The Stephen Wolfram Podcast

Stephen Wolfram answers questions from his viewers about the history of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Do you think it will be possible to recreate historical figures as bots to interact with and get their perspective on current research areas? - Why do many great mathematicians complete their most influential work in their early 20s? - Does "prompting" (as for LLMs) have some historical precursors? - So Feynman could have been a great prompt engineer (given that he was such a great expositor/teacher)? - How do you think future researchers will look back at this current time in history? We look at bones and architecture to determine facts about the past; what will they look at to determine facts of our time? AI? - ​Can we restore old, lost books by reading other old books which talk about them? - Seneca wrote many many letters. Could we detect if some have been wrongly attributed to him? - I love a historian David Lewis's possible world that we can create alternative history/hypothetical situations to learn what went wrong historically. I just wonder whether AI can utilize deep learning to generate the sequence of historical events with the constraint of data and and recreate the alternative historical events with the known variables to generate hypothetical outcome? - Isn't sonographic/x-raying safer than digging through ancient architecture? Or is it still dangerous somehow? - They have been using muons to probe the pyramids in Egypt. - Maybe AI can help with such more passive imaging through buildings? - Neural network weights will be a more efficient means of archive through the centuries than books and libraries—which will matter as with ChatGPT the volume of published writing will climb exponentially. - ​Prompting has relevance in psychology and philosophy. - Could it be that the best prompter now are poets? Or better... computational poets? - I don't think RAM or ROM-chips will survive the passage of time or solid state drives...

Stephen Wolfram answers general questions from his viewers about science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include:With the rise of AI, what will happen to the world of education? - Will we able to provide basic things to everyone with the use of only machines (specifically food, water and shelter)? At that point, will jobs be obsolete or not? - Are we about to reach a post-truth world due to AI-enabled misinformation? How do we combat this? - Since ChatGPT can currently only reproduce written human reasoning, will it even be possible for ChatGPT to be better than humans one day? - How can AI, through the lens of computational irreducibility, navigate the vast landscape of possible rule sets and achieve true intelligence, mirroring the complexity of our universe? - Do you think we will see more of this phenomenon where AI contributes to the fundamentals of science? - What do you think about AI alignment and the existential risk of AI? - What's it like to be an LLM? By extension, what's it like to be a computer? - Once AI can start programming, use those programs to solve problems and debug, will programmers become obsolete? - What are your suggestions for a high-school student who is interested in both AI and physics?

Stephen Wolfram answers questions about programming, computational thinking, and managing life. They discuss the development of Wolf Language, grading answers in a class, understanding country borders, learning in MBA school, systematic learning, determining principles and terms of service, exploring democratic systems, and the impact of AI innovation on jobs and social interactions.

Stephen Wolfram answers general questions from his viewers about science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: If ChatGPT's transformer model stores the averaging of the text that regular people produced on the internet plus millions of books, is it fair to say that it's going to produce mediocre output? What if we train a model with text produced by geniuses ONLY, like Euler, Gauss, Newton, Benjamin Franklin, etc.? Would it be superior? - What are you most excited to see from AI? - Is AI guaranteed to be 100% accurate? Or does it behave in a way similar to humans, where mistakes are possible and there should be some sort of quality assurance, either built in or separate, that requires human labor? - Does Elon Musk's call for halting AI development make any sense? Wouldn't people elsewhere do it anyway? Would this just hurt Western development at the cost of others pursuing it elsewhere? - Do you think if AI is given control of some trivial systems that it could inadvertently snowball into gaining control of other systems and become a hazard to humans? - ​A recent study has linearly mapped the activation of an LLM to activations in the brain. Do you think that might be a hint that we may be on the right path? - Do you think an artificially generated intelligence (AGI) could achieve an economic equilibrium for humans? - The interesting difference of ChatGPT to actual intelligence is you can fool it easily with crafted input. - Is there going to be a spread of misinformation due to AI (deep fakes, etc.)? - As someone with allergies, being able to adopt an AI robot dog would be kind of cool! - Human wants are not a fixed set of things. They evolve as society evolves. - Do you think AI might just be a part of evolution like farming, the usage of electricity and smartphones (in the "extension of man" sense), and that we actually don't really have a say in it? - With a powerful tool like AI, how does the education system need to be changed to meet the needs of future generations? How do teaching methods in schools need to be revamped? - The question is, will the dog have the IQ to understand us deeply? That's the problem with AI: we might be like dogs in terms of our understanding of AI. We might not understand it, and that's the scary part.

Stephen Wolfram answers questions from his viewers about the history of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: What's the history of AI? What's the first recorded example of artificial intelligence? - It's amazing how well the movie 2001 still holds up. - What did pattern matching look like in the Middle Ages? - What's the relationship between "cybernetics" and AI? Is it simply a popularized naming or deeper than that?

Stephen Wolfram answers general questions from his viewers about science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Suppose I wanted to store digital data in a way that would be accessible to archeologists 10,000 years in the future. How could I achieve this? The best I can come up with is the awkward thin aluminum or titanium punch cards. Obviously, there would also be sheets of metal with plain writing on them including very clear and detailed explanations of how to build a card reader. - I wonder how vinyl would hold up? - Could Earth ever get a second moon? What kind of effects could this have on Earth? - What should we do today to help survivors reboot civilization after a cataclysmic event? - I always liked the idea of putting all of Wikipedia and other literature in glass and sending it on a 1,000-year orbit for future generations. - Is the fact that the Moon exactly covers the Sun during an eclipse just a coincidence? - Detecting the signatures of technology of other civilizations will be very difficult/impossible if they don't want them to be seen easily. Stealth/camouflage is a survival tactic in the wild. - The topic of consciousness should be explored further.

Stephen Wolfram answers questions from his viewers about the history of science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: 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 answers questions about business, innovation, and managing life. Topics include his favorite book, diving deep into various topics, maximizing productivity by working around constraints, balancing interesting work and making money, saving experiences and code review, evaluating computer time usage, establishing the Wolfman Institute, and understanding the foundations and building from there.

Stephen Wolfram answers general questions from his viewers about science and technology as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-qa Questions include: Could every exoplanet have a habitable zone if one could get just far enough away from the star? What makes a planet habitable? - Why do we measure sound using decibels? - What advances in synthetic biology do you think will happen in the short term, the long term and the very long term? Have you visited Ginkgo Bioworks in Boston? - AI-designed proteins that do biocomputation - These processes, in the case of life, exist in a coevolved physiochemical balance. That would be hard to reproduce. - How do you think space travel will change/improve as technology advances? Will it become a regular form of transportation sometime in the future? - When helicopters were first developed, people thought they would transform cities and be our new taxis. But they're too expensive. - On the subject of shorter travel times, I remember Heinlein suggesting in his books using suborbital rockets to travel between destinations. Would such an idea be too expensive for companies to run? Or would such an idea be feasible to cut travel time? - I think the cost and safety risks associated with space and underwater ocean tourism will keep them from ever being commonplace. - Now your perspective on what's possible for travel is different than the younger generations. - In relation to what you are saying about air travel, cellphones and computers, all of those technologies went through a long period (10+ years) of being luxury goods that only the richest people on Earth could use. The same will probably be true for space travel. Do you think that problem will get better or worse over time?

Stephen Wolfram, Innovator and CEO, answers questions about business, innovation, and managing life. Topics include: beginning the livestreaming journey, dealing with decision fatigue, owning up to bad decisions, task-estimation practices, unconditional confidence, strategies for collaboration, AI tools in science and mathematics.