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Stephen Wolfram | The At Home CEO

Stephen Wolfram is the founder and CEO of the software company Wolfram Research. What happens when you track every email, every keystroke, every mouse movement and every project for 30 years? Today we find out the productivity strategies, personal infrastructure and tracking analytics from the man behind Wolfram Language and Wolfram Alpha - the answer engine which powers Siri & Alexa. Extra Stuff: Wolfram Alpha - https://www.wolframalpha.com/ Follow Stephen on Twitter - https://twitter.com/stephen_wolfram Seeking The Productive Life - https://blog.stephenwolfram.com/2019/02/seeking-the-productive-life-some-details-of-my-personal-infrastructure/ Stephen's Personal Analytics - https://blog.stephenwolfram.com/2012/03/the-personal-analytics-of-my-life/ Check out everything I recommend from books to products and help support the podcast at no extra cost to you by shopping through this link - https://www.amazon.co.uk/shop/modernwisdom - Listen to all episodes online. Search "Modern Wisdom" on any Podcast App or click here: iTunes: https://apple.co/2MNqIgw Spotify: https://spoti.fi/2LSimPn Stitcher: https://www.stitcher.com/podcast/modern-wisdom - I want to hear from you!! Get in touch in the comments below or head to... Twitter: https://www.twitter.com/chriswillx Instagram: https://www.instagram.com/chriswillx Email: modernwisdompodcast@gmail.com

Stephen WolframguestChris Williamsonhost
Jun 13, 20191h 11mWatch on YouTube ↗

EVERY SPOKEN WORD

  1. 0:000:50

    Automate everything: scaling output with a small team

    1. SW

      I mean, I have a pretty complicated company, but I try and understand, you know, every aspect of what we do, and I also know very well that if there's some part I don't understand, that's the part that's gonna get messed up. I mean, the one, one thing that happens in a company like mine, which is a tech company, is that, you know, I've also been pushing for another thing, which is automate everything I can. So you know, we've, we've got only 800 employees, but you know, the productivity that we manage to generate is a, a vast multiple of what you would expect from that number because over the years, you know, any process that I've seen where I can say, "Why do we have 20 people working on this for six months? This is something that can be automated." And while it's gonna take some effort to automate it, but once it's automated, you can just crank it out all the time. (wind blows)

  2. 0:501:40

    Why Chris wants to study Wolfram’s productivity systems

    1. CW

      I'm joined today by Stephen Wolfram. Stephen, welcome to the show.

    2. SW

      Thank you.

    3. CW

      I, uh, am particularly excited to speak to you today. Um, one of your blog posts that was released earlier this year, Seeking the Productive Life, was shared around in a number of different group chats, and when that happens, when it appears in a few different spheres of awareness, I think it's usually a pretty good, uh, pretty good idea that it's, uh, it's gonna be something interesting. So, I wanted to talk to you today about your approach to productivity and personal analytics before we actually get into what it is that you do. The, the work you do is, is interesting, but the way that you do it is almost as fascinating to me, which is (laughs)

    4. SW

      I, I like to think it's interesting. I've been doing it for, for decades, so-

    5. CW

      (laughs)

    6. SW

      ... it better be interesting, or I'm-

    7. CW

      (laughs) Right?

  3. 1:404:16

    “Thinking in public”: solving problems live with the team

    1. SW

      ... or I'm, uh, should be embarrassed, but yes. The, the, um, but yeah, you know, the main thing is that I like to do the things I like to do, and I like to not be distracted by things I don't need to be distracted by. And so I tend to build all these systems to try to automate as much as possible to try to, you know, be as concentrated as I can in actually doing the work I want to do. And so I've, I've, uh, and I would say the, the number one tool, which is not for everybody, that I've built to get, um, my work done is I built a company over the last 32 years that has, you know, 800 people in it. And it's sort of, uh, intended to be a machine for taking ideas that I have and turning them into real things. And so that, uh, but one of the things that is probably more, uh, uh, sort of generalizable is one of the ways that I tend to work is I'm, I'm, you know, on any given day, I'm trying to create things, I'm trying to have ideas, and I'm trying to turn them into real things. And, uh, I tend to follow the sort of approach of, uh, spending a lot of my time doing what I tend to call thinking in public, which means, you know, you're working with a team of people, and some people would imagine that, you know, when you're gonna go figure out what to do, you go off on your own, you hide away, you figure out what to do. That's not what I tend to do. What I tend to do is it's like I'm doing some meeting with the people who are involved, and that's the actual time when we figure out what we're gonna do. It's not something which is happening sort of behind the scenes. And I found that, you know, I have been a remote CEO for 29 years now, which is another bizarre feature, so most of my, uh, uh, you know, interaction with people is screen sharing plus audio. I usually avoid video. So like, the experience we're having right now is unusual for me. I'm, I'm usually a, uh, you know, I've got audio-

    2. CW

      Yep.

    3. SW

      ... I'm, uh, you know, sharing the thing that we're both talking about-

    4. CW

      Yep.

    5. SW

      ... but, uh-

    6. CW

      No face. (laughs)

    7. SW

      ... I'm not seeing the, the, uh, the people, um, uh, it- it's, um, and then, you know, I, I, what I like to do is to try and, you know, we're trying to figure something out, like today, there were several different meetings that I had about different kinds of things, and we figured out some things. Um, and that's always, you know, it's very satisfying, and you know, one has to have a, you know, what I'm typically doing is I'm typing into one of our notebook documents, and, uh, trying to, you know, set out what it is we figured out and so on, and then notes get taken and so on, and then it gets turned into something where something real can happen from it.

    8. CW

      I understand.

  4. 4:166:40

    Livestreaming internal meetings and real-time crowdsourced feedback

    1. SW

      And that's, um, you know, I, I like that, uh, it's, uh, I, I also tend to, uh, maybe it's an eccentricity, but it's turned out to be pretty interesting. We've, we've publicly live-streamed a lot of these internal meetings that we've had. So in the last year, we've probably live-streamed 300 hours of these things. And that's a fascinating dynamic because, uh, I originally started doing it just because I thought these meetings were interesting. They range from very intellectual stuff to very gritty stuff about software engineering. Uh, I just think these are interesting and, you know, why not, uh, have other people be able to sort of share the fun? But it's turned out we've ended up with, uh, you know, people join the, the live chat and so on, and we get a lot of sophisticated users of our products and a lot of other people who are experts in various kinds of things, and we get real-time feedback, which is pretty interesting. And so-

    2. CW

      So you're crowd- crowdsourcing some solutions, almost.

    3. SW

      Yeah, yeah, yeah. And I mean, there, there are things that have actually gone into our products that were suggested by people in the live chat, and you know, it's a very fast process. I mean, we could go and we could say, you know, "Okay, we, you know, world, here's what we're gonna do," and a week later people could respond to it, but actually this is like people are hearing what's going on-

    4. CW

      Real time.

