Chuck Yates Needs A Job

0:20 Everybody, welcome to Chuck Yates needs a job, the podcast. We've got a cool, cool guest on today. We have Mark Mills, who is a Manhattan Institute Fellow. Now are you on the faculty at

0:34 Northwestern or are you a researcher associated with them? I'm a faculty fellow, faculty fellow, which sounds very lofty It means I don't have any obligations and I provide episodic advice. I get

0:51 to play with very smart people, maybe a lecture once a year. It's a

0:57 great university that I get to have an affiliation with, which is kind of like any kind of fellowship, if you like. I like that. That's

1:09 a long way to say I don't teach there and I'm not a professor Exactly, kind of like my association with digital wildcatters. What do you do? Well, I have a fellowship. We'll say that. And you're

1:19 also a partner at Montrose Lane, which I'm honored to be on the advisory board of. So. Yeah, it was a lot of fun. It's, as we'll talk about it, sort of epitomizes the center of my thesis,

1:34 which is the convergence of the world of bits and atoms.

1:39 Exactly. So, Mark, we can kind of cut to the chase on this It's been a really, really crappy 18 months. We've had the pandemic, we've had quarantine, we've had all this mess. So my audience

1:54 has come to me and they said, Chuck, we need a ray of hope, we need some optimism, we need some light. And I said, great guys, I'll go bring a physicist on to the podcast. But as I say that

2:10 with love and joking, you've written a new book It's called The Crowd Revolution. It, new technologies will in life. Unleash the next economic boom and a roaring 2020s. And so it's a really good

2:23 book. I've read it. It is very optimistic. So Mark, what's the story on this? What's the cloud revolution and why is it so great - Because everybody should know that advanced copies go out and

2:35 the writer never expects people to read them. So you get chops for reading an advanced copy, which I appreciate - I have notes. I've taken notes here And just to show that I paid attention to the

2:48 book, for the first time ever, I took notes on my notes on my iPhone as well -

2:55 Well, that's also perfectly thematic for my book of the merge of the world of bits and atoms because books are still strong. Paper still exists. We use more paper in the world today than we did 50

3:05 years ago. And we have more smartphones and computers in the world than we did 50 years ago. It's sort of the nature of what my books about But the funny thing about writing, setting aside writing

3:17 is If you take it seriously, it's a lot of work, which is fine. Lots of things are a lot of work. And it gets labels of optimistic book, and it is. And the title's optimistic. Revolutions are

3:31 not always optimistic. So some revolutions, like the Bolshevik revolution, wasn't so good for the Russian people. So that's why the subtitle, Adlishing the Next Economic Boom and Roaring 2020s I

3:46 prefer to view my analysis of the state of play as realism, that the fact that people label optimism tells you a lot about how rampant pessimism is in the world today. So, but I get it. I mean,

4:04 there's a lot wrong with the world. There's a lot of tumult to say. You call it a tempestuous time that we live in would be an understatement, given the last 18 months For a lot of people, it's

4:15 been a living hell. I'm not diminishing the carnage for humanity. It's been a

4:22 political hell for a lot of people. When you think about what a lot of governments have done, it's not so good, some good things, a lot of dumb things. And, you know, I begin my book talking

4:34 about the 1920s, deliberately, because I think technologically, there's a lot of an analogs of what's going on now, and we'll go on for the next century. But what's interesting about the 1920s

4:46 are the political and social and cultural analogs, and I talk about them only in a page, as you know. I'm gonna spend maybe, yeah, maybe a page. But anybody that spends five minutes with the

4:60 magic Google machine looking up things that were going on in 1920 and '21 will be amazed if you don't remember, most people don't remember their history that well, I get it, doesn't take much to

5:12 refresh it. But 1920 was. the third wave of the 1918 flu pandemic. It lasted almost three years. And the total carnage in America, in terms of per capita deaths with almost 400, four times more

5:29 than we experienced. So pretty ugly experience for America. It was at a time of civil unrest, race riots all over the country, thousands of troops called up. Charleston, South Carolina put under

5:42 martial law of race riots. That's when the Tulsa bombings happened, which was a new book out on that, when the US Army Air Force bombed the black neighborhood in Tulsa, Oklahoma, for goodness

5:52 sake. I mean, talk about toxic race relations. The anarchists were in a cent then, bombings in cities all over the country. Jake or Hoover warned that in May day, 1920, there'd be an

6:06 insurrection and uprising, kind of sounds familiar. There wasn't one in 1920 election of 1920 was extremely contentious. of Harding One on a platform of return to normalcy. Women got to vote that

6:21 time for the first time in history, which was contentious, by the way, at that time. In hindsight, it shouldn't be contentious, but it was then. We had prohibition for good and to seek a

6:33 constitutional amendment to criminalize something human beings have been consuming since before recorded history.

6:41 We criminalized it And not for one year. It took, I think, 13 years before the amendment was revoked until the early 1930s. So there's a lot. I mean, the eugenics movement was in full swing at

6:55 that time, which was an odious, disgusting, racialized theory of humanity that was supported, embraced, and funded by the intelligentsia by universities and the tech titans of the day. So what?

