Business, Innovation, and Managing Life (January 3, 2024)

Okay. Hello everyone. Welcome to another episode of Q and A about business, innovation and managing life. I am not in my natural and usual habitat, so all sorts of terrible technical things might go wrong. But we'll, we'll see how, how we can get on here. So let's see, I see a bunch of questions that have queued up here, so let's see what I can take here. There's one from Ben. What have been some of the most fascinating questions you've answered. Are there topics still to explore? Oh boy. I'm a difficult one to ask that question of because I've spent my life working on kind of foundational questions about science and technology and so on. You know, a very, very fundamental question is sort of what's the raw material from which our universe is made? And in the last three and a bit years we've made tremendous progress on that and understanding sort of computational foundations for the structure of physics and so on. And now one of the things that's come out of that is the realization that the way we observe the universe is critical to what we perceive the laws of the universe to be. And so there are a lot of questions around that that I've been pretty interested in. At a broader scale. I have an interest in foundations of almost everything. How physics works foundationally, how mathematics works foundationally, how computation works, biology, economics, lots of different areas. And kind of, I think in a sense the sort of arc of my life at least has been sort of trying to do foundational things in science that inform foundational questions in technology, building tools from technology that then let one explore more in science. And so, for example, in our development of Wolfram language and our whole sort of making computable the world, it's all about kind of this question of how can we think about the world foundationally in computational terms. And I find these kinds of questions, these kinds of foundational questions really interesting. But it's also the case that they're very long term questions and they're questions where a lot of these questions I've thought about for 40 years, more than that. For example, recently I, I finished some work turned into a book on the second law of thermodynamics, the law that tells one that things that start orderly tend to become more random. That things where you have initially sort of systematic mechanical processes going on, that the energy will be dissipated as random heat, that's the second order of the dynamics says those things. It's been very confusing for the last 150 years. Kind of why the second law is true and how that all works. I think I figured out sort of scientifically how it works, which is kind of exciting. But the thing that is notable is I started thinking about the second law in 1972 when I was 12 years old, which means I'm ancient now, but it really took 50 years actually before I got to the point where I thought I really had a, a good explanation of what was going on there. It's a very long term thing. And thinking about these foundational questions can be very, very long term. And a lot of the things that I think are really interesting to figure out and which I think we can make progress on in, for example, the foundations of economics, the foundations of biology and so on, are things which I've thought about off and on for many decades. And I've gradually sort of accumulated more knowledge about these things. And you know, it's funny because I find that once I start thinking I'm going to pay attention to some particular field like let's say, biological evolution. I've paid attention to biological evolution since the early 1980s, theories about that, et cetera, et cetera, et cetera. You gradually, once you decide there's an area you're interested in, at least for me, I'm gradually picking up more and more information about this area. And as I go around the world and I talk to different people, it's like there'll be this person that I talked to 15 years ago when I learned this one particular thing that was interesting about biological evolution. I kind of put that in the bag of stuff that I know about that area. And then at some moment it gets sort of to the point where I say yes, I can really dig in and start seriously working on this and making progress. And I tend to, as an organizational matter for myself, I just have folders on my computer where, you know, when, when I get. So when I hear about something interesting, I'll make some notes, I'll stick it in the folder. When I see some paper or something or whatever in that area, I'll stick it in the folder. And then when I'm finally ready to really get going in that field, I'll go through everything that I've collected. And in fact, sometimes I'll go through it at intermediate stages. I was, I was just doing that, looking at some, some things related to the question of, of how well AI can contribute to science. I've been collecting things in that area for a long time. I was just, just yesterday actually looking through a bunch of the things that I've collected in that area to try and sort of refresh my. Develop my intuition to the point where I can actually go in and really start doing sort of serious work there. And so, so for me, at least, that's, that's been the, the thing. And, and there are, there are these areas like, I don't know, nanotechnology, you know, how do you, how do you make molecular scale stuff work? Which I've been interested in for a really long time. It's not quite gotten to the point where I can say I, I kind of. Where I'm. I'm ready to jump in and really do things in that area. Getting close, but it hasn't quite gotten to that point. So that's kind of been the rhythm of things I've done. And I have to say, I find it, you know, once, once I'm sort of primed to say this is an area I'm interested in, then it's really a useful thing to know those. This is an area I'm interested in, I might do serious things in. Because then as you go around the world and you're talking to people, you kind of know what you want to. What information you want to collect from them. Otherwise, it's like I run into somebody who's doing, I don't know, evolutionary biology, let's say, say, and it's like, well, that's very nice, and I can have a little discussion about it, But I don't really. It doesn't really. It doesn't really engage in my memory unless I have, for me, at least, unless I have some anchoring question that I'm trying to think about. In the case of evolutionary biology, it's kind of, what's the big theory? How do we really think theoretically about evolution at more than a descriptive level? So just a few thoughts about that. And I would say that in this question, are there topics still to explore? One of the things that, as a consequence of science I've done is there will always be an infinite frontier of science. You might say at some moment, everything about science will be figured out. Let's say we figure out the fundamental theory of physics. I think we're pretty close to that. Is that the end of science? Well, no. And the reason is a piece of science. It's this phenomenon I call computational irreducibility. Just because, you know, the rules by which something operates does not mean that you could immediately kind of jump ahead. And so, okay, then I know everything about that thing. You have to follow through these rules and see what their consequences are. And Sort of there are infinite potential consequences. So in a sense, there's always sort of an infinite frontier of things to discover. And another way to put that is that a lot of inventions, a lot of results in science and so on, are about kind of finding places where this whole computational irreducibility of what will happen, little places where you can jump a little bit ahead. You can use a little. A little sort of pocket of computational reducibility. And there are an infinite number of such pockets. In a sense, the inventions we make that allow us to take kind of the. The physical world and do useful things with it kind of we're jumping ahead. Instead of saying, oh, we just have a bunch of different kinds of atoms of this and that and the other, we say we have a smartphone made of all those atoms. The smartphone then allows us to do more things. And having that aggregated thing that we've sort of identified and put together, that's the thing that sort of is a island, a way to jump ahead from just having to follow through each of the details of what we do with each of those individual atoms. And it's sort of a fundamental feature. It follows from sort of very foundational issues about how computation works. In some sense, you can think of it as following from things like Godel's theorem from 1931 and the concept of universal computation, maturing machines, and so on. But there's sort of a bit of a stack of ideas that I suppose I've worked on a lot that really take you to the point of realizing there is sort of an infinite sequence of inventions and discoveries to be made. The only thing that's an issue is will we humans care about all those things, or will we get to a point where we say we know everything we care about, we're just going to lead our lives only dealing with that sort of sub part of the world that deals with things we already know about. Turns out that won't work, because. Turns out that the way the world operates, computational irreducibility eventually impinges on something where you thought you had this closed set of rules about how