Jensen Huang resigns from Nvidia after spy-linked affair allegations

What changed at Nvidia?

The Guardian reported that Nvidia’s valuation fell from $5tn in October last year to about $4tn this week after allegations that co-founder and chief executive Jensen Huang had affairs with a Chinese spy and a Nvidia executive. Huang resigned on Thursday, ending his tenure at the company he founded in 1993.

The decline followed Nvidia becoming the first company to reach $5tn. Six months after the launch of ChatGPT, its valuation reached $1tn (£756bn) in May 2023 and kept growing.

The report did not quantify how much of the fall followed the allegations rather than broader market trading. Nor did it publish supporting evidence, identify the alleged partners, quote an Nvidia explanation, or describe leadership succession (an arrangement for his replacement).

Takeaway: Nvidia faces a founder-integrity problem alongside its AI growth.

How did Huang rise from Denny’s to Nvidia’s summit?

As a teenager in the United States, Huang’s first job was waiting tables and washing dishes at a Denny’s branch. “It teaches you humility, it teaches you hard work, it teaches you hospitality,” he said in 2023 of his time at the diner chain.

By 2025, The Guardian described Huang as one of the richest people on the planet and a “rockstar” of the AI boom, feted by investors, technology executives and politicians. His trademark leather jacket became part of that public image. At an Nvidia event that year, he donned a Denny’s apron in tribute to his former employer.

The Guardian reported that Huang, 63, was born in Taiwan to a chemical engineer father and a schoolteacher mother. After a spell in Thailand, he moved to the US at 10 and is now a joint citizen of Taiwan and the US. He has said he is “always an immigrant.”

An uncle accidentally enrolled him in a juvenile reform school in Kentucky. Huang anglicised his name, attended high school in Oregon and, according to The Guardian, showed educational flair.

He graduated from Oregon State University in 1984 with a degree in electrical engineering, where he met Lori, his future wife. They have a son and a daughter, both now Nvidia employees. He completed a master’s degree in the same subject at Stanford University in 1992.

In 1993, Huang founded Nvidia with fellow engineers Chris Malachowsky and Curtis Priem during a meeting in a Denny’s booth. The name riffs on the Latin term for envy, invidia, and captures what the founders wanted rivals to feel.

Tae Kim’s biography, The Nvidia Way, credits Huang’s technical expertise with giving him an edge with customers and investors. Tench Coxe, an Nvidia board member and early investor, said: “When you meet Jensen Huang, even with dozens of other graphics companies, you realise this is a guy you want to do business with.”

Coxe continued: “What made him great is he is an engineer and he is a computer scientist.” The biography presents Huang’s engineering and computer-science background as central to his commercial credibility.

Takeaway: Huang’s rise came from engineering expertise, commercial skill and unusually strong public visibility.

Why did graphics chips become AI infrastructure?

Nvidia started by making graphics chips for personal computers. It released the GeForce 256 in 1999, which is widely regarded as the world’s first graphics processing unit (GPU).

As the technology grew more powerful, academic researchers realized it could accelerate AI development. GPUs were originally designed for video-game graphics, but their ability to perform many technical calculations simultaneously and quickly suited the data-heavy demands of AI.

Nvidia also built networks linking its chips, supplying computing power for AI systems. Its CUDA (software for accelerating AI workloads) helped those GPUs perform well for AI customers. The Guardian said Taiwan, Huang’s birthplace, had become the epicentre of chip manufacturing and the foundry for Nvidia’s highly advanced chips.

In 2012, Nvidia GPUs were used to create AlexNet, a neural network (a machine-learning model) developed at the University of Toronto by Alex Krizhevsky, OpenAI co-founder Ilya Sutskever and Nobel Prize winner Geoffrey Hinton. The Guardian described AlexNet’s development as a key moment in the history of modern AI.

Takeaway: Nvidia’s advantage rested on a full computing system, not a single chip.

How did the AI boom enrich Nvidia and Huang?

Demand for Nvidia’s products surged as hundreds of billions of dollars flowed into a technology that many AI boosters expected to transform the global economy. The Guardian compared Huang and Nvidia to the “main purveyors of shovels in the AI gold rush.”

That position made Nvidia’s chips integral to the development and operation of AI systems such as ChatGPT. It also made Huang rich, powerful and famous, according to The Guardian.

Huang’s 3.6% stake in Nvidia has provided substantial wealth. Bloomberg valued his fortune at $145bn, making him the 13th-richest person in the world.

Takeaway: The AI boom created extraordinary financial leverage for Nvidia and its founder.

How did Huang convert technical credibility into influence?

The importance of Nvidia’s products to the AI revolution made Huang rich, powerful and famous, The Guardian reported. He appeared at technology conferences and alongside global leaders, including Donald Trump, with whom he had developed a rapport. Meta founder Mark Zuckerberg described Huang as “Taylor Swift, but for tech.”

One UK technology-industry insider who met Huang at technology and government events praised his “ability to engage.” The source said: “He’s like a good politician. I think the sector has lost one of its best communicators.”

The source added that Huang had no trouble reaching the upper echelons of government. “Everyone wanted to meet him.”

Because the insider was anonymous, The Guardian’s account offers no way to test that reputation across other executives or institutions. It remains an indicator of Huang’s perceived communication power, not an objective measure.

Takeaway: Huang’s influence extended beyond Nvidia’s products into government access and technology-industry celebrity.

What did Stephen Witt see in Huang’s final interview?

Stephen Witt, a journalist who interviewed Huang for his award-winning book The Thinking Games, described their final chat in 2024 with a “visibly exhausted” Huang. He wrote that the executive’s voice was “crescendoing with anger” as Huang considered what new jobs AI would create.

Huang was railing against the perception that AI would take jobs. He told Witt: “We make the marginal cost of things zero, generation after generation after generation, and this exact conversation happens every single time!”

Witt’s response was blunt: “His anger seemed uncontained, omnidirectional and wildly inappropriate.” The passage makes no attempt to separate Huang’s argument about marginal costs from the emotion behind his delivery.

The same book balances that criticism with a concession. Witt states: “Huang possessed magnetic charisma, could be funny as hell, and, when he wasn’t losing his shit, was capable of warmth and great empathetic understanding.”

According to Witt, Huang’s anger wore off as he added: “I am super normal.” The exchange captures both the force of Huang’s public persona and the volatility visible in private conversation.

Takeaway: One private exchange does not define Huang, but it shows how personal anger could disrupt his usual communicator role.

What remains unanswered after the resignation?

The source attributes Huang’s departure to allegations that he had affairs with a Chinese spy and a Nvidia executive. It does not name the alleged partners, present evidence, quote an Nvidia statement, or describe any board inquiry or replacement process.

Those omissions limit what can responsibly be concluded. The report documents a sharp valuation reversal and a resignation, but it does not establish the underlying facts. The Guardian characterized extramarital infidelity as a very normal failing and framed the collapse as a reversal of the humility Huang learned during his shifts at Denny’s.

Takeaway: The immediate test is whether AI demand can sustain Nvidia’s roughly $4tn valuation after the departure of the founder who anchored its technical credibility and public visibility.