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Nvidia is facing the biggest crisis in its 33 year history. Founder Jensen Huang accused of multiple affairs, including with a direct report, and Alice Huang, an alleged Chinese spy who also worked with a major Nvidia customer Megaspeed, based out of Singapore, that put her in the middle of a sprawling effort to accumulate AI chips across Southeast Asia and possibly get them into the hands of restricted Chinese companies. Now he's out as CEO. Nvidia CEO Jensen Huang has officially resigned his post following reports of a second affair in one of the biggest shakeups in corporate America's history.
The entire story feels like it's a script for a movie. The fact that she may be a spy, that she worked for a distributor or a neocloud that was supplying, potentially, compute into China. If there was anything that breached the trust of the country or that breaks the trust of how he handled company secrets, I don't know that you can survive that. The relationship between Jensen Huang and Alice Huang dates back to 2023, a turbulent time for Nvidia, as it navigated the first in a series of strict export controls that the Biden administration placed on sending its most advanced chips to China in an effort to keep the world's second largest economy from leapfrogging the U.S.
in AI. It's also the year we sat down with Jensen Huang for an in-depth interview about the history of his company. That same day, we also interviewed another Nvidia executive who, it turns out, he also reportedly had an affair with. This isn't the first time Nvidia has found itself teetering on the edge of an uncertain future. It nearly went bankrupt a handful of times in early years, when Jensen Huang bet the company on impossible seeming ventures. Every company makes mistakes, and I make a lot of them, and you know, some of them puts the company in peril, especially in the beginning because we were small and we're up against very, very large companies and
we're trying to invent this brand new technology. Three decades and many AI chips later, and Nvidia's place at the very center of all AI computing sent its stock up 17 fold at its peak and gave Jensen Huang a net worth over $150 billion before it all took a tumble. That's remarkable for a man who dreamed up the idea with two fellow engineers out of a Denny's in the early 90s in hopes of bringing better 3-D graphics to PCs for better video games. In his humble beginnings, certainly played a role in him becoming great. But you know, he's been on the cover of Time Magazine. I think by now he certainly knew he was important as he flew around the world with the president of the United States. As investigations by Nvidia's own board and
government entities from House committees to the FBI dig into exactly what happened here, we take a look back at Nvidia's history from our own interviews with Jensen Huang and other company leadership to get a clear picture of where Nvidia stands today and all it stands to lose. In the first months of the AI boom, as Nvidia was on the cusp of becoming a household name, Jensen Huang had long term aspirations for leading his company. You are the longest running tech CEO.
Is there any end in sight? Well, as you could tell, I'm sprightly and quite enthusiastic and energetic, yet, um. Uh, I'm surrounded by amazing people. They keep me inspired. And I feel that we could do great things together. I feel that I'm making a real contribution to the company and to them. And so I think for so long as I, I believe I could do that. And, um, uh, I don't know exactly how that how long that's going to be, but 3 or 4 decades, I would say. And so hopefully, hopefully I'll get to enjoy this for a very long time.
Three years later, the question isn't whether Huang's contributions were meaningful, but whether his mistakes were, in fact just that. The fact that he may have used his influence in some way to help gain more access to compute in a region where it was clearly sensitive or not supposed to be available at all. In many cases, that's the question, because there is a chance that Jensen has done nothing different than Jeff Bezos and Sergey Brin and Bill Gates, and made a mistake in his personal relationship that has cost him dearly, reputationally and financially.
Because until now, Nvidia was one of the rare Silicon Valley giants that still had its founder at the helm. Jensen is so important to this company. The company has been built in his light. It's a reflection of who he is. The autocratic style that he imposes, the leaders that he has selected that are basically the execution of his will inside of the business. You can't send him off and just bring Jensen to it. 63-year-old Jensen Huang immigrated to the U.S. from Taiwan as a kid and studied engineering at Stanford and Oregon State, where he met his wife, Lori Mills. Marrying her in 1985.
In the early 90s, Huang met fellow engineers Chris Malachowsky and Curtis Priem at Denny's, where they talked about dreams of enabling PCs with 3D graphics, the kind made popular by movies like Jurassic Park at the time. If you go back 30 years, at the time, the PC revolution was just starting and there was quite a bit of debate about what is the future of computing and how should software be run. And there was a large camp, and rightfully so, that believe that CPU or general purpose software was the best way to go, and it was the best way to go for a long time. We felt, however, that there was a class of applications that wouldn't be possible without acceleration.
The friends launched Nvidia out of a condo in Fremont, California, in 1993. The name was inspired by envy for next version and invidia, the Latin word for envy. They hoped to speed up computing so much everyone would be green with envy. Data center chips remain its primary business. Led by industry leading graphics processing units originally sold as cards that plug into a PC's motherboard and now dominate in data centers, too, they accelerate, add computing power to central processing units, CPUs that primarily come from Intel and AMD.
