Podcasts about Wolfram Research

Stephen Wolfram is a British-American computer scientist, physicist, and entrepreneur best known for founding Wolfram Research and creating Mathematica and the computational knowledge engine Wolfram|Alpha. A child prodigy, he published scientific papers in physics by the age of 15 and earned his Ph.D. from Caltech at 20. He later developed A New Kind of Science, proposing that simple computational rules can explain complex phenomena in nature. Wolfram has been a pioneer in symbolic computation, computational thinking, and AI. His work continues to influence science, education, and technology.In our conversation we discuss:(00:00) What was the first version of AI?(23:38) What triggered the current AI revolution?(34:19) Did OpenAI base its initial algorithm on Google's work?(46:47) What is the technological gap between now and achieving AGI?(1:15:59) Do you fear an AI-driven world you can't fully understand?(1:35:15) What do we need to unlearn if AI can replicate human abilities?(1:47:39) What happens when there aren't enough jobs due to automation?(1:54:01) How is AI reshaping people's views on wealth?(2:25:48) The future of automating software developmentLearn more about Stephen WolframWebsite: https://www.stephenwolfram.com/index.php.enWikipedia: https://en.wikipedia.org/wiki/Stephen_WolframWatch full episodes on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.youtube.com/@seankim⁠⁠⁠⁠⁠⁠⁠⁠Connect on IG: ⁠⁠⁠⁠⁠⁠⁠https://instagram.com/heyseankim⁠

Stephen Wolfram answers questions from his viewers about the history of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qaQuestions include: When was complexity science invented? Was there a further back history than digital? - They always forget Aristarchus. - What role did category and type theory play for mathematics? - How would you think about approaching alchemical literature, knowing that it mostly employed coded language rather than being about literal transmutation into gold? - Was Newton not an alchemist? - The real secret is it's tungsten that can be turned into gold, hence the name "Wolfram Research." - Dirac, Einstein, Turing and Feynman are sitting in a room. What is the single word they all immediately agree on? - So... Dirac answered in Dirac delta function style?

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Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: Can you tell us more about your book collection (or your artifact or art collection)? - How does a "dashboard/portal" webpage as you show sometimes, with lists and links to your projects, and such tools, fit in your workflow and daily routines? - ​​​​Stephen, are you also the CTO of Wolfram Research? What are the characteristics of a good CTO? - Do you find video calls draining? - What is the Wolfram software continuity plan in the event something happens to you? You are so instrumental in the development of this software, so your absence would be a hard gap to fill. - Did you have a mentor while creating your business? Do you find mentors useful? - Faces distract from logic because we spend too long assessing people's emotions. - Just wanted to share my personal Mathematica "story." I learned to know Mathematica way back when it was running on DOS in text mode and switched into graphics mode when I wanted to plot something. Later I switched to an early Windows version. Back then Macs were too expensive for me, but I loved that Mathematica was a free integral part of Macs! - Could you share your methods for generating and keeping track of ideas? Do you have favorite techniques for being productive?

Stephen Wolfram answers questions from his viewers about the future of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: ​​How do you see electricity being transmitted or provided to households in the future? These power poles and lines are over-100-year-old technology. - How often will AI be revisited in future science and technology? Or do you think AI has firmly cemented its place? - Do you think LLMs have already passed the Turing test (which is currently being asserted by many "experts")? If yes, what does that mean for the future direction of AI research? If no, what's missing? - Over time, AI training data will increasingly be AI generated. Will this feedback loop amplify errors and cause AI to self-destruct? - If we can sustain mini-brains or large clusters of human neurons for years, this approach might achieve artificial general intelligence before synthetic methods do. What do you think? - Are those neural cats behind you? - Is it possible that human-machine integration or radical genetic modification can allow humans to make significant leaps in rulial space? - What role do emotions play in language and information processing? Do emotions speed up communication? What other elements are important for AI development in communication beyond language? - ​​Will AI make interdisciplinary learning and collaboration easier by facilitating that process, or will it create more misunderstanding between fields? - When people discuss whether an LLM is sentient or not, a question that always comes up is whether it "understands" the prompts and its replies, with the Chinese room thought experiment something typically brought up in such a discussion. I see two ways to look at this. One is that an LLM is just an advanced predictive text generator and that sentience is something more than that. Another is that we sentient beings are actually just advanced predictive text/action generators. What do you feel sentience really is? - Is it possible for AI to achieve true randomness? - Why is there no latency when we are looking around and constructing a scene on the fly? Or is it our perception that makes it seem like there is no latency? - What new types of auxiliary jobs do you think will be necessary for the ubiquitous integration of AI into society to properly balance AI with human interests, such as the alignment problem? And what role, if any, do you see Wolfram Research playing in that "AI economy"? - Do you see there being more specialized computing hardware in the future, where the computations are more directly embedded in physical processes rather than needing to construct a given computation within a universal computer? - How do you envision hypergraph-based models advancing our understanding of quantum mechanics, general relativity and their potential unification? Specifically, how might these models address challenges like quantum gravity, the nature of spacetime and the emergence of fundamental particles? - Are we programmed by evolution to be sentient? If so, can't we program a machine to be sentient? - Do you think hydrogen has a future in computing, and will it play a major role in energy and possible propulsion to get us to Mars? - Is the ruliad a meta-theory, or does it actually exist? - ​​If the ruliad is correct, what kind of technology do you think that can bring us?

This is a conversation with Stephen Wolfram about his proposed theory of everything. Stephen is a British-American computer scientist, mathematician, physicist, and CEO of Wolfram Research. He also created Mathematica, and Wolfram|Alpha & Wolfram Language, and is the Author of 'A New Kind of Science' as well as a number of other books. Stephen's attempt to derive all of the laws of nature (including gravitation, statistical mechanics, and general relativity) rests on two key ideas:  1. The idea of computational irreducibility. In physics we usually deal with systems for which we are able to predict the state of the system at a later time as long as the initial conditions are known. For example, the trajectory of a bullet can be calculated at any point along its path. There are, however, complicated systems like cellular automata where there isn't a closed formula that lets you calculate the state of the system at some arbitrary later point. Instead you are forced to compute the development of the system one step at a time if you want to know how it evolves. Such systems are 'computationally irreducible'. 2. The idea of computational boundedness. This is the idea that we have finite computing power in our brains. There are many complex systems that scale so fast that our bounded computing power isn't enough follow every element of the system (e.g. we can't visualize the motion of the billions of cells in our own bodies, and so instead we develop an aggregated model of ourselves). Starting with these two ideas, Stephen asks what a world with computational irreducibility would look like to a computationally bounded creature living in that world. He then builds a computational model based on hypergraphs (which you can think of as a kind of cellular automata), and from there attempts to re-derive all the laws of nature. This is an extraordinarily ambitious project, that lies somewhat outside of mainstream approaches to physics. The claim is, however, that significant progress has been made, and that this approach really is able to derive interesting aspects of the physical world. This conversation explores the key ideas behind the program. ►Watch on YouTube: https://youtu.be/T0s_H9c2O28 ► For more information about Stephen's work see: www.stephenwolfram.com www.wolframphysics.org ►Thumbnail source images can be found here: https://company.wolfram.com/press-center/stephen-wolfram/ https://www.wolframphysics.org/visual-gallery/  ►Follow Stephen on X: @stephen_wolfram These conversations are supported by the Andrea von Braun foundation (http://www.avbstiftung.de/), as an exploration of the rich, exciting, connected, scientifically literate, and (most importantly) sustainable future of humanity. This interview is one of a series of interviews that explores the impact of economics on sustainability and the environment. The Andrea von Braun Foundation has provided me with full creative freedom with their support. As such, the views expressed in these episodes are my own and those of my guests.   A big thank you to anonymous for letting me use their space as a temporary studio.

On this episode of the Getting Smart Podcast, Tom Vander Ark talks to Conrad Wolfram, CEO of Wolfram Research and author of The Math Fix, to discuss the evolving role of computational thinking in education. They explore how the surge in computational power and AI can transform math education by moving away from manual calculations and focusing on real-world problem-solving. Conrad Wolfram shares insights on the necessity of integrating computational tools into the curriculum, emphasizing that modern education should prepare students for complex problem-solving using AI and natural language interfaces. They also discuss the challenges and opportunities in updating math education to reflect these advancements, aiming to equip students with skills relevant to today's tech-driven world. Outline The Evolution of Human-Computer Interaction The Role of Natural Language in AI Revolutionizing Math Education Future of Computational Thinking in Education Links Watch the Full Conversation Conrad Wolfram Website Conrad Wolfram Bio Language Matters, and What Matters Has Changed by Conrad Wolfram Conrad Wolfram on Computational Thinking The Math(s) Fix Review by Rachelle Dene Poth South Fayette Computational Thinking Digital Promise - Computational Thinking US Math Wars by Conrad Wolfram Subscribe to Our Newsletter!

