Nvidia Corp GTC Berlin 2026 Keynote

Welcome to GTC. It is great to be here. Before we start, let us give it up for our pre-game show hosts. Smart and adorable. They spoke about AI infrastructure, sovereign AI safety, and physical AI. They covered an enormous amount of ground this morning, and we are going to take it one step further. It is really interesting. What do L'Oréal, Revolut, Spotify, Merck, Vodafone, Zara, Porsche, Nestlé, and HSBC have in common? They are all European companies and they are all working with NVIDIA on AI. Everybody here is all activated on the AI ecosystem and working towards the AI economy. We have been working here in Europe now for 33 years. You probably do not realize that NV1, NVIDIA's first chip, NV2 and NV3, which became RIVA 128, the chip that saved our company, really, and launched our company, were all built in Europe. Our first partner was SGS-Thomson.

We manufactured a chip in Crolles, France, assembled it in Malta and shipped it around the world. Our first largest customer, the largest customer of GeForce days in the beginning, was a company called MediaMarkt. Do you know them? MediaMarkt had a spectacular idea about building PCs, as you remember, and they were our largest customer. It was ELSA, a German company, that brought NVIDIA into the workstation industry in the year 2000. NVIDIA is in every single workstation all over Europe, designing cars. Everything from styling, design, engineering, simulation, all the way through to even inside the car, which a European company brought us into, Audi, in the year 2005. Then in year 2020, we started working on autonomous vehicles with Mercedes. As you could see, NVIDIA's life journey, the entire 33 years, I have spent a lot of time in Germany.

I am delighted to be back. Thank you. I am delighted to do GTC here. This last year, we started the new journey to building a new industry here in Europe, the beginnings of the AI economy. In the last year alone, we have invested nearly $10 billion in Europe across startups, big partnerships, small partnerships, all over Europe. This last week alone, as I journeyed from France and U.K. to Sweden, and now here in Berlin, we announced the investments of 14 startup companies. Overall, since the beginning, we now have 12,000 plus partnerships across Europe, and we are all working towards one goal now. After decades of advancement in the computer industry, we are now at the beginnings of a new industrial revolution. This image was generated by a computer. It was prompted by me. Nice, simple prompt about AI powering a new industrial revolution generated this.

I gave it a few partners that I wanted to highlight, companies that we are working with, and this is an extraordinary thing. In the mind of the AI, this is what it means to build a new industry, generation of tokens, the production of intelligence, which integrates into every single industry powering a new industrial revolution. A new industrial revolution happens when the new technology affects how we build something and what we can build. How we build something and what we can build. I think in every single way, artificial intelligence will affect everything we build and, in fact, enable us to build new things. In this way, because everyone will use it, every company will be powered by it, because it is digital intelligence, the foundation of everything.

Every single person will use it, every company will be powered by it, every industry will be transformed, and new ones will be created. In this way, like the electricity, it is a new industrial revolution, and we are at the very beginnings of that. The question is, what is AI? This is a big deal. If you want to be part of creating this future, understanding what is AI is vitally important. This is really a simple framework. We were early to observe that, in fact, AI is a manufacturing industry. AI is not just software technology. It is software technology, but not just. AI, of course, runs on a computer, but the way that the computer operates is fundamentally different.

Rather than a tool that is used by us, it is now part of a machinery. An infrastructure, factories that are producing intelligence that are integrated into every single industry and application. A simple model is to think of AI as a five-layer cake. Energy powers advanced computers that are part of an AI factory that generates tokens, digital intelligence from the models that run on it, that are integrated into every application. A five-layer cake. To be part of this AI economy, you do not want to just be consuming the AI, you want to be producing the AI. We could do all of that here in Europe, and in fact, we have already started. Europe is building its AI economy and its five-layer cake represented here.

We have great partnerships, and when you look across this five-layer cake, you can recognize that in fact it is a new industry because there is growth at every single layer. We are creating jobs, creating growth at extraordinary rate. Companies here in Europe, Schneider Electric, Siemens Energy, doing incredibly well around the world. We are the computing layer. We integrate into AI factories that are now flourishing all over Europe. Startup companies like Nebius is doing incredibly well. A new company called Firebird, which is setting up a new cloud in the Central Asia region. Even Cassava in Africa. Every single telco in the future, and I predict this, every single telco in the future, with 100,000 sites representing some 100 gigawatts of distributed telco base stations and data centers, will in the future evolve into a distributed AI network. So the AI infrastructure layer is being built out.

