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Breaking Math Podcast

Author: Gabriel Hesch and Autumn Phaneuf

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Hosted by Gabriel Hesch and Autumn Phaneuf, who have advanced degrees in electrical engineering and industrial engineering/operations research respectively, come together to discuss mathematics as a pure field all in its own as well as how it describes the language of science, engineering, and even creativity.  

Breaking Math brings you the absolute best in interdisciplinary science discussions -  bringing together experts in varying fields including artificial intelligence, neuroscience, evolutionary biology, physics, chemistry and materials-science, and more -  to discuss where humanity is headed.

website:  breakingmath.io 

linktree:  linktree.com/breakingmathmedia

email:  breakingmathpodcast@gmail.com

147 Episodes
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This episode is an interview with OnlineKyne [https://www.instagram.com/onlinekyne/?hl=en], the author of the book Math in Drag [https://www.onlinekyne.com/]. The conversation focuses on how to be an effective online educator and covers various topics in mathematics, including Cantor's infinite sets, probability, and statistics. The interview also delves into the process of writing the book and highlights the connection between math and drag. The chapters in the conversation cover the journey of a content creator, tips for science content creators, the concept of infinity, the significance of celebrity numbers, game theory, probability, statistics, and the ethical implications of math and drag. Takeaways * Being an effective online educator involves distilling complex concepts into concise and valuable content. * Math and drag share similarities in breaking rules and defying authority. * Mathematics has a rich history and is influenced by various cultures and individuals. * Statistics can be used to manipulate and deceive, so it is important to be critical of data and its interpretation. Chapters 00:00 Introduction 00:54 Journey as a Content Creator 03:50 Tips and Tricks for Science Content Creators 04:15 Writing the Book 05:12 Math and Drag 06:40 Infinite Possibilities 07:35 Celebrity Numbers 08:59 How to Cut a Cake and Eat It 09:57 Luck Be a Ladyboy 12:44 Illegal Math 16:02 The Average Queen 25:03 Math and Drag Breaking the Rules 27:22 Conclusion Subscribe to Breaking Math wherever you get your podcasts. Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://www.patreon.com/breakingmath], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Folllow Gabe on Twitter [https://x.com/TechPodGabe]. email: breakingmathpodcast@gmail.com
In this conversation, Gabriel Hesch interviews Kyne Santos [https://www.onlinekyne.com/], an online creator who combines art, music, and performance in math education. They discuss the intersection of math and music, the controversy surrounding math and drag, and the creative side of math. They also explore topics such as topology, mathematical shapes, and influential books in math. The conversation highlights the importance of challenging traditional definitions and finding new and innovative ways to engage with math education. Takeaways * Math and music have a strong connection, and math can be used to analyze, manipulate, and create music. * Combining art and math education can make learning math more engaging and fun. * Topology is a branch of mathematics that relaxes the rigid terms used in geometry and focuses on the similarities and differences between shapes. * Mathematical discoveries can come from playing around and exploring different possibilities. * Challenging traditional definitions and thinking creatively are important aspects of math education. Chapters 00:00 Introduction: Best Song Ever Created 02:03 Introduction of Guest: Kyne Santos 03:00 Math and Drag: Combining Art and Math Education 07:45 Addressing Controversy: Math and Drag 08:15 Music and Math: The Intersection 09:14 Mathematical Shapes: Mobius Strip 10:10 Topology vs Geometry 13:01 Holes and Topology 15:14 Topology and Thought Experiments 21:13 Aperiodic Monotiles: New Math Discovery 23:02 New Shapes and Descriptive Rules 25:26 Influential Books: The Quantum Story and Incomplete Nature 27:01 Conclusion and Next Episode Preview Subscribe to Breaking Math wherever you get your podcasts. Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://www.patreon.com/breakingmath], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Folllow Gabe on Twitter [https://x.com/TechPodGabe]. email: breakingmathpodcast@gmail.com
Tom Chivers [https://tomchivers.com/] discusses his book 'Everything is Predictable: How Bayesian Statistics Explain Our World' and the applications of Bayesian statistics in various fields. He explains how Bayesian reasoning can be used to make predictions and evaluate the likelihood of hypotheses. Chivers also touches on the intersection of AI and ethics, particularly in relation to AI-generated art. The conversation explores the history of Bayes' theorem and its role in science, law, and medicine. Overall, the discussion highlights the power and implications of Bayesian statistics in understanding and navigating the world.  