How Nvidia CEO Jensen Huang transformed his video game graphics company into a titan of AI

Nvidia’s groundbreaking innovation — the graphics processing unit —  is powering humanoid robots, the design of virtual movie sets and the creation of protein-based drugs to fight diseases. 

Insatiable demand for Nvidia’s GPU-powered technology, used for artificial intelligence, pushed the company into the stock market stratosphere, where it joined Microsoft, Apple, and Alphabet – the parent company of Google – to become one of just four U.S. companies to ever top $2 trillion in stock market valuation. 

Nvidia pressed ahead in March, when CEO Jensen Huang unveiled Blackwell, the company’s latest GPU. Designed in America, but made in Taiwan, Huang said Blackwell is the fastest chip ever and suited for AI.

“We’re hoping that it does things that surprise us,” Huang said. “That’s the whole point.”

Nvidia’s surprising start in a Denny’s 

The futuristic Nvidia campus sits just down the road from the company’s modest birthplace: a Denny’s in San Jose, California. As a teenager, Huang, now 61, worked as a dishwasher in a Denny’s. Three decades ago, it was in a San Jose Denny’s, where he and two friends, co-founders Chris Malachowsky and Curtis Priem, dreamed up a whole new way of processing video game graphics — and decided to start a company.

At the time, Huang was a 30-year-old electrical engineer, married with two young children. He and his two Nvidia co-founders had no idea how to start a company, but they went for it anyway.  

Their big idea was to accelerate the processing power of computers with a new graphics chip. Their initial attempt flopped and nearly bankrupted the company in 1996, but they were able to pivot and eventually create their groundbreaking GPU.

Just eight years after Nvidia was hatched in Denny’s, the company earned a spot in the S&P 500. Huang then set his sights on developing the software and hardware for a revolutionary, GPU-driven supercomputer, which would take the company far beyond video games. It seemed like a risky bet to Wall Street, but to early developers of AI, it was a revelation. 

“That was luck founded by vision,” Huang said. 

The technological capability they invented was perfect for AI researchers, he said. In 2016, Huang delivered Nvidia’s AI supercomputer, the first of its kind, to Elon Musk, then a board member of OpenAI, which used it to create the building blocks of ChatGPT. When AI took off, so did Huang’s reputation. 

He’s now a Silicon Valley celebrity. As someone who immigrated to the U.S. from Taiwan at age 9, Huang said he could never have conceived of his success. 

“It is the most extraordinary thing, Bill, that a normal dishwasher-busboy could grow up to be this,” Huang told 60 Minutes correspondent Bill Whitaker. “There’s no magic — it’s just 61 years of hard work every single day.”

People who work with Huang describe him as demanding, a perfectionist, and someone who’s not easy to work for. Huang said all those descriptions sound right to him.

“It should be like that,” he said. “If you want to do extraordinary things, it shouldn’t be easy.”

AI advancements made with Nvidia technology

At Nvidia’s annual developers conference in March, the mood wasn’t just upbeat, it was downright giddy. More than 11,000 enthusiasts — software developers, tech moguls, and happy shareholders — filed into San Jose’s pro hockey arena to kick off a four-day AI extravaganza. 

Huang showed off some of what AI has made possible in just the past few years, like an AI-powered simulation of Earth’s weather patterns, which will eventually be able to calculate and predict weather 3,000 times faster than a supercomputer while using 1,000 less energy, Huang said.

Pinar Seyhan Demirdag, Cuebric co-founder, relies on Nvidia GPUs to instantly turn simple text prompts into virtual movie sets for a fraction of the cost of some of today’s backdrops. She said her company is getting a lot of love from Hollywood. 

At Generate:Biomedicines, Dr. Alex Snyder – head of research and development – is using Nvidia’s technology to create protein-based drugs. She was initially skeptical about the use of AI for drug development. Then she looked at the lab data, and changed her mind. 

Now her team asks its AI models to create proteins to fight diseases like cancer and asthma. The AI generates proteins that don’t exist in nature, which are then rigorously tested in the lab. A drug to defeat the coronavirus is in clinical trials. 

“We’re not putting Frankensteins into people,” Snyder said. “We’re taking what’s known and we’re really pushing the field, we’re pushing the biology.”

Figure, a Silicon Valley startup with funding from Nvidia, has developed an Nvidia GPU-driven humanoid robot.  CEO Brett Adcock says the robot is designed to address labor shortages, and would not be possible without Nvidia’s technology. 

“We think they’re arguably the best in the world at this,” Adcock said. 

His prototype is not yet perfected, but the early results are so promising that German automaker BMW plans to start testing the robot in its South Carolina factory this year. Adcock envisions a future with billions of robots working alongside humans. 

Addressing worries about AI

Investors are bullish on Nvidia, but others fear AI technology is flying too high. Last year, more than 600 top AI scientists, ethicists and others signed a statement urging caution, warning of AI’s risk to humanity. Some worry about AI taking jobs as the technology advances.

“I think over time, AI and robotics will start doing more and more of what humans can and better,” Adcock said. 

As Huang sees it, when companies become more productive, earnings will increase, which means they can hire more workers. 

“You still want human[s] in the loop, because we have good judgment,” Huang said. “Because there are circumstances that the machines are not, just not going to understand.”

Huang sees an AI future of progress and prosperity — not one with machines as our masters. To him, AI is a game-changing technology.

“We need artificial intelligence to help us explore the universe in places that we could’ve never done ourselves,” Huang said.