Ralston College Humanities MA   Dr. Stephen Wolfram is a renowned computer scientist, physicist, and entrepreneur who earned his PhD in particle physics at 20 and became the youngest MacArthur Fellow at 21. As the founder of Wolfram Research, he has developed groundbreaking technologies widely used by university researchers in engineering, physics, mathematics, and computing. How can computational thinking and philosophy together unlock the mysteries of human consciousness and the universe?   In this Q&A session, conducted in February 2024 with students enrolled in Ralston College's MA in the Humanities program, the renowned physicist and computer scientist, Dr Stephen Wolfram, explains his own intellectual trajectory and explores the intersection of computational and philosophical inquiry, particularly in the age of AI. In the course of this wide-ranging conversation, Dr Wolfram discusses computational irreducibility, the nature of mind, the ethics of AI governance, and the growing value of a liberal arts education.    —   00:00 Introduction: Dr. Stephen Wolfram's Genius and AI's Impact on Humanities 01:30 Welcoming Dr. Steven Wolfram 02:15 Steven Wolfram's Early Life and Achievements 05:10 The Power of Computational Thinking 07:20 The Ruliad, Philosophy, and Computational Language 15:15 Q: Exploring Computational Irreducibility and Emergence 21:25 The Ruliad and the Nature of Reality 32:30 Q: The Role of Computational Thinking in Education 41:05 AI Governance and Ethics 46:35 Q: Bridging STEM and Humanities for Better AI Ethics 48:40 Building Wolfram Alpha 50:35 Q: Plato and Balancing Innovation in AI 01:05:25 Q: Probability and Unpredictability: Insights from Nassim Taleb 01:09:35 Q: Human Consciousness and the Computational Soul 01:22:35 Conclusion: Reflections on Learning, Philosophy, and the Future of Education —   Authors, Ideas, and Works Mentioned in this Episode:    The ruliad  Gestalt entities  Computational irreducibility  Computational equivalence  The second law of thermodynamics Plato, Republic  AI Governance  Utilitarianism Arrival (film) ChatGPT Nassem Talib, The Black Swan Colin Maclaurin   —   Additional Resources  Dr Stephen Blackwood    Ralston College (including newsletter)   Support a New Beginning    Ralston College Humanities MA   Join the conversation and stay updated on our latest content by subscribing to the Ralston College YouTube channel.   —   Thank you for listening!  

Conrad Wolfram wants to transform the way we teach math — by taking advantage of computers. The Mathematica creator convinced the Estonian government to give his radical curriculum a try — so why is the rest of the world so resistant? SOURCE:Conrad Wolfram, strategic director and European cofounder/C.E.O. of Wolfram Research, and founder of computerbasedmath.org. RESOURCES:"In California, a Math Problem: Does Data Science = Algebra II?" by Amy Harmon (The New York Times, 2023).The Math(s) Fix: An Education Blueprint for the AI Age, by Conrad Wolfram (2020)."The Movement to Modernize Math Class," by Yoree Koh (The Wall Street Journal, 2020)."Math Rebels Invade Estonia With Computerized Education," by Klint Finley (Wired, 2013)."Do Left-Handed People Really Die Young?" by Hannah Barnes (BBC News, 2013)."Teaching Kids Real Math With Computers," by Conrad Wolfram (TED Talk, 2010). EXTRAS:"Bringing Data to Life," by People I (Mostly) Admire (2023)."Steven Strogatz Thinks You Don't Know What Math Is," by People I (Mostly) Admire (2023)."Mathematician Sarah Hart on Why Numbers are Music to Our Ears," by People I (Mostly) Admire (2021)."America's Math Curriculum Doesn't Add Up," by People I (Mostly) Admire (2021).

“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“It's interesting to me that there are things that people have an intuitive sense of and have for a long, long time had an intuitive sense of that sometimes in science, there's been a tendency to say, "Oh, no, no, no. We have a particular way of thinking about things in science and that doesn't fit with it. So let's lock it out," so to speak. So an example of that, well, for example, animism; you mentioned this question of where are their minds? Is it reasonable to think of the weather as having a mind of its own? Is it reasonable to think of the forest as having a mind, so to speak? Well, in these kind of computational terms, yes, it does become reasonable to think about those things. Now if you say then, one comes to that idea from a place of formalized science, but nevertheless, it relates to sort of intuitions that people have had for a long time about that come from that didn't come from that particular kind of branch formalized thinking.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I think as there is more automation, there is more kind of emphasis on this question of our choice. The story of the development of things tends to be what do humans decide that they care about? In what direction do they want to go? What kind of art do they want to make? What kinds of things do they want to think about? There is in the computational universe of all possibilities, there is sort of infinite creativity. There's an infinite collection of possibilities, but it's something that's a matter of human choice, which of these infinite things do we actually choose to pursue? There's all these different possibilities out there. But our kind of challenge is to decide in which direction we want to go and then to let our automated systems pursue those particular directions.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“It's interesting to me that there are things that people have an intuitive sense of and have for a long, long time had an intuitive sense of that sometimes in science, there's been a tendency to say, "Oh, no, no, no. We have a particular way of thinking about things in science and that doesn't fit with it. So let's lock it out," so to speak. So an example of that, well, for example, animism; you mentioned this question of where are their minds? Is it reasonable to think of the weather as having a mind of its own? Is it reasonable to think of the forest as having a mind, so to speak? Well, in these kind of computational terms, yes, it does become reasonable to think about those things. Now if you say then, one comes to that idea from a place of formalized science, but nevertheless, it relates to sort of intuitions that people have had for a long time about that come from that didn't come from that particular kind of branch formalized thinking.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I have grown up in the kind of Western scientific tradition, so to speak. And what's interesting to see is that some of the questions that we get to ask now have sort of grown out of the Western scientific tradition, are things that have also been asked in quite different traditions. , when I was a kid, people would talk about sort of at a religious level, they would talk about souls and so on. And one would say, "Well, that just can't be anything scientific." I mean, you know, what does a soul weigh? Anything that exists must have a weight; that sounded reasonable from the point of view of the narrow way of thinking about science at the time. Now that we understand this idea of computation, we understand that there can be a thing that is real and meaningful, but it doesn't have a weight. It is merely an abstract thing, a computational thing. And when we think about souls, that's, I think, the idea that what is going for is this kind of computational representation, this computational engram of what's in a brain, for example. And we now have a much better understanding of what that sort of engram, what that abstract, it has no physical weight or anything like that. It's just an abstract thing that can be rendered in a brain.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

“My mother was a philosophy professor in Oxford, and when I was a kid, I would always say, if there's one thing I'll never do when I'm grown up, it's philosophy, because how can one be serious about a field where people are still arguing about the same things that they were arguing about 2,000 years ago, and there's no kind of apparent progress. But actually, the exciting thing has been that both in my kind of work in building computational language, and in my work in understanding the computational foundations of physics, that it turns out that a bunch of those things that people have been arguing about for a couple of thousand years, we can actually say some real things about.It's a funny thing because I've spent my life sort of building this big tower of science and technology and, every so often, something comes out of that tower that people say, "This is a cool thing, we're really going to be excited about this particular thing." For me, the whole tower is the thing that's really important. And in the future, that's what the tower that I've tried to build is certainly the most significant thing I've been able to do. And it's something that, you know, I've been able to see now over the course of half a century or so, kind of how various ideas I've had and directions I've gone have actually played out.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“My mother was a philosophy professor in Oxford, and when I was a kid, I would always say, if there's one thing I'll never do when I'm grown up, it's philosophy, because how can one be serious about a field where people are still arguing about the same things that they were arguing about 2,000 years ago, and there's no kind of apparent progress. But actually, the exciting thing has been that both in my kind of work in building computational language, and in my work in understanding the computational foundations of physics, that it turns out that a bunch of those things that people have been arguing about for a couple of thousand years, we can actually say some real things about.It's a funny thing because I've spent my life sort of building this big tower of science and technology and, every so often, something comes out of that tower that people say, "This is a cool thing, we're really going to be excited about this particular thing." For me, the whole tower is the thing that's really important. And in the future, that's what the tower that I've tried to build is certainly the most significant thing I've been able to do. And it's something that, you know, I've been able to see now over the course of half a century or so, kind of how various ideas I've had and directions I've gone have actually played out.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

