Ep130: The Digital Economy and Its Impact on Productivity
Welcome to Cloudlandia
The Productivity Paradox in a Digital World
This chapter explores the paradox of declining productivity despite significant technological advancements, tracing the history of productivity gains from early electrification to modern computing. It investigates the impact of the digital economy on value creation, focusing on how intangible assets like attention have reshaped traditional business practices and advertising. The discussion highlights the stark contrasts in success within the digital landscape, emphasizing the competitive nature of content creation and the emergence of new influential figures.
In this episode of Welcome to Cloudlandia, we have a thought-provoking discussion around AI and its future implications. We introduce Juniper, an advanced voice-based AI capable of tasks from writing to coding, giving insight into emerging technologies.
We explore impacts like the attention economy, where value emerges without physical costs. Success stories like Mr. Beast showcase uniqueness and AI's potential to tackle real issues.
The episode delivers a well-rounded look at AI capacities and societal changes. References to early smartphone adoption phases parallel today's AI capabilities.
SHOW HIGHLIGHTS
Links:
WelcomeToCloudlandia.com
StrategicCoach.com
DeanJackson.com
ListingAgentLifestyle.com
TRANSCRIPT
(AI transcript provided as supporting material and may contain errors)
Dean: Mr Sullivan, who is that person that gives the directions when we start the podcast?
Dan: Well, I'm not sure the one that says this podcast this call may be.
Dean: You are the first one on this conference phone call, oh my goodness, who is she?
Dan: Who is she? She's a bot. She's not real. She's a bot. She's not real. She's not real. She's not real, she doesn't sound.
Dean: I've heard worse sounding bots.
Dan: Dan, I have been experimenting, playing around with chat GPT-4.0. And I use it primarily in voice mode, meaning, you know, I just say things to it and it has an amazing Scarlett Johansson-like voice that has zero, not at all like Siri or Alexa. You know where those voices definitely sound like. They are bots. This, my GPT-4O I think her name's Juniper is the voice that I chose. She sounds like a real person, I mean, and has like real tone, real inflection, real like conversational feeling to it and I realized that I don't think we really understand what we have here. I mean, I look at it and I think, imagine if that was a real person.
Dean: Now, when you say we, who are you talking about?
Dan: I mean the collective royal we I I'm sorry I've never been around yeah, I just think we as a when I say we, we as a society or we as the people collectively using this, it reminds me of this Seinfeld episode where Kramer got this or Jerry got his dad, this wizard organizer, and they always use it as a tip calculator, like the least of all the functions that it has. They're just excited that it's a tip calculator, and I feel like that's the current level of my adoption of Juniper.
Dean: Yeah, I think the big thing is what you let's say, a year from now, level of my adoption of Juniper, you know, yeah, I think the big thing is what you let's say a year from now. You're using Juniper for a year. What do you think will be different as a result of having this capability, new capability?
Dan: Well, I think it's operator, you know, I think it's operator dependent, you know, I think it's up to me what I think if you said to me. You know, I think it's up to me what I think if you said to me listen, I'd like to introduce you to Juniper. She's going to come here and she'll be within. She's going to follow you around. She's going to be here within three feet of you or discreetly out of sight, whatever you, but whenever you call she'll be right there. She is a graduate level.
She is a graduate level student. She could pass the bar. She knows everything that's ever been recorded, she speaks every language. She never sleeps, she can write, she can draw, she can do graphics, she can do coding Whatever you like, and she's yours 20 to a month. Have fun, yeah, do you think you'd use it Well?
that's my question is that it feels like I'm not using it and I have it. That's essentially what I have. I've got it in my pocket. You know how they said. You know the iPod was launched with the promise of a thousand songs in your pocket. Well, I think this is really like. You know, an MBA or a PhD or whatever you want in your pocket is essentially what we have, and I find it very interesting.
Dean: No, I think it's unique, you know, and it's brand new. But what problem did you have that this solves?
Dan: Well, I think that it's not per se a problem, but I think that we're I really have been observing and thinking, and I've said it you know in lots of our conversations, that I think that 2020, you know, if we take the 50-year period from 1975 to 2025, that we've pretty much set the stage now for a new plateau launch pad kind of at the same time. I don't. I think that once we understand and people you know, I think it's almost like the iPhone had the app store, that became what Peter Diamandis called the interface moment.
