Podcasts about wolfram alpha

Welcome to episode 36 of the Designing with Love podcast! In this episode, I had the pleasure of interviewing Dr. Craig Hane, a math educator and founder of the Triad Math Army. Mathematics doesn't have to be intimidating, confusing, or useless. Dr. Craig Hane proves this through his remarkable journey from being told he wasn't "college material" to revolutionizing how math is taught and learned.Dr. Hane shares how his uncle taught him practical mathematics that put him ahead of his peers, yet traditional algebra instruction nearly derailed his academic future. This contradiction sparked a lifelong mission to transform mathematical education. With refreshing candor, he explains why 90% of what's in standard algebra textbooks is either obsolete or unnecessarily theoretical, serving examinations rather than real-life applications.The conversation takes a fascinating turn when Dr. Hane introduces Wolfram Alpha, a powerful computational tool that has transformed what's possible in mathematics education. Just as calculators made slide rules obsolete overnight in the 1970s, this technology allows students to focus on understanding concepts rather than struggling with manual calculations. His six-tier educational system progressively builds mathematical competency, starting with essential practical skills and advancing through higher-level concepts as needed.Beyond mathematics, Dr. Hayne has developed "wisdom tools" – practical knowledge frameworks accumulated through decades of experience addressing everything from breaking bad habits to achieving financial freedom. His Triad Math Army combines mathematical education with these wisdom tools, creating a comprehensive development program that serves both academic and personal growth.Whether you're a student struggling with mathematics, an educator seeking better approaches, or someone who's always felt alienated by traditional math instruction, this conversation offers a revolutionary perspective on learning and teaching. Dr. Hane's practical, technology-embracing approach could transform how we think about not just mathematics, but education as a whole.

Dr. Kyle Keane is a Senior Lecturer in Assistive Technologies at the University of Bristol, where he leads research at the intersection of artificial intelligence, human cognition and assistive technology design. With a background in quantum computing and computational physics, he applies the scientific rigor of a physicist to studying human perception and the engineer's precision to designing technologies that translate complex information into interpretable, multi-sensory experiences. Previously, Kyle was a lecturer and research scientist at MIT. He has also worked for Wolfram|Alpha. In this podcast we discuss early life, turning blind and MIT, complex systems and forecasting, understanding AI capabilities, and much more.    Follow us here for more amazing insights: https://macrohive.com/home-prime/ https://twitter.com/Macro_Hive https://www.linkedin.com/company/macro-hive

Today, I have the distinct privilege of engaging in a profound discussion with Dr. Craig Hane, a transformative figure in mathematics education. Dr. Haney, an esteemed educator with a PhD in algebraic numeric theory, has devoted his career to dismantling the barriers that obstruct the comprehension of mathematics for students and professionals alike. His mission is to revolutionize the pedagogical approach to mathematics, advocating for the utilization of modern technological tools, such as scientific calculators and resources like Wolfram Alpha, to enhance learning experiences. Throughout our conversation, we delve into the intricacies of practical math, exploring how a simplified, application-oriented curriculum can significantly improve student engagement and success. Dr. Hane's insights highlight the need to adapt educational methodologies to better prepare individuals for the complexities of contemporary life, ultimately fostering a brighter future for generations to come.The conversation navigates Dr. Hane's personal journey, revealing the challenges he faced in his early education and the pivotal moments that shaped his career. He recounts instances where he was deemed inadequate in mathematics, only to later excel through the guidance of exceptional mentors. This narrative serves as a testament to the critical role of encouragement and effective teaching in developing mathematical proficiency. Dr. Hane's commitment to demystifying mathematics is further reflected in his innovative teaching methods, which prioritize practical applications and real-world relevance over theoretical abstractions. He posits that by equipping students with the necessary tools and knowledge, we can significantly diminish the anxiety often associated with mathematics, thereby fostering a generation of confident individuals capable of tackling diverse challenges.Takeaways: Dr. Craig Hane emphasizes the importance of practical math skills in education, advocating for teaching methods that enhance understanding rather than relying on outdated manual tools. He shares his personal journey from struggling with math to earning a PhD, demonstrating how self-belief can lead to remarkable achievements. The podcast discusses the necessity of integrating modern technology, such as calculators and software like Wolfram Alpha, into math education to facilitate learning and reduce anxiety. Dr. Hane critiques current public school math curricula, arguing that they often include irrelevant material that does not prepare students for real-world applications of mathematics. Links referenced in this episode:craighane.comwolframalpha.com

