For most of the past decade, custom AI silicon was a Google story. The company began developing its Tensor Processing Units internally in 2015, deployed them quietly across its data centers, and said relatively little about them publicly for years. The rest of the industry watched with interest but did not replicate the strategy at scale, in part because the capital requirements of custom chip development were prohibitive for most operators and in part because Nvidia’s GPU ecosystem was performing well enough that the ROI case for custom silicon development was difficult to make at the board level. That period of cautious observation is over.