Right, that was the you know, that allowed, once people realized that the capabilities of the iPhone to both measure geographically where you are at any precisely at any moment, the gyro thing that can detect movement, the sound, the camera capabilities, the touch screen, all of those things, Well, people realized what the baseline capabilities of the phone were.
They were able to architect very specific, you know, starting with games very specific ways to use the capabilities that are very specific ways to use the capabilities that are built into the phone and I think that right now it's almost like it can do anything, and I think that we need to figure out the very specific use cases and I think we'll see people.
Dean: You keep saying we, but I don't think we is going to do it. I think you know, who we are. Do we have a cell phone number? Do we have a street address?
You know, I think you're having a very interesting personal experience with the new technology. Yeah, I don't know, I don't know if anybody else is going to be in on this, but the big thing is, how are you going to set it up so that you can prove that this is valuable? I mean, let's say, three months from now the time you come back to.
Toronto for your next strategic coach pre-zone workshop things you're going to test out and see if the inclusion of this spot with a very sexy Scarlett Johansson voice. This isn't the issue that she sued somebody for.
Dan: I think it's, I don't know actually this voice is. It's not exactly her, but it's, you know, it's that tone and things.
Dean: So yeah, so.
Dan: I don't know that. It's a pleasing voice, much more pleasing and personal than Siri or Alexa, for instance. Yeah, but yeah, I think you're absolutely right it does come down to and I think that's where the paralysis of you know the it can do anything, but you know what would be you know where my mind goes.
Dean: It's which, how that I already have, but am I going to assign this capability to so that I don't have to spend any time whatsoever interacting with this bot? But my who's a you know who's a live human being working for a strategic coach would that person actually work? Do this, you know, and actually and I tested out for three months what are you getting done faster?
So, for example, we have an AI newsletter that rewrites itself every two weeks and chooses new content, designs it and goes out and it uses up one hour of my Linda Spencer, who's one of my team members on the marketing team, and it's very interesting, I mean we have about 2000 people who read it and they grade it and everything like that.
But the only thing I have to do every two weeks she said here's the news, here's the results from the last newsletter, here's the design and contents of the next newsletter, yes or no? And I'll go through. I say, yeah, looks good, send it out, right. Yeah, now, that's not freeing me up, because we never had this capability before. It's a new capability, right, and it's been going for about nine months now and people will talk to me about it and you know everything like that and everything like that.
But I haven't seen that it's made a huge difference in the crucial numbers of strategic coach, which are marketing calls. Are we generating great leads that people are talking to us about? Are they signing up for the program? Are they whatever? So the normal measurements.
So I think, with any technology, the first thing I would establish before I got interested in the technology is what are the crucial numbers that we have that tell me that our business and myself are moving forward? And then, whatever I'm going to use the new technology for, it has to have an impact on those numbers. Yeah, I think that's yeah, because you know the amount of productivity. I'll use the United States as an example. You mentioned 1975 to 2025, 50 years of individual productivity in the United States was much higher in the 50 years before 1975, since it has been for the last 50 years since 1975. Even though there are these amazing books and that about how productivity is going through the world with the microchip. But the actual numbers which are gathered by the US government, the US Treasury Department, us Department of Labor, indicates that the level of individual productivity has actually gone down in the last 50 years even though the excitement level of productivity has gone through the roof.
Dean: By what measurement? What are they deciding? Is product?
Dan: Dollars of economic activity per hour per worker. Okay, that's how productivity is measured.
Dean: The number of workers.
Dan: You have the number of hours they work and the amount of economic dollars that their hour of activity produces. The productivity was much higher total for the entire all workers.
Dean: But is it all productivity or personal productivity? Like are you saying no all?
Dan: productivity? No, the entire GDP of the economy, measured by the number of workers. Yeah, okay by the number of workers it's going down, it's down. No, yeah, since 1975, it's not as great as it was from 1925 to 1975. So that 50-year period the productivity levels in the United States were bigger than the last 50 years.
Dean: Wow, that seems. That's surprising. What do you think that means?
Dan: Well, a lot of people are really excited and involving themselves in technological activity that produces absolutely no productivity. Yeah, they're very excited, they're very excited and they're getting very emotionally connected to this activity. But you know, I'm not saying that's not a great thing, I'm not. Maybe they're having more fun, Maybe they're you know, maybe they have.
Dean: What actually counts as GDP.
Dan: Well, GDP is amount of sales amount of sales.
