When OpenAI declared a “code red” this month to refocus its teams on competition from Google, I couldn’t help but think back to December three years ago, when the companies’ roles were reversed. It was Google who triggered the sirens to catch up with OpenAI. The following month, January 2023, saw the first mass layoffs in Google history. “A difficult decision to prepare us for the future,” as the company described it at the time.
I wonder if the ChatGPT developer might make similar headcount reductions early next year. This speculation has inspired me to make a whole series of predictions about what might happen in the coming year. Here’s a look at six of those ideas, honed with the true intelligence of WIRED’s colleagues.
Data center misinformation
Communities around the world are fighting against the construction of data centers. In the United States, many activists organize on social media using tools such as Facebook groups. The Chinese and Russian governments continue to exploit social media to spread disinformation masquerading as real news and authentic opinion. A slowdown in U.S. data center development would be a boon for China and Russia, both of which seek to surpass the United States in AI industrial and military capabilities.
Austin Wang, a researcher at the nonprofit think tank RAND who has studied Chinese-controlled propaganda farms, says there are currently no signs of worrying activity. “So far, many newly created anti-data center pages appear to be controlled by real American citizens,” Wang says.
But as anti-data center fervor grows, China and Russia may try to leverage grassroots organizing. And the job has become even easier thanks to AI that can quickly generate images and videos to piss people off on social media.
Robot demonstrations everywhere
In 2026, technology conferences, from the Consumer Electronics Show to Amazon’s hardware event, will likely be buzzing about AI-powered robots. Google and other big tech companies have spent years trying to train robots to perform household tasks through repeated practice. But now there is a new wave of hype. The type of AI models used in services like ChatGPT and Gemini are built into robots in the hope that they will perform tasks like folding clothes, with less training and greater accuracy.
Last September, Google released a video of a robot sorting trash, compost and recycling in response to a user’s voice commands. When Google executives take the stage at the company’s next I/O conference, I expect they will invite a robot to perform tasks such as, say, sliding a pizza into a never-before-encountered type of oven and, while cooking, retrieving a half-full Diet Coke from the bottom of a crowded refrigerator.
Barak Turovsky, the recently departed chief AI officer at General Motors and former head of Google’s AI division, says advances in robot capabilities are possible because large language models can understand a dishwasher manual, learn how to operate a dishwasher by watching a video, and understand how to grasp a specific part by deciphering a drawing. “The next frontier for big language models is the physical world,” he says.
