Neuromorphic Computing

AI has an energy problem. A massive one. Data centers now consume roughly 1,000 terawatt-hours of electricity annually — about as much as Japan. Every ChatGPT query, every image generation, every AI-powered search burns through watts at a rate that would make your electric bill weep. So when a team at the University of Cambridge publishes a chip design in Science Advances that could cut AI energy consumption by up to 70%, it’s time to pay attention. ...

What if the next great leap in AI hardware didn’t come from shrinking transistors — but from printing flexible circuits that literally speak the brain’s language? A team at Northwestern University just proved that’s possible. Published in Nature Nanotechnology, their research demonstrates printed artificial neurons that generate electrical patterns realistic enough to activate living mouse brain cells. Not simulate. Not approximate. Activate. This sits at the collision point of neuroscience, materials science, and AI’s looming energy crisis — and it deserves your attention. ...