Dean: Okay, so would the advertising sales that Mark Zuckerberg makes for Facebook count as GDP, or is it only in physical, like you know, shippable goods, or whatever?
Dan: Well, whatever, uh, you have a dollar spent on something that constitutes a sale to sale.
Dean: Okay, so advertising, so Google and Facebook and Netflix and all of those things count as GDP? Sure, okay, all right, then that seems impossible.
Dan: It seems impossible, but it's true.
Dean: That's pretty wild.
Dan: Yeah yeah. I'm not saying that Mark Zuckerberg isn't making a lot of money. I'm not saying Mark. Zuckerberg isn't productive. My feeling is that the technology is created, makes a lot of other people non-productive.
Dean: Yeah, and I wonder I mean that's a do you think you know if you measured that in terms of the total population versus the workforce? Is that what? In terms of the total population versus the workforce, is that what you know? I'm just looking for some explanation of this right.
Dan: Somewhere along the line, there has to be an economic transaction for it to constitute and everything else. See, this is the difference. Yeah and everything else See this is the difference? China talks about its GDP, but they don't use the same term that everybody else in the world uses. They use the economic value of what they've produced. So they can produce a million machines and they're sitting in a warehouse and they count that as GDP gross domestic product. But there was no sale, it's, you know, they spend it, it was an economic activity.
There was a transaction there, but there was no sale. So I think that's the big thing. It doesn't count unless there's a sale.
Dean: GDP, doesn't it?
Dan: doesn't count as GDP unless there's a sale. Somebody makes money, yeah.
Dean: Okay, money Okay, yeah, yeah, I mean, it's pretty.
Dan: No, I'm not saying it's not exciting. And here's the.
Dean: Thing.
Dan: Maybe it's an A&I, it's what I would R&D stage. The last 50 years have been R&D stage. For the next 50 years, which are going to be 100 times bigger of GDP. Okay, that may happen, but it's not happening yet.
Dean: Yeah, yeah, I mean it's pretty, yeah, it's pretty wild. I mean you can definitely see, like the capabilities of you know, you can definitely see this replacing many customer service interactions, for sure. For instance, it's like a you can definitely see that going away, that there's not going to be a need for humans manning a customer service telephone center, for instance you know, yeah, I mean if it's good, I mean if it's good you know, and it depends upon the service that's being talked about, but if it's good, you know, maybe it does See, efficiency is not effectiveness.
Dan: You know, and effectiveness is that you made a sale. Efficiency is we took all the activities leading up to a sale and we made them more, faster and easier. Yeah, the question is did you get a sale out of it?
Dean: Mm-hmm.
Dan: Mm-hmm, yeah, so. I don't know, but I think there's a bit of a magician show going with a lot of different kinds of technology, you know. I mean, it was like somebody was saying, you know, they were talking about EVs and specifically they were talking about a Tesla, and specifically they were talking about a Tesla. And he says do you know how much faster zero to 60 is in a Tesla than any gas-powered? Or you know, and I said, to tell you the truth, I don't know.
Dean: To tell you the truth. You know.
Dan: Geez, you know All the things I've been thinking about since last Monday. I'm sorry, I just didn't get to that one Anyway. And he says well, it's easily a second faster. I said good. I said now, where do you do this? There isn't any way. We're in greater Toronto, the area of greater. Toronto 6 million people, where you can go from 0 to 60 on a city street in two seconds. You know and everything like that.
He said, yeah, but boy, you know, I mean, just think of that, how much faster you can go. And I said, yeah, but Teslas don't go any faster in Toronto than any other car, that's true, and usually they're stopped.
Dean: Yeah, that's exactly right yeah.
Dan: So I think the Tech Magic Show, I think it multiplies people's imagination, but it doesn't multiply their results. You know, I think there's something about it. And I think this is great. I mean what you're telling me. I've had some really boring people on the other end of a phone call and Scarlett Johansson would really liven it up a little bit.
Dean: Absolutely yeah, yeah, exactly.
Dan: Yeah, I was noticing that Cleveland hired Jack Nicholson and they still use it. It must have been 20 years ago. All the announcements, the regular announcements like don't leave your bags unattended, and things like that, oh right. There's a whole bunch of just what I would call airport announcements, and they have Jack Nicholson doing it and you stop and listen every time it starts. You know it's very effective and I'm sure and I'm sure Scarlett, I'm sure Scarlett Johansson would do a good job too.
