The podcast discusses the creation of 'A New Kind of Science' and its 20th anniversary. It explores the author's transition to computational systems and their frustration with the slow progress in the research community. The speaker reflects on the history of building mathematical and Wolf language and the purpose of developing a science of complexity. They discuss their experience as a remote CEO and their exploration of cellular automata. The chapter also delves into experiments and observations related to complexity, patterns, and fluid dynamics. The speaker shares their experiences with researching fracture surfaces, collecting leaf samples, and various types of mollusk shells. They discuss the origin of patterns made from rules and the process of designing the book cover and choosing a title. The chapter concludes with reflections on internal drive and focus.

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: What causes snow? Why doesn't rain just turn into ice? - OK, Stephen really knows his stuff on this branch of physics... he's studied in detail. - Why is the density of solid water lower than liquid water? - Is there any other molecule that also expands when it is solid? - Why is the density of solid water lower than liquid water? - For ice skating, the ice melts at the contact of your blade so there is a small layer of liquid water due to friction, and hence it skates. - But you also can push and speed up on ice while skating, so an increase in the friction must have happened? - Apparently, gecko feet exhibit Casimir-like effects. - Stephen, if I may make a suggestion: you need a blackboard (or whiteboard) behind you for the explanations. - Is air a molecule? What is air? - Can you measure the absorption of CO2 by plants with this device?

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: Was the invention of computers inevitable? Will evolution always stumble upon universal computers, given enough resources? What are the implications for the laws of physics and reality? - I don't think computing technology could have possibly been conceived until after the Industrial Revolution. - ​Ideas alone don't govern how science evolves. It's a combination of factors, including technology, mode of production of society, etc. - The Sun's computation helps sustain us. - I like thinking about machine learning as a black box that gets to a human-comprehendible product, but the "reasoning" that enables it to get to that output is not really understood. Once we understand what's really going on in a machine learning model, we can be confident that its output is sound. - I started playing chess lately and I noticed that high-level and machine chess are a lot like proof of computational work and willingness to commit it. Do you have any thoughts on this? - I wonder how much power one would need in order to run a mechanical computer comparable to a modern CPU. - Historically speaking, do you think the modern AI systems are unique in terms of replacing human work, or just another step in automation? - ​I may change my email signature to "Written by ChatGPT. Please excuse any nonsense." - It's tempting to think general AI could emerge from some digital version of evolution. That seems to require digital entities competing for resources and a "will" to fight for survival. - Historically, how has written record keeping evolved? Will we ever revert back to oral records (spoken stories, songs, etc.)? - GPT-4 and GPT-5 are going to be amazing. - The question is whether the interviewer will care if the candidate is an AI. For some roles, it will not matter, and that number will increase. - Has ChatGPT passed the Turing test? Or can it pass the test soon? - I suspect the major deployment of AI in the short term will be phishing. For the time being, it can't replace regular employees at legitimate businesses because it can't be legally held culpable because it's not conscious. But for scammers, that's not an impediment.

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 you discuss the importance and relevance of ChatGPT. I find it astonishing. I am also wondering the extent to which its principles might inform Wolfram|Alpha simplified input. I'd also love a Wolfram ChatGPT interface. -  Is this livestream generated in realtime by a Stephen bot? - Wouldn't AI develop its own language that we won't understand? - What's the success rate of ChatGPT-generated code? Of course it depends on what code is widely available on the web. - Isn't there a feedback loop problem where the future language models will be trained on AI-generated text? - Oh, that also is good fun: At the beginning of a chat, you can prime ChatGPT to talk in certain ways (Texan southern, London slang, Jamaican, Creole, etc.) and it is so funny! - ChatGPT works across a bunch of languages quite well. ​For inputs and outputs. -  ​Is it possible to extrapolate what future neural nets will look like? Can they ever become as sophisticated as a human brain? Can they eventually become conscious and self aware? - The most mind blowing experiment was where ChatGPT imagines being a Linux machine and converses in "console." - In my experience, it was very hard to do actual "small talk," as ChatGPT either goes into "I'm only a language model and can't..." mode or the conversation gets very "not small" quickly. - The natural language interpretation of Wolfram|Alpha is so well refined that I really need to just crack open my voice assistant device and hack it to divert input to a kind of persistent personal notebook. -  I was able to get ChatGPT to write a graph programming language in JavaScript that fulfilled the full lambda cube. - There is a recent AI model that uses the image diffusion model to produce music via spectrograms. - So perhaps Meta could train a language model on its content from Facebook and WhatsApp (privacy issues aside) to be great at small talk? - Would you be willing to get a Neuralink implant at some point in your life? What would convince you to do so? - The first thing I REALLY want is a simple brain-keyboard. That would be awesome. - ​What are your thoughts on AI connecting to blockchains? They theoretically could become independent from humans. - The AGI of the future will be a comedian and heavily active in advertisement. - "Ownership" might even be an ethereal concept challenged by AI. - ​AI students...learning from AI professors?

