Making living cells blink fluorescently like party lights may sound frivolous. But the demonstration that it's possible could be a step toward someday programming our body's immune cells to attack cancers more effectively and safely. That's the promise of the field called synthetic biology. While molecular biologists strip cells down to their component genes and molecules to see how they work, synthetic biologists tinker with cells to get them to perform new feats -- discovering new secrets about how life works in the process. Listen on Apple Podcasts, Spotify, Google Podcasts, Stitcher, TuneIn or your favorite podcasting app, or you can stream it from Quanta. Steve Strogatz (00:03): I'm Steve Strogatz, and this is The Joy of Why, a podcast from Quanta Magazine that takes you into some of the biggest unanswered questions in science and math today. In this episode, we're going to be talking about synthetic biology. Simply put, we could say that synthetic biology is a fusion of biology, especially molecular biology, and engineering. The distinctive thing about it is that it treats cells as programmable devices. It's a kind of tinker toy approach that builds circuits, but not out of wires and switches like we're used to, but rather out of biological components, like proteins and genes. But also, the approach holds promise for illuminating how life works at the deepest level. It's one thing to strip cells apart to see how they work. But it's another thing to tinker with cells to try to get them to perform new tricks, which is something that my guest, Michael Elowitz, does. For example, a while back, he engineered cells to blink on and off like Christmas lights. Michael Elowitz is a professor of biology and biological engineering at Caltech and Howard Hughes Medical Institute. It's great to be here. Strogatz (01:53): So let's talk about the foundational idea of synthetic biology. I mentioned it in the intro, that's -- that living cells, we could think of as programmable devices. The field, synthetic biology, it seems like you guys have this philosophy that you can learn about cells by building functionality into cells yourself.

Melanie Mitchell, a professor of complexity at the Santa Fe Institute and a professor of computer science at Portland State University, acknowledges the powerful accomplishments of "black box" deep learning neural networks. But she also thinks that artificial intelligence research would benefit most from getting back to its roots and exchanging more ideas with research into cognition in living brains. This week, she speaks with host Steven Strogatz about the challenges of building a general intelligence, why we should think about the road rage of self-driving cars, and why AIs might need good parents. Listen on Apple Podcasts, Spotify, Android, TuneIn, Stitcher, Google Podcasts, or your favorite podcasting app, or you can stream it from Quanta. Melanie Mitchell: You know, you give it a new face, say, and it gives you an answer: "Oh, this is Melanie." And you say, "Why did you think that?" "Well, because of these billions of numbers that I just computed." Steve Strogatz [narration]: From Quanta Magazine, this is The Joy of x. Mitchell: And I'm like, "Well, I can't under-- Can you say more?" And they were like, "No, we can't say more." Steve Strogatz: Isn't that unnerving, that it's this great virtuoso at these narrow tasks, but it has no ability to explain itself? Strogatz: Melanie Mitchell is a computer scientist who is particularly interested in artificial intelligence. Her take on the subject, though, is quite a bit different from a lot of her colleagues' nowadays. She actually thinks that the subject may be adrift and asking the wrong questions. And in particular, she thinks that it would be better if artificial intelligence could get back to its roots in making stronger ties with fields like cognitive science and psychology, because these artificially intelligent computers, while they're smart, they are smart in a way that is so different from human intelligence. Melanie's been intrigued by these questions for really quite a long time, but her journey got started in earnest when she stumbled across a really big and really important book that was published in 1979.

Isaac Newton (left) and Gottfried Wilhelm Leibniz each independently invented calculus.Credit: Left, DeAgostini/Getty; Right, Lombard/ullstein bild via Getty Midway through Infinite Powers, Steven Strogatz writes that Isaac Newton and Gottfried Wilhelm Leibniz both "died in excruciating pain while suffering from calculi -- a bladder stone for Newton, a kidney stone for Leibniz". It was a cruelly ironic end for the scientists who independently invented calculus: the word comes from the Latin for'small stone', in reference to pebbles once used for counting. Such fascinating anecdotes abound in Infinite Powers. Strogatz, a mathematician working in nonlinear dynamics and complex systems, has written a romp through the history of calculus -- the study of how things change. Starting with the ancient Greeks, the book ends with connections between the field and artificial intelligence and machine learning. Calculus was key to working with Newton's laws of motion, which stimulated the Industrial Revolution.