HeyJaredBreaking Math Podcast
Breaking Math is a deep-dive science, technology, engineering, AI, and mathematics podcast that explores the world through the lens of logic, patterns, and critical thinking.
- Indexed episodes, last 90 days
- 5
- Latest publication
- Sep 9, 2026
- Audience
- Checking…
- Earliest in this view
- Jul 10, 2026
Latest episodes
Forecasting Explained: How Prediction Markets Beat Experts (opens the original)
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Professional forecaster Molly Hickman breaks down what it really means to assign a probability to the future — and why she believes generalists often out-forecast subject-matter experts. This episode explores the art and science of forecasting, from techniques to ethical considerations, and how AI and prediction markets are shaping our understanding of the future. Key Topics The definition of forecasting and its importance Techniques for starting in forecasting The role of AI and large language
What Actually Makes Something Alive? with Melanie Challenger (opens the original)
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What does it mean to be alive? In this episode of Breaking Math , Autumn and Noah speak with Melanie Challenger, author of Alive , about one of the most profound questions in science and philosophy: how do we define life? Challenger argues that life is not simply a machine-like process or a bundle of genetic instructions. Living beings are embodied, purposeful agents. From single-celled organisms to sequoia seeds, from animals to human beings, life is marked by an astonishing capacity to work to
Why Uncertainty Is Science's Greatest Strength with Stuart Firestein (opens the original)
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Neuroscientist Stuart Firestein (Columbia University) joins Breaking Math to make an extravagant claim: uncertainty isn't a weakness in science — it's the defining feature that makes progress possible. In this episode, we break down why the "one right answer" myth is one of the most damaging ideas in science, why real experts are often the most uncertain people in the room, and why authority and expertise pull in opposite directions, covering two fundamentally different kinds of probability, why
Robot Proof: Why Better AI Starts With Better People with Vivienne Ming (opens the original)
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Neuroscientist, entrepreneur, and author Dr. Vivienne Ming joins Autumn and Noah to make the case that if we want better AI, we need to build better people first. We get into why AI tutors that hand students answers make learning worse, not better; what her research on "hybrid intelligence" reveals about the human traits — not the AI model — that predict elite human-AI collaboration; a wild experiment running Dungeons & Dragons with Claude and Gemini as dungeon masters to expose the gap between
Why Nothing Works: Robber Barons, Algorithms & Governing AI (opens the original)
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In this episode, Historian and author Marc Dunkelman to explain why the 19th-century fight over railroad power is the exact fight we're about to have over algorithms and AI. Drawing on his acclaimed book Why Nothing Works: Who Killed Progress — and How to Bring It Back (a Best Book of the Year in the Financial Times and The Economist), Marc unpacks the two competing tools America has always used against concentrated power — antitrust vs. regulation — and why our government's "endemic diffusion o
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