    5. SW

      ... and they're typing things, and, uh, it's, it's, it's pretty interesting. And, and I think, um, uh, you know, to me, being able to do those kinds of figuring things out, uh, sort of live and in public, it makes perhaps egotistically the things feel a little bit more meaningful to me.

    6. CW

      I understand.

    7. SW

      So-

    8. CW

      So you, you can see-

    9. SW

      ... that's a, that's a process of figuring something out, and you put a lot of effort into it, and it's kind of fun if that effort is actually archived, and I'm not, you know, I haven't, I haven't, I haven't watched any of them.

    10. CW

      (laughs) Yeah.

    11. SW

      Since I made them, but I know other people have, and, um, uh, you know, and I think it's-... for, for me, you know, part of, you know, the things I've figured out over the last few decades about, particularly about software design and language design and so on, and, uh, this is my way of kind of helping educate about those things is, you know, you can actually see this happen and you can see what the process is. And I, I-

    12. CW

      Th- there's a, there's a term that one of the guys behind the Modern Wisdom Project, George, uses when he talks about evergreen content like that, so this is a discussion that I'm having with you. I've always said I would do this podcast even if nobody tuned in because I want to have these discussions with interesting people. However, George describes it as, "You at scale."

    13. SW

      Yeah.

    14. CW

      And I think that that's a nice way to describe what it is that you're doing 'cause that meeting would be going on anyway.

    15. SW

      That's correct.

  5. 6:4014:54

    Remote CEO for decades: building a culture of direct, low-friction communication

    1. CW

      The only difference is, (laughs) the only difference is the fact that now other people get to benefit. One of the things that you touched on right at the beginning there, some of the, the listeners may be taken away on the whirlwind that is Wolfram and, and, and what, (laughs) what the, the company does. But, um, one of the things you touched on that I thought was really interesting was that you are a remote CEO, which means that you do the vast majority of your work at home. I think you've cited that you're in the office for hours per year as opposed to-

    2. SW

      Yeah.

    3. CW

      ... days or weeks per year. Um, but, contrasted with that, you have this, uh, quite sort of crowdsourced, very interactive working style. I think when people think about the at-home CEO, if you were to say that, you kinda think of this Tony Stark kind of down in the dungeon on his own, tinkering and working away, especially when you then couple it with the fact that a lot of what your company does, uh, in as much as me as a good avatar for the layperson can understand is pretty hardcore mathematics and programming. Um, you think down in the dungeon, working on their own, uh, uh, sort of, and then every so often revealing something to the rest of the team. Um, is this a, a quirk of your personality or is this simply how you found to be the most optimal way to get stuff done?

    4. SW

      Yeah, I mean, I've done different things at different times in my life. This is a really good way to get stuff done, although it probably depends on my personality that it works. I mean, so for example, when I was first, um, uh, well, after I started the company, uh, for about 10 years, I kind of put myself on sort of pseudo-sabbatical-

    5. CW

      Hmm.

    6. SW

      ... working on a basic science project. And that project I did in a completely reclusive mode. I wasn't talking to anybody. I was just, it was me, uh, uh, happened to be in a, in a high-up room rather than down in the basement, but, uh-

    7. CW

      Yeah.

    8. SW

      ... other than that, it was, uh, pretty much caged and, uh, and working on my own. And I, I was, you know, I, I, my schedule was sort of shifted around, so I was working typically from, I would, I would do stuff with the company in the afternoons and then I would go off and, and start working on my basic science project, sort of, uh, I'd go off and do things. I've, during the time when I did the basic science project, I had some kids and, you know, I was doing things with the kids for a while, and then I would go and, uh, starting at like 8:00 or 9:00 in the evening, work until 6:00 in the morning, uh, doing basic science basically on my own. And, uh, it was a, you know, that was a, definitely a tenacity testing process to go do that for a decade basically. And, um, you know, I got it finished. I produced this book called New Kind of Science, which has had all kinds of consequences in the world. But, uh, it was, um, uh, you know, it was definitely a pretty intense way to work. So I, I changed the way I worked after that and, um, decided that I would try doing this much more, you know, with, with my internal group, kind of this thinking in public type mode. And it's great. Now, it depends on the fact that you have people that you're working with where there's sort of, uh, I don't know whether it's good chemistry, but where people kinda know what to expect. Um, and, you know, it's probably, it's probably, I don't know, one could probably figure it out, I, I should know the analytics of this from my, um, uh, from, uh, my live streams, but I'm guessing there's probably 150 people who sort of make an appearance in some live stream or another.

    9. CW

      Yep.

    10. SW

      So that's kind of the, out of maybe 800 people in the company, so it's probably the, you know, th- that's the set of people where they kind of, uh, are in the right flow to be able to be involved in these kinds of live stream type meetings.

    11. CW

      It's, it's interesting that you say that they need to know what to expect from you and kind of you do vice versa. If you were, I think a lot of people have just come off a podcast with Robert Greene and we're talking about inter-office politics and people having to wear masks and all sorts of things like that. Most people's jobs are a, um, combination of the solo warrior perhaps, cubicle work, typical knowledge work, emails backwards and forwards, and then some meetings, some collaborative meetings. And for the meetings, a lot of people have to play the role of whatever it is, the boss, the subordinate, the this, the that, the other. Um, I imagine if you were having to play a role to 150 people over a live stream for hours and hours every day, it would be exhausting. So I, I completely understand what you mean that you're able to have sort of brain to mouth to screen with as little friction as possible. And I think that actually probably quite nicely leads us onto your approach to productivity overall because having done as sophisticated an assessment (laughs) as I can of the most sophisticated approach (laughs) to productivity that I've seen, lack of friction kind of appears to be one of the, one of the things-

    12. SW

      Yeah.

    13. CW

      ... that, that, uh, uh, a meta-narrative about it. So would you be able-

    14. SW

      Yeah, I think that's right.

    15. CW

      ... would you be able to-

    16. SW

      I mean, look-

    17. CW

      ... just explain your, your approach to your personal infrastructure?

    18. SW

      Yeah. Well, okay. So a- but, but I mean, just to say one more thing about, about what you were just referring to 'cause I think it's interesting. I mean, the, the fact is, you know, my company is sort of constructed to be a direct communication kind of place. So, you know, we've a- a- another feature that makes the remote CEOing thing less weird or even more weird is that, you know, I set this example, you know, nearly 30 years ago being a remote CEO, so that means that the majority of people...... who work at my company work remotely.

    19. CW

      I was g- are they all at home as well?

    20. SW

      Yeah.

    21. CW

      Or in a-

    22. SW

      Yeah.

