Nvidia chips

Pivot mastery: Nvidia’s AI Category journey

Written by Jonathan Simnett

In a year of ongoing company consolidation and death in tech, GPU chipmaker Nvidia’s one-day market value increase this week was remarkable.

It was the largest rise in Wall Street history ever, outpacing even Meta Platforms’ record gain of $196 billion on February 2nd.

FOMO and boom

On the back of reporting another stunning set of earnings, record sales of $22.1bn in its fourth quarter, the company witnessed an astonishing 16.4% surge in its share price on the NASDAQ exchange, boosting its valuation by $276.7 billion. To put this in context, it surpassed the market capitalizations of both chip maker Advanced Micro Devices and Bank of America, and even exceeded the entire $265 billion market value of global sugared water vendor Coca-Cola.

Nvidia’s dominance in the high-end AI chip market, injected new impetus into the fear-of-missing-out (FOMO) AI stock trade and even contributed significantly to the broader stock market rally  A sure sign that the artificial intelligence (AI) boom that appears to be revitalising Silicon Valley, is in full swing and is affecting the broader economy

Category pivot of genius

But what is more fascinating about this goldrush is that it is the result of a Category pivot of genius that Nvidia has pulled off. It is currently believed to have over 90 per cent of the market share for AI GPUs and plans to release its next generation GPU called the B100 in 2024.

From Nvidia’s founding in 1993, CEO Jason Huang and his two co-founders clearly thought in terms of Category and the re-framing of customer demand.  They started by predicting a wave of accelerated computing, specifically in graphics-based processing. GPU, of course, stands for Graphics Processing Unit and their re-framing of customer demand was based on the customer FOMO of not being able to tackle business challenges beyond the capability of the general-purpose computing of the ‘90s.

Business and consumer

They also realised that rapidly growing consumer video games would demand high performance chips but would have incredibly high sales volumes. Video games became the company’s flywheel, funding the huge R&D spend that would keep them ahead in both markets. No wonder the company was quick to attract the attention of A-list West Coast VC investors such as Sequoia Capital.

From 2014, Nvidia diversified its business focusing on three markets: gaming, automotive electronics, and mobile devices.  But within this strategy, masked by endless product announcements, company acquisitions, a high-profile industry spat with Apple and a failed attempt to buy chip designer Arm, something more important was happening.

Nvidia was pivoting from leading the high performance computing chip Category leader to re-framing itself as the high performance AI enabling chip leader and was busy building its surrounding ecosystem and addressing new applications to the point where Nvidia’s web search slogan is now `the World Leader in Artificial Intelligence Computing.` 

The AI journey

One of the first pieces of evidence of this came in May 2017, when Nvidia announced a partnership with Toyota to use its Drive PX-series artificial intelligence platform for its autonomous vehicles. In July 2017, Nvidia and Chinese search giant Baidu announced a far-reaching AI partnership that included cloud computing, autonomous driving, consumer devices, and Baidu’s open-source AI framework, PaddlePaddle. In 2018, Google announced that Nvidia’s Tesla P4 graphic cards would be integrated into Google Cloud service’s artificial intelligence.

In October 2020, Nvidia announced a $100 million investment to build the massively powerful Cambridge-1 computer that employs AI to support healthcare research and, in September 2023, Getty Images said that it was partnering with Nvidia to launch Generative AI by Getty Images, a new tool that lets people create images using Getty’s library of licensed photos.

The lessons for Category creators

What this tells us is that to remain a Category leader you will have to evolve your Category and pivot on your strengths to re-frame customer demand. It tells us that creating Category leadership doesn’t happen overnight – it’s taken Nvidia nearly a decade to get there. 

It demonstrates Category creators experience much faster growth and receive much higher valuations from investors than companies bringing only incremental innovations to market. It reminds us, too, as the leader your competitors have to respond, validating your position.  It’s no accident that AMD’s web search slogan is now `Together we advance AI`

But, most of all, it reminds us that Category leaders accrue a massively disproportionate amount of value available in any market and that is worth every day of the effort required to do so. 

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