Think about Tesla charging extra for features like Autopilot, then look at your GPU card, and you'll get the idea

GTC Nvidia has laid out its roadmap, of sorts, to a trillion dollars in revenue.

That ten-figure revenue 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 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 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 $300 billion 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.

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

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.

VR universe revenues

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 $150bn software opportunity based on two opportunities. First, a per seat software subscription for professional designers and creators, which we estimate at 45 million [users] and second, a per-robot software subscription for digital twins, based on more than 10 million 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 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, 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. ®