    23. CW

      ... their own office or whatever? Yeah.

    24. SW

      Yeah. All, all kinds of random places. I don't even know where they are. I mean, occasionally there'll be some interesting things. Somebody will say, "Well, there's a, you know, there's a volcano erupting that you can see on-"

    25. CW

      Next to a shark or something like that.

    26. SW

      Yeah, right. And it's, it's, um, uh, and then you find out where they are, which I, I don't typically pay that much attention to.

    27. CW

      Yeah.

    28. SW

      Um, and, uh, you know, but I think that's a, um, the, the fact that one can develop a company culture where people are able to actually say what they think. And, you know, on these live streams, they're very unvarnished. And so people will be, uh, uh, you know, saying sometimes people will get quite passionate about things and, you know-

    29. CW

      Yeah, I bet they do.

    30. SW

      ... they'll attack me and tell me I'm a total idiot and so on. And it's, it's, um, but this is the way that I like to work because I found, you know, it turns out you can have the whole sort of posturing of, uh, that often happens in many kinds of business settings, but it's like a big waste of time. And so long as you can-

  6. 14:5418:27

    Choosing projects that fit your ‘matrices’: stacking systems to reduce overhead

    1. SW

      In terms of the, in, in terms of, uh, kind of my, my, uh, you know, sort of daily life, I tend to be a very, uh, uh, you know, it's very scheduled. It has very, it's very kind of structured and I've built, you know, all these systems for sort of prioritizing. I, you know, uh, uh, in a sense, I'm, I, I cheat because I have a whole company that's, that's dealing with things like prioritizing what I do, so-

    2. CW

      Yes.

    3. SW

      ... this is not, um, uh, but, you know, we've had to build these systems for, I would say the, the number one meta system is I have all these ideas all the time. Like I've had several ideas today, which, which will turn into, um, you know, which have the potential to turn into lots of work. Um, and, uh, you know, the, the, my, the thing I like to do is to have ideas that actually turn into something real. Um, I've, I find it very frustrating just to have ideas and not have anything happen with them. So, you know, the, it's, it's a question of how do you build a system where you can make concrete those ideas and, um, and then, um, uh, actually, um, uh, kind of, uh, you know, have the right project management and the right kind of flows to make that happen. But, you know, in terms of my own, um, uh, you know, like I, I like to work. I, I, you know, the work I do is what I choose to do. And so I like to be doing that as much as I can. So like I also, you know, I like to get exercise every day. And so like, you know, the, um, if I'm, uh, uh, you know, I set up a treadmill so that I can have a, you know, type on my computer while I'm, uh, walking on the treadmill and that works fine. I also typically do meetings. I usually try to, uh, try to get, um, meetings that I think are gonna be a b- bit frustrating scheduled for the time when I'm on the treadmill 'cause-

    4. CW

      (laughs)

    5. SW

      ... because then-

    6. CW

      Does anyone know? Is anyone listening?

    7. SW

      Yes, yes. I mean it's 39-

    8. CW

      And can they hear you plodding away and they think that's a signal that Stephen thought this was gonna be a shit meeting.

    9. SW

      (laughs)

    10. CW

      Like if there's anyone, if any one of Stephen's executives are listening and you hear him plodding away on the thing, that's 'cause he thought it was gonna be a boring meeting.

    11. SW

      Yeah. (laughs) Well, it's not so much boring, it's usually frustrating. It's usually like something is going wrong.

    12. CW

      Oh, so you need to, you need to get a little bit of energy out.

    13. SW

      Yeah, yeah, right. Because it's like, like, you know, "Why aren't we managing to do this? What's going on?" Et cetera, et cetera, et cetera. And then it's like, okay, I can increase by half a mile an hour how fast I walk.

    14. CW

      (laughs)

    15. SW

      And that's a, that's a much better way to manage my, uh, my frustration-

    16. CW

      Yeah. Look, yeah.

    17. SW

      ... rather than growling at people. Um-

    18. CW

      Fantastic. I absolutely, I absolutely love it. Um, I think if, if you were, if you were a layperson and you were to think, well, I'm the sort of person who likes to work. I want to maximize my ability to do the work that I like to do. Not only does it feel like, what I'm gonna guess is close to your highest calling in life, but also something that's enjoyable as well. Um, you would make it as easy as possible to do as much of that as possible, as, as high a velocity as possible, with as little waste. And reading through the blog post, which will be linked in the show notes below for the listeners who want to check it out, and I, I suggest that you do because it is a, it's a real monster. Um, but-

    19. SW

      (laughs)

    20. CW

      It really is. Um, the particular setup that you have, which is, uh, like you say, these matrices as, as you've described them, which are kind of these systems, I guess, um, people would, uh, in more sort of common, uh, common terminology.... where you have a desk which moves from sitting to standing very easily at the touch of a button. You've optimized the ergonomics. I think I'm right in saying that you're left-handed and you've realized-

    21. SW

      Yes.

    22. CW

      ... that you can... you use a older style roller mouse, right, rather than a track pad.

    23. SW

      Yeah, yeah, right.

    24. CW

      Go ahead.

  7. 18:2719:52

    Radical personal analytics: tracking emails, keystrokes, and workflow speed

    1. SW

      Usually, when I'm at my desk, yes, because I found that that's somewhat faster. I mean, you know, the point is because I record all this personal analytics about myself, most of it, you know, for the last 30 years, I've recorded tons of things, like o- obviously all the emails I send and receive, and then probably for the last 20 years, I think I've recorded every keystroke I type, and I record kind of an image of the screen that I've, uh, that I've... in, in front of me and things like this. And most of the time, I don't look at any of this, right? Most of the time it just goes, it just-

    2. CW

      Appears in a blog post in... at the start of the year. (laughs)

    3. SW

      Yeah. Yeah. Right. Well, right. I- i- you know, and occasionally I'll look at it, but you know, something like, is it faster for me to use a left-handed mouse or a track pad? I can answer that question 'cause just go look at the data and it takes me, you know, probably 15 minutes to go answer that question 'cause I've got different computers with different setups and I just can see how fast things work.

    4. CW

      Compare the... can compare the two, yeah.

    5. SW

      And that-

    6. CW

      I think I'm r- right in saying that you've done a third of a million emails since 1989, and more than 100 million keystrokes.

    7. SW

      No. No, no, no. Much more than that. I've done, um... let's see. I get a thing that shows me every month. Uh, so I've sent, uh, 850,000 emails. Um, s-

    8. CW

      Ah, this blog post from 2012.

    9. SW

      Yes. Right, right.

    10. CW

      Yeah. So-

    11. SW

      Yes, yes, yes. Yeah, so-

    12. CW

      You've really stepped it up. You've done half a million in the last, in the last... (laughs) s- seven years.

