Breaking Math Podcast

In this episode of Breaking Math, hosts Autumn and Gabriel take a deep dive into the paper “Towards Equilibrium Molecular Conformation Generation with GFlowNets” by Volokova et al., published in the Digital Discovery Journal by the Royal Society of Chemistry. They explore the cutting-edge intersection of molecular conformations and machine learning, comparing traditional methods like molecular dynamics and cheminformatics with the innovative approach of Generative Flow Networks (GFlowNets) for molecular conformation generation.The episode covers empirical results that showcase the effectiveness of GFlowNets in computational chemistry, their scalability, and the role of energy estimators in advancing fields like drug discovery. Tune in to learn how machine learning is transforming the way we understand molecular structures and driving breakthroughs in chemistry and pharmaceuticals.Keywords: molecular conformations, machine learning, GFlowNets, computational chemistry, drug discovery, molecular dynamics, cheminformatics, energy estimators, empirical results, scalability, math, mathematics, physics, AIBecome a patron of Breaking Math for as little as a buck a monthYou can find the paper  “Towards equilibrium molecular conformation generation with GFlowNets” by Volokova et al in Digital Discovery Journal by the Royal Society of Chemistry.Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

Mathematical Patterns in Plants: Fibonacci, Golden Ratio & Nature's Hidden Math with Christophe Gole & Nancy PickIn this episode of Breaking Math, host Autumn interviews authors Christophe Gole and Nancy Pick about the captivating world of mathematical patterns in plants, inspired by their book Do Plants Know Math?. Explore the intersection of mathematics and biology as they discuss the Fibonacci sequence, the golden ratio, and spiral formations that reveal nature's mathematical beauty. Learn about the optimization of plant structures, the role of women in mathematics, and get recommendations for further reading. Topics include phyllotaxis, fractals, and their connections to AI, physics, and topology.Keywords: mathematics, biology, plant math, Fibonacci, phylotaxis, spirals, golden ratio, fractals, nature, science, women in math,topology, ai, physics, math, plants, gardening Become a patron of Breaking Math for as little as a buck a monthYou can connect with Christophe Gole and Nancy Pick on LinkedIn, and find their Book “Do Plants Know Math?” on Amazon.Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

Math & Cartography: Dr. Paula Rowinska on Map Projections, Gerrymandering & Real-World MathIn this episode of Breaking Math, host Autumn interviews Dr. Paula Rowinska about her unique journey from earning a PhD in mathematics to writing about math and cartography. They discuss the fascinating connection between map-making and mathematics, debunking misconceptions about map projections and exploring key topics like the coastline paradox, gerrymandering, and the traveling salesman problem. Learn how these mathematical concepts play a crucial role in areas like crime analysis, geopolitics, and more. Perfect for enthusiasts of math, cartography, and real-world problem-solving.The conversation also celebrates the contributions of underrepresented women in mathematics and underscores the importance of math in everyday life. Tune in to discover how mathematics shapes our understanding of the world through cartography, topology, and even AI.Keywords: mathematics, cartography, map projections, coastline paradox, gerrymandering, women in math, traveling salesman problem, crime analysis, topology, metric map, ai, physics, mathBecome a patron of Breaking Math for as little as a buck a monthFollow Dr. Paula Rowinska at paulinarowinska.com and @PaulaRowinska on Twitter. You can also find her book Mapmatics on Amazon.Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

In this conversation, Gabriel and Autumn interview Jeff Perry, a career coach and author of the book 'The Intentional Engineer'. They discuss the importance of being intentional in one's career, understanding one's passions and skills, and building a strong professional network. Jeff shares his journey from being an engineer to becoming an engineer coach and offers advice on how to navigate career transitions. They also explore the concept of 'genius zones' and how to identify and leverage one's unique strengths and talents. In this conversation, Jeff discusses the concept of the zone of incompetence, competence, excellence, and genius. They share personal anecdotes and examples to illustrate these zones and emphasize the importance of self-awareness and collaboration. They also touch on the role of mindset in driving behavior and results, particularly in the context of engineering and tech careers. Jeff offers coaching and resources for individuals looking to make intentional career shifts or upgrades.Keywords: career, intentionality, engineering, skills, passions, network, genius zones, strengths, talents, zone of incompetence, zone of competence, zone of excellence, zone of genius, self-awareness, collaboration, mindset, engineering, tech careers, intentional career shiftsSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Jeff Perry on LinkedIn or learn more at jeff-perry.com. You can also find his book The Intentional Engineer, on Amazon.Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

Math & Language: Creativity, Quantification, and Making Math Accessible with Ben OrlinIn this episode of Breaking Math, hosts sit down with Ben Orlin, author of Math for English Majors and Math with Bad Drawings, to explore the intersection of math and language. Discover the unique skill sets required for mathematics and creativity, how math education can be made more accessible, and the role of quantification in empowering individuals across various fields, including literature and the arts. The conversation highlights the historical contributions of women in math, including the impact of Einstein’s wife on his work. Ben also shares insights into his writing process and the challenges of making math relatable to a broad audience. Learn how mathematical thinking can enhance one's appreciation for literature and the world.Keywords: math, language, skill sets, math education, accessibility, quantification, power of math, women in math, Einstein's wife, math, literature, book, writing, perspective, abstraction, relationshipsSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Ben Orlin on Twitter, and on his websites mathwithbaddrawings.com and mathgameswithbaddrawings.com  and find his book “Math for English Majors” on AmazonFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

