John Pavlus

The security system that underlies the internet makes use of a curious fact: You can broadcast part of your encryption to make your information much more secure.

To better understand machine learning algorithms, Lenka Zdeborová treats them like physical materials.

Machines work with words by embedding their relationships with other words in a string of numbers.

Neural networks and other forms of machine learning ultimately learn by trial and error, one improvement at a time.

The computer scientist Ellie Pavlick is translating philosophical concepts such as “meaning” into concrete, testable ideas.

Melanie Mitchell has worked on digital minds for decades. She says they’ll never truly be like ours until they can make analogies.

For all their triumphs, AI systems can’t seem to generalize the concepts of “same” and “different.” Without that, researchers worry, the quest to create truly intelligent machines may be hopeless.

The goal of the “busy beaver” game is to find the longest-running computer program. Its pursuit has surprising connections to some of the most profound questions and concepts in mathematics.

At the molecular level, glass looks like a liquid. But an artificial neural network has picked up on hidden structure in its molecules that may explain why glass is rigid like a solid.