Three massive issues we nonetheless don’t learn about AI’s power burden
—James O’Donnell
Earlier this 12 months, when my colleague Casey Crownhart and I spent six months researching the local weather and power burden of AI, we got here to see one quantity particularly as our white whale: how a lot power 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 printed, 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 previous sources, and a few new ones, to search out out. Learn the complete story.
MIT Know-how Evaluation Narrated: Google DeepMind has a brand new method to look inside an AI’s “thoughts”
We don’t know precisely how AI works, or why it really works so nicely. That’s an issue: It may lead us to deploy an AI system in a extremely delicate area like medication with out understanding its vital flaws.However a workforce at Google DeepMind that research one thing known as mechanistic interpretability has been engaged on new methods to allow us to peer below the hood.
