972: In Case You Missed It in February 2026
Jon Krohn recaps the month of February in this episode of In Case You Missed It. Across four interviews with Will Falcon (Episode 965), Tom Griffiths (Episode 969), Antje Barth (Episode 963), and Praveen Murugesan (Episode 967), Jon questions the brains behind some of the AI industry’s most innovative companies about launching a startup, developing a popular product, what artificial intelligence can still learn from human intelligence, and how AI might finally start to think on its own.
Additional materials: www.superdatascience.com/972
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969: The Laws of Thought: The Math of Minds and Machines, with Prof. Tom Griffiths
Princeton Professor Tom Griffiths talks to Jon Krohn about his new book, The Laws of Thought, which grapples with the mathematical models behind biological and artificial intelligence, and what makes the human brain so fascinating for psychologists and computer scientists to study. In this episode, he details how the mathematical principles governing the external world can also be used to explore cognitive science, or “the internal world.”
This episode is brought to you by the Dell, by Intel, by Cisco and by Acceldata.
Additional materials: www.superdatascience.com/969
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In this episode you will learn:
(01:18) Tom Griffiths’ current research
(21:23) On mathematical inference in LLMs
(35:19) How to engineer inductive bias
(52:00) How to model curiosity into AI systems
The logos, ethos, and pathos of your LLMs
Ryan is joined by Professor Tom Griffiths, the head of Princeton University’s AI Lab, to dive into findings from his new book The Laws of Thought, which explores the history of the philosophy, mathematics, and logic that underlie artificial intelligence, and scientists' efforts to describe our minds using mathematics. They discuss the challenges of understanding human cognition, the implications of probabilistic AI “thinking,” and where Aristotle fits into the philosophical discussions we’re having on consciousness and sentience in AI.
Episode notes:
The Laws of Thought details our quest to use mathematics to describe the ways we think, from its origins three hundred years ago to the ideas behind modern AI systems and how our human minds differ from the neural networks of AI.
Connect with Tom on LinkedIn and find more of his work at the Princeton website.
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Connecting Language and (Artificial) Intelligence: Princeton’s Tom Griffiths
In this bonus episode, Princeton University professor and artificial intelligence researcher Tom Griffiths joins Sam to unpack The Laws of
Thought, his new book exploring how math has been used for
centuries to understand how minds — human and machine — actually work.
Tom walks through three main frameworks shaping intelligence today — rules and symbols, neural networks, and probability — and he explains why modern AI only makes sense when you see how those pieces fit together.
The conversation connects cognitive science, large language models, and the limits of human versus machine intelligence. Along the way, Tom and Sam dig into language, learning, and what humans still do better — like judgment, curation, and metacognition. Read the episode transcript here.
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