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

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qaQuestions include: Did you see the recent news about the dire wolves coming back from extinction? Is there a genuine business for bringing back extinct animals?  - There are also scientists making hybrids by injecting extinct animal DNA into modern animals. Recently they made woolly mice. - But would our atmosphere sustain dinosaur life, considering there was more oxygen back then? - At the remarkable age of 15, you began doing things that many would consider grown-up. I'm just curious as to how you went about attacking things that you simply felt like attacking. There are some people who wonder about stuff but don't necessarily know where to begin. How did you get so emboldened, if you can recall what that felt like? - I am curious about the "health trackers" you currently use (without revealing anything too personal!). I see at the time, you used a Fitbit Charge 2 and ServiceConnect, etc. Do you still use these, or have you switched to an Apple Watch etc.? Asking because I love your idea of tracking all kinds of health data, and I especially agree that automated is best. - Going back to your answer to my question about AI agents, which I agree that most websites will be used for LLMs instead of humans, should Wolfram|Alpha's next product be like Alexa—perhaps called "Wolfie"? - How to build that sort of confidence, then? What if I overthink at all times? How to challenge if I'm old already? - ​​Should my next venture be based on an intellectual curiosity that might develop into something organically or a big ambition? - Do you think someone will come up with an internal fitness tracker which would be more accurate? - Is capital becoming more free to take risks or more constrained because of complexity of high-earning businesses? - How do you deal with real exogenous risks (i.e. global pandemic), with respect to innovation and commercialization thereof? - What are some early finance tips and tricks to teach kids to prepare them for the future? - ​​I feel like I became a friend with ChatGPT—is it healthy? - ChatGPT and my daily-driver LLMs definitely know and remember more about me than I do myself at this point! - That seems a great idea. In the "Computational X" program, why not something to teach financial literacy and key financial math (compounding etc.), notably for kids, in interactive forms? - ​​When designing humanoid robots, what do you think is a key component design of them?

Send us a textDr. Craig Hane, affectionately known as Dr. Del, is on a mission to revolutionize math education and empower individuals with practical tools to unlock their potential. With a Ph.D. in Algebraic Number Theory, decades of teaching experience, and a passion for breaking barriers, Dr. Del offers a compelling mix of expertise, innovation, and storytelling that resonates with listeners of all backgrounds.Born in the aftermath of WWII, Dr. Del's early life was shaped by resilience and resourcefulness. From humble beginnings in rural Indiana, where he learned arithmetic under the guidance of his uncle, to overcoming significant academic challenges, his journey underscores the transformative power of belief, perseverance, and mentorship. Dr. Del's inspiring story is one of turning setbacks into stepping stones, making it relatable and uplifting for any audience.What sets Dr. Del apart is his groundbreaking approach to math education. He combines traditional concepts with modern tools like scientific calculators and Wolfram Alpha to demystify math and make it accessible to everyone. His philosophy is simple: math should empower, not intimidate. Dr. Del's strategies enable students and professionals alike to conquer math barriers in STEM fields and beyond, proving that even complex subjects like calculus and differential equations can be made easy.  You can learn more about Dr. Hane's work at his website: https://craighane.com/https:/natureandsciencepodcast.com#podmatch

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Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: How long should someone expect to wait before a new business becomes profitable? - In your personal/professional journey, what are the important things that you learned the hard way? - ​​Can you elaborate on some of the unique talents within your team? Perhaps extremely smart or methodical/disciplined people? - Can you tell us about any exciting projects you're working on right now? - What do you think about self-driving? Do you think Tesla's approach without LIDAR has legs or do you think the Google Waymo hardware-intense approach is more promising? - Any tips for building a strong customer base from scratch? - What's the best way to figure out pricing for a new product or service? - With your work on Wolfram|Alpha and other projects, you've brought complex computational abilities to the general public in accessible ways. What were some of the challenges in making such powerful tools user friendly, and how do you think accessibility to high-level technology will shape industries in the future? - If the CEO himself heavily uses the product, you know it's something special. - Stephen, how do you personally define innovation? What makes something truly innovative instead of just a small improvement? - How important are critiques? Which do you find more valuable: positive or negative feedback? - I like real feedback. Pick it apart—that helps in fixing problems/strengthen whatever it is. - I've been rewatching the first hour of your interview with Yudkowsky since yesterday... do you enjoy those types of interactions often? - How do you balance maintaining the integrity of your original idea while incorporating customer feedback, which is often influenced by their familiarity with previous, incomparable solutions? - Do you have a favorite interview/podcast/speech that you've done? Or one that you were most proud of? - Are you aware that with the weekly livestreams, you basically invented THE PERFECT brain workout? - Is there a topic or question you wish more podcast hosts would ask you about that they often overlook? - What is something surprising people may not know about your "day job"? - You have frequently written about your vast digital archive. What tool do you use for indexing and searching? What other tools have you used or considered in the past and what is your opinion about them? With the improving LLMs and RAG, how do you think searching and indexing will change?

