This episode explores how AI, specifically OpenAI's recent breakthrough in solving an 80-year-old math conjecture, is transforming the field of mathematics. Featuring insights from Professor Daniel Litt, the discussion covers the implications of AI in mathematical research, the value of human verification, and the future of mathematical practice.

Key topics

AI solving long-standing mathematical problems

The role of human verification in AI-generated proofs

Implications of AI breakthroughs in discrete geometry

The future of mathematical research with AI

Number theory and algebraic constructions in AI discoveries

Chapters

00:00 Introduction to the Conjecture and Its Significance

01:15 Understanding the Erdős Problem

04:34 The Role of AI in Solving Mathematical Problems

09:17 The Implications of AI in Mathematics

10:32 AI vs Human Mathematicians: A Comparative Analysis

17:20 Standards for AI-Generated Proofs

21:10 Corporate Interests in Mathematical Research

24:42 The Future of Mathematics and AI

27:50 Final Thoughts on AI and Mathematics

31:37 Revolutionizing Mathematics: AI's Breakthrough in Discrete Geometry

37:37 Exploring the Implications: AI and the Future of Mathematics

38:03 The Role of AI in Mathematics

39:23 Human Value in the Age of AI

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In this episode with award-winning journalist and author Maia Szalavitz challenges the idea that addiction is simply about pleasure or willpower. Instead, she explains addiction as compulsive behavior that continues despite negative consequences — and shows why withdrawal, dependence, and addiction are not the same thing.

The conversation explores “wanting” versus “liking,” why dopamine is misunderstood, how social media and AI can exploit reward systems, and why punishment often fails. Ultimately, Szalavitz argues that recovery depends less on tough love and more on connection, purpose, safety, and care.

Chapters

00:00 Understanding Addiction: Definitions and Mechanisms

10:43 The Role of Dopamine in Addiction

14:18 Addiction as a Learning Disorder

16:22 Substance vs. Experience: The Nature of Addiction

20:13 Evidence-Based Methods for Overcoming Addiction

25:20 Finding Meaning and Purpose Beyond Addiction

33:30 The Pursuit of Meaningful Experiences

34:15 Understanding Dopamine and Pleasure

39:10 The Complexity of Addiction

43:00 Social Media and Addiction Dynamics

50:42 Generational Perspectives on Technology and Addiction

57:53 Lessons Learned in Addiction Science

01:02:03 Rethinking Addiction: A New Perspective

01:03:54 The Compulsive Nature of Addiction

01:04:14 Understanding Addiction Beyond Pleasure

01:05:27 The Importance of Connection and Compassion

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In this episode of Breaking Math, Autumn and Noah speak with Ron Wasserstein, Executive Director of the American Statistical Association, about what statistics means in a world increasingly shaped by AI, misinformation, and fragile public trust. Wasserstein argues that statistics is not merely a “bag of tools,” but a way of thinking: asking where data comes from, what it leaves out, how uncertainty should be communicated, and when numbers are being used to illuminate rather than manipulate.

Chapters

00:00 The Golden Age of Statistics

02:36 AI's Impact on Statistics

08:16 Data as Fuel for AI

10:55 Bias in AI and Statistics

14:01 Preparing Future Statisticians

16:58 Bridging the Gap: Academia and Industry

22:58 The Misconception of Statistics

23:08 The Role of Statistics in Public Discourse

26:20 The American Statistical Association's Mission

32:18 Statistics and Politics: A Historical Perspective

36:02 Addressing Misinformation and Misuse of Data

39:51 The Importance of Statistical Literacy

44:01 Misconceptions About Statistics and Expertise

46:57 The Essence of Statistics

47:22 Statistics as a Way of Thinking

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What if ransomware did not begin with criminals, but with curiosity? In this episode of Breaking Math, Autumn and Noah talk with Anja Shortland, professor of political economy at King’s College London and author of Dark Screens.