    13. SW

      Yes. Yes, that's right. Yeah, it's, it's... No, in fact, the, the number of emails that I've, uh, that I receive has gone up, the number that I send has gone up.

    14. CW

      Yep.

  8. 19:5227:32

    High-volume decision-making: email triage, delegation, and staying technical

    1. SW

      Um, it's, uh... yeah, I mean, that's another, you know, another feature of at least my life is you need to learn to make decisions quickly, otherwise you just go totally bonkers.

    2. CW

      Mm-hmm.

    3. SW

      So, you know, I'm getting hundreds of emails every day and, you know, uh, it's great when one of them is spam. It's pretty rare that it's spam 'cause-

    4. CW

      Archive.

    5. SW

      ... that's just a quick delete. Um, but, you know, most of the time they are emails that I sort of should get in some sense. And a lot of the time they are things which are some kind of decision, like, do we do this? Do we do that? Whatever. And, you know, one of the things I've tried to train myself to do is just make these decisions quickly, and it... you know, uh, experience helps a lot. I mean, one of the challenges in, um, in the business that I'm in, so to speak, is what do you delegate versus what do you just do yourself. And, you know, there's things where I just know pretty much what to do, it's gonna take me 10 minutes to do it. I could delegate it, but it's gonna take somebody a week to try and figure out what to do, and there's a chance that they won't do the right thing. And so what I tend to do, my solution to this is, that I'll tend to do this kind of, uh, thinking in public, uh, way of, of, you know, doing it. I'll say, "Yes, I'll do this, but you're gonna watch what I do," and so that way you learn, you know, how to do it for the next time.

    6. CW

      Yep.

    7. SW

      Um, and, uh, you know, that, that works pretty well, and it's, it's something, um... Uh, also, for me, you know, in, in, uh, you know, running a software company or something, you might think that the CEO of a software company of our size would never, like, look at the underlying, you know, server code or whatever else.

    8. CW

      (laughs)

    9. SW

      But the fact is, you know, from time to time, it's just easier for me to just look at it.

    10. CW

      Yeah.

    11. SW

      And it also... you know, the dynamic with the team, for example, tends to be, you know, you might think, "Oh my gosh, that's totally traumatic to have the CEO go look at something that some junior person was supposed to work on."

    12. CW

      Yeah.

    13. SW

      And, um, you know, and I suppose sometimes it is traumatic if something really stupid was done, but that's the rare case.

    14. CW

      Yeah.

    15. SW

      It's usually it was actually hard, and the main thing that is communicated is the CEO cares about what this junior person does and isn't totally clueless about what's involved in doing it. And that's a... you know, that's a positive message, so to speak. And I think this, this, um... you know, this theory that you should... I mean, I, I tend to delegate whatever I can delegate, that's one of my sort of principles of, of, uh, uh, of leading a productive life, is delegate what I can delegate, but don't delegate too much. And there are cases where one sort of instinctively delegates things. I mean, I've... over the last decade, I think I've learned more about this. You know, there are cases where it's like, oh, this is a trivial thing, this is something about some, uh, you know, random network issue, whatever, let me just delegate that. And turns out that's just a bad idea, because given the experience I have and so on, I can solve it in 10 minutes. Uh-

    16. CW

      Are there any metrics that you use for that or is it just experience? You said you've stepped it up recently.

    17. SW

      Just, just experience. Yeah, it's just experience. And I think... you know, one of the things that's complicated is, because, you know, I've been in, like, the software business and so on for a disgusting number of decades now-

    18. CW

      (laughs)

    19. SW

      ... you know, I just know a lot of stuff, and it's, it's, um... you know, and it's... and I've gotten better at problem-solving and debugging things and so on over the years, and there's not really a substitute for an extra few decades of debugging experience. And-

    20. CW

      I, I couldn't, I couldn't, I couldn't agree more. So, uh, to draw a little bit of an analogy between two industries that I th- probably guessed you never thought would, would be analogous. Um, I run club nights, so I'm a club promoter. Uh, running nightclubs, late-night industry and stuff like that. One of the things that's interesting, myself and my business partner are the two MDs of that company and there's a couple of other partners, but there isn't a person in that company who hasn't started out as a flyer boy at the bottom. And it means that I understand the craft of every single layer all the way up. And because the company-

    21. SW

      Right.

    22. CW

      ... is inherently quite flat, even now at s- t- 800 members of staff, for us, a lot of them part-time and a lot of them a lot less (laughs) technical than yours. But, um, because it's very flat and because our ascension through it w- required us to learn every step of the way and then model what we did and then distill that back down to the guys that are below us, if push comes to shove and I get asked a question about pretty much anything, the likelihood is that I've either got a similar experience or the very experience that that person's talking about. And I think to any business owners or, uh, uh, um-... uh, entrepreneurs in waiting that are listening, I think earning your craft and getting the bread and butter of your actual business understood to a high, high fidelity is a, a skill that's, that's super, super useful. And when you think about CEO, you think about this, especially remote CEO, if you're not the guy that's in the basement that's working and tinkering, you're the guy that rocks up in the boardroom, like on his private helicopter once every, whatever, for like the AGM. Like, picks up his, picks up his dividend and then goes back to the Seychelles or something like that. I don't think either of... There's not much romance in, in, in that person. It-

    23. SW

      Right.

    24. CW

      ... it's cool, it's cool to have a CEO, I think personally, to have one to get stuck in, like yourself.

    25. SW

      Right. I mean, you know, my, my principle about companies, I've told this to many entrepreneurs, is you know, on day one, the CEO has to do everything. And gradually, you understand more and more of what the company is doing, and then you can gradually, you know, hire people to whom you can delegate those things. But, you know, I know in the history of my company, everything, every area that I didn't really understand didn't get done very well. And that's partly-

    26. CW

      (laughs) .

    27. SW

      ... it's for two reasons. One, 'cause I wasn't there, you know. I think it's partly a, a question of how the motivation of people, it's like, "Oh, the CEO doesn't care about this. We're not gonna put so much effort into it." And it's partly just, it's harder for me to kind of assess it and clean it up and, and so on. So I, I think it's a, it's a really, it's a very good principle that one should, you know, understand, you know, every aspect of... I mean, I have a pretty complicated company, but I try and understand, you know, every aspect of what we do. And I also know very well that if there's some part I don't understand, that's the part that's gonna get messed up. I mean, the one, one thing that happens in a company like mine, which is a tech company, is that, you know, I've also been pushing for another thing, which is automate everything I can. So, you know, we've, we've got only 800 employees, but, you know, the productivity that we manage to generate is a, a vast multiple of what you would expect from that number because over the years, you know, any process that I've seen where I can say, "Why do we have 20 people working on this for six months? This is something that can be automated." And while it's gonna take some effort to automate it, but once it's automated you just crank it out all the time. And so-

    28. CW

      Scalability, right?