In this episode Autumn and Dr. Jonathan Schwabish discuss the importance of strategic thinking in data visualization and the key elements of good data. He emphasizes the need to understand the data and how it was collected, as well as the importance of starting bar charts at zero. He also highlights common mistakes in data visualization, such as distorting or lying with visuals, and the potential impact of data visualization on policy decisions. Looking to the future, he discusses the role of AI in data visualization, the integration of AI into visualization tools, and the potential of augmented reality and virtual reality in data visualization. Jon Schwabish discusses the different data visualization tools he uses, including Excel, R, Tableau, Datawrapper, and Flourish. He emphasizes the importance of choosing the right tool for the specific use case and audience. He also highlights the need for policymakers and individuals to be trained in interpreting and using data visualizations effectively. Schwabish discusses the ethical considerations in data visualization, such as using inclusive language and considering accessibility.Keywords: data visualization, strategic thinking, good data, common mistakes, impact on policy decisions, AI, augmented reality, virtual reality, data visualization tools, Excel, R, Tableau, Datawrapper, Flourish, policymakers, data interpretation, ethical considerations, inclusive language, accessibilitySubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Jon Schwabish  on Twitter  and on YouTube. Also go give PolicyViz Podcast a followFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

In this episode, Gabriel and Autumn interview mathematician, comedian, and author Matt Parker about his latest book, "Love Triangle." They discuss the unique page numbering system in the book, which is based on the sine function, and how it adds an extra layer of discovery for readers. They also explore the use of triangles and quads in 3D modeling, the concept of Perlin noise, and the perception of randomness. The conversation touches on the intersection of mathematics and creativity, as well as the practical applications of mathematical concepts in various fields. The conversation explores various topics related to mathematics, including the analysis of the Mona Lisa, the use of math in playing pool, the discovery of new shapes, and the application of math in various fields. The speakers discuss the motivation behind exploring these topics and the interplay between math and art. They also provide advice for science and math content creators on YouTube.Keywords: mathematics, book, Love Triangle, page numbering, sine function, triangles, quads, 3D modeling, Perlin noise, randomness, creativity, practical applications, mathematics, Mona Lisa, parallax, pool, shapes, Fourier analysis, YouTube, physics, AI, machine learningSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Matt Parker on Twitter  and on YouTube at @StandUpMaths and find his book "Love Triangle" on AmazonFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

Surprise! It's a Friday episode for you! Yes, yes it is a rerun, but we wanted to share it anyways.  We can't wait for our fall lineup because it's packed with surprises. See you back on Tuesday. Keywords: Black holes, gravity, universe, physics, ai, machine learning, education, statistics, engineering, humanitySubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

It's the last week of our summer break and we have 2 episodes this week for you as a little treat. So check out our show on Friday too for a little bit more fun. We can't wait for our fall lineup because it's packed with surprises. If you have not listened to the last two episodes, then we'd highly recommend going back and listening to those. We're choosing to present this information this way because otherwise we'd waste most of your time re-explaining concepts we've already covered.Black holes are so bizarre when we measured against the yardstick of the mundanity of our day to day lives that they inspire fear, awe, and controversy. In this last episode of the Abyss series, we will look at some more cutting-edge problems and paradoxes surrounding black holes. So how are black holes and entanglement related? What is the holographic principle? And what is the future of black holes?Keywords: Black holes, gravity, universe, physics, ai, machine learning, education, statistics, engineering, humanitySubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

Happy Summer! We have another week of our summer break after this episode from 2018. We will be back shortly with more content and surprises! 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?Keywords: Black holes, gravity, universe, physics, ai, machine learning, education, statistics, engineering, humanitySubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

Happy Summer! Check out part one of our three part series on black holes from 2018. Enjoy! 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?Keywords: Black holes, gravity, universe, physics, ai, machine learning, education, statistics, engineering, humanitySubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

In this minisode, Autumn explores the basics in the world of journal rankings and metrics. She discusses the importance of journal rankings and how they are determined, focusing on metrics like impact factor, mathematical citation quotient (MCQ), and publication power approach (PPA). She explains how these metrics provide insights into a journal's influence and performance, but also emphasizes the need for a comprehensive evaluation of research beyond just metrics.Keywords: journal rankings, journal metrics, impact factor, mathematical citation quotient, publication power approach, research evaluation, math, physics, ai, machine learning, education, publishing, academic journalsSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

In this episode Autumn and Anil Ananthaswamy discuss the inspiration behind his book “Why Machines Learn” and the importance of understanding the math behind machine learning. He explains that the book aims to convey the beauty and essential concepts of machine learning through storytelling, history, sociology, and mathematics. Anil emphasizes the need for society to become gatekeepers of AI by understanding the mathematical basis of machine learning. He also explores the history of machine learning, including the development of neural networks, support vector machines, and kernel methods. Anil highlights the significance of the backpropagation algorithm and the universal approximation theorem in the resurgence of neural networks.Keywords: machine learning, math, inspiration, storytelling, history, sociology, gatekeepers, neural networks, support vector machines, kernel methods, backpropagation algorithm, universal approximation theorem, AI, ML, physics, mathematics, scienceYou can find Anil Ananthaswamy on Twitter @anilananth and his new book “Why Machines Learn”Subscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