This conversation explores how playful hacking evolved into professionalized cybercrime, why ransomware gangs operate like morally questionable internet startups, how cryptocurrency made ransomware scalable, and why hospitals, governments, universities, and critical infrastructure remain especially vulnerable. We also dig into the mathematics behind encryption, asymmetric cryptography, game theory, negotiation, cyber insurance, and the uncomfortable trade-offs between freedom, privacy, and regulation.

Chapters

00:00 The origins of ransomware and early hacker culture

02:13 The evolution of ransomware attacks since 2013

03:14 The paradox of cybercriminals as entrepreneurs

06:19 Early hackers: Steve Jobs and Wozniak as pioneers

12:34 The moral and legal landscape of hacking and cybercrime

13:39 The importance of cybersecurity awareness for individuals

15:03 The arms race: attackers vs defenders and the role of math

16:02 The technological innovations behind ransomware

19:21 Asymmetric encryption and cryptocurrency in ransomware

20:53 Bitcoin and the dark web: enabling cybercrime

22:45 The impact of AI on future cyber threats and defenses

34:07 The future of ransomware and cybersecurity challenges

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What does it actually mean for a number to be “big”? In this episode of Breaking Math, Autumn chats with mathematician Richard Elwes to explore how huge numbers reveal the limits of human intuition, language, and even mathematics itself. The discussion moves from exponential growth in pandemics and finance to numbers larger than the universe itself, emerging in games like chess and abstract possibility spaces. Finally, it reaches one of the most profound ideas in modern mathematics: that there are true statements about numbers that can never be proven. This episode challenges how we think about scale, complexity, and the systems we rely on to make sense of reality.

Key Topics

Limits of ancient numeral systems like Roman numerals

Mathematical logic and the concept of huge numbers

Evolution of number notation from Roman to Hindu-Arabic systems

The significance of place value in expressing large numbers

The Mayan long count and its implications for understanding time scales

Chapters

00:00 Introduction and Inspiration for the Book

01:39 Redefining Big Numbers

01:55 Limits of Numerical Systems

05:33 Evolution of Number Sense

10:02 Language and Numerical Understanding

11:53 Cultural Influences on Numerical Systems

14:18 Hacks in Ancient Number Systems

16:55 Archimedes and the Concept of Infinity

22:01 The Importance of Place Value

25:45 Mayan Cosmology and Time Scales

31:55 Exponential Growth and Its Dangers

32:20 Understanding Exponential Growth

36:14 The Dangers of Exponential Growth

37:23 Limits of Exponential Growth in the Physical World

39:42 Exploring Possibility Space

45:38 Goodstein's Theorem and Mathematical Logic

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In this episode we sit down with Sheamus McGovern, founder of the Open Data Science Conference (ODSC AI), to unpack what AI actually looks like. Sheamus shares what’s really happening behind the scenes of the AI boom and why the biggest shift isn’t job loss, but a complete transformation of skills. From explaining why AI is reshaping—not replacing—jobs, to breaking down the gap between hype and real-world applications, this conversation explores how early algorithmic trading foreshadowed today’s AI revolution, why open-source tools like TensorFlow and PyTorch changed everything, what the “AI Skill Flip” means for your career, and why even data scientists are questioning their future. Along the way, the biggest mistake people make when trying to learn AI, and why the smartest approach isn’t to learn everything—but to start intentionally and build from there.

Timestamps

00:00 – The biggest misconception about AI

02:00 – Algorithmic trading and the origins of AI in finance

05:00 – The birth of ODSC AI and the data science movement

09:30 – Breakthrough moments in AI

16:30 – Democratization of AI and open-source tools

19:00 –The AI Skill Flip

24:00 – The truth about AI replacing jobs

27:00 – Real-world AI success stories

32:30 – How to actually start learning AI today

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In this episode, mathematician and award-winning magician Matt Baker explores the fascinating intersection of mathematics and magic, revealing how mathematical principles, intuition, and storytelling create unforgettable illusions. From a mind-reading trick based on the classic concept of “casting out nines” to his groundbreaking research on the Riemann–Roch theorem for graphs, Baker demonstrates how creativity and pattern recognition drive both mathematical discovery and magical performance.

