Inner Cosmos with David Eagleman

Why do we generally feel like the world is getting worse, when by almost all measures it’s getting better? How do ideas "have sex”, and why does that matter for innovation? Why do brains tend to systematically misread the future? What if optimism is a more rational stance than pessimism? If innovation isn’t primarily about lone geniuses, what’s it really about? Join Eagleman with scientist and author Matt Ridley to explore what it means to be, in Ridley’s phrasing, a "rational optimist".

Can you influence what you dream about tonight? Are you spending years of your life in a world you don’t recall? Can nightmares be manipulated as a therapy? Are dreams sometimes predictive of changes in your health before you become aware of them? Join Eagleman with Adam Haar Horowitz, a neuroscientist and dream engineer who spends his working days trying to help people during their night time.

How can a brain grow up in chaos but find its way to order? There are many ways to have a bad childhood, but why do some children break while others bend and keep going? How much of who you are is written in your genes & how much is sculpted by your environment? How many versions of you were possible & why did this one win out? Join Eagleman today with David Sussillo, who was abandoned as a child but grew up to become a neuroscientist & technologist. We’ll explore what his trajectory teaches about our genes, brains, and our own lives.

How can we improve political dialogue, and what does this have to do with the discovery that the universe behaves differently than expected? Why do we cling to beliefs even when evidence pushes against them? What if the biggest problem facing humanity could be solved with practice? Join Eagleman today with Saul Perlmutter, a Nobel-prize winning astrophysicist, but instead of the cosmos we talk about the inner cosmos: why polarization happens and how we might address it with a different kind of thinking.

Can the mind be captured with math? Modern AI seems to have burst out of the gate recently, but is it actually the latest chapter in a 300-year project to turn thought into something we can model? Why does current AI need petabytes of data, but a child can learn from just a few examples? Why does AI have 'jagged' intelligence – meaning it looks brilliant in one moment and then does something that seems nonsensical? In physics we have various laws (gravity, motion, etc), and today we’re joined by cognitive scientist Tom Griffiths to ask whether we're moving towards laws of thought.