“I think one very big example of this phenomenon is the computational irreducibility. This idea that even though you know the rules by which something operates, that doesn't immediately tell you everything about what the system will do. You might have to follow a billion steps in the actual operation of those rules to find out what the system does.There's no way to jump ahead and just say, "the answer will be such and such." Well, computational irreducibility, in a sense, goes against the hope, at least, of, for example, mathematical science. A lot of the hope of mathematical science is that we'll just work out a formula for how something is going to operate. We don't have to kind of go through the steps and watch it operate. We can just kind of jump to the end and apply the formula. Well, computational irreducibility says that that isn't something you can generally do. It says that there are plenty of things in the world where you have to kind of go through the steps to see what will happen.In a sense, even though that's kind of a bad thing for science, it says that there's sort of limitations on the extent to which we can use science to predict things. It's sort of a good thing, I think, for leading one's life because it means that as we experience the passage of time, in a sense, that corresponds to the sort of irreducible computation of what we will do.It's something where that sort of tells one that the passage of time has a meaningful effect. There's something that where you can't just jump to the end and say, "I don't need to live all the years of my life. I can just go and say, and the result will be such and such." No, actually, there's something sort of irreducible about that actual progression of time and the actual living of those years of life, so to speak. So that's kind of one of the enriching aspects of this concept of computational irreducibility. It's a pretty important concept. It's something which I think, for example, in the future of human society, will be something where people right now will think of it as this kind of geeky scientific idea, but in the future, it's going to be a pivotal kind of thing for the understanding of how one should conduct the future of human society.”Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

How can computational language help decode the mysteries of nature and the universe? What is ChatGPT doing and why does it work? How will AI affect education, the arts and society?Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist. He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics at Caltech by the age of 20 and in 1981, became the youngest recipient of a MacArthur Fellowship. Wolfram authored A New Kind of Science and launched the Wolfram Physics Project. He has pioneered computational thinking and has been responsible for many discoveries, inventions and innovations in science, technology and business.“I think one very big example of this phenomenon is the computational irreducibility. This idea that even though you know the rules by which something operates, that doesn't immediately tell you everything about what the system will do. You might have to follow a billion steps in the actual operation of those rules to find out what the system does.There's no way to jump ahead and just say, "the answer will be such and such." Well, computational irreducibility, in a sense, goes against the hope, at least, of, for example, mathematical science. A lot of the hope of mathematical science is that we'll just work out a formula for how something is going to operate. We don't have to kind of go through the steps and watch it operate. We can just kind of jump to the end and apply the formula. Well, computational irreducibility says that that isn't something you can generally do. It says that there are plenty of things in the world where you have to kind of go through the steps to see what will happen.In a sense, even though that's kind of a bad thing for science, it says that there's sort of limitations on the extent to which we can use science to predict things. It's sort of a good thing, I think, for leading one's life because it means that as we experience the passage of time, in a sense, that corresponds to the sort of irreducible computation of what we will do.It's something where that sort of tells one that the passage of time has a meaningful effect. There's something that where you can't just jump to the end and say, "I don't need to live all the years of my life. I can just go and say, and the result will be such and such." No, actually, there's something sort of irreducible about that actual progression of time and the actual living of those years of life, so to speak. So that's kind of one of the enriching aspects of this concept of computational irreducibility. It's a pretty important concept. It's something which I think, for example, in the future of human society, will be something where people right now will think of it as this kind of geeky scientific idea, but in the future, it's going to be a pivotal kind of thing for the understanding of how one should conduct the future of human society.”www.stephenwolfram.comwww.wolfram.comwww.wolframalpha.comwww.wolframscience.com/nks/www.amazon.com/dp/1579550088/ref=nosim?tag=turingmachi08-20www.wolframphysics.orgwww.wolfram-media.com/products/what-is-chatgpt-doing-and-why-does-it-work/www.creativeprocess.infowww.oneplanetpodcast.orgIG www.instagram.com/creativeprocesspodcast

Ever wondered why traditional math education might be holding back our true potential to understand and use mathematics effectively?Conrad Wolfram, strategic director of Wolfram Research and a prominent advocate for transforming math education, joins Jon and Kyle in this episode to explore revolutionary approaches to teaching math. With a fascinating journey from a math and physics enthusiast to a leader in computation software, Conrad sheds light on how our current education system may not be equipping students for the real-world challenges that await them in a technology-driven environment.What you'll learn:Discover Conrad's unique insights into the common misunderstandings and misconceptions in mathematics that can affect learners' confidence and interest.Learn about the shift towards computational thinking and how embracing technology can enhance our problem-solving capabilities.Gain an understanding of why a reevaluation of what and how we teach in math classes could lead to more effective and meaningful education outcomes.Dive into this thought-provoking discussion to see how we can leverage computers to transform math education for the better—listen to the latest episode now!Resources: US Math Wars: What I Know & What I Don't [Conrad Wolfram] District Math Leaders: How are you ensuring that you support those educators who need a nudge to spark a focus on growing their pedagogical-content knowledge? What about opportunities for those who are eager and willing to elevate their practice, but do not have the support? Book a call with our District Improvement Program Team to learn how we can not only help you craft, refine and implement your district math learning goals, but also provide all of the professional learning supports your educators need to grow at the speed of their learning. Book a short conversation with our team now. Love the show? Text us your big takeaway!Get a Customized Math Improvement Plan For Your District.Are you district leader for mathematics? Take the 12 minute assessment and you'll get a free, customized improvement plan to shape and grow the 6 parts of any strong mathematics program.Take the assessment

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: How would you describe what you do? Can you contain it to a single sentence? - What advice do you have for future programmers? - Any advice for someone content to just "get by" financially, with zero interest in the usual understanding of "career" and probably no kids–just looking to focus on other things? - Why don't you quit CEOing and commit full time to investigating whether nature is completely computable? Does running the everyday things help? Or do you just still find it fun? - Do you think there will come a major shift in business planning with AI? - ​How much control do you maintain over the Wolfram Institute? Do you find that loosening your grip on management of the fellows' research allows for a higher chance of success in discovery? - There is this tension regarding remote working vs. being in the office. From my experience in remote-working teams, juniors/new starters take a few months before they are efficient. It appears you have mastered remote working with your teams. What do you think makes remote working a success? - Whenever you were, or are, learning new stuff as part of your independent research efforts (whether that's directly related to your work at Wolfram Research or for your own purposes), do you have a structured purpose, i.e. "I will learn X subject, topic by topic," or do you take a looser approach to things? How do you know how much time to dedicate to your various research interests? - How is innovating "outside the system" different from working within institutions? Is one better than the other for certain fields?

