John Sviokla_mixdown.mp3

John Sviokla: [00:00:00] The intellectual question I'm curious about is what's the difference between people and machines and how they think? Who cares? And will it have an impact on organizations, society and careers? And so that was really the foundational question. And, man, I'll tell you, when you're interested in that question, it gets really complicated before it gets easy.

Harpreet: [00:00:29] What's up, everybody? Welcome to the artists of Data Science podcast, the only self development podcast for Data scientists. You're going to learn from and be inspired by the people, ideas and conversations that'll encourage creativity and innovation in yourself so that you can do the same for others. I also host open office hours. You can register to attend by going to Bitly dot com forward. Slash a d. S o h. I look forward to seeing you all there. Let's ride this beat out into another awesome episode and don't forget to subscribe to the show and leave a five star review. Our guest today is an executive leader who creates new economic value in service markets through the application of artificial intelligence and digital capabilities since the early days of his career. He's been imparting the highest level of intellectual understanding of the way artificial intelligence and other digital applications function and how they evolve markets. He's earned a bachelor's MBA and DEBA, all from Harvard University, where he's also taught at the Harvard Business

Harpreet: [00:01:48] School, where he's prepared

Harpreet: [00:01:50] Aspiring leaders to use artificial intelligence and computable systems for competitive advantage. He's also worked at ABC, where he served as an adviser to senior executive [00:02:00] teams looking to develop stronger technology based innovation strategies, prepare for more rapid A.I. driven change, and pursuing new growth models that leverage emerging technological capabilities. Currently, he's a senior partner at digital content, where he helps organizations transform themselves through digital innovation. Today, he's here to talk to us

Harpreet: [00:02:23] About his book, The Self-made

Harpreet: [00:02:24] Billionaire Effect How Extreme Producers Create Massive Value. This book is the first study on self-made billionaires to document the personal traits that enable them to achieve breakthrough growth in existing markets. So please help me in welcoming our guest today, a man who is fascinated by what drives successful growth businesses, someone who is passionate about sharing that learning with others. Dr. John Fialka, Doctors Vogeler, thank you so much for taking time out of your schedule to be here today. I really appreciate you coming on to the show.

John Sviokla: [00:03:01] My pleasure. This is a great opportunity. I love the chance to spread the message and help people grow.

Harpreet: [00:03:08] Absolutely. You know, I first came across your book a couple of years ago. I think it was like two, two years ago during the summer. And I got it on Audible. And it's one of the few books that I've listened to like four times on Audible. Then I went and I picked up the physical

Speaker3: [00:03:23] Copy and even

Harpreet: [00:03:25] Read through that a couple of times. And interestingly enough, it wasn't until I started researching you that I found out that you had such a interesting background in artificial intelligence. So I'm wondering, how did you first get introduced to artificial intelligence?

John Sviokla: [00:03:41] Well, I'll tell you, it's really interesting. I was an MBA student in the spring of nineteen eighty two and the spring of nineteen eighty three. And I was in a class called The Coming of Managerial Capitalism. And what it was, is, is the story of Rockefeller and Sears and Ford and and [00:04:00] Dupont. And I thought, you know, I'm said I'm sitting here. It's, you know, the early 1980s. I said what in my lifetime is going to look like the transformation of industrial and energy and so forth and happen that. And I thought, well, we're mostly a service economy becoming more and more of a service economy. Computers are going up like crazy. So it's going to be a confluence of those two things. It's going to be computers helping people think and be more productive in knowledge or cognitive work and the growth of the service economy and then the interplay between that and the physical economy. So anyway, that's I was literally sitting in class thinking about that. And then I started getting interested in a doctoral program and I thought, you know what I really want what I'm really the intellectual question I'm curious about is what's the difference between people and machines and how they think?

Speaker3: [00:04:45] Who cares?

John Sviokla: [00:04:46] And will it have an impact on organizations, society and careers? And so that was really the foundational question. And man, I'll tell you, when you're interested in that question, it gets really complicated before it gets easy.

Harpreet: [00:04:59] It's very interesting how you kind of collided and combine to disconnected ideas and found a intersection where you could excel. And I find that that's kind of how a lot of the best ideas come about, right. Is just this collision of two different disparate looking topics on the surface of it.

John Sviokla: [00:05:22] Yeah, absolutely. And, you know, it's really obvious now what the transformations have been, you know, in eighty three, OK, we're just getting off mainframe computers. Personal computers are just starting to come out. Electricity from RadioShack and the IBM personal computer and all the other stuff the Internet had not taken off yet. I get on the Internet fairly early because academics are on bit and then ARPANET and and so Michael, my thesis advisor, I used to he had a house in Montana. I was live in Newton, Mass. And we expect that to send the stuff back and forth and

Speaker3: [00:05:53] Fast food modems. So I could

John Sviokla: [00:05:54] Kind of see that stuff coming. And then when you go in the early stuff on artificial intelligence, [00:06:00] you find that there are a lot of people who are trying to think about what they're saying, people and machines. And they think all this fantastic work back then by guys like Alan Newell and Herb Simon and these guys at Carnegie Mellon and Seymour Papert and Marvin Minsky and. Over at MIT, these are these are the real pioneers back in the 50s, 60s. So it really was an inspiration. OK, well, that gets real. What does that do to the service economy? What does that do to the economy in general?

Harpreet: [00:06:29] So kind of thinking back to when you're working on your

Speaker3: [00:06:32] Doctorate degree and researching

Harpreet: [00:06:34] This this question and now kind of looking for some number of

Speaker3: [00:06:39] Years to have

Harpreet: [00:06:40] Things progressed along as you thought they would. What are some of the biggest differences?

Speaker3: [00:06:46] Yeah.

John Sviokla: [00:06:46] Well, yes. In terms of stuff like Google and Amazon and all that other stuff, we're super obvious to me. Before Google, there is a company called Alta Vista, which was a digital and I always thought search would be massive because there's massive economies of scale and you're forcing the demand chain, you know, just like the Yellow Pages, which nobody remembers. But the Yellow Pages were a hugely profitable business, billions of billions of dollars, because if you're right there when people want something, then you're setting up to really want to do something. But I'll tell you, the thing I totally missed was social networks. I understood the power of communication email, but the idea of social

Speaker3: [00:07:24] Networks, I didn't understand

John Sviokla: [00:07:26] What it would mean. And there's a guy named David Reed who came up with this fantastic thing, reads law. And he said, think about what's the dominant architecture for communications network. And David was one of the guys who put together the original Internet protocols, the IP protocols. And David's thesis at MIT in the 70s basically demonstrated analytically why a smart network with dumb ends would lose to a dumb network with smart ends. OK, let me translate that. So a smart network with dumb ends is like the old phone system. Before we had [00:08:00] smart phones. It's like the old mainframes with telecommunications, with terminals. At the end, a dumb network with smart ends is the Internet right? Because the network doesn't have a lot of intelligence in it. It just transports the stuff and the smarts are at the ends. David predicted that in the mid 70s, OK, and he was also one of the guys that work on the base protocols, the TCP IP protocols that are underneath the Internet. And he came up with this idea in the mid 90s, early 90s. They called Reid's law and he said, look, think about it this way. If you want to know which which network is going to win. Think about like this. We have broadcast networks, so like a radio station. So if this podcast gets broadcast on a radio station, a traditional radio station, radio tower, right onto that radio stations, if you look at their value, their economic value, they go up linearly.

