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16 episodes with Wolfram Language
3 episodes with Wolfram Language
2 episodes with Wolfram Language
2 episodes with Wolfram Language
2 episodes with Wolfram Language
2 episodes with Wolfram Language
2 episodes with Wolfram Language
2 episodes with Wolfram Language
2 episodes with Wolfram Language
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: For the new Notebook Assistant, what is the process for making a new product like that? - When making a new product, is it harder to create something brand new with no competition or easier when there are competing products to compare? - Good product; tbh I signed up and took it for a test drive yesterday. Great to chat and work Mathematica for a newbie like me; excellent progress in a short time. - I bought a Wolfram subscription for my daughter who is in Year 7. However, it seems it is not very straightforward in usability for a 12-year-old who can use in her study intuitively. - Would you consider enhancing or introducing new tools for a younger audience like my daughter? At least provide feature of ask random question in plain English and get concise answer with graphics to study science (chemistry, physics, biology). - Do you ever watch funny cat videos? - What do you think about Nvidia's CEO Jensen's approach to sending all through emails and having like 60 people directly report to him all day with email reports, and he is managing the whole company? - I would love to see software development discussions from the ground up. Sort of a Live Software Engineering series to complement the content of Live CEOing. E.g. building the WordCloud function. I like seeing the design reviews during Live CEOing, but I'm always wondering how the functions actually get implemented in code and how software developers approach programming Wolfram Language functions. - Do you have a cat? - How many meetings would you say you attend a day? How do you get the most out of them? - Apparently there is a small island inhabited by a throng of cats. They survive because the local fish jump out of the water onto the beach. - I saw a TikTok saying if you eat eggs raised on farms with cats on there, you can kick the allergy!! - Based on a random week earlier last month, you average about 12 meetings a week when they're "normal sized." - What are your tips for consistently practicing self-discipline?
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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-qa Questions include: Why is history important? - History is very good at preventing humanity from making the same mistakes. - How would you explain the history of pi? - Do we know why Brahmagupta came up with the rules for arithmetic and algebra with zero and negative quantities? His book does appear to be a discontinuous jump in understanding. - Do you know if there was any physical reason that the Greek "elements" were associated with particular geometric shapes? - The Pi Day thing is great; I think I might get a shirt. - To what extent did your own path/work intersect the heydays of Bell Labs and notable people therefrom? - Did you ever use an Amiga computer? - With mobile devices we are basically going back to terminals. - I used to have a Silicon Graphics Indigo 2 sitting on my desk for AutoCAD and 3D modeling. Those were great machines and fun times! - Speaking of McCarthy and those days, do you think that sticking to s-expressions as opposed to m-expressions and Wolfram Language-style ones impeded Lisp's adoption historically?
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: What can you tell us about the next Wolfram Language release? What are you most excited to see added to the language? - Do you worry about the increasing appearance of incompetence in the world? - The version numbers do get fuzzy over time.... Are you thinking about using years instead? It would be clearer how old your version is.... - Any advice for autodidacts? How does one turn a personal curiosity or question about science into a structured project that can be published, as you often do? - Do you think AI will take away some human autonomy, ultimately making humans less intelligent overall as they rely on AI too much? - How do you think the patent system could be improved by AI? - I wonder if we will go through a cycle of trusting AI far too much for answers to our questions, and then when we get too much incorrect information we give up and move to a position of total distrust. Where do you think we will end up? - What has been your favorite place/country to visit? Is there someplace you have yet to visit that you would like to? - What is like starting one's first business? I'm just wondering because I don't personally know anyone who has a business. - On that topic, if you had to start an innovation-intensive business nowadays, requiring R&D before revenues, would you go the VC route or find ways to bootstrap it (and if so, how)? - Can AI systems be effectively applied to customer support roles, or is there too large of a security vulnerability? - Can you elaborate on your experience expanding your business and products to be used by others whose language(s) you don't speak? - What's your favorite new revelation or idea you read in your recent deep dive into philosophy? - How often do you revisit your own personal goals in life and in your career? What are some things you look at that make you feel accomplished, whether small or big?
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-qa Questions include: What was more important to ancient civilizations, philosophy or science? - What have been your observations on the role of history in current science and research? Is it still relevant, or are we advancing fast enough to make it irrelevant? - Can you tell us about the history of the Wolfram Summer School? How did it start? - What is the history of formal verification in computer security? Particularly, how is it related to automated theorem proving and symbolic computation? Do people use Wolfram Language for formal verification? - Would you consider using one AI to formally verify software now? - What are some examples of scientific/technological "dead ends" other than alchemy (although I suppose we did learn things by accident with that one)? - What about Pythagoras? Philosophy or science? - Do we have enough information to answer this question (philosophy vs. science) for ancient South and Middle American civilizations?
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 do businesses adapt to changing technology? Are there existing strategies to combat roadblocks in development? - Is Wolfram Language much faster today than it was 35 years ago? - What has been the biggest or most notable technological advancement in your lifetime? - How do you think about the "buy" vs. "build" dilemma–notably for one so opinionated and driven to have it one's way as yourself, as opposed to being more compromising? - How do you think about and handle competition, be it business or technological competition (say LLMs vs. the Wolfram Language symbolic approach)? - Do you think having middle management in high-tech companies hinders innovation? - You just mentioned that someone can't build something that took 30 years to build. Do you think that will change with AI advancing enough to cut build timeframes by orders of magnitude? - Speaking of that area, what innovation and business lessons can be learned from Thinking Machines and such failed ventures? - Do you agree that technology is brimming with ideas and resources, many of which are free? This shift has transformed business approaches, with today's opportunities primarily centered around services. - I appreciate your approach to making software easy to use. I've used Oracle, SAP and JD Edwards ERP software and so much of it is overly complicated. We were tethered to them for support. - Any advice on starting a career in tech with everything moving at such a fast pace? - I've read about your endeavors, from writing books at 13 to earning a PhD at 20. How did you manage such accomplishments and cultivate the imagination needed for complex topics?
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.
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: Do you think a PhD is worth it when you are later in your career? Or should you just self-learn if you can? - As far as managing life, what has been your biggest takeaway in your career/personal life that you would like to pass on to the younger generation? - How do you approach risk-taking in business, and what advice would you give to aspiring entrepreneurs about managing risk? - Do you have any New Year's resolutions/big plans for 2024? - I am a software engineer, and the field of quant + data science is very appealing to me. What advice do you have? - I teach my first class tomorrow—what advice do you have? Do you have any advice on pricing software licences? - I build bespoke design software and I'm kind of winging the licences. What do you think of subscription vs. one-time purchase for software? - Imagine Mathematica with inline YouTube ads! - What is the coolest thing your company has ever done? - How much computational thinking and modeling do you do on the business itself, both for decision making and planning? - Do you consider yourself a celebrity? -What has been your coolest encounter/weirdest encounter? - What do you think about organic education matters? Basically, can you use AI to figure out a fixed point for education (what you want to understand) vs. testing for knowledge? - Can you ski? - Can you picture AI creating an alternative legal system? - I'm wondering how you imagine your symbolic language might interface with AI. I'm not sure about the implementation, but on a surface level, Wolfram Language feels closer to interfacing with an AI than text-based languages. - Your mother was a major anthropologist and philosopher. Has she had any impact on you? - It would be cool to live in that future where you talk to your AI in your house and it does things for you. - When talking to ChatGPT, I ask politely and say thank you—way more than I should, too. Uncanny valley and all that! (Plus being Canadian, maybe.) - Do you think there is harm in always learning? I think humans aren't built to be putting so much demand for energy on our brains. But darn, it feels good to learn! - Would you want yourself to be automated, so that you would no longer need to exist? How far would you want yourself automated?
