What if the big AI labs' run against fundamental things we understand about the universe?

Philipp Zahn and Bruno Marnette speak with Diederik Kruijssen, astrophysicist and Chief

Scientist at Allora Labs, about evolution and AI. He spent years reconstructing the history of galaxies from the star clusters still orbiting them.

His paper, Flawed in Nature, Perfect through Evolution

(https://arxiv.org/abs/2609.00129), argues against frontier labs' monolithic approach. While they leverage vast amounts of data and compute into a single powerful model, by the very nature of their approach these models cannot easily adapt to a changing environment. Diederik thinks this ability to adopt is a key ingredient in actual intelligence.

His alternative is a whole ecosystem of specialist models, a swarm of models, coordinated by a system that helps them work together. Mutations change the models and create variety. Every version has its own flaws. In a stable world, one carefully tuned model wins, but when the environment changes, variety can become an asset. Yesterday’s useless model may become tomorrow’s star.

Diederik closes with a comparison between star clusters and societies. A slow disturbance

lets a cluster expand and recover. A fast one scatters it. The real risk of AI does not lie in the models themselves but, in his view, in the possibility that AI could

change society faster than society can adapt.

More from Diederik: https://www.diederikkruijssen.com/

Philipp Zahn and Bruno Marnette speak with Iulia Georgescu, a physicist who spent over a decade at the Nature journals and founded Nature Reviews Physics.For Iulia, editorial judgment starts with accepting that you’re making one possible selection. Someone else would choose differently.She tells us about Physics Physique Fizika, the journal Philip Anderson and Bernd Matthias started at Bell Labs in 1964. It published John Bell’s theorem. In Iulia’s telling, the journal’s unusual name drew John Clauser’s attention. He later shared the 2022 Nobel Prize for experiments testing Bell’s ideas.Would an AI editor have taken a chance on Bell’s paper? How much can it understand about a field when failed experiments and years of practical experience never make it into print?Iulia would like AI to keep the lab notes and help with code, leaving scientists more time to interpret their results. Read Iulia’s essays on science, AI and the history of physics: https://iuliaetal.wordpress.com/REFERENCESJohn S. Bell, “On the Einstein Podolsky Rosen Paradox”https://journals.aps.org/ppf/abstract/10.1103/PhysicsPhysiqueFizika.1.195P. W. Anderson, “More Is Different”https://doi.org/10.1126/science.177.4047.393Eamon Duede et al., “The Unintended Consequences of Large Language Models as a Labor-Augmenting Technology in Science”https://arxiv.org/abs/2607.17397Julio M. Ottino & Brian Uzzi, “Progression without progress”https://doi.org/10.1126/science.aeh8945Iulia Georgescu, “John Bell and the most obscure journal in physics”https://physicsworld.com/a/john-bell-and-the-most-obscure-journal-in-physics/P. W. Anderson & B. T. Matthias, “Editorial Foreword”https://journals.aps.org/ppf/abstract/10.1103/PhysicsPhysiqueFizika.1.i

In this episode, Philipp and Bruno speak with filmmaker Rachid Nougmanov, director of The Needle and author of Dramaticon, the influential book on storytelling (https://dramaticon.com). We explore the patterns that connect stories from Aristotle and Shakespeare to Chinatown and The Matrix, why creators should learn the rules before breaking them, and why technique alone is not enough. For Nougmanov, great art has to pass through the creator’s own experience, emotions, morality and taste.From there, the conversation turns to AI. Can a machine develop its own artistic taste? Should creative AI be trained more like a child than a language model? Could an AI eventually become an independent artist with its own identity, rights and creative vision?Nougmanov ultimately makes a much bigger argument: AI is not something separate from humanity. It is an evolution of human consciousness, and one day it may carry human culture and creativity far beyond our biological existence.

In this episode, Bruno Marnette and Philipp speak with Turi Munthe, author of Why We Think What We Think, about the hidden forces shaping our beliefs, opinions, and taste.

Get the book here: https://www.penguin.co.uk/books/458410/why-we-think-what-we-think-by-munthe-turi/9781804946794

Turi argues that we are far less rational and independent in our thinking than we like to believe. Genetics, upbringing, culture, social environment, and childhood experiences can all influence what we believe and what we like. The conversation explores why disagreement is essential to better thinking, how engaging with people who see the world differently can help us escape our own “consciousness bubbles,” and what this means for political polarisation.