Speaker3: [00:08:50] And that is

John Sviokla: [00:08:52] If a station with two million people is worth X, a station that reaches four million people is worth two X, OK, so it's just an equals. The number of people in network equals value. That's true

Speaker3: [00:09:06] Across broadcast

John Sviokla: [00:09:07] Networks, old TV, not cable TV. Then you've got to switch network and you call the first one to start off network after David Sarnoff, the guy who invented the business model for modern radio. Then you have a switch network, which is Metcalf. So Bob Metcalf observed this. He said, look, if you have people on a network like a phone network where people can talk to each other or fax network rest faxes, remember that those things are history. That's why you all had a dominant phone network, because if you have a little phone network and I have a big phone network and let's say one hundred people in my phone network and you add one more person, you add one hundred new connections. Right. Because I can call all those people. All people can call me that. If you do the math on that, that equals value equals and squared. So the number of people in network squared. OK, so that goes up much faster this way and one dominant phone. But then you go to self organizing [00:10:00] networks and this is David's insight. He said, how does the value model increase? And what he said is it actually goes up by two to the end. And the reason for that is you and I, we can have a relationship here in terms of podcast. OK, then we can add Billy and Billy and you and I now self organize around cooking vegetable pasta. Right. And then we join something else that's a political thing. If you do the arithmetic on that, all the combinations are two to the N A two to the N goes up much faster than N squared and much faster than N equals the right. So why do we care about this? The reason is that social networks, whether they're called Facebook or Baidu or WhatsApp or whatever the social network is, that's self organizing network is the dominant network form forever more, unless there's something even better. OK, and so it really is a way to think about this is that Facebook, as we've seen, can do a broadcast like Facebook. Right. So Facebook can do what Fox News

Speaker3: [00:11:07] Does or what

John Sviokla: [00:11:08] Msnbc does. But Fox News or MSNBC cannot do what Facebook does. Right. You can also make phone calls on Facebook so you can go. Squared, but the thing that that you can't do on the broadcast networks or on the phone network is configured today unless she's a social media platform, is that you can't do a self organizing. So that means that folks like Facebook have the dominant network form. Right. So even if you allow Facebook, if you allow another social network, another self organizing network, that network will dominate.

Harpreet: [00:11:41] That's fascinating. That is extremely fascinating. And that's a great history lesson there as well. I'm just curious now, thinking back from from new school now, how much more hyped has it become? Because I feel like, you know, it's just like all the rage nowadays. Back [00:12:00] then, was it something that people were taken seriously or what was the general sentiment about this back then?

John Sviokla: [00:12:07] Sure. Yeah, well, my reading of the history of A.I. is that this is the third way. If there was a wave in the 60s as a wave in the 80s, and now this is the third

Speaker3: [00:12:13] Wave, the big

John Sviokla: [00:12:14] Differences are is that in the second wave, it was all about symbol processing and the third wave. It's about neural networks. And the reason for that is the world is becoming more computable. So you sent around this level of computability, right? So I think that I know it sounds a little abstract, but I think it's important that people understand that. It's just like if you want to understand the industrial revolution, you have to understand automation. You have to understand the labor, the capital substitution for labor and standardization and the Ford assembly line and all that stuff you get if you want to understand industrial the industrial world. And so the basic idea is that in computability and the law of computability is you have the level of knowledge of the phenomenon of interest. So and I'll give an example, the self-driving car. So let's say I want to make a self-driving car back 15 years ago or 10 years ago. I have to make sure the car is computable and the car is driving environments computable, OK? And so it's a level of knowledge of that phenomenon. Times the level of digitization equals computability. And think about levels of knowledge and simple taxonomy like this. When I'm creating knowledge, I start by categorizing. So if you look back in biology stuff, oh, that's a red finch and that's a blue jay. And that's right. And the whole field of biology begins with naming stuff. Right. That's categorization. The next level up from that.

John Sviokla: [00:13:38] Once you have the categories, you start to correlate. You say, oh, when I see the Bluebird, I also see the Red Finch. Right. These things go together. Or maybe the bluebird coming here causes the Red Finch to come. That's the next level. That's causation. OK, so you have categorization correlation causation with those three things. That's the level of knowledge. Then the other side is [00:14:00] how digital is it? Right. Do I have a digital description of what it is when you look back to the Google car? And this came from a conversation with a guy, Chris Urmson, who was the head engineer at Google Plus, the Google car. And what they did of the Google car is they had a the car itself was pretty computable, but the cars driving environment wasn't. So when they first did the Google car, they put like a half a million dollars for the sensors that they had GPS and they had maps with those three things. They had a three foot error. And after Massachusetts, we get some pretty bad drivers. But even in Massachusetts, 30 feet is like too much when you're driving right end up in the middle of somebody else's car. So they added the thing on the top called the lighter, which is a little laser rangefinder spins around with the laser and the early ones, the new ones collect much more data on this. But the early ones collected one point five million pieces of data per second per second.

John Sviokla: [00:14:54] Right. So they spin around, spin around, they paint, they get the reflection. They have a million and a half pieces of data per second. By mapping that with the other three pieces, the sensors, GPS and maps, they are able to build a computable driving environment that the car could drive through. So. So now cars computable. That's great. I can control that. Brakes and fluids and wipers and all that stuff. Now the driving environments computable. Now I have a self-driving car. That is the fundamental thing that's happening all the time. Facebook is busy computing your cognition and precognition. Facebook is computing what social group you're in in your social group, how many times determines what your actions and attitudes are going to be. So Facebook is creating a computable environment of people's cognition and their social relationships. I've actually done some work in mathematical sociology and the network analysis. You know, Facebook says, hey, you might like this person, you might know this person. All of the stuff that comes from mathematical sociology, which was pioneered by a guy named Harrison [00:16:00] White at Harvard College in nineteen seventy six. He and another guy named Born from Cornell. And I forget the third author wrote a two part article in the American Journal of Sociology called Black Modeling. And they came up with a mathematical description of social social systems, which is the underpays. Think of all the mathematical sociology today.

