro Yamanishi, President of Industrial Automation at OMRON. “By combining NVIDIA Physical AI frameworks with Dassault Systèmes’ Virtual Twin Factory and OMRON’s automation technologies, manufacturers can move from design to deployment with greater confidence and speed.”

“Lucid’s award-winning engineering and technology continues to set new standards in the automotive industry, and Dassault Systèmes remains a key partner, enabling us to stay at the forefront of vehicle and powertrain engineering,” said Vivek Attaluri, Vice President of Vehicle Engineering at Lucid. “Agility, speed of innovation and rapid iteration are at the core of our work flows, and our exploration of Virtual Twin AI-based physics, powered by NVIDIA’s open-source physics informed AI models, has the potential to help our teams move from concept to production faster than ever before, without sacrificing predictive accuracy. We look forward to continued collaboration and leveraging these new tools to support Lucid’s future innovations.”

“NIAR empowers the next generation of aircraft. From asset digitization through design and manufacturing creation and validation, Virtual Twin technology introduces unparalleled capabilities and efficiency. Dassault Systèmes’ Virtual Companions for engineering, leveraging the 3DEXPERIENCE agentic platform using NVIDIA Nemotron open models and Dassault Systèmes Industry World Models, accelerate the by-design compliant synthesis of aircraft Virtual Twins. Using the platform to align the Virtual Twin to the means of compliance, reduces certification efforts while preserving sovereignty of the information,“ said Shawn Ehrstein, Director, Emerging Technologies and CAD/CAM, National Institute for Aviation Research, Wichita State University.

The partnership was announced at 3DEXPERIENCE World, Dassault Systèmes’ annual event dedicated to the design and engineering communities. You will also find the full video discussion featuring NVIDIA’s Jensen Huang and Dassault Systèmes’ Pascal Daloz.

This article was provided by Dassault Systèmes (Vélizy-Villacoublay, France). For more information, visit here .

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Transcript

00:00:00 Hey, [cheering] thank you so much for the warm welcome and welcome back. Today is a special day but few minutes before right just to do a quick summary of what I discussed with you yesterday. If you remember, we talk about the future, but more importantly, we talk about how we are building it. And the future is not only about

00:00:36 empowerment. It's also about inventing new things, new opening, new possibilities with you and for you. So if we step out for a moment, you know the previous century, the 20th century was really about the industry using and producing objects. In this new century, industry is producing knowledge and knowhow and the

00:01:03 knowledge and knowhow are generating the objects. This is where the true value lies. This is where the power is and that's why we bring together the virtual twins and the 3D universes. 3D universities are not applications. They are knowledge factories. Factories where the knowledge is enriched. The know how it's scale and the result are trusted. And to

00:01:31 supercharge this, we are using AI. Not a generic AI, not a surface level AI, but what we call a real world AI grounded in industry, engineering, and science. So it's not only about large language model. It's about what we call the world models because LLMs do not build satellites. They don't design aircraft. They don't discover cancer therapies. You do and we

00:02:03 help you to certify it. So the war model make in fact the virtual twin truly generative. And to make this possible we combine the power of a virtual twin with the accelerated computing. And to continue these conversations, I'm now very pleased and honored to invite on stage someone who is defining, someone who is shaping the foundation of artificial

00:02:31 intelligence. So, please give a warm welcome to Jason Juan, founder and CEO of Nvidia. [cheering and applause] [laughter] Pascal. Hey everybody. [cheering]
>> Uh,
>> are you call solid workers?
>> Hard workers.

00:02:58
>> Hard workers.
>> So, welcome on stage, Jason. Jason,
>> thank you.
>> It's always a pleasure to have you.
>> I don't know if people realize, but we have a long-standing relationship, right? I think we almost started the collaboration 30 years ago. A quart yeah over a quarter century ago.
>> Do you remember how it started?

00:03:19
>> Well, it was we started during the last computing platform revolution. In fact, um the personal computer re revolution and what used to be uh Unix workstations uh was migrating to Windows-based workstations and the technology that made it possible for us to collaborate was based on OpenGL and we invented a technology called CGFX which is the the precursor of CUDA.

