Hey everybody. Are you called SolidW orkers?
Hard workers.
Hard workers. Welcome on stage, Jensen.
Thank you.
It's always a pleasure to have you. I don't know if people realize, but we have a longstanding relationship, right? I think we almost started the collaboration 30 years ago.
Yeah, over a quarter century ago.
You remember how it started?
Well, it was we started during the last computing platform revolution, in fact, the personal computer revolution. What used to be Unix workstations was migrating to Windows-based workstations. The technology that made it possible for us to collaborate was based on OpenGL, and we invented a technology called CgFX, which is the precursor of CUDA. OpenGL became RTX today, fully path traced and physically based, and CgFX, of course, became CUDA. Here we are working together again as we reinvent the computing platform. Everything that we do is in the digital world. 40 years ago, the SO revolutionized the idea of virtual twins. The idea of a virtual twin, of course, is to represent the physical world in a computer. Now we're going to represent the physical world at a much, much larger scale in a completely revolutionized computer, an AI computer. This is a really, really fantastic time.
You're right. It's an incredible journey. As you say, now we are entering into a new chapter. We are now what we call in the generative economy, where we are powering 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 altogether. As you know, in the last generation, the representation of the designs 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. In the world of generative computing models, the entire computing stack is being reinvented. Because AI is foundational to every single industry, it is going to become an infrastructure. Just as 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 literally every society will have it.
So this is the beginning of a new industrialization, which is really fantastic for you because, as you know, the SO is the engine of the representation of everything that you want to build. In the future, in fact, in the past, I would say that we spent a third of our time in design, in digital, maybe two-thirds of the time in physical. It is very likely in the future we're going to spend 100% of the time in digital. Even after we're done designing it, simulating it, validating it, we have to integrate it with software. So everything that's inside the SO systems, whether it's CATIA or SIMULIA or BIOVIA or let's see, what are the other Vias? We got DELMIA.
DELMIA.
DELMIA. [crosstalk] We got ENOVIA. And listen, all of those Vias are going to be built on top of NVIDIA. Did we know that a quarter century ago? And so anyhow, the design, the representation, all the simulation, and even the operations of it, because everything will be software-defined in the future. Everything from a pair of tennis shoes will be software-defined in the future. And so cars are software-defined. The robots that build the cars are software-defined. The factories where the robots 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 the SO. And so we'll be designing everything, operating everything really as a Virtual Twin and realizing your vision for the first time.
Before we go further, if you look around the crowds, you know at Dassault Systèmes.
Kind of a ruckus crowd.
Yeah. At Dassault Systèmes, we work with 45 million people around the world, 400,000 customers, more than 15 million engineers, researchers. So I think you have here probably one of the, if not the largest, engineering community in the world. They do more than half of the products surrounding us every day: robots, drones, planes, cars, medical devices, drugs, homes, cities, factories. So this is an amazing community. Don't you think so?
I know they think so. Absolutely. Yeah, we're all engineers.
You are an engineer.
Yeah, yeah, sure. I'm still an engineer.
You belong to this community.
I am. If I would start all over again, I chose to use SOLIDWORKS.
That's why the world model matters, in fact, because for this community, the success is not about automation. They don't want to automate the past. They want to invent the future. And this 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, we have some concrete examples. I think Jensen and I, we have selected some use cases we want to share with you. Let's start with research and engineering first.
Yeah. And so remember that almost everything that we did together starts with the computing platform. And when PCs went into the cloud, the SO reinvented itself again. And now we're extending from cloud to AI, we're reinventing again. And so today we're announcing a massive partnership. This is the largest collaboration our two companies have ever had in over a quarter century. 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 our body of work over the quarter of a century.
Now we're going to fuse these technologies into the SO so that all of you will have to benefit of accelerated computing, artificial intelligence, and be able to work at a scale that's 100 times, 1,000 times, and very soon a million times greater than what you were able to do before. What used to be pre-rendered or what used to be offline simulations will now be literally the virtual twin vision that you've always had along. Everything will be done literally in real time. We'll design products and simulate it in a wind tunnel in real time. We'll connect these robots and let them operate in a factory in real time, and they'll be building your products literally in real time. All of this is going to be happening in the next five, 10 years. This is going to be extraordinary.
