Breaking Math Podcast

Author: Autumn Phaneuf & Noah Giansiracusa

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. Hosted by Autumn Phaneuf, an expert in industrial engineering, operations research, and applied mathematics, and Noah Giansiracusa, a mathematician and leading voice in algorithmic literacy and technology ethics, the show is dedicated to uncovering the mathematical structures behind science, technology, and the systems shaping our future.What began as a conversation about math as a pure and elegant discipline has evolved into a platform for bold, interdisciplinary dialogue. Each episode of Breaking Math takes listeners on an intellectual journeyinto the strange beauty of chaos theory, the ethical dilemmas of AI and algorithms, the hidden math of biology and evolution, or the physics governing black holes and the cosmos. Along the way, Autumn and Noah speak with working scientists, researchers, and thinkers across fields: computer scientists, physicists, chemists, engineers, economists, philosophers, and more.But this isnt just a podcast about equations. Its a show about how mathematics shapes the way we think, decide, build, and understand the world. Breaking Math pushes back against the idea that STEM belongs behind a paywall or an academic podium. Its for the curious, the critical, and the creativefor anyone who believes that ideas should be rigorous, accessible, and infused with wonder.If youve ever wondered:Whats the math behind machine learning and modern algorithms?How do we quantify uncertainty in climate and economic models?Can intelligence or consciousness be meaningfully described in AI?Why does beauty matter in an equation?Youre in the right place.At its heart, Breaking Math is about building bridgesbetween disciplines, between experts and the public, and between abstract mathematics and the messy, magnificent reality we live in. With humor, clarity, and deep respect for complexity,
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Language: en

Genres: Mathematics, Natural Sciences, Science

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