Although Nvidia now makes its own CPUs as well. You know, there were one among tens of GPU makers at that time. They are the only ones, and them and AMD actually who really survived. Um, because they. Nvidia worked very well with the software community. This is not a chip business. This is a business of figuring out things end to end. But at the start, its future was far from guaranteed. In the beginning, there weren't that many applications for it, frankly, and we smartly chose one particular combination that was a home run. It was computer graphics, and we applied it to video games.
Now, Nvidia is known for revolutionizing gaming and Hollywood with rapid rendering of visual effects. Nvidia designed its first high performance graphics chip in 1997. Designed, not manufactured. Because Huang was committed to making Nvidia a fabless chip company, keeping capital expenditure way down by outsourcing the extraordinary expense of making the chips to TSMC. On behalf of all of us. You're my hero. Thank you, thank you, thank you. Nvidia today wouldn't be here if and nor the other thousand fabulous semiconductor companies wouldn't be here if not for the pioneering work that TSMC did. In 1999, after laying off the majority of workers and
nearly going bankrupt to do it, Nvidia released what it claims was the world's first official GPU, the GeForce 256. It was the first programable graphics card that allowed custom shading and lighting effects. By 2000, Nvidia was the exclusive graphics provider for Microsoft's first Xbox. Microsoft and the Xbox happen at exactly the time that we invented this thing called the Programable shader, and it defines how computer graphics is done today. Nvidia went public in 1999, and its stock stayed largely flat until demand went through the roof during the pandemic. In 2006, it released a software toolkit called Cuda that would eventually propel it to the center of the AI boom.
It's essentially a computing platform and programing model that changes how Nvidia GPUs work from serial to parallel computing. Parallel computing is, let me take a task and attack it all at the same time using much smaller machines, right? So it's the difference between having an army where you have one giant soldier who is able to do things very well, but one at a time, versus an army of thousands of soldiers who are able to take that problem, right and do it in parallel. You know, they quickly realized that the smartphone market wasn't for them. So they exited right from that.
Nvidia also made early moves toward data center CPUs in 2020 when it tried to acquire ARM, which licensed its signature processor architecture to major companies making their own chips like Apple, Google and Amazon. The $40 billion deal fell through because of significant regulatory challenges, and instead, Nvidia made a series of other big deals to drive its tech forward from a $7 billion acquisition of networking chip company Mellanox to its biggest purchase yet - $20 billion to acquire assets from AI chip designer Groq, which led to a new type of chip Nvidia calls a language processing unit and a $5 billion investment in Intel with a plan to develop custom Intel CPUs for data centers and PCs.
Since 2023, Nvidia has grown fast from 26,000 to 42,000 employees across 38 countries. Its polygon themed headquarters in Santa Clara, California, was redesigned in 2022 in an ode to the polygon as a basic building block of 3D computer graphics. The billions of chips it designs there now span far more industries, from data centers to autonomous cars, robots, and, of course, AI. We're in every cloud made by every computer company. And then all of a sudden, one day, a new application that wasn't possible before discovers you.
More than a decade ago. Nvidia's Cuda and GPUs were the engine behind AlexNet. What many consider AI's Big Bang moment. It was a new, incredibly accurate neural network that obliterated the competition during a prominent image recognition contest in 2012. Turns out, the same parallel processing needed to create lifelike graphics is also ideal for deep learning, where a computer learns by itself rather than relying on a programmer's code. We had the good wisdom to go put the whole company behind it. We saw early on, about a decade or so ago, that this way of doing software could change everything, and we changed the company from the bottom, all the way to the top and sideways.
Every chip that we made was focused on artificial intelligence. Bryan Catanzaro was the first and only employee on Nvidia's deep learning team in 2016. Last year, Nvidia's overall research roster had grown to around 400 people. For ten years, Wall Street asked Nvidia, why are you making this investment? No one's using it. And they valued it at $0 in our market cap. And it wasn't until around 2016 that after ten years after Cuda came out, that all of a sudden people understood this is a dramatically different way of writing computer programs,
and it has transformational speedups that then yield breakthrough results in artificial intelligence. In 2023, we also talked to Kimberly Powell. It's now come out that Jensen Huang reportedly had an affair with her, too. As Nvidia's VP of healthcare, she was excited about the real world power of AI to help with faster drug discovery and DNA sequencing that takes hours instead of weeks. We were able to achieve the Guinness World Record in a genomic sequencing technique to actually diagnose these patients and administer one of the patients in the trial to have a heart transplant, a 13-year-old boy who's
thriving today as a result, and then also a three-month-old baby that was having epileptic seizures. And to be able to prescribe an anti-seizure medication. And when crypto started to boom, Nvidia's GPUs became the coveted tool for mining the digital currency. Which is not really a recommended usage, but that has created, you know, problems because crypto mining has been a boom or bust cycle. So gaming cards, right, go out of stock prices, get bid up, and then when the crypto mining boom collapses, then there is a big crash right on the gaming side. Although Nvidia did create a simplified GPU made just for crypto, it didn't stop miners from buying up gaming GPUs, sending prices through the roof and causing sticker
shock among Nvidia's original loyal fan base of video gamers. Now, of course, it's AI that's leaving those gamers brokenhearted, as Nvidia prioritizes its limited supply of memory wafers and substrates for its flagship data center GPUs. In 2023, Huang showed us the A100, its Ampere line of GPUs that were packaged into $200,000 server boards used to train the earliest iterations of OpenAI's ChatGPT. When we ship them, we don't ship them in packs of one. We ship them in packs of eight. That A100 was the original Nvidia chip the Biden administration banned from being sold to China in 2022. About a quarter of your revenue comes from mainland China. How do you calm investor fears over the new export controls?