the world should work. It's kind of like I invent a set of laws, and I say this set of laws is going to describe everything that's going to happen in the world. It's going to tell me what I should do and shouldn't do. It will always be the case that eventually something that just naturally happens in the world will give you a case that wasn't covered by that sort of closed collection of Laws. So it's sort of inevitable that innovation is both possible forever and forever going to be forced upon one. But I think it's still sort of at what rate and how that works does depend on what humans want. I mean, in other words, if humans decide we're done with progress, we're just going to go hang out. We've got, you know, there are certainly cultures in which that's happened. Right now. It's like we're really happy. We don't need electricity, we don't need this, we don't need that. We are happy as humans doing some particular set of things that is sort of a limited. That thing which doesn't break out into this new area of innovation and progress. And, you know, there are other people like myself. I'm always interested in kind of the new, or at least I have been my life so far. It's always that the new always takes more effort than the. Than the current, so to speak. The new is both, both, I suppose, exciting and enriching, but it also takes effort to do new stuff. And there's a. There's a tremendous tendency for everybody, including myself, to say, hey, I know how to do that. Let me just keep doing that. For me in particular, I've. I just find it so exciting to see new things, so to speak, new intellectual vistas, so to speak, that I'm always driven to, you know, even if it's like, yes, I can do that, I can do it well, it's kind of fun, but it's like, but there's another thing to see. And I'm always, I'm always, you know, I happen to be built in such a way that I'm, I'm always interested in that. Let's see, Joey is asking what are the biggest opportunities and challenges facing businesses in our industry in the next five years? You know, I think the business that I'm in, in a sense, is trying to make the world computational, trying to make it so that we have this way of thinking about the world in kind of structured computational terms and trying to provide a language and a system that allows us to make use of that thinking. I would say the biggest challenge in my world is for people to understand this computational way of thinking about the world. It's kind of like there was a time when people learned logic and that was a way of thinking about the world. There was a time when people learned mathematics. That's a way of thinking about the world. This computational thinking idea is a tremendously important way of thinking about the world. And It's a question of how do people learn that? How do people conceptualize the world in this new way? And I spent the last 40 years building our computational language, Wolfram language, that is a language for letting you decide, describe things computationally. Kind of like mathematical notation is in mathematics. It's kind of a thing for concretizing computational ways of thinking about the world. And I would say that both the biggest opportunity and the biggest challenge is for people to really understand that computational way of thinking. It's an opportunity because every field, basically, it's a way of structuring one's thinking of about every kind of field and making systematic progress with the help of computers. And it's tremendously, tremendously powerful. I mean, computational X is for all. X is kind of the future of everything in terms of intellectual development. I mean, imagine that we didn't have mathematics as a way of thinking systematically about things. We wouldn't have most of modern engineering, and we wouldn't have just vast pieces of the modern world. But mathematical thinking is a small subset of computational thinking. Computational thinking is this tremendously powerful thing. Question is, how do people learn this stuff? And as I say, I've tried to do my bit in the last 40 years developing our computational language as a way to concretize computational thinking, but it's still a big kind of societal issue. Like, how do you teach people computational thinking? The efforts to do that, that say, oh, you should learn programming, well, that isn't really the same thing. Learning how to make a computer go do a loop of operations or set variables or whatever else is not the real story of computational thinking. That's a story of how computers work inside and how we connect the things we want to do to some aspects of how computers work inside. It's a. Computational thinking is a much more, much more general way of thinking about the world. And for example, I'm trying to do a project right now of trying to write a sort of book and course and so on about computational thinking. I'm only on about page. I don't know how many pages it is probably about page eight or something of this project. So still early days, but it's been interesting to see kind of. I thought, well, you know, I'm sort of frustrated that I have to do this myself because I figure that lots of other people who have, through our computational language and so on, understood things about this area. But I'm. I'm ending up doing it myself. But as I get into it, I realize it's actually quite difficult there's actually a lot of sort of rethinking of how one presents things, thinks about things and so on. That's necessary to really broadly express computational thinking. But this is, you know, this is something that's far away from what is taught sort of in education system. It's something. Well, that's the thing. If people really understood this, this would be tremendously valuable. Now I think it helps, you know, LLMs being able to write some computational language code from much vaguer kind of sort of natural language. That's certainly helpful. It's kind of a follow on to, you know, in Wolfram Alpha we're able to take sort of small snippets of natural language and do very precise things with them. AIs and large language models take big complicated chunks of language and don't do such precise things with them, but can sort of untangle them in certain ways. That's pretty useful as an on ramp to sort of this precise computational way of thinking. So that's sort of an opportunity, I think the, and that, you know that there are many more detailed pieces to that of sort of. To what extent do the LLMs end up being these kind of large scale cloud based systems as opposed to things where it's just the little linguistic layer and most of what's there is the linguistic layer on top of kind of the computational system underneath and that, that becomes a thing that you can, you know, run on your phone or whatever else. So I think those are, those are a few directions there. Let's see, all kinds of questions here. Well, Apollinario is asking what are the best approaches to develop a sound computational thinking? Are there good books and courses? Well, that's what I'm trying to write. So thank you for asking that question because it's a helpful motivational statement. But you know, I think right now there are endless examples of people doing things with Wolfram language that are pretty good examples. And you'll find that, oh, I mean sort of a rather practical piece is the book I wrote in 2016 called elementary Introduction to Wolf and Language. But that's, that's a, that's at the more practical level, that's at the less conceptual level, but that's a good kind of on ramp to this. And then looking at a bunch of the things people have done on Wolfram community and other other places with the language. Let's see. Question here from 1h. I can never decode these, these handles. Quite an interesting question. Are there fields, you know, have depth but don't Interest you at all? Yeah, fortunately, lots. Because otherwise, I mean, one has to pick one's battles. I mean, I have picked off some pretty big things like, like fundamental theory of physics or foundational ideas about computation and so on. But there's, you know, there are, there are things where I know there's a lot there and I just don't know it. I mean, for example, politics is an area where I just, I don't know much about it. I, you know, I have only a tremendously sort of superficial level of kind of news following type thing. And you know, there are clearly lots of it. I know a little bit about political philosophy, but that's, that's, but that's an area with lots of depth of some sense, I suppose in, in, you know, as I'm, as I'm thinking about this, I'm, I'm. My immediate response is, oh, there are lots of things that I don't know about. You know. Another area that there are a lot of kind of. You might think of them as not very sciency type areas, but like fiction, for example, is something about which I know rather little and I don't really. Not something I expose myself to terribly much and I just don't know much about it. But in terms of sort of more sciencey areas, what are some areas? I don't know. There are areas of engineering have lots of depth and where I'm like, yes, if I ever needed that, I would try to learn it, but I don't know it right now. And you know, I'll typically know the kind of physics end of that piece of engineering, but not, it's, but not kind of the, the full story of how you really do it. Gosh, I'm just trying to think of different areas. I mean, another area that I was. Yeah, I mean the, this is, this is actually a worse