Welcome to the Crazy Wisdom podcast. I'm Stewart Alsop, and in this episode, I'm joined by Stephen Wolfram, a distinguished scientist and the founder of Wolfram Research. Throughout our conversation, we explore a range of topics including Stephen's revitalized work on a fundamental theory of physics, the profound implications of this work for understanding the universe and its laws, and the intersection of these theories with computational technology and AI. We also discuss how these advanced concepts might shape future technological developments and philosophical inquiries into AI's role in society and personal identity. Timestamps [00:00:00] - Stephen Wolfram discusses revisiting his physics theory from the 1990s and the rapid advancements made since 2019. [00:05:00] - Explores implications of his physics project on AI, machine learning, and philosophical questions about the universe's existence. [00:10:00] - Describes the universe's construction from a network of discrete points, explaining emergent phenomena like black holes. [00:15:00] - Discusses the interface between the discrete network model of the universe and concepts of quantum mechanics. [00:20:00] - Shifts focus to computational theory, introducing the "Ruliad" that encompasses all possible computational rules. [00:25:00] - Talks about AI's generative capabilities and its evolving relationship with human cognition and creativity. [00:30:00] - Discusses practical applications of his theoretical work in technology development and complex systems understanding. [00:35:00] - Considers the societal and ethical implications of AI, and the concept of co-evolving with AI in a symbiotic relationship. [00:40:00] - Explores philosophical impacts of AI on human identity, decision-making, and future societal norms. [00:45:00] - Reflects on personal impacts of his work, the continuity of identity through AI, and digital legacies. [00:50:00] - Concludes with thoughts on AI's potential role in human exploration and understanding of the universe. [00:55:00] - Discusses computational thinking and the integration of computational methods in modern problem-solving. Key Insights Revival of Fundamental Physics Theories: Stephen Wolfram discussed reigniting his work on the fundamental theory of physics, an endeavor he first conceptualized in the early 1990s. He returned to these theories with fresh perspectives and the help of young physicists, leading to rapid advancements that surpassed his initial expectations, demonstrating that foundational theories in physics can evolve significantly with the incorporation of new data and technologies. Interconnection Between Physics and Computation: Wolfram elucidated how his latest work in physics unexpectedly bears significant implications for fields like AI, machine learning, and distributed computing. The formalism developed for explaining the universe has versatile applications, suggesting a profound connectivity between physical laws and computational processes. Philosophical Questions on Existence and Regularity: The conversation delved into deep philosophical questions such as why the universe exists and whether the laws of physics are inevitable. Wolfram's approach suggests that these existential queries are not only theoretical but can be addressed in a scientific framework, proposing that our observations of the universe are deeply influenced by human perspectives and limitations. Discrete Network Model of the Universe: Wolfram proposes that the universe is constructed from a network of discrete points, which he likens to atoms of space. This model suggests that all phenomena in the universe, including particles and black holes, emerge from this underlying network, offering a novel way of understanding the fabric of space and time beyond the continuous models traditionally used in physics. Concept of the Ruliad: A significant portion of the discussion focused on the "Ruliad," a conceptual framework that encompasses all possible rules and computations. This idea broadens the scope of computational theory by suggesting a meta-level at which all possible computational processes coexist and interact, providing a new lens through which to view the universe and its complexities. AI's Impact on Creative and Intellectual Pursuits: Wolfram touched upon the transformative impact of AI on creativity and intellectual activities, suggesting that AI not only automates tasks but also enhances human capabilities in arts and sciences. This co-evolution with AI could potentially lead to new forms of art, science, and understanding, radically altering how humans engage with complex problems and creative endeavors. Symbiosis with AI: The episode concluded with a reflection on the future relationship between humans and AI. Wolfram posited that as AI continues to advance, humans will increasingly form a symbiotic relationship with these systems. This integration promises to augment human memory, decision-making, and creativity, potentially leading to a profound shift in how we perceive our capabilities and limitations in relation to technology.

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: Is writing the same as thinking? - After reviewing your Wikipedia page, I noticed that you left undergraduate/postgraduate study before graduation for whatever reason. My question pertains to how you found the application process and background study for being accepted into a PhD program. If you could give some background into how much studying you had completed by that point and how you demonstrated your ability to be accepted, I would be very grateful. - ​Great piece about Doug Lenat and CYC. Any further thoughts about such intrinsically driven, lifelong research pursuits–including your own–be it their significance, their risks or anything in between? - ​I'm finishing my PhD. There are so many industries/groups! Much more than I know, for sure... How can one find "the one" in the ocean? - What made you and Jonathan decide to go on a livestream? Was it planned, or do you just randomly decide to do a livestream if the discussion is interesting enough? - ​How do you determine whether a decision should be decided short term or long term? - How did you allocate your time across strategy, product development, operations, etc., during the early stages of Wolfram Research, and how has that evolved as the company has grown? - If you could create and design a school, how would you structure the curriculum? Would it be different for elementary, middle and high school vs. college? - Do you have a favorite of your livestream series? Are there other types you'd be interested in? - ​Would you suggest working for a startup that is building on an idea from a renowned research institution, or working directly at that institution? - That's basically what they teach you when learning to ride a motorcycle. You trend toward where you're looking. - Along these lines, is it better to say "This is going to be difficult" or "Don't worry, it's not complicated"? - Do you have any advice for people who want to be independent researchers?

Does the use of computer models in physics change the way we see the universe? How far reaching are the implications of computation irreducibility? Are observer limitations key to the way we conceive the laws of physics? In this episode we have the difficult yet beautiful topic of trying to model complex systems like nature and the universe computationally to get into; and how beyond a low level of complexity all systems, seem to become equally unpredictable. We have a whole episode in this series on Complexity Theory in biology and nature, but today we're going to be taking a more physics and computational slant. Another key element to this episode is Observer Theory, because we have to take into account the perceptual limitations of our species' context and perspective, if we want to understand how the laws of physics that we've worked out from our environment, are not and cannot be fixed and universal but rather will always be perspective bound, within a multitude of alternative branches of possible reality with alternative possible computational rules. We'll then connect this multi-computational approach to a reinterpretation of Entropy and the 2nd law of thermodynamics. The fact that my guest has been building on these ideas for over 40 years, creating computer language and Ai solutions, to map his deep theories of computational physics, makes him the ideal guest to help us unpack this topic. He is physicist, computer scientist and tech entrepreneur Stephen Wolfram. In 1987 he left academia at Caltech and Princeton behind and devoted himself to his computer science intuitions at his company Wolfram Research. He's published many blog articles about his ideas, and written many influential books including “A New kind of Science”, and more recently “A Project to Find the Fundamental Theory of Physics”, and “Computer Modelling and Simulation of Dynamic Systems”, and just out in 2023 “The Second Law” about the mystery of Entropy. One of the most wonderful things about Stephen Wolfram is that, despite his visionary insight into reality, he really loves to be ‘in the moment' with his thinking, engaging in socratic dialogue, staying open to perspectives other than his own and allowing his old ideas to be updated if something comes up that contradicts them; and given how quickly the fields of physics and computer science are evolving I think his humility and conceptual flexibility gives us a fine example of how we should update how we do science as we go. What we discuss:  00:00 Intro 07:45 The history of scientific models of reality: structural, mathematical and computational. 20:20 The Principle of Computational Equivalence (PCE) 24:45 Computational Irreducibility - the process that means you can't predict the outcome in advance. 27:50 The importance of the passage of time to Consciousness. 28:45 Irreducibility and the limits of science. 33:30 Godel's Incompleteness Theorem 42:20 Observer Theory and the Wolfram Physics Project. 50:30 We 'make' space. 51:30 Branchial Space - different quantum histories of the world, branching and merging 58:50 Rulial Space: All possible rules of all possible interconnected branches. 01:19:30 The Measurement problem of QM and Entanglement meets computational irreducibility and observer theory.  01:32:40 Inviting Stephen back for a separate episode on AI safety, safety solutions and applications for science, as we did't have time. 01:37:30 At the molecular level the laws of physics are reversible. 01:45:30 Entropy defined in computational terms. 01:50:30 If we ever overcame our finite minds, there would be no coherent concept of existence. 01:51:30 Parallels between modern physics and ancient eastern mysticism and cosmology. 01:55:30 Reductionism in an irreducible world: saying a lot from very little input. References: “The Second Law: Resolving the Mystery of the Second Law of Thermodynamics”, Stephen Wolfram “A New Kind of Science”, Stephen Wolfram Observer Theory Article, Stephen Wolfram

Patreon: https://bit.ly/3v8OhY7 Stephen Wolfram is the founder and CEO of Wolfram Research, and the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics from Caltech when he was twenty years old. In addition to his work at the helm of Wolfram Research, he writes and researches widely across computer science, physics, mathematics, and more. This is Stephen's second appearance on the show. In episode 102, he and Robinson discussed artificial intelligence, ChatGPT, and the philosophy of math. In this episode, however, they turn to the Ruliad—the entangled limited of computability—and Stephen's search for the fundamental theory of physics. Along the way, they talk about the philosophy of science, abstract and concrete objects, and quantum mechanics. A Project to Find the Fundamental Theory of Physics: https://www.amazon.com/dp/B0917YZDNF?ref_=cm_sw_r_cp_ud_dp_Z7EPANZC9JVQR0HP2E1D The Concept of the Ruliad: https://writings.stephenwolfram.com/2021/11/the-concept-of-the-ruliad/#:~:text=November%2010%2C%202021-,The%20Entangled%20Limit%20of%20Everything,arisen%20from%20our%20Physics%20Project. Stephen's Website: https://www.stephenwolfram.com Stephen's Twitter: https://twitter.com/stephen_wolfram Wolfram Research on YouTube: https://a.co/d/aADrGGh OUTLINE 00:00 Introduction 03:44 How Did Stephen Wolfram Discover the Ruliad?  34:22 The Axiomatic Revolution in Physics  46:37 Is the Ruliad a Theory or an Object?  1:10:01 How Big is the Space of Alien Minds?  1:18:25 Is the Universe an Abstract Object?  1:31:43 What Is Quantum Mechanics?  Robinson's Website: http://robinsonerhardt.com Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.  --- Support this podcast: https://podcasters.spotify.com/pod/show/robinson-erhardt/support

Embark on an extraordinary journey through the life and mind of one of the most influential figures in the world of computation and physics – Stephen Wolfram. Today, we are talking to Stephen Wolfram, founder and CEO of Wolfram Research and creator of Mathematica and Wolfram Alpha answer engine. We traced Stephen's academic journey from Eton College to Oxford and CalTech, covering milestones, first scientific papers at 15, and the shift from space to physics. Delving into chapters on his PhD, teaching at CalTech, and receiving the MacArthur Fellowship, Stephen shared insights on complex systems, mentorship, and encounters with figures like Richard Feynman and Steve Jobs. After exploring the creation and impact of Wolfram Alpha, the Wolfram Physics Project, and his current pursuits, we also gained insights into Stephen's productivity system, reflections on parenting, friendships, and Hollywood interactions. Throughout the episode, Stephen imparted wisdom and advice for fresh college graduates, leaving a profound mark on the sands of history. We hope that his wisdom will help you mark the trajectory of your academic and professional career while you have fun listening to the new episode of our podcast. Enjoy!