The Creative Process in 10 minutes or less · Arts, Culture & Society
“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
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: Which do you think is more likely, teleportation or time travel? - I'm curious about accurately reconstructing the past using present data. Imagine a pool table where we can trace ball trajectories backward from current positions and vectors. If this works for a simple model, could we apply it to reality, tracing back to the very first moments of the universe? This could be like a "playback" of history. Do you think it's feasible with sufficient data, advanced computation and AI assistance, or are there insurmountable challenges? What ethical considerations might this raise? - We are definitely generating a germ factory on our keyboards and mice. We should use it. - "There is one more way to get from one place to another." This is what gravitational lensing is when light travels on multiple paths to us, right? - At this level, wouldn't there be some ambiguity, e.g. many different possible motions of molecules would produce the same pattern on sand? - Weren't there recently studies from MIT that were able to make hash collisions on purpose? - Will a web browser ever have a native runtime for a language other than JavaScript, e.g. Python, Wolfram Language, etc.? - It worries me, letting a user space code run into kernel space directly. - Is LLM the wrong direction for AI?
O Hipsters: Fora de Controle é o podcast da Alura com notícias sobre Inteligência Artificial aplicada e todo esse novo mundo no qual estamos começando a engatinhar, e que você vai poder explorar conosco! Para comemorar 1 ano do lançamento do podcast, conversamos com Stephen Wolfram, um dos cientistas da computação mais renomados do mundo, responsável pelo desenvolvimento da Wolfram Language e do Wolfram Alpha. Durante o papo, conversamos sobre as possibilidades que o ChatGPT abriu para interações com a Wolfram Language, sobre a importância de se aprender e praticar o pensamento computacional, e sobre a pergunta que não quer calar: o futuro é open source, ou aberto? Vem ver quem participou desse papo: Marcus Mendes, host fora de controle Fabrício Carraro, Program Manager da Alura, autor de IA e host do podcast Dev Sem Fronteiras Guilherme Silveira, CINO e co-fundador da Alura Roberta Arcoverde, Diretora de Engenharia na Stack Overflow Stephen Wolfram, cientista da computação e criador da Wolfram Language
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: Just saw your new blog about Ed Fredkin–what an interesting read! What was writing the blog like? Do you enjoy these more biographical pieces vs. more purely technical pieces you've written? - When you first created Wolfram Language and the other products around it (Mathematica), how did you develop a team of engineers/scientists to work on building your vision? - Any advice for students returning to school in the coming weeks? - Any advice regarding trying to promote technology "from the future"? - I really would like to program, but I feel like I need to grasp every concept before moving forward. Should I give up? It seems like there's always something I don't know, and sometimes others can't explain it, either. Do you deal with this? Any tips? - Do you think it's harder to kick-start a business today than it was 40 years ago? - Agree: Finance, especially quantitative finance, is a black hole for talent/smart minds. - Picking a major that determines your life/career at 18 seems daunting. What advice do you have? I worry about picking something and regretting it later, or feeling like I've wasted my time if I decide to change my major after a year or two. - Some industries just squeeze the juice out of bright young people until there's nothing left and you're replaced: finance, consulting, law, advertising, etc. How do you avoid this? - Regarding: Picking a major that determines your life/career at 18 seems daunting. What advice do you have? I worry about picking something and regretting it later, or feeling like I've wasted my time if I decide to change my major after a year or two. - What do you think is the best way to organize creative work? Personally, I don't think much of creative work is possible to formulate in a step-by-step plan off the bat. - I envy cats with their 18–20 hours/day of sleep. - If you are running a business, is it necessary to have the knowledge or ability to run any aspect of that business yourself, or can you rely on people to run those areas for you? - If you read books, you get better at reading books. If you program, you get better at programming. If you program with a book next to you, you get better at finding relevant examples in that book. But you don't learn to program by reading a book. - Do you think philosophy is still relevant in all these areas? - How would you deal with falling down the recursive rabbit hole too much? Because this makes learning about a specific subject extremely slow. - What do you make of company governance? Is there a "best way to set up a company board" etc.? - I'm really curious on your thoughts about these UAPs as a leader in your field. What is your opinion on what's going on?
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
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
Dr. Stephen Wolfram is a physicist and founder of Wolfram Research Inc. (creator of Wolfram Alpha, Mathematica, and the Wolfram Language). He is also recognized as the author of "A New Kind of Science," a groundbreaking work exploring computational systems and their implications in the natural world. In our conversation, we discuss: The story of starting Wolfram Research Why he decided to bootstrap the company Lessons learned on people management and leadership How Stephen thinks about product design, and decision making framework Thinking in first principles Artificial Intelligence: thoughts on when AGI could arrive How AI will continue to shape society What skillsets people should be developing NOW to be successful in the future Stephen's relationship with money and what it means to him How to increase the chances that you'll be wealthy and much more Learn more about Stephen: Website: https://www.stephenwolfram.com/ Twitter: https://twitter.com/stephen_wolfram If you enjoy the podcast, would you please consider leaving a short review on Apple Podcasts/iTunes and a rating on our Spotify show? It takes less than 60 seconds, and it really makes a difference. Past guests on Growth Minds include: Robert Kiyosaki (Rich Dad Poor Dad), Steve Aoki, Robert Greene, Dr. Jason Fung, Dr. Steven Gundry, Neil deGrasse Tyson, Dennis Rodman, Wim Hof, Robin Sharma, Vanessa Van Edwards, King Bach, Daniel Pink, Dr. William Davis, Doctor Mike, Lewis Howes (School of Greatness), Tom Bilyeu (Impact Theory), Andrew Yang, Dr. Paul Conti, Charles Hoskinson (Ethereum), Dr. Drew (After Dark), Jo Koy, Jordan Belfort (Wolf of Wall Street), Gad Saad, Adam Carolla, Louis the Child, Vishen Lakhiani (Mindvalley), Bret Weinstein (DarkHorse Podcast), James Nestor, Dave Rubin, Scott Adams (Real Coffee with Scott Adams), and more.
Stephen Wolfram answers questions from his viewers about the history science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Please discuss the history of graph theory and network theory. What was the role of computation? - So graph theory evolved as a theory after practice, like thermodynamics and the steam engine? - Graphs as knowledge representation were popular in AI the late 60s, and more formally in theoretical CS a decade later. - Was it a big effort to integrate graphs in Wolfram Language? Is it missing some part of the recent developments? - Has anyone formulated Zermelo-Fraenkel set theory in terms of graph theory? - At what point in history did mathematics reach a level where a single individual could no longer learn all "known knowledge" at that time within their lifetime? - It seems too often amazing discoveries go years without being picked up by a particular community. - If Aristotle were alive today, how might he describe modern technology? How would one explain modern technology to someone from Aristotle's time? - Would you say the words "soul" or "spirit" were used in the past in much the same way we use the term "software" today? - Why would cellphones be inconceivable? They work the same way speech does. The only difference is that the ancients didn't know about the electromagnetic field. - In your own experience, have there been any major changes to a field of study that changed the way one would view a certain topic? I remember being in school studying astronomy when Pluto was declared to no longer be a planet and my professor's lesson plan had to adapt in an instant. - I like pondering what Professor Einstein may have been able to do with Wolfram|Alpha.