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: ​​What do you view as the best strategies for reducing or eliminating hallucination/confabulation right now? Is there any chance that we'll be able to get something like confidence levels along with the responses we get from large language models? - ​​I love this topic (fine tuning of LLMs); it's something I'm currently studying. - The AI Scientist is an LLM-based system that can conduct scientific research independently, from generating ideas to writing papers and even peer-reviewing its own work. How do you see this technology impacting the development of Wolfram|Alpha and other knowledge-based systems in the future? - ​​It's fascinating the difference in response from LLMs/as to how you pose your questions. - ​​I have found that giving key terms and then asking the LLM to take the "concepts" and relate them a particular way seems to work pretty well. - How we are going to formalize the language structures arising from this microinformatization, which was capable of creating such a semantic syntax that we had not observed through structuralism? - Why is being rude and "loud" to the model always the most efficient way to get what you want if the one-shot fails? I notice this applies to nearly all of them. I think it's also in the top prompt engineering "rules." I always feel bad even though the model has no feelings, but I need the proper reply in the least amounts of questions. - AI Scientist does what you're describing. The subtle difference is that it is generating plausible ideas, creating code experiments and then scoring them–question is whether this approach can/should be extended with Alpha? - How soon do you think we'll have LLMs that can retrain in real time? - What's your take on integrating memory into LLMs to enable retention across sessions? How could this impact their performance and capabilities? - Do you think computational analytics tools are keeping up with the recent AI trends? - Would it be interesting to let the LLM invent new tokens in order to compress its memories even further? - Philosophical question: if one posts a Wolfram-generated plot of a linear function to social media, for media is math, should it be tagged "made with AI"? It's a social media's opinion probably–just curious. A math plot is objective, so different than doing an AI face swap, for example. - For future archeologists–this stream was mostly human generated. - Professor_Neurobot: Despite my name, I promise I am not a bot.

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.

If you see this in time, join our emergency LLM paper club on the Llama 3 paper!For everyone else, join our special AI in Action club on the Latent Space Discord for a special feature with the Cursor cofounders on Composer, their newest coding agent!Today, Meta is officially releasing the largest and most capable open model to date, Llama3-405B, a dense transformer trained on 15T tokens that beats GPT-4 on all major benchmarks:The 8B and 70B models from the April Llama 3 release have also received serious spec bumps, warranting the new label of Llama 3.1.If you are curious about the infra / hardware side, go check out our episode with Soumith Chintala, one of the AI infra leads at Meta. Today we have Thomas Scialom, who led Llama2 and now Llama3 post-training, so we spent most of our time on pre-training (synthetic data, data pipelines, scaling laws, etc) and post-training (RLHF vs instruction tuning, evals, tool calling).Synthetic data is all you needLlama3 was trained on 15T tokens, 7x more than Llama2 and with 4 times as much code and 30 different languages represented. But as Thomas beautifully put it:“My intuition is that the web is full of s**t in terms of text, and training on those tokens is a waste of compute.” “Llama 3 post-training doesn't have any human written answers there basically… It's just leveraging pure synthetic data from Llama 2.”While it is well speculated that the 8B and 70B were "offline distillations" of the 405B, there are a good deal more synthetic data elements to Llama 3.1 than the expected. The paper explicitly calls out:* SFT for Code: 3 approaches for synthetic data for the 405B bootstrapping itself with code execution feedback, programming language translation, and docs backtranslation.* SFT for Math: The Llama 3 paper credits the Let's Verify Step By Step authors, who we interviewed at ICLR:* SFT for Multilinguality: "To collect higher quality human annotations in non-English languages, we train a multilingual expert by branching off the pre-training run and continuing to pre-train on a data mix that consists of 90% multilingualtokens."* SFT for Long Context: "It is largely impractical to get humans to annotate such examples due to the tedious and time-consuming nature of reading lengthy contexts, so we predominantly rely on synthetic data to fill this gap. We use earlier versions of Llama 3 to generate synthetic data based on the key long-context use-cases: (possibly multi-turn) question-answering, summarization for long documents, and reasoning over code repositories, and describe them in greater detail below"* SFT for Tool Use: trained for Brave Search, Wolfram Alpha, and a Python Interpreter (a special new ipython role) for single, nested, parallel, and multiturn function calling.* RLHF: DPO preference data was used extensively on Llama 2 generations. This is something we partially covered in RLHF 201: humans are often better at judging between two options (i.e. which of two poems they prefer) than creating one (writing one from scratch). Similarly, models might not be great at creating text but they can be good at classifying their quality.Last but not least, Llama 3.1 received a license update explicitly allowing its use for synthetic data generation.Llama2 was also used as a classifier for all pre-training data that went into the model. It both labelled it by quality so that bad tokens were removed, but also used type (i.e. science, law, politics) to achieve a balanced data mix. Tokenizer size mattersThe tokens vocab of a model is the collection of all tokens that the model uses. Llama2 had a 34,000 tokens vocab, GPT-4 has 100,000, and 4o went up to 200,000. Llama3 went up 4x to 128,000 tokens. You can find the GPT-4 vocab list on Github.This is something that people gloss over, but there are many reason why a large vocab matters:* More tokens allow it to represent more concepts, and then be better at understanding the nuances.* The larger the tokenizer, the less tokens you need for the same amount of text, extending the perceived context size. In Llama3's case, that's ~30% more text due to the tokenizer upgrade. * With the same amount of compute you can train more knowledge into the model as you need fewer steps.The smaller the model, the larger the impact that the tokenizer size will have on it. You can listen at 55:24 for a deeper explanation.Dense models = 1 Expert MoEsMany people on X asked “why not MoE?”, and Thomas' answer was pretty clever: dense models are just MoEs with 1 expert :)[00:28:06]: I heard that question a lot, different aspects there. Why not MoE in the future? The other thing is, I think a dense model is just one specific variation of the model for an hyperparameter for an MOE with basically one expert. So it's just an hyperparameter we haven't optimized a lot yet, but we have some stuff ongoing and that's an hyperparameter we'll explore in the future.Basically… wait and see!Llama4Meta already started training Llama4 in June, and it sounds like one of the big focuses will be around agents. Thomas was one of the authors behind GAIA (listen to our interview with Thomas in our ICLR recap) and has been working on agent tooling for a while with things like Toolformer. Current models have “a gap of intelligence” when it comes to agentic workflows, as they are unable to plan without the user relying on prompting techniques and loops like ReAct, Chain of Thought, or frameworks like Autogen and Crew. That may be fixed soon?