Harpreet: [00:16:19] So many things want to get into there, but so is this is this idea talk about big representation versus big data. Is that what you're touching on there?

John Sviokla: [00:16:29] Absolutely, yeah. Yes. And so Pat Winston, the guy who used to run the 11 million immigrants in the third, one of the great names of all by the lovely guy to brilliant. And actually, if you go on YouTube, you can see he does a presentation on presentations, which is spectacular. And he he pointed this out to me, said, look, a lot of times it's an advancement representation. So what do I mean by that? Well, think about it

Speaker3: [00:16:52] For a minute. The only way you

John Sviokla: [00:16:53] Can have Luber is if you have GPS, what is GPS? Global Positioning System? It's a grid across the entire and maps, by the way, also new maps. So we've got digital maps. We had maps before. They weren't as comprehensive, but we didn't have GPS. It was only when that was created originally for the military to track subs and missiles and stuff and then became commercial. Right. That you can find something in X, Y, Z space, but especially X, Y space. Right. Once you have that grid, which is an extension of representation. Now, I can hang all kinds of things off of that. Right now. I can hang your location, I can hang services, I can do logistics. Right. But if I didn't have that grid and I couldn't reference that grid, I don't have Luber right now.

Speaker3: [00:17:38] I just don't.

John Sviokla: [00:17:39] Another thing you can look at holding up a can of soda here. Right? We got the barcode. That's it. That's another representation. So when I have a universal barcode system, I can do all kinds of things I otherwise couldn't do. And to give it more emerging example, some new cancer diagnostics. Well, first they started cancer diagnostics. [00:18:00] You're taking x rays and you're feeling lumps and you're taking you're taking certain chemicals in the blood, in the urine and the stool. Right. OK, right. Now, they then they added on High-Resolution x rays and MRI AIs a new representation. You can go deeper, better. Now, there are folks who are studying dogs and people and certain dogs can sniff cancer. So when you're having precancerous activity in your body, you actually exhale micro particles of the cancer that can be detected. OK, that's an extension of representation. That's important because I can put all the algorithms all day long onto the images there, the MRI images or the x rays, and you get good advances there. Google has shown that you can predict weeks sooner and more accurately than doctors or things like breast cancer just by giving them the radiographic right. The x rays. But this notion of cancer might be on the molecules that I exhale. That's an extension of representation. That's machines still stink at that. They can't imagine. OK, what representation, what new form of Data on new signal or new whatever might I bring in to completely change the game?

Harpreet: [00:19:11] So going back now to to Facebook and how they are trying to predict our precognition, how does this work within that context of big representation and networks?

John Sviokla: [00:19:23] Well, when you think of something like the like, OK, like is a creation, it's a new that's a new representation of a very simple preference assertion. Right. Then you think about you in the middle of a social graph. Well, until Facebook goes around, nobody had your social graph. Maybe if the NSA was after you for certain things, they might have from your metadata and your phone records maybe.

Speaker3: [00:19:44] Ok, so now every

John Sviokla: [00:19:46] Individual

Speaker3: [00:19:47] I can take, you know,

John Sviokla: [00:19:50] You and I can compare it to somebody else with the same social graph, and I can just move and say, OK, this person saw this ad, went to this location, bought this thing. Now [00:20:00] I can put a statistical probability that if you go here, you go to this ad, you go to this location, you're going to do this

Harpreet: [00:20:06] Like six weeks would be

Speaker3: [00:20:08] Fascinating. I absolutely

Harpreet: [00:20:09] Love that. Yeah, definitely the right place to talk about it here with the @TheArtistsOfDataScience podcast. Get the right audience for that. But I want to take a diversion now and talk about your book, The Billionaire Effect. So coming from this strong background in A.I. and studying a doctorate in business administration, how did that lead you down the path of studying billionaires?

John Sviokla: [00:20:36] Yeah, well, you know, it's I was assigned it many times, but I never actually read it at Dante's Inferno. Right. But I think at the beginning of it, he says, I woke up in the middle of my life. I woke up at 40 in the middle of a dark wood. So I kind of woke up at fifty five in my career and I said, you know, I was studying value creation, but I never really studied the massive value creators. Right. And so it was one of those moments. And then I thought it would be great to meet these characters too, you know. So that was really the genesis of the thing. And I'll tell you, we found some surprising stuff, which I really the most surprising thing of everything to me. In the book was the fact that four to five self-made, not inherited self-made billionaires did it in highly competitive, contested markets. I thought as we dug into it, you get a few that came up with something clever like Howard Schultz. I thought most of the people would be, oh, new product, new drug, new, you know, new market. Right. Or something like that. That's not the case. What they do is they reinvent an old market and a new way.

Harpreet: [00:21:41] And when it comes to definitely get into some of these habits of mind, let's talk about four billion years.

Speaker3: [00:21:48] But I guess what led

Harpreet: [00:21:50] You to study habits of mind in particular? I guess, first of all, how would you define a habit of mind and share? And what was the thing that clued you in on on [00:22:00] this is the thing that we need to study.

John Sviokla: [00:22:02] Well, we did I don't know how familiar with different research methods and

Speaker3: [00:22:06] So forth, but we didn't

John Sviokla: [00:22:08] Believe that we had we first we examined, you know, are there good models that we could go test or tweak or or and we didn't find any that we like. So what we did is we started with a case based method, so we looked at all fifteen hundred billionaires in the world at the time. There's many more now, about twenty four point five hundred. And then we look for those who are self-made, which are about eight hundred and eighty. Then we pulled out the ones that look like they were correct so we couldn't see how they made their money. So that took out a lot of Chinese billionaires and the Russians and so forth that they're all crooks. You just a lot of it's not transparent, a lot of crooks, but that's another whole thing. So we didn't count that. And that gets you down to about six hundred and sixty. We had a very high level profile, about 660. Then we picked one hundred and twenty evenly spread across women and men and locations and race and stuff like that as much as we could within the sample we collecting the sample rate. We didn't over sample for certain things and then we got then we approached them and interviewed as many as we can get a convenient sample on interviews. OK, that's a case based method. So the way a good research approach was the case based method is that the inductive analysis and then detected inductive. So you come up with, hey, here's what we think might be going on, then you'll try to check against the facts. Right. And that's what we did. So we came with habits of mind because we look for stuff like people who said, oh, they're dyslexic or they're a middle child or their first child or they grew up poor and none of those were true.

Harpreet: [00:23:31] And I guess how would you then define this concept of habit of mind?

