I am becoming increasingly convinced, along with other observers and no less a figure than Colette Kress, Nvidia’s chief financial officer, that Nvidia is transforming from a cyclical hardware business into a recurring subscription enterprise software business with massively increased sales.
The implications for the valuation of the business are mind blowing. The recent move to a $1 trillion valuation could be just the beginning.
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Graphics processor veteran NVIDIA (NVDA 3.62pc) reported second-quarter results on Wednesday, Aug. 19. The results edged out analyst expectations and the headlines highlighted the fact that data centre sales outweighed gaming products for the first time in NVIDIA’s history.
If you look a little closer at NVIDIA’s report and earnings call, you’ll find evidence of an even more significant change to the company’s business model. Yes, semiconductor designs are still at the core of NVIDIA’s day-to-day operations, but the company is also growing its software sales. That road points to wider profit margins and more reliable revenue streams in the long run because most of NVIDIA’s software sales are tied to long-term subscription packages.
The company is not yet ready to break out software sales and operating profits into separate line items in its quarterly reports. Instead, we have to look for clues like management comments in order to see the business category gaining momentum.
The software sales largely fall into three separate buckets.
- AI: NVIDIA supports several software frameworks for artificial intelligence (AI) number-crunching, all optimized to take full advantage of GeForce graphics chips and Tesla (TSLA 1.66pc) high-performance computing processors. The NVIDIA DIGITS neural network training system is an in-house solution for which NVIDIA offers enterprise-grade support services.
- Self-driving cars: The NVIDIA DRIVE AGX Orin platform is a self-driving car system that’s both built around NVIDIA’s high-performance math processors and designed like a modular software product. Upgrades, bug fixes, and new features can be added through over-the-air software updates, and many features are available under subscription-style licensing terms. The Mercedes-Benz division of German automaker Daimler AG recently committed to a DRIVE AGX partnership that will put NVIDIA-powered Mercedes cars on the road by 2024.
- Data centre networking: Through the recent acquisitions of Mellanox and Cumulus Networks, NVIDIA has become a significant force in the market for software-defined data centre networks. This ultra-flexible network management approach comes with multiyear license and support agreements, pushing NVIDIA even further into the realm of software-based business.
NVIDIA Loves the Data Centre
The AI and data centre networking efforts are really two sides of the same ambitious enterprise computing coin. NVIDIA’s management is putting together a top-to-bottom data centre framework that should generate strong growth for years to come. It’s all based on software-defined virtual computing services, which, in turn, depend on NVIDIA’s processors. Building the best processors or the fastest computer systems isn’t the name of the game anymore. It’s more about managing an entire data centre like a single unit that can be split up and directed to various services with the help of systems management software.
“Going forward, you optimize at the data centre scale,” said NVIDIA CEO Jensen Huang. “And the reason why I know this for a fact is because if you’re a software engineer, you would be sitting at home right now and you would write a piece of software that runs on the entire data centre in the cloud. You have no idea what’s underneath it, nor do you care.”
The architecture starts with great microchips, but Huang sees software taking the whole system to another level.
“Now we take this thing all the way through systems, the system software, algorithms, networking, all the way up to the entire data centre And the difference is absolutely shocking,” he said. “You know, we built our data centre, Selene, and it took us four weeks … It is the seventh-fastest supercomputer in the world, one of the fastest AI supercomputers in the world.”
And the software focus isn’t exactly a new idea for NVIDIA. The market success you see today started with development efforts and design decisions many years ago.
“NVIDIA is a software-defined company today,” Huang said, “with rich software content like GeForce NOW, NVIDIA virtual workstation in the cloud, NVIDIA AI, and NVIDIA Drive that will add recurring software revenue to our business model.”
It should be pretty clear from this report that NVIDIA is leaning into subscription-based software sales in a big way. The company is following the lead of pretty much every enterprise software giant on the market, all of whom have been trading in their old single-sale software licenses for repeatable subscription sales in recent years. Many things can be sold as a service these days, including NVIDIA’s data centre networking tools and artificial intelligence platforms.The Motley Fool, 21 August 2020
The interesting thing about this article is that it was written nearly three years ago since when Nvidia’s software sales will have made enormous progress and, as we know, it is becoming a key player in AI and its cleverer brother, generative AI.
