The Download: more energy-efficient AI, and the problem with QWERTY keyboards

On a table in his lab at the University of Pennsylvania, physicist Sam Dillavou has connected an array of breadboards via a web of brightly colored wires. The setup looks like a DIY home electronics project, but this unassuming assembly can learn to sort data like a machine-learning model. While its current capability is rudimentary, the hope is that, if it works, it could help spark a far more energy-efficient approach to building faster AI. Have you ever thought about the fact that, despite the myriad differences between languages, virtually everyone uses the same QWERTY keyboards? Many languages have more or fewer than 26 letters in their alphabet--or no "alphabet" at all, like Chinese, which has tens of thousands of characters.