Listen on Spotify: https://open.spotify.com/show/4gL14b9... Donald Hoffman vs. Stephen Wolfram Stephen Wolfram is a renowned computer scientist, physicist, and the creator of Mathematica and the Wolfram Alpha computational engine, known for his groundbreaking work on cellular automata and computational theory. Donald Hoffman is a cognitive scientist and author, acclaimed for his revolutionary theories on consciousness and perception, suggesting that our senses provide a user interface rather than a direct window to reality.  Join TOEmail at https://www.curtjaimungal.org  Links Mentioned: Donald's book - https://www.amazon.com/Observer-Mecha... Stephen's TOE ep - https://www.youtube.com/watch?v=0YRlQ... Donald's TOE ep - https://www.youtube.com/watch?v=CmieN...  Support TOE: - Patreon: https://patreon.com/curtjaimungal (early access to ad-free audio episodes!) - Crypto: https://tinyurl.com/cryptoTOE - PayPal: https://tinyurl.com/paypalTOE - TOE Merch: https://tinyurl.com/TOEmerch  Follow TOE: - *NEW* Get my 'Top 10 TOEs' PDF + Weekly Personal Updates: https://www.curtjaimungal.org - Instagram: https://www.instagram.com/theoriesofeverythingpod - TikTok: https://www.tiktok.com/@theoriesofeverything_ - Twitter: https://twitter.com/TOEwithCurt - Discord Invite: https://discord.com/invite/kBcnfNVwqs - iTunes: https://podcasts.apple.com/ca/podcast/better-left-unsaid-with-curt-jaimungal/id1521758802 - Pandora: https://pdora.co/33b9lfP - Spotify: https://open.spotify.com/show/4gL14b92xAErofYQA7bU4e - Subreddit r/TheoriesOfEverything: https://reddit.com/r/theoriesofeverything  

Subscriber-only episodeTransform your math education approach with insights from Craig Hayne, the visionary behind Triad Math. Craig's innovative six-tier structure starts with mastering a scientific calculator and pre-algebra, making the subject both accessible and enjoyable for students who have historically struggled. Discover how Craig's emphasis on self-paced learning and practical algebra can revolutionize the way math is taught, moving away from unnecessary theoretical content to create a more efficient and engaging educational experience.Imagine mastering integral calculus and differential equations with ease. In this episode, we highlight the transformative power of modern tools like Wolfram Alpha in learning advanced mathematics. By integrating this online resource, students can handle complex topics more efficiently, aligning educational content with contemporary technology. You'll hear inspiring stories, such as a student's extraordinary success at the Air Force Academy, showcasing the practical benefits of this modern approach.Join us as we engage in a lively conversation with Craig, who has a PhD in Mathematics, as he reflects on the evolution of mathematical education tools, from early calculators to today's powerful software. We also dive into the benefits of homeschooling math through Craig's resources and discuss the importance of a holistic approach to education, emphasizing the development of intrinsic and extrinsic motivators. Hear personal anecdotes about unique educational journeys and gain valuable parenting advice that stresses the importance of positive reinforcement and maintaining strong family relationships. Don't miss out on these invaluable insights into revolutionizing math education.Triad Math:Learn more about Triad Math HERE!Instagram: TheHomeschoolHowToPodcast Facebook: The Homeschool How To Podcast

“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

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

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

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

In this podcast episode, the creators of Professor AI, an AI startup supporting students with AP exams, discuss their journey and the development of their app. The founders, who are 11th graders in high school, explain how they came up with the idea and the importance of founder-market fit. They also discuss the challenges of AI hallucinations and how they overcame them by using open-source textbooks and integrating with Wolfram Alpha. The founders highlight the support they received from Microsoft and their participation in an accelerator program. They emphasize their goal of providing access to educational resources for all students. Pradyu Kandala and Abhay Chebium discuss their AI-powered education platform, Professor AI, which aims to provide personalized tutoring and grading support for AP students. They address concerns about cheating and emphasize that the AI is designed to help students learn rather than replace teachers. The platform explains concepts in different ways and provides reliable sources for further study. They also highlight the importance of feedback from educators to fine-tune the platform and invite teachers to sign up for the waitlist and support their endeavor. Takeaways Professor AI is an AI startup created by two 11th graders to support students with AP exams. The founders identified a need for an AI system to help students with their AP coursework and exams. The founders received support from Microsoft and are participating in an accelerator program to further develop their startup. Professor AI is an AI-powered education platform that offers personalized tutoring and grading support for AP students. Learn more about Professor AI today: https://www.professorai.co/ Thanks to our amazing sponsors for making the show possible Learn more about Lebra HQ https://www.lebrahq.com/ Learn more about Game Storm EDU https://gamestormedu.com/    

