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What's up in

In a second season of enlightened conversations, Steven Strogatz and leading researchers nourish our pandemic-starved minds.

To the surprise of experts in the field, a postdoctoral statistician has solved one of the most important problems in high-dimensional convex geometry.

The learning algorithm that enables the runaway success of deep neural networks doesn’t work in biological brains, but researchers are finding alternatives that could.

Two teams found different ways for quantum computers to process nonlinear systems by first disguising them as linear ones.

Even as mathematicians and computer scientists proved big results in computational complexity, number theory and geometry, computers proved themselves increasingly indispensable in mathematics.

Today’s information age is only possible thanks to the groundbreaking work of a lone genius.

Jelani Nelson designs clever algorithms that only have to remember slivers of massive data sets. He also teaches kids in Ethiopia how to code.

A cryptographic master tool called indistinguishability obfuscation has for years seemed too good to be true. Three researchers have figured out that it can work.

Deep neural networks, often criticized as “black boxes,” are helping neuroscientists understand the organization of living brains.