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‘The rocket ship keeps going off’: Inside the Nvidia phenomenon with author Stephen Witt

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For employees at Nvidia, the chipmaker at the center of the artificial intelligence boom, the financial incentives to retire are staggering, yet few are heading for the exits. According to Stephen Witt, the freelance journalist and author whose book on the most valuable company in the world, The Thinking Machine, just became the FT and Schroders business book of the year, this retention of wealthy engineers comes down to a fear of missing out on history (along with all that money, of course).

“I think if the company was selling breakfast cereal, a lot of them would retire, but they’re making what they believe to be the single most important technology of all time,” Witt told Fortune in a recent interview, referring to Nvidia’s groundbreaking GPU chips that function as something like the oil wells of the AI boom.

“They’re engineers,” Witt said of Nvidia CEO Jensen Huang, his friends, his investors, and his employees, all of whom he talked to for his deeply reported book. He described their attitude as one of “I can’t leave now … I just can’t not be working with this technology. It’s like a once-in-a-lifetime opportunity.” Acknowledging that Nvidia’s soaring valuation to a $4-trillion-plus market capitalization doesn’t hurt, Witt explained how “the rocket ship keeps going off,” both from a technological and financial standpoint. The thing is, he explained, “they’re a very generous employer, especially with employee stock purchasing programs.”

Field of GPU dreams

Nvidia’s journey was not an overnight success, according to Witt. The author described the company’s early development of GPUs for AI as a Field of Dreams scenario where it built technology “without any users, without any customers.” Seen through the lens of capitalism, developing a new technology, at least for “very long-dated technologies, the market will not work” without some kind of buffer to allow time for the tech to mature, Witt concluded: “Jensen was a singular individual, and his stock price went down, or was stagnant, for 10 years while he was developing these platforms, for people to compute. He was not rewarded for a long, long, long time for doing this.”

Nvidia’s financial performance and stock price have taken off since 2015, to Witt’s point, and began gathering steam in the 2004–07 period, when academic AI researchers discovered the benefit of Nvidia’s GPUs. And there was a long period where the stock was not generating great returns, but Nvidia’s chips were always popular with gamers, and so the market worked to at least that extent.

Witt noted that he found similar dynamics in previous reporting, having written a book about MP3 file-sharing tech in 2015 (How Music Got Free). “That was also true of those guys,” he said, who likewise faced many years of development before it paid off. “If we were working in a corporation, I don’t think anyone would have had the patience. We needed almost a third base between academia and finance to sort of make this work.” Witt cited other examples, such as neural nets and the state-sponsored TSMC, one of Nvidia’s closest rivals in the advanced semiconductor space.

Witt said his reporting revealed that many Nvidia workers were initially on the losing side of this dynamic, having bought into employee stock ownership programs and seen the stock fall 50% or 60% from there. “The employees would get upset. They’d be like, ‘Oh, my God … I invested, I maxed out my cap to, you know, an employee stock purchasing program, and … now it’s underwhelming, and I don’t know if I’ll ever make it back.” At that point, Huang instituted a program to allow workers to buy the stock at a discount to the current market price, but also at a discount to any price in the past two years. “And then the stock turned into a rocket ship,” said Witt. Soon enough, he found, “every employee started maxing out these contributions to the employee stock purchase program, and then the stock continued to go up another, like, hundred times on these very low-cost basis transactions.”

The bubble question

Now that the market has caught up, questions of a financial bubble loom. Witt, who has worked for a hedge fund and said he approaches journalism with a shareholder’s mindset, admits the possibility of a crash if cash flows don’t eventually align with infrastructure spending: “So, so much is predicated on getting the timing of cash flows correct. And it may be the case that we throw all this money into building data centers and buying Nvidia chips, and that doesn’t pay off at the exact right time, and then everything crashes for a little while. That may be happening right now.”

Yet Witt also drew a sharp distinction between financial bubbles and technological utility, saying that the now well-trod comparisons of AI to the internet and railroad booms may have some merit. But echoing similar remarks from leaders such as JPMorgan CEO Jamie Dimon, Witt said of AI: “This stuff is real.” Witt predicted that breakthroughs from Nvidia, TSMC, and others will lead fo a “spreading wave of robots and autonomy,” recalling Huang’s own prediction that in 10 years, anything that moves will be autonomous. “We’re moving into the world of AI,” Witt added, saying that in 10 years, “we will interact with AI as frequently as we interact with the internet or electricity. And there’s a big scramble on to be the company that gets it in front of me. I think that explains all the investment.”

The political dynamic

The big scramble for funding also has a political effect, of course. “Jensen was forced to become a political creature, especially this year,” Witt said, suggesting that “he kind of pivoted into being almost like Trump’s Thomas Cromwell,” likening him to the famous advisor to King Henry VIII, although Huang is a close external advisor and not in Trump’s cabinet, with someone like Treasury Secretary Scott Bessent or Commerce Secretary Howard Lutnick a much closer analogue. (Witt said as an aside that he’s been reading Hilary Mantel’s modern classic Wolf Hall lately, and the subject was on his mind.) On Huang and Trump’s relationship, Witt added: “He became, like, a real advisor in the game … And he was really successful in that regard.”