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Steven Wolfram on AI Alignment, published by Bill Benzon on August 21, 2023 on LessWrong. Joe Walker has a general conversation with Wolfram about his work and things and stuff, but there are some remarks about AI alignment at the very end: WALKER: Okay, interesting. So moving finally to AI, many people worry about unaligned artificial general intelligence, and I think it's a risk we should take seriously. But computational irreducibility must imply that a mathematical definition of alignment is impossible, right? WOLFRAM: Yes. There isn't a mathematical definition of what we want AIs to be like. The minimal thing we might say about AIs, about their alignment, is: let's have them be like people are. And then people immediately say, "No, we don't want them to be like people. People have all kinds of problems. We want them to be like people aspire to be. And at that point, you've fallen off the cliff. Because, what do people aspire to be? Well, different people aspire to be different and different cultures aspire in different ways. And I think the concept that there will be a perfect mathematical aspiration is just completely wrongheaded. It's just the wrong type of answer. The question of how we should be is a question that is a reflection back on us. There is no "this is the way we should be" imposed by mathematics. Humans have ethical beliefs that are a reflection of humanity. One of the things I realised recently is one of the things that's confusing about ethics is if you're used to doing science, you say, "Well, I'm going to separate a piece of the system," and I'm going to say, "I'm going to study this particular subsystem. I'm going to figure out exactly what happens in the subsystem. Everything else is irrelevant." But in ethics, you can never do that. So you imagine you're doing one of these trolley problem things. You got to decide whether you're going to kill the three giraffes or the eighteen llamas. And which one is it going to be? Well, then you realise to really answer that question to the best ability of humanity, you're looking at the tentacles of the religious beliefs of the tribe in Africa that deals with giraffes, and this kind of thing that was the consequence of the llama for its wool that went in this supply chain, and all this kind of thing. In other words, one of the problems with ethics is it doesn't have the separability that we've been used to in science. In other words, it necessarily pulls in everything, and we don't get to say, "There's this micro ethics for this particular thing; we can solve ethics for this thing without the broader picture of ethics outside." If you say, "I'm going to make this system of laws, and I'm going to make the system of constraints on AIs, and that means I know everything that's going to happen," well, no, you don't. There will always be an unexpected consequence. There will always be this thing that spurts out and isn't what you expected to have happen, because there's this irreducibility, this kind of inexorable computational process that you can't readily predict. The idea that we're going to have a prescriptive collection of principles for AIs, and we're going to be able to say, "This is enough, that's everything we need to constrain the AIs in the way we want," it's just not going to happen that way. It just can't happen that way. Something I've been thinking about recently is, so what the heck do we actually do? I was realising this. We have this connection to ChatGPT, for example, and I was thinking now it can write Wolfram Language code, I can actually run that code on my computer. And right there at the moment where I'm going to press the button that says, "Okay, LLM, whatever code you write, it's going to run on my computer," I'm like, "That's probably a bad idea," because, I don't know, it's going ...
Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Steven Wolfram on AI Alignment, published by Bill Benzon on August 21, 2023 on LessWrong.Joe Walker has a general conversation with Wolfram about his work and things and stuff, but there are some remarks about AI alignment at the very end:WALKER: Okay, interesting. So moving finally to AI, many people worry about unaligned artificial general intelligence, and I think it's a risk we should take seriously. But computational irreducibility must imply that a mathematical definition of alignment is impossible, right?WOLFRAM: Yes. There isn't a mathematical definition of what we want AIs to be like. The minimal thing we might say about AIs, about their alignment, is: let's have them be like people are. And then people immediately say, "No, we don't want them to be like people. People have all kinds of problems. We want them to be like people aspire to be.And at that point, you've fallen off the cliff. Because, what do people aspire to be? Well, different people aspire to be different and different cultures aspire in different ways. And I think the concept that there will be a perfect mathematical aspiration is just completely wrongheaded. It's just the wrong type of answer.The question of how we should be is a question that is a reflection back on us. There is no "this is the way we should be" imposed by mathematics.Humans have ethical beliefs that are a reflection of humanity. One of the things I realised recently is one of the things that's confusing about ethics is if you're used to doing science, you say, "Well, I'm going to separate a piece of the system," and I'm going to say, "I'm going to study this particular subsystem. I'm going to figure out exactly what happens in the subsystem. Everything else is irrelevant."But in ethics, you can never do that. So you imagine you're doing one of these trolley problem things. You got to decide whether you're going to kill the three giraffes or the eighteen llamas. And which one is it going to be?Well, then you realise to really answer that question to the best ability of humanity, you're looking at the tentacles of the religious beliefs of the tribe in Africa that deals with giraffes, and this kind of thing that was the consequence of the llama for its wool that went in this supply chain, and all this kind of thing.In other words, one of the problems with ethics is it doesn't have the separability that we've been used to in science. In other words, it necessarily pulls in everything, and we don't get to say, "There's this micro ethics for this particular thing; we can solve ethics for this thing without the broader picture of ethics outside."If you say, "I'm going to make this system of laws, and I'm going to make the system of constraints on AIs, and that means I know everything that's going to happen," well, no, you don't. There will always be an unexpected consequence. There will always be this thing that spurts out and isn't what you expected to have happen, because there's this irreducibility, this kind of inexorable computational process that you can't readily predict.The idea that we're going to have a prescriptive collection of principles for AIs, and we're going to be able to say, "This is enough, that's everything we need to constrain the AIs in the way we want," it's just not going to happen that way. It just can't happen that way.Something I've been thinking about recently is, so what the heck do we actually do? I was realising this. We have this connection to ChatGPT, for example, and I was thinking now it can write Wolfram Language code, I can actually run that code on my computer. And right there at the moment where I'm going to press the button that says, "Okay, LLM, whatever code you write, it's going to run on my computer," I'm like, "That's probably a bad idea," because, I don't know, it's going ...
Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Steven Wolfram on AI Alignment, published by Bill Benzon on August 21, 2023 on LessWrong. Joe Walker has a general conversation with Wolfram about his work and things and stuff, but there are some remarks about AI alignment at the very end: WALKER: Okay, interesting. So moving finally to AI, many people worry about unaligned artificial general intelligence, and I think it's a risk we should take seriously. But computational irreducibility must imply that a mathematical definition of alignment is impossible, right? WOLFRAM: Yes. There isn't a mathematical definition of what we want AIs to be like. The minimal thing we might say about AIs, about their alignment, is: let's have them be like people are. And then people immediately say, "No, we don't want them to be like people. People have all kinds of problems. We want them to be like people aspire to be. And at that point, you've fallen off the cliff. Because, what do people aspire to be? Well, different people aspire to be different and different cultures aspire in different ways. And I think the concept that there will be a perfect mathematical aspiration is just completely wrongheaded. It's just the wrong type of answer. The question of how we should be is a question that is a reflection back on us. There is no "this is the way we should be" imposed by mathematics. Humans have ethical beliefs that are a reflection of humanity. One of the things I realised recently is one of the things that's confusing about ethics is if you're used to doing science, you say, "Well, I'm going to separate a piece of the system," and I'm going to say, "I'm going to study this particular subsystem. I'm going to figure out exactly what happens in the subsystem. Everything else is irrelevant." But in ethics, you can never do that. So you imagine you're doing one of these trolley problem things. You got to decide whether you're going to kill the three giraffes or the eighteen llamas. And which one is it going to be? Well, then you realise to really answer that question to the best ability of humanity, you're looking at the tentacles of the religious beliefs of the tribe in Africa that deals with giraffes, and this kind of thing that was the consequence of the llama for its wool that went in this supply chain, and all this kind of thing. In other words, one of the problems with ethics is it doesn't have the separability that we've been used to in science. In other words, it necessarily pulls in everything, and we don't get to say, "There's this micro ethics for this particular thing; we can solve ethics for this thing without the broader picture of ethics outside." If you say, "I'm going to make this system of laws, and I'm going to make the system of constraints on AIs, and that means I know everything that's going to happen," well, no, you don't. There will always be an unexpected consequence. There will always be this thing that spurts out and isn't what you expected to have happen, because there's this irreducibility, this kind of inexorable computational process that you can't readily predict. The idea that we're going to have a prescriptive collection of principles for AIs, and we're going to be able to say, "This is enough, that's everything we need to constrain the AIs in the way we want," it's just not going to happen that way. It just can't happen that way. Something I've been thinking about recently is, so what the heck do we actually do? I was realising this. We have this connection to ChatGPT, for example, and I was thinking now it can write Wolfram Language code, I can actually run that code on my computer. And right there at the moment where I'm going to press the button that says, "Okay, LLM, whatever code you write, it's going to run on my computer," I'm like, "That's probably a bad idea," because, I don't know, it's going ...