This discussion Autumn and Gabe delves into Ismar Volic's personal background and inspiration for writing the book, “Making Democracy Count” as well as the practical and theoretical aspects of voting systems. Additionally, the conversation explores the application of voting systems to everyday decision-making and the use of topological data analysis in understanding societal polarization. The conversation covers a wide range of topics, including data visualization, gerrymandering, electoral systems, and the intersection of mathematics and democracy. Volic, shares insights on the practical implications of implementing mathematical improvements in electoral systems and the legal and constitutional hurdles that may arise. He also discusses the importance of educating oneself about the quantitative underpinnings of democracy and the need for interdisciplinary discussions that bridge mathematics and politics.Keywords: math podcast, creativity, mascot, background, Matlab, ranked choice voting, elections, author's background, inspiration, voting systems, topological data analysis, societal polarization, mathematics, democracy, data visualization, gerrymandering, electoral systems, interdisciplinary discussions, practical implications, legal hurdles, constitutional considerationsYou can find Ismar Volic on Twitter and LinkedIn @ismarvolic. Please go check out the Institute for Mathematics and Democracy and Volic’s new book “Making Democracy Count”Subscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTokFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Become a guest hereemail: [email protected]

In this conversation, Gabe and Autumn celebrate the 101st episode of Breaking Math and discuss the evolution of the podcast. They highlight the importance of creativity in teaching mathematics and share their plans to expand Breaking Math into Breaking Math Media. They also discuss the history of physics and the big questions that inform the podcast. The hosts express their desire to collaborate with listeners and explore practical applications of math in different fields. They also mention books like 'A Quantum Story' and 'Incomplete Nature' that delve into the mysteries of quantum mechanics and consciousness. The hosts highlight the unique and creative nature of their podcast, inviting listeners to join them in the Math Lounge, a metaphorical nightclub where math and creativity intersect.Keywords: Breaking Math, podcast, creativity, mathematics, Breaking Math Media, physics, history, quantum mechanics, book discussion, double-slit experiment, quantum mechanics, interdisciplinary discussions, machine learning, neuroscience, gamification of math, collaboration, practical applications, consciousness, Math LoungeSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTubeFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.email: [email protected]

In this episode of Breaking Math, Autumn and Gabe explore the concept of nothingness and its significance in various fields. They discuss the philosophical, scientific, mathematical, and literary aspects of nothingness, highlighting its role in understanding reality and existence. They mention books like 'Incomplete Nature' by Terence Deacon and 'Zero: The Biography of a Dangerous Idea' by Charles Seife, which delve into the concept of absence and zero. The episode concludes by emphasizing the complexity and versatility of nothingness, inviting listeners to think deeper about its implications.Keywords: nothingness, philosophy, science, mathematics, literature, reality, existence, absence, zeroSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, WebsiteFollow Autumn on Twitter and InstagramFollow Gabe on Twitter.Have suggestions or want to come on the show? Fill out the form here.email: [email protected]

In this conversation, Autumn Phaneuf interviews Zach Weinersmith, a cartoonist and writer, about the feasibility and implications of space settlement. They discuss the challenges and misconceptions surrounding space colonization, including the idea that it will make us rich, mitigate war, and make us wiser. They explore the potential of the moon and Mars as settlement options, as well as the concept of rotating space stations. They also touch on the physiological effects of space travel and the need for further research in areas such as reproduction and ecosystem design. The conversation explores the challenges and implications of human settlement in space. It discusses the lack of data on the long-term effects of space travel on the human body, particularly for women. The conversation also delves into the need for a closed-loop ecosystem for sustainable space settlement and the legal framework surrounding space exploration and resource extraction. The main takeaways include the importance of addressing reproductive and medical challenges, the need for a better legal regime, and the debunking of misconceptions about space settlement.Follow Zach Weinersmith on his website and TwitterSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, WebsiteFollow Autumn on Twitter and InstagramFolllow Gabe on Twitter.Have suggestions or want to come on the show? Fill out the form here. email: [email protected] City on Mars, Keywords space settlement, feasibility, challenges, misconceptions, moon, Mars, rotating space stations, reproduction, ecosystem design, space settlement, human reproduction, closed-loop ecosystem, space law, resource extraction, logistics, math.

In this conversation, Autumn Phaneuf and Zach Weinersmith discusses his new book, A City on Mars, which takes a humorous look at the challenges of building a Martian society. He explores the misconceptions and myths surrounding space settlement and the feasibility of colonizing Mars. He argues that space is unlikely to make anyone rich and that the idea that space will mitigate war is unsupported. He also discusses the potential benefits and limitations of settling on the Moon and Mars, as well as the technical challenges involved.Follow Zach Weinersmith on his website and TwitterSubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, WebsiteFollow Autumn on Twitter and InstagramFolllow Gabe on Twitter.email: [email protected] City on Mars, space settlement, Mars colonization, misconceptions, myths, feasibility, space myths, space economics, war, Moon settlement, technical challenges, logistics, math.

