Computing Power is King! Jen-Hsun Huang discusses how AI is restructuring the global value chain, when will Bots become popular, and can AI accelerate the return of manufacturing to the United States?

In this article, NVIDIA CEO Jensen Huang talks about how AI will lead the new industrial revolution, reshape industries, and change the job market of the future. (Synopsis: Jensen Huang rejects blockchain? Nvidia Inception's official website explicitly excludes applications for "crypto startups") (background supplement: Huang Jenxun shouts "no cryptocurrency"! Nvidia suddenly shouted to stop Arbitrum cooperation, why did her attitude take a big turn? Jensen Huang, co-founder and CEO of Huida NVIDIA, recently shared his insights on the development of artificial intelligence (AI) in a recent interview with the Hillen Valley Forum forum. He positions AI as a new industrial revolution and gives us a grand picture of how AI will reshape all walks of life in the 21st century economy and how human society will respond to this change. AI Factory: A Source of Wisdom for a New Era Huang Jenxun first explained what an "AI factory" is. He pointed out that AI is not only a new technology, it is built in a very different way than the software of the past, and can perform tasks that the software of the past could not do. What's more, the production model of AI has changed, "In the past, software was produced by human input code," Huang said, "Today, we have a new industry, software is produced by machines." These machines, large supercomputers, operate through electricity and produce tokens, which can be recombined into various forms of wisdom such as numbers, words, protein structures, images, videos, three-dimensional models, and so on. "I call it an AI factory because it only does one thing every day: producing tokens." The smart tokens produced by these AI factories will penetrate into various fields, including healthcare, financial services, engineering, supply chain management, and especially the education field that Huang is very optimistic about. He believes that just as electricity played a role in the industrial revolution of the past, the intelligence produced by AI factories will also go back and revolutionize every existing industry. For example, the car company of the future will not only make physical cars, but will also set up AI factories to produce the tokens that drive those cars. "Ten years from now, every car company will also produce tokens that run in those cars." This shift foreshadows the future when any company that makes physical products may need an AI factory to produce the "brains" it needs to produce its products. The immediate impact of this on the market is that the demand for computing power, energy, and related infrastructure will surge, and companies like NVIDIA that provide the underlying technology will continue to be at the top of the wave. The Evolution of AI and the Future of "Physical AI" Jensen Huang reviewed the development of modern AI, dividing it into several stages. About 12~14 years ago, the breakthrough of computer vision represented by AlexNet opened a wave of "perceptual AI", allowing machines to understand the meaning of image, sound, vibration, temperature and other information. Then, about five years ago, "generative AI" came into focus, and AI models learned to understand information and transform it, such as translating English into French or generating images based on text prompts, like a general-purpose translator. Right now, we're in the era of "reasoning AI." This kind of AI can not only understand and generate, but also solve problems and identify unseen situations. They use human-like reasoning skills to gradually break down problems and apply learned rules and principles to solve them. "We call it proxy AI, and it's proactive." Huang explained that these digital robots can understand tasks, learn, use tools such as computers and browsers, and perform tasks for humans, such as accessing SAP systems for supply chain issues or Workday for human resources. He foresees that future CEOs will manage both the physical and digital workforce, and that IT departments may become "human resources" that act on AI. The next wave is "physical AI". This requires AI to understand the laws of physics, such as friction, inertia, causality, and common sense in the real world. For example, an object does not pass through a table, and a ball rolling off the table will sit on the floor instead of disappearing into another dimension. AI with these physical reasoning capabilities, once placed in physical robots, gave birth to "robotics". Huang believes that this is critical to the future of manufacturing in the United States and globally. "When we build new plants and factories across the United States, we want to take advantage of the latest technology. Hopefully, within the next decade, these next-generation factories and factories will become highly robotized, helping us cope with the severe global labor shortage." This vision implies a huge market opportunity for the robotics industry, sensor technology and related software development. The Global AI Race and the U.S. Response In the face of the global AI race, Huang offered his views on how the U.S. government should respond. He stressed that it is important to understand the nature of the race, which is an "infinite game" rather than a game with a fixed time limit. NVIDIA's own 33-year history, spanning the PC revolution, the Internet revolution, the mobile revolution, and the current AI revolution, is the embodiment of long-term thinking. He analyzes the keys to success from three aspects of AI: Technical: Intellectual capital is critical. Huang cautions that 50% of the world's AI researchers are of Chinese descent, and this factor must be factored into strategic considerations. This means that talent attraction, development and international cooperation will be key. AI factory level: Energy is at the core. AI factories operate by converting electricity into digital tokens, just as the industrial revolution in the past converted energy into physical products or electricity itself. Therefore, an adequate and cost-effective energy supply is the basis for the development of AI factories. At the infrastructure and application level: Huang pointed out that the winners of the last industrial revolution were not the countries that invented technology, but the countries that applied it the fastest, and the United States was a model. So for AI, it's all about positive applications, not fear. This includes upskilling the workforce to enable it to apply AI and encouraging the adoption of AI technologies by all sectors of society. Huang's views undoubtedly provide clear guidance for policymakers and market investors. In the AI race, it is not enough to focus on technology research and development, energy policy, talent strategy, and promoting industrial adoption will be just as important, if not more critical. The short-term market reaction may be reflected in an increased focus on energy stocks, AI infrastructure concept stocks and the edtech sector. The Real Impact of AI on the Job Market: Transforming Not Replacing In response to concerns that AI could lead to mass unemployment, Huang offered a more nuanced view: "New jobs will be created, some jobs will disappear, but every job will be changed." He stressed that the problem should not be taken to extremes, but should be analyzed from the basis of basic principles. At the basic technology level, the development of AI itself has created new jobs. Huang cited San Francisco as an example to point out that the city has been revitalized by AI. "AI creates a new kind of work because the way software is developed has changed. Software that used to be coded by humans and run on CPUs is now software built by machine learning and running on GPUs." This means that every layer, from tools, compilers, and methodologies to data collection, management, and AI security, is giving birth to new technologies and jobs. ...