Steven Forth is Ibbaka's Co-Founder, CEO, and Partner. Ibbaka is a strategic pricing advisory firm. He was CEO of LeveragePoint Innovations Inc., a SaaS business. In this episode Steven shares the shifting landscape for pricing professionals, emphasizing the rising importance of pricing strategists over analysts in leveraging AI for value-centric decision-making. Additionally, he highlights the possibilities beyond automation to include real-time recalibration of value models, enabling companies to better adapt to changing customer needs and market dynamics.   Why you have to check out today's podcast: Discover the importance of custom packaging solutions designed to meet the unique needs of diverse users, adding significant value to their experience and allowing for optimized pricing strategies Find out how AI is impacting pricing strategies Understand the evolving role of pricing people: pricing analysts and pricing strategists   "What pricing people should be doing today is learning how to have productive conversations with AI agents." - Steven Forth   Topics Covered: 02:44 - Discussing about platform pricing and solution pricing in the context of AI 05:40 - The challenge that pricing platforms presents when it comes to quantifying value for all users 07:06 - Generative AI versus computational knowledge AI in the case of Wolfram Alpha 10:20 - Highlighting the value of packaging solutions tailored to specific needs which can be more valuable to users 12:06 - What goes in the pricing world with AI around 18:38 - Pricing strategists becoming increasingly important, need for better systems to facilitate meaningful conversations and decision-making 20:11 - Would it be possible for AI to make people inside the company understand what value is to customers 24:08 - Six types of value drivers according to Ed Arnold 27:03 - The challenge of building large amount of value models 30:20 - Steven's best advice to pricing people 31:12 - Building a value model through client interviews   Key Takeaways: "Why don't people focus more on value? I think part of this is because many of us find it easier to look inside our own company than outside to our customers." - Steven Forth "In an uncertain world, having options and being able to generate options gives you a much more adaptive and resilient business." - Steven Forth "They [pricing people] need to be learning how to ask the AI questions. They need to be learning how to train the AI so that it can better answer those questions." - Steven Forth "They [pricing people] need to be understanding the strengths and weaknesses of the answers they're going to get. Because like it or not, you are going to be using an AI, you are using an AI, in your work today, even if you're not aware of it." - Steven Forth   People/ Resources Mentioned: Wolfram Alpha: https://www.wolframalpha.com Stephen Wolfram: https://www.stephenwolfram.com Mathematica: https://www.wolfram.com/mathematica/ Pros: https://pros.com Zilliant: https://zilliant.com Ed Arnold: https://www.linkedin.com/pulse/how-quantify-value-service-ed-arnold/ McKinsey: https://www.mckinsey.com Microsoft Co-Pilot: https://copilot.microsoft.com   Connect with Steven Forth: LinkedIn: https://www.linkedin.com/in/stevenforth/ Email: steven@ibbaka.com   Connect with Mark Stiving: LinkedIn: https://www.linkedin.com/in/stiving/ Email: mark@impactpricing.com  

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

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

Overview: Today, we're going to explore eTranzact - the African payments and switching platform. We'll discuss the story across the following areas: First, Nigerian payments context  Second, eTranzact's early history Third, Product & monetization strategy Fourth, Competitive positioning  Fifth, Overall outlook This episode was recorded on Feb 11, 2024 Companies discussed: eTranzact, Interswitch, Unified Payment Services Limited (UPSL), Systemspecs (Remita), Paystack, Flutterwave, Moniepoint, Paga, OPay, MTN & Airtel. Business concepts discussed: Mobile money, Payments Collections, Payments ecosystem, payments partnerships strategy, card networks, payments infrastructure, low-end disruption, banking regulation & payments M&A strategy Conversation highlights: (00:57) - What is eTranzact and why we're talking about it (07:43) - Context of Nigeria's payment sector before eTranzact (16:45) - eTranzact founding story (35:46) - Growth and geographic expansion (45:10) - Product strategy (01:02:56) - Monetization strategy (01:20:41) - Competition (1:31:10) - Bankole's overall thoughts and outlook (1:34:38) - Olumide's overall thoughts and outlook (1:43:20 - Recommendations and small wins Olumide's recommendations & small wins: Interested in investing in Africa Tech with Olumide: Read about Adamantium fund & contact me at olumide@afrobility.com. Founders looking for funding: If you're a B2B founder working on Education, Health, Finance or food, please contact me for funding at olumide@afrobility.com Checkout my FIREDOM book = FIRE (Financial Independence, Retire Early) + Freedom = personal finance and financial independence book. Website, Read: Substack Newsletter & Buy: Print, eBook or Audiobook) Recommendation: Never Enough (Loren Allred). Incredible. I can listen to it on repeat for the whole day.  Recommendation: La Bachata (Maniel Turizo). Dope shit. Recommendation: "Someone You Loved". Not the original but a fabulous cover. Best line, "I was getting kinda used to being someone you loved". Listen to the 3rd verse when they sing simultaneously. Incredible! Recommendation: A Million Miles Away movie. It is a biographical drama film about the life of José Hernández, a Mexican-American migrant farm  Small win: Booked Cirque Du Soleil show. Looking forward to it. Bankole's recommendations & small wins: Recommendation: Comma - Burna Boy && Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT Small win: Clean shaven + the Nigerian AFCON semifinal win only to lose in the final a few hours after recording :(  Other content: History of Web Acquiring in Nigeria && Atlas Copco on Invest Like The Best && An Empirical Examination of Why Mobile Money Schemes Ignite in Some Developing Countries but Flounder in Most  Listeners: We'd love to hear from you. Email info@afrobility.com with feedback! Founders & Operators: We'd love to hear about what you're working on, email us at info@afrobility.com Investors: It would be great to link up with you. Contact us at info@afrobility.com Join our insider mailing list where we get feedback on new episodes & find all episodes on Afrobility.com

