So good morning everybody. Hello Jensen. Good to have you. Tim, good to be here. Look, this is an interesting press conference for us this morning because we do it very interactive, not by presentations only, and therefore it would be a nice dialogue. I was thinking how to start that session. Yesterday evening I was with my fitness trainer and I did fitness. I can tell you fitness is only working if your muscles are in good shape, if your technique is perfect, and if your mentality is at the right edge, otherwise you can forget every training. What we are talking today is exactly about that. It's about how can we make Germany fit. This is the whole purpose of this exercise. What is the heart of Germany? It's our industrial core. That is what it is. This is the heart which we have to train now. The muscle of this body I would call it Deutsche Telekom. We are the infrastructure. We have the connectivity. We built the infrastructure of data centers across the globe. We have 186 data centers which we operate already today. We are the muscle of the body. And then we have the brain of the body. I can tell you the brain is here. I'm very happy that Jensen is here today. He's running the most wealthy company on Earth, which is for me a very impressive achievement. I'm more impressed about the technology. It's the brain of the future. Without AI, you can forget the industrialization. You can forget the German industries. If we are not adapting AI in our industries, I can tell you there will be no prospect. There will be no prosperity in our society in the future. So therefore, we need a good brain for that. We have the muscle. We have the brain. And on top of that we have the skin, and that is even new what we are presenting today. The skin of what we are talking about is SAP, because it's very important that you don't only run a compute machine, that you have a T-cloud or an environment of infrastructure. You even need a skin which is making the world open, which is enabling all industries. Therefore I'm very happy that Christian Klein is here from SAP, where we are launching a new cooperation here as well at this event. So I hope that you understand already what we are talking about and what we want to do. But I want to hand it over now to Jensen about how he looks at the world and especially about the German situation and what we're doing here today.
Thank you, Tim. I always love coming to Germany because this is the land of engineers. This is where we're all very welcome, and I feel very welcome every time I'm here. I'm also very happy to be here today because this idea actually started with me and I approached you about this great idea. Our industry, this story really started with the transformation of our industry. As you know, we're at a transition time in the computer industry. After 60 years of general purpose computing, the technology that Nvidia invented over the course of 30 years is now shifting how everything is done. Every single layer of the computer industry, from the chips to the systems to the software to the applications, are being completely revolutionized by artificial intelligence. After 15 years of working on AI, it is now transforming every single industry, including finally manufacturing. Manufacturing is extremely difficult, and the reason for that is because physical AI needs to understand the structure of the world and the laws of physics. The work that is done here in Germany is done at such an extraordinary scale and precision. We have to have incredibly good AI. But finally that day is here, and this is a very exciting time because Germany had a vision of Industry 4.0, fusing digital with physical. And finally now with artificial intelligence, we will supercharge Industry 4.0, and this will be the era of industrial AI. So I'm very excited about that.
Today is a very big day. We talked about Industry 4.0, and I think the architecture and the concept was right, but the problem was the execution in Germany didn't take place. The step going into investments and using the technology for making Industry 4.0 happen was something which was at least slowly happening. At the same time, the world was waking up. China was waking up, the US was waking up on all these possibilities to create this next generation of industrialization. What you can see on that slide is that today 70% of all GPUs are sitting in the US, 14% sitting in China and in Asia mainly in China, and only 5% sitting here in Europe as a total. So how can Europe and especially Germany at the core with this industrial competence adapt into this next generation? That is why we started this initiative to say we have to build a stack here in Germany which is enabling our industry to participate in this next generation evolution of the industrialization.
And Tim, your vision is absolutely spot on. The reason for that is because these GPUs, these computers are the modern versions of factories. These are factories just like factories of cars and all the industrial factories of Germany. These are factories of intelligence. In the future in Industry 4.0 with AI, every company that's a manufacturing company will have two factories: the factory for the car and the factory for the AI that drives the car.
And maybe the core of all this is the compute power which the companies have or need to deploy these digital twins, to use this virtual world to optimize processes, to optimize their scientific work and all of this. We have here today something which you brought with us which is going to be implemented very soon in Germany, and maybe we show it to the public today. So by the way, let's just open up here together and then you say what this is here.
This is one GPU. People think that Nvidia builds chips. We do build chips, and these chips go into what is a GPU supercomputer that we invented, started working on almost 30 years ago, and this is our latest version. This is called Blackwell, and this is a few thousand pounds. I can tell you the exact price, so it's quite costly, but anyway, it's very good value.