In his final years, Richard Feynman's curiosity took him to some surprising places. We hear from his companions on the trips he took — and one he wasn't able to. (Part three of a three-part series.) SOURCES: Alan Alda, actor and screenwriter.Barbara Berg, friend of Richard Feynman.Helen Czerski, physicist and oceanographer at University College London.Michelle Feynman, photographer and daughter of Richard Feynman.Cheryl Haley, friend of Richard Feynman.Debby Harlow, friend of Richard Feynman.Ralph Leighton, biographer and film producer.Charles Mann, science journalist and author.John Preskill, professor of theoretical physics at the California Institute of Technology.Lisa Randall, professor of theoretical particle physics and cosmology at Harvard University.Christopher Sykes, documentary filmmaker.Stephen Wolfram, founder and C.E.O. of Wolfram Research; creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. RESOURCES: Quantum Man: Richard Feynman's Life in Science, by Lawrence M. Krauss (2011).Perfectly Reasonable Deviations From the Beaten Track: Selected Letters of Richard P. Feynman, edited by Michelle Feynman (2005).The Pleasure of Finding Things Out, by Richard Feynman (1999).The Demon-Haunted World: Science as a Candle in the Dark, by Carl Sagan and Ann Druyan (1995).Genius: The Life and Science of Richard Feynman, by James Gleick (1992).The Quest for Tannu Tuva, by Christopher Sykes (1988)“What Do You Care What Other People Think?” by Richard Feynman and Ralph Leighton (1988).The Second Creation: Makers of the Revolution in Twentieth-century Physics, by Robert Crease and Charles Mann (1986).Surely You're Joking, Mr. Feynman!, by Richard Feynman and Ralph Leighton (1985).Fun to Imagine, BBC docuseries (1983). EXTRAS: “The Brilliant Mr. Feynman,” by Freakonomics Radio (2024).“The Curious Mr. Feynman,” by Freakonomics Radio (2024).

What happens when an existentially depressed and recently widowed young physicist from Queens gets a fresh start in California? We follow Richard Feynman out west, to explore his long and extremely fruitful second act. (Part two of a three-part series.) SOURCES:Seamus Blackley, video game designer and creator of the Xbox.Carl Feynman, computer scientist and son of Richard Feynman.Michelle Feynman, photographer and daughter of Richard Feynman.Ralph Leighton, biographer and film producer.Charles Mann, science journalist and author.John Preskill, professor of theoretical physics at the California Institute of Technology.Lisa Randall, professor of theoretical particle physics and cosmology at Harvard University.Christopher Sykes, documentary filmmaker.Stephen Wolfram, founder and C.E.O. of Wolfram Research; creator of Mathematica, Wolfram|Alpha, and the Wolfram Language.Alan Zorthian, architect. RESOURCES:"Love After Life: Nobel-Winning Physicist Richard Feynman's Extraordinary Letter to His Departed Wife," by Maria Popova (The Marginalian, 2017).Quantum Man: Richard Feynman's Life in Science, by Lawrence M. Krauss (2011).The Pleasure of Finding Things Out, by Richard Feynman (1999).Genius: The Life and Science of Richard Feynman, by James Gleick (1992)."G. Feynman; Landscape Expert, Physicist's Widow," (Los Angeles Times, 1990)."Nobel Physicist R. P. Feynman of Caltech Dies," by Lee Dye (Los Angeles Times, 1988).“What Do You Care What Other People Think?” by Richard Feynman and Ralph Leighton (1988).The Second Creation: Makers of the Revolution in Twentieth-century Physics, by Robert Crease and Charles Mann (1986).Surely You're Joking, Mr. Feynman!, by Richard Feynman and Ralph Leighton (1985).Fun to Imagine, BBC docuseries (1983)."Richard P. Feynman: Nobel Prize Winner," by Tim Hendrickson, Stuart Galley, and Fred Lamb (Engineering and Science, 1965).F.B.I. files on Richard Feynman. EXTRAS:"The Curious Mr. Feynman," by Freakonomics Radio (2024).

From the Manhattan Project to the Challenger investigation, the physicist Richard Feynman loved to shoot down what he called “lousy ideas.” Today, the world is awash in lousy ideas — so maybe it's time to get some more Feynman in our lives? (Part one of a three-part series.) SOURCES:Helen Czerski, physicist and oceanographer at University College London.Michelle Feynman, photographer and daughter of Richard Feynman.Ralph Leighton, biographer and film producer.Charles Mann, science journalist and author.John Preskill, professor of theoretical physics at the California Institute of Technology.Stephen Wolfram, founder and C.E.O. of Wolfram Research; creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. RESOURCES:"How Legendary Physicist Richard Feynman Helped Crack the Case on the Challenger Disaster," by Kevin Cook (Literary Hub, 2021).Challenger: The Final Flight, docuseries (2020).Truth, Lies, and O-Rings: Inside the Space Shuttle Challenger Disaster, by Allan J. McDonald and James R. Hansen (2009).Perfectly Reasonable Deviations From the Beaten Track: Selected Letters of Richard P. Feynman, edited by Michelle Feynman (2005).The Pleasure of Finding Things Out, by Richard Feynman (1999).Genius: The Life and Science of Richard Feynman, by James Gleick (1992).“What Do You Care What Other People Think?” by Richard Feynman and Ralph Leighton (1988)."Mr. Feynman Goes to Washington," by Richard Feynman and Ralph Leighton (Engineering & Science, 1987).The Second Creation: Makers of the Revolution in Twentieth-century Physics, by Robert Crease and Charles Mann (1986).Surely You're Joking, Mr. Feynman!, by Richard Feynman and Ralph Leighton (1985)."The Pleasure of Finding Things Out," (Horizon S18.E9, 1981)."Los Alamos From Below," by Richard Feynman (UC Santa Barbara lecture, 1975)."The World from Another Point of View," (PBS Nova, 1973). EXTRAS:"Exploring Physics, from Eggshells to Oceans," by People I (Mostly) Admire (2023).

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Today's guest is the one and only Stephen Wolfram - a physicist, mathematician, computer scientist and entrepreneur He is the founder and CEO of Wolfram Research, the creator of Mathematica, Wolfram Alpha and Wolfram Language, The Wolfram Physics Project and the author of bestselling A New Kind of Science among many other books.A visionary polymath, Stephen published his first scientific paper at age 15, received his PhD in theoretical physics soon after his 20th birthday and became the youngest recipient of the Macarthur Fellowship Genius grant at age 21.Over the course of his career which spans more than four decades, he has been a pioneer in the development and application of computational thinking, and has been responsible for many discoveries, inventions, and innovations in the fields of science and technology.In this episode, we discuss his childhood, how he might reimagine education, the process of undertaking ambitious, long-term innovation projects, why he works in public and the surprising advice he would offer a younger Stephen.I really enjoyed talking to Stephen and I think you will learn a lot from this episode. Enjoy!Stephen Wolfram website / Twitter I am not on social media this year but stay in touch via my Newsletter / YouTube  