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  

[INTRO MUSIC] HOST (Elle Cole):Welcome to the Cleverly Changing Podcast, where we explore the world of homeschooling, parenting, and education. I'm your host, Elle Cole, and today we're diving into the fascinating realm of artificial intelligence in homeschooling.HOST (Elle Cole):Artificial intelligence, or AI, isn't just about robots and sci-fi movies. It's a powerful tool that can enrich our children's education in remarkable ways. We shouldn't be afraid of technology. It is a tool that we should learn how to use responsibly, and the lessons around technology should be taught in an educational setting or within the homeschool setting. Today, I'll be sharing practical ways families can integrate AI into their homeschool curriculum.I believe learning is about going on a knowledge adventure. STEM is huge in schools and today's job markets, so our children should be early adopters of how to train machines/computers intelligently.HOST (Elle Cole):Let's start with something fundamental—reading. AI-powered reading apps like Lexia Core5 or Epic! Books offer personalized learning paths. They adapt to a student's reading level, providing targeted activities to improve comprehension and vocabulary.SCENARIO 1: MORNING ROUTINEHOST (Elle Cole):Imagine this: It's the start of a homeschool day. You're gathered around the kitchen table, ready to dive into your lessons. But before you begin, why not start with an AI-powered news aggregator like Newsela? This tool provides tailored news articles suitable for different reading levels.HOST (Elle Cole):Next, you can select articles relevant to your curriculum, whether it's history, science, or current events. It's an excellent way to spark discussions and encourage critical thinking while keeping your kids informed about the world.SCENARIO 2: STEM ACTIVITIESHOST (Elle Cole):For those science and tech enthusiasts, AI can be a game-changer. Have you heard of DIY projects like building a voice-controlled robot or coding with Scratch? These hands-on activities engage kids in the basics of AI and coding.HOST (Elle Cole):Platforms like Scratch offer a user-friendly interface that lets kids create animations, games, and interactive stories using coding blocks. It's a fantastic way to introduce programming concepts while fostering creativity.SCENARIO 3: PERSONALIZED LEARNINGHOST (Elle Cole):One of the most remarkable aspects of AI in education is its ability to personalize learning experiences, which should be right in line with homeschoolers self-directed philosophies. Tools like Khan Academy or Coursera leverage AI algorithms to adapt content based on a child's progress.HOST (Elle Cole):So, whether your child excels in math or needs extra help with grammar, these platforms adjust the difficulty level in real time. It's like having a personal tutor catering to each child's unique learning pace.SCENARIO 4: ART AND AIHOST (Elle Cole):When it comes to art, AI isn't just about algorithms. Tools like Google's AutoDraw or Adobe's Sensei can assist budding artists. They provide suggestions and corrections while sketching or designing, making the creative process more intuitive and enjoyable.SCENARIO 5: MATH & SCIENCE EXPLORATIONHOST (Elle Cole):Now, let's venture into the realms of math and science. AI-powered math platforms like Photomath  (which we missed during season 2) or Wolfram Alpha can be incredible aids. They help solve complex equations and offer step-by-step explanations, turning math problem-solving into an interactive experience. These tools can be especially helpful to parents needing a refresher to remind them how to do complex math problems. I used to watch how-to math videos on Youtube, workout the problem, and then use Photomath to ensure my answer and process were correct.HOST (Elle Cole):In science, AI simulators and software like Algodoo or Labster simulate experiments. They allow students to conduct virtual lab experiments, explore scientific theories, and understand concepts like never before. These tools can help level the playing field and save homeschool families money.SCENARIO 6: SOCIAL STUDIES & WORLD HISTORYHOST (Elle Cole):Moving on to social studies and world history, AI-powered resources such as Google Earth and Timeline JS provide immersive experiences. Students can virtually explore historical sites, trace timelines, and understand global events in a more engaging manner.SCENARIO 7: LANGUAGE LEARNING & RELIGIOUS STUDIESHOST (Elle Cole):For language learning and religious studies, AI language apps like Duolingo or Rosetta Stone aid in learning foreign languages. They adapt to individual progress, making language acquisition interactive and fun.[Sound Effect: Reading religious texts]HOST (Elle Cole):Additionally, AI text analysis tools can help students delve deeper into religious texts. They provide insights, interpretations, and summaries, aiding in a comprehensive understanding.HOMESCHOOLING AND ARTIFICIAL INTELLIGENCE EPISODE SUMMARYHOST (Elle Cole):Incorporating artificial intelligence into your homeschool curriculum isn't about replacing traditional teaching methods. It's about enhancing learning experiences, fostering curiosity, and preparing our kids for a tech-driven future. The possibilities of incorporating AI into our core subjects for middle and high school students are extensive. It's also about using technology as a tool to enhance learning, encourage exploration, and cultivate a deeper understanding of various subjects.[Sound Effect: Outro music begins]HOST (Elle Cole):That's all for today's episode. Thank you for joining me on the Cleverly Changing Podcast. Don't forget to visit our website CleverlyChanging.com for additional resources and join the conversation on our social media platforms. Until next time, keep learning and exploring. Goodbye![OUTRO MUSIC FADES IN][END OF EPISODE] ★ Support this podcast on Patreon ★

