NVIDIA is speedrunning accelerated computing adoption across industries to entrench itself in all economic verticals

CUDA moat will be overcome but it won't matter; Jensen uses AI-hype cycle to rapidly diffuse accelerated computing and thus build a deeper moat than CUDA ever was; margins will remain high for decades

NVIDIA had an incredible, rollercoastery ride in 2024 so far. Much has been said about the reason for NVIDIA's dominance, which initially baffled many. A year ago, Wall Street saw NVIDIA's run-up as fake, hyped, and a sign of tulip-like exuberance, some still do. But the rally only started there and every quarter P/E ratios faithfully returned to average values after each earnings beat. Thus, investors looked more closely and came to embrace NVIDIA's "CUDA moat" as the answer to its margins and unique market position. This story sustained NVIDIA's rally through its June 2024 stock split. Recently, AI chip stocks have taken a beating due to interest rate-story driven market rotations, AI ROI fears and questions about Hyperscaler CapEx sustainability. For NVIDIA specifically not only are their sales volumes in doubt but even more so the sustainability of their margins since if CUDA were the only thing justifying their green dominance then it's only a short matter of time until AMD with it's ROCm and frameworks like OpenAI's Triton open up machine learning inference to agnostic chipsets. To me, these fears are overblown. I won't be going into AI ROI and CapEx spend in this post, but instead focus on the more general 5-year picture of NVIDIA's strategic positioning with implications for the endurance or erosion of their moat and margins in the market.

To understand where NVIDIA is going, we need to first understand the character and psychology that is driving NVIDIA and its founder-CEO Jensen Huang:

Jensen sees the future a decade out due to first-principle, in-the-limit extrapolation

Jensen tells the story that in 2012 when AlexNet broke the ImageNet glas ceiling using two NVIDIA GPUs he started to see the future of AI: models would be broadly, generally useful and incredibly capable if scaled up; and his role in it: to provide the semiconductor soil on which machine learning engineers could grow their models exponentially. This led to human-level models in image recognition, image segmentation, recommender systems and recently natural language understanding and generating (read my last post on LLMs). Jensen's foresight started even before that when in the early days of CUDA around 2007 he collaborated with scientists to help them parallelize their HPC workloads on NVIDIA GPUs which were purpose-built for parallelization of graphic processing workloads. From this behavior of re-orienting the company towards AI, ten years before the release of ChatGPT, we can learn an important characteristic of Jensen and his firm: Huang is a true first-principles, in-the-limit thinker. Unfortunately these words have become buzzwords now in VC World, but having a physics background myself, I can say that it's true for Jensen.

When Jensen saw AlexNet, he broke it down to the essentials and reasoned up from there. This relatively simple model vastly outperformed all other approaches, it was trivially scalable and that scaling was assured as it depended on scaling of data (which is plentiful) and of compute (which grows by orders of magnitude every couple of years). Besides that, while AlexNet was about object recognition using CNNs, the underlying principle of autonomously learning neural network parameters using gradient descent and simple loss functions meant that what AlexNet achieved was basically domain agnostic, making machine learning of the neural network kind a strong contender for a path to generalized intelligence machines. Extrapolating out from these essential insights, the new multi-decade mission of NVIDIA became clear and Jensen was not afraid to risk the company on it which itself is culturally geared to invest way ahead of any hope of financial returns, based on first-principle analysis alone. Thus, we know Jensen has the capability to see far into the future and has the courage to create exactly that future. Now let's try to look into his psyche.

Jensen breathes Andy Grove's paranoid spirit

There is something in Jensen's psychology that is driving him to look that far into the future and move to secure his/NVIDIA's position in it. Jensen himself comes from a humble background, the typical American Dream story. Starting NVIDIA was incredibly hard and bumpy in the beginning, with 1997 turning into a make-or-break year for them. It is impossible to locate when exactly, between being brought up in Taiwan, working at Fast-Food restaurants as a youth in the US, his studies, early career and the early years of NVIDIA, but at some point did Jensen Huang develop the Andy Grove'ian "Only the paranoid" trait. The psychology of always looking over your shoulder, never becoming comfortable with your situation and working incessantly to stay ahead and stay in the clear. This guy not only loves his work, loves the technology, loves the future he is bringing about, he is also terrified about it all not working out, about NVIDIA making a mistake, about having understood a long-term trend incorrectly and about playing the wrong bets or not enough of them.