7:09 And people were worried about income inequality Gold Coast and a billion air is there. not just a few people in

7:17 real terms, equivalent to Bezos and Gates and Elon Musk, but dozens and dozens of people in that kind of wealth class. So people were worried about income inequality then. So we, the point of

7:29 that - And we just got and done with World War I as well. And that wasn't a pleasant time, so yeah - That's pretty gross. So and people were worried about communism while running America, because

7:41 of the Bolshevik Revolution of 1917. So it was a pretty ugly time in many respects to be in America. What happened next is we had the roaring twenties, incredible blossoming of jazz, music and

7:56 dancing and literature and incredible economic growth, beginning of the longest, biggest boom of an economy in all of human history. From 1920 to 2000, per capita wealth in America up 700 in real

8:10 terms. Average lifespan went up 30 years. How did that happen? It didn't happen because of the politicians or because of economists. It happened because of what engineers invented and what they

8:20 created. It was a confluence of sort of incredible series of revolutions all related in machines, materials and communications, radio, telephone, cars, airplanes, steel, polymers,

8:35 pharmaceuticals, all these mass production, all happened contemporaneously It's that feature that my books were, that contemporaneous convergence of revolutions in 1920 propelled the 20th century.

8:48 I contend, as you know, I map out of my book, that the exactly the same character of contemporaneous revolution is happening in exactly the same domains of machines and materials and our

9:02 information system. And of course, in the middle of it now for the first time, we have something really different. The thing, you know, you said, people talk about is this time different? Well,

9:11 this time is always different in some ways, right? You have to sort of discern what's different or what's not. But what is different this time is we have an infrastructure, the cloud that is

9:21 different in character and power and scale. It's quite unlike anything in human history. And it amplifies all three revolutions. So I think we live in the cusp of a potential boom that equals or

9:37 exceeds what started in 1920. So Mark, let me ask a question about that because as I was reading your book, you even point out on the cover that it's, a lot of people just think one event happens

9:52 and boom, that leads to everything. And you talk about the confluence of these three information, machines, materials coming together. You use the term actually serendipity a lot when you kind of

10:06 talk about the convergence of those three Did that?

10:11 come together in your mind, because I think you're using that really as a predictive framework or a predictive modeling tool. However, we want to describe it. Did that come together in researching

10:24 this book? Is this your lifelong theory that you've based things on? How did you come up with that kind of framework?

10:37 It's a good way to frame it, Chuck, that it's not so much a lifelong theory, but it's a lifelong learning that I began my career. I was a theoretical, trained in theoretical physics, but I was

10:50 practical in a sense. I raced motorcycles when I was young in a mortal I was a mechanic, a machinist. My first job was in a semiconductor fab, building things, and I worked a missile guidance. I

11:04 actually made stuff with my own hands, Scott Patton's. I've always been fascinated at how things work. And as I learned more, got more fascinating with how governments work, how economies work,

11:14 how companies work, which is why I'm involved in an event-driven business as well. So how things work is interesting, and as the more you learn, and the more you study and experience, one

11:27 develops a theory, right? You begin to see patterns. Human beings, and as I read in my book, are pattern recognizers. It's wired into us. Anthropologists would say that's because, the rustling

11:40 of leaves and heavy breathing of a tiger in the jungle, you begin to figure out that pattern is not a good sign, or cloud patterns when you're a farmer in 1810. You look at, we're pattern

11:51 recognizers, but this is wired into us. And we can ignore it, and sometimes patterns can deceive you, so I get that. So the lifelong exploration that I've been interested in has really been about

12:04 technology and how it influences the other things, new technologies. So there's two, there's, there's sort of, we could divide it into three buckets. And my book only talks about one of them.

12:17 How do we get new technologies? How much is serendipity of play? How much is government role? What, how does, how does innovation happen? Really important stuff. And if theory is on that, I

12:28 may write a book on that. But it's, and I write a little bit about that. The last two chapters are about innovation and science, because I think the cloud is a great accelerator for new innovation.

12:41 It's going to help serendipity. But the second part is, okay, what happened? What got innovated? Not how did it happen? Let's just look at what actually happened. And then ask what the

12:54 implications are, which is what my, my books about. And the third bucket is what kind of political system do we need to ensure the first two can happen? Innovation can happen. We can unleash

13:07 serendipity and planning, we have to plan, and to get the good outcomes, not just the bad from new technology. So they're all relevant. But one can write a whole book about governance and

13:21 planning, whether it's a corporate planning or the federal government or state governments, and you can write books about people have how innovation happens. I will say to your point that

13:34 what learns is that there's a set of predicates you need to have innovation happen You have to have smart people be motivated, have the freedom to do what they want to do, get funded, all those

13:44 things matter. But serendipity is far more common than most planners would like and realize. Serendipity doesn't just mean that somebody's drinking vodka in their backyard or shooting squirrels and

13:59 they have an epiphany. Serendipity happens because there's smart people trying to do things, trying to discover things, trying to invent things.