Please check out Numerai - our sponsor @ http://numer.ai/mlst Patreon: https://www.patreon.com/mlst Discord: https://discord.gg/ESrGqhf5CB The Second Law: Resolving the Mystery of the Second Law of Thermodynamics Buy Stephen's book here - https://tinyurl.com/2jj2t9wa The Language Game: How Improvisation Created Language and Changed the World by Morten H. Christiansen and Nick Chater Buy here: https://tinyurl.com/35bvs8be Stephen Wolfram starts by discussing the second law of thermodynamics - the idea that entropy, or disorder, tends to increase over time. He talks about how this law seems intuitively true, but has been difficult to prove. Wolfram outlines his decades-long quest to fully understand the second law, including failed early attempts to simulate particles mixing as a 12-year-old. He explains how irreversibility arises from the computational irreducibility of underlying physical processes coupled with our limited ability as observers to do the computations needed to "decrypt" the microscopic details. The conversation then shifts to discussing language and how concepts allow us to communicate shared ideas between minds positioned in different parts of "rule space." Wolfram talks about the successes and limitations of using large language models to generate Wolfram Language code from natural language prompts. He sees it as a useful tool for getting started programming, but one still needs human refinement. The final part of the conversation focuses on AI safety and governance. Wolfram notes uncontrolled actuation is where things can go wrong with AI systems. He discusses whether AI agents could have intrinsic experiences and goals, how we might build trust networks between AIs, and that managing a system of many AIs may be easier than a single AI. Wolfram emphasizes the need for more philosophical depth in thinking about AI aims, and draws connections between potential solutions and his work on computational irreducibility and physics. Show notes: https://docs.google.com/document/d/1hXNHtvv8KDR7PxCfMh9xOiDFhU3SVDW8ijyxeTq9LHo/edit?usp=sharing Pod version: TBA https://twitter.com/stephen_wolfram TOC: 00:00:00 - Introduction 00:02:34 - Second law book 00:14:01 - Reversibility / entropy / observers / equivalence 00:34:22 - Concepts/language in the ruliad 00:49:04 - Comparison to free energy principle 00:53:58 - ChatGPT / Wolfram / Language 01:00:17 - AI risk Panel: Dr. Tim Scarfe @ecsquendor / Dr. Keith Duggar @DoctorDuggar
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 do you prepare for your keynote talks about new technologies and Wolfram Language features? - What barriers currently still exist that keep AR/VR from being widely useful in the workplace? - One thing I genuinely appreciate about Stephen is his obvious incredible delight when explaining concepts, particularly related to science. Does he ever have to force it? - Do you take part in clinical trials? - Diagnosing is definitely a potential job for AI. - Can Wolfram Language screen for diseases or illnesses? - Is it possible to change human DNA by intention, I mean eating foods or taking medicine? - Do you try to convince your children to go to specific universities/schools, or do they decide by themself without any impact from you? - Multiple screens are nice but I feel it's less productive sometimes. Sort of the same thing as multitasking being a myth. - I feel like I am someone who has a lot of interests. I did my engineering degree a decade ago but I want to study mathematics, physics, philosophy and neuroscience too. Have you also been someone with diverse interests? If so, how do you manage them? I feel like I struggle with wanting to learn so much more—I feel like its a lot better to be focused and simple minded. - Any tips for fixing a chaotic filesystem? My files are scattered everywhere. - What do you do when you feel like you're stuck in the mud and can't get out? - How do you write? - How much do you use the mouse while writing in a notebook? - Do you have any preferences in reading hard copy vs digital? - You should have an automatic email word cloud generator. - Does UV hurt the paper? - Physical books are heavy and bulky, while ebooks are never bigger than your favorite tablet! - What is the oldest book you own? - Do you think storage devices like tapes and punch-cards might come back sometime?
In this thought-provoking podcast episode, we discuss the mysteries surrounding Large Language Models (LLMs) and their implications for the future of artificial intelligence (AI) with Stephen Wolfram, creator of Mathematica, Wolfram | Alpha & Wolfram Language. We dive into the fascinating world of Large Language Models (LLMs) and their surprising capabilities. He also discusses the underlying scientific principles behind LLMs, including the concept of computational irreducibility, and how they function as probabilistic sentence finishers. Wolfram reflects on the potential applications of LLMs in computational contracts and the challenges of aligning AI systems with human aspirations. As the conversation delves into the future of AI governance, Wolfram explores the complexities of regulating AI and the importance of finding a balance between human intervention and autonomous decision-making. This episode offers a captivating exploration of the evolving landscape of AI and its impact on various industries and job roles. If you enjoy the podcast, please follow us on Spotify and rate us 5 stars on Apple Podcasts. Socials Stephen Wolfram Stephen Wolfram's Website Tommy's Twitter Follow Delphi Digital Subscribe to Delphi Digital: https://members.delphidigital.io/home Twitter: https://twitter.com/Delphi_Digital YouTube: https://youtube.com/@Delphi_Digital Disclosures: This conversation is for informational purposes only and does not constitute legal or investment advice. Actual results may vary materially from any forward looking statements made and are subject to risks and uncertainties. This podcast is not investment advice. Do not buy or sell tokens based off this episode.
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 much time do you spend on building Wolfram Language vs. doing research on the Physics Project? And what are the pros and cons of doing both things? - When working on something new, how do you know if you're making progress? Have you had stretches of time when you were exploring something, but it turned out that you weren't making much progress? - How do you choose whether to throw a project in the trash or not? Sometimes you invest so much of yourself in something that it feels just impossible to do so. - What tools, practices and/or policies can be implemented to mitigate the effects of reduced attention span and memory from social media use (and short-form content in general)? - When you code, do you apply a test-driven design approach, or do you enjoy a more exploratory approach? - What's "a day in the life of Stephen Wolfram" look like these days? - With so much email, how do you bucket your email? Have you been running it through a rules engine of your own design? - Why do so many companies prove such easy targets for hackers? Is robust security really so hard? - Any future interviews of any public physicists, mathematicians, etc. coming soon? - Do you take notes of things you learn? What's the system that you use for managing new information (when researching or learning new things)? - What is your opinion on solo work vs. group work and how it impacts the legacy of a product that has tangible and intangible business products? - How do you identify great developers? Do you test developers, be that with code or psychometrics, as part of the hiring process, or do you prefer to rely on conversation? - Any philosophy book or article you recommend reading?
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.
