『Breaking Math Podcast』のカバーアート

Breaking Math Podcast

Breaking Math Podcast

著者： Autumn Phaneuf
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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 Gabriel Hesch, an electrical engineer (host from 2016-2024) with a passion for mathematical clarity, the show is dedicated to uncovering the mathematical structures behind science, engineering, technology, and the systems that shape 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 journey—whether it’s into the strange beauty of chaos theory, the ethical dilemmas of AI, the deep structures of biological evolution, or the thermodynamics of black holes. Along the way, Autumn and Gabriel interview leading thinkers and working scientists from across the spectrum: computer scientists, quantum physicists, chemists, philosophers, neuroscientists, and more.

But this isn’t just a podcast about equations—it’s a show about how mathematics influences the way we think, create, build, and understand. Breaking Math pushes back against the idea that STEM belongs behind a paywall or an academic podium. It’s for the curious, the critical, the creative—for anyone who believes that ideas should be rigorous, accessible, and infused with wonder.

If you've ever wondered:

  • What’s the math behind machine learning?
  • How do we quantify uncertainty in climate models?
  • Can consciousness be described in AI?
  • Why does beauty matter in an equation?

Then you’re in the right place.

At its heart, Breaking Math is about building bridges—between disciplines, between experts and the public, and between the abstract world of mathematics and the messy, magnificent reality we live in. With humor, clarity, and deep respect for complexity, Autumn and Gabriel invite you to rethink what math can be—and how it can help us shape a better future.

Listen wherever you get your podcasts.
Website: https://breakingmath.io
Linktree: https://linktr.ee/breakingmathmedia
Email: breakingmathpodcast@gmail.com

Copyright Breaking Math 数学 科学
エピソード
  • Robin Hood Math

    Robin Hood Math
    2025/08/05

    In this episode of Breaking Math, Dr. Noah Giansiracusa discusses his book 'Robin Hood Math', emphasizing the importance of mathematical literacy in navigating an algorithm-driven world. He explores how math can empower everyday people, the writing process behind his book, and practical applications of math in daily life, including social media algorithms and financial decisions. The conversation highlights the simplicity of the math that truly matters and encourages listeners to reclaim agency through understanding mathematics.

    Takeaways

    • Math is a powerful tool that can empower individuals.
    • The concept of Robin Hood Math aims to redistribute mathematical knowledge.
    • Mathematical literacy is becoming as essential as reading.
    • Algorithms are deeply embedded in our daily lives, influencing decisions.
    • Understanding expected value can improve decision-making.
    • Averaging guesses can lead to better predictions.
    • Social media algorithms prioritize engagement, affecting content visibility.
    • Credit scores are calculated using weighted sums of various factors.
    • Many important mathematical concepts are simpler than they appear.
    • Mathematical literacy can help close equity gaps in society.

    Chapters

    • 00:00 Monetizing Social Media for Educators
    • 02:25 The Birth of Robin Hood Math
    • 05:18 Empowering the Everyday Person with Math
    • 08:01 The Writing Process and Surprising Discoveries
    • 10:37 Practical Math Lessons for Everyday Life
    • 13:22 Understanding Algorithms in Social Media
    • 21:56 Understanding Engagement Algorithms
    • 24:28 The Impact of Mathematics on Financial Decisions
    • 29:54 Empowering Through Mathematical Literacy
    • 32:23 Exploring Key Themes in Mathematics

    Follow Noah on Twitter, BlueSky, Instagram, LinkedIn and on his Website
    Subscribe to Breaking Math wherever you get your podcasts.
    Become a patron of Breaking Math for as little as a buck a month

    Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTok

    Follow Autumn on Twitter and Instagram

    Become a guest here

    email: breakingmathpodcast@gmail.com
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    33 分
  • What are Swim Training Patterns?