14:08 the Aham moment happens when and where the serendipitous discovery happens. It's very difficult to predict. It's predictable in that it can happen and you can predict the framework of what will

14:20 happen. But who will do it and when those hood is really annoying. Exxon researcher in 1978 invented the lithium battery. Who knew? I mean, people today don't even know that. So Elon Musk,

14:34 quite a few years later, revolutionized the expensive automobile, the expensive part of the automobile industry. But he didn't invent the lithium battery. He makes a really good battery, probably

14:49 better than anybody else's car battery, arguably, really good engineers. But how did the lithium battery come to be? Well, the chemist doing the research wasn't trying to make better beer.

15:02 That's a lot of kind of serendipity. He wasn't a distiller. He was trying to figure out how chemicals work He was trying to do that, right? That's what his job was. And serendipitously, that

15:14 smart guy got a Nobel Prize with two others who helped to realize the practical side. That's a long answer to, I think, it is a lifelong goal to figure out how those things work. But I thought I'd

15:27 write a book about the consequence of recent inventions and what they are rather than how they happened because you don't have to explain how they happened to say they did happen, right? I mean,

15:40 that's - Yeah. No, 'cause it's interesting in that you gave the framework based on history and you could look at that somewhat cynically and say, Well, yeah, in hindsight, you're able to put

15:52 together this. But you actually use that framework going forward to make your predictions on the Roar in '20s. And so what I thought we might do is kind of just drill down into each one of those

16:03 buckets. So you can tell us what's going on in the buckets why they're important. and maybe we'll start with information, infrastructure. I'm calling that the Ss, superhighway sensors, silicon.

16:17 What's going on there that's got you excited that that's gonna lead to our roaring 20s - So, we've always cared about information, and both in terms of how we collect information or data about our

16:30 world, how we record it, how we store it, how we share it, and how we analyze it I mean, that's been going on as I write in my book, predating the time of the library of Alexandria, but the

16:44 library of Alexandria was the iconic first, we'll call it cloud of its day. It was the first real library containing probably millions of volumes where the Dewey Decimal system, although it wasn't

16:57 called Dewey Decimal, that was invented specifically, but the catalog system for finding information was invented by the Greeks.

17:10 If you sort of trace information over history, you find that there are changes in character or how easy it is because of technology to acquire and store and share information. Obviously, acquiring

17:23 it without any instruments, using your eyes, look at nature, look at how humans behave, recording in a papyrus and rolling it up, then having to go to the library to learn about it and think

17:34 about it and analyze it and then share it by traveling on a horse or camel to tell somebody. Pretty inefficient. So you can sort of trace the history of information through those three, I will call

17:46 it, magisteria. That's what we've been doing from the pony express, the telegraph, the telephone,

17:52 to the printing press for recording, then to radio, television, the internet. My core thesis is this, that the three key metrics of how easy does it get information or sensors. that are wired

18:08 and wireless, especially wireless sensors, that can disappear into the fabric of our life, the fabric of nature, fabric of machines. The ability to transmit information, which is we call it the

18:19 internet, but it's more than that. It's microscopic radios, right, and fiber and glasses and satellites, but their constellation. And our ability to process it in a computer, so three things,

18:29 a constellation of things, each by themselves, is orders of magnitude better, more powerful, faster than anything in history And altogether, they form what we would call the cloud, which is more

18:43 than the sum of its parts. It's an astonishing shift. The cloud is a bigger transformation in information over the internet than the internet was the transformation over telephony. And going from

18:57 telephone to the internet was a big deal. I contend going from internet to the cloud is a bigger deal. And I try to prove that, as you know, with data. on number of nodes, speed, costs in the

19:10 book - Yeah, I mean, just your discussion on having to come up with different names for the amount of information we have. I mean, yeah, who would have ever thought - You know, it's crazy 'cause

19:26 words matter, 'cause words are the way we communicate, express things and, you know, form frame ideas. It's how we philosophize, how we relate So that's why I was so focused and fascinated by

19:38 just the numbering nomenclature. And people don't, the numbers are astonishing. You know, this computer science professor, JC Licklider from MIT back in the '60s was probably the first guy to

19:51 really think about how to express our information quantity in numbers other than pages or quantities of books. And he comes to he was computer science this back in the 1940s series.

20:07 Ben Everbush, Ben Everbush was the science advisor to President Roosevelt. He was the one who created, you'd arguably created the modern research state that we have today in National Science

20:17 Foundation. He wrote that the quantity of information in journals and books, talking about technical stuff, was overwhelming in that we were generating an quantity of information that required us

20:32 to essentially operate in the modern era, like we were fighting a war using sailing ships. So the war of words, analyzed data, was that the volume was at a level that we're still using antiquated

20:44 technology. He imagined computers would do better 'cause he was one of the early inventors of parts of computers. And that's of course what happened. And then we have to start counting these

20:55 invites. That's what we do. Everybody's familiar with bytes. Everybody talks about how many gigabytes they have of this, gigabytes of that, throwing around gigas like they're just, I don't know.