00:03:49 OpenGL became RTX today, fully path trace and physically based and CGFX of course became CUDA and here we are working together again as we reinvent the computing platform. You know everything that we do is in the digital world. 40 years ago revolutionized the idea of virtual twins. The the idea of a virtual twin of course is to represent the physical

00:04:13 world in a computer. And so now we're going to represent the physical world at a much much larger scale in a completely revolutionized computer and AI computer. And so this is a really really fantastic fantastic time.
>> You're right. It's an economable journey. And as you said now we are entering into a new chapter. We are now what we call in the generative economy

00:04:36 where you know we are pouring the virtual twin with accelerated artificial intelligence. From your perspective, Jensen, what is happening in the global industry right now?
>> Well, we're reinventing the computing stack all together. And as you know, in the last generation, uh the representation of the designs

00:04:59 were structured representations, meaning we specified every geometry, we specified every material, we specified literally everything. Now, it's going to be a generative computing model. And in the world of generative generative computing models, the entire computing stack is being reinvented. And because AI is foundational to every single industry, it is going to become an

00:05:23 infrastructure. Just as uh water was infrastructure, electricity is infrastructure, internet was infrastructure, now artificial intelligence will be infrastructure. We're growing so fast because every single industry needs to build it. Every single country will be powered by it. And um literally every society will have it. And so this is the beginning of a

00:05:44 new industrialization which is really fantastic for you because as you know do uh is the engine of the representation of everything that you want to build and in the future in fact you know in the past I would say that we spent a third of our time in design and digital maybe twothirds of the time in physical it is very likely in the future

00:06:11 We're going to spend 100% of the time in digital and even after we're done designing it, simulating it, validating it, we have to integrate it with software. And so everything that's inside the DO systems, whether it's Katilla or Simoleia or Biovilla or let's see what what are the other vas we got? We got
>> Delmia, we got Inovia. And and listen,

00:06:38 all of those VAS are going to be built on top of Nvidia. [laughter] [laughter] Did we know that a quarter century ago? And so so anyhow anyhow the the the design this the representation all the simulation and and even the operations of it because everything will be software defined in the future. you know

00:07:04 everything from a a pair of tennis shoes will be software defined in the future and so cars are software defined. Um the robots that build the cars are software defined. The the factories where the robots you know are orchestrated build the cars are software defined and the cars themselves are software defined. So everything will be software defined. Everything will be represented inside

00:07:23 the so and so we'll be designing everything um operating everything really as a virtual twin and realizing your vision for the first time.
>> Yeah. You know, before we go further, if you look around the crowds, you know, at
>> kind of a ruckus crowd.
>> Yeah. [cheering]

00:07:44 [applause] [cheering]
>> At Daso system, we work with 45 millions people around the world, 400,000 customers, more than 15 millions engineers, researchers. So I think we are you have here probably one of the if not the largest engineering community in the world. They do more than half of the

00:08:09 products surrounding us every day. Robots, you know, drones, planes, cars, medical devices, drugs, uh home, city, factories. So this is an amazing community. Don't you think so? I know they think so. [laughter]
>> Absolutely. Yeah, we're all engineers.
>> You are an engineer.
>> Yeah. Yeah. Sure. I'm still an engineer.

00:08:40
>> So you you belong to this community.
>> I am. If I was to start all over again, I chose to use Solid Works. [laughter]
>> You know, that's why the world model matters. In fact, because for these communities, the success is not about automation. They don't want to automate the past.
>> They want to invent the future. And this

00:09:08 is the reason why we are announcing this new chapter in our partnership because together we are bringing the virtual twin factory with the AI factory. This opportunity is really enormous for you guys and for us. So to prove the power of this right we have some concrete example I think uh Jensen and I we have selected some use cases we want to share with you let's start with

00:09:35 research and engineering first. Yeah. And so, you know, I remember that almost everything that we do together starts with the computing platform. And when when PCs went into the cloud, the so reinvented yourself again. Uh when now we're extending from cloud to AI, we're reinventing again. And so this to today we're announcing a massive partnership. This is this is the the largest

00:10:01 collaboration our two companies have ever had in over a quarter century. Y
>> uh do the so is going to integrate NVIDIA CUDA X acceleration libraries, NVIDIA AI for physical AI and for agentic AI and NVIDIA omniverse our version of digital twin technologies. And so all of these libraries represent the bo our body of work over the quarter of a century. Now we're going to fuse

