Nvidia: Rider of the AI Wave

IT TAKES TIME to become the world’s most valuable company. In Nvidia’s case, that was about 31 years. It was in 1993 that three men got together at a restaurant in California to make a decision on forming a company. Of those founders, Nvidia is now identified with one name— Jensen Huang, its chief executive officer. From what was just one among numerous startups vying for the same slice of the computer graphics market, Nvidia on June 18 overtook Apple and Microsoft, who had been shuffling each other at the top for the last five years, with a market capitalisation of $3.34 trillion. No one would have predicted this even a few years ago. Consider what has happened to its stock price: it was $5 in 2019 and now it is at $135—twenty-seven times. It has nearly tripled since the beginning of the year.

What changed to make a company making a component inside computers that the general public is not even aware of touch such stratospheric highs? The answer: generative artificial intelligence (AI). With everyone realising AI has arrived, it has also become clear that the chips most relevant to this era, the one that trains the incredible amounts of data that lead to the illusion of intelligence, are GPUs. Nvidia holds a near monopoly in GPUs. What it does is summarised in Huang’s LinkedIn profile: “Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. GPU computing went on to ignite modern AI—the next era of computing—with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.” When they began, however, AI was nowhere in the picture. They were interested in video games. In a 2017 interview to Fortune, Huang recounted them realising that video games offered very computationally challenging problems on one hand, but huge sales volume on the other. “Those two conditions don’t happen very often. Video games was our killer app—a flywheel to reach large markets funding huge R&D to solve massive computational problems,” he said.

It wasn’t easy. Within a few years, they had run into existential difficulty when their main product wasn’t compatible with a platform that Microsoft was promoting. They had to lay off 60 per cent of the staff and were down to their last dollar when a Japanese gaming company put in $5 million as investment to give them a breather. They reworked the product and stabilised until by the end of the decade, they were one of the two companies still standing in the GPU market.

The company also realised early that the AI era would begin, and began investing heavily into it a decade ago. The New York Times wrote last year, “The onetime industry upstart achieved that dominance by recognizing the A.I. trend early, tailoring its chips to those tasks and then developing key pieces of software that aid in A.I. development.” The GPU is used by written code of programmes, and chip manufacturers and programmers work in collaboration. One of Nvidia’s moat in AI is that most programmers work with them on their software technology. Any competitor will have to make not just better GPUs, but also get the programming community on board. Nvidia meanwhile invests billions in research and development to maintain its distance from competitors. Elements like these make the market believe the company will remain a backbone of the AI landscape for a long time.

There are however many who think that the company’s stock is in bubble territory. No matter how essential it is to generative AI, Apple still makes more in profits than Nvidia’s revenues. The Wall Street Journal compared Nvidia to Cisco, a similar provider of computing infrastructure, that also briefly became the world’s most valuable company at the height of the dotcom bubble—at that time, it was the potential of the internet, now it is AI. Cisco is still at a very good 63rd most valuable company in the world and when the hysteria of AI tempers down, Nvidia might also find it hard to remain at the top.

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