AI has been all about GPUs. That’s changing fast.

For years, Nvidia‘s rise has been synonymous with one idea: GPUs are the engine of artificial intelligence. They powered the training boom that turned large language models from academic curiosities into trillion-dollar ambitions. But Nvidia’s $20 billion deal with Groq is an admission that the next phase of AI won’t be won by GPUs alone.

Groq makes a very different type of AI chip called a Language Processing Unit, or LPU. To understand why Nvidia spent so much, and why it didn’t simply build this technology itself, you have to look at where AI workloads are heading. The industry is moving from training models to running them in the real world. That shift has a name: inference.

Inference is what happens after a model is trained, when it answers questions, generates images, or carries on conversations with users. It’s becoming the dominant task in AI computing, and could dwarf the training market in the future, according to estimates recently compiled by RBC Capital analysts.

This…