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: Have you ever owned a pet? Is there any animal you've ever wanted as a pet, even if it wasn't a typical one, like a Komodo dragon? - Fall weather is here! Is there a season or time of year where you are more/less productive as an effect of the weather? - I went swimming today-about 100x better than walking. - I've only come across one joke in the Wolfram Language documentation, but I did find it quite funny and in good taste. Based on context, I think Jonathan Gorard wrote it. What do you make of this? - What is your history with/view on science fiction (books, movies, etc.)? - How important it is to save money vs. to spend it? How do you understand on what things it is worth spending money? - Well, I quit smoking, so I'm using that money on the lottery instead. - When is a technology mature enough to be "trusted" (i.e. autonomous driving)? - What are your views on making very powerful and trained open-source AI models like Stable Diffusion illegal vs. allowing them to exist? "OpenAI" or open-source AI? - How do you feel about making your email address public as a famous person? - How did you originally generate funding to start your company? - How do you choose whether to throw a project in the trash or not? Sometimes you invest so much of yourself in something that it just feels impossible to do so. - What are general tips you have as far as educating people?
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
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
Stephen Wolfram answers general questions from his viewers about science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: As the Wolfram Language grows, will the number of lines of code ever shrink? What could cause such a trend? - Scientists are trying to elucidate the origins of life on Earth. The current focus is exploring the "RNA world." This occurred 4.5 billion years ago. Could there have been dimensional fluctuations back then? - Why are small children able to spin around so quickly without getting dizzy, while adults become nauseous? - Do we still need the appendix? Are there any parts in our body that we "evolved away"? - Is science getting harder? Are ideas getting harder to find? - Yes, the more we've learned, the more we've learned that there's a lot more to learn! - How ironic then, that Albert Einstein started his revolution in physics while working in a patent office! - One thing that interests me is predicting what the future will look like (Alan Turing predicted computers would be capable of playing chess 50 years from when he said that, and sure enough, by 1997 they were able to do so).
Stephen Wolfram answers questions from his viewers about the history science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Do you think we'll ever get to the stage of having flying cars? Is there any historical evidence? - Even now with traction control, anti-lock braking systems, automatic crash avoidance and the like, driving cars has automated "smart" safeguards nowadays. - It seems like many science discoveries or inventions happen due to some mistake or error that ultimately makes the insight or experiment work. How prevalent is this? - Can you talk a little bit about the history of automated theorem proving? Do you think we are on the cusp of an era when computers will be proving theorems and mathematicians will interpret them? - I think one interesting question would be to flip that around: could one use theorem-proving algos to figure out why black-box neural nets do what they do? - Will artificial general intelligence be the future of automation or a symbolic language like the Wolfram Language? - I think the computational mathematics system of the future will be generating new languages, new notations, new proofs, new theorems and new conjectures. - Artificial intelligence is an effort to create electronic learning. Not human thinking. A self-learning program will not develop human-like emotions. It has no physiological needs, and it has no need to fear. It can be replicated, it can be backed up, it can be turned off and on.
HUGE ANNOUNCEMENT, CHATGPT+WOLFRAM! You saw it HERE first! YT version: https://youtu.be/z5WZhCBRDpU Support us! https://www.patreon.com/mlst MLST Discord: https://discord.gg/aNPkGUQtc5 Stephen's announcement post: https://writings.stephenwolfram.com/2023/03/chatgpt-gets-its-wolfram-superpowers/ OpenAI's announcement post: https://openai.com/blog/chatgpt-plugins In an era of technology and innovation, few individuals have left as indelible a mark on the fabric of modern science as our esteemed guest, Dr. Steven Wolfram. Dr. Wolfram is a renowned polymath who has made significant contributions to the fields of physics, computer science, and mathematics. A prodigious young man too, Wolfram earned a Ph.D. in theoretical physics from the California Institute of Technology by the age of 20. He became the youngest recipient of the prestigious MacArthur Fellowship at the age of 21. Wolfram's groundbreaking computational tool, Mathematica, was launched in 1988 and has become a cornerstone for researchers and innovators worldwide. In 2002, he published "A New Kind of Science," a paradigm-shifting work that explores the foundations of science through the lens of computational systems. In 2009, Wolfram created Wolfram Alpha, a computational knowledge engine utilized by millions of users worldwide. His current focus is on the Wolfram Language, a powerful programming language designed to democratize access to cutting-edge technology. Wolfram's numerous accolades include honorary doctorates and fellowships from prestigious institutions. As an influential thinker, Dr. Wolfram has dedicated his life to unraveling the mysteries of the universe and making computation accessible to all. First of all... we have an announcement to make, you heard it FIRST here on MLST! .... Intro [00:00:00] Big announcement! Wolfram + ChatGPT! [00:02:57] What does it mean to understand? [00:05:33] Feeding information back into the model [00:13:48] Semantics and cognitive categories [00:20:09] Navigating the ruliad [00:23:50] Computational irreducibility [00:31:39] Conceivability and interestingness [00:38:43] Human intelligible sciences [00:43:43]
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: If you could live anywhere in the world, where would it be? Any business/scientific reason why that place? - University vs. experience in programming and computer science: which one is more valuable? - How do you manage technical debt? - What advantages come from using Wolfram Language as in-house code? - How do you manage technical debt in Java codebases? - Good afternoon, Dr. Wolfram. How do you cope with the stress of releasing new products? As it is very hard to judge the success beforehand, do you have any techniques to reduce that stress? - If you were never allowed to use Wolfram Language, what would you use? - Do you find that innovation is largely driven from within, or is it largely external (e.g. your users push you for more features)? - How does Stephen see the current co-creation space and how can we bring the benefits to smaller businesses with smaller budgets? - What is the best way to fund a research project? - Would you always have to artificially describe some midterm future application of your research to sell a business plan to some investors?
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.
Valentine's Day is coming up, and Lexman is looking for a special someone to spend it with. He interviews Stephen Wolfram, creator of the Wolfram Language, about gravitons and how they might play a role in love.
A conversation with Stephen Wolfram. Books: A Project to Find the Fundamental Theory of Physics: https://www.wolfram-media.com/products/a-project-to-find-the-fundamental-theory-of-physics.html A New Kind of Science: https://www.wolframscience.com/nks/ The Physics Project: https://www.wolframphysics.org 00:00:00 Introduction 00:01:11 Looking at Stephen Wolfram's Educational journey 00:05:39 Things learnt in school are actually useful! 00:06:34 Particle Physics and Stephen's early years 00:11:39 Stephen Wolfram's first paper 00:16:19 Using computers for algebraic calculations 00:22:00 Launching his own company 00:23:00 Starting to study cellular automata 00:26:30 The importance of using technology to help advance physics 00:28:14 The advice Stephen would give to his teenage self 00:30:00 The importance of choosing the right problems 00:35:44 Stephen's views on ‘modern' physics 00:38:21 Ruliology and A New Kind of Science 00:40:56 Working on a generalisation of calculus? 00:45:16 Applying learnings from the Physics Project to other fields such as Mathematics, Chemistry, Biology and Economics 00:50:00 Physics as a remarkable export field 00:54:24 History of tools to describe the universe 00:55:17 Computation as a very general paradigm & Wolfram Language 01:00:12 Wolfram Summer Camp 01:02:40 The possibility of a special relativity of economics 01:06:21 Live streaming and open source nature of the Physics Project 01:09:18 The concept of the Ruliad 01:15:28 Taking measurements and moving through Ruliad Space? 01:22:00 Quantum mechanics and relatively - a beautiful symmetry 01:34:00 Thank you and goodbye
In this episode of the Origins Podcast, Stephen Wolfram joins Lawrence Krauss for a fascinating conversation around Stephen's upbringing, his education path, Mathematica, and what he's working on now. They also cover various concepts around symbolic manipulation and the importance of knowing how to type. 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.
Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas
It's not easy, figuring out the fundamental laws of physics. It's even harder when your chosen methodology is to essentially start from scratch, positing a simple underlying system and a simple set of rules for it, and hope that everything we know about the world somehow pops out. That's the project being undertaken by Stephen Wolfram and his collaborators, who are working with a kind of discrete system called “hypergraphs.” We talk about what the basic ideas are, why one would choose this particular angle of attack on fundamental physics, and how ideas like quantum mechanics and general relativity might emerge from this simple framework.Support Mindscape on Patreon.Stephen Wolfram received his Ph.D. in physics from Caltech. He is the founder and CEO of Wolfram Research, and the creator of Mathematica, Wolfram|Alpha, and the Wolfram Language. Among his awards are a MacArthur Fellowship. Among his books is A New Kind of Science. He recently launched the Wolfram Physics Project.Web siteWolfram ResearchTalk on Computation and Fundamental PhysicsAmazon.com author pageWikipediaTwitterSee Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.
Education On Fire - Sharing creative and inspiring learning in our schools
Conrad Wolfram – Strategic Director and European CEO/Co-Founder, Wolfram Research Conrad Wolfram, physicist, mathematician and technologist, is Strategic Director and European Co-Founder/CEO of Wolfram - the “math company” behind Mathematica, Wolfram Language and Wolfram|Alpha (which powers knowledge answers for Apple's Siri) for over 30 years. Wolfram pioneers new approaches to data science and computation-based development, with technology and consulting solutions that drive innovation in analytics, software development and modelling. Working with start-ups to Fortune 500 companies, it spans industries as diverse as medicine, finance and telecoms. Conrad is recognised as a thought leader in AI, data science and computation, pioneering a multiparadigm data science approach. Conrad is also a leading advocate for a fundamental shift of math education to become computer-based or alternatively introduce a new core subject of computational thinking. He founded https://www.computerbasedmath.org/ (computerbasedmath.org) and computationalthinking.org to fundamentally fix math education for the AI age - rebuilding the curriculum assuming computers exist. The movement is now a worldwide force in re-engineering the STEM curriculum. His groundbreaking book https://www.wolfram-media.com/products/the-maths-fix.html ('The Math(s) Fix) - an education blueprint for the AI age' www.themathsfix.org was released on 10th June 2020 Conrad regularly appears in the media to talk about subjects ranging from decisions and data science to 21st century education. He attended Eton College and holds degrees in Natural Sciences and Math from the University of Cambridge. http://www.conradwolfram.com (www.conradwolfram.com) If you would like to support the Education on Fire GoFundMe campaign to create a valuable resource for our children based on the wisdom of our inspiring guests please click below. https://uk.gofundme.com/f/education-on-fire-book-fundraiser (https://uk.gofundme.com/f/education-on-fire-book-fundraiser) Show Sponsor The National Association for Primary Education has an online conference on 8th March 2021 entitled: https://nape.org.uk/conference (TOWARDS A BALANCED AND BROADLY-BASED CURRICULUM) Virtual Conference – Monday 8th March 2021, 4.15pm-6.45pmThe Conference, embracing a theme which has always been central to debate about children’s entitlements, has been highlighted by OfSTED as critical in curriculum development and its central importance has been further accentuated by the pressures under which primary schools are working in the post-lockdown phase as they prioritise what is perceived as essential in educational recovery. The impact of the coronavirus pandemic on children’s education may be perceived as a justification for narrowing the curriculum at the expense of the arts and the humanities, but this conference will explore the case for preserving young children’s entitlement to as rich and diverse a curriculum as possible. Dr. Eaude’s keynote lecture will set the scene, highlighting some key issues and considering some lessons to be learnt from the period of lockdown. The subsequent presentations will focus on classroom practice, providing a spotlight on innovations which have been implemented in school and offering guidance for the future. All are most welcome at this event, including teachers, teacher assistants, governors and students and it’s our hope that the conference will play its part in bringing together a range of stakeholders in primary education, all with a commitment to enhancing children’s entitlement to a balanced and broadly-based curriculum. To book or find out more https://nape.org.uk/conference (https://nape.org.uk/conference) Support this podcast
Stephen Wolfram is a British-American computer scientist, theoretical physicist, and businessman. He is also known for his work in mathematics. In 2012, he was named an inaugural fellow of the American Mathematical Society. In this episode of the InfoQ podcast Charles Humble talks to him about Wolfram Language, its origins and the influences on its creation. In a wide-ranging discussion they also cover the ergonomics of programming languages; Wolfram|Alpha’s integration with Siri, Alexa, and the upcoming integration with Microsoft Excel; how ideas from physics, such as reference frames, may be useful for distributed systems programming; and live streaming language design discussions via Twitch. Listen to the podcast for more. Curated transcript and more information on the https://bit.ly/32F7RtR Follow us on Facebook, Twitter, LinkedIn, Youtube: @InfoQ Follow us on Instagram: @infoqdotcom Stay informed on emerging trends, peer-validated early adoption of technologies, and architectural best practices. Subscribe to The Software Architects’ Newsletter: www.infoq.com/software-architects-newsletter/
Wolf Tivy and Ash Milton talk with Stephen Wolfram about the role institutions play in generating intellectual progress in science, as well as his development of a new computational paradigm for understanding fundamental physics. 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.
Welcome to another episode of Develomentor. Today's guest is 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. Stephen is shaping the future of computing every day.Over the course of more than four decades, he has been a pioneer in the development and application of computational thinking. He has been responsible for many discoveries, inventions and innovations in science, technology and business.(https://www.stephenwolfram.com)If you are enjoying our content please leave us a rating and review or consider supporting usQuotes“Most of science is incremental. But there are these rare moments when fields of science have this explosion of activity and there’s tons of low hanging fruit to be picked.”“We’re trying to raise the level of how computation can be used by a much broader range of people and its working!”“The idea that space and time are the same kind of thing is basically wrong. It was a sort of mathematical gloss on top of Einsteins theory of relativity. The mathematics works on nicely, but on the conceptual level it’s the wrong way to go.”—Stephen WolframAdditional ResourcesWolfram Alpha is a computational search engine and an incredible tool – https://www.wolframalpha.com/Listen to Guy Kawasaki interview Stephen Wolfram – https://podcasts.apple.com/us/podcast/guy-kawasakis-remarkable-people/id1483081827?i=1000459949118Stephen’s writings about his personal infrastructure –https://writings.stephenwolfram.com/2019/02/seeking-the-productive-life-some-details-of-my-personal-infrastructure/Check out Stephen’s book – A Project to Find the Fundamental Theory of Physics – https://www.wolfram-media.com/products/a-project-to-find-the-fundamental-theory-of-physics.htmlStephen Wolfram’s TED talk about Wolfram Alpha and the future of computingYou can find more resources in the show notesTo learn more about our podcast go to https://develomentor.com/To listen to previous episodes go to https://develomentor.com/blog/Connect with Stephen WolframLinkedInTwitterhttps://www.stephenwolfram.com/Follow DevelomentorTwitter: @develomentorConnect with Grant IngersollLinkedInTwitter
Stephen Wolfram is a scientist, physicist, and businessman best known for his work in computer science, mathematics, and theoretical physics. Over more than four decades, Wolfram has been a pioneer in the development and application of computational thinking—and has been responsible for many discoveries, inventions, and innovations. Based on both his practical and theoretical thinking, Wolfram has emerged as an authority on the implications of computation and artificial intelligence for society and the future, and the importance of computational language as a bridge between the capabilities of computation and human objectives. He is the creator of Mathematica, the creator of Wolfram|Alpha, and the founder and CEO of Wolfram Research. He is the author of Cellular Automata And Complexity, Adventures of a Computational Explorer, The Mathematica Book, How to Teach Computational Thinking, On the Quest for Computable Knowledge, A New Kind of Science, An Elementary Introduction to the Wolfram Language, and most recently, Idea Makers: Personal Perspectives on the Lives & Ideas of Some Notable People.