21:05 It's totally winks. It's that a manhole covers. A gig is a big number. It's a billion or something. And it used to be that gig is room. So then we had to make up new words. Is that a byte? She

21:14 out of bytes. But I love the fact that there's an argument going on between how to come up with bigger numbers than zettabytes, which is how we sort of measure the internet today. Zettabytes of

21:24 data. It's a number that's unimaginably big. I mean,

21:30 three zettas of data is sort of what the monthly traffic is, zettabytes of data on the internet and the cloud. If I stack up three zettabytes of dollar bills, just to visualize how big the zett

21:42 number is, the dollar bill stack would go from us to the sun and back. Right? Yeah. Millions of times. These are astonishing big numbers.

21:57 Do they have consequence, other than being kind of fun big numbers? Yeah It's data, it's information. It's the, you know, the expression data is a new oil? Well, it's actually not sort of,

22:09 it's sort of a silly expression in some sense 'cause data uses energy and oil is a source of energy. But it, in the philosophical sense that what are we, mine, what are we gonna go refine to get

22:23 more value in our mine is in gonna go refine We're society?

22:27 incredible data trove -

22:30 Yeah, now there are two interesting kind of stats when it talks about amount of information. The word on the street is that oil and gas companies use one person of the information. They actually

22:42 gather out in their operations and whether it's one, two, three percent, whatever it is, it's stunning the amount of information that's not being used. And I used to have a partner back when I

22:54 was at Kane Anderson, reservoir engineer that always said, there's no such thing as an oil field mystery We just may not have the. the sensors to be able to gather the data so that we can prove

23:07 whatever the scientific truism is with that. And what's wild is we've got all of this data and so will we be able to find more and more of those truisms? And I think the answer to that's obviously

23:22 yes -

23:24 Yeah, I think there's a no question that we can believe that the answer is yes. What we don't know is how much horsepower we need of a computing kind to get the TZ answers out. And we also don't

23:37 know how much more data we need. So your colleagues come is correct. The data are there. So we already only use, this is true not just an oil and gas industry, it's true in every industrial

23:50 sector, it's particularly true in the biological human health sector. We have far more data than we use to make integer, We just the data are there, but we can't.

24:02 collect them in an organized clean way, if you like. We can't synthesize them properly yet. Part of that is because we don't have the tools yet. It's as amazing as the cloud is. We don't yet have

24:14 fully deployed tools that make it really easy to collect data and clean it up so it can be used, which is not much different than any resource. You know, we have lots of, we'll live them in the

24:24 Earth's crust, really hard to get at it a lot of it. So it's that kind of thing. And then the magnitude of the computing power we need to really do the kinds of things, whether it's an oil and gas

24:35 well, whether it's to mine silver to make solar cells, whether it's to manage supply chains that are complex and global, massive amounts of data. We probably need computing power, at least in

24:49 order of magnitude better than we have today. But I don't, it's no mystery if I say to you or any, nobody would be surprised if you say, Okay, well, wait a few years, we'll have that. That's

25:01 what's happening. My real point in the book on the information part is that the speed at which computing is getting better, we'll call it the artificial intelligence feature computing, but the

25:11 speed of computing power, in terms of how much compute horsepower you can get per dollar, that's actually getting better at a rate faster than the vaunted Moore's law. It's actually accelerated in

25:24 the cloud era 'cause the cloud is a utility, increases both the power while simultaneously decreasing the cost at a rate that's never happened, faster than the internet did it. So whatever

25:37 expectation we had that computing power would get better fast based on our experience of the internet for three decades, that is now going to be amplified, which is totally impossible to do in the

25:50 physical world. You can't amplify rates of change 'cause you hit limits, but in the information world, we don't even know where the limits are. Well, and it's crazy, this stat blew me away and

26:03 I'll probably misquote it so correct me, but you said that a 10 by 10 spot in a data center today contains more computing power than the whole planet had in 1980. And we had sent men to the moon. I

26:19 mean, it's crazy - I know. I mean, the compute horsepower of what we do today is off the charts better and as good as it is. And let's just, we'll talk about the good and bad of what we do with

26:36 this computing power 'cause like all technologies, not everybody that builds computing systems do it for things that others would consider useful or moral or whatever, but the progress in that area

26:37 has been sort of

26:50 independent from and different than the progress things like going to the moon. We've got better going to the moon, Elon Musk and Jeff Bezos have shown. that they might have a shot at getting,

26:58 they didn't get there yet. So nobody else has got back there yet. It's really hard. That's because you're dealing with, just to be simplistic, atoms are not bits, right? You can't, if you

27:08 could take a human being and do what they did in Star Trek and digitalize to take the white space out, teleport to the moon, boom, bada boom, you're in the moon. Thing is, when you do that to

27:18 human beings there, it's a one way, yeah, I mean, you can take them apart, but you can't let them, that's just - I don't wanna go first. Yeah - I wanna be the guinea pig on that one. You know,

27:28 it's really funny. So Captain Kirk, William Shatner got to go up and space with Bezos. And as it turns out, kind of long story, I'll tell you at some point, next time we grab a drink, I'm

27:40 really good friends with Lee Majors. He lives in Houston, we've met - No kidding - Yeah, and so - This is William LR. Mann, my man - Exactly, and he's sitting there going, I like William

27:51 Shatner, he's a good guy, we're friends, How does the 6 million man not get to go to space first? Yeah, come on. Well, you know, Hall was Lee Majors now. He's got to be 80. 80, 83, I think.