Speaking about this, let's start with life. I think life is the most complex system ever created. When you think about it, how much knowledge is encoded in the living world? With our virtual twins, we are learning from life. We are also understanding it in order to replicate and to scale it. So this is possible.
This is NVIDIA AI integrating with BIOVIA.
Yes.
BIOVIA.
We will come back to this.
Yeah.
But this is possible because I think we have this foundation. We call it the World Model. The World Model where it 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. And so, of course, in the world of physical design, the design started with your imagination, and you represented that physical object using structured information, geometries, and textures that were 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 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, and interpret it so that we can understand it in human language. Beyond that, you can now translate and generate new proteins that could be used for a drug or generate new chemicals that could be used for a drug. And then, of course, generate new materials that could be stronger, be more heat resistant, lighter, easier to manufacture, last longer. All of those properties 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. It is already happening. In fact, we have a case, the Bel Group. You know them. They do the famous Babybel. Their mission is very simple. They want to basically produce healthier foods for millions of consumers. 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 reinventing what we call the food science. Before, hundreds of physical tests for one single product. Now they generate automatically, and this is what you can see on the screen, they generate automatically the protein from the virtual twins because it's, again, 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 have the life of the people in your hands. That's what we do. Now let's move to something else. You started to speak about it. You have seen on screen, this is changing, in fact, the daily life of the engineers. In the space, 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. 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. years ago, I introduced the idea to scientific computing and simulations, the idea that in the future, not only will we use principled simulations where the equations, the laws of physics are 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 analogy I would give. It's a little bit like our dogs able to catch a ball out of the air. And yet they're not doing physics simulations 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 idea that an AI could learn how to predict physics and learn how to predict very accurately how materials would crumble, what happens to a crash, those capabilities are within grasp. We have a technology called PhysicsNeMo. PhysicsNeMo is essentially a physics-aware AI model simulation system and AI framework that allows us to create these AI models that are either trained by principled simulators or work alongside principled 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 at 10,000 times greater scale. And that's just where we are right now. Imagine where we're going to be in the future.
The idea of simulation and emulation coming together to help you design is going to be really revolutionary.
Again, this is exactly what you see here with a customer called Lucid. We know them. They are one of the most innovative car companies 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 program's development. So the engineers, they don't only design the shape, they design the behavior, and we certify it. So this is exactly what you say. This is this joint vision, appointing designers and engineers and also unlocking the business people 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 a physical asset. I think we are all in agreement with this. It's made of virtual and real at the same time.
Let us know how physical AI 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 build will a lot be impacted by the factories you design and build. 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 not just one object. It's millions of objects.
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, space it properly, organize the robots within it, run the robot AIs so that these AI robots could be operating inside the factory, manipulating things, assembling things, moving things, keeping things safe. All of this is going to happen inside a virtual twin. So the products that the SO 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 exactly.
You're going to need some fast computers, is what I'm saying.
And again, this is exactly what we do with OMRON. 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 software-defined factory.
That's right.
Where 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, resilient, and also adaptive. But there is another kind of factories. You spoke a lot about this, the AI factories. They are building everywhere. They are extremely complex. What does it take to make them or to build them and to make them a reality?
Well, we're going through what clearly is a new industrial revolution, a fundamental technology that impacts the productivity of many 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. 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 building a lot of chips, which is the reason why the number of chip factories is 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 another factory. What comes out of that is a supercomputer.
Those supercomputers go into 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 AIs. While these factories are incredibly complex, a gigawatt AI factory is about $50 billion. Now we're building tens of gigawatts around the world. It's an enormous infrastructure buildout, the largest industrial infrastructure buildout in human history. So the amount of technology that comes together inside these factories is extraordinary. We want to make sure that they work the first time. So the way we're doing it, we're using MBSE, the SO product, mechanical.
What? Model-based design.
Model-based design.
Engineering.
I wish it would have been something VIA.
Not yet. Not yet.