Welcome to another engaging episode of the Breaking Math Podcast! Today's episode, titled "What is the Use?," features a fascinating conversation with the renowned mathematician and author, Professor Ian Stewart. As Professor Stewart discusses his latest book "What's the Use? How Mathematics Shapes Everyday Life," we dive deep into the real-world applications of mathematics that often go unnoticed in our daily technologies, like smartphones, and their unpredictable implications in various fields.We'll explore the history of quaternions, invented by William Rowan Hamilton, which now play a critical role in computer graphics, gaming, and particle physics. Professor Stewart will also shed light on the non-commutative nature of quaternions, mirroring the complexities of spatial rotations, and how these mathematical principles find their correspondence in the natural world.Furthermore, our discussion will encompass the interconnectivity within mathematics, touching upon how algebra, geometry, and trigonometry converge to paint a broader picture of this unified field. We also discuss the intriguing concept of "Fearful Symmetry" and how symmetrical and asymmetrical patterns govern everything from tiger stripes to sand dunes.With references to his other works, including "Professor Stewart's Cabinet of Mathematical Curiosities" and "The Science of Discworld," Professor Stewart brings an element of surprise and entertainment to the profound impact of mathematics on our understanding of the world.So stay tuned as we unlock the mysteries and the omnipresent nature of math in this thought-provoking episode with Professor Ian Stewart!

Tom Chivers 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 for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, WebsiteFollow Autumn on Twitter and InstagramFolllow Gabe on Twitter.email: [email protected]

Summary**Tensor Poster - If you are interested in the Breaking Math Tensor Poster on the mathematics of General Relativity, email us at [email protected] this episode, Gabriel Hesch and Autumn Phaneuf interview Steve Nadis, the author of the book 'The Gravity of Math.' 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.Chapters00:00 Introduction and Book Overview08:09 Collaboration and Writing Process25:48 Interest in Black Holes and Recent Developments35:30 The Mathematical Foundations of General Relativity44:55 The Curvature of Spacetime and the Equations of General Relativity56:06 Recent Discoveries in General Relativity01:06:46 Emmy Noether's Contributions to Conservation Laws01:13:48 Einstein's Cosmological Constant and Dark EnergySubscribe to Breaking Math wherever you get your podcasts.Become a patron of Breaking Math for as little as a buck a monthFollow Breaking Math on Twitter, Instagram, LinkedIn, WebsiteFollow Autumn on Twitter and InstagramFolllow Gabe on Twitter.email: [email protected]

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. (Find out more about the Ray Kitty Creation Workshop by clicking here). 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 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 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? by authors Dr. Kelly and Zach Weinersmith. Zach Weinersmith is the artist and creator of the famous cartoon strip Saturday Morning Breaking Cereal! We've got a lot of great episodes coming up! Stay tuned.

An interview with Prof. Marcus du Sautoy about his book Around the Wold in Eighty Games . . . .a Mathematician Unlocks the Secrets of the World's Greatest Games. Topics covered in Today's Episode: 1. Introduction to Professor Marcus du Sautoy and the Role of Games- Impact of games on culture, strategy, and learning- The educational importance of games throughout history2. Differences in gaming cultures across regions like India and China3. Creative Aspects of Mathematics4. The surprising historical elements and banned games by Buddha5. Historical and geographical narratives of games rather than rules6. Game Theory and Education7. Unknowable questions like thermodynamics and universe's infinity8. Professor du Sautoy's Former Books and Collections9. A preview of his previous books and their themes10. Gaming Cultures and NFTs in Blockchain11. Gamification in Education12. The Role of AI in Gaming13. Testing machine learning in mastering games like Go14. Alphago's surprising move and its impact on Go strategies15 . The future of AI in developing video game characters, plots, and environments16. Conclusion and Giveaway Announcement*Free Book Giveaway of Around The World in 88 Games . . . by Professor Marcus Du Sautory! Follow us on our socials for details: Follow us on X: @BreakingMathPodFollow us on Instagram: @Breaking Math MediaEmail us: [email protected]

SummaryBrain Organelles, A.I. and Defining Intelligence in  Nature- In this episode, we continue our fascinating interview with GT, a science content creator on TikTok and YouTube 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 DiscountUse My Special Link to save e 30%  Off Your First Month of Any ZenCastr Paid Plan

This episode is inspired by a correspondence the Breaking Math Podcast had with the editors of Digital Discovery, a journal by the Royal Society of Chemistry.  In this episode the hosts review a paper about how the Lean Interactive Theorem Prover, which is usually used as a tool in creating mathemtics proofs, can be used to create rigorous and robust models in physics and chemistry.  Also -  we have a brand new member of the Breaking Math Team!  This episode is the debut episode for Autumn, CEO of Cosmo Labs, occasional co-host / host of the Breaking Math Podcast, and overall contributor who has been working behind the scenes on the podcast on branding and content for the last several months. Welcome Autumn!  Autumn and Gabe discuss how the paper explores the use of interactive theorem provers to ensure the accuracy of scientific theories and make them machine-readable. The episode discusses the limitations and potential of interactive theorem provers and highlights the themes of precision and formal verification in scientific knowledge.  This episode also provide resources (listed below) for listeners interested in learning more about working with the LEAN interactive theorem prover.  Takeaways Interactive theorem provers can revolutionize the way scientific theories are formulated and verified, ensuring mathematical certainty and minimizing errors. Interactive theorem provers require a high level of mathematical knowledge and may not be accessible to all scientists and engineers. Formal verification using interactive theorem provers can eliminate human error and hidden assumptions, leading to more confident and reliable scientific findings. Interactive theorem provers promote clear communication and collaboration across disciplines by forcing explicit definitions and minimizing ambiguities in scientific language. Lean Theorem Provers enable scientists to construct modular and reusable proofs, accelerating the pace of knowledge acquisition. Formal verification presents challenges in terms of transforming informal proofs into a formal language and bridging the reality gap. Integration of theorem provers and machine learning has the potential to enhance creativity, verification, and usefulness of machine learning models. The limitations and variables in formal verification require rigorous validation against experimental data to ensure real-world accuracy. Lean Theorem Provers have the potential to provide unwavering trust, accelerate innovation, and increase accessibility in scientific research. AI as a scientific partner can automate the formalization of informal theories and suggest new conjectures, revolutionizing scientific exploration. The impact of Lean Theorem Provers on humanity includes a shift in scientific validity, rapid scientific breakthroughs, and democratization of science. Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript! 

