Nvidia’s Jensen Huang is one of the tech industry’s longest-serving chief executives, leading the chipmaker since cofounding it in 1993. Now he’s the recipient of a long-standing technology award: the IEEE Medal of Honor, established by a predecessor of the Institute of Electrical and Electronics Engineers in 1917.
Huang was named the recipient of the medal (and an accompanying $2 million prize) at the Consumer Electronics Show on January 6 in recognition of his lifetime of work in accelerating computing—the technique of using specialized chips like Nvidia’s graphics processing units to speed specialized operations such as rendering images for video games, crunching numbers for scientific research, or, critically for the industry today, powering artificial intelligence.
Nvidia reached an unprecedented $5 trillion market valuation in October, with its chips providing much of the computing power behind today’s AI.
“It just is so important to have this kind of compute power at our fingertips, to be able to make advances so quickly,” says Mary Ellen Randall, president and CEO of IEEE.
Nvidia released what it calls the first GPU, the GeForce 256, in 1999. At the time, the chip was principally recognized for advancing computer gaming, letting developers and artists add unprecedented levels of graphical detail without compromising speed. Under Huang’s leadership, the company soon began work on CUDA (Compute Unified Device Architecture), a system that enables developers to harness the parallel processing capabilities of its chips for a variety of computational tasks.
That proved to be critical for recent advances in AI; Nvidia’s chips and development platforms today power AI technologies such as ChatGPT and other large language models, as well as autonomous vehicles and industrial robots.
Nvidia’s market capitalization has fallen since its October high amid questions about a possible AI bubble, including concern about Nvidia’s investments in AI firms that in turn purchase its chips. But the company maintains a valuation of more than $4 trillion as huge swaths of the economy seek to harness artificial intelligence software that its chips are optimized to run.