00:10:28 these technologies into the so so that all of you will have the benefit of accelerated computing artificial intelligence and be able to work at a scale that's a hundred times a thousand times and very soon a million times greater than what you were able to do before. What used to be, you know, pre-rendered or what used to be offline simulations will now be

00:10:55 literally the virtual twin vision that you've always always had along. Everything will be done literally in real time. You know, we'll we'll design design uh products and simulate it in a wind tunnel in real time. uh we'll interconnect these robots and let them operate in a factory in real time and they'll be building your products literally in real

00:11:19 time and all of this is going to be happening and you know in the next 5 10 years this going to be extraordinary speaking about this let's start with life I think life is the most complex uh system ever created right when you think about it how much knowledge is encoded in the living world with our virtual twins. You know, we are learning from life. We are also understanding it

00:11:46 in order to replicate and to scale it. So this is possible.
>> This is NVIDIA AI integrating with Biovilla.
>> Yes,
>> Biova, right?
>> We will come back to this.
>> Yeah.
>> But you know this is possible because I think we have this foundation. We call

00:12:02 it the world model.
>> Yeah. the world model where it's grounded in biologies in physics material sciences. So the key question I have for you is what does it take to compute a world model for life of life? Well the most important thing the first thing that we have to do is understand the language of life.
>> Yeah. And so you know if of course in

00:12:24 the world of of physical design the design started with your imagination and you represented that physical object using structured information geometries and textures that were uh designed by you. However life is different. Life existed before us. And so we have to go learn the language of DNA, learn the language of proteins and learn the language of cells and understand how

00:12:50 they interact and its properties. That first stage of learning the meaning of life is what we are in the process of tackling. The second part of course is generative. Once you could learn something, learn the meaning of something, we can translate it between languages. We can translate between human language and the language of biology between the language of biology

00:13:12 and interpret it so that we can understand it in human language. Beyond that you can now translate and generate gen generate new proteins that could be used for a drug or generate new chemicals that could be used used for a drug and then of course generate new uh materials that could be stronger uh be more heat resistant, lighter, easier to manufacture, last longer. All of those

00:13:36 properties um are now kind of within our grasp and this is one of the reasons why this is likely going to be one of the most impactful areas of engineering in the next decade. Exactly. And it is already happening. In fact, we have a case, you know, the Bell Group, you know them, they do the famous baby bell, right? And their mission is very simple. They want to basically produce healthier

00:14:01 foods for million of consumer. But at the same time they want to consume less water and they want to progressively change or at least complement the dairy protein with the non-dairy proteins. So that's the reason why they are inventing what we call the food science. Before you know hundred of physical test for one single product now they they generate automatically and

00:14:29 this is what you can see on the screen. they generate automatically the protein from the virtual twins because it's against powered by the biological world model. So the result it's not only faster innovations, it's also certified decisions because you cannot play when you are you have the life of the people in your hands. That's what we do. Now

00:14:53 let's move to something else and you started to speak about it. You know you have seen on screen this is changing in fact the daily life of the engineers in the spa. You know now you define the specs you run your simulations and automatically the generative experience is producing and exploring in fact the space of possibilities and finding the optimum solutions for you.

00:15:20 Actually the virtual twin is exploring an infinite of possibilities. So the question I have for you could we compute infinity
>> we can't compute infinity but we can imagine infinity which is the reason why these surrogate and emulation models the fusion of simulation and artificial intelligence is so powerful. Eight years ago I introduced the idea to scientific

00:15:46 computing and simulations. the idea that in the future not only will we use principled simulations where the the [clears throat] equations the laws of physics are well well understood and well represented however the simulation time takes way too long. Why don't we augment that with generative methods of predicting the future using artificial intelligence? It's a little bit like the

00:16:10 analogy I would give. It's a little bit like um are dogs able to catch a ball out of the out of the air and yet they're not doing physics simulations of of balls bouncing or elastic nature of the ball. They're just literally watching us and predicting where it's going to go and they snatch it out of the air. And so the the idea that an AI could learn how to predict physics and

00:16:35 learn how to predict very accurately how materials would crumble, what happens to a crash, those things, those capabilities are within grasp. We have a technology called physics Nemo. Physics Nemo is essentially a physicsaware AI model simulation system and AI framework that allows us to create these AI models that are either trained by principal simulators or work alongside

