We can’t not talk about power these days. We’ve been talking about it ever since the Stargate project, with half a trillion dollars in datacenter investment, was floated early in the year. We’ve been talking about it ever since the now-classic “Stochastic Parrots” paper. And, as time goes on, it only becomes more of an issue. Stochastic Parrots deals with two issues: AI’s power consumption and the fundamental nature of generative AI; selecting sequences of words according to statistical patterns. I always wished those were two papers, because it would be easier to disagree about power and agree about parrots. […]

Earlier this year, when my colleague Casey Crownhart and I spent six months researching the climate and energy burden of AI, we came to see one number in particular as our white whale: how much energy the leading AI models, like ChatGPT or Gemini, use up when generating a single response.  This fundamental number remained elusive even as the scramble to power AI escalated to the White House and the Pentagon, and as projections showed that in three years AI could use as much electricity as 22% of all US households.  The problem with finding that number, as we explain […]

In Silicon Valley’s imagined future, AI models are so empathetic that we’ll use them as therapists. They’ll provide mental-health care for millions, unimpeded by the pesky requirements for human counselors, like the need for graduate degrees, malpractice insurance, and sleep. Down here on Earth, something very different has been happening.  Last week, we published a story about people finding out that their therapists were secretly using ChatGPT during sessions. In some cases it wasn’t subtle; one therapist accidentally shared his screen during a virtual appointment, allowing the patient to see his own private thoughts being typed into ChatGPT in real […]