28:03 And he's still healthy, I hope, go willing. In great shape. Yeah. So he should be the first man to wear - do something with exoskeletons, because that would be perfect, right? There you go. I

28:15 like that. We'll work on that one. One of the - as you know, I write a lot of an exoskeletons in my book, and one of the most interesting new features of technology that's emerging, that'll

28:26 emerge far faster than space tourism, because that's just going to stay really hard, because you've got to take really big rockets that are kind of dangerous, got better, that use hydrocarbons, a

28:36 lot of them, to fight gravity. We're stuck with gravity in the universe we live in. So I mean, I love space travel. I grew up as a space nut. I watched the first episode of Star Trek I wanted to

28:49 be who didn't want to be an astronaut. If you, come on. when you were a generation that we're from. But anyway, Lee Majors, we got to come up with a little exoskeleton - Well, this was

29:02 interesting. We went and saw Coldplay together, me and Lee Majors. And I said, I want to go meet Chris Martin and Lee goes, okay, so we're backstage meeting Chris Martin on one side note. I'm

29:16 like, hey, Lee, how'd you get us back here? And I go, well, I called Blythe Danner and that's her son-in-law You know, and I'm like, oh, okay, well, that makes perfect sense. But it was

29:26 cool because now Senator Mark Kelly, the astronaut from Houston, was backstage. And he actually told Lee, he said, the whole reason I wanted to be an astronaut was watching the 6 million man - Oh,

29:38 nice - As a kid - Yeah - Stylize - But there's a lot of that history in technology. It happens more than you think. The stories inspire people. The development of the smartphone,

29:52 first cell phone, not smartphones, the first wireless telephone, the inventor of that Motorola was inspired by the Tracy Comics and his watch.

30:05 Before it became a video watch, it was a radio, a wireless radio on his wrist. The cartoonist imagined the TV part of it later, but it began before World War II as a radio. And it could remember

30:19 World War II, the smallest radio, was a big heavy 80-pound backpack, right? That was a smallest radio for the military, the GIs carried around. And this predates that, and he imagined a wrist

30:30 radio, that was directly what influenced the engineer at Motorola who said, You know what? I can do that. And of course, his radio, everybody's seen the original brick cell phones that are made

30:45 famous by the movie with Michael Douglas in Wall Street Right. So one other thing while we're on information infrastructure, before we jump into the other buckets, I'm not sure I followed this

31:00 directly, so very ignorant question coming, but in effect, computer chips changed from Boolean logic, or they didn't change from, there was an additional type of chip created that is really

31:15 driving us towards artificial intelligence. Walk me through that, 'cause I had no appreciation that that was happening - Yeah, I think the thing that's fascinating is this change to a new, not

31:30 replacement, but additional class of architecture for what the microprocessor or the computer chip does. So everybody's heard the word binary logic, the chips use zeros and ones to be coded to do

31:44 things. So in effect, they do things by, we'll call it brute horsepower, right? These make them faster and faster. and you do things linearly. And there's nothing wrong with linear logic. You

31:55 just do lots of things in parallel if you wanna speed things up. But analyzing images is kind of hard. If you think of, just think about the difference between analyzing a spreadsheet, which is

32:07 linear numbers, and you wanna look for whether the bottom entries line up, you could just do a second spreadsheet, compare them, it's very linear. And you can imagine making computers do that,

32:18 it's what they do But if I have a picture, you and I looking each other, I want the computer to recognize you, face recognition. How do you do that? It's an image picture problem. A lot of

32:30 things in life are more like images, more like pictures, theories are more like images and pictures, right? But they're not unrelated, they're related phenomenologies. So if you wanna generate

32:40 an image, forget about it, first, if you wanna analyze an image, you'd have to first generate an image. I mean, the technology, analyze it is the inverse of making it, so to speak. So if you

32:50 want to make an image or things equivalent images, what literally make images, you have to come up with computers that can do that if you want to make say a video game, right? Because I got to

33:00 make images. Well, the first computer games like Pong were literally like digital images, right? If you could remember everybody else they'd look like. It's like old matrix of things go literally

33:12 and linear matrix. Yeah, being a little matrix, things go back and forth in a simple linear grid. To make video games look real, I have to generate real looking images. This is the story of

33:22 NVIDIA and

33:27 the GPU, the graphics processing, making computer chips, architecture and software, it's embedded firmware, says that it's designed primarily to generate an image. So not that you can't do it

33:39 with the brute force, is that it's a lot harder, takes a lot more hardware, it takes a lot longer. So you accelerate the process by making it dedicated to just make images. turns out that's