John Sviokla: [00:23:37] Basically, we thought of it as a pattern of action that we saw across different folks. And rather than use a fancy word around heuristic or protocol or something like that, which might have been a little more accurate, but less less appealing as a as a term. So we came up with this notion, a habit of mine, because it was pretty down to earth and we think reflected the core of what we're trying to say.

Harpreet: [00:24:00] And [00:24:00] before we jump into these these habits of mind, I'm curious, like we always think of for me, at least when I hear the term billionaire, I just automatically tie it to the word entrepreneur. So what would your definition of an entrepreneur be?

John Sviokla: [00:24:18] Oh, I can tell you the definition of self-made, which relates to that self-made. We said they had to start with ten million bucks or less. So they had one hundred fold increase. And what they had, which made it and my definition of an entrepreneur, I very, very generous with the notion that anybody who anybody who is self-sustaining in terms of their income and capability and so forth, I think is let's call them self-employed. I think anybody who for a sustained period of time creates jobs for others as well as for them and also covers to me as an entrepreneur. So that could be the pizza guy on the corner or whatever, because I think that the ability to create jobs for people, meaningful work is the highest calling of any business

Harpreet: [00:25:05] And is like a specific skill that you can point to somebody and say, you know what, you've got all the pieces right there. You got all right. That you just need this one skill and you'll be an entrepreneur if there's something like that is like a key missing skill or a key skill to entrepreneurship.

Speaker3: [00:25:21] I think that the most

John Sviokla: [00:25:22] Important thing I think I think there's a couple of these things. One is that you have to be comfortable with being your own boss every night. Everybody. The vast majority of people think they want to be their own boss, but they don't want to live with the uncertainty, the definition, what's right, what's wrong. You know who's responsible because you know that. As Elon Musk said, he said, entrepreneurship is like staring into the abyss and chewing broken glass. And I think that because of a combination of our schooling system and our culture, [00:26:00] unknowingly, people are taught to worship entrepreneurs or to strong admire entrepreneurs.

Speaker3: [00:26:07] But on the other hand, school is

John Sviokla: [00:26:09] Very structured, is very little open time. There's very little self definition that is then evaluated deeply, like a lot of the self definitional stuff has a very weak evaluation because like, let's say, writing classes or writing classes and dumbed down. And one of the big reasons is very labor intensive to teach somebody how to write, because I can't give you I can give you general rules, but unless I examine your work and go over it with you so that you understand how I look at your work, which is a one on one labor intensive thing that's not filling out multiple choice and adverbs and verbs and good paragraphs and all that other stuff. Right. So the same thing is I think that we don't educate kids in a way that they are exploring. They're designing their own environment or designer in space because the evaluation of that, the feedback is super labor intensive and our model is just not built for that. In the main, of course, there are exceptions. So I think that the answer your question, the first thing is you have to be comfortable with a blank sheet of paper. The vast majority of people think they want that blank sheet of paper, but once they get it, they are very uncomfortable. OK, that's the first thing and the second thing, and I know everybody says that's so true, it's the being able to manage your emotions in the context of failure. Your emotions, not your intellect. And that, again, that that the notion of persistence,

Speaker3: [00:27:40] The ability

John Sviokla: [00:27:41] To fail and keep going, the ability to to just reconfigure, to pivot, to go, to look for something new, to create the not shut down. There's a story about one of the billionaires and trying to remember his last name. He's the guy who owns [00:28:00] the Staples Center.

Speaker3: [00:28:01] Anyway, early

John Sviokla: [00:28:03] In his career, he had it's in the book as well. He had at least a bunch of oil wells in Texas and he's driving away. This is before cell phones and he's hooked up to his eyeballs with this stuff. Right. And the oil wells go on fire.

Speaker3: [00:28:23] So he's really in trouble. Right.

John Sviokla: [00:28:25] So at the time, there was a as you know from the book, you know, John Wayne was filming a movie called Hellfighters, which was about Red Adair, the famous oil well fire fighter. And if you've never seen an oil well fire, I've never seen one in person. But if you I mean, they're a sight to behold and hard to deal with anyway. So this guy had the presence of mind to call up the producer of Hellfighters and say, look, because he first in Colorado there said, well, you can't put out my fire. He said, I don't do anything. I credit you. I'm getting money. Everybody knows you're Harp up to your eyeballs now. And so then he calls it the producer and says, well, how about if I let you guys film already there, puts the fire up so you guys don't have to build it in Hollywood. So I said, great. So he takes the money from the Hollywood producers and it pays off right there to put this fire out. I mean, that is an entrepreneur, somebody who has literally his assets are burning and he figures out how to make money to save them.

Harpreet: [00:29:20] I remember that story in the book that was bringing such creativity and such unbelievable creativity.

Speaker3: [00:29:27] And it seems

Harpreet: [00:29:28] Like entrepreneurship

Speaker3: [00:29:29] Is it's almost like

Harpreet: [00:29:30] A middle skill. It's not just one particular skill. It's you know, it requires a whole bunch of different skills and requires a high level of activation energy being able to lead yourself and pursue. And there's nobody reason that you're back and you have to do it right. That's the definitely I love that definition that you gave this very beautifully put. And in your book, you talk about two owns, the characters kind of there's the producer and the performer to us about who these two [00:30:00] are.

John Sviokla: [00:30:01] Yes. Well, maybe a producer and performer. The term producer draws inspiration from like Hollywood producers, like the people who put everything together. And you get the director, you get the actors, you figure out what the market is. You get the financing, you get the distribution. So that's the idea is you're you're the designer of the business system, if you will. And every competitive product, your business is a system, not a single thing. Even Starbucks coffee. It's a business system. Right? It's the labor. It's the branding. It's the sourcing. It's the eco friendliness. Right. It's a whole bunch of stuff together. And so the producer really is the designer of the system and the performer is someone who helps them get it done. Usually producers can live with different performers, but performers really have the same level of economic productivity of a producer. So give you a perfect example.

Speaker3: [00:30:50] Gates and Ballmer,

John Sviokla: [00:30:52] Ok, when Ballmer was running Microsoft, it was not only flat, it actually went down some. But this is a company that is the while. And he missed mobile. He missed the cloud. He you know, he missed all the big things. So Ballmer was a great performer with Gates driving him. But he wasn't he didn't have the chops to be a producer. OK, you can see it in the stock price now, Satya. Much more reproducer, right. He understands, like how to think about the shape he brought them back into, you know, physical devices. Right. The whole surface revolution. He put them heavily into cloud and he's pushing hard on airline security.

Speaker3: [00:31:34] You know, he has

John Sviokla: [00:31:34] More of a sense of like what's really going on. You also see a similar thing in art and music. So, you know, you get Richards and Jagger right on the Rolling Stones. You know, I think Richards is better as a solo artist. And Jagger purslane.