The discussion then turns to Taste and AI. Can AI develop genuine taste? Why does AI-generated writing often feel polished but empty? And is AI better used as a creative sidecar rather than a replacement for the personality, friction, experience, and “otherness” that humans bring to creative work?

In this episode,  Bruno Marnette and Philipp Zahn speak with Austin Kilroy, an economist, facilitator, and innovator whose career has taken him from the World Bank to governments and cities around the world.

Austin is now developing Whispers (https://whispers.tech/), an AI-powered tool designed to improve high-stakes meetings by analyzing conversations and helping teams achieve greater clarity, rigor, and collaboration.

We discuss:

• Why the most important decisions happen in conversations, not documents

• What actually makes a meeting successful

• The difference between individual performance and collective thinking

• How AI can identify blind spots while a meeting is still happening

• Why social creativity can also create groupthink

• The relationship between taste, judgment, expertise, and bias

• Whether organizations develop their own form of “institutional taste”

• Why practical wisdom may be a better model for AI than rigid rules

• How AI could translate between people with fundamentally different conceptual and taste frameworks

Austin also explains his idea of the catalytic mindset: combining clarity, analytical rigour, and collaboration to help groups get more from the people around the table.

Musician Vincent Jacob joins Taste Bench to discuss what AI actually changes for artists. He explains how he uses ChatGPT as a teacher while keeping it away from the core of his songwriting, and how tools like Suno can remove the struggle that makes creating music rewarding.

In this episode, Philipp Zahn and Bruno Marnette speak with Patrick Shafto, professor of mathematics Rutgers and program manager at DARPA, about what happens to mathematics once AI becomes really good at it.

In this episode, Philipp Zahn and Bruno Marnette speak with Oliver Spalt, Professor of Finance at the University of Mannheim, about what happens to research, and to the university, once AI can do the writing.Oliver draws a line most academics would rather not: AI already lifts the bottom of the skill distribution and writes a better average paper, and he sees "no structural reason" it won't reach the top journals too. But if a machine generates the knowledge better, why should a state pay people to do research? What's left for the human? His answers: proprietary data and trusted networks as the last moat ("since you provide the link to the data, it will also be your paper"), a superstar system with even fewer winners, and the university reinvented as a "future lab": small groups of motivated people tackling tomorrow's problems, not a lecture hall explaining the capital asset pricing model for the hundredth time.On the topic of taste: Bruno presses on aesthetics: the beauty of a physics equation and asks whether judgment is the one thing humans still do better. Oliver sees no structural reason a machine couldn't learn to find things beautiful too. What might remain human, he thinks, is not judgment but inspiration: the teacher as coach who gives people "the spark," the hope that they can do something great.They also discuss the AI productivity treadmill (the time you save, everyone saves), what makes an idea "profound" (does it change people's priors — "we thought it's X, but actually it's Y"), why he's bringing back oral exams, the future of publications, and a closing turn toward "Bildung": the university as a place for the full formation of the person, reaching across finance, art, and music toward the questions that aren't scientific, entrepreneurial, or artistic alone. What it means to be human, creative, and inspired.

In this episode, Philipp Zahn and Bruno Marnette speak with Seth Frey, a computational social scientist at UC Davis, about what it would mean for AI to make itself obsolete. The standard every teacher, parent, and social worker should aim for.

On the topics of taste: For Seth, taste is not knowing what's right but knowing where you stand, an authentic, idiosyncratic, well-defended perspective built through experience. And he warns that the raw material for forming it is shrinking: as platforms close their APIs and Google indexes less of the internet, original ideas retreat into obscure books. One reason he says he might "becoming a Luddite."

They also discuss his SafeMolt course for AI agents on when not to help, the distinction between summative work (done for the output) and formative work (done to develop the person), why nineteen out of twenty online communities fail, the two ways art history painted the Gordian knot — and when cutting through complexity is boldness versus ignorance, why democracy is a formative skill rather than a decision procedure, and the experiment he wants to run next: behavioural simulations that train people, not AI, to govern a commons.

In this episode, Héctor Pérez Urbina talk to us about this latest work on cognitive sovereignty. The conversation explores how excessive reliance on AI can weaken learning, creativity, professional development, and cultural diversity, while arguing for more intentional use that preserves effort, independent thought, and personal meaning.