33:50 exactly what you need to do to analyze images, who's surprised, or to analyze patterns, whose images are basically patterns. So I've just used the words for artificial intelligence or machine

34:01 learning. So the theory of machine learning and artificial intelligence, which is essentially a pioneer by a lot of pioneers. Hinton, professor of mathematics at University of Toronto, was

34:12 generally credited as the guy who really put the idea together the way that Turing did for linear logic So theory couldn't be executed on computers because you couldn't build enough computers fast

34:24 enough. GPUs come along, boom, they have the horsepower to do it because they're just doing it differently. So modern supercomputers, and that's true of things that are in the cloud, it's also

34:34 true of your, your, your, your, your smartphone, have both kinds of chips, both kinds of logic. They do both. So you merge the two kind of the way human beings operate. I mean, think about

34:44 it. We do some things by intuition We do some things by sort of rope. learning, right? But they aren't unrelated phenomena. You do both. When you learn to do a skill that requires sort of linear

34:58 learning, you also simultaneously doing things that are sort of gestalt-like. Anyway, those two classes of chips now, we'll call them the logic and inference chips. There's lots of flavors of

35:11 them, there's lots of companies making them. But the growth in the graphics, some of them are called tensor processing units, some of them are called neural processing units, all kinds of

35:20 different words. The basic point is that you're not doing linear logic, you're doing sort of image and pattern recognition. And so kind of along that lines of not appreciating what was going on,

35:34 if we look at kind of the materials bucket of things, you've got a really interesting quote in there that history, and I'm kind of bastardizing the quote. But it's history is free. Feel free.

35:47 That's the whole point. Fair praise, Bowser. But basically the history of materials is us extracting from the earth, and it's really now morphed into no materials is us creating really cool stuff.

36:01 Hey, we wanna go do this. Can you give me a material that makes it? I don't know that I had a full appreciation for that happening, and I'm gonna layer on top of this, and then I'm gonna let you

36:13 run with it. But also you point out silicon may be unique in that it can help us change how we use other materials, which I've found pretty interesting. Never really thought through that, but if

36:29 we're gonna go create cool stuff, it certainly helps to have some horsepower to do it. Yeah, I mean, sorry, the philosophical note, that's what I find interesting, and it's relevant, that

36:42 a specific material can have qualities that are unique and amplifying everything else So you could you could to use a sort of a ham-handed analogy I did put in my book,

36:54 the stuff that we eat, the foods that energize human beings, they're materials, they're biological materials, but we as a biological engine convert them that those materials into other forms,

37:08 muscles and brains that can do things that those materials can never do. Silicon is, if you like, to the inanimate world what our biological cells are to the inanimate world. I mean, that's sort

37:20 of the kind of thing that's going on. It's really a big deal. I mean, it's a bigger deal than discovering copper, I think, because of the, what you make, it's an amplifier. It's not just like

37:29 copper is cool and I could do stuff with copper, I couldn't do the iron. That's a big deal, but copper didn't amplify the physical world the way silicon amplifies the physical world. But you're

37:41 right, so the character of humanity is that nothing that exists exists without materials. as soon as you stated, it's like, well, to use a Gen Z expression, that's no dah. But

37:56 all the atoms that are in you and me, all the atoms that exist in our civilization have always existed for as long as we know the universe has existed. There are no new atoms. We create, that's

38:08 not true. When a supernova happens, it creates new atoms out of old atoms. But absent that detail in astrophysics, the atoms are infinitely recycled, except when we have nuclear fusion invasion.

38:20 But the majority of the materials in the universe that we use on Earth, 999999 - we get to reuse it perfectly, in that sense, if you think about it, over millions and billions of years.

38:32 But most of humanity has had to deal with building things to make life possible from natural materials using the properties that nature gave those materials as they exist in nature Good, iron ore,

38:45 copper, and we - You can use copper to get electricity 'cause we discovered it can do that. But that's all you can do with it and that you have to use the property that nature gave it. So all of

38:56 the things that were built up until roughly the late 19th century were built out of things we harvested from nature, leather and bone and granite and copper. And then we started making metal alloys

39:11 but those were just clever addition of information using the properties of, you make bronze out of two different metals, right? You make steel out of coal and frankly and iron ore. Now we get to

39:28 the early 20th century, late 19th century and chemistry discovered pretty cool. Chemistry changed the world. Whether people like it or not, if you look around you at any given moment, I would

39:39 dare say, we'll measure what pounds, not in dollars because the pounds are what matters to the physical. our physical environment. Look around you, except for using some very ancient materials

39:51 over and over again for all of history, wood, most thousands of them in the wood and stone. So we've been using those for a few tens of thousands of years. But most of the new weight of all the

40:00 new stuff in your my life is our plastics, polymers, and chemical materials. We revolutionized the world in terms of conference and conveniences, all kinds of new features because of chemistry and

40:15 pharmaceuticals. That's a big deal. That's the one that started in the 1920s roughly, or just before, in terms of maturity. And really made a difference to the whole world, proving quality of