I then found another amazing article outlining Nvidia’s journey to $1 trillion in revenue (that compares with last quarter’s Q1, 2024, $7bn and the forecast of $11bn for the second quarter which so stunned Wall Street.
Nvidia Has Laid Out its Roadmap, of Sorts, to a Trillion Dollars in Revenue.
That sales projection has no timeline, and is ambitious considering the revenue from the most recent financial year was just $26.9bn, up 61 percent annually. The GPU giant’s GTC (GPU Technology Conference) event this week indicated its path at least involves extracting repeat revenue from software that runs atop Nvidia’s hardware. This has been apparent for a while now, from past statements and launches.
GTC focused heavily on AI and graphics applications that cut across Nvidia’s GPU, CPU, data processing, and automotive offerings. It is Nvidia’s belief that software in the long run will generate more cash through subscriptions and upgrades than money coming in through one-time hardware shipments. These subscriptions will be tied to the software layer of Nvidia’s full stack of technology.
Nvidia CFO Colette Kress broke down the $1tr revenue opportunity, saying $100bn could come from gaming, $300bn from chips and systems, $150bn from AI Enterprise software, $150bn from Omniverse Enterprise software, and $300bn from the automotive sector.
As an example, Nvidia is helping car makers to put Netflix-style subscription services to enable features like autonomous driving, from which Nv will presumably take some kind of cut. Mercedes Benz and Jaguar Land Rover will put autonomous cars with Nvidia’s computers and software on the roads in 2024 and 2025 respectively, it is hoped.
“These services give OEMs (Original Equipment Manufacturers) an exciting opportunity to transform their business model like we have seen Tesla do with their Autopilot software that has grown in price from less than $5,000 to $12,000 a car today,” said Ali Kani, vice president and general manager of Nvidia’s automotive division, during an investor day presentation that ran alongside GTC.
Software represents a vast majority of the $300bn automotive opportunity, said Kress at the investor meeting.
“Our software content per vehicle can be in the thousands of dollars over the lifetime of the vehicle compared to the hundreds of dollars for the hardware. And second, software scales with the installed base of vehicles, not annual production,” she added.
Nvidia’s automotive business has three components: the Drive software stack for autonomous driving; in-vehicle hardware; and the datacenter infrastructure for management, training, and simulation, which were all upgraded at GTC.
Preeminent automotive chip players, such as Renesas and NXP, are largely focused on supplying the components. Nvidia’s full-stack approach takes some stress away from vehicle makers by providing the necessary tools and resources to train, test, and deploy complex AI systems. Intel and Qualcomm, and others, are also offering auto chips, but largely work with partners, like with the PC and smartphone markets.
Virtual Reality is Expensive
Nvidia is also placing big bets on what it calls the Omniverse and Facebook’s Meta has called the Metaverse, which are virtual-reality universes in which users can play, interact, and build things. Nvidia sees opportunities in the hardware, and tools for creation and collaboration, for these 3D immersive spaces.
The ‘verse opportunity could be expensive for Nvidia’s consumer GPU users.
“The graphics required to deliver a cinematic VR experience in a massive multiplayer, physically accurate world will likely require three to four orders of magnitude more than the performance of our highest-end GPUs,” said Jeff Fisher, senior vice president of gaming at Nvidia, during the investor conference. That means physical upgrades and software to make use of it.
He also threw in buzzwords about virtual economies within the ‘verses, with NFTs, real-estate, and cryptocurrencies as the backbones of it all.
“The GPU is offering more value than ever. Based on our data, they are spending $300 more than they paid for the graphics card they replaced,” Fisher added.
There are three billion gamers globally, the number is growing every year, and there is no difference in hardware (GeForce hardware) and software (GeForce Now in the cloud) revenue opportunities, Kress claimed.
“The per user pricing is similar and annualizes at over $100 per year,” Kress said.