Chapters

00:00 The Interplay of Math and Magic

04:58 Aesthetic Connections in Math and Magic

08:57 Balancing Family, Math, and Magic

12:34 The Impact of Magic on Mathematical Thinking

16:32 The Art of Clarity in Communication

16:44 A Live Magic Demonstration

25:14 Intuition and Pattern Recognition in Math

30:03 The Riemann-Roch Theorem for Graphs

41:42 The Role of AI in Mathematics and Magic

50:21 The Art of Communicating Mathematics

50:47 The Magic of Math and Performance

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In this episode, Thomas Plümper and Eric Neumayer explore the hidden challenges in modern science, from outright fraud to the subtler practice of “tweaking” data that distorts results. They examine why the self-correcting nature of science often falls short, how incentives and academic pressure drive misconduct, and the double-edged role of AI in both enabling and detecting fraud. The conversation also tackles debates around p-values and statistical reasoning, shares cautionary case studies, and proposes solutions like greater data transparency and stronger verification standards.

Chapters

00:00 Introduction to Fraud in Research

06:21 The Nature of Fraud Detection

08:56 Incentives and Motivations for Fraud

10:43 Self-Correction in Science

12:13 Understanding Statistical Significance

13:04 The Role of Replication in Research

14:32 Bayesian vs Frequentist Approaches

23:09 Understanding Bayesian Statistics and Its Implications

26:24 The Humility of Empirical Science

27:16 Concrete Examples of Scientific Fraud

32:52 Proposed Solutions to Scientific Fraud

34:50 The Reality of Scientific Fraud and Human Nature

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This Women in History Mini-Series episode with Dr. Victoria Bateman explores the inspiring story of Mary T. Washington Wylie, the first African-American woman CPA, her challenges, achievements, and legacy in breaking racial and gender barriers in the early 20th century. Mathematics is supposed to be objective—but access to it has never been equal.

Chapters

00:00 Introduction to Mary T. Washington Wylie

00:48 Early Life and Challenges

02:58 Breaking Barriers in Accountancy

05:25 Pioneering a Path for Others

07:21 Legacy and Impact

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In this episode of Breaking Math, we sit down with Dr. Hortensia Soto, former president of the Mathematical Association of America, to explore the role of mathematics in a world shaped by AI, education, and access. We discuss how debates in math are often really about opportunity and inclusion, how educators can navigate the rapid pace of AI, and why communication and human connection matter more than ever. The conversation also highlights the importance of financial literacy, embodied learning, and collaboration, reframing mathematics not as a set of answers, but as a way of thinking grounded in curiosity, effort, and relationships.

Chapters

00:00 Introduction to Hortensia Soto and the Math Community

02:48 The Role of AI in Mathematics

05:17 Access to Mathematics and Its Political Nature

07:34 The Importance of Financial Literacy in Math Education

10:19 Communication Skills for Mathematicians

13:06 The Culture of the Mathematical Association of America

15:29 Reflections on Leadership in the Math Community

25:01 Innovative Approaches to Mathematics Education

25:50 Recognizing Math Identity in Students

27:02 Nurturing Student Potential

35:31 The Role of AI in Learning

38:26 The Human Element in Mathematics

39:51 Mathematics Beyond Symbols and Procedures

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This Women in History Mini-Series episode with Dr. Victoria Bateman explores the groundbreaking contributions of Florence Nightingale, highlighting her use of data and statistics to revolutionize healthcare and public health during the 19th century. Discover how her innovative use of data visualization and her perseverance against gender biases transformed modern nursing and public health policy.

Chapters

00:00 Introduction to Florence Nightingale's Legacy

02:21 The Crimean War and Nightingale's Impact

05:18 Data Collection and Analysis in Healthcare

07:18 Overcoming Gender Bias in Medicine

09:23 Innovations in Data Visualization

11:59 Nightingale's Lasting Influence and Conclusion

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