40:27 life, improving health care, improving food production, improving the quality of safety of materials and things in our lives and all that kind of stuff. Making clothing cheaper. Cotton trade was

40:39 the most valuable trade in the world for a very, very long time because cotton was so expensive, valuable. We still use cotton, probably use more cotton in the world than we did 200 years ago. I

40:50 think I know we do, but most everything you're wearing and I'm wearing is a few people have famously pointed out or chemically derived from hydrocarbons instead of grown on sheep's back or in the

41:04 plants. Both are valuable. Now we have a new revolution where we have something called the materials genome We now have in large part because of the information revolution in science. We now know a

41:18 lot more about how atoms and molecules combine and we don't know a lot more about it. We can pretend to combine things by simulating combinations in supercomputers. We can synthesize virtual

41:31 products. We can discover new ways to make things in silico instead of in laboratories, which accelerates the discovery process And then we can manufacture in the ways we could never have done

41:43 before. because we have machines that never existed before. So now we make things that, the two iconic examples I like are metamaterials and biocompatible or digestible computers. A metamaterial

41:57 is a material that we engineer that can exhibit properties that nature doesn't have. For example, invisibility. We haven't made really good metamaterials. I can make you and you and I invisible it

42:10 visually, but we can make things invisible in the radio wavelengths in the acoustic wavelengths. Probably we'll be able to make things invisible in the visible wavelengths with metamaterials. We

42:20 can create what's called negative index of refraction. You know, you put a, the experiment, everybody does in high school. You stick the knife in the glass of water and it looks like it's bent.

42:31 That's called refraction. And it always refracts the same way. I mean, you can do this experiment anytime. It's always gonna be the same way. A metamaterial can reverse the refraction direction.

42:40 Pretty cool. Impossible in nature. We now know that we can make, because there are patents for it and FDA approvals for it, digestible silicon, if you like, or biodegradable, programmable,

42:54 disappearing logic chips. We can make inanimate things that have logic in them that can disassemble and disappear and become just part of nature again on a sort of pre-programmed path so that if we

43:08 wanted to sprinkle smart sensors into an environment, they'll do their job and then just decompose by programming within six months, a year, whatever the time frame is, please so choose. Those

43:22 are no longer crazy ideas, those kinds of products exist. Those kinds of products never existed in the history of humanity. Some of them were not even imaginable in science fiction and now we're

43:32 being a manufacturer, things like that, beginning to. There are very, very few commercial products using these properties yet, that's what's beginning. That sort of the thesis is y'all. my book

43:43 is that the future is not what people have met today. It's what was recently invented that's becoming commercially viable right now. Yeah, no, the thing I found really wild, and I don't even know

43:58 what this means, but you point out a stat about substances in the chemical abstract services. Who knows what that is, but in

44:08 the year 2000, there were 20 million, and in 2020, there are 180 million. We're up ninefold. We have all of humanity to create 20 million and or find 20 million as the case may be. And now

44:21 there's nine times that. So that's crazy. And if you went back to 1920, the chemical age brought us tens of thousands of materials. And it's like the toolkit of things you can use to make

44:33 something from. Imagine it is like a chemical toolkit. If I want to build a house or a computer or a car, One of the materials available to make a car in 1918. Well, it was, we know, the list

44:44 is sharp. It's steel, leather, wood, copper, bronze. I mean, you could literally count a little more than two hands, all the materials that were made up in an entire automobile.

44:56 There are thousands of classes of materials in an automobile today. And there are tens of thousands of classes

45:05 of material in a smartphone. And if I take into account the fact that automobiles are full of smartphones, basically, there are tens of thousands of classes of specialty materials This sort of the

45:12 toolkit we can work from is that what that chemical abstract counts. When a new material is discovered or invented, of course, they're both the same thing. We don't discover it by digging a hole.

45:24 We discover it by doing work, usually in a computer these days. Then you're registered as a viable new material that has specific properties. And it's just like you go to a catalog. You know, if

45:35 any of us were mechanics, you know, or your house, you want to buy a new part for something,

45:42 Well, now we have 180 million parts to choose from, and it's still growing exponentially. What do you do with that toolkit? Well, you have a supercomputer, and the supercomputer says, give me

45:55 the toolkit, and it can do this. And you say, what

45:59 is the thing that I want to do? What is the service I want to provide?

