NVIDIA President and CEO Jensen Huang speaks at the Computex 2024 trade show in Taipei, Taiwan, earlier this month. Photo/The Associated Press by Qiang Yingying
It all started in 1993 at a Denny's in San Jose.
Three engineers, Jensen Huang, Chris Malachowski and Curtis Priem, met at a restaurant in what is now the heart of Silicon Valley to discuss developing a computer chip that would make video game graphics faster and more realistic.
That conversation, and others that followed, led to the creation of Nvidia, a tech company that has rocketed up the stock market ranks and briefly surpassed Microsoft this week as the most valuable company on the S&P 500.
The company's market capitalization now exceeds $3.2 trillion (NZ$5.2 trillion) and its dominance as a chipmaker has positioned Nvidia as a poster child for the artificial intelligence boom that CEO Huang calls “the next industrial revolution.”
During a conference call with analysts last month, Huang predicted that companies using Nvidia chips will build a new type of data center he called “AI factories.”
Huang added that training AI models is becoming a more rapid process as they become “multi-modal” (able to understand text, voice, image, video and 3D data) and can also “reason and plan.”
“People talk about AI as if Jensen suddenly came on the scene 18 or even 24 months ago and figured this out,” said Daniel Newman, CEO of technology research firm Futurum Group.
“But if you actually go back and listen to Jensen talk about accelerated computing, you'll find that he's been sharing that vision for over a decade.”
Headquartered in Santa Clara, California, the technology company invented the graphics processor unit (GPU) in 1999, sparking the growth of the PC gaming market and redefining computer graphics.
Nvidia's specialized chips are now a key component powering various forms of artificial intelligence, including the latest generative AI chatbots such as ChatGPT and Google's Gemini.
Neumann added that Nvidia's GPUs are a key factor in the company's success in artificial intelligence.
“They've taken an architecture that was supposedly being used for a single purpose to power games and figured out how to network these things,” he said.
“GPUs became the most attractive architecture for AI, from gaming and graphics rendering and so on, to actually using them on data… We ended up creating a market that didn't exist before: GPUs for AI, or GPUs for machine learning.”
AI chips are designed to perform artificial intelligence tasks faster and more efficiently.
General-purpose chips like CPUs can be used for more simple AI tasks, but they are becoming “less and less useful as AI advances,” according to a 2020 report from Georgetown University's Center for Security and Emerging Technology.
Tech giants are buying up Nvidia chips as they push deeper into AI, the movement that enables self-driving cars and creates stories, art and music.
“Jensen will basically make AI understandable and then Apple will make it consumable,” Newman said.
The company developed an early lead in the hardware and software needed to adapt its technology for AI applications, in part because of Huang's entry into the technology when it was still in its infancy more than a decade ago.
“Nvidia has been working on different parts of this problem for over 20 years now. They have a deep innovation engine that dates back to the early 2000s,” said Chirag Dekate, an analyst at technology research and consulting firm Gartner.
“What Nvidia did 20 years ago is identify an adjacent market, cultivate it, and discover that they could take the same processors, the same GPUs, that they were using for graphics, and make them capable of solving highly parallelized tasks.”
At the time, AI was still in its infancy, he said.
But Nvidia's realization that GPUs would be central to AI development “was the fundamental breakthrough that was needed,” Dekate said.
“Before that, we were kind of in the dark ages of analytics,” he says. “The analytics were there, but we just couldn't make the AI element come to life.”
Analysts expect Nvidia's revenue to reach $119.9 billion in the fiscal year ending January 2025, roughly double its revenue in fiscal 2024 and more than four times its revenue in the previous fiscal year.
“My hypothesis is that the kind of exponential growth we're seeing at Nvidia today could become a pattern that reproduces more frequently in the coming decades,” he said.
“This is a golden age. It's a great time to be an AI engineer.”
-Sarah Parvini, Associated Press Technology Writer