    29. SW

      Yeah, right. And it's, it's, um... I mean that's been... Look, that's been the story of, of what we've built, you know, as a company that's, you know, the products we've built and so on, help other people do that too, but the, you know, the customer number one for these things is ourselves.

    30. CW

      Yeah.

  9. 27:3236:59

    Desk ergonomics and physical ‘anti-stagnation’ hacks (plus the sleep clock)

    1. CW

      I wanted to, uh... I, I did want to get onto your very special travel clock, but before I get to that, there's one thing that I noticed in your, uh, in the article that you talked about your, your personal infrastructure. You use a term that says, "Any flat surface on your desk being a potential stagnation point for accumulating-"

    2. SW

      Yes.

    3. CW

      "... piles of stuff." And that is such a universal truth that-

    4. SW

      Yeah.

    5. CW

      And anyone who's listening, like look at... Unless you're a, a neat freak, look at your desk, and if there's spare s- like flat space, there's stuff on it. Like I'm looking at mine now, I'm looking around you and there's like a set of AirPods, like a, a diffuser that I've not used in months. There's like a coaster, like an external hard drive. So, your, um, actual physical infrastructure in terms of the way that you have your desk set up is to minimize that as well, right?

    6. SW

      Yeah, yeah, right. No, I have, you know, one of my little hacks there is I have a, you know, I have a, a fancy old wooden desk that I've used for, for, for decades. It's, um... But it has these pullouts that I had put in at the front. So, you know, there's the surface of the desk which really just has keyboard and, you know, the monitors and things like that. And I admit it has a pile of books on it right now, which it probably shouldn't have. Um, but, um-

    7. CW

      Stephen, come on.

    8. SW

      (laughs) But it's... Well, the problem with it, you know, this is a problem. I'm, I happen to be working on some historical thing I was doing last couple of days, and the problem with historical, you know, research is it tends to involve physical books. And you kinda have to put them somewhere, they're either on the floor or they're on your desk.

    9. CW

      Yup.

    10. SW

      So, these ones are on my desk. The good news about these books is once this piece is finished, which it will be in the next day or so, those books will go back-

    11. CW

      Back in the cupboards.

    12. SW

      ... get reshelved. Um, but, uh, you know, but what I do to, to try and sort of minimize stagnation, desk stagnation so to speak is I just have these pullouts in the front of the desk. And so, you know, if I need to actually, well, eat my lunch or, um, you know, sign a document or, or look at a book actually-

    13. CW

      Mm-hmm.

    14. SW

      You know, just pull them out of the front of the desk and, uh, do that. But I can't leave them pulled out because then I couldn't, um, you know, the-

    15. CW

      Get in the way.

    16. SW

      Right. And so, so it kind of forces me to, you know, after I'm done with it, you know, clear it off, push it back in.

    17. CW

      I totally get it.

    18. SW

      And that's a... Um, it's, uh, it's, it's a, it's a nice, um... It's a, it's a little hack.

    19. CW

      Yeah.

    20. SW

      I mean, I, you know, I've, I've gradually accumulated a lot of these kind of little hacks over time. Um, I mean, another one that I tend to, which you alluded to is kind of, um, uh, like, you know, I have a, a sleep clock that I, uh, that is, um, it's just a piece of code, Wolfram Language Code, that just puts up an interface that, you know, I press a button that says I'm going to sleep now. It starts a count up timer that I can see as, as the time and the count up timer, and then it also sends a message.... to, uh, uh— actually, where does it send the message to? It sends a message to some system which anyway ends up with a thing that lets my, uh, assistant know kinda when I went to sleep. And then if I'm in some weird time zone, they can kinda predict, oh, he'll be up again in, in, you know, eight hours or something.

    21. CW

      X number of hours.

    22. SW

      Um, and-

    23. CW

      I mean, that's... So it's just, for me, to hear that you have... Obviously, I'm gonna guess, compared with some of the stuff that you guys do, that will be, that piece of code will be like 2 + 2 = 4. Um-

    24. SW

      Yes.

    25. CW

      (laughs) But the fact that you're able to create... You think, "I have this particular productivity problem in my life. I also have either the personal capacity or the t- capacity within my company to fix this problem," it must be a little bit like being a kid in a playground sometimes for you, where you're like, "Oh, uh, like, this, this is a small problem that I've encountered." And what have we been talking about so far? That when you do come up against things, we model the issue, create a solution, and then just scale, and the, the problem looks after itself. 'Cause I'm gonna guess, 20 years ago, you will have gone to bed in some weird time zone and missed a morning meeting.

    26. SW

      Yes. Yes, and that's... This was the fix. And now, you know, and this fix has been, uh... I haven't had to touch this fic- fix in ages, and that's the... Yeah, I mean, that's the... You know, I think this is... Look, maybe it's something that I get from being involved in the software industry, is that there are bugs in software. And one of the things, if you're a software CEO, is when you notice a bug, you report it and you try and get it fixed.

    27. CW

      Mm-hmm.

    28. SW

      And I think I'm, I follow sort of the same principle in my personal productivity and, and life and so on-

    29. CW

      Yeah.

    30. SW

      ... is, you know, there are these things that obviously kinda goofy-

  10. 36:5951:18

    Switching on instantly: context switching, memory decay, and rational procrastination

    1. SW

      Yeah, I mean, look, this whole question about being, you know, instantly on and able to, like, be productive quickly, over the years or decades, I've gotten incredibly much better at that. So for example, I, after I spent that 10 years sort of being kind of reclusive and so on, I, um, you know, I would try to set up meetings but I wouldn't have them, like, back to back and things like this, and I would find out, you know, I'd get into some meeting about some topic and it would be, like, the first 10 minutes I'd have to be telling jokes 'cause my, my brain wasn't, you know, wasn't set for the actual topic. And gradually, over the years, I taught myself to basically be able to, you know, I, I have meetings scheduled back to back and, you know, after I finish one, I'm going into the next one, I'm looking at the agenda, and then I'm on and I'm able to, you know, launch into it. Now, I also know that I have certain memory decay times. So for example, I know if there's some meeting that has complicated stuff we've figured out and we didn't get it finished, I know I have about three days to get the follow on, and then I have, you know, I'll, with... in three days I'll still have the complete mental state, uh, remembered. If it's more than that, I'm gonna have to go look at the notes and things like this to be able to figure out what was happening.

    2. CW

      Mm-hmm.

    3. SW

      And, you know, I think that's, for me, in terms of productivity, the ability to just go into some meeting and immediately be, yes, I, you know, I'm, I'm on, I'm understanding what's going on. Now, you know, in terms of a personal motivation, um, you know, I think by most people's standards I'm a very, you know, even-tempered kind of, um, uh... However, you know, I consider myself a procrastinator. Uh-

    4. CW

      (laughs)

    5. SW

      ... I think others would probably not.

