The “species” category is almost certainly the best known of all the taxonomic classifications that biologists use to organize life’s vast diversity. It’s a linchpin of both conservation policy and evolutionary theory, though in practice biologists have struggled to find a definition that works across the natural world. In this episode, Kevin de Queiroz, a zoologist and evolutionary biologist, talks with host Janna Levin about the variety of ways to conceive of a species, and ways to understand the relationships among living things.

When we think about medicine’s war on cancer, treatments such as surgery, radiation and chemotherapy spring to mind first. Now there is another potential weapon for defeating tumors: statistics and mathematical models that can optimize the selection, combination or timing of treatment. Building and feeding these models requires accounting for the complexity of the body, and recognizing that cancer cells are constantly evolving. In this episode, host Steven Strogatz hears from Franziska Michor, a computational biologist, about how our understanding of evolutionary dynamics is being used to devise new anticancer therapies.

If instruments do someday detect evidence of life beyond Earth, whether it’s in this solar system or in the farther reaches of space, astrobiologists want to be ready. One of the best ways to learn how alien life might function can be to study the organisms called extremophiles, which live in incredibly challenging environments on or in the Earth. In this episode, Penelope Boston, a microbiologist who has worked for many years with NASA, speaks with Janna Levin about the bizarre life found in habitats such as caves, how it would be possible to detect life beyond our solar system and what it would mean for humanity if we do.

The principles of thermodynamics are cornerstones of our understanding of physics. But they were discovered in the era of steam-driven technology, long before anyone dreamed of quantum mechanics. In this episode, the theoretical physicist Nicole Yunger Halpern talks to host Steven Strogatz about how physicists today are reinterpreting concepts such as work, energy and information for a quantum world.

Observations of the cosmos suggest that unseen sources of gravity — dark matter — tug at the stars in galaxies, while another mysterious force — dark energy — drives the universe to expand at an ever-increasing rate. The evidence for both of them, however, hinges on assumptions that gravity works the same way at all scales. What if that’s not true? In this episode, theoretical physicist Claudia de Rham explains her work on an alternative explanation called “massive gravity” to host Janna Levin.

Within just a few years, artificial intelligence systems that sometimes seem to display almost human characteristics have gone from science fiction to apps on your phone. But there’s another AI-influenced frontier that is developing rapidly and remains untamed: robotics. Can the technologies that have helped computers get smarter now bring similar improvements to the robots that will work alongside us? In this episode, Daniela Rus, a pioneering roboticist at the Massachusetts Institute of Technology, talks to host Steven Strogatz about the surprising inspirations from biology that may help robots rise to new levels.

Can you keep a secret? Modern techniques for maintaining the confidentiality of information are based on mathematical problems that are inherently too difficult for anyone to solve without the right hints. Yet what does that mean when quantum computers capable of solving many problems astronomically faster are on the horizon? In this episode, host Janna Levin talks with computer scientist Boaz Barak about the cryptographic techniques that keep information confidential, and why “security through mathematics” beats “security through obscurity.”

Listen on Apple Podcasts, Spotify, TuneIn or your favorite podcasting app, or you can stream it from Quanta.

Ask a question of ChatGPT and other, similar chatbots and there’s a good chance you’ll be impressed at how adeptly it comes up with a good answer — unless it spits out unrealistic nonsense instead. Part of what’s mystifying about these kinds of machine learning systems is that they are fundamentally black boxes. No one knows precisely how they arrive at the answers that they do. Given that mystery, is it possible that these systems in some way truly understand the world and the questions they answer? In this episode, the computer scientist Yejin Choi of the University of Washington and host Steven Strogatz discuss the capabilities and limitations of chatbots and the large language models, or LLMs, on which they are built.

Listen on Apple Podcasts, Spotify, TuneIn or your favorite podcasting app, or you can stream it from Quanta.