By Julia Love
Publication Date: 2026-05-18 13:38:00
In the race to build the infrastructure that powers artificial intelligence, Alphabet Inc.’s Google has an enviable position: The company has a healthy cloud computing business, makes its own chips, and has struck deals to share them with companies like Anthropic PBC and Meta Platforms Inc.
Google’s success has made its computing resources so valuable, though, that its own AI researchers have to get in line.
Last summer, Andrew Dai, then a researcher in Google’s AI lab, discovered a blind spot in Gemini, the company’s flagship AI model. While playing a board game, Dai took pictures of the board and asked Gemini a simple question: who’s winning? To his surprise, Gemini was stumped, as were models from rivals. He became convinced of the need to build AI that could better understand what was happening in images.
Dai discussed his idea with some of his colleagues, but he quickly concluded that he wouldn’t be able to secure enough computing power to tackle the problem within…
