When OpenAI declared a “code red” this month to refocus its teams on competing with Google, I couldn't help but think back to December three years ago, when the companies' roles were reversed. Google was the one that sounded the sirens to overtake OpenAI. What followed the next month, in January 2023, were the first major layoffs in Google's history. “A difficult decision to prepare ourselves for the future,” as the company described it at the time.
I wonder if the ChatGPT developer could make a similar staff cut early next year. This speculation inspired me to make a whole series of predictions about what might happen in the coming year. Here's a look at six of the ideas, refined with the real intelligence of WIRED colleagues.
Disinformation about data centers
Communities around the world are fighting against the construction of data centers. In the US, 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 opinions. Slowing data center development in the US would be a boon for China and Russia, both of which are trying to surpass the US in industrial and military AI capabilities.
Austin Wang, a researcher at the nonprofit think tank RAND who has studied Chinese-controlled propaganda farms, says there are no signs of worrying activity at this point. “Many newly established anti-data center pages appear to be operated by real US citizens so far,” Wang said.
But as anti-data center fervor increases, China and Russia could look to strengthen the grassroots organization. And the job has become even easier thanks to AI that can quickly generate images and videos to stir people up on social media.
Robot demos everywhere
By 2026, tech conferences from the Consumer Electronics Show to Amazon's hardware event will likely be buzzing with AI-powered robots. Google and other major tech companies have tried for years to train robots to perform household tasks through repetitive practice. But now there is a new hype. The kind of AI models used in services like ChatGPT and Gemini are being integrated into robots in the hope that they can perform chores, such as folding clothes, with less training and greater accuracy.
Last September, Google released a video of a robot sorting waste, 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'll prompt a robot to take on tasks like, say, sliding a pizza into some kind of oven it's never seen before and, while it's cooking, pulling a half-full Diet Coke from an overcrowded refrigerator.
Barak Turovsky, the recently departed Chief AI Officer at General Motors and a former leader in Google's AI division, says improvements in robots' 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 grab a specific part by deciphering a drawing. “The next frontier for large language models is the physical world,” he says.