Which is then above that, the AI models. It is really important to recognize that long before the AI models emerge, the infrastructure has to exist. Just as before you can have an internet, you have to have the networking. Just as before you could really enjoy the capabilities of electricity, you have to have electrified houses, electrified power plants. So the models are the next layer. It is also interesting to observe that the model layer is not just language models. It represents language, biology, chemicals, physics, robotic actions, animation, and it represents models of all sizes. These different industries are going to be powered by different modalities of AI models, which then integrate into the AI natives, the startups. There are so many here in Europe. So Europe's AI economy is starting and it is really accelerating. It is great to see.

At the foundation of it, where we contribute, most people think is GPUs. It is true. We started in 1993 building a graphics chip which emerged into the GPU, the programmable shading GPU. Over time, we added CUDA acceleration to that, reinvented computing as we know it, which then brought forth artificial intelligence. NVIDIA today is really a full stack, end-to-end, complete AI factory platform. The breadth of the technology of our company over the years has really expanded. Everything from GPU computing, Vera Rubin is our latest generation, to the NVLink switches that connect them into one giant GPU. The Vera BlueField-4 compute that we recently introduced, and I will say a few words about that later, to Spectrum-X, which is our Ethernet solution, making NVIDIA the largest networking company in the world today, to Groq 3, a decode accelerator for token generation.

To Vera BlueField-4 storage acceleration, which I will say a few words in that in just a second, and Vera RTX compute, and I will mention that in just a second. This now represents the breadth of technology necessary to create the AI factory. Nothing works unless you have software that activates it all. The first part is the system software that runs the AI factory. These systems are gigantic. A 1 gigawatt data center, 1 gigawatt AI factory costs about $50 billion. Land, power, shell, all of the compute networking storage, power cooling all connected together. Multiple acres of AI factory. Just turning it on and operating is a marvel in itself. The magnificent amount of software necessary to energize this factory, to put it to use and produce tokens is an extraordinary feat. NVIDIA offers the entire full stack software.

On top of that are what we call the CUDA-X libraries, the algorithms of our company. What NVIDIA truly is an algorithm company that designs silicon to accelerate them. Of course, one of them is cuDNN, what many researchers recognize as the library that brought forth, that started the big bang of modern AI, cuDNN. cuDNN is to AI what SQL is to the world's database industry. It is a domain-specific language, a domain-specific library. Just as OpenGL and DirectX enabled real-time computer graphics, cuDNN enabled the AI computing industry. 350 other libraries. Those libraries are, in fact, the crown jewels of our company. Everything from computational lithography to signal processing, image processing, data processing, particles, fluids, sparse solvers. Incredible breadth of libraries that many of you in the audience have connected into your company. This is how we open new markets.

This is how we connect NVIDIA into algorithms that enable you to do computation at incredible speeds. Finally, on the right-hand side, on that side, the models. This is the new software, the new engine of new applications. It sits on top of and it collaborates with the CUDA-X libraries. These models NVIDIA had been working on across multiple domains. With these models, it opens up new opportunities, and I have lots to say about that later on. Every single generation, NVIDIA started with Pascal. The AI era started with the Pascal new, what is called DGX-1 system. DGX-1 brought to the world the world's first AI supercomputer. I introduced it 10 years ago. Delivered the first one to OpenAI. Started their computation journey. From Pascal to Volta to Ampere, then to many of you who heard about us for the very first time, Hopper, the current generation, Blackwell, and then now Vera Rubin in full production.

Notice 6 generations of architectures. With each generation, we advanced the technology. In the course of that last 11 years, we have improved AI performance by 1 million times. If you would take a step back and think about what would Moore's law have done, in 10 years' time, the first 5 years would have improved by a factor of 10. The second 5 years by another factor of 10. 100x improvement in 10 years' time, in the same period of time. Because of the way NVIDIA extreme co-designs, we are innovating across every single computer, across every single stack of the software, optimizing new algorithms, creating new algorithms while creating architectures to accelerate it.

Working across that entire domain, what we call extreme co-design, we were able to accelerate AI by 1 million times, and we are going to continue to do so. This is what NVIDIA builds today, and this is the foundation by which we can enable Europe to be part of the AI ecosystem, the AI economy. Each generation, in the beginning, Pascal was GPUs, Volta was GPUs, Ampere was GPUs, and Hopper was GPUs. We invented the new DGX form factor. Then it was Blackwell that introduced to the world the first rack scale computing, and I will show you that in just a moment. Rack scale computing turned one entire system into one giant computer, one GPU. Now with Vera Rubin, we are extending it to processing beyond models, beyond large language models, to now processing the entire agent. We will refer back to this slide later, but remember this.