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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.
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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
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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 TakeawaysTags: #BreakingMath #FluidDynamics #AnimalBehavior #MathInNature #SheepHerding #Robotics #ScienceExplained #EmergentBehavior
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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 Learn more about Mersenne primes: Mersenne Prime HistoryBecome a patron of Breaking Math for as little as a buck a month
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In this episode of Breaking Math, hosts Gabriel Hesch and Autumn Phaneuf dive into the cutting-edge world of Generative Flow Networks (GFlowNets) and their role in artificial intelligence and material science. The discussion centers on how GFlowNets are revolutionizing the discovery of new materials for carbon capture, offering a powerful alternative to traditional AI models. Learn about the mechanics of GFlowNets, their advantages, and the groundbreaking results in developing materials with enhanced CO2 absorption capabilities. The episode also explores the future potential of GFlowNets in AI-driven material discovery and beyond, emphasizing their transformative impact on carbon capture technology and sustainable innovation.
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You can find the paper “Discovery of novel reticular materials for carbon dioxide capture using GFlowNets” by Cipcigan et al in Digital Discovery Journal by the Royal Society of Chemistry.Follow Breaking Math on Twitter, Instagram, LinkedIn, Website, YouTube, TikTok
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Explore the intriguing intersection of science and spiritualism in the Victorian era. This episode uncovers how prominent scientists like Michael Faraday, William James, and Marie & Pierre Curie engaged with supernatural phenomena and the rise of spiritualism. Discover the scientific efforts to debunk or understand paranormal activities, and how these investigations shaped modern science. Dive into the fascinating legacy of this 19th-century movement and its lasting impact on today's scientific inquiries into the unknown. Perfect for fans of history, science, and the supernatural.
Keywords: Victorian era, spiritualism, science, supernatural, Michael Faraday, William James, Alfred Russell Wallace, Curies, Eleanor Sidgwick, idiomotor effect
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AI & Consciousness: Philosophical Debates, Ethical Implications & the Future of Conscious Machines
In this episode of Breaking Math, hosts Autumn and Gabriel explore the intricate relationship between artificial intelligence (AI) and consciousness. Delve into historical perspectives, philosophical debates, and the ethical questions surrounding the creation of conscious machines. Key topics include the evolution of AI, challenges in defining and testing consciousness, and the potential rights of AI beings. We also examine the Turing Test, the debate between strong AI vs. weak AI, and concepts like personhood and integrated information theory. Perfect for anyone interested in AI ethics, the nature of consciousness, and the responsibilities of advanced AI technology.
Keywords: AI, consciousness, Turing test, strong AI, weak AI, ethics, philosophy, personhood, integrated information theory, neural networks
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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, AI
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You 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, TikTok
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Mathematical Patterns in Plants: Fibonacci, Golden Ratio & Nature's Hidden Math with Christophe Gole & Nancy Pick
In 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
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You 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, TikTok
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Math & Cartography: Dr. Paula Rowinska on Map Projections, Gerrymandering & Real-World Math
In 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, math
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Follow 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, TikTok
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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 shifts
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Math & Language: Creativity, Quantification, and Making Math Accessible with Ben Orlin
In 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, relationships
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Follow 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, TikTok
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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, accessibility
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Follow Jon Schwabish on Twitter and on YouTube. Also go give PolicyViz Podcast a follow
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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 learning
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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, humanity
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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, humanity
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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.
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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.
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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 journals
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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, science
You can find Anil Ananthaswamy on Twitter @anilananth and his new book “Why Machines Learn”
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- Visa fler