    6. CW

      (laughs)

    7. SW

      Um, but, you know, there'll be things where, um, I would say that I do, uh, rational procrastination to some extent, in the following sense: that there are things like, I don't know, there'll be... that I'm gonna give a talk somewhere, let's say, and there's the question of how long in advance do I prepare something, right? And the answer is, I leave it until the absolutely last minute, um, and why do I do that? Because for example, if I'm giving a talk somewhere and, uh, uh, you know, the more I know about the environment in which I'm giving the talk, if I've seen the audience, things like this, the more likely I am to be able to, uh, sort of do a relevant job than if I'm sitting, you know, two days earlier trying to prepare what I'm doing. So, so there's sort of forms of procrastination like that that, um, I tend to... and I, you know, sometimes I will break my own rule and end up preparing something further in advance, or another, another case is, is, um, uh, product releases. And the question is, you're working very hard to do a product release and it's like, when do you write the marketing materials for the product release? Now, sometimes, sometimes I like to write them before we even start building the product, 'cause then I know what, you know, why anybody would be expected to care about this. But often, it's like you have to wait until the thing is done, basically. Because otherwise, you, you just, you know, there's... you can waste a lot of cycles, um, you know, inventing things which, oh well, actually it turns out once you've done it, you understood something different, and so on. But I think in terms of this, um, you know, p- personal motivation, uh, look, the m- the number one, the zeroth feature of my personal motivation is the things I do are things I really like to do.

    8. CW

      Mm-hmm.

    9. SW

      Now, you know, when you build... I do big projects, you know, I do projects that last decades and, you know, it is not the case that every micro piece inside every project is as fascinating as every other one.

    10. CW

      (laughs)

    11. SW

      But, but somehow, you know, I find the, you know, I can sort of... I manage to average that out. You know, I think different people, uh, tend to be at different times in their lives actually optimized for different lengths of projects. Like, I find, you know, in our company for example, you know, there are people who are, like, optimized for the 15-minute project and those people, you know, if they're in technical support, for example, it's fantastic. They'll, you know, they'll come in, some issue will come in, they'll solve it in 15 minutes, everybody will be happy, on they go. And there are other people who are optimized for, you know, the three-month project and if you feed the three-month project person the 15-minute project, they'll spend the first week, you know, preparing the structure that they need-

    12. CW

      Yeah.

    13. SW

      ... to do the project (laughs) and it's all a big disaster.

    14. CW

      You could have, you could have done it halfway before lunch. Yeah, exactly.

    15. SW

      Yeah, yeah, right. So I mean, I think, you know-

    16. CW

      (clears throat)

    17. SW

      ... I, I, it's one of these things where, you know, you have to be picking projects which are sort of optimized for your, uh, you know, for, for... I mean, I, I wouldn't claim that every single thing that I do every single day... Like this morning, I was working on some stuff that it was like, eh, it's kind of, uh, you know, I, it's not... I don't consider it the most thrilling but yet, you know, the end kind of justifies the effort spent on it. And I find that, you know, almost anything done sufficiently well is interesting, um, and you know, people are always saying, "Oh, this is such a boring area. I can't, you know, I can't study in, in..." whether it's in science or in technology development, you know, "This is just so boring." And, and it's, it's like, no, if you actually try and think about it and you try and really understand what's going on, it will be interesting and, uh, you know, that's, that's also a, a piece of self-motivation that, that I use 'cause it's what my experience has been, um, and you know, sometimes when you do things where you think, oh, this is kind of boring, I'm just gonna skate over the top of it.

    18. CW

      Mm-hmm.

    19. SW

      Um, then it is boring.

    20. CW

      Yep.

    21. SW

      But when you actually dive in-

    22. CW

      100%.

    23. SW

      ... and you really try to understand what's going on, turns out it's actually pretty interesting and, and pretty intellectually challenging or, or whatever else.

    24. CW

      Yeah. (laughs) Right.

    25. SW

      But in terms of, in, in terms of walking outside, you know, I, I, um, my wife had been saying for probably 20 years that, you know, it was a good... walking outside was a, outside was a good thing. I was like, "I ignore that," you know, it doesn't... it's who cares?

    26. CW

      Yeah.

    27. SW

      But, um, I finally...... realized through some analytics that I did, to be fair-

    28. CW

      (laughs) Of course, of course.

    29. SW

      ... that, uh, that it was, (laughs) that it was having a, that when I, happened that I was, you know, spending time outside, it happened that my resting heart rate was lower-

    30. CW

      Yep.

  11. 51:1856:07

    Wolfram|Alpha: what an ‘answer engine’ computes that search can’t

    1. CW

      past experience that you've had. I think there's a lot to be said, as we've touched on already, that just spending time and attention, as you'd refer to it in the gym, of- of just getting to grips with the bread and butter and then beginning to slowly add more and more on and expand that domain of competences is something that's very useful for a lot of people. So final thing, um, Wolfram|Alpha is an answer engine, not a search engine. Would you be able to-

    2. SW

      Yes.

    3. CW

      ... ex- would you be able to explain to the listeners who don't understand what an answer engine is, what- what that means, please?

    4. SW

      Well, we u- we usually like to use the term computational knowledge engine. That's our fancier term for it.

    5. CW

      (laughs) Okay, yeah.

    6. SW

      But, um, you know, what it is is a- a thing where you ask it a question in natural language, and it will try and compute the answer to that question. So you might ask it, I don't know ... And- and- and, you know, you can use it. It- it provides computational knowledge for Siri and for Alexa, so you'll- you'll

    7. CW

      Oh yeah, it's the- it's the basis-

    8. SW

      ... keep up-

    9. CW

      It's the basis of Siri and Alexa, right? Like, one of the- the bottom end-

    10. SW

      Well, the com- the knowledge components, yes. Yes. So it's- it's- it's the thing that's answering. It's not the thing that's saying, "Play this song."

    11. CW

      (laughs)

    12. SW

      It's the thing that's answering the question, you know, "What's the population of such-and-such a place?" Or, you know, if you type in ... A good party trick with Wolfram|Alpha is type in a first name, and, uh, it'll give you the- the, uh ... Uh, mostly US data, though it has some other countries as well. Um, it'll give you the number of people with that name who have been born every year s- in the last 100 years, okay? So but then what it has to do, 'cause it's actually computing things, is it knows the mortality curves for, um, for people, and so it can figure out, you know, what is the distribution of people alive today who have, you know, first name Chris, for example.

    13. CW

      Yeah.