Nvidia also expects to generate close to $150bn in subscription software through enterprise use of Omniverse, which is aimed at engineers and designers who want to build and simulate things in a 3D VR space.
“We also estimate a $150bn software opportunity based on two opportunities. First, a per seat software subscription for professional designers and creators, which we estimate at 45m [users] and second, a per-robot software subscription for digital twins, based on more than 10m factories and warehouses,” Kress said.
At GTC, Nvidia also announced the Enterprise AI 2.0, aka “the operating system of AI,” Manuvir Das, vice president of enterprise computing at Nvidia, said during the investor conference.
Compared to its 1.0 predecessor, the software has expanded hardware support with the ability to run on CPU or GPU parts, as opposed to only GPUs. The software will also run on virtualized and bare metal servers, with support for VMWare, Red Hat, and other platforms in major public clouds, compared to only VMware support in its predecessor.
“For Nvidia AI Enterprise, we estimate the total available opportunity at $150bn based on the installed base of enterprise servers and our per server software pricing,” Kress said.
Nvidia’s software assets are built on the closed-source CUDA (parallel programming for GPUs) framework, which Nvidia considers a crown jewel. At GTC, the company announced more than 60 updates to CUDA-related software libraries, including frameworks for quantum computing, 6G networks, robotics, cybersecurity, and drug discovery.
“With each new SDK (software development kit), new science, new applications and new industries can tap into the power of Nvidia computing. These SDKs tackle the immense complexity at the intersection of computing algorithms and science,” said CEO Jensen Huang during a keynote on Tuesday.
It’s interesting that Google has opted for a build approach, creating its own AI accelerators in the cloud and in handheld devices, and Facebook is taking a buy approach, using Nvidia’s GPUs and AMD CPUs for its research.The Register, 25 March 2022
I am starting to becoming interested in Colette Kress, who is emerging as a key figure in the Nvidia story.
The implications of Nvidia becoming primarily an enterprise software company with sales of $1 trillion, much of it recurring and with software profit margins, are staggering for the valuation of the business. If this objective is achieved the company is going to be worth at least $10 trillion, maybe more taking the shares to at least $4,000.
The chart does not tell us anything that dramatic but is compatible with a continued strongly rising trend.
The chart shows an extended base pattern stretching over some 15 years, an explosive breakout and then two consolidations, from the latest of which the shares have just broken decisively higher. My guess is that Nvidia could reach a $2 trillion valuation with surprising speed.
Strategy – Fundamentals and a Chart Befitting the World’s Most Exciting Company
The transition by Nvidia into becoming an enterprise software business is a massive ‘something new’ which is going to play out over many years. We have just had a powerful buy signal from the 6m moving averages. These buy signals are rare and I believe should be acted upon.
The more I learn about Nvidia the more amazing I think this company is and as they grow the innovation engine at the heart of the business can only become more powerful in a virtuous circle of growth.
Obviously it is easy for Colette Kress to pluck figures out of a hat showing how Nvidia could reach $1 trillion in revenue but they show the scale of the group’s ambition and in the light of what is happening now at the business they are not absurd.
The graphic below shows how Nvidia’s sales have grown since the year to 31 January 2015. Analysts are looking for $43bn for 2024 and $52bn for the year to 31 January 2025. If sales grow at the same pace over the next 10 years 2035 would see revenue close to $600bn. If sales growth accelerates as seems likely then 10 years from now we could reach that $1 trillion revenue figure.
These are guesses but the fact that such numbers are in the conversation shows what an exciting business Nvidia is and don’t forget that this is a company at the heart of a technology revolution which is showing signs of going exponential. The next, 2024, bar on the chart below is expected to be around $43bn.
Generative AI is driving exponential growth in compute requirements and a fast transition to NVIDIA accelerated computing, which is the most versatile, most energy-efficient, and the lowest TCO [total cost of ownership) approach to train and deploy AI. Generative AI drove significant upside in demand for our products, creating opportunities and broad-based global growth across our markets.Colette Kress, CFO, Q1 2024, 6 June 2023
Exponential growth in compute requirements is a phenomenally exciting development for Nvidia.
Nvidia NVDA. Buy @ $422