The conversation explores the role of AI in prediction and the importance of Bayesian thinking. It discusses the progress of AI in image classification and the challenges it still faces, such as accurately depicting fine details like hands. The conversation also delves into the topic of predictions going wrong, particularly in the context of conspiracy theories. It highlights the Bayesian nature of human beliefs and the influence of prior probabilities on updating beliefs with new evidence. The conversation concludes with a discussion on the relevance of Bayesian statistics in various fields and the need for beliefs to have probabilities and predictions attached to them. Takeaways * Bayesian statistics can be used to make predictions and evaluate the likelihood of hypotheses. * Bayes' theorem has applications in various fields, including science, law, and medicine. * The intersection of AI and ethics raises complex questions about AI-generated art and the predictability of human behavior. * Understanding Bayesian reasoning can enhance decision-making and critical thinking skills. AI has made significant progress in image classification, but still faces challenges in accurately depicting fine details. * Predictions can go wrong due to the influence of prior beliefs and the interpretation of new evidence. * Beliefs should have probabilities and predictions attached to them, allowing for updates with new information. * Bayesian thinking is crucial in various fields, including AI, pharmaceuticals, and decision-making. * The importance of defining predictions and probabilities when engaging in debates and discussions. Subscribe to Breaking Math wherever you get your podcasts. Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://www.patreon.com/breakingmath], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Folllow Gabe on Twitter [https://x.com/TechPodGabe]. email: breakingmathpodcast@gmail.com
Summary **Tensor Poster - If you are interested in the Breaking Math Tensor Poster on the mathematics of General Relativity, email us at BreakingMathPodcast@gmail.com In this episode, Gabriel Hesch and Autumn Phaneuf interview Steve Nadis, [https://www.discovermagazine.com/author/snadis/1] the author of the book 'The Gravity of Math [https://www.hachettebookgroup.com/titles/steve-nadis/the-gravity-of-math/9781541604292/].' They discuss the mathematics of gravity, including the work of Isaac Newton and Albert Einstein, gravitational waves, black holes, and recent developments in the field. Nadis shares his collaboration with Shing-Tung Yau and their journey in writing the book. They also talk about their shared experience at Hampshire College and the importance of independent thinking in education.  In this conversation, Steve Nadis discusses the mathematical foundations of general relativity and the contributions of mathematicians to the theory. He explains how Einstein was introduced to the concept of gravity by Bernhard Riemann and learned about tensor calculus from Gregorio Ricci and Tullio Levi-Civita. Nadis also explores Einstein's discovery of the equivalence principle and his realization that a theory of gravity would require accelerated motion. He describes the development of the equations of general relativity and their significance in understanding the curvature of spacetime. Nadis highlights the ongoing research in general relativity, including the detection of gravitational waves and the exploration of higher dimensions and black holes. He also discusses the contributions of mathematician Emmy Noether to the conservation laws in physics. Finally, Nadis explains Einstein's cosmological constant and its connection to dark energy. Chapters 00:00 Introduction and Book Overview 08:09 Collaboration and Writing Process 25:48 Interest in Black Holes and Recent Developments 35:30 The Mathematical Foundations of General Relativity 44:55 The Curvature of Spacetime and the Equations of General Relativity 56:06 Recent Discoveries in General Relativity 01:06:46 Emmy Noether's Contributions to Conservation Laws 01:13:48 Einstein's Cosmological Constant and Dark Energy Subscribe to Breaking Math wherever you get your podcasts. Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://www.patreon.com/breakingmath], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Folllow Gabe on Twitter [https://x.com/TechPodGabe]. email: breakingmathpodcast@gmail.com
Summary:  The episode discusses the 10,000 year dilemma, which is a thought experiment on how to deal with nuclear waste in the future.  Today's episode is hosted by guest host David Gibson, who is the founder of the Ray Kitty Creation Workshop [https://www.youtube.com/@RayKitty]. (Find out more about the Ray Kitty Creation Workshop by clicking here [https://mrdave.raykitty.com/]).   Gabriel and Autumn are out this week, but will be returning in short order with 3 separate interviews with authors of some fantastic popular science and math books including: * The Gravity of Math:  How Geometry Rules the Universe [https://www.hachettebookgroup.com/titles/steve-nadis/the-gravity-of-math/9781541604292/] by Dr. Shing-Tung Yau and Steve Nadis.    This book is all about the history of our understanding of gravity from the theories of Isaac Newton to Albert Einstein and beyond, including gravitational waves, black holes, as well as some of the current uncertainties regarding a precise definition of mass.  On sale now!   * EVERYTHING IS PREDICTABLE: How Bayesian Statistics Explain Our World [https://www.netgalley.com/widget/516523/redeem/23dc460e436c2d0582e559b4d84ee909cf774accba78999f2291a8f97813bae0] by Tom Chivers.  Published by Simon and Schuster.   This book explains the importance of Baye's Theorem in helping us to understand why  highly accurate screening tests can lead to false positives, a phenomenon we saw during the Covid-19 pandemic; How a failure to account for Bayes' Theorem has put innocent people in jail; How military strategists using the theorem can predict where an enemy will strike next, and how Baye's Theorem is helping us to understang machine learning processes - a critical skillset to have in the 21st century. Available 05/07/2024 * A CITY ON MARS: Can we settle space, should we settle space, and have we really thought this through? [https://www.penguinrandomhouse.com/books/639449/a-city-on-mars-by-kelly-and-zach-weinersmith/]  by authors Dr. Kelly and Zach Weinersmith.  Zach Weinersmith is the artist and creator of the famous cartoon strip Saturday Morning Breaking Cereal [https://www.smbc-comics.com/]!   We've got a lot of great episodes coming up!  Stay tuned.
