Some kinds of computer chips have gained attention recently because they are used in computers linked to artificial intelligence (AI).

    Some experts describe AI chips as similar to graphics chips that speed up complex video games. Makers of AI chips say they are designed for AI systems like ChatGPT and will make them faster and less costly.

    The sudden interest in such chips is happening during what some experts call an AI revolution that could change the technology industry.

    Nvidia, led by Jensen Huang, is a maker of graphics chips. The company is based in Santa Clara, California. Nvidia also is a designer of AI chips. Stock shares of the company increased in value by 25 percent last Thursday after company officials predicted a large increase in income. The company's stock was briefly valued at more than $1 trillion recently.

    What are AI chips?

    Hanna Dohmen is a researcher with the Center for Security and Emerging Technology in Washington, D.C. She said: "There really isn't a completely agreed upon definition of AI chips."

    The term is used to talk about computing equipment that is specialized to deal with AI workloads. For example, AI chips are used in "training" AI systems to work out difficult problems.

    Coming from video games

    Three businessmen founded Nvidia in 1993 to expand the abilities of graphics on computers. Within a few years, the company had developed a new chip called a graphics processing unit, or GPU. GPUs speed up video games by performing several graphics jobs at the same time.

    The method is known as parallel processing. It would be important in the development of both games and AI.

    Two students from the University of Toronto used a GPU-based network to win a 2012 AI competition called ImageNet. The network, known as a neural network, could identify photo images at much lower error rates than competitors.

    The award began an interest in AI-related parallel processing. And it created new business for Nvidia and its competitors while providing researchers powerful tools for exploring AI development.

    Modern AI chips

    Eleven years after that ImageNet competition, Nvidia is the main supplier of chips for building and updating AI systems. One of its recent products, the H100 GPU, has 80 billion transistors. That is reportedly about 13 million more than Apple's latest top processor used in its MacBook Pro computers. However, this technology is costly. One online seller lists the H100 for $30,000.
    在ImageNet竞赛举办11年后,英伟达成为构建和升级人工智能系统的芯片的主要供应商。其最新产品之一H100图形处理单元拥有800亿个晶体管。据报道,这比苹果在其MacBook Pro电脑中使用的最新顶级处理器多出约1300万个。然而,这项技术成本高昂。一位网络卖家将H100标价为3万美元。

    Nvidia does not make these GPU chips itself. The company depends on manufacturers such as Taiwan Semiconductor Manufacturing and South Korea's Samsung Electronics.

    Some of the biggest buyers for AI chips are cloud-computing services. Technology companies, like Amazon and Microsoft, use these chips for cloud computing.

    These companies permit buyers to pay for temporary computing power to do AI jobs. Other companies then can use AI systems without a big investment in buildings and equipment. And the cloud-computer services include other tools for drug discovery or helping to oversee customers.

    Other uses and competition

    Parallel processing has many uses outside of AI. A few years ago, for example, Nvidia graphics cards were in short supply because cryptocurrency miners had bought most of them. A cryptocurrency is a digital form of money that is not overseen or controlled by a government.

    Cryptocurrency miners set up banks of computers to solve mathematical problems for cryptocurrency rewards. That problem went away as the cryptocurrency market collapsed in early 2022.

    Researchers say Nvidia will face more competition. One possible competitor is Advanced Micro Devices (AMD), which already competes with Nvidia in the market for computer graphics chips. AMD has recently taken steps to build its own lineup of AI chips.

    I'm Gregory Stachel.