Stephen Wolfram discusses various topics including the process of writing blog posts, compensation in virtual companies, defining writing styles, learning multiple languages, and the value of exposing children to a second language.

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: Do you think it's possible to sustain life on Mars? How far into the future do you see this happening? - Maybe biological switches would change everything for a biological machine. - Could you explain the fundamental principles of biology? - Aren't neurons the biological analog of switches? - Can machine learning help solve inverse scattering problems where the forward scattering problem is highly nonlinear? - How do x-rays work to see only the bones and ignore skin? - I think bone opacity also comes down to water contents (there is just more water in tissue). - Can those x-rays be used for automatic detection of changes within the molecule structure of crystallized solids as well? - Do you think ecology will play an important role in understanding molecular computation? - Ecology is a complex system. Physics is easy: just analyze a single particle's or body's motion. Ecology has vast interconnections and mechanisms.

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: Historically,​ what are some of the most prominent developments in the twentieth-century history of software design? - I watched the recent NASA rocket launch and wondered what's new in the past 60 years. - ​Why did American English develop common words for every third order of magnitude (million, billion, trillion)? Other languages seem to have different common words, like lakh in Hindi for 100,000. - ​I remember a comment from an old programmer saying the first time they saw a screen used with a computer was in the movie 2001. - Why is ChatGPT blowing up now when GPT-3 was known in 2020 and GPT-2 in 2019? - How much do you think real science and technology are shaped by the ideas from science fiction? - The thing about ChatGPT is that it uses the same architecture as GPT-3 with the same number of parameters. The fact that a fine tuning can create such a leap in capability suggests that we are in a hardware overhang. - Has there been any technology in history that's been perfected (e.g. the wheel), or is there always room for improvement? - Printers. Paper jammed 30 years ago, paper jams today. - Let's not ask the AI to design a new type of paperclip. - Paper jams happen today, but paper itself has become irrelevant. Such is the case with technology. Old technology doesn't get better, it gets replaced. - When and why was dark energy hypothesized? - Once we get 3D nano-replicators, we won't need roads; we can just teleport from place to place.

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: Can you talk a bit about Pangaea? How do continents shift? Is it possible to reform Pangaea? Is there technology that could prevent this? - How does ChatGPT work? - Could you say that Chat GPT has made a graph of the space of words or ideas? - I'd love to see a thesaurus based on vectors into semantic space, so you could ask it to give you a word with a meaning close to "A" but heading in the direction of "B." - How well does ChatGPT handle slang or figures of speech? Does it understand text as literal, or is it capable of picking up these notes? - Could it be that ChatGPT isn't accurate because its training data is text, which may or may not correspond to the real world? Shouldn't we use only real-world data, such as sensory information of sight, sound, touch, taste, smell? - With all the new "AI" tools rolling out, what do you think will be the effect on "truth" and "facts" as we know them? - Does ChatGPT's ability to mimic emotions means that it is able to feel anything, and how much consciousness does it have? - Do you believe physics boundaries need to be coded explicitly, or do you think enough data will result in the model learning principles? - How does a neural network experience time? How do all these threads of computation combine to form a whole from its parts?

Stephen Wolfram answers viewer questions about business, innovation, and managing life. Topics include the daily questions CEO's should ask, benefits of walking as exercise, using ChatGPT for writing, motivation in business, generative AI companies, managing email, finding focus in research, and open sourcing the Stephen Wolfram bot.

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 could Aristotle have accomplished if he had a modern machine-learning system? Could he have discovered logic? - Didn't Noam Chomsky also do some work in the intersection between math/logic and language? I wondered if language models are based on that at all? - Will the next generation of ChatGPT or VoiceGPT have any negative recourse, especially when it comes to impersonation? - A similar Chomsky idea is "can a submarine swim?" In English it can't, and in Japanese it can. - Do you think AI presents an existential risk? If so, how could we mitigate it? - How do you think Einstein or even Stephen Hawking would react to ChatGPT? Are there any figures in science who predicted this development? - Given what we have learned from AI models, does learning from history allow us to better predict the future? Does modeling the past imply modeling the future? - Ants are structured distinctly enough and that can lead to immediate conclusions on many levels.

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: Is it possible to produce large amounts of crude oil artificially by manipulating chemical kinetics? - How is the distance to a distant galaxy determined? - What industries do you think will be most disrupted by ChatGPT and Midjourney AI applications? - Thoughts on integrating the Wolfram interface with ChatGPT? - An automatic nonsense/false detector would be a interesting tool to have. - With generative images, Dall-E needs to be able to recycle its output image for incremental improvement. - Chat GPT will edit your e-mails into publishable books. - What are some of the most interesting ChatGPT prompts you've come up with that can aid in everyday life? - I've used ChatGPT to help give me ideas for movie scripts. - Couldn't the detector be used as a way to make the output of ChatGPT actually be coherent? Isn't the detector just the necessary component for ChatGPT to learn from its mistakes? - How could a language model be integrated with a symbolic system? - Stephen, do you think ChatGPT is over-hyped? Chomsky chuckled about the literally 60 years he's heard we're "on the verge of an AI Revolution." - Instead of training on text, wouldn't training on the senses that we use, such as video and audio be better? I suspect that a model that can predict the next video frame will be as intelligent as a human. Video contains text inside itself as well as other degrees of freedom that humans have access to. - Do you log all of your keystrokes, etc with the expectation that you will provide this information to an AI to try to understand your thought patterns? - I've used it to construct a 365-day nutrition plan I'm just having my first breakfast based on it!

The speaker reflects on a lost epilogue from 'A New Kind of Science'. They discuss the role of professional vs amateur science and the potential of studying systems based on simple rules. They also talk about their progress in working through unfinished chapters and archival materials. The online version of the NKS book is discussed, as well as the impact of cellular automata and the fourth paradigm. The emergence of computational language and its impact on ideas is explored. The next step in physics is discussed, along with changing paradigms and geographic distribution. The chapter ends with reflections on design choices and future breakthroughs in science.

In this episode of "What We've Learned from NKS", Stephen Wolfram is celebrating the 20th anniversary of A New Kind of Science with a look at the making of and current state of NKS in an ongoing livestream series, also available on YouTube here: https://wolfr.am/12aAqLklA

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.