Summary Brain Organelles, A.I. and Defining Intelligence in  Nature-  In this episode, we continue our fascinating interview with GT, a science content creator on TikTok [https://www.tiktok.com/@bearbaitofficial] and YouTube [https://www.youtube.com/@bearbaitofficial] known for their captivating - and sometimes disturbing science content. GT can be found on the handle '@bearBaitOfficial' on most social media channels.   In this episode, we resume our discussion on Brain Organelles -  which are grown from human stem cells - how they are being used to learn about disease, how they may be integrated in A.I.  as well as eithical concerns with them. We also ponder what constitutes intelligence in nature, and even touch on the potential risks of AI behaving nefariously. You won't want to miss this thought-provoking and engaging discussion. 30% Off ZenCastr Discount Use My Special Link to save e 30%  Off Your First Month of Any ZenCastr Paid Plan [https://zen.ai/1e7eBWWMLcSL_G10VxiSlQ]
Join Sofia Baca and her guests Millicent Oriana from Nerd Forensics and Arianna Lunarosa as they discuss energy. The sound that you're listening to, the device that you're listening on, and the cells in both the ear you're using to listen and the brain that understands these words have at least one thing in common: they represent the consumption or transference of energy. The same goes for your eyes if you're reading a transcript of this. The waves in the ears are pressure waves, while eyes receive information in the form of radiant energy, but they both are still called "energy". But what is energy? Energy is a scalar quantity measured in dimensions of force times distance, and the role that energy plays depends on the dynamics of the system. So what is the difference between potential and kinetic energy? How can understanding energy simplify problems? And how do we design a roller coaster in frictionless physics land?[Featuring: Sofia Baca; Millicent Oriana, Arianna Lunarosa] This episode is distributed under a Creative Commons Attribution-ShareAlike 4.0 International License. Full text here: https://creativecommons.org/licenses/by-sa/4.0/
An interview with Dr. Sabine Hossenfelder about her second book Existential Physics [https://www.penguinrandomhouse.com/books/616868/existential-physics-by-sabine-hossenfelder/]. Sabine is host of the famous youtube show Science with Sabine [https://www.youtube.com/@SabineHossenfelder].
The world around us is a four-dimensional world; there are three spatial dimensions, and one temporal dimension. Many of these objects emit an almost unfathomable number of photons. As we developed as creatures on this planet, we gathered the ability to sense the world around us; and given the amount of information represented as photons, it is no surprise that we developed an organ for sensing photons. But because of the amount of photons that are involved, and our relatively limited computational resources, it is necessary to develop shortcuts if we want to simulate an environment in silico. So what is raytracing? How is that different from what happens in games? And what does Ptolemy have to do with 3D graphics? All of this and more on this episode of Breaking Math.
Physical objects are everywhere, and they're all made out of molecules, and atoms. However, the arrangement and refinement of these atoms can be the difference between a computer and sand, or between a tree and paper. For a species as reliant on tool use, the ability to conceieve of, design, create, and produce these materials is an ongoing concern. Since we've been around as humans, and even before, we have been material scientists in some regard, searching for new materials to make things out of, including the tools we use to make things. So what is the difference between iron and steel? How do we think up new things to make things out of? And what are time crystals? All of this and more on this episode of Breaking Math. This episode is released under a Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license. More information here: https://creativecommons.org/licenses/by-nc/4.0/ [Featuring: Sofía Baca, Gabriel Hesch; Taylor Sparks]
Black holes are objects that seem exotic to us because they have properties that boggle our comparatively mild-mannered minds. These are objects that light cannot escape from, yet glow with the energy they have captured until they evaporate out all of their mass. They thus have temperature, but Einstein's general theory of relativity predicts a paradoxically smooth form. And perhaps most mind-boggling of all, it seems at first glance that they have the ability to erase information. So what is black hole thermodynamics? How does it interact with the fabric of space? And what are virtual particles?
The idea of something that is inescapable, at first glance, seems to violate our sense of freedom. This sense of freedom, for many, seems so intrinsic to our way of seeing the universe that it seems as though such an idea would only beget horror in the human mind. And black holes, being objects from which not even light can escape, for many do beget that same existential horror. But these objects are not exotic: they form regularly in our universe, and their role in the intricate web of existence that is our universe is as valid as the laws that result in our own humanity. So what are black holes? How can they have information? And how does this relate to the edge of the universe?
29: War