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include:What are your thoughts on operational systems and how they impact personal productivity? Have you ever used Microsoft Windows? Could you tell us a bit of your computer setup (OS, productivity tools, files sync systems, etc.)? - With consistent routines and self-tracking, have you developed a strong intuition for how many keystrokes you've made in a day or how many steps you've taken in a day? Other Wolfram-y intuitions? - I'm working on an IRC-client for my old Tiki 100 computer. I will only use IRC on that computer. It has to send signals to the PC that reroutes it into IRC though. But it should work. - The Tiki 100 is a Norwegian computer released in 1984. It has a Zilog Z80 processor and 64 KB RAM and some chunky video framebuffer. - ​Would you be able to go back to pencil and paper? Like pure research? - My first experience on a computer was the Commodore 64 playing Oregon Trail. Did you ever program any games? - Do you have any career advice/job seeking advice? I graduated, and searching for a job is quite slow. I've also been considering starting some sort of (3D printing) business instead but don't really know how I can gain the skills for that. What made you start a business? - How do you manage the "holiday madness" around this time of year (packed stores, more drivers than usual on the roads, house full of family)? - How do you apply computer science, 500+ employees, new kind of business to architecture and city planning for billions? - Do you ever feel like you spend too much time managing people instead of solving technical problems, or is the balance just right? - Is it safe to say a business is a machine made of people? - How do you decide balancing effort towards invention vs innovation? Not just your own effort and time but also the Wolfram organization. - Can this sort of scaling (employees needed for a functioning company) get modeled and planned by your technologies? - I guess sub-projects are a good thing to have when doing projects that involve more than one person. - ​As technologies become more and more complicated, do you sometimes feel a sense of losing control, or that it gets really overwhelming to try and understand how everything works? - ​How do you encourage people to envision a positive future when things aren't currently going as they expect?

Jonathan Gorard joins Stephen Wolfram to discuss ongoing science research. They explore the concept of rulial relativity, the distinction between normalizing and strongly normalizing systems in term rewriting, decidability and primitive recursive functions, non-terminating rewriting sequences, evolutionary perception and course screening, regular patterns and proof theory, observers in computation, randomness and complexity, primitive recursive functions and limited number systems, linear logic and sub-integer set theory, state and event canonicalization in multi-way systems, gravitational radiation and bronchial space, defining fluid velocities, and functoriality with a geometrical interpretation.

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: What is some history of thermodynamics you found interesting while working on your new project? - What is the history of mathematical rigor? - What's the history of chocolate? What technology allowed the creation of chocolate candies to become so popular? - In the history of computer architecture and software, who are the most important pioneers of parallel processing? - Did you ever use Xanadu's network communication/hypertext publishing technology? - ​Can you discuss the history of GNU? - How much more prevalent will cloud computing become in the future, as the need for computational resources is exponentially increasing compared to the cost-speed of processors? - Can you talk about the history of the public's perception of its own scientific literacy? - I think it also changed with the advent of memes, which made the most important subcultures swim up more easily than less important ones. - Will we go back to science illiteracy?

Stephen Wolfram answers various questions about the history of science and technology, including topics like thermodynamics, mathematical rigor, the history of chocolate, pioneers of parallel processing, the history of GNU, the future of cloud computing, the public's perception of scientific literacy, and the consequences of memes on subcultures.

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: Are there nuclear reactions going on inside our bodies? - Do you think we'll ever be able to replace damaged brain parts with computational parts as another form of prosthesis?   --  What ethical implications will become relevant when we combine machine learning and brain sensors/effectors? - Suppose a rule creates a memory in our brain. Then it could be an irreducible problem to make a true brain interface for any individual that could interpret a memory or preexisting concept. Truly a fascinating subject. Assuming we are able to completely understand the human brain, one could probably make a complete copy - basically, we could "fork" one brain into multiple copies! - Do you think neurons do their signal processing based mostly on discrete states or the temporal difference between states? - Even though all brains are different, don't they all "implement" the same underlying ideas? Doesn't this point to some Platonic realm of reality? - One of the issues with being able to read and decode a memory is that someone will have the ability to write artificial memories into a brain. It's somewhat scary to think that could happen one day, but it could also be used for good. - What about a Turing test, but for memories; like in Inception? - Perhaps the only difference between dreams and reality is just a matter of degree? Perhaps it just depends on its logical coherence? Once the logical coherence is larger than what the brain can be aware of, it is considered "real." - We've co-evolved with our environment so it should be coherent to us, but if we inject things into our environment that we haven't co-evolved with or evolved in, we get confused.

Stephen Wolfram answers questions from his viewers about business, innovation, and managing life as part of an unscripted livestream series, also available on YouTube here: https://wolfr.am/youtube-sw-business-qa Questions include: Is it worth moving to the USA from the UK/Europe to pursue a career in science, mathematics or engineering? What if one wants to change the world? - How long should one wait after college to start some startup in an area of their interest/expertise? - When you are thinking deeply about a problem, do you think "on paper" or on a computer or a tablet or...? Do you find one of them to be better than the others? - Can you tell a couple "stamp-licking" stories from the early days of starting Mathematica/Wolfram Research? - What are your thoughts on crypto and blockchain from a business perspective in general? - What do you think have been some of the most interesting and hard questions you've been asked here and elsewhere? - Can ChatGPT increase productivity? Is outsourcing writing skills beneficial or damaging? - "AI did my homework" is the inverse of "the dog ate my homework." You don't want to be in either situation! - Visual AI can produce amazing inspirations for jewelry and that sort of intricate art. - Do you drink caffeine sources like tea or coffee? How many per day? - What practices do you use to gauge and cultivate meaningful accountability as an individual and as part of a collective? - ​What was your revenue plan and time-to-revenue when starting your company? - We know that you use a hierarchical knowledge organization (files in folders) but did you ever try to use a networked knowledge organization (e.g. Logseq, Roam Research, Mem.ai, etc)? Thoughts on the best way to organize knowledge? - Wolfram documentation is amazing because it's connected (related functions). - I think the knowledge graph thesis is to give people epistemological tools and make it visual. But epistemology isn't something people worry about all the time while writing daily notes. - Have you "driven" a Tesla in Full Self-Driving mode? It's out now for beta testing and it's magical. It's so, so good. Purely a vision + neural net implementation. - Do you enjoy collecting and organizing physical books? Libraries are endless fun!