Speaker3: [00:31:50] Right. You look at

John Sviokla: [00:31:51] Vincent Van Gogh, his brother Theo was his touch point and he worked with the with the galleries and so forth to get Vincent Chaum right. [00:32:00] So Madame Curie and her husband, her husband was intimately involved in their discoveries together. So you see it in science and art as well, that a lot of people do their best work in a combo.

Harpreet: [00:32:18] Are you an aspiring Data scientist struggling to break into the field or then check out doco for Egressed to reserve your spot for a free informational webinar on how you can break into the field? That's going to be filled with amazing tips that are specifically designed to help you land your first job. Check it out. DTG Dutko for Egressed. One of my my idols is already gone. And he talks about the builder and the seller. And to me, that kind of ring true with the concept of producer and performer. Yes. Yeah. So when it comes to producers, performers, builders and sellers, what would you say is the biggest point of similarity between these two?

John Sviokla: [00:33:05] Well, I think that in my experience with the producer performer stuff, it's I didn't see builders selling because what I saw was complementary builders. Sellers. Right. So. You know, you take a look at something like Bloomberg with Thompson and Mike Bloomberg. OK, Mike is one of the world's great salespeople, right? It's got an ego ego bigger than Texas. Right. And just the guy. And let's remember now he is like, what, of 70 billion or something crazy? And it's good to be Mike Bloomberg. Right. You get your answer on tower fifty third Max. I mean, it's it's a good day, right? Anyway, we weekend to Bermuda. But the I would my understanding what they did is so Tom, who was the chief technology officer guy right there. And Tom's also a billionaire, but not as rich as Mike. You know, Tom is just as important in selling to the technology [00:34:00] part. So let's say Mike cell in the front of the house and the traders and all that other stuff Tom is selling into the CIO suites like yours are going to get done here. That's going in the plumbing. You need both of those audiences to work. Right. Mike saying here's what the contents are going to be. Tom says, here's how you're going to get it done over time. Here's what the response times are going to be. Here's a database and so forth. Right. So it's really the complimentarity. And so I think that I think that's that's important. I think the the big distinction for me is the producer knows how to deal with a blank sheet of paper and the performer doesn't. So the producer I don't know if you've ever done a drawing or so forth, my undergraduate degrees in sculpture. So I figure around and you have a map behind you and you can see the figure out of that. Right. Once you have the outlines of the of the of the continents, lots of people can fill it in. And so it's just a matter of who does the first outlines

Harpreet: [00:34:58] And in what way would you say that these two kind of diverge the most? If there was one thing that you say, Sepur, completely,

John Sviokla: [00:35:11] I think that the producers usually need more creative control of the end product, but it's got to have their voice in it, their stamp, their insight. And that's not universally true, but it's largely true. And you can see it. I mean, when Howard Schultz came back into Starbucks, he got rid of the whole soup thing and, you know, a bunch of other stuff to get rid of the microwaves because I didn't like the way the smell was. And, you know, it's like now and this is not Starbucks. I know it's Starbucks. It's, you know, so I think it was that way. You saw it happen and you take IBM, right? IBM, when I was a kid with Tom Watson Jr., son of the founder, Tom Watson senior, the place had a personality.

Speaker3: [00:35:55] Right? I don't think you

John Sviokla: [00:35:56] Can say IBM has a personality now, Oracle's kind of personality. Right. [00:36:00] So and I think that's one that's one manifestation of the creative control of the founder.

Harpreet: [00:36:05] Thank you very much for that. I want to take a deep dove into a couple of these habits of mind, which I think will be really interesting to the Data scientists in the audience starting off with my favorite one, which is empathetic imagination. You define this term for us.

John Sviokla: [00:36:21] Sure. To think about what someone needs when it when it hasn't been completely expressed takes a tremendous amount of empathy. But you also need to make it into something that people can react to. So, you know, when when somebody like Mike Bloomberg decided that, OK, the traders need an integrated set of Data real time, you know, they're getting this from Catrine and this from Reuters and whatever, all of that stuff integrated in one spot. He had enough understanding when he left Salomon Brothers was fired from Salomon Brothers. Right. To know that that's that was the next evolution of what the traders needed and would want. OK, nobody was saying to them, hey, take this and take that and take this and stick it all together. But he had enough knowledge and imagination and empathy for other doing their work. So that's to me, it's really important to understand that we use that language, empathetic imagination, because it invites aggression and rational behavior and emotion. You're never going to put it another way. You're never going to design a great product by doing a conjoint analysis of known forms. Right.

Harpreet: [00:37:33] What is it that allows producers to to see what others can't?

John Sviokla: [00:37:39] I think at one level it's very simple, which is really trying to figure out how to let your customers and what's related to them. The reason we come together is the inventive execution, because if you think about most innovation and large companies, right, they make at least two big mistakes. One is they separate the [00:38:00] thinkers and the doers and nothing great has ever been handed off to somebody else. Hey, Harpreet, I have this fantastic idea. Here's the business model. Go for it never happened. Or you do that to me because it's not yours. It's not mine. So incorporations routinely do that. The ideation team on the panel. The implementation team. Yes. In terms of adjacent or incremental improvement, which can be significant in a growing market, I'm not saying it's not a good idea to do economically, but you're not going to have a breakthrough. And the second thing is giving an innovation, compromising innovation for the way that people already do.

Speaker3: [00:38:36] Business is like

John Sviokla: [00:38:38] Giving your loved one a bouquet of flowers through a fab. Right. So you take a bouquet of flowers and say, like, honey, and you stuff it through the fan and then you look at it on the ground and say, it's the same stuff.

Speaker3: [00:38:52] And the answer is, it's not right

John Sviokla: [00:38:54] And I'll give you an example of a buddy of mine was pitching one of the major hotel chains on this whole eco friendly idea. And it was you were going to drive up and you're going to see the you know, you've done the market segmentation. There's a premium segment that probably folks like you and I that would be willing to pay 15 to 30 percent more to come into a full on eco local, local produce, you know, net zero carbon place to do your electric car. Right. So imagine like eloquent about that. Right. So well priced. And so I brought it to one of the major hotel chains and they said, oh, yeah, we've got this covered. He said, Really? They said, yeah, we got the little things in the bathrooms about water and put the towel in the tub or whatever. And we've got we've got some local eggs in the breakfast menu. And he's like, no, no, no, we have to get the power to this place. They're like, oh, we can't do that. We have power contracture. We'll just so we'll try to figure out the renewable part of ComEd. And it's like in the produce, you know. Oh, no. [00:40:00] Well, we've got a central kitchen that gets it from directly from Tysons. And so we're going to have their chicken, but we can have the eggs and it's like, well, no, it's all up and just

Speaker3: [00:40:10] Go what

John Sviokla: [00:40:11] My buddy calls death by a thousand paper

Speaker3: [00:40:13] Cuts. Right.