Well, Nvidia's technology is export controlled. It's a reflection of the importance of the technology that we make. The first thing that we have to do is comply with the regulations. And it was a turbulent, you know, month or so as the company went upside down to re-engineer all of our products so that it's compliant with the regulation. The regulation is going to be just fine. We're going to be able to work through it. But as export controls got tighter and tighter, Nvidia ended up redesigning three different chips from 2022 to 2024 to keep its GPUs legally selling in
China. But after China's deep sea launched in 2025, trained on Nvidia chips, the Trump administration placed even stricter limitations that Nvidia said would cost it $5.5 billion in canceled orders. A few months later, Huang said, we are 100% out of China. In reality, the company maintained business in the region. In its most recent annual report, Nvidia said about 9% of its revenue came from China, including Hong Kong. Although that includes segments outside of restricted data center chips such as gaming, auto and industrial. A report in May from short seller Culper Research alleged Nvidia's China exposure was much higher.
The firm said that more than 20% of Nvidia's fiscal 2026 compute revenue was driven by China, supported by illegal GPU diversion and Southeast Asian intermediaries. According to the report, Nvidia didn't respond to requests for comment because it turns out there's a loophole that allows Chinese companies to rent Nvidia graphics processing units and data centers, even when they're restricted from buying them outright. And that's why Jensen Huang and Alice Huang's relationship gets even messier, because just months after those 1st October 2022 export controls, Megaspeed set up a subsidiary in Malaysia and reportedly purchased nearly
$5 billion worth of Nvidia's most advanced chips, leading the Commerce Department and Singapore Police to launch investigations into Megaspeed over alleged China export violations. Fast forward to 2026, and Huang's cozy relationship with President Donald Trump led to a shift as he advised the White House on AI safety and pushed for looser regulations. And he was a last minute addition to the roster of tech executives who joined Trump on a trip to China in May after the president was briefed on intelligence concerns, according to The Times. In December, Trump said Nvidia would be allowed to ship its A200 chips to China again,
provided the U.S. gets a 25% cut of sales. But now China is restricting those sales. The U.S. has licensed sales to Chinese companies like Alibaba, Tencent and ByteDance, but Beijing hasn't approved large scale imports and H200 shipments to China made up less than 1% of data center revenue in the most recent quarter. Another major geopolitical risk for Nvidia is its dependance on TSMC in Taiwan. There's two issues. One, Will China take over the island of Taiwan at some point? And two, is there a viable, you know, competitor to TSMC? And as of right now, you know, Intel is trying aggressively to get there. And we will see.
And this is not just an Nvidia risk. This is a risk for AMD, for Qualcomm, even for Intel. This is a big reason why the Biden administration passed the Chips act in 2022, which set aside $52 billion to incentivize chip companies to manufacture on U.S. soil. Now, TSMC is spending $265 billion to build a massive campus of chip fabrication plants fabs in Arizona. The fact of the matter is, TSMC is a really important company and the world doesn't have more than one of them. It is imperative upon ourselves and them for them to also invest in diversity and redundancy. And will you be moving any of your manufacturing to Arizona?
Oh, absolutely. We'll use Arizona. Yeah. Yeah, absolutely. Another risk to Nvidia's dominance comes from custom AI accelerators, now made in-house by some of Nvidia's biggest customers. As Google, Amazon, meta, Microsoft and OpenAI seek an alternative to Nvidia's costly, supply constrained GPUs. See, the biggest question for them is how do they stay ahead? Because their customers can be their competitors also. Um, you know, Microsoft, uh, can try and design these things internally. Amazon and Google are already designing these things internally.
The amount of power that the world needs in the data center will grow. And you can see in the recent trends, it's growing very quickly and that's a real issue for the world. Now, agentic AI has taken over from call and answer chatbots, and those agents require much more orchestration and data retrieval, leading to a resurgence in demand for the CPU. Nvidia announced its first data center CPU, Grace, in 2021, and now has an entire CPU only rack for its latest Vera processors, from GPUs to CPUs, Cuda software to full rack scale systems like Vera Rubin, there is no doubt that Nvidia's technology is the
very backbone on which AI is built. The questions now go far deeper for the man who built Nvidia and for the future of Nvidia itself. Is Nvidia too big to fail? Yes. This is a company that has hundreds of billions of cash on the balance sheet, owns meaningful shares of the most important companies in the world. The unwind would be almost impossible. There's no way there's enough capacity in the world to move what they have planned to build to others, so I think it can survive.
It is bigger than an individual.