00:17:01 principal simulators. So it's grounded in the laws of physics but able to predict 10,000 times faster. And now if everything is already running in real time then you can predict it 10,000 times greater scale. And that's just where we are right now. Imagine where we're going to be in the future. Uh the idea of simulation and emulation coming together to help you design is going to

00:17:24 be really revolutionary. And again, this is exactly what you see here with a customer called Lucid. You know, we know them. It's they are one of the most innovative car company in the world. And what do they do? In fact, they embed the crash behavior, the aerodynamics, the vehicle performance upstream early in the vehicle programs developments. So the engineers, they don't only design

00:17:50 the shape, they design the behavior and we certify it. So this is exactly what you say. This is this John vision empowering designer and engineers and also unlocking the business people you know to develop the delightful experience for their customers. Now let's talk about factories. You start to touch a little bit this topic. The factories are not anymore today only

00:18:13 a physical assets. I think we are all in agreement with this. It's made of virtual and real and same times. So let us know how physic AIs is really used to run the factories. Well the way that people used to think about designing products is they design the product and they build the factory. In the future, it's very likely that the products that you are able to design and

00:18:40 build will a lot be impacted by the factories you design and built. And so, it's very likely in the future, well, it will be. It's in fact now that every single factory is designing CAD. That's obvious, but it will be simulated and operated completely inside a virtual twin. And operating a factory of these gigantic scales inside a virtual twin is extraordinarily complex. A factory is

00:19:06 not just one object. It's millions of objects. And we want to also simulate or emulate how these factories will operate in the real world so that we could arrange the manufacturing lines properly, arrange it in the right sequence, um space it properly, organize the robots within it, run the robot AIs so that these ro AI robot robots could be operating inside the factory,

00:19:36 manipulating things, assembling things, moving things, keeping things safe. All of this is going to happen inside a virtual twin. And so, you know, do the the products that do is going to help people build and design are going to become gigantic in the future. These are going to be systems of objects, systems of AI, systems of robots all coming together into a giant factory. This is

00:20:01 exactly
>> they're going to these are fast computers is what I'm saying. [laughter] And again this is exactly what we do with Omron. You know you have seen on the screen they don't use the virtual twin only to visualize the factories. In fact they do much more. They engineer what we call a softwaredefined factory.
>> That's right.

00:20:19
>> And where where is the difference is coming from is in fact they are designing the autonomous part day one. It's not something they come when the production system is already up and running and they try to infuse the autonomous part in it. So as a result those factories they become much more flexible, resilience you know and also adaptative.

00:20:42 But there is another kind of factories right and you you talk a lot about this the AI factories they are building everywhere they are extremely complex. What does it takes to make them or to build them and to make them a reality?
>> Well, we're going through what what uh uh clearly is a new industrial revolution, a fundamental technology that impacts the productivity of many

00:21:12 industries. That's why it's an industrial revolution. Just as energy did that, just as mechanical energy, power did that, just as electricity and of course the internet did all that. um we're now seeing artificial intelligence doing that. In order to make this possible, we need to industrialize and really scale three different giant industries. The first one of course is

00:21:33 building a lot of chips, which is the reason why the number of chip factories are increasing. You're going to be you're involved in a whole bunch of chip factories and so chip factories and packaging factories just to make all these semiconductor products. The second is computer factories. Once the chips are done, it goes into into another factory. What comes out of that is a

00:21:52 supercomputer. Those supercomputers go into an artificial intelligence factories. Right now, as we're speaking, these three entirely what used to be three different industries are all growing incredibly fast so that we could create the infrastructure for intelligence and manufacturing the the AIs. While these factories are incredibly complex, they're you know a

00:22:17 gigawatt AI factory is about $50 billion. And now we're building tens of gigawatts around the world. It's an enormous infrastructure buildout. The largest industrial infrastructure buildout in human history. And so the amount of technology that comes together inside these factories are extraordinary. And we want to make sure that they work the

00:22:36 first time. And so the way we're doing it, we're using MBSC do product mechanical
>> what?
>> Model based design.
>> Modelbased design. So
>> engineering. I wish you would have been something via [laughter] you know

00:22:52
>> not yet not yet
>> okay all right so you know MBVIA that's it [laughter] modelbased via and then and then um uh so so what goes into them what goes into these systems are giant data centers with lots of supercomputers the amount of energy necessary of course a gigawatt largest factories ever and it cost so much money so we design, we plan, we