Okay. All right. So BIOVIA, that's it. Model-based VIA. And then 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, 1 gigawatt, largest factories ever, and it costs so much money. So we design, we plan, we simulate everything in MBSE before we build it. And so our expectation is, and we even run the network and run the supercomputers inside the virtual twin before we even 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 performance, modulate the power, modulate 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 Virtual Twin is not only about 3D. It's, as you say, it's about revealing the architecture, revealing the system underneath, and obviously revealing the knowledge at scale.
It looks real.
It's real.
Yeah, it looks real, right? It looks real. It operates really. It integrates all industrial bill of 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. We could see in advance where there's something that fits or doesn't fit. We know exactly how many parts. So the 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 this is incredible. And we have everything digitally. And so no mistakes will be made.
Now I'm counting on you to sell it to your ecosystem, right?
Yeah, absolutely. Well, we're the first customer.
You are?
Yeah, we're the first customer.
You are the first customer. Now, 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 companions do. We made a live demo yesterday just to showcase what is coming. And you know engineers, they spend too much time to look for information or to do something else. This is not engineering. So now look at it. In a few seconds, you started from a sketch. We produce automatically, we moved from 2D to 3D. It's a full parametric model, simulation ready. I think this is really revolutionizing everything people are doing, and it's changing completely the workflows. Now, there are questions in this room. The question is this one. Do you think this will replace the engineers?
Well, before I answer that, one of the really revolutionary things that has made possible for us because of AI is the ability to go from an interchange between structured information and unstructured information. Unstructured information is essentially a photograph, or it could be a recording, it 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 3D. And once you have it in 3D, that information is precise, it's controllable, it's interchangeable. We can enhance it, we could improve it. And so 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 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 and so forth. Now, these agents, these agents are going to be companions of ours because they're going to; we're going to essentially be their manager, their architect. We're going to be the manager, the architect, the creator. And we're going to have a lot of agents or companions help us perform different tasks. Whereas most people think that the number of designers, therefore, will be less than the past. And the number of software tools that you will use will be less than the past is exactly the opposite.
It is very likely, and I'm certain this is going to happen, that every designer, every SOLIDWORKS 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 the SO tools. So the number of users of the SO tools is going to go from biological to biological as well as AI-based. And so the number of tool use will explode. And so this is the software industry, of course, is going to be great for the software industry, is going to be great for all the designers because you have so many companions to help you do things.
What would be really fantastic is that you're working with your companions, and then it's time for cocktail. Because it's solidly 4:30 P.M. somewhere, and so you kick off your team to go explore all these different areas. 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 to optimize for these areas, give me 10 designs. When you come back, you have all those choices. Then you can go in and fine-tune it specifically yourself because you have the structured data, the 3D data. So I think the opportunities to reinvent how you think about design and creativity, it's going to be completely revolutionary for everybody.
That's also something we can showcase. In fact, you take NIAR. NIAR is the National Institute for Aviation Research. They're based in Wichita. They focus on research, testing, but also certifying. We know that certifying an airplane, it's a nightmare. It takes between 3-5 years. It's more than 10,000 requirements you need to be fulfilled. Now, I think with the virtual companions, what could we do? The regulations could be automatically ingested without having to read millions of pages. The conformity is constantly verified, which means now we are moving from, if you want, it's by design, it's a compliance by design. 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 is, how does it take to move from a language model to a world model?
Well, the language model has to obviously understand syntax and vocabulary and structure of language and has taste. What's a better way to compose a paragraph? And it has guardrails. What are the things it should talk about and things that it should avoid talking about? In the world model, instead of taste and values, it has to obey the laws of physics. It has to understand causality, that if you tip over a domino, all of the dominos that are connected to it or nearby it will be tipped over. It has to understand what comes after and what comes before and understand inertia and friction, understands gravity, of course. It understands contact. All of the things 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.
We have to use laws of physics and simulation and a whole bunch of examples to teach it the laws of physics. Then, of course, one of the things that you mentioned, 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 upstream, shift it left. We want to shift left basically everything. One of the things that are very hard, as you mentioned, compliance is hard because that's where machines meet society and humans. That language model where human values could be now integrated into or shifted left into the design process. You're constantly in compliance. You're constantly obeying the laws of physics because of the world model. You're constantly designed for manufacturability.
