The interesting part of MIT’s protonic/analog AI work isn’t

The interesting part of MIT’s protonic/analog AI work isn’t just “AI but faster.” It’s that they’re trying to move some machine learning math out of power-hungry digital chips and into materials that behave more like brain synapses, which could matter a lot more for laptops, phones, and edge devices than another giant datacenter GPU.