Witt observed of the dynamic that “Trump likes to be close to Jensen because Jensen’s a winner. And Trump likes winners, and Jensen’s basically the biggest winner there is right now.” Huang also needs certain support from the federal government, Witt added, not just exemption from tariffs for Taiwan, but also in selling certain chips to China. “Maybe even most importantly, and maybe least discussed, he needs absolutely to secure an ongoing pipeline of H-1B visas for his best technical work,” Witt said, noting that one-third, if not more, of Nvidia’s employees are South Asians. “They’re extremely dedicated, they’re extremely bright, and it’s part of really what makes Nvidia work.”

Ultimately, Nvidia’s soaring valuation is underpinned by a new geopolitical narrative. Witt argues that the U.S. is engineering a merger between Silicon Valley and the Pentagon, fueled by fears of an “AI gap” with China. “Just as in the old days,” Witt said, “you would talk about the fear of a missile gap with the Soviet Union. Now, it’s an AI gap with China.” And on that count, Witt added, Trump likes winners, “and he’s got a winner in AI.”



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Epstein files: Trump, Clinton, Summers, Gates not returning any results in search bar

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The Justice Department released a massive trove of files related to the late sex trafficker Jeffrey Epstein on Friday, but the site housing the information was failing to turn up any results.

The data dump came on the deadline that Congress established last month for disclosing the highly anticipated information, though a top Justice official suggested that not all the documents would come out at once with more due in the coming weeks.

While President Donald Trump, former President Bill Clinton, former Treasury Secretary Larry Summers, Microsoft cofounder Bill Gates and scores of other powerful men have been linked to Epstein, their names failed to come up in a search of DOJ’s “Epstein Library.”

“No results found. Please try a different search,” the site says after queries for their names.

The site adds that “Due to technical limitations and the format of certain materials (e.g., handwritten text), portions of these documents may not be electronically searchable or may produce unreliable search results.”

However, Clinton also appears in photos that were released as does the late pop singer Michael Jackson. Other records were heavily redacted.

Deputy Attorney General Todd Blanche told Congress that the Justice Department had identified 1,200 victims of Epstein or their relatives and redacted materials that could reveal their identities, according to the New York Times.

Last month, an overwhelmingly bipartisan vote in Congress produced legislation to force the Trump administration to release the DOJ files, though emails and photos from Epstein’s estate had already come out.

One of the sponsors of that legislation, Rep. Ro Khanna, warned on Friday that if DOJ doesn’t show that it’s complying with the law, Congress could hold impeachment hearings for Attorney General Pam Bondi and Blanche.

Earlier on Friday, Blanche told Fox News that “several hundred thousand” pages would be released on Friday. “And then, over the next couple of weeks, I expect several hundred thousand more,” he added.

This story was originally featured on Fortune.com



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Want a job in AI-era tech? Forget prestigious degrees—tech leaders want to see your GitHub projects and internships

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For decades, computer science has been sold as one of the surest paths to economic security. And leaders across politics and industry—from former President Bill Clinton and Secretary of State Marco Rubio to Steve Jobs and Bill Gates—have at times urged students not to overlook the field, framing coding skills as the secret to stable, high-paying jobs.

But as artificial intelligence rapidly reshapes the workplace, that promise is starting to look less certain.

A new survey of more than 200 engineering leaders, conducted by tech training nonprofit CodePath and shared exclusively with Fortune, shows entry-level tech hiring is slowing. More than one-third of respondents, 38%, said their company has reduced the number of entry-level hiring over the past year, and nearly 1 in 7 reported pausing Gen Z hiring altogether.

At the same time, 18% said hiring had stayed the same, and 8% reported an increase. Despite the overall slowdown, CodePath CEO Michael Ellison—a Y Combinator alum—argues telling people to avoid tech right now would be a mistake.

“That’s just kind of like taking crazy pills if you end up choosing not to invest in the tools that make you the most powerful—of telling computers what you want them to do in an age where computers are becoming exponentially more powerful,” Ellison told Fortune. “So to me, it’s like saying, ‘don’t learn how to use the internet.’”

Ellison’s argument reflects a broader shift in how computer science fits into the AI economy. As generative AI tools become more capable, understanding how software works—and how to direct, customize, and integrate AI systems—is increasingly seen as a foundational skill rather than a specialized one.

That demand is already showing up in the labor market. AI literacy topped LinkedIn’s list of the skills professionals are prioritizing and companies are hiring for right now. And a Lightcast analysis of more than 1.3 billion job postings in 2024 found roles advertising at least one AI or generative AI skill offered an average of $18,000 more in annual compensation that those that did not.

Notably, the majority of those roles were outside the tech sector. Some 51% of jobs requiring AI skills were in non-tech industries, up from 44% in 2022—a sign coding and AI fluency are becoming relevant far beyond Silicon Valley.

