What's up in

The real-world version of the famous “traveling salesman problem” finally gets a good-enough solution.

A new idea is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn.

A tiny self-organized mesh full of artificial synapses recalls its experiences and can solve simple problems. Its inventors hope it points the way to devices that match the brain’s energy-efficient computing prowess.

Computer scientists are finding ways to code curiosity into intelligent machines.

John Nash’s notion of equilibrium is ubiquitous in economic theory, but a new study shows that it is often impossible to reach efficiently.

A new paper claims that a common digital security system could be tweaked to withstand attacks even from a powerful quantum computer.

The computer scientist Cynthia Dwork takes abstract concepts like privacy and fairness and adapts them into machine code for the algorithmic age.

*Quanta Magazine* invites readers to share about their early math and science learning experiences and to explore the interactive survey results.

The impasse in math and science instruction runs deeper than test scores or the latest educational theory. What can we learn from the best teachers on the front lines?