question for me than I had, that I had imagined as I, as I picked it up to try to answer it. Because in fact I really am interested in an awful lot of different things, although I haven't gotten very deep in many of them. Another area I haven't gotten very deep in is music. Lots of sort of theoretical depth there, which I don't, I mean, I know a little bit about it, but I don't know. You know, there's, there's clearly a lot of depth that I haven't, haven't penetrated and where I, I am, you know, it's kind of like if one had an infinite lifespan, one would, I would be interested in all these things, but One has to pick one's battles, I suppose. And I've tended to, you know, what I tend to do is to, you know, what are the criteria first? Well, lots of things I find interesting, but they're things where I think I can really make progress and where I'm not going to be waiting for some ambient, you know, technological or sort of issue in the world to resolve, where I might have to wait for 30 years for that to resolve. I mean, for example, when I was a kid in the 1960s and so on, I was interested in space and I got, you know, interested in how would you design spacecraft, things like this. And thank goodness I didn't stay doing that because I would have been waiting for 50 years. Was kind of the ambient structures in the world to develop to the point where one can really sort of, where an individual can innovate in things to do with space. And so, you know, one criterion is, is it the right time? Is the world sort of set up? Is the ambient technology and knowledge and so on to the point where one can really actually make progress? Where one person or one person plus maybe a company of 800 people or something can make progress? Or is it something which requires a heavier lift, more time, more resources than one can marshal to get at it? That's, that's one kind of criterion is sort of can one make progress? The other question that has some effect on me is if I make progress, is there any way of telling the world, is it the case that the thing one's making progress on is there effectively a distribution channel for the ideas? And I have to say that hasn't affected me as much as perhaps it should have done. But, you know, for instance, I don't know. I wrote this book recently about metamathematics and there's no market for metamathematics. I mean, there was a big enthusiasm for metamathematics in the 1930s, 1940s. Most of those people are long gone. There's certainly interest in metamathematics, but it's not the professional, you know, if I say what's the market size of professional people interested in that? It's microscopic. If you ask what's the set of people in the world who have a sort of philosophical conceptual interest is much larger than that. But it's still the case that sort of a market driven analysis would cause one not to work in that area. And there certainly are areas where I wonder about that. So, for example, another area I've been considerably interested in is kind of AI. I don't Know what the right word is? Management, governance. I don't know what the right word is. AI. Sort of how one thinks about sort of AIs in the world and their interaction with humans and society and so on. And you know, some of what I think about there has the sort of frustrating feature that okay, I figure out something about, you know, sort of the AI future of democracy or something and I realized I don't know what to do with this because you know, there's so many strong kind of opinions and ideologies and so on in these areas that if I say well, I've got this, I've got this idea over here and it has some kind of technological entanglements, it's like no, no, no, that, that violates this ideology and that ideology and it's kind of very unpleasant. You know, one has to figure out how does one, how does one do something in this area without just, you know, sticking oneself into something where there's just a, you know, intense, intense fighting going on all the time. You know, I had this experience actually I wrote this book called the New Kind of Science that came out in 2002 and sort of one of the use cases of the new kind of science had to do with physics. And I'd been involved in physics, I'd been a professional physicist, so to speak, a number of years earlier than that. And in the world of physics pretty universally the tools I built get used by people. So I sort of had, and I had many friends in the physics area. But yet back in 2002 physics as a field had sufficient self esteem or arrogance you might say, to say we don't need a new approach to physics, we've got great stuff already. And so the response from my friends in physics to the things I was sort of a new foundational directions was very negative. And so, you know, I decided at the time, I'm not going to work on this right now. I've got a zillion other things to work on where kind of the I'm not, I don't have to fight. People might not, you know, nobody's going to aggressively fight back. It's really a question of build things and the world might care, the world might not care, I can feel good about them and so on. Now happily, 15 years or so later, when I came back to working on physics, physics as a field had tanked in terms of self esteem because it really hadn't a lot of things and things like string theory and so on hadn't really worked out the way people had hoped a very different response. Very much more, you know, very much more collaborative and, you know, much pleasanter to be around, so to speak. And so that's a. That's a reason to now, now explore that area. And we've been very successful there and it's all good. Let's see, Just comments saying a person that easily gets distracted. Jack of all trades, master of none. I envy people that dedicate their focus on a specific field to become an expert, but I fail to do so myself. As I'm getting older, I still dabble around and try to find my thing. Still. Do you, Is there. Do I have a suggestion for an approach that can make one more focused in a single field without that initial spark? I have a very maybe optimistic view of people, which is that we all have certain characteristics and we're all kind of naturally built different ways. And I kind of feel like we all have something going for us and the question is, can we match the thing that's going for us with things that really work in the world as the world is? And I think it's a question of if you are a person. I know people who are like, I'm doing one thing, I'm going to do it my whole life. It is one very specific thing. I'm going to be the world expert on that thing. And that's my thing. And that's a way of life. There's a different way of life which is I'm interested in lots and lots of different kinds of things. Now, sometimes the interest in lots and lots of different kinds of things allows you at some moment in your life to realize, oh my gosh, there are 20 different areas that I've been interested in, and now I can pull them all together and make them into something great. And I've seen that a number of times. I suppose a person who, I'm afraid, didn't like me very much, but that's beside the point. A chap called Vanuat Mandelbrot, inventor of fractals. He was in a situation where he'd done many different random things in his life. And at some point he was writing this book which became a book called Fractals, where he was trying to pull together all these different things which really actually were not that convincingly fitting together. But he managed to find a theme and the theme was very strong and the theme was an important contribution to science. But really he'd been a dabbler in lots of different areas and somehow he managed to pull out of all that dabbling A theme. So I think, you know, one exercise is, if you've dabbled in many different areas, is there in fact a theme? Because many of us actually, you know, I've worked in a lot of different areas, but in a sense, the way I've done it has always been the same. It's always this kind of look at foundations, build up from foundations. It turns out there's a lot of commonality in the foundations that I'm using and that allows me to understand more and to build, build something bigger out of all those different areas I've been working on. So I would say that the first kind of thing for the dabbler is, was there a common theme? Is there a common theme? Can you pull that out and then realize that all these things that you thought were unconnected actually become just sort of legs in this big thing that you're building? That's one thing. Another thing is there are different sort of activities in the world where dabbling is what matters. I mean, if you're like, tell me an interesting thing. One, you know, one interesting thing every day. If it's always about the same topic, that's less interesting to people than if it's about lots and lots of different topics. I mean, similarly, you know, there are different kinds of professions, whether you're, you know, doing expository writing about different areas, where it's like, oh, well, I want to dabble in this area for two weeks as I write about that, and then I'm going to work in some other area and so on, and you're delivering a portfolio of things. But in terms of, of sort of the one true spark, what I've noticed is that people, I suppose I've the. For me, it's like I'll notice things and then I'll be like, I'm really excited about that. I'm going to chase that. But one thing that can happen is that the world sort of evolves and