By Dina Bass
Publication Date: 2026-04-20 14:15:00
In a matter of months, Google’s AI chips have become one of the hottest commodities in the tech sector. Leading artificial intelligence developers, including some of the firm’s biggest rivals, are stocking up on them.
Now, the Alphabet Inc.-owned company aims to build on its momentum with the likely introduction of new chips dedicated to inference, or running AI models after they’ve been trained. With this push, Google is poised to further challenge market leader Nvidia Corp. in a fast-growing category for semiconductors that’s fueled by surging adoption of AI software.
As demand grows for quickly processing AI queries, “it now becomes sensible to specialize chips more for training or more for inference workloads,” Google Chief Scientist Jeff Dean said in an interview. “We are looking at a whole bunch of different things,” he added, including the speed of AI results it wants to enable.
The company plans to announce its new generation of custom-designed chips, known as tensor processing units, or TPUs, at the Google Cloud Next conference in Las Vegas this week. Amin Vahdat, who oversees Google’s AI infrastructure and chip work, declined to comment on plans for an inference chip that can speed up AI outputs, but said more will likely be shared “in the relatively near future.”
Nvidia’s graphics processing units, or GPUs, remain the gold standard for AI, particularly for training more advanced models. But a growing number of up-and-comers are vying to…