29: War

2018-07-1437:28

In the United States, the fourth of July is celebrated as a national holiday, where the focus of that holiday is the war that had the end effect of ending England's colonial influence over the American colonies. To that end, we are here to talk about war, and how it has been influenced by mathematics and mathematicians. The brutality of war and the ingenuity of war seem to stand at stark odds to one another, as one begets temporary chaos and the other represents lasting accomplishment in the sciences. Leonardo da Vinci, one of the greatest western minds, thought war was an illness, but worked on war machines. Feynman and Von Neumann held similar views, as have many over time; part of being human is being intrigued and disgusted by war, which is something we have to be aware of as a species. So what is warfare? What have we learned from refining its practice? And why do we find it necessary?
The fabric of the natural world is an issue of no small contention: philosophers and truth-seekers universally debate about and study the nature of reality, and exist as long as there are observers in that reality. One topic that has grown from a curiosity to a branch of mathematics within the last century is the topic of cellular automata. Cellular automata are named as such for the simple reason that they involve discrete cells (which hold a (usually finite and countable) range of values) and the cells, over some field we designate as "time", propagate to simple automatic rules. So what can cellular automata do? What have we learned from them? And how could they be involved in the future of the way we view the world?
The spectre of disease causes untold mayhem, anguish, and desolation. The extent to which this spectre has yielded its power, however, has been massively curtailed in the past century. To understand how this has been accomplished, we must understand the science and mathematics of epidemiology. Epidemiology is the field of study related to how disease unfolds in a population. So how has epidemiology improved our lives? What have we learned from it? And what can we do to learn more from it?
In this episode, Dr. Destine Nock, CEO of Peoples Energy Analytics and a Professor at Carnegie Mellon University, joins Autumn to dive deep into the world of energy equity. They explore how cutting-edge data analytics are revolutionizing the landscape of affordable energy access. As the global demand for sustainable energy solutions continues to grow, the need to ensure fair and inclusive energy distribution becomes more critical than ever. Together, our hosts break down how data-driven insights are being leveraged to develop and implement policies that make energy more accessible to underserved communities, tearing down socioeconomic barriers and paving the way for a more equitable future. Dr. Nock and Autumn discuss the powerful role that advanced analytics play in everything from analyzing consumption patterns to optimizing renewable energy distribution. They explore real-world case studies, highlight key initiatives, and speak with experts who are at the forefront of these transformative efforts. By the end of this episode, you'll understand how strategic use of data can drive lasting change and help us build a world where energy is not a privilege but a right accessible to all. Subscribe to Breaking Math wherever you get your podcasts. Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Dr. Destenie Nock on LinkedIn [https://www.linkedin.com/in/desdes/] and on her website [https://destenienock5.wixsite.com/destenienock]. Check out Peoples Energy Analytics [https://www.peoplesenergyanalytics.com/] as well. Follow Breaking Math on Twitter [https://x.com/breakingmathpod], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/], YouTube [https://www.youtube.com/@BreakingMathPod], TikTok [https://www.tiktok.com/@breakingmathmedia] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Follow Gabe on Twitter [https://x.com/TechPodGabe]. Become a guest here [https://www.breakingmath.io/contact] email: breakingmathpodcast@gmail.com
What is Chaos Theory?

What is Chaos Theory?