Dean: Absolutely. Yeah, yeah, it's so, it's so funny. I mean, that seems. I'm just dumbfounded by the fact that productivity has decreased in the 50 years that we're talking about here.
Dan: Yeah Well, think of the 50 years, though, and you gave me that great book.
Dean: Yeah, you gave me the book that was 1900 to 1950, 1925.
Dan: But 1925 to 1975, the entire country was being electrified. They're laying in lines and everybody was the farm that I was on. I was born in 1944. That farm was electrified in 1928. So it was only 16 years that they had electricity. Right, and you know they were putting in the entire water systems. The Tennessee Valley Authority was putting in all these dams and the electric plants. You know Lake Mead as a result of the Hoover Dam.
They were putting in all those dams and that just produced enormous jumps and the cars were going in, the gas systems, all the infrastructure for gasoline was going in. It was just a monstrously productive period of time. And then all the production that went into the second world war, which they then had as productive capability after the war stopped and so they had all the manufacturing capabilities you know and you know and so. But there's to see the thing is, the real jump that's happened is the jump in computing. There's no question.
Dean: There's been a monstrous jump.
Dan: It's a billion times since 1970. It's a billion times. That doesn't translate into money, and money is what productivity is based on. How much more money are you making per hour of human labor? How much more money are you making for our human labor? Now maybe somebody will say well, we got to start counting the robots in our GDP. Something is doing work. Yeah, Just I mean wow, wow, wow, the only problem with you know the only thing about robots, though they're shitty consumers.
Dean: Yes, exactly that's so funny. Yeah, they don't buy anything you know.
Dan: Yeah, A computer is a good worker, you know. It doesn't take breaks, doesn't get sick you know doesn't form unions anything. You know it doesn't go home, it doesn't have a house, doesn't have furnishings doesn't need furniture doesn't go out to eat.
Dean: Right, right. We're definitely in a stage right now where there's opportunities more than ever for economic alchemy, creating money out of nothing, seemingly compared to 1975.
I'm not sure how that happened, I think, since in the digital world we're essentially creating money out of ether, you know, out of attention, even in a way that if we just take the attention economy or the portion of the money that is derived from the advertising world in, where it was print ads, television ads, radio ads those were things that were kind of happening in 19, right and, but they were selling sort of physical goods, whereas now I remember having a conversation with Eben Pagan about this, when I did a book Stop your Divorce in 1998, when it was when PDFs were just coming to be a thing where you could create a digital document that didn't require printing a physical book and you could email that or somebody could download it.
And I just realized that you know, in that we've literally sold $5 million of a picture of a book not physically printing. These thousands and thousands of books, it's literally no zero physical good. That's why I wondered about whether the GDP is only measuring you, because we're definitely in a time where you can create money from nothing and the way that was driven was from Google AdWords.
Dan: You can't create anything from nothing. No, I mean nothing physical, any. You can't create any. I don't think you can create anything from nothing there. No, I mean okay, nothing physical. Okay, that's what I mean.
Dean: Yeah, like you look at it, that the book, you know we created the book and turned it into a pdf that was put on a website that there's no physical manifestation of it's, only digital. You can only see it online. People would search on Google for save my marriage or how to stop a divorce, or any of the keywords we could magically get in front of those people on their screen. They could click oh, stop your divorce, how do I do that? They click on that. They read this digital.
It didn't cost anything other than what was paid for was that we paid google for the, you know, for sending that, you know the ability to display that person, that opportunity to somebody. We paid google every time somebody clicked on that ad and then they would buy the book and it would automatically take them to a page to download the book. There was no inter, no human interaction and no physical exchange. It was all 100 digital and that was where, you know, I started referring to that as alchemy, really like creating money out of of bits. You know, yeah, yeah, that's so that.
Dan: Yeah, I think there's no I think there's uh no question that we've moved into a what I call a non-tangible realm of creating value, creating property and everything else, but at the end of the day it all adds up somewhere where this constitutes an economic transaction and as far as the accountants care, they don't care whether it was something physical or sold or everything. There's taxes that are taken out of that. I don't see the remarkable difference. You're using a different medium, but there is work that goes into that.