The mathematics curriculum of today was created before computers. Conrad Wolfram has written a book, The Math(s) Fix and how AI can be part of this process of learning new math. He says we're "making humans into third rate calculators instead of helping humans be problem solvers." He also argues that math should be approachable for everyone and we spend too much time in schools on the wrong tasks. We even talk about some of the charts and numbers shared during the covid19 health crisis and the need for critical thinking in every area of society. www.coolcatteacher.com/e680 Sponsor: Welcome TGR Foundation and Discovery Education as a sponsor to my podcast. For nearly 25 years, the TGR Foundation, a Tiger Woods Charity, visualized a world where opportunity is universal and potential is limitless. Their mission is to empower students to pursue their passions through education - instilling in them the strength and skills to persevere and define their own path. Their award-winning curricula has already reached more than one million students. Now in the age of COVID-19 the TGR Foundation and Discovery Education introduce the first module in a new series of no-cost digital professional learning resources, empowering educators with new strategies to support student success far beyond school campuses. The PD series provides every educator, especially those from under-resourced communities, the access and materials needed to transform teaching during COVID-19 and beyond. Check it out at coolcatteacher.com/tgr. Conrad Wolfram - Bio as Submitted Conrad Wolfram – Strategic Director and European CEO/Co-Founder, Wolfram Research Conrad Wolfram, physicist, mathematician and technologist, is Strategic Director and European Co-Founder/CEO of Wolfram - the “computation company” behind Mathematica, Wolfram Language and Wolfram|Alpha (which powers knowledge answers for Apple's Siri) for over 30 years. Wolfram pioneers new approaches to data science and computation-based development, with technology and consulting solutions that drive innovation in analytics, software development and modelling. Working with start-ups to Fortune 500 companies, it spans industries as diverse as medicine, finance and telecoms. Conrad is recognised as a thought leader in AI, data science and computation, pioneering a Multi-Paradigm data science approach. Conrad is also a leading advocate for a fundamental shift of maths education to become computer-based or alternatively introduce a new core subject of computational thinking. He founded computerbasedmath.org and computationalthinking.org to fundamentally fix maths education for the AI age - rebuilding the curriculum assuming computers exist. The movement is now a worldwide force in re-engineering the STEM curriculum. His groundbreaking book 'The Math(s) Fix - an education blueprint for the AI age' www.themathsfix.org is released on 10th June. Conrad regularly appears in the media to talk about subjects ranging from decisions and data science to 21st-century education. He attended Eton College and holds degrees in Natural Sciences and Maths from the University of Cambridge. Disclosure of Material Connection: This is a sponsored podcast episode. The company who sponsored it compensated me via cash payment, gift, or something else of value to include a reference to their product. Regardless, I only recommend products or services I believe will be good for my readers and are from companies I can recommend. I am disclosing this in accordance with the Federal Trade Commission 16 CFR, Part 255: "Guides Concerning the Use of Endorsements and Testimonials in Advertising."
STEPHEN WOLFRAM (https://www.edge.org/memberbio/stephen_wolfram) is a scientist, inventor, and the founder and CEO of Wolfram Research. He is the creator of the symbolic computation program Mathematica and its programming language, Wolfram Language, as well as the knowledge engine Wolfram|Alpha. His most recent endeavor is The Wolfram Physics Project. He is also the author, most recently, of A Project to Find the Fundamental Theory of Physics. The Conversation: https://www.edge.org/conversation/stephen_wolfram-computation-all-the-way-down
Stephen Wolfram is a computer scientist, mathematician, and theoretical physicist who is the founder and CEO of Wolfram Research, a company behind Mathematica, Wolfram Alpha, Wolfram Language, and the new Wolfram Physics project. He is the author of several books including A New Kind of Science, which on a personal note was one of the most influential books in my journey in computer science and artificial intelligence. Support this podcast by signing up with these sponsors: – ExpressVPN at https://www.expressvpn.com/lexpod – Cash App – use code “LexPodcast” and download: – Cash App (App Store): https://apple.co/2sPrUHe – Cash App (Google Play):
Stephen Wolfram is a computer scientist who designed Mathematica, Wolfram Alpha, and the Wolfram Language. He talks to Mikah Sargent about translating between human language, mathematics, and programming languages, how computational language works, and how he has spent his life trying to build computational intelligence up. Host: Mikah Sargent Guest: Stephen Wolfram Download or subscribe to this show at https://twit.tv/shows/triangulation. Sponsors: capterra.com/triangulation LastPass.com/twit
Stephen Wolfram is a computer scientist who designed Mathematica, Wolfram Alpha, and the Wolfram Language. He talks to Mikah Sargent about translating between human language, mathematics, and programming languages, how computational language works, and how he has spent his life trying to build computational intelligence up. Host: Mikah Sargent Guest: Stephen Wolfram Download or subscribe to this show at https://twit.tv/shows/triangulation. Sponsors: capterra.com/triangulation LastPass.com/twit
Stephen Wolfram is a computer scientist who designed Mathematica, Wolfram Alpha, and the Wolfram Language. He talks to Mikah Sargent about translating between human language, mathematics, and programming languages, how computational language works, and how he has spent his life trying to build computational intelligence up. Host: Mikah Sargent Guest: Stephen Wolfram Download or subscribe to this show at https://twit.tv/shows/triangulation. Sponsors: capterra.com/triangulation LastPass.com/twit
Stephen Wolfram is a computer scientist who designed Mathematica, Wolfram Alpha, and the Wolfram Language. He talks to Mikah Sargent about translating between human language, mathematics, and programming languages, how computational language works, and how he has spent his life trying to build computational intelligence up. Host: Mikah Sargent Guest: Stephen Wolfram Download or subscribe to this show at https://twit.tv/shows/triangulation. Sponsors: capterra.com/triangulation LastPass.com/twit
Every year for the past 17 years, Wolfram Research has hosted the Wolfram Summer School, where students and professionals from all over the world come to work on exciting and innovative projects using Wolfram Language. This year Stephen attended, and had the opportunity to speak with Stephen Wolfram. Stephen Wolfram is the founder and CEO of Wolfram Research, the company behind big tech products like Mathematica and Wolfram Alpha. Links to Stephen's work and Wolfram Research news: http://www.wolfram.com/ https://blog.stephenwolfram.com/ Follow the podcast @EndeavourPod Hosted by @StephenSchroed Theme music by @BrkmstrCylinder Email endeavourpodcast@gmail.com Find out more at https://endeavour-podcast.pinecast.co
Our guest this week is Stephen Wolfram. Stephen is the creator of Mathematica, Wolfram|Alpha and the Wolfram Language; he’s the author of A New Kind of Science; and the founder and CEO of Wolfram Research. Over the course of nearly four decades, Stephen 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. For show notes visit: https://kk.org/cooltools/stephen-wolfram-founder-at-wolfram-research
Our guest on today’s episode of the Austinpreneur podcast is Stephen Wolfram. Stephen is a mathematician, a physicist, an entrepreneur, and author of a best-selling book. He’s also the creator of the Wolfram Language, one of the only true, symbolic programming languages in everyday use today trying to describe the real world.Wolfram language is the smarts behind Siri and Alexa.On today’s podcast we talked about Wolfram Language and how you could be using it in your own businesses.