different opportunities come along. Like, you know, if you really wanted to be a prompt engineer before there were LLMs, Prompt Engineering wasn't a thing. You know, if, if you were like, I'm a good expository writer, I really want to be an AI wrangler using my expository writing, that wasn't a thing until LLMs came along. So what tends to happen is things, things evolve in the world and something new comes along. And what I've noticed is that there usually is a set of people in the world for whom that new thing that came along is the thing for those People. And those people might be. When it comes along, they might be 20 years old, they might be 60 years old, but when the thing comes along, it's, you know, they kind of notice that it's their thing, they grab onto it and then they have an exciting ride. And one might be more and less lucky that in the span of one's life that the thing that really is the thing one resonates with comes along or doesn't come along. And I think that's the. But one of the things that's important there is to be kind of watching the scenery, so to speak, well enough that if the thing does come along that you can grab onto it. Now, sometimes people are not in a life situation where they can really go whole in, you know, whole hog into this particular thing. It is always worth remembering that, you know, one does have sort of, you know, in most situations, people have sort of the hobby time, the time when they might have been watching television or something, but where they're, you know, they could be pursuing something that. That is an intellectual interest. And that's always a. Tends to be more of a possibility than people sometimes, sometimes would say. Let's see. John asks, how do you keep track of what you want to learn and how do you manage your time effectively so you dedicate ample time to each of the things you want to learn? I can only learn when I have a reason to learn, really. I mean, I learn a little bit by just talking to people and just reading random articles about things just because, oh, I happen to run across it. But serious learning I can really only do in response to something I want to do, some project or something like that. And for me, it's pretty concrete how I keep track of these things. I just have folders on my computer, like 50 of them or something that are the things I'm trying to sort of. I'm circling around, getting ready to really get serious about. And that's kind of my mechanism for that. I think, as I was saying earlier, there comes a point where I get really serious about a project, and I'm very intensely focused on that for however long it takes to make it happen. But before that time, I'm kind of just circling, just sort of collecting things. And I don't really set myself any particular timeframe because it's kind of like I might run into somebody who happens to be a world expert on this, and I can ask them the key question. And maybe I didn't even know what the right question to ask was, but something that they said Kind of tipped me off to this is the question I should be asking. And I'm off and running there. I don't really budget that time because I just don't know what I'm looking for. And once I'm actually locked in on a project, well, then I'm much more serious. And. And then, you know, one of the things about projects actually, particularly projects I do. So there's like, okay, I'm trying to solve this problem, let's say. Then there's a different issue, which is am I going to do it as a scholar and am I going to know the history of the field? Am I going to know all the sort of academic tentacles of the thing? And that's actually a slightly different project from just doing the project. I mean, when you do the project, sometimes it's like you, yes, I want to know what other people did, because that's going to help me. Sometimes it's like the thing I'm doing is just too far away from what anybody else has ever done. There really isn't going to be that much useful stuff, almost certainly. And so to know what the connections are is really a matter of scholarship rather than a matter of necessity for doing the project. And sometimes I've. Sometimes, for example, the project I did on the second law of thermodynamics, the things that I was saying was sort of sufficiently radical that I wanted to check that, you know, the conventional wisdom. Why do I disagree with the conventional wisdom? Where did the conventional wisdom come from? So I was highly motivated in that case to really do the scholarly deep dive on the history and so on and piece all those things together. But that's sort of a separate branch, I would say, from. From the. From the project of just sort of getting to the answer, so to speak. Let's see. Eddie asks, do you have some activity to calm your brain down after perhaps a long day of concentrating to wind down before you go to sleep? I'm a very habitual person. So I go to sleep at a pretty much a fixed time of something past 2am local East Coast US time, kind of wherever, more or less wherever I am, unless I'm sort of in some really exotic time zone where I have to kind of randomize myself for hopefully not too long. You know, I suppose it has been for me A. The fact that I'm sufficiently habitual means, oh my gosh, you know, by that time it really quite suddenly, you know, very specific time. I'll usually be like, I'm working along and I'm just. I'M just gonna get tired and then I'll fall asleep. And I suppose one thing, this is a, maybe a too much information, personal sort of thing. I, When I was a, a kid, I, I kind of, I used to be too revved up. I couldn't sleep and so on sometime I was maybe 14, 15 years old, I just decided I'm going to learn to sort of relax. I lie on my back, close my eyes, and I sort of taught myself, okay, I kind of switch off and go to sleep. And I suppose I taught myself too well because, you know, if I'm like going to a dentist or something and I'm tipped back, I'm like, I, I always have to apologize. I say I'm probably going to fall asleep because I've sort of set myself this kind of reflex of, in that. I don't know, I don't know. I don't know whether what, I don't know whether this is something everybody could do or whether it's a sort of a special to the way that, that I'm built. But I found that, that having that sort of both the, the general habitual thing of timing and also the specific. Oh yeah, well, I'm, I'm just used to the fact that if I, you know, lie, lie flat and I just, you know, I just fall asleep and that's, that's just what I do. So if I'm. Actually, there have been other situations where I don't know, in, in different, different kinds of situations of one reason or another. I'm lying flat and it's just like I, I fall asleep. I find it, I find it very hard to stay awake in that situation. And so that, that's, for me, that's, that's what I tend to do. And I, I, I've not, I really haven't done any of the things that people say about, you know, changing the light levels that you have and this and that. I really haven't done any of that. I supp. Eating, you know, dark chocolate shortly before I go to sleep because I figure that probably is a bad idea, but, but, and I, I'm not a coffee drinker or anything like that at all. So, so that's not really an issue for me. But that's, that's my, you know, habit is my main, my main mechanism for that. And I do think that the other thing that I have noticed is the one absolute. It's probably true for most people if you're kind of, you say I'm going to go to sleep and then I'm going to keep thinking about this thing that I was thinking about. Oh, and I have an idea about it. It's like unless you write down that idea, you're not going to be able to fall asleep because you're kind of looping saying, I'm going to maintain that idea, I'm going to maintain that idea. And you know, at least for me, it's like you write it down. Okay, we're done now. Now you can fall asleep type thing. Let's see. Pastor asks if you learn to surf, something I've never done, then you wait for the right wave. What was the wave that I caught that, that kicked off my career? Yeah, I mean, there's a definite answer to that. I was, when I was a kid, aged about 10, 11 or so, I got interested in physics and it so happened that by the time I was like 13, 14 years old, physics was really in a golden age. A lot of things were getting discovered and I kind of, you know, I surfed that wave basically because, and it turned out, you know, when there is a young field, physics wasn't a young field, but there was a. Particularly when there's a young field, if you're, you can enter that field with fairly low cost because there's not a lot to know. It's not a giant stack of, you have to learn all this stuff to be able to contribute. You can enter that field and if you kind of hit it at the time when it is in its maximum vibrancy, most fields of intellectual fields, technological fields, actually go through these kind of five or ten year intense periods when something opens up, some new method is invented, some new technology, whatever else, and then there's a whole bunch of low hanging fruit to be picked. And it's five or 10 years worth of low hanging fruit. And at that time it starts very small, not very many people know to pick that fruit. Then people realize there's a lot of fruit being picked. So lots of people go into that area and then all the low hanging fruit gets picked and then it's a long hard grind. But at the point where there's just early fruit being picked, typically