Reasoning is a team sport

What can a translator of the Bible teach us about AI? Philipp Zahn and Bruno Marnette speak with Robert Alter, Emeritus Professor of Hebrew and Comparative Literature at UC Berkeley, about his new book, The Language of Fiction (2027). Robert explains how great writers do something with language that no one has done before. One of his examples is Faulkner using "abrupt" as a verb: the word surprises the reader and then, on reflection, fits the whole novel. In his view, AI can imitate Faulkner's style, but not make that move, because it cannot be inferred from other works. And since we are language-using animals, he argues, some people will keep enjoying this mastery of language, even in the age of AI. We also discuss his work on the Hebrew Bible. In The Art of Biblical Narrative (1981), he proposed reading the Bible as literature. He then applied that close reading to his own translation, which took 23 years. He wrestled with every word and found meanings that earlier translators had missed. More on The Language of Fiction: https://www.hup.harvard.edu/books/9780674308374 REFERENCES Robert Alter, The Art of Biblical Narrative, revised edition (Basic Books, 2026) https://www.hachettebookgroup.com/titles/robert-alter/the-art-of-biblical-narrative/9781541609273/ Robert Alter, The Hebrew Bible: A Translation with Commentary (W. W. Norton, 2018) https://wwnorton.com/books/9780393292497

Philipp Zahn and Bruno Marnette speak with Jack Marsh, co-founder of Not Quite Past. The London company uses AI to design custom tiles in historical Delft styles, which are then produced in Stoke-on-Trent. Interior designers and private customers buy them. Jack studied art history, and for him slop is not really new. We go back to the Great Exhibition of 1851, where machine-made English ornament was judged a national embarrassment. Jack explains how the public reacted, and how that reaction led to the museum known today as the V&A. As Jack puts it, a museum against slop. We talk about the industrialists who took up the new production methods and still made high-quality products, bought by the elites of their day. For Jack, this is the model for how to use AI. We also discuss why his customers rarely design their own tiles, and why perfect copies of historical tiles can feel lifeless. More from Jack: https://www.notquitepast.com/

Most talk about AI and children is either fear or hype. Few people actually teach kids how the systems work. Saranyan Vigraham does. He is Director of Engineering at Meta, where he works on compute and AI infrastructure, and he teaches AI and ethics to middle schoolers at Khan Lab School. He does not think AI output is bad, or that craftmanship will die. His worry is that people who never practiced a craft can now make work that looks like they did, while the ones who did get harder to find and harder to pay. AI also took away two things that build craft over time: waiting, and feedback you can use. In this episode he also takes us through the experience he had with two side projects of his. One was in cybersecurity, which he knows only from reading. He built something convincing, but had no opinion of his own, so the feedback people gave him was useless. That project stalled. The other was in developer tooling, which he knows cold. People disagreed with him there too but he kept building. The AI he wants instead runs on your own device, owned by no frontier lab. It learns with you, knows when to shut up, and sends you out to check what you learned.

Markus J. Buehler is a professor at MIT. His field is materials science but his research spans across other fields: Biology, chemistry, engineering, and, yes, music.

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/