Stephen Wolfram is the founder and CEO of the software company Wolfram Research. What happens when you track every email, every keystroke, every mouse movement and every project for 30 years? Today we find out the productivity strategies, personal infrastructure and tracking analytics from the man behind Wolfram Language and Wolfram Alpha - the answer engine which powers Siri & Alexa. Extra Stuff: Wolfram Alpha - https://www.wolframalpha.com/ Follow Stephen on Twitter - https://twitter.com/stephen_wolfram Seeking The Productive Life - https://blog.stephenwolfram.com/2019/02/seeking-the-productive-life-some-details-of-my-personal-infrastructure/ Stephen's Personal Analytics - https://blog.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life/ Check out everything I recommend from books to products and help support the podcast at no extra cost to you by shopping through this link - https://www.amazon.co.uk/shop/modernwisdom - Get in touch. Join the discussion with me and other like minded listeners in the episode comments on the MW YouTube Channel or message me... Instagram: https://www.instagram.com/chriswillx Twitter: https://www.twitter.com/chriswillx YouTube: https://www.youtube.com/ModernWisdomPodcast Email: modernwisdompodcast@gmail.com
Stephen Wolfram reads a recent essay, "What We've Built Is a Computational Language (and That's Very Important!)" and explains how he's built the Wolfram Language as a way to communicate computational ideas. Read the essay: https://wolfr.am/Drl0JCmF
STEPHEN WOLFRAM (https://www.edge.org/memberbio/stephen_wolfram) is a scientist, inventor, and the founder and CEO of Wolfram Research. He is the creator of the symbolic computation program Mathematica and its programming language, Wolfram Language, as well as the knowledge engine Wolfram|Alpha. He is also the author of A New Kind of Science. The Conversation: https://www.edge.org/conversation/stephen_wolfram-mining-the-computational-universe
In this episode, Haley interviews Stephen Wolfram at the Ninth International Conference on Complex Systems. Wolfram is the creator of Mathematica, Wolfram|Alpha and the Wolfram Language; the author of A New Kind of Science; and the founder and CEO of Wolfram Research. Wolfram talks with Haley about his professional journey and reflects on almost four decades of history, from his first introduction to the field of complexity science to the 30 year anniversary of Mathematica. He shares his hopes for the evolution of complexity science as a foundational field of study. He also gives advice for complexity researchers, recommending they focus on asking simple, foundational questions.
In this episode preview, we share a clip from our interview with Stephen Wolfram. Wolfram is the creator of Mathematica, Wolfram|Alpha and the Wolfram Language; the author of A New Kind of Science; and the founder and CEO of Wolfram Research. Wolfram shares with us his disappointment that the basic science of complexity has not been more explored. He states, “the great thing about the basic science is that it will survive forever”.
In breaking news, Andy and Dave discuss the recently unveiled Wolfram Neural Net Repository with 70 neural net models (as of the podcast recording) accessible in the Wolfram Language; Carnegie Mellon and STRUDEL announce the Code/Natural Language (CoNaLa) Challenge with a focus on Python; Amazon releases its Deep Lens video camera that enables deep learning tools; and the Computer Vision and Pattern Recognition 2018 conference in Salt Lake City. Then, Andy and Dave discuss DeepMind’s Generative Query Network, a framework where machines learn to turn 2D scenes into 3D views, using only their own sensors. MIT’s RF-Pose trains a deep neural net to “see” people through walls by measuring radio frequencies from WiFi devices. Research at the University of Bonn is attempting to train an AI to predict future results based on current observations (with the goal of “seeing” 5 minutes into the future), and a healthcare group of Google Brain has been developing an AI to predict when a patient will die, based on a swath of historical and current medical data. The University of Wyoming announced DeepCube, an “autodidactic iteration” method from McAleer that allows solving a Rubik’s Cube without human knowledge. And finally, Andy and Dave discuss a variety of books and videos, including The Next Step: Exponential Life, The Machine Stops, and a Ted Talk from Max Tegmark on getting empowered, not overpowered, by AI.
STEPHEN WOLFRAM (https://www.edge.org/memberbio/stephen_wolfram), distinguished scientist, inventor, author, and business leader, is Founder & CEO, Wolfram Research; Creator, Mathematica, Wolfram|Alpha & the Wolfram Language; Author, A New Kind of Science. The Conversation: https://www.edge.org/conversation/stephen_wolfram-ai-the-future-of-civilization
Dr. Stephen Wolfram is the Founder and CEO of Wolfram Research. In addition, he is the creator of the Wolfram Language, the computational platform Mathematica, and the computational knowledge engine Wolfram Alpha, as well as the author of the bestselling book A New Kind of Science. Stephen attended Oxford University and he received his PhD in Theoretical Physics from the California Institute of Technology. Afterward, he joined the faculty at Caltech and became the youngest recipient of the MacArthur Fellowship. Later, he founded the Center for Complex Systems Research and joined the faculty at the University of Illinois. Shortly afterwards, he founded his current company Wolfram Research and has made substantial advances in mathematics, physics, and computation. Stephen is here with us today to tell us all about his experiences along the way in life and science.
Mike has an impressive entrepreneurial background including co-founding four new ventures, raising over seven million dollars of capital and authoring or co-authoring 10 patents. Most recently he's working on redefining search with Leap.it for which he's raised around $2.5 million dollars. Needless to say I had a lot of questions for Mike and we talked about taking on Google, the value of higher education, innovative disruption, strategic product development, going mobile first, managing other people's money and a lot more.Podcast: (function() { $('#audio289609 audio').mediaelementplayer({ features: ['playpause', 'current', 'progress', 'duration', 'volume', 'popup', 'download'] }); }).call(this); Links:Leap.itRensselaer Polytechnic InstituteKC ChamberWolfram Language1 Billion Bits
In der 7. Ausgabe gibt es zu hören: IT-Keller bedankt sich für die Erwähnung im PodUnion Magazin (PMB009 – Audiozeug) bzw. die netten Kommentare vom #GeekTalk Podcast; ein bisserl Gerede über MacBook Pro, Mac Pro und Bootcamp; WLAN Problem - Macbook Pro (Retina, 15", late 2013) mit Netgear WAG102; Pono Music (Kickstarter-Projekt, Pono Audio Format); App für barrierearmes Kino (Greta); Rapid Serial Visual Presentation, Spritz, simple Spritz reader using Wolfram Language; fehlende Liste aller jemals abgegebenen +1; ROLF Spectacles; Wearable "Ein Ring, sie zu knechten, ..." (Kickstarter-Projekt); und noch ein bisschen mehr. Gäste: Bernhard und Thomas
Wolfram Language. The "goto fail" SSL bug and the chances that it was nefariously introduced by an NSA effort, possibly as part of their $250 million annual budget for such operations. Apple's warrant canary. Casey's and Marco's hard-to-find bugs and language misfeatures. (Perl protects John from writing bugs.) Whether language-interpreter warnings should be treated as errors in production. The Scriptnotes episode with the Final Draft CEO, the follow-up in the next episode, and Kent Tessman's response. After-show: Google lobbying against Glass bans while driving, and Objective-C exception conventions. Next week will be the Software Methodologies show. For real this time! Sponsored by: Picturelife: The one app your photos need. Back up, search, edit, and share on Mac and iOS. Squarespace: Everything you need to create an exceptional website. Use promo code CASEY for 10% off. HelpSpot: Simple, powerful, customizable help-desk software with no monthly fees. Use code ATP14 for $100 off.
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