00:23:18 simulate everything in MBSSE before we build it. And so, uh, our expectation is and we even run the network and run the supercomputers inside the virtual twin before we even break break ground. That allows us to save tons of time and tons of money. And over time, of course, this data center has an AI that keeps it optimal. It's AIS that modulate the

00:23:43 performance, modulate the power, modulate the the temperature, modulate cooling, and in doing so, if you want to do so successfully, you need artificial intelligence. And so that operating loop, so we're going to have these digital these virtual twins of these AI factories running forever, training and updating our models.
>> So again, this is proving that the

00:24:04 virtual twin is not only about 3D,
>> it's as you say, it's about revealing the architecture, the revealing the system underneath and obviously revealing the knowledge at scale.
>> And it looks real
>> and it's real.
>> Yeah, it looks real, right? It looks real. It operates really. It integrates all, you know, industrial bill of

00:24:23 material. And so the bill of material comes in from manufacturers and suppliers. We integrate everything really physically. And so we have a very clear list of bill of material. We know exactly what we're going to buy. We know which part is going to integrate with another. Uh we could see in advance whether something fits or doesn't fit. we know exactly how many parts. So the

00:24:43 inventory bill of material of this supercomputer comes out. This AI factory comes out adds up to about $50 billion bill of material. And so um this is incredible and we have everything digitally and so you know no mistakes will be made.
>> Now I'm counting on you to sell it to your ecosystem, right?
>> Yeah. Absolutely. Well, you're we're the

00:25:02 first customer.
>> You are?
>> Yeah, we're the first customer.
>> You're the first customer.
>> [applause]
>> Now the the next topic I want to discuss with you is really how do we put the knowledge at work. So this is exactly what our virtual companion they do. We

00:25:21 made a live demo yesterday just to showcase what is coming and you know engineers they spend too much time to look for informations or to do something else. This is not engineering. So now look at it. in few seconds you know you we started from a sketch we produce automatically the we moved from 2D to 3D it's a full parametric model simulation already I

00:25:48 think this is really revolutioning everything uh people are doing and it's changing completely the workflows now there is a question in this room and the question is this one do you think this will replace the engineers
>> well before I answer that the the um one of the one of the really revolutionary things that has made possible for us because of AI is the ability to go from

00:26:15 an interchange between structured information and unstructured information. Unstructured information is essentially a photograph or may it could be a recording could be a video and we want to take that unstructured information and now represent it in a structured way. We need artificial intelligence to go from 2D to 3D image to to to 3D. And and once you have it in

00:26:37 3D, that information is precise. It's controllable. It's interchangeable, right? We can enhance it. We could improve it. And so it is com it's now in our structured database. We can go from structured to unstructured obviously very easily. And so now we have the representation, the ability to use agents and use AI to manage our information so that we can augment um

00:27:02 the design process. We could decide that this part I'm going to design specifically by hand here. I'm going to take an image. I'm going to import it and then I'm going to modify it. So on so forth. Now these agents these agents are going to be companions of ours because they're they're going to we're going to essentially be their manager, their architect.

00:27:22 We're going to be the manager, the architect, the design, the the, you know, the creator, and we're going to have a lot of agents or companions help us perform different tasks. Whereas most people think that that the number of designers therefore will be less than the past and and uh the the number of software tools that you will use will be less than the past is exactly the

00:27:46 opposite. It is very likely and and and I'm I'm certain this is going to happen that every designer, every Solid Works designer, every designer in the future will have a team of companions and you've trained these companions and you've taught them different skills and you've helped them coordinate and work with each other and work with you and they're all going to be using DO tools.

00:28:10 So the number of users of the soul tools is going to go from biological to biological as well as AI based. And so the number of tool use will ex will explode. And so this is um the software industry of course is going to be great for the software industry. It's going to be great for all the designers because you have so many companions to help you do things. And what what would be really

00:28:32 fantastic is that you're you're working with your companions and then you know it's time to it's time for cocktail and [laughter] and um because it's solidly 4:30 somewhere and and and so you kick off your team to go explore all these different areas and you know I want you to explore this, I want you to explore that, I want you to optimize for these areas and give me three designs. I want

00:28:55 to optimize for these years. Give me 10 designs. And when you come back, you have all those choices and then you can go in and fine-tune it specifically yourself because you have the structure data, the 3D data. And so I think the the uh the opportunities to reinvent how you think about design and creativity is going to be completely revolutionary for everybody.