    What are Swim Training Patterns?
    2025/07/29

    In this conversation, Dr. Christoph Bartneck discusses the intersection of swimming and computer science, exploring how mathematical patterns can enhance swim training. He introduces the concept of a formal swim markup language to improve data exchange and training efficiency. The discussion also delves into the visualization of swimming techniques, the importance of mental engagement in training, and the aesthetic appeal of mathematics. Christoph shares insights on the challenges of writing his book and his vision for creating a global community around swimming and mathematics.

    Takeaways

    • Programming languages can optimize swim training.
    • There's a gap in literature between math and sports science.
    • Data exchange in swimming training is challenging.
    • Visualizing swimming techniques aids in understanding.
    • Mathematical patterns can enhance training routines.
    • Repetitive tasks in swimming can be likened to repetitive songs.
    • Engagement in training is crucial for success.

    Chapters

    • 00:00 The Motivation Behind Swim Training Patterns
    • 02:32 Intersection of Swimming and Computer Science
    • 05:56 Challenges in Measuring and Documenting Swim Performance
    • 09:32 The Role of Patterns in Swim Training
    • 11:54 Mathematical Patterns and Their Application in Swimming
    • 15:14 Exploring Repetitiveness in Music and Swim Training
    • 18:08 Art Projects and Mathematical Patterns
    • 21:13 Fermat's Theorem and Impossible Squares
    • 23:14 Making Math Accessible in Swim Training
    • 26:40 The Importance of a Shared Language in Coaching
    • 27:35 Applying Pattern-Based Approaches to Sports
    • 29:17 The Role of Structure in Training Across Sports
    • 30:02 Current Use of Frameworks in Elite Swimming
    • 30:10 Innovative Training Philosophies in Swimming
    • 32:30 Programming Languages and Their Applications in Sports Science
    • 34:56 The Joy of Writing and Creating
    • 38:59 Challenges in Writing and Communicating Mathematical Concepts
    • 41:37 The Journey of a Book and Community Engagement

    Follow Christoph on his YouTube Channel and on bartneck.de.
    Subscribe to Breaking Math wherever you get your podcasts.
    Become a patron of Breaking Math for as little as a buck a month

    Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTok

    Follow Autumn on Twitter and Instagram

    Become a guest here

    email: breakingmathpodcast@gmail.com
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    46 分
  • AI Ethics: Algorithms Go To College

    AI Ethics: Algorithms Go To College
    2025/07/22

    In this episode of Breaking Math, Autumn explores the complex world of AI ethics, focusing on its implications in education, the accuracy of AI systems, the biases inherent in algorithms, and the challenges of data privacy. The discussion emphasizes the importance of ethical considerations in mathematics and computer science, advocating for transparency and accountability in AI systems. Autumn also highlights the role of mathematicians in addressing these ethical dilemmas and the need for society to engage critically with AI technologies.

    Takeaways

    • AI systems can misinterpret student behavior, leading to false accusations.
    • Bias in AI reflects historical prejudices encoded in data.
    • Predictive analytics can help identify at-risk students but may alter their outcomes.
    • Anonymization of data is often ineffective in protecting privacy.
    • Differential privacy offers a way to share data while safeguarding individual identities.
    • Ethics should be a core component of algorithm design.
    • The impact of biased algorithms can accumulate over time.
    • Mathematicians must understand both technical and human aspects of AI.
    • Society must question the values embedded in AI systems.
    • Small changes in initial conditions can lead to vastly different outcomes.

    Chapters

    • 00:00 Introduction to AI Ethics
    • 02:14 The Accuracy and Implications of AI in Education
    • 04:14 Bias in AI and Its Consequences
    • 05:45 Data Privacy Challenges in AI
    • 06:37 Mathematical Solutions for Ethical AI
    • 08:04 The Role of Mathematicians in AI Ethics
    • 09:42 The Future of AI and Ethical Considerations

    Subscribe to Breaking Math wherever you get your podcasts.

    Become a patron of Breaking Math for as little as a buck a month

    Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTok

    Follow Autumn on Twitter and Instagram

    Become a guest here

    email: breakingmathpodcast@gmail.com
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    12 分
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