The new secret to landing a tech job

Still, slowing hiring doesn’t mean aspiring technologists should give up. Instead, the CodePath data suggests candidates may need to rethink what they emphasize—and what they leave off—when applying for tech roles.

When asked which signals matter most outside the interview process, engineering leaders indicated proof of real-world skills matter far more than formal credentials. Side projects or portfolios topped the list, cited by 38% of respondents, followed by internship experience (35%), and public code portfolios like GitHub (34%).

Traditional markers of achievement, by contrast, carried far less weight. Just 4% of leaders said credentialing programs were a top influence in hiring decisions, while only 23% cited a candidate degree or academic focus and 17% pointed to school prestige.

The shift away from pedigree suggests employers are seeking evidence candidates can actually do the work. Greater fluency with AI tools and frameworks was the most common skill expectation for early-career hires, followed by faster time to writing production-ready code and the ability to learn new tools or programming languages quickly.

And despite buzz about tech layoffs, job opportunities do still exist. The U.S. federal government, for example, recently announced it would be hiring about 1,000 new engineers, data scientists, and AI specialists. No degrees or work experience is required—and salaries will range from $150,000 to $200,000. Meta has also still been hiring young talent in recent weeks, with job postings for roles such as product software engineers.

Ellison’s advice for those seeking roles is simple: Opportunities are out there as long as you are willing to dig in deeper—and build a portfolio that hiring managers are looking for.

“People are rewarded for being aggressive and for going after what they want,” he said. It’s surprising the opportunities that are hidden in plain sight.”

This story was originally featured on Fortune.com



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You’re not imagining it: The AI job squeeze isn’t some future apocalypse, it’s already quietly underway. 

Professor Yoshua Bengio spent four decades building the technology that is now coming for your job. He is a computer science professor at the Université de Montréal, a Turing Award winner, and one of the most-cited scientists in the world on Google Scholar—and now he’s turned his back on his life’s work to warn that your job is probably already under threat. 

Desk jobs, or as Bengio called them, “cognitive jobs, the jobs that you can do behind a keyboard,” will be the first casualties of automation. 

“It’s just a matter of time,” the AI pioneer stressed on Steven Bartlett’s Diary of a CEO podcast.

“Unless we hit a wall scientifically, like some obstacle prevents us from making progress to make AIs smarter and smarter, there’s going to be a time when they’ll be doing more and more, able to do more and more of the work that people do … And then, of course, it takes years for companies to really integrate that into their workflows, but they’re eager to do it. So it’s more a matter of time than, is it happening or not?”

And he admitted that it’s Gen Z new-hires who are currently being hit hardest by AI, as junior roles are the easiest to cut, consolidate, or backfill with software—but eventually everyone’s jobs will be impacted within five years.

It’s not just office jobs that are at risk; even trade jobs and democracy itself are threatened 

For years, degrees were pushed as the key to success for the young and aspirational looking to nab well-paying and stable jobs. But now, even highly educated students are finding themselves “unemployable” as employers launch a “wait-and-watch strategy” in the midst of AI. Graduates in the U.K. are facing the worst job market since 2018. And companies like Intel, IBM, and Google have been freezing thousands of would-be new roles that AI is expected to take over in the next five years.

But it’s not just a blip or a reflection of the current economy, Bengio warned. As more firms lean on AI and eventually robots, too, the technology will only get smarter, he said. 

“As companies are deploying more and more robots, they will be collecting more and more data. So eventually, it’s going to happen,” Bengio said when asked whether AI will be able to wipe out all work. Even young people trying to outsmart automation by ditching degrees or upskilling into trade jobs are destined for the same dead end.

“So if you do a physical job—as Geoffrey Hinton is often saying, you should be a plumber or something—it’s going to take more time [for AI to replace your job], but I think it’s only a temporary thing.” 

Now, knowing the devastation AI could cause, Bengio said he regrets his life’s work. 

“I should have seen this coming much earlier, but I didn’t pay much attention to the potentially catastrophic risks,” the 61-year-old admitted. “But my turning point was when ChatGPT came, and also with my grandson, I realized that it wasn’t clear if he would have a life 20 years from now, because we’re starting to see AI systems that are resisting being shut down.”

He’s since founded LawZero, a nonprofit organization focused on building safe and human-aligned AI systems. But at the current rate of change, his warning is clear: It’s not just jobs, even democracy could collapse in as little as two decades.

His message for CEOs? “Step back from your work. Talk to each other, and let’s see if together, we can solve the problem. Because if we are stuck in this competition, we’re going to take huge risks that are not good for you, not good for your children.”

Join us at the Fortune Workplace Innovation Summit May 19–20, 2026, in Atlanta. The next era of workplace innovation is here—and the old playbook is being rewritten. At this exclusive, high-energy event, the world’s most innovative leaders will convene to explore how AI, humanity, and strategy converge to redefine, again, the future of work. Register now.



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