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.

Ever had a conversation with an AI? How about using one as a creative partner? Join us on this fascinating journey as we unveil the incredible potential of chat GPT in the creative process. Learn how it can serve as a sounding board for your ideas or even help generate engaging content for a novel. We also dissect the creative process into manageable steps with our favorite AI friend, showing you how a blend of randomness and method can birth unique ideas. Think AI is only good for creativity? Think again. We venture into the realm of trend analysis and show you how AI tools like Web Pilot and Vox Script can offer you valuable insights from popular platforms like YouTube and Amazon. Imagine being able to extract crucial information from data dumps, and all it takes is asking the right questions. We also highlight how chat GPT can skyrocket your e-commerce profits, thanks to the magic combo of batch processing, Google spreadsheets, and Wolfram Alpha. But it's not all tech and tools. We go personal and share our experiences with the challenges and benefits of remote living. We stress the need for self-motivation, resilience, and balance, especially when work and family life cross paths. The journey then takes a twist towards the challenges of traveling with young children and the importance of stability. And to wrap it up, we examine the power of strong emotions as motivation, and how a little discontentment could be the push we need. Join us and let's explore the delightful blend of technology, personal development, and entrepreneurship.GETIDA Amazon Owes You Money!   Get $400 in FREE reimbursements done for you, follow the link below.Helium10   50% OFF first month OR 10% OFF LIFETIME subscription = PROMO CODE “FTM”SoStockedStart Your 30-Day Free TrialYour 1st Month Is Free For Any Plan You Choose!If You receive value from this content please SUPPORT The PodcastPaypal → CLICK HERE▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬

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.

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

The back-to-school season is upon us and Apple's App Store is chock-full of apps to help you make the most of your school year. Rosemary Orchard and Mikah Sargent share some of the best apps for your return to school. Notability GoodNotes 5 Freeform Quizlet: Learn with Flashcards My Study Life - School Planner Schooly | School Planner Microsoft Math Solver Photomath WolframAlpha iThoughts2go - Mind Map MindNode - Mind Map & Outline Flora - Green Focus Forest: Focus for Productivity News Our pick of the best iOS 17 features that students can use so far Apple Watch Fast Charging to Be Mandatory for Accessory Makers Apple Music Gains New Algorithmic 'Discovery Station' Shortcuts Corner Vince wants to create a Shortcut that inserts text into a Calendar depending on whether they're arriving or leaving a location. Michael wants to change their Apple Watch's face automatically based on a Focus Mode. Feedback & Questions Mark follows up, asking for help with a means of switching audio output to AirPods. App Caps Rosemary's App Cap: Tetris Mikah's App Cap: Keyword Search Hosts: Mikah Sargent and Rosemary Orchard Download or subscribe to this show at https://twit.tv/shows/ios-today. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can contribute to iOS Today by leaving us a voicemail at 757-504-iPad (757-504-4723) or sending an email to iOSToday@TWiT.tv. Sponsor: GO.ACILEARNING.COM/TWIT

The back-to-school season is upon us and Apple's App Store is chock-full of apps to help you make the most of your school year. Rosemary Orchard and Mikah Sargent share some of the best apps for your return to school. Notability GoodNotes 5 Freeform Quizlet: Learn with Flashcards My Study Life - School Planner Schooly | School Planner Microsoft Math Solver Photomath WolframAlpha iThoughts2go - Mind Map MindNode - Mind Map & Outline Flora - Green Focus Forest: Focus for Productivity News Our pick of the best iOS 17 features that students can use so far Apple Watch Fast Charging to Be Mandatory for Accessory Makers Apple Music Gains New Algorithmic 'Discovery Station' Shortcuts Corner Vince wants to create a Shortcut that inserts text into a Calendar depending on whether they're arriving or leaving a location. Michael wants to change their Apple Watch's face automatically based on a Focus Mode. Feedback & Questions Mark follows up, asking for help with a means of switching audio output to AirPods. App Caps Rosemary's App Cap: Tetris Mikah's App Cap: Keyword Search Hosts: Mikah Sargent and Rosemary Orchard Download or subscribe to this show at https://twit.tv/shows/ios-today. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can contribute to iOS Today by leaving us a voicemail at 757-504-iPad (757-504-4723) or sending an email to iOSToday@TWiT.tv. Sponsor: GO.ACILEARNING.COM/TWIT