that area is not that visible. And you know, so you have to be kind of alert to find those kinds of things. And I was fortunate, I suppose, that physics, which I was interested in, I had gotten interested in sort of independently, kind of got this big boost in 1974 with a bunch of discoveries in particle physics and so on. And I was able to make some contributions to that. And that was super helpful to me that as a 16 year old kid or something, I was able to do professional grade particle physics and make contributions where people would say, oh, that's clever type thing. That was a big. I would say, not so much what other people said, but what I could see for myself, so to speak. It was very satisfying and confidence building to be able to make progress in something which seemed like an important field and so on. For me personally, the other thing that really launched things I've done is computers and the fact that computers got to the point where one could really use them, one could just use them, one didn't have to kind of, you know, know how to build a piece of electronics to use them, one could just use them and they sort of. Things started to scale up that way. And I think that's. And for me the thing that was really important is, is yes, you can actually use them. And you know, in physics, for example, people were like, oh, computers, well, there's something else, we don't use those for physics. And I'm like, but look, it's a tool, you can use it. And bringing that together with the things that I was interested in physics and content, that was an important kind of launching thing. But I would say that the thing, it's sort of both. I landed in a field that was sort of in its golden age. I had this methodology, namely computation, which was a methodology that was out there but not widely appreciated by scientists, for example. And I suppose the third thing for me is that I kind of had progressive achievement in the sense that I did something, it worked out okay, then that gives you the confidence to do something more ambitious next. And so I kept doing that and have kept doing that sort of my whole life. And you know, the fact that one has the confidence, oh, I'm going to do some project, you know, I've got projects right now that in the abstract they're just crazy difficult projects. It's like, how could this possibly, how could one possibly make progress? You know, let's say finding some foundational theory for economics. How could one possibly make progress on that? People have been thinking about that for 500 years or whatever. You know, how could one make progress? I don't know if I will, but I, I'm not immediately turning away because I know I've made progress on a lot of things where people have said, you know, this is the thing that they'll never make progress on. And I think that there's both the confidence to try and do difficult things, but also another important thing for me, at least, and I've seen it in other people as well, is I don't kind of. It's not like I say, I've done these difficult things. The next thing I do must be more difficult than everything I've done so far. It's like I'm just going to do what I think is interesting. Even if the thing that's interesting, if I'm lucky, maybe it'll be easy. It's not. And maybe it will be. Maybe the thing I'll do will be super important. Maybe it won't be that important. I'm not insisting on sort of progressive growth in the difficulty or importance of the things I'm doing. And I think that's a very significant thing because I see a lot of people who get trapped. You do one good thing and then you say, now the next thing I do must be at least as good as the thing I already did, or at least as important. And that's a trap, because sometimes you won't be able to find that next most important thing, and sometimes you don't even know what's going to be important and what's not. So you should just do it. If you think it's interesting, do it. Even if that next thing you do ends up being kind of a thing that you think is rather easy. Like, for example, this last year when ChatGPT came out and so on, we were involved with it and such. Like, I thought, okay, people have been asking me, how does ChatGPT work? So I should sit down for, you know, a week or something and write out sort of my version of, of kind of how that works. Well, I thought that would be kind of a simple thing to do. It was rather simple to do. But then as I was doing it, I realized, wait a minute, I've got some theory about how it works that's turned out to be quite interesting. And also the thing that I wrote, you know, millions of people have read it, and I think it's had some significance in the world in terms of people's understanding of kind of what the whole shtick of LLMs is and such like. So that thing that I thought was kind of a, oh, this is simple throwaway, you know, not really that terribly important, turned out to be much more important than I expected, both because I discovered more and because it had more influence in the world than I'd expected. So, you know, it would have been a mistake for me to say, oh, that's too easy for me, I shouldn't do it. So that's you know, I try to not fall into that trap. Question here. Let's see, Pastor asks, let's see. How is publishing as a singular author on innovative ideas changed your life trajectory? Do you feel like institutional authority was important for you to be heard, or was it truly the merit of your work? I'd like to say that if anybody paid attention to things I've done, it's because of the things I've done. But I don't think that's realistic. I think that there's a certain prior that people assign to things and to whether they should bother to pay attention to things. That depends on kind of the history and environment of the source of the ideas. Now, I have to say that sometimes it surprises me because I think I built a reasonable amount of credibility for myself in my life, and I've built tools a lot of people use. And it surprised me sometimes that people are like, well, yes, I know you've done a lot of very good things, but this new thing you've done, I think that's totally crazy. Even when it isn't, and it hasn't been so far, it sort of surprises me because when I see something that I see, oh, this person has a long history in doing, delivering really interesting things in these areas of, let's say, technology, and then they do something different over in this area, my prior for that is, I'm going to take that more seriously than if I look at this person and the person has never produced anything that interesting. It doesn't mean they couldn't produce something interesting. But my prior for, you know, saying I should look seriously at this, if the person has delivered real things before, I'm going to look more seriously because I think the likelihood of that they produced five really good things. And the sixth thing is just total nonsense, is love. Whereas if they produce zero things in the past, the first thing, I don't know whether it's going to be good or not. It's not as obvious. And similarly, if they produce five things that were all pretty silly and then they produce another thing, my prior is going to be, it's probably pretty silly. It's probably, you know, sometimes when there's a new thing that comes into existence, it'll take some learning, some. Some effort to dig into it, figure out what's going on with it, and so on. Should you put that effort in? There are cases where somebody will tell me, oh, I heard about this thing from this place, and so on, and it's like, oh, my gosh, I've seen five Other things there and they've all been nonsense. It's going to be very hard to convince me to look at the sixth thing. Whereas the other way around, five things that have all been really good, I'm going to look at the sixth thing. So I think it would be unrealistic to say that that isn't an effect. I think it is and I think it's very rational for people looking at things to pay attention to that. Now in terms of in the modern world, you know, if I say I'm a professor in place X I think that was probably more significant decades ago, few decades ago than it is today. I think people are a lot more familiar with the fact that ideas can come from companies or independent people, whatever else. It's much more the history of that person than it is, oh they're a professor at esteemed University X. Now that's happened for two reasons. One, because there's been more innovation from places outside of the mainstream esteemed Professor X. And second, because some of the esteemed Professor X's have done pretty silly stuff and that means that sort of their, the platform they built for credibility has been deeply eroded I think which is perhaps a shame, perhaps not a shame, perhaps it's actually a good thing for the world because it levels the playing field for where innovative ideas can come from. And the thing to realize is when there is a very well developed area and very institutionalized structure, it's much more difficult for innovative ideas to come from that. And so you don't want to stifle the less well defined, less institutionalized areas if you want innovation to happen and if you say the only innovation can come from the heavy institutionalized, well plumed, with good plumage so to speak places, then you're immediately writing out lots of innovation. I mean if you take an area like machine learning for example, a lot of the innovation there did not come from the obvious sort of well plumed, well