This conversation explores the topic of brain organoids and their integration with robots. The discussion covers the development and capabilities of brain organoids, the ethical implications of their use, and the differences between sentience and consciousness. The conversation also delves into the efficiency of human neural networks compared to artificial neural networks, the presence of sleep in brain organoids, and the potential for genetic memories in these structures. The episode concludes with an invitation to part two of the interview and a mention of the podcast's Patreon offering a commercial-free version of the episode.Takeaways Brain organoids are capable of firing neural signals and forming structures similar to those in the human brain during development. The ethical implications of using brain organoids in research and integrating them with robots raise important questions about sentience and consciousness. Human neural networks are more efficient than artificial neural networks, but the reasons for this efficiency are still unknown. Brain organoids exhibit sleep-like patterns and can undergo dendrite growth, potentially indicating learning capabilities. Collaboration between scientists with different thinking skill sets is crucial for advancing research in brain organoids and related fields.Chapters 00:00 Introduction: Brain Organoids and Robots 00:39 Brain Organoids and Development 01:21 Ethical Implications of Brain Organoids 03:14 Summary and Introduction to Guest 03:41 Sentience and Consciousness in Brain Organoids 04:10 Neuron Count and Pain Receptors in Brain Organoids 05:00 Unanswered Questions and Discomfort 05:25 Psychological Discomfort in Brain Organoids 06:21 Early Videos and Brain Organoid Learning 07:20 Efficiency of Human Neural Networks 08:12 Sleep in Brain Organoids 09:13 Delta Brainwaves and Brain Organoids 10:11 Creating Brain Organoids with Specific Components 11:10 Genetic Memories in Brain Organoids 12:07 Efficiency and Learning in Human Brains 13:00 Sequential Memory and Chimpanzees 14:18 Different Thinking Skill Sets and Collaboration 16:13 ADHD and Hyperfocusing 18:01 Ethical Considerations in Brain Research 19:23 Understanding Genetic Mutations 20:51 Brain Organoids in Rat Bodies 22:14 Dendrite Growth in Brain Organoids 23:11 Duration of Dendrite Growth 24:26 Genetic Memory Transfer in Brain Organoids 25:19 Social Media Presence of Brain Organoid Companies 26:15 Brain Organoids Controlling Robot Spiders 27:14 Conclusion and Invitation to Part 2References:Muotri Labs (Brain Organelle piloting Spider Robot)Cortical Labs (Brain Organelle's trained to play Pong)*For a copy of the episode transcript, email us at [email protected] Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!  Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonSummary:

This is a follow up on our previous episode on OpenAi's SORA. We attempt to answer the question, "Can OpenAi's SORA model real-world physics?" We go over the details of the technical report, we discuss some controversial opinoins by experts in the field at Nvdia and Google's Deep Mind. The transcript for episode is avialable below upon request.Help Support The Podcast by clicking on the links below: Try out ZenCastr:   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Patreon Link:  All content is available commercial free on patreon YouTube Channel:  Enjoy this content? subscribe to our YouTube Channel

OpenAI's Sora, a text-to-video model, has the ability to generate realistic and imaginative scenes based on text prompts. This conversation explores the capabilities, limitations, and safety concerns of Sora. It showcases various examples of videos generated by Sora, including pirate ships battling in a cup of coffee, woolly mammoths in a snowy meadow, and golden retriever puppies playing in the snow. The conversation also discusses the technical details of Sora, such as its use of diffusion and transformer models. Additionally, it highlights the potential risks of AI fraud and impersonation. The episode concludes with a look at the future of physics-informed modeling and a call to action for listeners to engage with Breaking Math content.Takeaways OpenAI's Sora is a groundbreaking text-to-video model that can generate realistic and imaginative scenes based on text prompts. Sora has the potential to revolutionize various industries, including entertainment, advertising, and education. While Sora's capabilities are impressive, there are limitations and safety concerns, such as the potential for misuse and the need for robust verification methods. The conversation highlights the importance of understanding the ethical implications of AI and the need for ongoing research and development in the field.Chapters00:00 Introduction to OpenAI's Sora04:22 Overview of Sora's Capabilities07:08 Exploring Prompts and Generated Videos12:20 Technical Details of Sora16:33 Limitations and Safety Concerns23:10 Examples of Glitches in Generated Videos26:04 Impressive Videos Generated by Sora29:09 AI Fraud and Impersonation35:41 Future of Physics-Informed Modeling36:25 Conclusion and Call to ActionHelp Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!    Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonContact us at [email protected]#OpenAiSora #

Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% Discount   Use my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTubeTranscripts are available upon request. Email us at [email protected] us on X (Twitter)Follow us on Social Media Pages (Linktree)Visit our guest Levi McClain's Pages: youtube.com/@LeviMcClainlevimcclain.com/SummaryLevi McClean discusses various topics related to music, sound, and artificial intelligence. He explores what makes a sound scary, the intersection of art and technology, sonifying data, microtonal tuning, and the impact of using 31 notes per octave. Levi also talks about creating instruments for microtonal music and using unconventional techniques to make music. The conversation concludes with a discussion on understanding consonance and dissonance and the challenges of programming artificial intelligence to perceive sound like humans do.Takeaways: The perception of scary sounds can be analyzed from different perspectives, including composition techniques, acoustic properties, neuroscience, and psychology. Approaching art and music with a technical mind can lead to unique and innovative creations. Sonifying data allows for the exploration of different ways to express information through sound. Microtonal tuning expands the possibilities of harmony and offers new avenues for musical expression. Creating instruments and using unconventional techniques can push the boundaries of traditional music-making. Understanding consonance and dissonance is a complex topic that varies across cultures and musical traditions. Programming artificial intelligence to understand consonance and dissonance requires a deeper understanding of human perception and cultural context.Chapters00:00 What Makes a Sound Scary03:00 Approaching Art and Music with a Technical Mind05:19 Sonifying Data and Turning it into Sound08:39 Exploring Music with Microtonal Tuning15:44 The Impact of Using 31 Notes per Octave17:37 Why 31 Notes Instead of Any Other Arbitrary Number19:53 Creating Instruments for Microtonal Music21:25 Using Unconventional Techniques to Make Music23:06 Closing Remarks and Questions24:03 Understanding Consonance and Dissonance25:25 Programming Artificial Intelligence to Understand Consonance and Dissonance

We are joined today by content creator Levi McClain to discuss the mathematics behind music theory, neuroscience, and human experiences such as fear as they relate to audio processing. For a copy of the episode transcript, email us at [email protected].  For more in depth discussions on these topics and more, check out Levi's channels at: Patreon.com/LeviMcClainyoutube.com/@LeviMcClainTiktok.com/@levimcclainInstagram.com/levimcclainmusicHelp Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our Patreon

Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonPart 2/2 of the interview with Brit Cruise, creator of the YouTube channel "Art of the Problem," about interesting mathematics,, electrical and computer engineering problems. In Part 1, we explored what 'intelligence' may be defined as by looking for examples of brains and proto-brains found in nature (including mold, bacteria, fungus, insects, fish, reptiles, and mammals). In Part 2, we discuss aritifical neural nets and how they are both similar different from human brains, as well as the ever decreasing gap between the two. Brit's YoutTube Channel can be found here: Art of the Problem - Brit CruiseTranscript will be made available soon! Stay tuned. You may receive a transcript by emailing us at [email protected] a supporter of this podcast: https://www.spreaker.com/podcast/breaking-math-podcast--5545277/support.

In this episode (part 1 of 2), I interview Brit Cruise, creator of the YouTube channel 'Art of the Problem.' On his channel, he recently released the video "ChatGPT: 30 Year History | How AI learned to talk." We discuss examples of intelligence in nature and what is required in order for a brain to evolve at the most basic level. We use these concepts to discuss what artificial intelligence - such as Chat GPT - both is and is not.Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our Patreon

Transcripts of this episode are avialable upon request.  Email us at [email protected]. In this episode Gabriel Hesch interviews Taylor Sparks, a professor of material science and engineering, about his recent paper on the use of generative modeling a.i. for material disovery.  The paper is published in the journal Digital Discovery and is titled 'Generative Adversarial Networks and Diffusion MOdels in Material Discovery. They discuss the purpose of the call, the process of generative modeling, creating a representation for materials, using image-based generative models, and a comparison with Google's approach. They also touch on the concept of conditional generation of materials, the importance of open-source resources and collaboration, and the exciting developments in materials and AI. The conversation concludes with a discussion on future collaboration opportunities.Takeaways Generative modeling is an exciting approach in materials science that allows for the prediction and creation of new materials. Creating a representation for materials, such as using the crystallographic information file, enables the application of image-based generative models. Google's approach to generative modeling received attention but also criticism for its lack of novelty and unconditioned generation of materials. Open-source resources and collaboration are crucial in advancing materials informatics and machine learning in the field of materials science.Help Support The Podcast by clicking on the links below: Start YOUR podcast on ZenCastr!   Use my special link  ZenCastr Discount to save 30% off your first month of any Zencastr paid plan Visit our PatreonHow is Machine Learning being used to further original scientific discoveries?  

In October of 2023, Sofia Baca passed away unexpectedly from natural causes. Sofia was one of the founders and cohosts of the Breaking Math Podcast. In this episode, host Gabriel Hesch interviews Diane Baca, mother of Sofia Baca as we talk about her passions for creativity, mathematics, science, and discovering what it means to be human. Sofia lived an exceptional life with explosive creativity, a voracious passion for mathematics, physics, computer science, and creativity. Sofia also struggled immensely with mental health issues which included substance abuse as well as struggling for a very long time understand the source of their discontent. Sofia found great happiness in connecting with other people through teaching, tutoring, and creative expression. The podcast will continue in honor of Sofia. There are many folders of ideas that Sofia left with ideas for the show or for other projects. We will continue this show with sharing some of these ideas, but also with sharing stories of Sofia - including her ideas and her struggles in hopes that others may find solace in that they are not alone in their struggles. But also in hopes that others may find inspiration in what Sofia had to offer. We miss you dearly, Sofia.

