Three huge issues we nonetheless don’t learn about AI’s vitality burden
—James O’Donnell
Earlier this yr, when my colleague Casey Crownhart and I spent six months researching the local weather and vitality burden of AI, we got here to see one quantity particularly as our white whale: how a lot vitality the main AI fashions, like ChatGPT or Gemini, expend when producing a single response.
We pestered Google, OpenAI, and Microsoft, however every firm refused to offer its determine for our article. However then this summer time, after we revealed, an odd factor began to occur. They lastly began to launch the numbers we’d been calling for.
So with this newfound transparency, is our job full? Did we lastly harpoon our white whale? I reached out to a few of our outdated sources, and a few new ones, to seek out out. Learn the total story.
MIT Expertise Evaluate Narrated: Google DeepMind has a brand new option to look inside an AI’s “thoughts”
We don’t know precisely how AI works, or why it really works so properly. That’s an issue: It may lead us to deploy an AI system in a extremely delicate discipline like drugs with out understanding its essential flaws.However a staff at Google DeepMind that research one thing known as mechanistic interpretability has been engaged on new methods to allow us to peer beneath the hood.