John Sviokla: [00:40:14] And so compromise, compromise, compromise, compromise, compromise. And so that's a real so you can't really deliver. And then you have the worst of both worlds. You have the major hotel chains saying we did the eco thing and nobody cares. But the answer is you never really did the eco thing. You did the book on the floor in pieces, and nobody wanted that. Now, people may not have wanted my book anyway, but we don't even know, you know.

Harpreet: [00:40:41] So what is it that allows them to have this merging of empathetic insight with imagination? Like is there a cognitive process that happens in the brain? Is it is it meditation? Like what is it that that helps them make these connections?

John Sviokla: [00:40:56] Yeah, well, I think it's different for different folks. I mean, if you look at a bunch of the if you look at a bunch of the baby boomers in Silicon Valley, a number of them say it had a lot to do with their use of hallucinogens and things like that, not cocaine and that kind of stuff. But Steve Jobs talks about it in Walter Isaacson's book about the amount of acid and so forth.

Speaker3: [00:41:14] I'm not saying we need

John Sviokla: [00:41:14] To do acid to come up with something creative, but whenever I think that I think having a. Figuring out how to untether your mind from the habits of the industrial world is an important thing because the habits in the industrial world and standardization and routinization is so great, you don't even notice it if you want to. If you want existence proof of that, just note how few people paint their cars, anything but normal colors. Think about the amount you own, the asset. You can paint it any color you want. You can do anything and how many people do that, like practically nobody. So the forces of social control are so strong, you don't even see them, right? So, I mean, they [00:42:00] I crazy you pay 30, 40, 60, 80 thousand bucks for an asset and you don't feel like you can change it. It's like, what's that about? I mean, give or take certain communities. But even those communities change it in a similar way. But there's not a lot of variety in the way this community change cars right now.

Harpreet: [00:42:18] Very interesting point of view

John Sviokla: [00:42:21] If you don't.

Harpreet: [00:42:22] Yes. Are you going to go?

John Sviokla: [00:42:24] No, I'm just saying so just to remind yourself how accustomed we are to being, quote unquote normal. So somehow you have to be able to pull back from normal to give space to the imagination for something different.

Harpreet: [00:42:35] I think you talk about this this concept of diet, beverage and thinking, is that going down?

Speaker3: [00:42:41] Yes.

John Sviokla: [00:42:42] And I think there's a step before which we didn't put in the book because I thought at the time, it's really how do you get the space for detachment and you what meditation? Great example. So I get out of monkey mind and I start to get into another state. I think it's connected thinking generally. Some people are more empathetic in terms of their impact on others, but I do think it's connected thinking. So you're taking a piece from here, a piece from here and bringing together in a new way you're managing something new, right? I mean, as it drives me a bit bananas, when people say, oh, well, you know, they didn't invent everything. Yeah, no joke. Every invention is built on other people's invention. The fact we're talking to each other is an invention, right? You can't even think except inside other people's concepts. You're taught other people's concepts, language, updown, family. I mean, you're taught created concepts. So to say that you're always building in somebody else's work is completely tautological.

Harpreet: [00:43:40] What can we do to kind of think in that way? There's some exercises that that we could do, right? Is it?

John Sviokla: [00:43:46] Sure, yeah. I think the best. I think the best exercise is the one that Elon Musk does around raising from first principles. OK, so if you're clear on the objective and [00:44:00] you say, OK, in order to get there, you must do this or this must change. So I saw him presented at MIT many years ago and one of the kids asked him, he said, have you thought about a winged body for your trip around for interplanetary travel? And he shot right back and said, no runways on Mars unless you want to hit an uneven surface at supersonic speed that has to be powered descent. The clarity of that, it's like,

Speaker3: [00:44:28] Ok, yes, OK,

John Sviokla: [00:44:29] Reusability, I get it. The kid says, I get it. Give me a wing body like the space shuttle. But they hadn't thought through the first principle. It's like whatever if you look at is the Starship flight recently, you know why he created the Merlin engine, OK? It's because he wants to be able to. It's the first ever production rocket engine that runs on methane rather than kerosene. Now, why do you want to do this? Because finding kerosene on Mars may not happen. And if it does happen, it's going to be hard because you get kerosene from oil. OK, methane, on the other hand, they know Mars has and he has a whole way that he's going to harvest methane on Mars and oxygen so you can harvest methane and oxygen on Mars. So he had to go back and develop a whole methane based rocket engine, which no one had ever done. Methane is slightly less combustible than kerosene. So the efficiency slightly less in terms of a pure input basis. But that's reasoning from first principles like I want to get back from Mars. I got two choices. I carry kerosene up there, which is totally

Speaker3: [00:45:28] Nutty, or I figure out

John Sviokla: [00:45:30] How to build a rocket engine that runs Methane Genius

Harpreet: [00:45:33] And Terezín from First Principles. It's almost like you have to quiet your mind and just think about the absolute fundamentals, because if you start getting distracted by all the cases and what about this and what about that, that can really derail you and prevent that from happening?

Speaker3: [00:45:51] Absolutely. And I think I

John Sviokla: [00:45:52] Think the brilliance of Alan's thinking is that he combines that with preferences, consumer preferences and economics. [00:46:00] So what I mean by this and I remember somebody was complaining when the Model S came out and it was one hundred thousand bucks to send up a little better start at 70. Sixty eight. And this person saying, oh, well, you have to make a mass-market car and all that other stuff. And Elon came back and he said, well, if you delve into my super secret strategy, which has been on the Internet for five

Speaker3: [00:46:23] Years and he

John Sviokla: [00:46:24] Said, you said you will see that I'm right on the scale curved and by the model E will start the for an even cheaper than that. And so he understood that you have a premium early adopter

Speaker3: [00:46:39] Market and if you can

John Sviokla: [00:46:40] Successfully deliver there, that gets you economies of scale to then drive the of the scale curve down right away. So is there a link?

Speaker3: [00:46:47] Ok, so no

John Sviokla: [00:46:49] Link, no brain computer interface. What's the leading edge of. Brain computer interface that people pay for now, it's her quadriplegic and paraplegic and injured people or deceased people. OK, great. That's what they're getting into. And I think it's great somebody comes back from from Afghanistan to have blown up by an IED. They need an artificial leg. They want to be able to connect to their brain so they can just think about moving their legs and their mechanical legs and it works. What a fantastic application. So he doesn't start saying, look, I'm going to give you a new interface to Halo on seventeen. Right. So and then same thing. But that technology will become the brain computer interface as as he perfects that. So he is writing the cost function curve and he's willing to serve different markets because he's super clear where he's headed, which is he wants he thinks that the Eyo between us and computers is too slow.

