The Economist's cover story, September 3 (lifted in toto with links to the rest of the package):
The chipmaker’s enormous bets are how capitalism is supposed to work
NVIDIA was named in 1993 after the Latin word for envy. Sure enough, the American colossus inspires plenty of it. Insatiable global demand for its graphics-processing units (GPUs), the chips that power artificial intelligence, has made Nvidia the world’s most valuable company, worth $5.4trn. Next year it may also become the most profitable, generating $370bn in net income. By 2029 its sales could hit $1trn.Jensen Huang, Nvidia’s boss, is truly the magician at the heart of the AI boom. His firm’s share price is 14 times what it was on ChatGPT’s release in late 2022. The ten biggest public companies championing AI make up 40% of the value of the S&P 500 index. Nvidia alone accounts for 8% and unlike, say, Apple or Tesla, which make smartphones and cars, it is almost solely a bet on AI. The company has produced about 15 cents of every dollar the American stock market has returned since 2023—returns that have kept consumers spending despite rising interest rates, tariffs and a war with Iran.
Yet many also see Mr Huang as a magician in a more worrying sense, fearing that he is an illusionist inflating a dangerous bubble. Through $1trn-worth of deals, Nvidia provides data-centre landlords and AI labs with cash or guarantees so that they can buy its GPUs. Some call it the “bank of AI”. At the very least, Nvidia’s critics say, its financial engineering smacks of the “vendor financing” which pumped up the revenues of networking-gear makers like Cisco in the dotcom mania of 2000-01, whose collapse brought about a recession.
Look more closely, however, and the worries are mostly unjustified. If Nvidia’s bets on ai come good, they could accelerate the technology’s adoption, boosting productivity and living standards. If they misfire, the cost will fall chiefly on Nvidia’s shareholders. That is how capitalism is supposed to work.
True, the dotcom and AI booms share unnerving similarities: an exciting new technology, an epic bull run, hubristic tech bosses. Nvidia’s rise from seller of chips to video-gamers and cryptocurrency miners to linchpin of the economy has been so rapid that many people have yet to learn how to say its name (“en-vidia”, not “nuh-vidia”). This mirrors the ascent of Cisco, which in 2000 briefly also became the world’s most valuable firm. Just as Cisco’s sales of routers and switches presupposed exponential growth in web traffic, Nvidia’s GPU revenues assume endless demand for AI tokens.
Cisco was right about eventual demand but wrong about the timing—hence the dotcom crash. Today it is the pace of AI adoption that is hard to forecast. Set aside Claude-addled software engineers and usage remains fledgling. If it does not soon soar, Nvidia’s customers may call in the guarantees just as the chipmaker’s own sales nosedive. Since no one is sure how quickly GPUs lose their value, any used chips Nvidia repossesses may be worthless.
Nvidia’s financial wizardry is partly defensive. Its latest GPUs no longer have the market to themselves. Roughly half Nvidia’s revenue comes courtesy of America’s cloud-computing “hyperscalers”, chiefly Amazon, Google, Meta and Microsoft, which are designing their own silicon. Non-Nvidia AI chips account for 38% of the market, up from 26% in 2023. To stay ahead, Nvidia used to spend over a fifth of sales on research and development. Now it spends less than a tenth.
Last, the scale of Nvidia’s financial commitments can look terrifying. Morgan Stanley puts its overall credit exposure—ie, its modest borrowing plus support for customers—at $200bn by the start of 2029. In time Nvidia’s shadow debt could reach $300bn or more. It is a gargantuan sum: today only America’s six largest banks carry more debt.
Yet the differences from the dotcom boom are more important than the similarities. Nvidia’s balance-sheet is extraordinarily robust. The company has $99bn of cash and is churning out more. In each of the past three years annual sales have roughly doubled. Gross margins have fattened from less than 60% to 75%. Mr Huang’s cult-CEO status now rivals that of Elon Musk. But whereas Mr Musk's firms generate little cash (at Tesla) or burn lots of it (at SpaceX), Nvidia will yield about $200bn this year.
This means that, whereas Cisco used debt, Nvidia can use cash to backstop its deals with buyers of its GPUs. Even if its commitments came due and its cashflows levelled off starting next year, by 2028 it would still be less leveraged than all but 39 non-financial firms in the S&P 500 are today. Profits would need to drop by 60% from that plateau for Nvidia to forsake its investment-grade credit rating.
And demand for AI is not illusory, as it was for Pets.com and other revenueless dotcom darlings. The sales of Anthropic, the leading AI lab, shot up from $5bn in the first quarter to $11.5bn in the second. OpenAI, its main rival, is probably not far behind. The hyperscalers are also booking AI income. All told, AI may be earning American tech around $150bn a year, from nothing a few years ago. That is still far from the $2.5trn needed to cover AI capital spending, but growth is fast.
Mr Huang thinks that the biggest obstacle to the AI revolution is not lack of demand for AI but inadequate infrastructure. The markets will not provide capital on the scale that is necessary, so Nvidia is offering financing itself. Nvidia has an advantage in understanding the balance of risks and rewards. Although this bet is big enough to affect the economy, it is an entrepreneurial one. Every company that reinvests cash rather than returning it to shareholders also gambles that it can beat the market. Companies exist to make such concentrated bets. If investors want to diversify, they can do so themselves.
And Mr Huang is hardly alone. The hyperscalers, the world’s most successful companies before Nvidia came along, are making the same bet. So are some big names on Wall Street. Last month Goldman Sachs, BlackRock, Blackstone and others joined Nvidia in a $500bn data-centre initiative. And so are Mr Huang’s shareholders, who haven’t yet rushed for the exit. If they are all wrong, it is their money on the line. And if they are right, the AI era may arrive a bit sooner.