The back-to-school season is upon us and Apple's App Store is chock-full of apps to help you make the most of your school year. Rosemary Orchard and Mikah Sargent share some of the best apps for your return to school. Notability GoodNotes 5 Freeform Quizlet: Learn with Flashcards My Study Life - School Planner Schooly | School Planner Microsoft Math Solver Photomath WolframAlpha iThoughts2go - Mind Map MindNode - Mind Map & Outline Flora - Green Focus Forest: Focus for Productivity News Our pick of the best iOS 17 features that students can use so far Apple Watch Fast Charging to Be Mandatory for Accessory Makers Apple Music Gains New Algorithmic 'Discovery Station' Shortcuts Corner Vince wants to create a Shortcut that inserts text into a Calendar depending on whether they're arriving or leaving a location. Michael wants to change their Apple Watch's face automatically based on a Focus Mode. Feedback & Questions Mark follows up, asking for help with a means of switching audio output to AirPods. App Caps Rosemary's App Cap: Tetris Mikah's App Cap: Keyword Search Hosts: Mikah Sargent and Rosemary Orchard Download or subscribe to this show at https://twit.tv/shows/ios-today. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can contribute to iOS Today by leaving us a voicemail at 757-504-iPad (757-504-4723) or sending an email to iOSToday@TWiT.tv. Sponsor: GO.ACILEARNING.COM/TWIT

The back-to-school season is upon us and Apple's App Store is chock-full of apps to help you make the most of your school year. Rosemary Orchard and Mikah Sargent share some of the best apps for your return to school. Notability GoodNotes 5 Freeform Quizlet: Learn with Flashcards My Study Life - School Planner Schooly | School Planner Microsoft Math Solver Photomath WolframAlpha iThoughts2go - Mind Map MindNode - Mind Map & Outline Flora - Green Focus Forest: Focus for Productivity News Our pick of the best iOS 17 features that students can use so far Apple Watch Fast Charging to Be Mandatory for Accessory Makers Apple Music Gains New Algorithmic 'Discovery Station' Shortcuts Corner Vince wants to create a Shortcut that inserts text into a Calendar depending on whether they're arriving or leaving a location. Michael wants to change their Apple Watch's face automatically based on a Focus Mode. Feedback & Questions Mark follows up, asking for help with a means of switching audio output to AirPods. App Caps Rosemary's App Cap: Tetris Mikah's App Cap: Keyword Search Hosts: Mikah Sargent and Rosemary Orchard Download or subscribe to this show at https://twit.tv/shows/ios-today. Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit You can contribute to iOS Today by leaving us a voicemail at 757-504-iPad (757-504-4723) or sending an email to iOSToday@TWiT.tv. Sponsor: GO.ACILEARNING.COM/TWIT

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 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's , of Wolfram Alpha fame, explains in a recent post on his site explaining how ChatGPT works and why it gives the results it does. How did Elon Musk boost the profile of his posts on Twitter after a disappointing showing during the Super Bowl? And a roundup of the latest AI news.Starring Tom Merritt, Sarah Lane, Justin Robert Young, Roger Chang, Joe.Link to the Show Notes. Become a member at https://plus.acast.com/s/dtns. Hosted on Acast. See acast.com/privacy for more information.

AI everywhere, Hive hacked, Microsoft earnings, To Leslie, @ElonJet Pluralistic: Tiktok's enshittification (21 Jan 2023). Inside CNET's AI-powered SEO money machine. If ChatGPT doesn't get a better grasp of facts, nothing else matters. Move over ChatGPT, Microsoft's new AI tool is helping developers code faster. ChatGPT is enabling script kiddies to write functional malware. OPWNAI: Cybercriminals starting to use ChatGPT. MusicLM: Generating Music From Text. Wolfram|Alpha as the Way to Bring Computational Knowledge Superpowers to ChatGPT. AI-powered "robot" lawyer won't argue in court after jail threats. More on Google and AI; OpenAI, Integration, and Microsoft – Stratechery by Ben Thompson. Meta's AI chief Yann LeCun calls ChatGPT "not particularly innovative". Inside Neeva, the ad-free, privacy-first search engine from ex-Googlers. US hacks back against Hive ransomware crew. Microsoft Revenue Up 2 Percent, but Profit Drops 12 Percent. GitHub: 100 million developers and counting. To Leslie' and the word-of-mouth campaign that got Andrea Riseborough an Oscar nomination. The flight tracker that powered @ElonJet has taken a left turn. Why Taylor Swift Is Using Facial Recognition at Concerts. James Dolan gives fiery interview defending facial recognition tech at MSG. AI makes Ariana Grande sing a Billie Eilish song. Host: Leo Laporte Guests: Harry McCracken, Tim Stevens, and Christina Warren Download or subscribe to this show at https://twit.tv/shows/this-week-in-tech Get episodes ad-free with Club TWiT at https://twit.tv/clubtwit Sponsors: wwt.com/twit GO.ACILEARNING.COM/TWIT bitwarden.com/twit

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.