    14. SW

      Right? So then a good party trick is, um, you- you type in somebody's name, and it'll give this distribution. It'll say, "Most common age of a person with that name." And just 'cause of the way statistics works, there's a pretty good chance that the person you're talking to who has that name-

    15. CW

      Yeah.

    16. SW

      ... is of that age.

    17. CW

      Yeah.

    18. SW

      So that's, uh- that's, um ...

    19. CW

      That's fascinating.

    20. SW

      I mean, so- so, you know, and- and what we're doing in- in Wolfram|Alpha is we've been ... For the last few decades, we've been accumulating kind of knowledge about the world in computable form. So, you know, you can say, "Where's the International Space Station?" Okay, so that's something you actually have to compute. You can't just, uh ... That's not just ... 'Cause it moves all the time.

    21. CW

      Mm-hmm. Mm-hmm.

    22. SW

      And you have to be working out, you know, what its orbit is, and so on, and then computing the answer to that question. So what we're- what we really ... The- the thing we've done is- is mostly translating human natural language, the kinds of questions people ask, into a computational language, and then using the knowledge that we built up and our knowledge base to be able to answer those questions. I mean, kind of the goal in the end is there's a bunch of systematic knowledge that our civilization has- has built up. You know, my goal, which, to be fair, I've had since I was probably about 12 years old, is kind of to accumulate that knowledge ...... in computational form and have it be the case that any question that can be answered on the basis of knowledge that's known in our civilization, we should be able to automate answering that question. That's kind of the- the goal. And, and you know, we've been able to do that in more and more domains, and that's, um... So that- that's- that's the story of Wolfram|Alpha. And, you know, I use it like, um... Oh, I'll use it probably today, I'll go type in "sunburn" and it'll tell me, 'cause it knows where I am and it knows the UV index data and so on, and it knows, you know, I can look up for my skin type, it'll tell me, you know, it's... whatever it is, 35 minutes to- to sunburn if I don't put on sunscreen or a hat or whatever else.

    23. CW

      Yeah.

    24. SW

      And that's, uh... And I've... Actually, I've been doing QA of that particular function now for probably, uh, eight or nine years, and I can say that the only times I've gotten sunburned are the times when I thought I was smarter than it was. (laughs)

    25. CW

      Oh, it's the same as when you try and go... you don't listen to Google Maps and you think, "No, no, no, no, this way home is always quicker," and it- it knows that there's a traffic- the traffic jam there, and sure enough, you're sat in the traffic, kicking yourself for not listening to Google Maps earlier on. So yeah, to any of the listeners who want to go and, uh, play some of these games, Wolfram|Alpha at wolframalpha.com, and just type in, "Where is the International Space Station?" Or type in someone's first name. Are there any other, uh, cool things before we go that you- you want people to do?

    26. SW

      Oh gosh, there are lot- lots of, lots of things. I mean, there are lots of kind of... Uh, people always enjoy these estimate-type things of, you know, how many, uh, uh, you know, how many soccer balls fit in a 747 or something. These kinds of things. Or- Or one that I was trying to figure out, uh, actually it took two steps to do this, was, uh, if you took all the water in all the oceans on Earth and you rolled it all up into a ball, how big would that ball be? Um, and it's, uh... Which is relevant 'cause I was trying to understand something about the origin of water on the Earth, um-

    27. CW

      Oh (laughs) of course, it was relevant.

    28. SW

      Yeah.

    29. CW

      (laughs)

  12. 56:071:10:51

    Wolfram Language and computational contracts: making the world executable

    1. SW

      It's- it's, um... I mean this is, uh, uh, you know, the- the, um... I mean just to- to- to fill in for a second, the- the- the main, sort of, intellectual thread of what- what I've tried to do for a long time is this thing we call Wolfram Language, which is an attempt to make, kind of, a full-scale computational language, which means, you know, you have programming languages where you're kind of telling, a step at a time, you're telling a computer what to do. Uh, the goal of sort of our kind of computational language effort is to have a language to represent things in the world computationally. So in a- in a standard programming language, you might have something that says, "This is the value of a variable," something like this. But, uh, in- in our language, in a sort of full computational language, you know, the town of Newcastle is an entity, and you can compute things about it. So I can say, "What's the geodistance from Newcastle to Boston?" Or something. So it's being able to have a- a language for expressing things in the world in a way that you can compute from them. And that's, um... I mean, I think it's a... I- I've- I've been working on this now, well, kind of for 40 years actually, altogether, but- but, um, I- I've only, uh, I steadily understand, you know, that this is an important thing, because... Well, it's- it's the thing that people use, they- they use our products in- in, um, well, lots of R&D and education kinds of settings. Uh, products are really widely used to- to figure out new, you know, to figure out new things. But- but there are... What's, um, what's interesting about this process... So just to tell a sort of historical tale. You know, there was a time, uh, when people, uh, like 400 years ago or so, people were doing math, and they did math by writing everything out in words. So there wasn't a plus sign, there wasn't a times sign. That was only invented 400 years ago.

    2. CW

      I didn't know that.

    3. SW

      Yeah. And so, when... once that had been invented, then things like algebra got invented, and calculus got invented, and so on. But while you were still kind of writing out all your math in words, that was very hard to invent. There wasn't a good way to kind of, uh, express mathematical ideas in a kind of language that was convenient for people. Well, we're in the same situation with computational ideas, and that's kind of what we've been trying to solve, is to create a computational language that allows one to sort of express computational ideas, um, in a way that both computers can read and humans can read. Um, and this has been a pretty successful thing, and we're kind of seeing, you know, all these different fields you can call, you know, computational X, where X is, you know, archeology, zoology, whatever else. All these fields, they need kind of a- a computational language to express the computational ideas that come up in these fields, and that's kind of what I built. And-

    4. CW

      I think that, uh, uh, i- i- you've touched on something there which the listeners may be thinking sounds a little bit esoteric, but when you actually think about it, the fact that the democratization of knowledge as it is... Kind of in the way that Wikipedia, I suppose, works, in that you want to find something out and then Wikipedia gives it back to you. But the thing that you want to find out has to be searched for in an incredibly specific way, in the right language, for the correct thing that is... that you want it to do, and it will feed out a very narrow range of results based on what it is that you want. But obviously, with Wolfram Language, taking natural language, converting that into computer code that then feeds back out something legible by a human who has no, no training, no s- special understanding of this, and then gives them the answer that they wanted, or potentially an answer that they didn't even know that they wanted but is the one that they wanted (laughs) -

    5. SW

      Right.

    6. CW

      ... um, and then I think... Am I right in saying that you're looking to even step this up even further and allow laypeople to create computer programs? "I want a program that will do this for me."

    7. SW

      Sure. Yeah, yeah, right.

    8. CW

      And you want to then be able to create natural language to compute a program, to understand it, to then create a computer program to then do what the person wanted.

