Study of NVDA
Nvidia briefly eclipsed Microsoft and Apple this month to become the world’s most valuable company in a remarkable rally that has fueled much of this year’s gains in the S&P 500 index. At more than $3 trillion, Huang’s company was at one point worth more than entire economies and stock markets, only to suffer a record loss in market value as investors locked in profits.
Yet as long as Nvidia chips continue to be the benchmark for AI training, there’s little reason to believe the longer-term outlook is cloudy and here the fundamentals continue to look robust.
One of Nvidia’s key advantages is a sticky AI ecosystem known as CUDA, short for Compute Unified Device Architecture. Much like how everyday consumers are loath to switch from their Apple iOS device to a Samsung phone using Google Android, an entire cohort of developers have been working with CUDA for years and feel so comfortable there is little reason to consider using another software platform. Much like the hardware, CUDA effectively has become a standard of its own.
- 06/27/2024 – Nvidia’s Market Cap Plummets $500 Billion as CEO Jensen Huang Fails to Reassure Skittish Investors | Watch (msn.com)
Nvidia’s market cap dropped around $500 billion since it became the world’s most valuable company. Skittish investors were awaiting comments at its annual meeting that might reverse the trend. CEO Jensen Huang discussed Nvidia’s success but didn’t offer new information on how it will compete with rivals or details on its next-gen AI chip, Blackwell. Huang failed to provide a timeline for when Blackwell will be available, though he said it will be Nvidia’s most successful product. The stock stayed down more than 2% after the meeting.
Hotz is right about identifying one of Nvidia’s biggest advantages: It’s not Nvidia’s hardware, it’s its software. Cuda, the middleware layer that is used to implement A.I. applications on Nvidia’s chips, is not only effective, it is hugely popular and well-supported. An estimated 3 million developers use Cuda. That makes Nvidia’s chips, despite their expense, extremely sticky. Where many rivals have gone wrong is in trying to attack Nvidia on silicon alone, without investing in building a software architecture and developer ecosystem that could rival Cuda. Hotz is going after Cuda.
But there is more to Nvidia’s market dominance than just powerful silicon and Cuda. There’s also the way it can link GPUs together inside data centers. One of Huang’s greatest acquisitions was Israeli networking company Mellanox, which Nvidia bought for $6.9 billion in 2019. Mellanox has given Nvidia a serious leg up on competitors like AMD. Michael Kagan, Nvidia’s chief technology officer, who had also been CTO at Mellanox before the acquisition, recently told me that one of the ways Nvidia had wrung more efficiency out of its data center GPUs was to move some of the computing into the network equipment itself. (He likened it to a pizza shop that, in order to get more efficient, equipped its delivery drivers with portable ovens so the pizza would finish cooking as the delivery driver drove it to a customer’s house.) And Nvidia isn’t sitting still when it comes to networking either. At Computex, the company announced a new ethernet network called Spectrum X that it says can deliver 1.7 times better performance and energy efficiency for generative A.I. workloads.
Improvements like this will make Nvidia very hard to catch. Of course, Nvidia isn’t perfect. And we’ll have more on one area of the generative A.I. race where it may have stumbled in the Brainfood section below.