You're constantly designing to use components that are approved with vendor approval list and whatever it is so that by the time that you're done with the design, it's good to go.
Now, I hope you have a better idea about what this partnership is about. I think together with NVIDIA, we are delivering the 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 think we help you to certify your decision. We help you to eliminate the bad choices before they become expensive mistakes. And we also help you to create new categories of solutions. You call it the software-defined products, the software-defined factories, the software-defined objects at large. And more importantly, we need to protect your knowledge as well. So how do you do this?
How do you think we can protect the knowledge of all the millions of people using our software?
Well, first of all, before I go there, I think that our partnership today and what we're announcing is really genuinely extraordinary. The type of things that you will be building in the future are simply impossible without accelerated computing. It's impossible without real-time simulation. It's impossible without artificial intelligence. Instead of thinking about what could be more productive, yes, productivity is going to be enhanced and you'll be a lot more productive and you'll be able to do things more quickly than the past. Just as PCs did that for us, just as the cloud did that for us, just as the internet has done that for us, every technology revolution had made us more productive.
However, this time, the type of things that you'll be able to do when you think about the scale, 100 times, 1,000 times, 1,000,000 times, these are going to be things that are just simply impossible to do before. Now, our partnership started with computer graphics. Our computer graphics, as you've seen, become fully ray traced and physically based and it looks completely photorealistic and it's real-time. 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 of accelerated computing and NVIDIA's GPUs are going to revolutionize the tools and revolutionize, therefore, how you design and what you can design and ultimately how your companies operate. So I think that that's number one.
The other part that's extraordinary, of course, is that in the future, almost everything that we do will have AI in the loop. When people think about AI, they have humans in the loop. That's important. 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. That AI, therefore, will codify your skills, codify your preferences, codify your habits, codify the domain expertise that you have. That is your companion. That companion sits with you. It's not going to be in the cloud, not going to be public because it captures your expertise. 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.
It captures a lot of my sensibility and a lot of 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 now all of you will have companions that codify your knowledge, codify your sensibility.
Last word about why do you think this partnership is unique? You already said a few words, but you are also partnering with other companies, especially in our space. Why do you think what we are doing together is something unique?
Well, the SO, your place in the world of virtual twins, your vision that started it all, CATIA will always be CATIA. SOLIDWORKS will always be SOLIDWORKS. SIMULIA will always be SIMULIA. All the other IAs will always be, and you'll come up with other IAs. And they'll all be built on top of NVIDIA. That's the part that I like the best. But the ecosystem, the ecosystem that you serve, the ecosystem, and all of you here that are so passionate about the SO products, and all of your companies that are built on top of the SO products are now going to be accelerated and amplified by accelerated computing and AI. And that's really what's really exciting here. And it happened at precisely the time when the world is reindustrializing, starting the largest industrial infrastructure buildout in human history, $ trillions, tens of $ trillions.
Estimates have it close to $100 trillion, $85 trillion in the next 10 years. All of that needs to be designed, simulated, validated, prototyped. And of course, because everything is going to be software-defined and everything will be AI-driven, all of that needs to have virtual twins. And so I think the vision that the SO had 40 years ago is coming true.
It's coming true.
Yeah. And it's coming true right now. And this partnership brings it to life. And so I'm delighted to be partnering with you, Pascal. And our quarter of a century partnership means a lot to me. CATIA brought us, brought NVIDIA into the industrial workstation world. And today, we still, CATIA and SOLIDWORKS are to us very, very personal and really important to all of us. And without all of you and the amazing work that you do, many of the things that our engineering and scientists pursue wouldn't have an opportunity to come to life. And so I want to thank all of you for all the incredible things that you do and Pascal for the great partnership and all of my friends at the SO. Thank you for everything. Thank you.
Thank you again, Jensen. Now, you belong to this community.
Oh, wow. Yeah.
Make sure.
I am definitely a SolidW orker.
Make sure you come back. If you are not coming back, send your virtual twin.
No, I'm coming back. My Virtual Twin gets to stay home and work. Take care, guys.
Take care, guys.