2024-11-1215:171

In this captivating episode of Breaking Math, hosts Gabriel and Autumn dive deep into chaos theory—a fascinating branch of mathematics that explores the behavior of complex systems highly sensitive to initial conditions. They break down the butterfly effect, revealing how tiny variations can lead to major consequences and discuss the inherent unpredictability in weather forecasting and the financial markets. The episode also uncovers chaos theory's influence on human physiology, such as heart rate variability, and the mathematical beauty of fractals. Additionally, the hosts explore philosophical viewpoints, emphasizing how accepting life's uncertainties can foster adaptability and resilience. Key Takeaways: Chaos Theory: Small actions can trigger significant outcomes, impacting everything from nature to human-made systems. Butterfly Effect: Demonstrates how tiny differences in initial conditions can lead to vastly different outcomes. Weather Forecasting: An excellent real-world illustration of chaos theory, showing how unpredictable weather can be. Financial Markets: A reminder of the chaotic, complex forces that drive economic shifts and unpredictability. Human Physiology: Chaos theory sheds light on natural processes, like the variability of heart rhythms. Fractals: These intricate patterns showcase self-similarity and are visually striking examples of chaos in nature. Philosophical Implications: Embracing chaos and uncertainty equips us to be more adaptable and creative. Life's Unpredictability: A reflection of chaotic systems, reminding us to value flexibility.   Interconnectedness: Understanding chaos theory enhances our appreciation of how interwoven our world truly is. Keywords: Chaos Theory, Butterfly Effect, Weather Forecasting, Economics, Fractals, Unpredictability, Complex Systems, Human Physiology, Philosophical Implications, Adaptability. Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://x.com/breakingmathpod], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/], YouTube [https://www.youtube.com/@BreakingMathPod], TikTok [https://www.tiktok.com/@breakingmathmedia] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Follow Gabe on Twitter [https://x.com/TechPodGabe]. Become a guest here [https://www.breakingmath.io/contact] email: breakingmathpodcast@gmail.com
In this episode of Breaking Math, we dive deep into the transformative power of large language models (LLMs) like GPT-4 in the fields of chemistry and materials science, based on the article "14 examples of how LLMs can transform materials science and chemistry: a reflection on a large language model hackathon" by Jablonka et al. from the Digital Discovery Journal. Discover how AI is revolutionizing scientific research with predictive modeling, lab automation, natural language interfaces, and data extraction from research papers. We explore how these models are streamlining workflows, accelerating discovery, and even reshaping education with personalized AI tutors. Tune in to learn about real-world examples from a hackathon where scientists used LLMs to tackle some of the most pressing challenges in materials science and chemistry—and what this means for the future of scientific innovation. Keywords: GPT-4, large language models, AI in chemistry, AI in materials science, predictive modeling, lab automation, AI in education, natural language processing, LLM hackathon, scientific research, molecular properties, Digital Discovery Journal, Jablonka Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://x.com/breakingmathpod], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/], YouTube [https://www.youtube.com/@BreakingMathPod], TikTok [https://www.tiktok.com/@breakingmathmedia] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Follow Gabe on Twitter [https://x.com/TechPodGabe]. Become a guest here [https://www.breakingmath.io/contact] email: breakingmathpodcast@gmail.com
