It's difficult for humans to identify phase transitions, or exotic states of matter that come about through unusual transitions (say, a material becoming a superconductor). They might not have to do all the hard work going forward, however. Two sets of researchers have shown that you can teach neural networks to recognize those states and the nature of the transitions themselves. Similar to what you see with other AI-based recognition systems, the networks were trained on images -- in this case, particle collections -- to the point where they could detect phase transitions on their own. They're both very accurate (within 0.3 percent for the temperature of one transition) and only need to see a few hundred atoms to identify what they're looking at.