And you had a big payoff with one, but there were another thousand people right at the same time you were doing that and their results? They put in a lot of work, they put in a lot of effort and it didn't produce any money whatsoever. Efforts go into GDP, your efforts go into GDP and there's way more of them than there is of you. So it brings you the overall results down and you know so and we kind of know. We kind of know that. You know productivity numbers. You know, like, on a year I know people talk about well, that productivity is going to go up by 20% as a result of that.
Well, that may be true for a single company, but that's not true for the industry they're in, because their new thing going up by 20% may actually make obsolete 5 or 6 or 20 other companies who have had productivity that a year before, but now they have no productivity at all. So their loss of productivity is balanced against the gain of productivity.
Dean: Yeah, that's interesting. I guess you think about that. That could be true in all the casualties of the digital transition here, right Like, what do you look at?
Dan: Well, certainly the advertising world, certainly the advertising world, I mean before Mark Zuckerberg and before Google, newspapers like the New York Times.
Dean: Daily.
Dan: Edition was very thick.
Dean: Yeah.
Dan: And half of it was advertising. Now it's very thin okay because, they don't have the same. Yeah, but there's winners and losers, you know, in this, and you have a technological breakthrough, you have far more losers than you do winners.
Dean: Yeah, I'm looking at like I was just listening to an interview with that Tucker Carlson did with someone I forget who, some former CBS correspondent you know, and they were talking about the new. You know what's really changed now is the reach capabilities you know, like Tucker really primarily being on his own platform but using the reach of x has, you know it's the audience is accessible to everybody, as opposed to him in the beginning of their careers, the only way to get reach was to be signed to a, a digital, or assigned to a traditional network where the eyeballs were.
But, now the eyeballs are accessible to everybody and it really becomes these are my words, but it's more of a meritocracy in a way that you're you know that it's available for everybody. The cream definitely can rise to the top if you've got a voice that people resonate with.
Dean: Yeah, I mean, and Tucker's a star, tucker's a star. He's got his following, he's got probably a couple million followers. Whatever he was big when he was on Fox and he had the top numbers on Fox and everything like that, but there aren't two of them.
Dean: Right, and you can't replace him with an AI either.
Dean: No, but what I mean is we pick out the winners. It takes a lot of losers to get to a winner, you know and I think this is more extreme in the Cloudlandia world than it is in the physical world- you know. I mean, I think there's a thing called network effect and the network effect is you can only have one Amazon. Basically, you can only have one Amazon. Because, the nature of Amazon is to suck everybody's customers up into one destination.
There aren't five Amazons competing with each other, and that's what digital does. A person like Taylor Swift couldn't have existed 20 years ago. They wouldn't have had the reach. Yeah, that's true, and she's got the reach today.
I mean she's coming along and she's got a lot of things going for her. She's very attractive, she's very productive, she pumps out songs all the time and the songs seem to resonate with a mood in the public right now. And everybody's got their cell phones and everybody's got that. And what I'm saying is, if you have one Taylor Swift, you can't have two. Well, yeah, that's.
Dean: I mean it's, I wonder you start to see that she's just a, she's one voice, right Like I look at, I've been following rabbit holes like up the chain. You know and I start so Taylor Swift is a good example that many of her biggest hits and biggest success have been in collaboration with Max Martin, who is a producer who I often talk about and refer. Second, he's got the second biggest number of number one songs to his credit, right behind. He just passed Paul McCartney or John Lennon, and only Paul McCartney is ahead of him. Now he's about five songs behind Paul McCartney.
What I realized is, you know, there's a way that it's kind of like you get max martin's voice is really what is, you know, behind most of the the most popular music, or much of the most popular music, and yet not many people could pick him out of a lineup. And then then I went another layer up. It just dawned on me, like in the last couple of weeks here, that the real catalyst to Max Martin's success was Clive Davis. Who is? Do you know who? Clive Davis is the former, or still, record executive.
Dean: He was the head of so far, your records so far. So far, you're introducing me to a lot of new people.
Dan: Okay, great well, I, I just love this that. You know, max martin, I've been saying, as that's the thing, like you think about one thing Max Martin's one thing has been making hit records. Right, that's all he's done. Making pop songs since 1996, or what is first number one. But if you trace it all the way back, the catalyst to it because he was in Sweden, there was a group years ago called Ace of Bass and they had a number one song.