known really didn't actually at all from, from it came from things that were a bit more interstitial and you know, in, in, in recent times. So let's m asks, have you ever thought about leaving the software world and producing hardware? You know, people suggest this I would say at different rates of it's become a little less common. But people would suggest every couple of years, oh you know, you want your software to run better, make hardware. I remember my first company, this is back in 1982 or so one of the more stupid decisions that that company I brought in a CEO. I was not the CEO I was just the technical founder and that was the time we had a bunch of software. The hardware, workstation computers and so on weren't really up to running the software that we had. So it was like, let's build hardware that can run our software. And I was like, let's not. We're a software company. The economics and so on of the hardware are quite different. And by the way, other people are going to build this hardware and they have much more economy of scale than we do for making something good happen here. And so I think the, the and this has come up over and over and over again. I mean people have like, let's make a kind of a cheap thing that sort of everybody can run Wolfram language on. Well, the Raspberry PI has provided that and so on. I remember one time we were looking at should we make a calculator? Probably a little bit more than 10 years ago now, should we make a Wolfram language enabled calculator? And actually we built a really pretty nice piece of software that ran on the iPad. This must have been right when the iPad came out in 2010 or so. And we actually invented some pretty interesting user experience kind of methodology for how to enter things in a touchscreen that were had various kinds of notation and so on. But anyway, we made this thing, it was kind of an interesting problem. How do you make a calculator with 5,000 buttons, which is kind of what a Wolfram language calculator will be like. And obviously you don't make 5,000 buttons. You have other mechanisms for dealing with that from a UX point of view. But anyway, we made this thing and then it was a question of, well, were we going to make it as a hardware calculator? Because we could. And sort of funny, funny story because we have this summer program for high school students, we have another summer program for grown ups, so to speak. Actually, right now we're in the middle of a winter school that we have for grown ups also. But I was at the summer camp and I'm like, should we make a calculator? And all these kids, high school kids, were like, yes, you should make a calculator. And I showed the demo of what we had and they're like, yes, you've got to build this, you've got to make a piece of hardware. And then I went to the, we run them simultaneously. So I went to our summer school of grownups and I said, should we make a calculator? And they're kind of like, why would you make a calculator? Nobody cares about calculators. If we want to do these things, we'd use a computer. And then I realized at some point that there's this weird dynamic of calculators getting sold to high school kids because a calculator is a closed object that you can use in a test. By the way, I think it's a big mistake that that's. I've always thought that having kind of a, a well defined piece of software that's accessible to anybody is much better than having a $200 calculator that only some small subset of kids can buy that does things. It just seems like a goofy kind of weird, you know, evolution of commercial interests in the world. But that's what's happened. But any case, it was kind of a, you know, that was a let's do a hardware play of making a calculator. And then like, that's for a particular use case of using it in a test that nobody cares about other than this very artificial kind of, kind of setup. So that's been our story. And I think, I think for me, sort of the dynamics of making hardware are so different from software. I mean, occasionally we've thought about making various kinds of specific devices. I've been interested in kind of making a universal sensor platform. You know, when one has a universal computer, you feed in any program, it will do compute different kinds of things. What about sensors? If you want to measure something, humidity versus, you know, carbon monoxide level versus, you know, light level of this versus wind speed versus whatever else. Is there a thing you can get that would have a set, a small number of broad spectrum sensors from which you can synthesize information about all those different kinds of things? I think the answer is yes, there are about 10,000 kinds of things you can measure. We've inventoried that for WolframAlpha and for our, our knowledge base and so on. It's a question of can you, can you sort of break that down into things where, oh, you've got a microphone, you've got a camera. Now you can deduce things from looking at the images and the sounds and deduce all of those particular things. So that's, that's a case where I, I actually have thought about building hardware for that. Well, more to the point, I tried to convince the CEOs of several large semiconductor companies and they're like, realistically, we can't do something as innovative as this. Try a smaller company. And then for smaller companies it's like, look, the investment to make this work is Just too big for our small company. So it's kind of like you're caught between those two things. You can't do innovation in a large production kind of oriented environment. And yet in hardware, unlike in software, the sort of minimum investment is really quite large. Let's see. Natha asks, is it feasible for an individual to start a software company from scratch today the way I did long ago with developing S and P forerunner to Wolfram language? I should emphasize that I did not build S and P on my own. I had a team of people. I, you know, with mathematical and Wolf language, again, team of people. I did a lot of the work, I designed the thing, I wrote a bunch of core code, but I didn't do all the work. And could I have done all the work. You know, it would have taken a bunch more years. I don't think it would have made a better product. I think the, you know, how big a team do you need to do? What size, what kind of software thing? You know, there are, there are things where, you know, if you, if you take the constraint, I want to do something where I can do it all with my own fingers, so to speak, then that in modern times, particularly I would like to say with technology we, we've built with Wolfram language and all the automation we built there, it is much more realistic for an individual person to build a substantial product offering. And it also depends on are the deployment mechanisms smooth enough. And we've worked very hard with Wolfram language to provide deployment in the cloud, on the desktop, as standalone, in this and servers, et cetera, et cetera, et cetera, so that an individual can readily deploy in all those different channels. And so I think it becomes realistic with the kind of technology stack we have, becomes pretty realistic for an individual person. And it's happened a bunch of times for an individual person to build a pretty substantial kind of product in that area. If you insist, oh, I'm going to just use, you know, write everything in C code or something. Then it's going to be much more difficult to get to the point depending on what your product is. I mean, you might have some product that is just some amazing, you know, component for some networking thing or something like this where it's just the raw code and that's all you need. But I think in for many kinds of things going from the idea to the reality, well, that's what we've spent so many years building a unique technology stack for making that possible. And you know, I think much more of that should be done It's a great opportunity for people and that's a place where an individual can really build a substantial thing. Are there other types of technology or software you would like to experiment with your future endeavors? Oh yes. I mean one in particular we've worked for, for a decade now with a. Well, I would say a startup. It's no longer really a startup because it's at least a decade old called Emerald Cloud Lab that is making automated biology and chemistry experiment technology using, using Wolfram language. And I have long been intending to, to actually use that to do a bunch of biology and chemistry experiments. I've never been other than the most minimal, you know, put a bunch of chemicals in a test tube and stir them. I've never really done those kinds of experiments, but this is my opportunity to do that. That's a place where I'd really like to do some experiments. I'd like to do some experiments in nanotechnology which are sort of enabled by that. That's still a little bit further down the line I think in terms of, in terms of software. I mean, you know, right now playing with, using all kinds of neural net based systems and so on and trying to understand how they work and trying to see what their uses and limitations are, that's another kind of technology, I suppose. Oh, another thing is sensor technologies. You know, I'd like to understand what it's like to have a different experience of the world. You know, presumably soon we'll get better sort of augmented reality experience. But it's like, okay, put an infrared sensor, an ultraviolet sensor, let me get a