Yes, I agree. Very good value.
There are currently 16 different chips that are connected together into one giant GPU, and this is the Blackwell B200.
So the initiative which we have together is that we are launching a new data center coming soon, and I go into the details in a second, with 10,000 of these GPUs. This is going to be a data center under all security standards which is going to be taking place in Munich. It is in a special prepared location which is three to four floors under the ground. It is powered by local renewable energy 100%, and on top of that by water cooling by a local river which is enabling the cooling process. A GPU needs a very special environment for being deployed, and we worked on the possibility to start with 10,000. Now some journalists and some people would immediately say, 'By the Americans they are putting gigabit factories into place, their announcement up to 70 gigawatt in the US right now. So what do you think that we are just starting with 10,000 now?'
Well, starting is the most important part. Here we are. Starting is the most important part. This computer is a factory. This is quite an interesting thing. This computer, you apply energy to it. It runs an artificial intelligence model, and what comes out of it are tokens. These tokens are like you market the tokens for dollars per million tokens, just like electricity dollars per kilowatt hour. This is the new industrial revolution, a machine that generates a commodity that has tremendous value, which is the reason why this is a factory. Germany is going to be incredibly good at running these factories because as you know, Germany is really good at building and running factories, and this is going to be the new industrial factory.
Jensen, can you give for the ones who don't work in this industry every day some examples about how this AI GPUs can create productivity, can create time to market, can create value for different industries?
Well, the first thing is we have to teach the model, which is software. We have to teach the model the language of information. We taught it of course English and German. We also taught it mathematics. We taught it robotic articulation motion. We can also teach it chemistry, biology, fluid dynamics. We could teach this software almost anything that has information encoded. So once you teach this computer running the software, the AI model, the language of that information and how to think and reason about that information, then it can translate the information. So let me give you an example. I can give this computer numbers in English, and then I say to this computer translate it to German. It will output numbers that will become German. I could also give it a whole lot of English in a book and I say summarize all of that for me, and it will generate a summary of the book. The key is that it understands the meaning of the information, and the key is this computer can understand, can learn the meaning of the world's information.
I like the algorithm behind, but the question is what is the economical benefit? Germans always count the beans. To give you some examples where I see benefits from GPUs: in the past, car manufacturers used a kind of physical car to test the wind channel and to improve the streaming around the cars. Now they could put every detail into the machine and can simulate it on the computer. So the cost for the optimization of the car frame is significantly optimized. We have the example of the chemical industries. If you are working on new chemicals, the way of molecular structures and what you need, you can reduce the time to market significantly by almost 50% if you work in a digital environment in an optimized way. We talk about the optimization where a company which is producing pills, you can reduce the ingredients by 60% if you optimize the way how you manufacture the medical services. So the raw material consumption, the effectiveness, the time to market, the trial and error cycles, everything is going to be simulated in the machines. You have billions of data points which you put into the system, but you have to work with them in a very fast manner because otherwise you need a lot of CPUs which are eating a lot of energy, and then it's getting inefficient. With the GPUs you're able to do this in a much more efficient way.
That's right. That's spot on. The real idea here is that we're producing intelligence. Now intelligence as you know is very difficult to see, but the benefits of intelligence is very clearly easy to measure. One of the things that we all know is that the world has a shortage of labor. Let me give you one example of labor. Let's pretend for a second that the shortage of labor we have is somebody to drive the car. Somebody drove me here today. You asked the question what is the value of artificial intelligence? In the case of the car, the self-driving car, we now have a digital and AI chauffeur. That AI chauffeur can learn to recognize the environment and manipulate the steering wheel and the gas pedal. It does this incredibly well. What is the value of that AI? Maybe it's $20 per hour, whatever is the price of an AI chauffeur. So whether it's measured in labor cost or it's measured in the benefit of the output, you said in many examples the number of drug discoveries has doubled if your productivity improves, and you could measure the amount of output. That is the value of AI. But what comes out of this machine is basically numbers because it's a computer, and these numbers are reformulated into intelligence: the intelligence of human language, the intelligence of numbers, the intelligence of chemicals and proteins.
Now I think we understand the need for GPUs compared to CPUs. They are much more efficient in the way of creating results. They are less energy consuming than using all the chipsets which you can have in a normal data center. On top of that, they work simultaneously and in parallel.