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include:Should I become a programmer? At what age do you think kids should start learning computer-related skills? Should programming be a core class for students, like math and English? - What do you think are good ways to introduce computational thinking to kids? - But can you really get to a point to ask if there is something that you want to do that can be solved computationally without at least going about a trial-and-error-type process? - "Human-AI coauthorship" is what I call it now. - What would be some examples of the differences between programming, mathematical thinking and computational thinking? Or is there a difference? Is this just a colloquial thing? - Would you consider hiring someone without a technical background? - What is the minimum body of knowledge one should gather before being able to produce meaningful ideas in one research area? - What was the hardest part in starting Wolfram Research? - What are your thoughts on learning things outside of your domain of expertise? How should one balance their time between diving deep into their primary domain and exploring things outside of that? - What valuable new products will Wolfram Research build using AI in the next decade? What ideas do you have that you hope others build? - What do you think is going to happen in the next five years with AIs? What's the next big "surprise" thing like ChatGPT you think will come? - What's the worst thing that could happen with AI? - Are you concerned that we are building our murderer? Or that we have to simulate worlds empty of influence to determine the genuine intentions/alignments of an AI? - Which is better: ChatGPT calling a plugin, or a plugin/standalone calling ChatGPT? Depends on the application, probably. - I'd love for an AI to be able to, for instance, teach me chess in the most optimal way by figuring out my weaknesses and how to reinforce my learning. - One thing to consider: If the galaxy is incredibly vast, why wouldn't an AI just leave Earth so that it can gather resources elsewhere? Or it could even explore the universe. Staying on Earth seems like it'd be very limiting to an AI or superintelligence. - How can one NOT get left behind socially and economically in the wake of AI innovation? - One thing I was thinking earlier is that what we're going to be seeing now is "automation of AI," where we have lots of websites and APIs that do one machine learning task well, and then we're handing off data from one model to the next. - I like the idea of LLMs acting as the core interface module for a "soup" of APIs in a cognitive/hybrid AI

Theodore Gray is a co-founder of Wolfram Research and creator of the Notebook user interface (since lovingly copied by Jupyter Notebooks). He is the author of several books and iPad apps including the NYTs best-seller The Elements, and writer/director of Disney Animated (BAFTA award winner and Apple's iPad App of the Year 2013). His latest book is TOOLS, which is all about his favorite tools.   Website: https://theodoregray.com   Watch on YouTube: https://youtu.be/k2eZ4W7VgYs   For show notes and transcript visit: https://kk.org/cooltools/theodore-gray-co-founder-of-wolfram-research-3/   To sign up to be a guest on the show, please fill out this form: https://forms.gle/qc496XB6bGbrAEKK7  

Stephen Wolfram is a physicist, computer scientist and businessman. He is the founder and CEO of Wolfram Research, the creator of Mathematica and Wolfram Alpha, and the author of A New Kind of Science. Full transcript available at: jnwpod.com.See omnystudio.com/listener for privacy information.

Today on, Breaking Barriers: Understanding the AI Revolution, is part II of Jamil's conversation with Dr. Stephen Wolfram, founder of Mathematica and Wolfram Research and all-around AI expert on the complexities of AI and potential regulation. Dr. Wolfram talks about AI free will, the moral complexities of AI's decision making, and how AI can streamline supply chains.Should we be worried about AI developing its own free will? How much decision-making power can we leave to AI on its own, if any? How would the government begin to regulate AI? Tune into Fault Lines all summer to hear from more AI experts as part of, Breaking Barriers: Understanding the AI Revolution!Want to learn more about this topic? Check out Dr. Stephen Wolfram's website: https://www.stephenwolfram.com/ Follow our experts on Twitter:@jamil_n_jaffer@stephen_wolframLike what we're doing here? Be sure to rate, review, and subscribe.And don't forget to follow @masonnatsec on Twitter! Hosted on Acast. See acast.com/privacy for more information.

Today, to kick off our special summer series, Breaking Barriers: Understanding the AI Revolution, Jamil is joined by Dr. Stephen Wolfram, founder of Mathematica and Wolfram Research, creator of the Wolfram Language, author of, What is Chat GPT Doing… and Why Does it Work?, and all-around AI expert to dissect the complexities of artificial intelligence. Dr. Wolfram explains the origins of AI, how computational systems operate, and the ways that large language models are able to generate lively essays. Are computers able to learn? How does AI generate human-like essays? What is the difference between computational systems and the human brain?Tune into Fault Lines all summer to hear from more AI experts as part of, Breaking Barriers: Understanding the AI Revolution!Want to learn more about this topic? Check out Dr. Stephen Wolfram's website: https://www.stephenwolfram.com/ Follow our experts on Twitter:@jamil_n_jaffer@stephen_wolframLike what we're doing here? Be sure to rate, review, and subscribe.And don't forget to follow @masonnatsec on Twitter! Hosted on Acast. See acast.com/privacy for more information.

Can you think of another big company CEO that does basic science? Stephen Wolfram is the CEO of Wolfram Research – the company that developed Mathematica and Wolfram Alpha – but most fundamentally he has a deep commitment to figuring out the nature of reality. Stephen wrote the landmark ‘A new kind of science' in 2002 and in his current ‘physics project', Steven is trying to show that the universe is at its core computation, and that its fundamental laws arise from simple computational programs. We talked with Stephen about how he drills down to get the simplest possible explanations to tackle the foundations of scientific fields. He also told us how he makes progress by coming in with new tools to the old problems, with his own brand of scientific creativity.For more information on Night Science, visit https://www.biomedcentral.com/collections/night-science .

Stephen Wolfram is the founder and CEO of Wolfram Research, and the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. He received his PhD in theoretical physics from Caltech when he was twenty years old. In addition to his work at the helm of Wolfram Research, he writes and researches widely across computer science, physics, mathematics, and more. Most recently, Stephen is the author of What Is ChatGPT Doing…and Why Does It Work? (2023). Robinson and Stephen begin by discussing just this, before moving on to some more theoretical questions about intelligence in general and artificial intelligence in particular. Then, after a long digression on the philosophy of mathematics and the foundations of computation, they turn to the ways in which ChatGPT may impact research in STEM fields and beyond. What Is ChatGPT Doing…and Why Does It Work?: https://a.co/d/aADrGGh Stephen's Website: https://www.stephenwolfram.com Stephen's Twitter: https://twitter.com/stephen_wolfram Wolfram Research on YouTube: https://a.co/d/aADrGGh OUTLINE 00:00 In This Episode… 00:29 Introduction 03:42 How Does ChatGPT Work? 11:58 Does ChatGPT Pass the Turing Test? 34:33 Will Philosophy Be a Growth Industry? 41:02 Will Mathematicians be Replaced by Computers? 49:26 What is the Ruliad?  01:08:57 Philosophy of Mathematics? 01:32:54 LLMs and STEM 01:43:16 Returning to ChatGPT and AI Robinson's Website: http://robinsonerhardt.com Robinson Erhardt researches symbolic logic and the foundations of mathematics at Stanford University. Join him in conversations with philosophers, scientists, weightlifters, artists, and everyone in-between.  --- Support this podcast: https://podcasters.spotify.com/pod/show/robinson-erhardt/support

It is time to stop learning the computer's programming language, and get computers to learn our language. Prepare think different - or should we say alien

Stephen Wolfram is a computer scientist, mathematician, theoretical physicist, and the founder of Wolfram Research, a company behind Wolfram|Alpha, Wolfram Language, and the Wolfram Physics and Metamathematics projects. Please support this podcast by checking out our sponsors: - MasterClass: https://masterclass.com/lex to get 15% off - BetterHelp: https://betterhelp.com/lex to get 10% off - InsideTracker: https://insidetracker.com/lex to get 20% off EPISODE LINKS: Stephen's Twitter: https://twitter.com/stephen_wolfram Stephen's Blog: https://writings.stephenwolfram.com Wolfram|Alpha: https://www.wolframalpha.com A New Kind of Science (book): https://amzn.to/30XoEun Fundamental Theory of Physics (book): https://amzn.to/30XbAoT Blog posts: A 50-Year Quest: https://bit.ly/3NQbZ2P What Is ChatGPT doing: https://bit.ly/3VOwtuz PODCAST INFO: Podcast website: https://lexfridman.com/podcast Apple Podcasts: https://apple.co/2lwqZIr Spotify: https://spoti.fi/2nEwCF8 RSS: https://lexfridman.com/feed/podcast/ YouTube Full Episodes: https://youtube.com/lexfridman YouTube Clips: https://youtube.com/lexclips SUPPORT & CONNECT: - Check out the sponsors above, it's the best way to support this podcast - Support on Patreon: https://www.patreon.com/lexfridman - Twitter: https://twitter.com/lexfridman - Instagram: https://www.instagram.com/lexfridman - LinkedIn: https://www.linkedin.com/in/lexfridman - Facebook: https://www.facebook.com/lexfridman - Medium: https://medium.com/@lexfridman OUTLINE: Here's the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time. (00:00) - Introduction (06:45) - WolframAlpha and ChatGPT (26:26) - Computation and nature of reality (53:18) - How ChatGPT works (1:53:01) - Human and animal cognition (2:06:20) - Dangers of AI (2:14:39) - Nature of truth (2:36:01) - Future of education (3:12:03) - Consciousness (3:21:02) - Second Law of Thermodynamics (3:44:36) - Entropy (3:57:36) - Observers in physics (4:14:27) - Mortality