In this episode of Breaking Math, we explore the unexpected link between sheep herding and fluid dynamics!  Did you know that the way sheep move in a herd is governed by the same mathematical principles as water flowing in a river? By following simple rules of alignment, cohesion, and separation, sheep create a coordinated, fluid-like movement that scientists can model to predict behavior. Join us as we break down how these principles apply not only to animal herds but also to real-world applications like robotics, autonomous vehicles, and crowd management. Whether you're a math lover, curious about animal behavior, or fascinated by the science behind traffic flow, this episode reveals the incredible power of mathematics in nature. Don't forget to subscribe for more insights into the surprising connections between math and the world around us! Timestamps: 00:00 - Introduction to Sheep Herding and Fluid Dynamics 02:15 - What is Fluid Dynamics? 06:30 - How Sheep Behave Like Particles in a Fluid 10:45 - Mathematical Models of Herding Behavior 16:20 - Real-world Applications: From Farming to Robotics 20:55 - Conclusion & Key Takeaways Tags: #BreakingMath #FluidDynamics #AnimalBehavior #MathInNature #SheepHerding #Robotics #ScienceExplained #EmergentBehavior Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://x.com/breakingmathpod], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/], YouTube [https://www.youtube.com/@BreakingMathPod], TikTok [https://www.tiktok.com/@breakingmathmedia] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Follow Gabe on Twitter [https://x.com/TechPodGabe]. Become a guest here [https://www.breakingmath.io/contact] email: breakingmathpodcast@gmail.com
In this exciting episode of Breaking Math, we explore the groundbreaking discovery of the largest prime number ever found—M136279841, a Mersenne prime with over 41 million digits! Join us as we dive deep into the story behind this astonishing mathematical achievement, led by Luke Durant, a volunteer from the Great Internet Mersenne Prime Search (GIMPS) project. Discover how Mersenne primes work, why they're so important to the world of mathematics, and how cutting-edge technology like GPUs has revolutionized the search for these massive numbers. We also discuss the critical role that prime numbers play in cryptography and online security, making this discovery relevant far beyond just the realm of theoretical mathematics. Learn about the global collaborative effort that made this record-breaking discovery possible, and find out how you can join the hunt for the next giant prime! Whether you're a math enthusiast, a tech geek, or just curious about the wonders of numbers, this episode is packed with insights that will inspire you to think about prime numbers in a whole new way. Key Takeaways: * The discovery of M136279841, a prime number with 41,024,320 digits. * The role of Luke Durant and the GIMPS project in pushing the boundaries of prime number research. * How GPUs are transforming the way we discover massive primes. * The importance of prime numbers in modern cryptography and technology. * The connection between Mersenne primes and perfect numbers. Links Mentioned: * Join the GIMPS project and search for the next prime: www.mersenne.org/download [http://www.mersenne.org/download] * Learn more about Mersenne primes: Mersenne Prime History [http://www.mersenneforum.org/] Become a patron of Breaking Math [https://www.patreon.com/breakingmath] for as little as a buck a month Follow Breaking Math on Twitter [https://x.com/breakingmathpod], Instagram [https://www.instagram.com/breakingmathmedia/], LinkedIn [https://www.linkedin.com/company/breaking-math/], Website [https://breakingmath.io/], YouTube [https://www.youtube.com/@BreakingMathPod], TikTok [https://www.tiktok.com/@breakingmathmedia] Follow Autumn on Twitter [https://x.com/1autumn_leaf] and Instagram [https://www.instagram.com/1autumnleaf/] Follow Gabe on Twitter [https://x.com/TechPodGabe]. Become a guest here [https://www.breakingmath.io/contact] email: breakingmathpodcast@gmail.com
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Comments (17)

