Nvidia is the most valuable company in the world. With a capitalization of about 3.4 billion euros (twelve zeros), the company has shattered all expectations by surfing the wave of artificial intelligence (AI) like no one else. The market expects this technology to cause a revolution in multiple sectors, but for the moment the true great revolution is the one being carried out by Nvidia, which has gone from fighting to enter among the 20 most listed companies to looking in the rearview mirror at all the others. in less than two years.
It is a boom that, beyond the stock market fluctuations, is evident in each income statement: almost 50,000 million euros of net profit in its third fiscal quarter, presented this Thursday. It is 190% more than the same period in 2023. Jensen Huang, its co-founder and CEO since 1993, explained during a call with investors what the two ways of looking at it are. One considers Nvidia the seller of artificial intelligence chips that everyone wants. The other is being the lever of “the third industrial revolution.”
“The tremendous growth of our business is being driven by two fundamental trends that are driving the global adoption of Nvidia computing,” began the businessman, known for appearing in public wearing a black leather jacket.
A different brain model
“First, computing is undergoing a reinvention, a platform shift, from coding to machine learning. From code execution on CPUs to neural network processing on GPUs,” describes Huang, 61 years old and who has been running his company for more than 30 years.
CPUs and GPUs are the two types of brains that a computer can have. The design of central processing units (CPUs) allows them to do many different and complex tasks, such as running all types of programs, managing an operating system, and coordinating all the processes of a computer. The problem is that their performance plummets when they have to perform more than a few tasks at a time.
Graphics processing units (GPUs), on the other hand, are designed to do many simple tasks at the same time. They are not as versatile as CPUs, but they can handle immense volumes of data at the same time. Nvidia is a specialist in this technology, both in hardware and software, and each of its new chips further expands the volume of data that a system that equips them can handle.
For decades, the main commercial application of GPUs and the business from which Nvidia made money was video games. GPUs are ideal for processing your graphics and they got their name from them. With the explosion of artificial intelligence, GPUs have proven to be more useful than CPUs for the large volume of parallel calculations that their training and execution requires. In the last quarter, the video game division left about $3.2 billion in Nvidia’s coffers. That of data centers and chips, about 30.7 billion.
“The coding runs on the CPU, but the machine learning that creates neural networks runs on the GPU. That fundamental shift, from coding to machine learning, is widespread right now. There are no companies that are not going to do machine learning. Machine learning is also what enables generative AI, so right now there are trillion-dollar computer systems being retrofitted for machine learning,” summarizes Huang.
In this global re-digitization, your company has no rival in the market. Google uses Nvidia products. Its maximum competition, Microsoft, too. If Elon Musk ever manages to present a fully autonomous Tesla, it will be thanks to Nvidia chips. Without them, ChatGPT would be dozens of times less powerful. Situations like this are repeated in thousands of smaller companies that are entering the AI business, as well as in state supercomputers.
AI factories
The second trend that Huang points out is that “generative AI is not just a new software capability, but a new industry” that will change the conception of today’s data centers.
“Data centers are going to truly become AI factories. We will generate AI just as we now generate electricity. And if the number of customers is large, just as the number of electricity consumers is large, these generators will be operating 24 hours a day, seven days a week,” Huang describes: “We are going to see this new type As a system, I call it an AI factory, because that’s the closest thing to what it is. “It’s different than a data center of the past.”
I call it an AI factory, because that’s the closest thing to what it is. It is different from a data center of the past
Jensen Huang
— Nvidia CEO
It is about the “creation of a new industry”, a “third industrial revolution” as described by the CEO of Nvidia. Not only for the current generative AI but for the next step, “agent” AI, a technology with more capacity than the current one that allows machines to move between humans. This new era of humanoid robotics is on the company’s roadmap and “it is not science fiction,” as several robotics experts explained in this elDiario.es report.
“AI is transforming all sectors, companies and countries. Enterprises are adopting agentic AI to revolutionize workflows. Over time, AI coworkers will help employees do their jobs faster and better. Investments in industrial robotics are skyrocketing as advances in physical AI drive demand for new infrastructure,” Huang continued.
AI coworkers will help employees do their jobs faster and better
Jensen Huang
— Nvidia CEO
“Countries around the world recognize the fundamental AI trends we are seeing and have become aware of the importance of developing their AI and national infrastructures. The age of AI has arrived and it is big and diverse. Nvidia’s experience, scale and ability to offer a full stack and complete infrastructure allow us to serve all the multi-billion dollar AI and robotics opportunities ahead of us,” the entrepreneur concluded his call with investors.
The hidden face of the revolution
Despite making a direct reference to electricity, Huang has not entered into one of the great debates that accompanies the revolution he defends: energy. The thousands of GPUs like those manufactured by Nvidia, which, as its CEO indicates, can work 24/7, consume a lot of electricity by working without rest and having very intensive computational procedures.
The new generations of powerful Nvidia GPUs that are making their way into data centers have caused Google and Microsoft to skyrocket their polluting emissions and move further and further away from their goal of being carbon neutral by 2030. Amazon employees, for example, For their part, they have denounced that the multinational cheats its emissions figures and that these are increasingly higher.
“Its data centers, heavy consumers of energy, operate in the heart of coal-dependent regions, and the company’s expansion is increasing demand for more oil and gas,” they noted after the publication of Amazon’s environmental impact report, which ensures that its polluting emissions are decreasing.
This is a debate that is also taking place in Spain, one of the countries that is attracting new data center deployments. Amazon and Microsoft have invested billions in Aragon to build this type of infrastructure, Meta will do so in Talavera de la Reina and others such as IBM or Google have also chosen the country to be the center of their computing processes in southern Europe. .
Although one of Spain’s competitive advantages in this sense is precisely the possibility of powering data centers with renewable energy, the concerns of some activist groups extend to the use of water for cooling these large infrastructures. The employers’ association assures that the figures have been exaggerated and that new generation data centers do not imply water costs, but multinationals such as Amazon and Microsoft have refused to reveal their consumption figures when asked by elDiario.es.
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