sense of the world with those other kinds of components added. So, you know, and I think even with augmented reality and, and there's, there's probably other. I mean I, I've used that over. Gosh. I first played around with, with VR back around 1919, 1991 and various times tried to see whether it was actually useful to me for, you know, visualizing things. So on it it hasn't been so, so far and I have the problem that I tend to get motion sick using those things. But that's a temporary technological problem. I think maybe it's a permanent physiological problem for me. I don't think so. I think it just has to do with the delay between when you move your head and when the system responds to that. But that's a place where I'm very curious whether, you know, once I am familiar with using that, what will it enable for me? I don't know yet. Rickness comments They're a big User of Orphan Cloud when on mobile. And this is a poke that the iOS version of our Wolfram Cloud app should be given more love. Thanks for the poke. I'll pass on the poke. I don't disagree with you. I use this a bunch myself and mostly I use it as there's a notebook and I have it in an email or something and I can open the notebook on my phone. I don't tend to do as much editing on my phone. It's a rare sort of emergency case that, that I'll actually edit. And you know, I think this is one of the things like, like for me as an old fogey, you know, I just do simple things on my phone. I don't, you know, for anything serious, I'm going to get out my computer and. But you know, I, I see the young and it's not just the young who have smaller fingers than I do. It's the conceptually young, so to speak. The, you know, using their phones for everything. And the question of sort of programming on one's phone, we've done some experiments with that and I think there's more UX that could be done. I, I'd be interested to know where, whether people really care about that. I haven't quite seen that take off. I think by the time one's doing sort of programming, one's probably using a computer. See, Patrick is asking, would you say that the accessibility of education on the Internet is making universities obsolete? I don't think so. You know, during the pandemic it looked like that might be the end because it was like education went online. If that works, then who needs a university with all the physical plants and all that kind of thing. But it didn't work that well. It didn't work for K, it worked really badly for K12 and it worked not as well for universities. And I think part of the point is many people like being around people and they like the dynamic of kind of learning together and being together and so on. Not me particularly, I'm not shy and people avoiding. But I suppose I have a strong enough, I'm strong enough willed in terms of the things I want to do that I'm just going to sit and do them. I don't really need to be in an environment where it's like, yeah, you should do this class or you should all collectively do this thing. For me personally, that doesn't make much difference. In fact, it actually is a negative effect for me because I'm kind of strong willed and I want to do my Thing, I don't want to do the thing that was part of the sort of the collective thing to do. But I would say that the vast majority of people, particularly at the stage where they're just sort of in college or something like that, they want to be at a university physically there having the kind of full experience. I mean, I have to say, particularly in the U.S. i, I sort of roll my eyes slightly at the almost resort nature of, you know, kind of the, the, the full service kind of luxury resort character. I don't know how luxury, sometimes the dorms are not that luxury even at very fancy universities. But in, you know, the fact that there's this kind of full experience of, you know, you have the swimming pool and the squash courts and the concerts and the this and that, it's kind of a, an all in experience. It's not true in all countries. In some countries it's people don't even live at the university and they just, you know, it's just classes and nothing but classes, so to speak. So I think the, it's sort of interesting. I think that in the kind of work sector there's been much more success in work from home and distributed teams and things like this than there is in the online education sector. I mean online education certainly has its place and for some people and situations it's super valuable and maybe much better than the in person thing. But it seems like people still want the in person thing. Now the question is, well, what should universities be teaching and are they modernizing that? And you know, one thing that's happened particularly in US universities is a certain narrowing perhaps of, you know, in some, for example, the sort of narrowing of ideologies of universities has been an unfortunate thing. I think it's not universally true. There's certainly universities that have different, but it seems like a lot of the elite universities have become very narrowed in that respect and that's a shame. And that will be a, you know, going forward that will be a big, you know, I see that a bunch with people who work at our company and things like this and people who are out and about in the world having ideas, but not part of academia. They say, I don't like academia. Academia has a sort of ideological structure that I don't like. I like the ideas, but I don't like the ideological structure. And I don't think those two things come hand in hand. I think they're just a feature of the actual evolution of universities. And that's sort of a negative thing. As far as I'm concerned, I think the broader the ideological base and the cultural base and so on of universities, the more they're able to kind of carry sort of civilization forward, so to speak. You know, as soon as they get narrowed into, we're just doing this very specific thing. I mean, the lesson of history, particularly in things like the churches and things like this, is that, know, as you, as you narrow it down and it becomes some, some subset of what's needed and you kind of say it's our way or, or, you know, it's kind of like we just have this one particular direction. It doesn't end up being the thing that will, will sort of carry forward civilization, I think. But, you know, I, I, I feel like in terms of can you learn without a university? The answer is absolutely yes. But that was, that was always true. When I was a kid, you know, I didn't, nobody sort of told me this, but you know, like when I'm 11, 12 years old, I realized you can learn physics by just reading books. And you know, I didn't even know that you could go to lectures about these things. I just figured you'd read the book and you'd learn about it. And, and in fact it, it, so that's always been possible. You, you know, it's, it's, it's a lot easier with the web, I suppose, and, and maybe it, the, but it's always been possible and it's been a matter of will, I would say, rather than motivation, rather than, rather than the access to the, to the, to the materials. And I mean, then that's where universities, and they're sort of collective, we're all in it together and we're going to learn math or whatever it is, or we're going to learn, you know, medieval literature or something. It's kind of like there's, there's a certain, certain satisfaction or something in being part of some, some group of people that's all excited about that particular kind of thing. So let's see. Okay, maybe a couple more things here and then I should wrap up for today. Just is commenting. They work in logistics and we're far away from using AI. We actually took a step backwards just now with an internal software solution that does not work for specific customers at all. I do have ideas, but I have to open tickets that are never resolved. I know for sure my ideas can be built into the system. I'm about to give up or write a better system. How would you approach a huge business about this? You know, innovation is very difficult for big Companies and mostly they don't do it. Mostly they get their innovation by gobbling up small companies that did the innovation. Sometimes big companies will have an innovation group that is responsible for the rhythm of work that is innovative, which is very different from the rhythm of work that is mainstream production. And to be clear, if you want to make money, mainstream production is almost certainly the way to go. Innovation is not. You know, in the long term, innovation can make money if it's handled correctly, but in the short term innovation just costs money typically. And it is absolutely correct in some sense for sort of business folk who are running a company for the sake of maximizing the amount of money it makes to just figure out what makes money and do more of it, which is very different from innovating and doing something better. And you know, there may be cases where they're very paradoxical things that happen. Like for example, you know, software can be bad and that's actually good for the company that makes it because then people spend more on services having people, you know, it's just like we'll make this piece of open source software and it's bad and you always have to buy services and that's how the company makes its living. So it's kind of paradoxical. You would think, oh, let's make the best product we can. I've always tried to set up our company so that we are aligned with trying to make the best product we