Join Sofía Baca and her guests, the host and co-host of the Nerd Forensics podcast, Millicent Oriana and Jacob Urban, as they explore what it means to be able to solve one problem in multiple ways.This episode is distributed under a Creative Commons Attribution-ShareAlike 4.0 International License. For full text, visit: https://creativecommons.org/licenses/by-sa/4.0/[Featuring: Sofía Baca; Millicent Oriana, Jacob Urban[Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript!

The history of mathematics, in many ways, begins with counting. Things that needed, initially, to be counted were, and often still are, just that; things. We can say we have twelve tomatoes, or five friends, or that eleven days have passed. As society got more complex, tools that had been used since time immemorial, such as string and scales, became essential tools for counting not only concrete things, like sheep and bison, but more abstract things, such as distance and weight based on agreed-upon multiples of physical artifacts that were copied. This development could not have taken place without the idea of a unit: a standard of measuring something that defines what it means to have one of something. These units can be treated not only as counting numbers, but can be manipulated using fractions, and divided into arbitrarily small divisions. They can even be multiplied and divided together to form new units. So where does the idea of a unit come from? What's the difference between a unit, a dimension, and a physical variable? And how does the idea of physical dimension allow us to simplify complex problems? All of this and more on this episode of Breaking Math.Distributed under a CC BY-SA 4.0 International License. For full text, visit: https://creativecommons.org/licenses/by-sa/4.0/[Featuring: Sofía Baca; Millicent Oriana, Jacob Urban]Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript!

Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript!Join Sofia Baca and Nerd Forensics co-host Jacob Urban as they discuss all things counting!Counting is the first arithmetic concept we learn, and we typically learn to do so during early childhood. Counting is the basis of arithmetic. Before people could manipulate numbers, numbers had to exist. Counting was first done on the body, before it was done on apparatuses outside the body such as clay tablets and hard drives. However, counting has become an invaluable tool in mathematics itself, as became apparent when counting started to be examined analytically. How did counting begin? What is the study of combinatorics? And what can be counted? All of this and more, on this episode of Breaking Math.This episode is distributed under a Creative Commons Attribution-ShareAlike 4.0 International License (full text: https://creativecommons.org/licenses/by-sa/4.0/)[Featuring: Sofia Baca; Jacob Urban]

As you listen to this episode, you'll be exerting mental effort, as well as maybe exerting effort doing other things. The energy allowing your neurons to continually charge and discharge, as well as exert mechanical energy in your muscles and chemical energy in places like your liver and kidneys, came from the food you ate. Specifically, it came from food you chewed, and then digested with acid and with the help of symbiotic bacteria. And even if that food you're eating is meat, you can trace its energy back to the sun and the formation of the earth. Much of this was established in the previous episode, but this time we're going to explore a fundamental property of all systems in which heat can be defined. All of these structures had a certain order to them; the cow that might have made your hamburger had all the same parts that you do: stomach, lips, teeth, and brain. The plants, such as the tomatoes and wheat, were also complex structures, complete with signaling mechanisms. As you chewed that food, you mixed it, and later, as the food digested, it became more and more disordered; that is to say, it became more and more "shuffled", so to speak, and at a certain point, it became so shuffled that you'd need all the original information to reconstruct it: reversing the flow of entropy would mean converting vomit back into the original food; you'd need all the pieces. The electrical energy bonding molecules were thus broken apart and made available to you. And, if you're cleaning your room while listening to this, you are creating order only at the cost of destroying order elsewhere, since you are using energy from the food you ate. Even in industrial agriculture where from 350 megajoules of human and machine energy, often 140 gigajoules of corn can be derived per acre, a ratio of more than 400:1, the order that the seeds seem to produce from nowhere is constructed from the energy of the chaotic explosion from a nearby star. So why are the concepts of heat, energy, and disorder so closely linked? Is there a general law of disorder? And why does the second law mean you can't freeze eggs in a hot pan? All of this and more on this episode of Breaking Math.Distributed under a CC BY-SA 4.0 License (https://creativecommons.org/licenses/by-sa/4.0/)[Featuring: Sofia Baca; Millicent Oriana, Jacob Urban]Help Support The Podcast by clicking on the links below: Try out ZenCastr w/ 30% DiscountUse my special link to save 30% off your first month of any Zencastr paid plan Patreon YouTube Breaking Math WebsiteEmail us for copies of the transcript!

Christopher Roblesz is a math educator who, until the pandemic, worked as a teacher. It was his experiences during the pandemic, and his unwavering passion for preparing disadvantaged youth for STEM careers, that eventually led him to developing mathnmore, a company focused on providing an enriched educational experience for sstudents who are preparing for these careers.More on energy and entropy next time!All of this and more on this interview episode of Breaking Math![Featuring: Sofia Baca; Christopher Roblesz]

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. Sabine is host of the famous youtube show Science with Sabine. 