00:29:16 That's also something uh we can showcase. In fact, you take NAR. NAR is a national institute for the aviation industry. They are based in Wittita and they focus on research testing but also certifying and we know that certifying an airplane you know it's a nightmare. It take between three to five years it's more than 10,000 requirement you need to be fulfilled. Now I think with the

00:29:41 virtual companions what could we do? The recolleations could be automatically ingested right without having to read millions of pages and the conformity is constantly verified which means now we are moving from if you want um it's by design it's a compliance by design right and there is no and it's not anymore a cost it could become a competitive edge in fact so the question I have for you

00:30:07 is how does it take to move from a language model to a world on.
>> Well, the language model has to um uh obviously understand syntax and vocabulary and structure of language and and has taste. You know, what's a what's a better way to compose a paragraph and it has guard rails. What are the things it should talk about and things that it should avoid talking about? Um in the

00:30:30 world of in the world model instead of taste and values, it has to obey the laws of physics. It has to understand causality that if if you tip over a domino, you know, all of the dominoes that are connected to it or nearby it will be tipped over. It has to understand what comes what comes after and what comes before. It understand inertia and friction, understands

00:30:53 gravity, of course. It understands um uh uh contact, you know, all of the things that that you understand as you're designing things. We have to teach the AI that sensibility. that's not necessarily captured in language and all the language in the world won't capture that and so we have to use laws of physics and simulation and a whole bunch of examples to teach

00:31:17 it the laws of physics and then of course one of the things that you you mentioned uh design for manufacturability today is integrated into the design process instead of you coming up with the design and then another team decides whether it's manufacturable design for manufacturability is really upstreamed shift it left. We want to shift left

00:31:40 basically everything. And so one of the things that are very hard as you mentioned compliance is hard because that's where machines meets society and humans. And so that language model where human values could be now integrated into or shifted left into the design process. And so you're constantly in compliance. You're constantly obeying the laws of physics because of the world

00:32:05 model. You're constantly designing for manufacturability. You're constantly designing to use components that are approved with, you know, vendor approval list and whatever it is so that by the time that you're done with the design, it's good to go. Yeah. Now, I hope you have a better idea about what this partnership is about. I think together with Nvidia, we are delivering the

00:32:30 knowledge factory. and to power the virtual twins with our virtual companions with an accelerated AI computing. This is more than performance. I think it's as you say it's an acceleration but more importantly this is opening the new possibilities. Whatever the size of the company, whatever the industry you are in, I

00:32:53 think we help you to certify your decision. We help you to eliminate the bad choices before they become expensive mistake. And we also help you to create new categories of solution. You call it the softwaredefed products, the softwaredefined factories, the softwaredefined objects at large. And more importantly, we need to protect your knowledge as well, right? So how do

00:33:18 you how do you think we can protect the knowledge of all the million of people using our software? Well, first of all, before I go there, I think that that um our partnership today and what we're announcing is ex is really genuinely extraordinary. Um the the type of things that that you will be building in the future are simply impossible without accelerated

00:33:42 computing. It's impossible without real-time simulation. It's impossible with art artificial intelligence. Instead of thinking about what could be more productive, yes, productivity is going to be enhanced and and you'll be you'll be a lot more productive and you'll be able to do things more quickly than than the past just as PCs did that for us, just as the cloud did that for

00:34:02 us, just as internet has done that for us. Every technology revolution had made us more profit, more pro more productive. However, this time the type of things that you'll be able to do when you think about the scale a 100 times, a thousand times, a million times, these are going to be things that are just simply impossible to do before. Now the our our partnership started with

00:34:24 computer graphics and our computer graphics as you've seen uh become fully ray traced and physically based and it looks completely photorealistic and it's real time and and so the foundation of our partnership has always been RTX and computer graphics but we've now extended it to CUDA X we've extended it to AI and we've extended it to Omniverse. All of these computing platforms sitting on top

00:34:48 of accelerated computing and vidious GPUs are going to revolutionize the tools and revolutionize therefore how you design and what you can design and ultimately how your companies operate. And so I think that that's that's number one. The the other part that's extraordinary of course is that in the future almost everything that we we do will have AI in the loop. You