can for the customers we have, so to speak, rather than trying to do something that's kind of weird and you know, sort of an indirect way to, to make, make the company be, be commercially viable. But I think kind of in the, I've got a better way to do it. There's a big company that's doing it a particular way and you've got a better way to do it. It's really challenging. I mean, well managed companies, sometimes if somebody comes up and says, I've got this great way of doing it, I can show up, you know, show how this works and so on. Sometimes with really good management, people will say, fantastic, show us that and it's a big win. A lot of times that innovation will be blocked by the incumbents of like, we don't want innovation, we don't want you coming in, taking over our jobs. We've been doing this job for 25 years and we're very happy doing it. Let's just keep doing it. And I suppose the worst case which you see with some frequency is the innovator just gets fired because it's like we don't want, we don't want to hear about that innovation. We just want, I mean, it's a lot better than the, you know, burnt at the stake back in the, in long ago in history. So we can be grateful for that. But it's still, you know, this, we don't want innovation. Just get rid of that. We don't want to hear about that. I mean, that's certainly something you see and I'm afraid, you know, if I'm to be, to be a little bit cynical but you know, that is what you will find in certain cases bringing innovation to a, to an existing running large business. And as I said, I don't think it's irrational because if your goal is to make money, then doing more of the same is probably the right thing. Now in terms of entering a market where you have something, oh, like I was just talking to a company that I'm an advisor to yesterday that has a solution that costs 10 times less than the current incumbent solution. And it's like, why aren't people using this? And I had to say, I think that the very fact that you're charging 10 times less is a problem because people look at it and say, how can these be doing the same thing? One costs 10 times less than the other. There must be a trick here. There must be something that we're missing really. You should just increase your prices. So maybe it's half the price or something but. And pocket the difference, so to speak. Because as soon as it's 10 times less, there's a signal. It's very hard to signal that this is really doing the same thing. Weird and paradoxical, but I think. Correct. And I think when you say, well, we've got, you know, the thing is in an industry that is. You mentioned logistics as an industry. You know, I've seen cases, I've seen startups that have been successful at things with logistics where there are various kinds of optimization like weather related optimization or even routing optimization and so on. Where it's like, you know, you don't get the biggest companies as your first customers. You kind of create something and then you get typically the companies which are sort of on the edges of logistics. Like it's not really a logistics company, it's, you know, routing school buses or something. And they're not, they're just thinking, oh my gosh, we should start to use something more sophisticated than just a person with a clipboard kind of thing. And that's a place where a young company with an innovative solution can enter by the time you're saying, you know, package delivery or something like this, where you have giant, giant companies doing it, they're not going to listen to some kind of upstart small company, typically, and they probably shouldn't from a commercial point of view, even though in the end that might be the thing to do. The best possibility is that at some point the small company gets kind of notable enough that it gets eaten by the big company. Unfortunately, usually when small companies are eaten by big companies, the small company is ground up by the teeth of the big company and little is left. Unfortunately, it's a bad thing for both sides. There are cases where the small company that gets eaten by the big company becomes the future of the big company. But those cases are the exception rather than the rule. The rule is that somebody sees something where they say, oh, that's going to be valuable, they buy it, and it's really hard to ingest the value into the big company. And there's lots of, lots of mechanics that don't really work very well. Okay, one last thing here. Al is commenting, or maybe it's AI is commenting. How do we encourage more people to study the difficult mathematics behind machine learning and robot. Robot process automation, especially when people are younger and more neuroplastic, so that many of the most groundbreaking developments are accessible to a greater contingent of global society? Well, I'd like to think that the kinds of things I'm trying to do with computational thinking might help in that respect. I think one of the challenges is what do you really want to teach? If you're teaching the mechanics of mathematics, there's only a small subset of people that are going to be into that. I think what you have to do is leverage what people are intrinsically interested in and amplify from that and teach the modern skills, modern computationally oriented skills based on what people. Amplifying what people are intrinsically interested in. I think that's a, that's a good potential approach. Plus also, you know, there's sort of a societal issue of, oh, I don't know, do you? Okay, there's kind of what's cool to do at a given time. And, you know, there was a time when, oh, I don't know, there was a time when being a techie was definitely not cool. You know, there was a time when, you know, being, being a politician was cool. Being a techie was, was, you know, just a, a weird thing which people did in a corner somewhere. There was a, you know, there's a time when being a A professional manager was the coolest thing you could be. And then there was a time when. When being an entrepreneur was the coolest thing you could be. There was a time when, you know, being an entrepreneur was seen as the scrappy thing that people didn't really talk about doing. And, you know, it's. Over the course of time, things become cool and not so cool. Like, being a physicist actually has been surprisingly cool. I don't know what it was like before the Manhattan Project and things like that, but being a physicist has been cool at least since probably the 1940s or 1950s, and least somewhat cool. Being an academic, being a professor, that was at some, at one time, that was like, as cool as could be. And then it became less cool. So, you know, I think one of the issues is what, from a societal point of view, the kinds of things that people, you know, do you want to be a computational thinker when you're growing up? Do you want to be an entrepreneur? Do you want to be this? Do you want to be that as kind of a. If society starts valuing those things? You know, one thing that I think is sort of interesting is there are. There are things where sort of, let's take, I don't know, actors, for example. You know, people know the names of famous actors. They're notable people. And it didn't have to be that way. It could have been the case that the only thing you ever know about is, like, the producer of the movie and the actors are just sort of, you know, they're plugged in, they're plugged out, they're just operatives somewhere. But they became a thing where you know about the individual people. Well, there are other areas, I don't know, like computer system design. Most people have not heard of the individuals who design most of the computer systems that they use. And, you know, it's not a thing where there's a lot of glorification of that activity. Even though things that people who design computer systems create end up getting used by zillions of people, and their creativity is directly impinges on a lot of people's lives, but yet it doesn't happen to be a thing that society has identified as being a thing. You kind of glorify, so to speak. So I think that there's a certain amount of. I'm not sure it's one of these, be careful what you wish for. If you're in the business of actually doing those things, which I'm saying should be glorified, because I'm not sure that that necessarily is a. Is a good outcome, so to speak, for the. For the people doing it. But for society as a whole, the idea that there are people, there are things there, you know, they're real achievements. There is. Is something that I think is. Is. Would help in terms of having kids. You know, kids would say, you know, what do you want to be when you're growing up? I want to be a rock star. Are. I want to be a. You know, I want to be something where they've. They've heard of it. It's like, I want to be a computational language designer. Nobody's heard of that. You know, nobody. I want to be a. A. People have sort of heard if I want to be a programmer, but mostly they've heard of that because they say, I want to go into the tech industry because I can make a bunch of money in the tech industry. The actual. What do you do every day as a programmer? I'm not sure people know. And sometimes when they find out, they're horrified. They say, oh, my gosh, I don't want to do this. But, you know, So I think that that will be one comment there. All right, we should wrap up for now. Thank you for a lot of interesting questions and comments, as usual, and I look forward to seeing you another time. Bye for now.