But when you go all the way back to how that happened, it was because Clive Davis, who was the head of Columbia Records and all its subsidiaries, arista and Jay Records, and all its subsidiaries, arista and J Records and all of these things, he found that song. He's like a guesser and better. He was guessing that song is going to be a hit and he signed Ace of Base to bring them to America. So he plucked this obscure Swedish band out of and brought them to America and on the wave of that, created the opportunity for Max Martin to work with all these great artists that happened to be under the direction of Clive Davis. And if you go even one layer beyond that, the guy that owns Bertelsmann, you know G Music Group in Germany. They own almost all the record labels, kind of thing. It's him seeing Clive Davis and putting up a million dollars for Clive Davis to start this record label. It's amazing that it all, kind of you know, goes back to capital allocation.
Dean: But the big thing is none of that has to do with any productivity.
Dan: Yeah, that's the thing I wonder, you know, I mean that really.
Dean: No, well, what you're talking about is. You mentioned a name. Yes, and he does this and he's very successful and he's famous for being successful. But at the same time that he was doing what he was doing, there were 9,999 who were waiting on tables and doing this on weekends and nights, yeah, okay, and they weren't making any money at all. So what.
I'm saying is when you pick a winner out and you see, see how productive they are using new technology you also have to account for the people who are using the new technology and not making any money at all, and therefore it's not more productive. Yeah.
Dan: Yeah.
Dean: And I mean, you know we haven't talked about him for a while, Mr Beast. Yeah, and people say, see what you can do when you're 18? You won't see anything because he's so unique. And he has such a set of circumstances that there's nothing that he does that is repeatable by another person.
Dan: I mean, yeah, he just became just in the last, I haven't heard anything about him.
Dean: Is he still doing stuff? I don't know. Is he still doing stuff? I don't know. Is he still doing stuff? Yeah, yeah, he just became. Or is he retired at 28?
Dan: No full steam ahead.
Dean: He's got a 300-foot.
Dan: He just became the number one subscribed channel in the world. He was the number one individual but there was this T-Series channel in India, which wasn't a person a different thing. Now he's the number one thing. He's now working on an Amazon show. He's taking his stuff to to amazon still full steam ahead with his, with his videos, but he's doing a big game show series in uh with under the amazon banner yeah, yeah, yeah.
Dean: it's really interesting because you know again I go back that it seems to me that a lot you know and I've made this statement before is that a new technology comes out, or a new form of a new technology comes out. A whole series of people say I'm going to create a new company based on this technology and I want you know, I need some early investors.
I need investors to get there, and so there's a whole industry for doing that in Silicon Valley and other places, and so billions are raised, not just for the one you know, not one investment, but for let's say 50 investments. And none of them go anywhere, none of them go anywhere.
Dan: You know, nothing happens, okay, but people did make money because it's based on a Ponzi scheme kind of thing that the early investors get paid out by the late investors who end up pulling nothing and everything else.
Dean: None of that represents productivity. Right A lot of action, a lot of excitement, a lot of money, but no productivity. And we're seeing that with AI. Goldman Sachs, the big investment bank, came out that, going on two years since open AI, we just don't see that there's any money to be made with this, except if you're like the chip maker, NVIDIA.
They make a lot of money and they're very productive, and I think the reason is that I think that AI, if I look at the next 10 years, I think it's going to be very effective, it's going to be very useful and it's going to be very important for solving complexity problems that we already have on the planet. Okay, and you know, a great example is just large city congestion complexity, like Toronto, I think, may have the worst traffic congestion in North America.
Dan:
I did notice a big difference in that, even in the five years since I was there.
Dean: Yeah. And the main reason is that they're making new cars, but they're not making new roads.
Dan: Yeah, and I noticed that they've actually added a lot of bike lanes too, which have taken out some of the actual lanes.
Dean: Yeah, Actual lanes, yeah, yeah, so without some new kind of solution to congestion and I think AI is the perfect tool for this and that all the traffic lights, all the traffic lights in the city are a single system and you're just changing the frequency of the lights changing and everything around the car changing the frequency of the lights changing and everything around the country, and there's a sort of a master view, how you know you can reduce the amount of people just stuck in the city by 40% if we just get all the lights. That's a complexity problem.
Dan: You know and for example.
Dean: The other thing is they haven't. You know, for all. The study of weather is probably the most complex system that we have on the planet and to this day they have no notion what effect clouds have on climate. You know they don't. They really. Clouds are just very complex. So if you had the ability to, I mean, they know different types of clouds and different things that happen when you have different types of clouds. They know that, but there's no unification of their understanding of the cloud system.