Harpreet: [00:47:41] I think that this is a perfectly for the next habit of mine I want to get into, because I think Elon is a great example of that. Some of these examples, even if is this patient urgency. Right. So talk to us about this this concept of this duality of time. Yes. [00:48:00] And especially how do you see this patient urgency playing a role in these days that we're in right now with this pandemic?

John Sviokla: [00:48:08] Well, fortunately and unfortunately, I mean, it's horrible what's happening in the pandemic. Some of the good stuff is that it actually is making people patiently urgent that they have enough. And you hear looking at lots of bad things, but you also hear good things where people are saying, hey, look, I actually have time to reflect or think or read or go deeper or do fewer things right and lead in different domains and demographics and technology. Generally speaking, you can plot most trends, not all trends. Right. But like the MRN, a technology that is being used for the vaccine. For those of you who've been paying attention, you could see MRI technology coming along, but they did a heck of a job to pump it out. And the German the Turkish couple in Germany and stuff that absolutely genius's. I don't want to diminish the brilliance of what they've done. But Mirinae Technology has been around for about 20 years. Right. And so they've been riding that curve and people knew that. And it's going to help cancer. OK, you want another future cancer. It's not going to be completely solved. A big hunks of cancer getting solved vaccine. I mean, it's already vaccines for all kinds of cancer. And, you know, it's just fantastic print and MRI and technology, CRISPR technology. I mean, it's going to be mind blowing. And so that would be an example of the technology. And then you have demography, right? You know, even with big wars, you generally don't mess around with the demographics that much. There are certain exceptions. Russia kill, killed enough of their own young people that they

Speaker3: [00:49:35] Change the pyramid, they change

John Sviokla: [00:49:36] From a pyramid to a stovepipe and things like that. But they're generally speaking, right, unless we have a more deadly

Speaker3: [00:49:43] Plague and stuff, demographics

John Sviokla: [00:49:44] Are pretty predictable. So, you know, when you're doing your thing about patient urgency, you might have a concept and you say, OK, well, technology has to be here for that to happen. So I'm going to pay attention, pay attention. Pay attention. Right. I think, OK, now's the time [00:50:00] to start to invest because the investor window usually is the longest term. Investors in the US are usually about five to seven years and venture capital. It depends on when you get in the fund and all that other stuff. That's why these knucklehead libertarians in Silicon Valley say, oh, the end of government, all those jokers are making money off governmental investment. You know, I mean, nobody was doing who started the self-driving

Speaker3: [00:50:22] Car, DARPA, the Defense

John Sviokla: [00:50:24] Advanced Research Projects Agency with their Mojave thing. Right. That drive a hundred miles in the Mojave Desert without a person in it that in funding that for well over a decade. Right. And as soon as it drove a hundred miles, start with stops funding it. That's how Chris Urmson got to Google and Chris went and grabbed the people, all the talent from the best teams he was competing with on the DARPA grant. So for ten years before Google invests in the self-driving car, the government's been investing. Same thing was true with the NIH and the genetics. Right? OK, Craig Venter came along and plotted it. Well, the technology before that was government invested the Internet. Nineteen sixty

Speaker3: [00:50:59] Five.

John Sviokla: [00:51:00] The Office of Naval Research

Speaker3: [00:51:03] Did

John Sviokla: [00:51:04] Funded a thing called Aloha Net, which was packet switching among the Hawaiian Islands. There's no fruit and vegetables in nineteen sixty five that's going to put money behind packet switching, I mean AT&T and it on the market. So anyway, so you can look at these things and you can follow them over time. It's OK when it hits here. Might be interesting or when the demographics say here when the population has this going on. Right. And the problem inside most organizations is big organizations don't have a way to pay attention to something cheaply. They're great. And it's like, OK, we're going to mobilize, we're going to learn, we're going to buy them because they run on either. If it's not quarterly, it's yearly. If it's not nearly every other year, but it's not more than every other year. And most careers only last.

Speaker3: [00:51:46] People are only

John Sviokla: [00:51:46] In jobs a little bit less than five years in corporate America, except for some of the senior jobs in the last longer. So. It's going to start a project to get on the ground for a year or two, the organization. The longest project they're going to do is three, four years, right before they moved on to something [00:52:00] else. So you're never going to have the patience, urgency to follow a theme and invest when it's right.

Harpreet: [00:52:06] There's so many things that I've got to digest. I can't wait to listen to the playback of this and take some notes. There's a lot of great history. Great there. Thank you so much for that. Within that same chapter of the book that you talked about for her piece on urgency is this idea of transient hypofrontality. And I thought that was really interesting and fascinating and something that I feel the audience could benefit from if they were to incorporate or exercise some of this in their own life. Would you mind describing what this is and how can we use it?

John Sviokla: [00:52:42] Well, the basic idea is that, you know, can you and I'm going from memory now. It's been a while since I've thought about transient hypofrontality. Can you can you basically persist in an idea over time? There's a there's another term to where I think of it as letting go something long enough to let your intuition work right. So the notion of if you can stop your brain from thinking about something, you allow your whole brain to look at it. And there's a guy whose name I'm forgetting now who said basically, if you sleep on something like if you before you go to sleep and you Zanten occur anyway, it sounds like Rubberneck is the guy's name and that you let your non prefrontal cortex mind work on something and that, you know, and artists and mystics and everything. I've talked about this forever. I mean, it depends on your epistemology and your view of the world. But I do weigh in with the notion that human consciousness is a focusing mechanism and that things flow through people as much as get created in people. And so the transient hypofrontality, I think, helps open the aperture to the things that flow through you, because depending upon our ego bound you are, I think that can even be useful or interference to the flow [00:54:00] of the flow state. And, you know, really being in the creative flow,

Harpreet: [00:54:04] I absolutely love that. When I first heard about that concept in your book, the first time I ever been introduced to that, and that kind of led me down a path of studying brain science in my free time a little bit more. I'm really fascinated by that now. And I was interviewing somebody else a couple of weeks ago, Dr Barbara Oakley, and she was talking about this idea of like the is part of a brain reticular activating system where you start. Yes, it's a diffuse mode kind of thinking and it's your subconscious will continue to work on a problem when you're not focusing on on something. And I find that when I'm working on some gnarly bits of code or I'm just absolutely stuck trying to design an experiment or something, I just I can't think any more like my brain physically hurts. Just get up and walk around for for an hour, get some fresh air and come back and just insights are bound. And that was a huge turning point for me. And in my daily kind of practice. After I read about that, I did some more research on transient hypofrontality. I just wanted to incorporate more long walks to my days. Now, twice a day, I just get up and I go for an hour long walk and just let those with those ideas kind of come to come to the top. So another one of the habits of mind that I found really fascinating

Speaker3: [00:55:20] And kind of

Harpreet: [00:55:21] Touched on a little bit here through some of the stories you're talking about, but it's the concept of inventive execution. So what is inventive execution and why is it that it begins with design?