    9. SW

      Well, here's the- here's the issue. The issue is that natural language is really good if you have a quick question you're asking. If you're trying to say, "Let me define how this really complicated thing works,"... that's not something where natural language is not particularly good at that. That's where computational language is really good. The trick is to have people be able to think in this computational language, and that's what happened, you know, when mathematical notation was invented and so on, people started being able to think in mathematical notation. They started being able to, to actually, you know, think through the math that everybody's taught these days, you know. After 400 years, everybody gets taught this stuff.

    10. CW

      Mm-hmm.

    11. SW

      Probably too many people get taught some aspects of it, but, um, uh, you know, when it comes to computational language, you know, we're just at the very beginning of people learning this and learning it, you know, early in their lives and, you know, when they're 10 or 11 years old or whatever. And, um, you know, once they learn it, then they get to take the sort of computational thinking that they might be doing and put it in some concrete form that both they can read and a computer can also go execute. And that's a, you know, for, for, you know, from a sort of big picture point of view, in a sense, what one is doing by creating what, what I've been trying to do in creating this computational language, it's giving people a language in which to think computationally, which also happens to be a language that computers can execute. But it's a, one of the, the really important things I think is that it provides a way to kind of formulate your thoughts computationally. And that's something, you know, when we talk about making, you know, personal productivity and so on, a lot of, I suspect, I can't necessarily trace all the, all the connections, but a lot of what I end up doing in trying to sort of formulate how I want to set up systems and so on, is informed by the fact that, you know, I've spent a large part of my life sort of inventing this computational language to try and take sort of general thinking about things and make it computational. And once you've made it computational, you have it in a sort of more streamlined, concrete form so that, for example, you can automate it and get a computer to do it. And that's kind of the, um, uh, that- that's, uh, you know, that's a big piece of sort of the, the intellectual effort. And I suspect that, you know, when it comes to, I don't know, um, making the, uh, the sleep time o'clock or something, there are, you know... Yes, that's very easy to do in the, in the language that we have, and, you know, but, um, uh, and it's also, but it's also something where probably certain aspects I, I, you know... It's always a little bit hard to introspect and understand this, but certain aspects of how that works are probably because I thought about it in a sort of a computational way of this is how it, you know, this is how to structure it, and it's not just like, "Oh, well, I'd like to know kind of when I, you know, how long it was, you know, how long I've been asleep," type thing. It's kind of, there's a little, probably a little bit more to it, which is a little bit hard to introspect and, and see through. But I think that's the, um, uh-

    12. CW

      There's a mode of, a mode of, of, uh, thinking that you have, uh, internalized that is your work, which sounds really weird 'cause I, uh, as a layperson, again, I don't, I don't code. I, I don't understand how to code. But I would have thought that the, uh, transfer from screen to real world would have been really limited. But what it actually appears is that you want to define things as clearly as possible, have a number of variables that you can control, and then have as little friction and then bugs in the system, and then you've created a, a, a lifestyle, a productivity, a work cadence out of that and all of these other solutions.

    13. SW

      See, I, I would think so one of the, one of the directions is creating computational contracts, so people, um, you know, blockchain people talk about spot contracts and so on. So the generalized version of that is computational contracts. That is, you know, I'm sure in your work life it's full of contracts of one kind or another.

    14. CW

      Yep.

    15. SW

      And those contracts are written down in legalese. They're written in sort of a version of English that is a little bit closer to code because you're trying to be a little bit precise about, you know, this is what we mean exactly-

    16. CW

      Good point.

    17. SW

      ... uh, et cetera. But, um, you know, what, uh, what we will achieve with this sort of computational language direction, you will be able to write contracts in code. And that means that... The, the importance of that is, you know, sometimes the contracts as they're currently done, you know, you actually want some wiggle room in some place or another.

    18. CW

      (laughs) Yeah.

    19. SW

      But, you know, when, when contracts are being executed automatically by machines and things, it's, uh, it's really, you can't really do that, and that's where, you know, if you can express sort of a human, uh, what you want to have happen, and you can express it in computational language, turn it into a computational contract, have it automatically executable, then that's, uh, that's an interesting thing that, that makes, uh, makes a, a... You know, you've talked about friction. That's a, that's a great friction reducer, is to be able to say, "No, it doesn't need a person in the middle of, you know, saying, 'This is how this should work.'"

    20. CW

      Yeah.

    21. SW

      It's just automatic, you know. It's, it's you have some contract that says, I don't know, what, you know, based on the number of the, you know... If you're promoting something, maybe, you know, you have some PR firm or something, based on the number of media mentions they'll get, you know, some, uh, you know, uh, uh, commission-

    22. CW

      Amount.

    23. SW

      ... some such other thing. And, and, but then what does that mean computationally? Well, that means computationally you have a program that says it's gonna go search the web, it's gonna have these criteria for deciding if it's a mention of this thing, and then there's just gonna be some formula in there, and maybe it's gonna use some machine learning classifier to decide if it was a positive sentiment mention or a negative sentiment mention. But in the end of it, it's just a piece of code and nobody gets to, you know, nobody has to go figure anything out. It's just, you know, the code runs, somebody gets paid, you know, $100 or something-

    24. CW

      Yeah.

    25. SW

      ... or, or they don't. And, um, it kinda makes the world a, uh, a, you know, a more efficient place. And it's-

    26. CW

      There's gonna be solicitors everywhere all over the globe just tearing their hair out at the sounds of this, Steven. You're terrifi- you're terrifying everybody in law at the moment here.

    27. SW

      You know what? It- it's- it's gonna be the other way. It's like the paperless office, right? When everybody said the paperless office, it's gonna be, you know, nobody's gonna have anything printed out and so on, at least for a while, at least for a few decades, there was a lot more paper around. Because what will happen in this case with computational contracts is there'll be a lot more contracts in the world, and because there'll be a lot of things where there was no point in having... You know, right now it's too much friction to have a contract, but you know, it's like, uh, you know, many things that people do, there'll be a little contract that says... And things will happen automatically based on that or whatever else. And, you know, a lot of the... I mean know from, because we've interacted with a lot of law firms and so on, that, you know, the- the sort of big, more sophisticated ones are like, "We want to get involved in this. We want to be writing computational contracts, and we want to be the ones creating the intellectual property that is all those weird clauses that get added, you know, that's like, well, you know, we'll sell you all these clauses that will take care of, you know, what happens if it rains when you're doing some event or something."

    28. CW

      Ah. Yeah, of course, because you're going to have to have someone who understands the law to interpret it into the programming language. And that particular... In the same way as I want to make... I want to process a document, I need a word processing piece of software, you also require this recipe almost.

    29. SW

      Yeah. Yeah. Right.

    30. CW

      Fascinating.

Episode duration: 1:11:38

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