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]

Robert Black is an author who has written a six-book series about seven influential mathematicians, their lives, and their work. We interview him and his books, and take a peek into the lives of these influential mathematicians.Addendum: Hey Breaking Math fans, I just wanted to let y'all know that the second material science podcast is delayed.[Featuring: Sofía Baca; Robert Black]

Matter is that which takes up space, and has mass. It is what we interact with, and what we are. Imagining a world without matter is to imagine light particles drifting aimlessly in space. Gasses, liquids, solids, and plasmas are all states of matter. Material science studies all of these, and their combinations and intricacies, found in examining foams, gels, meshes, and other materials and metamaterials. Chris Cogswell is a material scientist, and host of The Mad Scientist Podcast, a podcast that takes a critical look at things ranging from technological fads, to pseudoscience, and topics that deserve a critical eye. On the first of a pair of two episodes about material science, we interview Chris about his experience with studying material science, and ask questions about the subject in general.Links referenced by Chris Cogswell:- https://www.youtube.com/watch?v=bUvi5eQhPTc is about nanomagnetism and cool demonstration of ferrofluid- https://www.youtube.com/watch?v=4Dlt63N-Uuk goes over nanomagnetic applications in medicine- http://yaghi.berkeley.edu/pdfPublications/04MOFs.pdf Great review paper on new class of materials known as MOFs which are going to be very important in coming years- https://www.youtube.com/watch?v=IkYimZBzguw Crash course engineering on nanomaterials, really good introduction to the field- https://www.youtube.com/watch?v=t7EYQLOlwDM Oak Ridge national lab paper on using nano materials for carbon dioxide conversion to other carbon molecules- https://www.youtube.com/watch?v=cxVFopLpIQY Really good paper on carbon capture technology challenges and economics[Featuring: Sofía Baca, Gabriel Hesch, Meryl Flaherty; Chris Cogswell]--- This episode is sponsored by · Anchor: The easiest way to make a podcast. https://anchor.fm/appSupport this podcast: https://anchor.fm/breakingmathpodcast/support

Seldom do we think about self-reference, but it is a huge part of the world we live in. Every time that we say 'myself', for instance, we are engaging in self-reference. Long ago, the Liar Paradox and the Golden Ratio were among the first formal examples of self-reference. Freedom to refer to the self has given us fruitful results in mathematics and technology. Recursion, for example, is used in algorithms such as PageRank, which is one of the primary algorithms in Google's search engine. Elements of self-reference can also be found in foundational shifts in the way we understand mathematics, and has propelled our understanding of mathematics forward. Forming modern set theory was only possible due to a paradox called Russel's paradox, for example. Even humor uses self-reference. Realizing this, can we find harmony in self-reference? Even in a podcast intro, are there elements of self-reference? Nobody knows, but I'd check if I were you. Catch all of this, and more, on this episode of Breaking Math. Episode 70.1: Episode Seventy Point One of Breaking Math Podcast[Featuring: Sofía Baca, Gabriel Hesch; Millicent Oriana]

This episode description intentionally left blank!   As in completely on purpose.   Fun Fact!  The creators of the Breaking Math Podcast, Sofia and Gabriel always thought it was funny that many books that we've read - even going back to our childhood - had a page in it with the sentence printed, "This Page Intentionally Left Blank."   Like-  okay; what does this 'intentionally left blank page' add to the reading experience?  Does anyone know?  Oh look here!  There is a wikipedia page on it. Huh.  Now I know.  Now we know.   And knowing is half the battle!    Sofia would frequently leave post-it notes on Gabe's laptop saying, "This Post-it note intentionally left blank."  Because . . . . why?   Sofia would often leave a twitter or facebook post that declared "This post intentionally left blank."   And now - we release an entire podcast episode that is intentionally left blank.  Are we trolls?  NO!  We prefer to think of ourselves as artists in the style of Banksy making a statement! 

Michael Brooks is a science writer who specializes in making difficult concepts easier to grasp. In his latest book, Brooks goes through several mathematical concepts and discusses their motivation, history, and discovery. So how do stories make it easier to learn? What are some of the challenges associated with conveying difficult concepts to the general public? And who, historically, has been a mathematician? All of this and more on this episode of Breaking Math.  Songs were Breaking Math Intro and Outro by Elliot Smith of Albuquerque.  This episode is published under a Creative Commons 4.0 Attribute-ShareAlike-NonCommercial license. For more information, visit CreativeCommons.org  [Featuring: Sofía Baca, Gabriel Hesch, Meryl Flaherty; Michael Brooks]t

There are times in mathematics when we are generalizing the behavior of many different, but similar, entities. One such time that this happens is the use cases of Big O notation, which include describing the long-term behavior of functions, and talking about how accurate numerical calculations are. On this problem episode, we are going to discuss Big O notation and how to use it.This episode is licensed by Sofia Baca under a Creative Commons Attribution-ShareAlike-NonCommercial 4.0 International License. For more information, visit CreativeCommons.org.[Featuring: Sofía Baca]

The world is often uncertain, but it has only been in the last half millennium that we've found ways to interact mathematically with that concept. From its roots in death statistics, insurance, and gambling to modern Bayesian networks and machine learning, we've seen immense productivity in this field. Every way of looking at probability has something in common: the use of random variables. Random variables let us talk about events with uncertain outcomes in a concrete way. So what are random variables? How are they defined? And how do they interact? All of this, and more, on this episode of Breaking Math.Interact with the hosts:@SciPodSofia@TechPodGabeOr the guest:@KampPodMilliePatreon here: patreon.com/breakingmathpodcastFeaturing music by Elliot Smith. For info about music used in ads, which are inserted dynamically, contact us at [email protected][Featuring: Sofía Baca, Gabriel Hesch; Millicent Oriana]