So, yes, Jensen is a true first-principles, in-the-limit thinker, but his psychology also does not allow him to become complacent or rest on his laurels. Huang looks as much into the future, to see and create everything he is fascinated by as much as he does to see where he might be wrong and how NVIDIA could fail. This creates a powerful mix which is culturally imprinted on NVIDIA and all the more potent due to NVIDIA's talent-draw and capital power which bestows them not only with the capacity to develop something out of nothing, decades in advance of it bearing fruit, but also with the stamina to stick it out for that long, without becoming ideological about it.

Now that we know how Jensen is equipped, let's dive into how and where he is driving his firm with Grove’ian paranoia to maintain NVIDIA's dominance for the long term.

NVIDIA creates markets from scratch by building bespoke SDKs to run vertical-specific applications on its GPUs

"It really is about the expansion of our accelerated computing platforms into new markets, into new companies, into new industries. That is probably the single best early indicator of near term future success if you will, within the next six months, within the next year." – Jensen Huang via Stratechery

Jensen is a market builder, an architect of ecosystems. Most prominently, CUDA was elemental in creating a software ecosystem for deep learning. On the hardware side, NVIDIA is embedded in a deep ecosystem of server builders, hyperscalers, enterprise customers and startups. In software, CUDA is way more than a LLM-accelerator: NVIDIA invested in it for over a decade to build a huge range of software development kits (SDKs) on top to enable users to accelerate their specific workloads using NVIDIA GPU parallelization just as he did with the very first scientists NVIDIA collaborated with in 2007. That's the goal. CUDA in Tensorflow and Pytorch enabled the deep learning revolution and the ChatGPT moment. Now, Jensen wants to create such moments in practically all other industries. There are no real incumbents in this space because nothing like it had been possible before. NVIDIA is making it possible.

"It’s really about the Nvidia’s SDKs and where it’s going, [they] open us directly into new worlds and those SDKs accelerate applications that people are already using." – Jensen Huang via Stratechery

NVIDIA and accelerated computing will become indispensable to most industries

In this sense, ChatGPT did not change much about the overall NVIDIA strategy of conquering "new worlds" via enabling them to do accelerated computing. What it did do is shorten timelines drastically because the "GenAI Hype" created a sociological imperative for shareholders to pressure CEOs to pressure their CIOs to "do something with AI". The AI trade has been wobbly lately and AI ROI is yet uncertain, but I believe the trend is irreversible now, because not only are LLMs economically useful as seen tangibly in Klarna and Perplexity, but accelerated computing is sound from a first principles perspective as well. So Jensen essentially uses the LLM hype to connect every industry he can with NVIDIA GPUs and co-develop industry specific accelerated computing solutions with and beyond GenAI, for example: BioPharma and Protein Design, Customer Service, Robotics, Driverless Trucking and autonomous vehicles incl Tesla, Industrial Digital Twins, ERM, and more.

“As you listen to Huang’s keynotes, and hear all the talk about their vision of the future – AI Factories, Omniverse, Digital Twins, and all the rest – take them all with a grain of salt. They are good ideas (mostly). Some of them could turn out to be incredible businesses. But they each matter less than the fact that Nvidia is willing to try all of them out. The company’s vision of the future, like its products, is not deterministic. Nvidia is playing, and playing, the odds, and that ability to take risks is the key to their success.” – Digits to Dollars, "On Paths Not Taken"

This means NVIDIA's long-term moat won't be CUDA, but it's broad accelerated computing software ecosystem embedded in an overwhelming amount of industry verticals. Jensen will not only create those markets in the first place but what NVIDIA builds here is also unlikely to be replicated any time soon by its AI accelerator competitors, who are still catching up with what CUDA has done in deep learning.

In some cases, it's not so much NVIDIA creating entirely new, zero-revenue today markets, but injecting itself and massively speeding up (20x) existent wide-spread computing processes with real economic value behind it:

"Developing new software library means opening up whole new markets, even basic ones like data processing with cuDF: SQL, spark and pandas." – What’s Next in AI: NVIDIA’s Jensen Huang Talks With WIRED’s Lauren Goode, 39min12s

NVIDIA's strategy can thus be summarized as an "up- and outwards" push, verticalizing into higher-level software ecosystem as well as hardware systems-building to nurture and establish accelerated computing in as many industries as possible, merging NVIDIA solutions into the fabric of future economies and becoming fundamentally indispensable for all kinds of applications, products and processes. At least, that's the idea.

Judging by Jensen's potent mix of decades long experience, clear-headed first-principled, in-the-limited long-term thinking, Grove'ian paranoia, an organization with proven executive aptitude and a large and growing partner-ecosystem, I see the odds for this future coming about decidedly in NVIDIAs favor. I therefore expect NVIDIA’s margins to remain ridiculously elevated for the next decade.