Archive

With lots of data, a strong model and statistical thinking, scientists can make predictions about all sorts of complex phenomena. Today, this practice is evolving to harness the power of machine learning and massive datasets. In this episode, co-host Steven Strogatz speaks with statistician Emmanuel Candès about black boxes, uncertainty and the power of inductive reasoning.

New observations of microscopic vortices confirm the existence of a paradoxical phase of matter that may also arise inside neutron stars.

Yizhi “Patrick” Cai is coordinating a global effort to write a complete synthetic yeast genome. If he succeeds, the resulting cell will be the artificial life most closely related to humans to date.

It was intuitive, even obvious. It was also wrong.

A new experimental proposal suggests detecting a particle of gravity is far easier than anyone imagined. Now physicists are debating what it would really prove.

All modern multicellular life — all life that any of us regularly see — is made of cells with a knack for compartmentalization. Recent discoveries are revealing how the first eukaryote got its start.

Dijkstra’s algorithm was long thought to be the most efficient way to find a graph’s best routes. Researchers have now proved that it’s “universally optimal.”

The idea of a species is fundamental to the way that many people understand the structure of life on Earth. But ask 10 specialists how they define the concept and you might get 10 answers. In this episode, co-host Janna Levin speaks with evolutionary biologist Kevin de Queiroz about what makes defining and delineating species such a slippery process, and why it matters to our understanding of both evolution and conservation.

The giant holes in galaxies’ centers shouldn’t be able to merge, yet merge they do. Scientists suggest that an unusual form of dark matter may be the solution.