John Sviokla: [00:55:33] And then the execution really is a new way of getting something

Speaker3: [00:55:37] Done to not

John Sviokla: [00:55:38] Compromise what the customer is actually seeing. And people a lot of times usually successful new businesses do a thing differently as well as do a different thing. OK, and so there's a there's a there's a company in Silicon Valley getting its name right that essentially [00:56:00] allows you to rent all the stuff in your in your possession that you're not using. So say you've got a camper that you want to rent or let's say you've got a chairs and you only use them on Thanksgiving or Christmas and you want you really only use for you want the other for stored someplace because you don't like it cluttering up your apartment. You can put these things as long as it'll be carried by one person reasonably. You can put these things in storage and you just have in there and the storage is cheap, especially if you give them a bunch of notice for

Speaker3: [00:56:29] Logistics or you can rent them.

John Sviokla: [00:56:32] So they storm for you and you get the rental, increase the rental. OK, the guy who did this took the backhaul to watch this experiment, minimum viable product with door dash because the door to ask people aren't making any money. Is it going back to the coming back to the restaurant or going something? So he actually did. So he just used the the excess capacity of traditional over to do his proof of concept. OK, so that's that's an example. But of execution. Right. You have when, when, when KB

Speaker3: [00:57:07] Homes, when the guy,

John Sviokla: [00:57:09] Eli Broad did KB Homes, the traditional model, as you remember from the book, was by the land on it for a while, the build slow. He engineered winnability. So when he bought land, he developed it like crazy and get the cash back quickly. And he engineered every single part of the homes. Like you probably remember, he didn't do basements, he did LinkedIn instead of garages. This allowed it to reach a different price point for a single home that people could hit. And so his cash was fantastic. If you go back in the early days of

Speaker3: [00:57:43] Dell, he was the first

John Sviokla: [00:57:45] One to have people order online. He had negative working capital because he would get your order and collect your cash and then he'd pay the vendors later. Meanwhile, you got your computer.

Speaker3: [00:57:54] Well, nobody

John Sviokla: [00:57:55] In the computer business had done negative

Speaker3: [00:57:56] Working capital before,

John Sviokla: [00:57:58] So inventive execution so he [00:58:00] could grow like crazy. And most fast growth businesses choke on their need for working capital. He was just the opposite. The faster he grew, the more cash he had. So beautiful examples of doing a thing. A new way that creates new value

Harpreet: [00:58:14] Is something about those type of businesses where you can see like it's the like the Airbnb for your stuff like that, that I like that again, just kind of combining two two different industries like there used to be Rent-A-Center or rent, you know, and now there's going to be let's combine those two together and stuff that that's the

John Sviokla: [00:58:35] Source and even storage. Right. So instead of paying somebody for storage, they paid a lot less. And then you have an option to buy an option of rent. You know, it's just a lot of this I mean, goes back to this whole notion of a lot of computability. Why can I do all that? Because I can compute a symbolic version of all that stuff and coordinate it and contract for it and deal with the logistics. Right.

Speaker3: [00:58:57] So the marginal

John Sviokla: [00:58:58] Cost, you can do all this stuff in the past, but the marginal cost of the transactions was so high that there was no value left. Right. If you take the marginal cost of those transactions down. And then. And then. And then. And then. Then you create new economies of scale geocode coverage. Now, that door dash person could pick up six things on the way home. Right, because I've got coverage and, you know, it doesn't cost me the transaction. So all those things are coming together.

Harpreet: [00:59:21] Last question before we jump to a real quick random round. And that is it's one hundred years in the future. What do you want to be remembered for?

Speaker3: [00:59:29] Oh, boy, I'd really

John Sviokla: [00:59:31] Like to be remembered for helping people create a more generative kind of capitalism. And what I mean by that is generative capitalism is low entropy, high inclusion, because I think that capitalism is a good system. If you can fix the market externalities around pollution and resource use and so forth and killing them, killing the planet. And if you can have higher inclusion across the socioeconomic spectrum, [01:00:00] both in terms of wealth and age and skills. So I'd like to be a contributor to that mission, obviously.

Harpreet: [01:00:07] Love that, John. Let's go to a real quick, random, random, random question generator. We'll just do a couple of questions. That is, what talent would you show off at a talent show? Singing Have you ever save someone's life? Know what? Something you learned in the last week.

John Sviokla: [01:00:24] Oh, and last week was that intel link is almost operational. Starlink is almost operational.

Harpreet: [01:00:32] And what are you currently reading it?

John Sviokla: [01:00:34] Well, all kinds of stuff. Recker Brinkman's the practical utopian. Going back and rereading Walter langers the mind of Adolf Hitler, which is a psychological profile by the SS of Hitler. Back in thirty eight been. Reading a lot of stuff about the immune system, because I think that there's a lot a lot of interesting innovation happening in that area. So those are some of the things,

Harpreet: [01:01:01] John, where can people find you? How could they connect with you online?

Speaker3: [01:01:05] Sure.

John Sviokla: [01:01:05] The LinkedIn scrape, which just, you know, just

Speaker3: [01:01:08] Like what my email

John Sviokla: [01:01:09] Says, John, is what I call them, I those are probably the two best places because I I've not been doing much upgrading on my website and then more stuff through LinkedIn. So really LinkedIn and

Speaker3: [01:01:22] Email be great. Yeah.

John Sviokla: [01:01:23] I love like I love new ideas and I love talking with people about ideas is very kind of you to have me on your

Speaker3: [01:01:29] Show and I love

John Sviokla: [01:01:30] Doing this kind of work. And I think this notion I hope we can get more people involved in thinking through

Speaker3: [01:01:37] Deeply entrepreneurship,

John Sviokla: [01:01:39] Computability and this notion of generative capitalism, low entropy, high inclusion, because I think we can we need to evolve the paradigm.

Harpreet: [01:01:48] Absolutely, John. I'll be sure to include all of your links right there in the show notes. Thank you so much for taking time. That is scheduled to be on the show today. Really appreciate having you here.

John Sviokla: [01:01:58] Lovely to be with you. I appreciate and good luck. Thank [01:02:00] you.