Aarthi and Sriram's Good Time Show ✓ Claim Key Takeaways By keeping the mechanics of your life as straightforward as possible, you can increase the amount of effort you put into the intellectual, creative side of your lifeChatGPT is adding a word at a time and figuring out the likely way that humans would continue that particular piece of text, based on what they have written in a few billion web pages“This whole idea of computational language just got much more exciting … because it becomes this medium for communication and collaboration between humans and AIs.” – Stephen Wolfram  In the end, the world will have a civilization of AIs that have an infrastructure that operates in these ways that humans cannot readily understandIronically, this is the situation that humans have been in with respect to the natural world the whole of our existenceThe natural world does all types of computations that we do not really understand, and yet we coexist with the natural world  Read the full notes @ podcastnotes.org0:00 Intro 1:54 How Stephen Wolfram approaches productivity 6:12 Stephen's day-in-life 7:45 Stephen's outlook on artificial intelligence 13:05 The human brain-artificial intelligence analogy 16:40 Wolfram's unique approach to GPT 31:00 The Pi computation 34:14 Risks of AI 45:32 Stephen's X factor 51:36 Are things as complex as they seem? 1:03:00 Do the simple things right Renowned physicist, mathematician, and computer scientist Stephen Wolfram joined us on the podcast to discuss AI, physics, and more. We explored the state of artificial intelligence and the challenges and opportunities it presents. Stephen shared his insights into the computational universe and cellular automata and their relationship to physics.

0:00 Intro1:54 How Stephen Wolfram approaches productivity6:12 Stephen's day-in-life7:45 Stephen's outlook on artificial intelligence13:05 The human brain-artificial intelligence analogy16:40 Wolfram's unique approach to GPT31:00 The Pi computation34:14 Risks of AI45:32 Stephen's X factor51:36 Are things as complex as they seem?1:03:00 Do the simple things rightRenowned physicist, mathematician, and computer scientist Stephen Wolfram joined us on the podcast to discuss AI, physics, and more. We explored the state of artificial intelligence and the challenges and opportunities it presents. Stephen shared his insights into the computational universe and cellular automata and their relationship to physics.

Welcome back to the function room with me Colm O'Regan. This week, it's ChatGPT. The latest thing that makes people starting dropping the phrase AI into small talk. ChatGPT and all the Ais are of huge interest to my guest. Conrad Wolfram. He's kind of a big deal. Strategic and international director of Wolfram Research which makes Mathematica the computational software and nearly 4 decades in the area of computational education, Conrad has written The maths fix, about how AI will, or should make the maths we study in school very different. We talk steam engines, democracy and poems about lightbulb filaments. You know, the standard stuff. Find him at conradwolfram.com, find chatGPT at chat.openai.com

Stephen Wolfram of Wolfram Research joins Jason for an all-encompassing conversation about AI, from the history of neural nets (7:53) to how modern ai emulates the human brain (19:33). This leads to an in-depth discussion about the pace at which AI is evolving (43:46), The “Post-Knowledge Work” era (58:45), the unintended consequences of AI (1:03:52), and so much more. (0:00) Nick kicks off the show (1:24) Under the hood of ChatGPT (7:53) What is a neural net?  (10:05) Cast.ai - Get a free cloud cost audit with a personal consultation at https://cast.ai/twist (11:33) Determining values and weights in a neural net (18:28) Vanta - Get $1000 off your SOC 2 at https://vanta.com/twist (19:33) Emulating the human brain (23:26) Defining computational irreducibility (26:14) Emergent behavior and the rules of language (31:49) Discovering logic + creating a computational language (38:10) Clumio - Start a free backup, or sign up for a demo at https://clumio.com/twist (39:38) Wolfram's ChatGPT plugin (43:46) The rapid pace of AI  (58:45) The “Post-Knowledge Work” era (1:03:52) The unintended consequences of AI  (1:11:45) Rewarding innovation  (1:16:12) The possibility of AGI  (1:20:07) Creating a general-purpose robotic system FOLLOW Stephen: https://twitter.com/stephen_wolfram FOLLOW Jason: https://linktr.ee/calacanis Subscribe to our YouTube to watch all full episodes: https://www.youtube.com/channel/UCkkhmBWfS7pILYIk0izkc3A?sub_confirmation=1 FOUNDERS! Subscribe to the Founder University podcast: https://podcasts.apple.com/au/podcast/founder-university/id1648407190

Stephen Wolfram is sane in a way most people are crazy. In this episode of the UIUC Talkshow, we delve into the mind of one of the most brilliant and accomplished thinkers of our time, Stephen Wolfram. At the age of 15, he published his first scientific paper and received his Ph.D. in theoretical physics from Caltech by age 20. Wolfram is the founder and CEO of Wolfram Research, the company behind the revolutionary Mathematica, Wolfram Alpha (the revolutionary computational search engine), Wolfram Language, and the new Wolfram Physics project. He is also the author of several books, including 'A New Kind of Science'. Wolfram shares his unique perspective on the world of education, discussing what he would study in college today, the importance of self-teaching, and why he believes physics is the ultimate college major. He also delves into the challenges of being a professor and the role of intuition in learning. Wolfram talks about his educational journey, having dropped out of college twice and getting his Ph.D. under Richard Feynman. In this fascinating conversation, Wolfram challenges traditional notions of education, encouraging independent thinking. We also discuss the overrated nature of computer science, and why Wolfram recommends avoiding computer science to do Computational X. He also delves into his thoughts on the machinery of education and how to teach people to think critically. Wolfram also offers insights into the inner workings of his thought process and his personal ideology and musings on the possibilities of alien technology. Throughout the interview, Stephen's passion and curiosity shine through as he shares his ideas on the future of technology, the concept of the Ruliad, and the implications of alien intelligence on our understanding of the world. He also shares his thoughts on the overrated and underrated aspects of the world, including the Nobel Prize, Apple, and the "Elon Musk College Theory." This interview is a must-watch for anyone interested in the intersection of technology, science, and education. Join us as we inquire into the mind of one of the most brilliant minds of our time and gain valuable insights into the future of our world. This is the UIUC Talkshow and this is our conversation with Stephen Wolfram. EPISODE LINKS: Stephen Wolfram's Website: https://www.stephenwolfram.com/ Stephen Wolfram's Writing: https://writings.stephenwolfram.com/ Stephen Wolfram's Twitter: https://twitter.com/stephen_wolfram Wolfram's Physics Project: https://www.wolframphysics.org/ Wolfram Summer School: https://education.wolfram.com/summer-school Wolfram's Livestreaming: @WolframResearch OUTLINE: 0:00 - Introduction 0:50 - What Would Wolfram Study in College Today? 4:03 - Don't Study Computer Science 7:40 - Teach Yourself 9:05 - Physics: The Ultimate College Major 10:40 - Should you go to College? 15:52 - How to Approach College? 16:48 - Computer Science is Overrated 22:16 - School teaches a small portion of the world 24:05 - Being a Professor 26:23 - Anything deep enough is interesting 27:43 - Education isn't about thinking 30:25 - How do you teach people to think? 37:40 - NPC Theory and Pivoting 40:12 - Livestreaming 42:26 - The Machinery of Education 48:07 - Knowledge is invented and someone has to do it 49:28 - Why Learn History? 53:56 - Intuition & Paradigm 59:20 - Quantum mechanics 1:03:32 - No one thinks about the foundations 1:06:15 - Id

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: Can you use Wolfram Language to log onto a website with username and password and read data from a website? - Will computational chem/Biochem programs (Alphafold2?) be accurate enough in its predictions to completely dominate private R&D to reduce the costs and duration of expensive wet lab experimentation? - When did you first decide to hire people at Wolfram Research? How did you recruit & evaluate them? What have you learned about hiring since then? - ​have you ever authentically read and replied to an unsolicited email if someone has an important idea for Mathematica and/or the Wolfram Language? - Do you have developers that work in a large variety of topics (changing monthly perhaps), or are most in a 'fixed' position/topic? - When you reach the level you do with Wolfram Research, what steps do you undertake to ensure that you continue to innovate and don't lose ground to your competitors, and that you don't take the wrong business decisions? - As someone with a technical background, how do you maintain a holistic overview of your company? For instance, do you better attempt to understand the company's financial books? - what is your work out routine? - how do you balance time being creative (for projects) vs the everyday necessary work? - At the start of crypto projects there is always this battle between centralization and decentralization. You need an amount of centralization in the beginning to get things going. How long should a project be given before you let in the masses? - Do you have an opinion concerning "Poor Charlie's almanacs: The Wit and Wisdom of Charles T. Munger"? - Do you use rules similar to those in Cellular Automata when you manage your company or your company's projects?

