Sunday, February 25, 2024

"Nvidia Hardware Is Eating the World" (NVDA)

From Wired, February 23:

Tech companies can’t get enough of this tech company. Earnings are off the charts. WIRED probes the mind of its CEO, Jensen Huang.

Talking to Jensen Huang should come with a warning label. The Nvidia CEO is so invested in where AI is headed that, after nearly 90 minutes of spirited conversation, I came away convinced the future will be a neural net nirvana. I could see it all: a robot renaissance, medical godsends, self-driving cars, chatbots that remember. The buildings on the company’s Santa Clara campus weren’t helping. Wherever my eyes landed I saw triangles within triangles, the shape that helped make Nvidia its first fortunes. No wonder I got sucked into a fractal vortex. I had been Jensen-pilled.

Huang is the man of the hour. The year. Maybe even the decade. Tech companies literally can’t get enough of Nvidia’s supercomputing GPUs. This is not the Nvidia of old, the supplier of Gen X video game graphics cards that made images come to life by efficiently rendering zillions of triangles. This is the Nvidia whose hardware has ushered in a world where we talk to computers, they talk back to us, and eventually, depending on which technologist you talk to, they overtake us.

For our meeting, Huang, who is now 61, showed up in his trademark leather jacket and minimalist black sneakers. He told me on that Monday morning that he hates Monday mornings, because he works all day Sunday and starts the official work week already tired. Not that you’d know it. Two days later, I attended a health care investment symposium—so many biotech nerds, so many blazers—and there onstage was Huang, energetic as ever.

“This is not my normal crowd. Biologists and scientists, it’s such an angry crowd,” Huang said into a microphone, eliciting laughter. “We use words like creation and improve and accelerate, and you use words like target and inhibit.” He worked his way up to his pitch: “If you want to do your drug design, your drug discovery, in silicon, it is very likely that you’ll have to process an enormous amount of data. If you’re having a hard time with computation of artificial intelligence, you know, just send us an email.”

Huang has made a pattern of positioning Nvidia in front of every big tech trend. In 2012 a small group of researchers released a groundbreaking image recognition system, called AlexNet, that used GPUs, instead of CPUs, to crunch its code and launched a new era of deep learning. Huang promptly directed the company to chase AI full-steam. When, in 2017, Google released the novel neural network architecture known as a transformer—the T in ChatGPT—and ignited the current AI gold rush, Nvidia was in a perfect position to start selling its AI-focused GPUs to hungry tech companies.

Nvidia now accounts for more than 70 percent of sales in the AI chip market and is approaching a $2 trillion valuation. Its revenue for the last quarter of 2023 was $22 billion—up 265 percent from the year prior. And its stock price has risen 231 percent in the last year. Huang is either uncannily good at what he does or ridiculously lucky—or both!—and everyone wants to know how he does it.

But no one reigns forever. He’s now in the crosshairs of the US-China tech war and at the mercy of regulators. Some of Huang’s challengers in the AI chip world are household names—Google, Amazon, Meta, and Microsoft—and have the deepest pockets in tech. In late December the semiconductor company AMD rolled out a large processor for AI computing that is meant to compete with Nvidia. Startups are taking aim too. In last year’s third quarter alone, venture capitalists funneled more than $800 million into AI chips, according to the research firm Pitchbook.

So Huang never rests. Not even during interviews, as I learned when, to my surprise, he started interviewing me, asking me where I was from and how I ended up living in the Bay Area.

Jensen Huang: You and I are both Stanford grads.

Lauren Goode: Yes. Well, I went to the journalism program, and you did not go to the journalism program.

I wish I had.

Why is that?

Well, somebody who I really admire, as a leader and a person, is Shantanu Narayen, the CEO of Adobe. He said he always wanted to be a journalist because he loved telling stories.

It seems like an important part of building a business, being able to tell its story effectively.

Yes. Strategy setting is storytelling. Culture building is storytelling.

You’ve said many times you didn’t sell the idea of Nvidia based on a pitch deck.

That’s right. It was really about telling the story.

So I want to start with something that another tech executive told me. He noted that Nvidia is one year older than Amazon, but in many ways Nvidia has more of a “day one” approach than Amazon does. How do you maintain that outlook?

That’s really a good phrase, frankly. I wake up every morning like it’s day one, and the reason is there’s always something we’re doing that has never been done before. There’s also the vulnerable side of it. We very well could fail. Just now, I was having a meeting where we’re doing something that is brand-new for our company, and we don’t know how to do it right.

What is the new thing?

We’re building a new type of data center. We call it an AI factory. The way data centers are built today, you have a lot of people sharing one cluster of computers and putting their files in this one large data center. An AI factory is much more like a power generator. It’s quite unique. We’ve been building it over the last several years, but now we have to turn this into a product.

What are you going to call it?

We haven’t given it a name yet. But it will be everywhere. Cloud service providers will build them, and we’ll build them. Every biotech company will have it. Every retail company, every logistics company. Every car company in the future will have a factory that builds the cars—the actual goods, the atoms—and a factory that builds the AI for the cars, the electrons. In fact, you see Elon Musk doing that as we speak. He’s well ahead of most in thinking about what industrial companies will look like in the future.

You’ve said before that you run a flat organization, with between 30 to 40 executives who report directly to you, because you want to be in the information flow. What has piqued your interest lately, that makes you think, “I may need to bet Nvidia on this eventually?”

Information doesn’t have to flow from the top to the bottom of an organization, as it did back in the Neanderthal days when we didn’t have email and texts and all those things. Information can flow a lot more quickly today. So a hierarchical tree, with information being interpreted from the top down to the bottom, is unnecessary. A flat network allows us to adapt a lot more quickly, which we need because our technology is moving so quickly.

If you look at the way Nvidia’s technology has moved, classically there was Moore’s law doubling every couple of years. Well, in the course of the last 10 years, we’ve advanced AI by about a million times. That’s many, many times Moore’s law. If you’re living in an exponential world, you don’t want information to be propagated from the top down one layer at a time....

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