Nvidia CEO Jensen Huang revealed just how much AI is playing a part in rendering computer graphics, saying it can no longer be done without AI.

Nvidia has been on the forefront of AI development, with its GPUs powering some of the world’s most powerful AI models. Even in its traditional business, however, the company is relying heavily on AI to render graphics for computer games and other applications.

Listen to a podcast conversation on Nvidia’s use of AI to ‘infer 32 pixels.’ What’s it about?

Speaking at the Goldman Sachs Communacopia + Technology Conference, Huang emphasized the importance of AI.

Well, in our company, we use it for computer graphics. We can’t do computer graphics anymore without artificial intelligence. We compute one pixel, we infer the other 32. I mean, it’s incredible. And so we hallucinate, if you will, the other 32, and it looks temporally stable, it looks photorealistic, and the image quality is incredible, the performance is incredible, the amount of energy we save—computing one pixel takes a lot of energy. That’s computation. Inferring the other 32 takes very little energy, and you can do it incredibly fast.

So one of the takeaways there, is AI isn’t just about training the model, of course, that’s just the first step. It’s about using the model. And so when you use the model, you save enormous amounts energy, you save enormous amount of time—processing time. So we use it for computer graphics….if not for AI we wouldn’t be able to serve the autonomous vehicle industry. If not for AI, the work that we’re doing in robotics, digital biology, just about every tech bio company that I meet these days are built on top of Nvidia.

Graphics Upscaling

Upscaling is a process that renders some parts of a graphic at lower resolution for the sake of speed, and then later upscales it to a higher resolution. The first type of upscalers were spatial, and had substantial limitations.

Temporal upscalers are the next generation of the technology and rely heavily on AI for the process. As Huang describes, the demand for advanced graphics has reached the point where it is no longer feasible to rely solely on traditional processing, while AI-powered upscaling is able to deliver a solution.

The revelation is a powerful example of how companies are using AI behind the scenes, across a range of industries, to do the heavy lifting in various applications—often without the user realizing it.

AI Hallucinations

Huang’s statement also demonstrates that AI hallucination can be used in a productive way. Hallucination—where AI randomly creates fictional information—is an issue that no AI firm has been able to address, with top executives at multiple companies saying no one knows how to address it.

“No one in the field has yet solved the hallucination problems,” said Google CEO Sundar Pichai in mid 2023. “All models do have this as an issue.

“There is an aspect of this which we call—all of us in the field—call it a ‘black box,’” he added. “And you can’t quite tell why it said this, or why it got it wrong.”

Similarly, after announcing Apple Intelligence at WWDC 2024, Apple CEO Tim Cook acknowledged that hallucinations are a fact of life when working with AI.

“It’s not 100 percent. But I think we have done everything that we know to do, including thinking very deeply about the readiness of the technology in the areas that we’re using it in,” Cook said. “So I am confident it will be very high quality. But I’d say in all honesty that’s short of 100 percent. I would never claim that it’s 100 percent.”

While AI hallucinations may be a fact of life, one no one seems able to address, Nvidia is demonstrating there are practical use cases in which hallucinations are beneficial.