josef

very informative.... thanksss

Jan 31st
Reply

Alex Clark

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Jul 1st
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Yousef Parrish

If you're looking for the best math for kids book, there are a few things to keep in mind. Toddlers can already grasp basic math concepts. In order to make math more fun, teach them simple math concepts through play and daily experiences. For older children, you can introduce more complex math concepts with https://www.frolicplayspace.com/target-10/ age-appropriate activities. However, if your child is just starting kindergarten, you may want to look for a more fun math book.

Apr 22nd
Reply

drtfh serfgre

I teach mathematics at one of the universities in my city. Last week I searched the Internet for various interesting articles and tasks for a story at the university. In the end, I found a very useful website that contains a large number of different articles and facts related to mathematics. One of them was - https://artdroid.com/what-are-the-factors-of-7/ . It seemed to me a good material for students. I advise you to study it too.

Jan 13th
Reply

Joshua Jarrott

What a fun episode! The name "Peirce" in "peirce quincuncial projection" is pronounced like "purse", after the 19th century philosopher-logician Charles Sanders Peirce.

Oct 2nd
Reply

Thomas Martin

Fascinating conversation.

Sep 16th
Reply

Andrew Dias

I really wish there was another podcast that goes over the same topics but without Sophia hosting. She is not great at explaining concepts. There is the tendency to do the typical thing of trying to simplify ideas, but in the process end up making it too obscure to really understand. Case in point is the fact that her mom (who teaches math) can't understand what is being explained.

Feb 15th
Reply

Andrew Dias

Good episode content. A couple things: much of the discussion about the individual axioms become convoluted with the language and examples that are used. The point is to either clearly state the axiom or provide examples that simplify the understanding, not complicate it. Also, Gödel is roughly pronounced "GER-dle", not "go-DELL."

Nov 27th
Reply

Numoru WE3

Thank y'all for this episode... I've been down and depressed for a sec, this brought me back...thanks for the knowledge, laughs, and time taken for doing this during everything.love

Jun 16th
Reply

Christi Sewell

False assumptions, bad conclusions. What about the modern example of Jaime Escalante and his ability to challenge elitism to economically challenged young adults with no time to study? Still they overcame it. Why? They wanted something enough to MAKE time for it and they had a teacher that demanded discipline.

May 24th
Reply

Koenigsegg

Awesome

Jul 5th
Reply

Vincent Kong

keep up the good work, love from UK

Apr 23rd
Reply

Paul Billington

wonderful

Apr 7th
Reply

Susa Rantanen

Just what i was looking for, although I can barely keep up sometimes, since my knowledge in math isn't great. Still super interesting!

Oct 12th
Reply

Elham Nazif

Lohnverstoß

Oct 10th
Reply

David Calano

Great podcast!

Apr 29th
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Pratiksha Devshali

it's superb.. loved it.. the creators of this podcast are great :)

Oct 27th
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