How A Shifting AI Chip Market Will Shape The Future Of Nvidia

The AI chip battle that Nvidia has dominated is already shifting to a new front—one that will be much larger but also more competitive.

- Asa Fitch

Nvidia built itself into a $2 trillion company by supplying the chips essential for the incredibly complicated work of training artificial intelligence models. As the industry rapidly evolves, the bigger opportunity will be selling chips that make those models run after they are trained, churning out text and images for the fast-growing population of companies and people actually using generative AI tools.

Right now, that shift is adding to Nvidia's blockbuster sales. Chief Financial Officer Colette Kress said this past week that more than 40% of Nvidia's data center business in the past year - when revenue exceeded $47 billion - was for deployment of AI systems and not training. That percentage was the first significant indication that the shift is underway.

Kress's comments allayed some concerns that the shift toward chips for deploying AI systems those that do what is called "inference" work threatens Nvidia's position because that work can be done with less powerful and less-expensive chips than those that have made Nvidia the leader of the AI boom.

"There is a perception that Nvidia's share will be lower in inferencing vs. training," Ben Reitzes, an analyst at Melius Research, said in a note to clients. "This revelation helps shed light on its ability to benefit from the coming inferencing explosion."

Many rivals believe they have a better shot in the AI market as chips for inferencing become more important.

Intel, which makes central processing units that go into data centers, believes its chips will be increasingly appealing as customers focus on driving down the cost of operating AI models. The kinds of chips Intel specializes in are already widely used in inferencing, and it isn't as critical to have Nvidia's cutting-edge and more expensive H100 AI chips when doing that task.