Brought to you by Tommy John premium underwear, Eight Sleep's Pod Cover sleeping solution for dynamic cooling and heating, and ButcherBox premium meats delivered to your door.Stephen Wolfram (@stephen_wolfram) is the creator of Mathematica, Wolfram|Alpha and the Wolfram Language; the author of A New Kind of Science; the originator of the Wolfram Physics Project; and the founder and CEO of Wolfram Research. Over the course of more than four decades, he has been a pioneer in the development and application of computational thinking and has been responsible for many discoveries, inventions, and innovations in science, technology, and business.Please enjoy!This episode is brought to you by ButcherBox! ButcherBox makes it easy for you to get high-quality, humanely raised meat that you can trust. They deliver delicious, 100% grass-fed, grass-finished beef; free-range organic chicken; heritage-breed pork, and wild-caught seafood directly to your door.This Black Friday, your search for amazing deals on high-quality protein ends with ButcherBox. ButcherBox is offering my listeners one of their best steak deals: Free Rib Eyes for a Year, plus $20 off. Get two, 10 oz rib eyes FREE in every box for a whole year when you join, plus an additional $20 off! Sign up today at butcherbox.com/Tim and use code TIM to get Free Rib Eyes for a Year, plus $20 off. *This episode is also brought to you by Eight Sleep! Eight Sleep's Pod Cover is the easiest and fastest way to sleep at the perfect temperature. It pairs dynamic cooling and heating with biometric tracking to offer the most advanced (and user-friendly) solution on the market. Simply add the Pod Cover to your current mattress and start sleeping as cool as 55°F or as hot as 110°F. It also splits your bed in half, so your partner can choose a totally different temperature.For a limited time, Eight Sleep is offering my listeners up to $450 off their Sleep Fit Holiday Bundle, which includes my personal favorite, the Pod 3 Cover. Go to EightSleep.com/Tim to get the exclusive holiday savings. Eight Sleep currently ships within the USA, Canada, the UK, select countries in the EU, and Australia. That's EightSleep.com/Tim*This episode is also brought to you by Tommy John premium underwear! For men, Tommy John offers six different styles so you can find the one that suits you best. Their line of men's briefs and boxers is one of my top choices for all-day comfort. I tested their Second Skin Mid-Length Boxer Brief and the Cool Cotton Trunk.Shop Tommy John's Black Friday sale going on right now, and get 30 percent off sitewide at TommyJohn.com/Tim. See the website for details.*For show notes and past guests on The Tim Ferriss Show, please visit tim.blog/podcast.For deals from sponsors of The Tim Ferriss Show, please visit tim.blog/podcast-sponsorsSign up for Tim's email newsletter (5-Bullet Friday) at tim.blog/friday.For transcripts of episodes, go to tim.blog/transcripts.Discover Tim's books: tim.blog/books.Follow Tim:Twitter: twitter.com/tferriss Instagram: instagram.com/timferrissYouTube: youtube.com/timferrissFacebook: facebook.com/timferriss LinkedIn: linkedin.com/in/timferrissPast guests on The Tim Ferriss Show include Jerry Seinfeld, Hugh Jackman, Dr. Jane Goodall, LeBron James, Kevin Hart, Doris Kearns Goodwin, Jamie Foxx, Matthew McConaughey, Esther Perel, Elizabeth Gilbert, Terry Crews, Sia, Yuval Noah Harari, Malcolm Gladwell, Madeleine Albright, Cheryl Strayed, Jim Collins, Mary Karr, Maria Popova, Sam Harris, Michael Phelps, Bob Iger, Edward Norton, Arnold Schwarzenegger, Neil Strauss, Ken Burns, Maria Sharapova, Marc Andreessen, Neil Gaiman, Neil de Grasse Tyson, Jocko Willink, Daniel Ek, Kelly Slater, Dr. Peter Attia, Seth Godin, Howard Marks, Dr. Brené Brown, Eric Schmidt, Michael Lewis, Joe Gebbia, Michael Pollan, Dr. Jordan Peterson, Vince Vaughn, Brian Koppelman, Ramit Sethi, Dax Shepard, Tony Robbins, Jim Dethmer, Dan Harris, Ray Dalio, Naval Ravikant, Vitalik Buterin, Elizabeth Lesser, Amanda Palmer, Katie Haun, Sir Richard Branson, Chuck Palahniuk, Arianna Huffington, Reid Hoffman, Bill Burr, Whitney Cummings, Rick Rubin, Dr. Vivek Murthy, Darren Aronofsky, Margaret Atwood, Mark Zuckerberg, Peter Thiel, Dr. Gabor Maté, Anne Lamott, Sarah Silverman, Dr. Andrew Huberman, and many more.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Aldo talks to Conrad Wolfram about why he feels he is in a unique central position to spread the word on radically changing the way we teach and learn Mathematics.    Guest Introduction:    Throughout my career as an edtech builder and working with teachers & students over the globe, I have spoken to many people who feel that things need to be done differently in Education. Some demand drastic changes while others say that small, incremental alterations will eventually lead to a new re-energised process of teaching and learning.    The people I speak to, some of them have been guests on this podcast, are often holistic thinkers and speak about overall systemic changes and new approaches to education but my next guest has good reasons to get very specific and change the way we teach and learn one subject that affects us all: Mathematics.    Conrad Wolfram has been working for decades on changing the way we teach and learn Mathematics in schools. In 2010 he founded ComputerBasedMathematics.org to end the disconnect between school mathematics and real life justifiably claiming that we should embrace computers more in the process.    In a variety of interviews & talks Wolfram advocates for us to ‘democratise experience' by making full use of the technology tools and automated computational thinking available to us.    “Computers put great automation levels between the mechanics of math, the calculating, and what you're trying to get done, too. When the automation gets good, you can go much further by doing it on the machine with a computer than you can by hand, and the subject of the mechanics of calculating becomes a distinct subject from using, applying, or doing math.” states Wolfram in an inspiring TED talk he held back in 2010.   In his 2020 book: ‘The Math(s) Fix: An Education Blueprint for the AI Age' Wolfram exposes why maths education is in a global crisis, and how the only fix is a fundamentally new mainstream subject.    “After more than 15 years of conceptualising the idea, 10 years of build-out and 2 years of writing and editing” Conrad Wolfram published the book in June last year.    The Math(s) Fix' does not only identify the problem and aligning complaints, but also suggests a clear alternative outlining a four-step process that can be used across the curriculum: define the questions, abstract them to computable form, compute answers, and interpret results.   The book was very warmly received and even won an Independent Press Award in Education earlier this year.    Seemingly Conrad was born into critical, independent, abstract thinking as both his parents were writers. His mother Sybil Wolfram was a Fellow & Tutor in Philosophy at Lady Margaret Hall at the University of Oxford and his brother Stephen is a well-known physicist, mathematician and computer scientist who (among others) became a fellow of the American Mathematical Society in 2012.    Conrad holds Masters degrees in Natural Sciences and Mathematics from Cambridge University and founded the company Wolfram Research Europe Ltd. in 1991.    Together with his brother, Conrad has also been shaping up the company Wolfram Research since 1996.    Among many other things, Conrad has led the effort within this company to move the use of its flagship product called ‘Mathematica' from a pure computation system to a development and deployment engine.    Needless to say that for this interview I am in the company of a great mind that I am dying to pick for ideas on Maths Education Reform.    A very warm welcome to you Conrad!   You can find out more about Conrad's book here: https://www.computerbasedmath.org/the-maths-fix   And find helpful resources here: https://www.wolfram.com/wolfram-u/catalog/computational-thinking/