00:35:15 know, when people think about about AI, they have humans in the loop. And that's important. But remember, you also now have your companion, your AI in the loop. That AI is going to remember how you'd like to do your preferences. And that AI therefore will codify your skills, codify your preferences, codify your habits, codify the domain expertise that you

00:35:42 have. And that is your companion. And that companion sits with you. It's not going to be in the cloud, not going to be public because it captures your expertise. You know, if you look at my inbox, in a lot of ways, that's captured 33 years of my knowledge of my expertise. It's not available for everybody. It's not open sourced, of course, and it's it captures a lot of my

00:36:05 sensibility, a lot my knowledge. In the future, I will have companions that are going to continue to work with me. I wish I had it 33 years ago to be honest and and now all of you will have companions that codifies your knowledge, codifies your sensibility. Last word about why do you think this partnership is unique? You already say a few words but you are also partnering

00:36:28 with other companies especially in our space. Why do you think what we are doing together is something unique? Well, the so your your place in the world of virtual twins, your vision that started it all. Katillaa will always be Katilla. Solid works will always be solid works. Simoleia will always be Simoleia. You know, all the other EAS will always be, you know, and and you'll

00:36:55 come up with other other EAS and they'll all be built on top of Nvidia. That's the part that I like the best. But [laughter] but the the ecosystem the ecosystem that you serve, the ecosystem and all of you here that are so passionate about the the so products um and and all of your companies that are built on top of the so products are now going to be

00:37:19 accelerated and amplified by accelerated computing and AI. And that's really what's really exciting here. And it happened at at precisely the time when the world is reindustrializing
>> reinventing
>> starting the largest industrial infrastructure buildout in human history. Trillions of dollars, tens of trillions of dollars. You know,

00:37:44 estimates have it close to a hundred trillion 85 trillion dollars in the next 10 years. All of that needs to be designed, simulated, validated, right? prototyped and and and of course because everything has is going to be softwaredefined and everything will be AIdriven all of that needs to have virtual twins and so I think that the the uh the

00:38:09 vision that do so had 40 years ago
>> is coming true.
>> It's coming true.
>> Yeah. And it's coming true right now. Um and this partnership brings it to life. And so I'm delighted to be to be uh uh partnering with you Pascal and and uh you know our quarter of a century partnership means a lot to me. I you know it really Katillaa brought us

00:38:35 brought Nvidia into the industrial workstation world and today we still Katillaa and Solid Works are you know to us uh very very personal and really important to all of us and without all of you and the amazing work that you do uh many of the things that our our you know engineering and scientists uh pursue uh wouldn't have an opportunity to come to life and so I want to thank

00:39:01 all of you for for uh all the incredible things that you do and Pascal for the great partnership and all of my friends at the Thank you for everything. [cheering] [applause] [applause]
>> Thank you.
>> Thank you.
>> Now you you belong to this community.

00:39:24
>> Oh, so make sure
>> I am definitely a solid worker. [laughter] Make sure you come back. And if you're not coming back, send your virtual twin.
>> No, I'm coming back. My virtual twin gets to stay home and work.
>> All right. Take care, guys.
>> Take care, guys. [applause]
>> A unique partnership combining DASO

00:39:48 systems virtual twin factory and NVIDIA's AI factory for all industries. Where scientific and industrial knowledge and knowhow meet global scale computing technologies to form a shared industrial architecture. Model, simulate, reveal, validate with the precision, trust, speed, and context to turn scientific results into industrial decisions.

00:40:18 Molecular and protein simulations accelerated 200 times. Expanded engineering possibilities with real-time simulation for every designer. Agile and rapid adaptation of industrial processes through seamless integration and training of autonomous robots in the virtual twin of production systems. Test manufacturing scenarios and

00:40:43 validate them instantly. Deploy them within days in the real world. A new infrastructure emerges. The AI factory, a system that produces intelligence understood, controlled, and optimized through its own virtual twin. Driving a new workplace revolution through an agentic platform of skilled virtual companions to enable

00:41:12 strategic human machine collaboration at every stage of work. Together, we are making world models for industry a reality. Where virtual twins and accelerated computing work as one. Trusted decisions grounded in science at scale. This is the future of industrial AI.

Dassault Systèmes and NVIDIA Partner to Build Industrial AI Platform Powering Virtual Twins

Dassault Systèmes and NVIDIA Partner to Accelerate Every Industry

Global Leaders Build the Future of Industry With Dassault Systèmes and NVIDIA

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