And so you'd have to apply it to that. Now, you're not creating anything new with this. You're solving an existing problem. With this, you're solving an existing problem. My sense is that the best use of technology is always to solve some problem that you already have not create a new opportunity that's interesting.
Dan: So maybe that's how I mean yeah, go ahead. I was just saying maybe that's how I should be thinking about my relationship with juniper yeah, what?
Dean:what complexity problems do you have?
Dan: Exactly what complexity problems do I already have that Juniper could solve for me?
Dean: Yeah, like getting out of bed in the morning. That's a complexity problem. When does my first coffee arrive? Exactly yeah, why am I still thinking about this? Why at this late date.
Dan: Oh man, that is so funny.
Dean: It is funny.
Dan: The funny thing is I posted up on Facebook right before we got on our podcast today. I took a picture of my. I have these. I have these Four Seasons Valhalla coffee cups and I took a. I made a coffee before our here and I posted up a picture of it right Pre-podcast caffeination, prior to the prior to our podcast here. So I'm fully caffeinated. I'm on the, I'm on the juice.
Dean: Yeah, I will tell you this. Chris Johnson, great thinker in the FreeZone program he's got it's not his system, he's licensed his system from someone else but he had 32 callers to set up meetings with their primary salespeople for his company and he's in the placement business. He finds really good high-level people to go into construction companies and engineering companies. And he was telling us that his 32 human callers could make 5,500 phone calls and produce a certain result in a day of phoning.
And since he's brought in his AI system, they can do 5,500 in an hour and produce a better result of people agreeing to phone calls. Well, that's productivity.
Dan: Yeah, I guess. So yeah, pretty amazing huh.
Dean: And he let go his 32 humans. Oh, my goodness. Wow, so this is AI making outbound phone calls? These are all AI and they've got complete voice capability of responding to responses and everything else. And then they get better every day. They have sort of upgrades every day for it. And that's productivity, that's productivity.
Dan: Yeah, there's, yeah, that's a. That's an amazing story. An amazing story, I mean, you start to see, I just look at the things, even when we had the AI panel at FreeZone in Palm Beach. You're just seeing the things, even what Mike Kamix is able to create and the things that Lior is doing. You just think, man.
Dean: I think we're early.
Dan: Yeah, absolutely, we're early.
Dean: Yeah, I mean I think we're in the first or second year of the internet with us, right?
Dan: Exactly, I agree. That's why I say, that's why, in my summation here, I'm kind of thinking you know 2025, give it another 18 months. It's only 18 months old now when you really think about it. Right, this is it's 18 months, and give it another 18 months and we'll see that people you're already starting to see that people are taking the AI capabilities and they're honing it into an interface. That is, a logo maker, for instance, or AI. You know that it's already honed into the ability to specialize in making logos based on your prompts, or and I think that's where that's what I meant by the interface moment is people are going to start carving out, packaging very specific outcomes from the capabilities. Like, if we have these capabilities, what can we do and just deliver that specific outcome, rather than the capability to create that outcome that's why it's funny that that's kind of parallel to what I've been saying.
I've seen people that are taking and training large language models based on your you know, all of the you know let's call it all the Dan Sullivan content that's been out there and then touting it as you know, having Dan Sullivan in your pocket, that you can ask Dan anything of it in your pocket, that you can ask Dan anything. But I think the ability to ask you anything isn't as useful as the ability to have Dan ask you things. Yes, I think that's the question.
Dean: So in the last quarterly book, and the one we're finishing right now. So it was everything is created backward, where the tool we featured was the triple play, and then the next one is called casting, not hiring, where the tool is the four by four casting tool. We call it the four by four casting tool, and this is where I'm asking them questions.
Dan: Right, okay.
Dean: I don't see any value whatsoever of them asking me questions.
Dan: Right.
Dean: Because I'm not getting the benefit of the question. Some software program is handling it, so I'm not learning anything and I've got a rule that I don't involve myself in any activity where I don't learn something new.
Dan: Okay.
Dean: So there's getting the benefits, but plus we'd be competing with ourselves.
Dan: I love it All, right Well off, we go.
Dean: I will phone you next week I'll be at the cottage. I'll be looking out at a mystic blue lake while I'm talking.
Dan: Oh, wow.
Dean: It's really good yeah.
Dan: Awesome. Well, have a great week, okay, and I'll talk to you next week. Thanks, thanks, dan. Bye.
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