Explainers

Anne Carpenter, senior director of the Imaging Platform of the Broad Institute of the Massachusetts Institute of Technology and Harvard University, describes how her interest in developing new medicines led her to work at the interface of biology and computer science.

Laura Kreidberg discusses how she’ll use NASA’s James Webb Space Telescope to peer into the skies of rocky planets orbiting other stars and look for signs of habitability, or even life.

The neuroscientist Anil Seth of the University of Sussex discusses the principles, philosophy and experimentation that have brought scientists closer to understanding the phenomenon of consciousness.

The genomics researcher Karen Miga explains why it’s so important to learn the DNA sequence information buried in parts of our genome that were resistant to scrutiny.

Melanie Mitchell, the Davis professor of complexity at the Santa Fe Institute, has worked on digital minds for decades. She says AI will never truly be “intelligent” until they can do something uniquely human: make analogies.

The Standard Model of particle physics is the most successful scientific theory of all time. In this explainer, Cambridge University physicist David Tong recreates the model, piece by piece, to provide some intuition for how the fundamental building blocks of our universe fit together.

Nathan Seiberg explains the importance of math in figuring out and understanding the ultimate laws of the universe.

Federica Coppari describes how she uses giant lasers to study the insides of exotic exoplanets.

Quantum computers aren’t the next generation of supercomputers — they’re something else entirely. Before we can even begin to talk about their potential applications, we need to understand the fundamental physics that drives the theory of quantum computing.