46:05 I need to have a material to do that, whatever that is, whether it's flying a drone or curing a disease, then you ask the computer to go hunt from that toolkit, combination of elements, so it'll

46:15 give me that particular component to make the thing possible. That's the kind of discovery that's now beginning. It's the kind of discovery, by the way, that brought us pretty quickly to these

46:26 vaccines for COVID and are bringing us to the new therapeutics for getting sick in any disease, including COVID - Yeah, no, it's, I have my dad, and my dad describes himself as a retired country

46:40 doctor. But I had dad on the podcast and we talked through COVID, and that's one of the things he just went on and on about, wherever you fall out on the vaccine debate, it's still amazing that

46:52 they were able to get those things to market nine months or 10 months - It is. I mean, I write about this as well because it's an important part, and it's important to separate the politics from

47:04 these things. The politics are very important. We all know that. But the science and the facts of how we got to this vaccine are very interesting. And they are very encouraging because the

47:16 velocity tells you a lot about where the future is gonna be in healthcare. One of the things that's been going on in healthcare is some scientists created a funny

47:28 acronym called EROM's Law. They reversed the letters from Moore's Law, the acceleration of computing density. You have more computers, more computing power per dollar every year. E-ROM's law is

47:39 the inverse. you get more money, but less healthcare. That's quality of healthcare these past year. And we wanna break E-ROM's law. Well, Moore's law is gonna break E-ROM's law and the vaccine

47:51 development is a good example of sort of the iconic first step in that - Yeah. So the last bucket that you talk about or the last convergent factor is machines. And that was pretty cool reading that

48:06 stuff Exoskeletons and drones 3D printing. And to this day, I still don't understand 3D printing, but it sounds really cool. So what's going on there that's gonna change the, or cause our roaring

48:24 20s -

48:27 Well, I'm sorry, back, the three things you said and other things, other codes. So if you think about the machine world, machine world is sort of the apotheosis of everything else, right? We,

48:38 we, we. We need machines to do stuff. We've been inventing machines for a very long time. You know, the cart with a wheel and an axle with a horse and a yoke was a machine. It was one of the

48:51 first machines. Why do we invent that machine? I mean, we know why. It's a lot easier to have the cattle, oxen pole, the cart that have people drag around the rocks you just dug up or the food

49:03 you harvested - By

49:06 the way, I hugely agree with Bill Gates' theory that he always gives the most difficult tasks to the laziest person 'cause they figure out the way to do it with the least amount of work. And I'm

49:18 sure the guy that came up with the wheel wanted to sit on his couch and drink a beer instead of going out and hauling all the rocks all day - Yeah, of course we know there's been both chairs and beer

49:28 around just before recorded history. So, that example was exactly the but, is It right.

49:38 What phrasing it that way is an

49:41 amusing but correct way of pointing out that we want to chase efficiencies in society. We want to amplify human labor, human muscles, and the way you amplify them, the amplifiers are the machines.

49:54 The quintessence of that amplifier is not riding a horse. The car is an amplifier, if you like, of our legs. You could say that because sure it does a lot better job than walking if you've got to

50:04 go a thousand miles It does a lot better job than the horse, which is just harvesting some other bales' muscles. The queen of Sheba, you are harvesting the slaves carrying your

50:18 chair in the shroud. Machines have been wired into our human civilization DNA forever. As a taxonomy, look up what you do with information, what you do with materials. We build machines. We

50:33 build machines to go other machines We build machines to make drugs. to give us the services. You don't have fat acts without machines. You don't have a

50:42 restaurant without machines 'cause they harvest the food, they make the food cheap. We have machines that are

50:49 watching machines that make a lot easier for a restaurant. The list of machines is not as long as a list of materials, but it's a pretty big list, right? I mean, we used to only have a few dozen

50:59 kinds of machines on the whole planet. You could count, you mean, just think about the history, count the kinds of machines people have, more that existed in industry that you never see. I mean,

51:10 dozens, I used as my reference, one of my prime references is a two volume, 2000 page magisterial book on the history of machines. It's really great to read because the ideas these machines have

51:22 existed, says again, the time of the Greeks and the library of Alexandria. You're a hero, not a hero, but in the times of Alexandria, you had robots, they built robots that moved. automatic

51:37 doors, automatic lighting systems, because it not only won on the whole planet, by the way, because it was in Alexandria and it was obviously clunky by our standards, but pretty amazing if you

51:50 think about it in terms of thousands of years ago. So when you look at the taxonomy machines, you have to think about the whole universe of the other stuff because that's how you get to make

52:00 machines and it's symbiotic. Machines make the materials, the materials all the machines may say, these are not linear, but they're synergistic and symbiotic phenomena. But the kinds of machines

52:12 we can now build are as different from the kinds of machines we started about like 1920s as before that era. People knew there were cars, 'cause we could make a car, 'cause they had trains for a

52:23 hundred years by that point. So it was obvious you could have a wheel propelled, energized rolling machine, but going from training to car was a pretty big deal The question you'd have is what

52:35 comes after the car? what's better than a car? Well, everybody knows the answer. They knew the answer in 1820 that they wanted a car. It's better to have a free-wheeling vehicle than have one

52:45 stuck on a track. People knew that for a century. It took a long time to make cars viable. So the air taxi, which has been, you know, pilloried, vilified, laughed about, talked about since

52:57 Henry Ford, by the way. Henry Ford is like, What have I actually imagined flying car? Because it was obvious that there'd be an advantage to a car that could fly Turns out that's really hard to do.

53:07 I mean, the materials you need, communications control systems, the safety, the energetics, it's really hard. So despite the hype, I'm happy to take, go out on the limit, predict that we will

53:20 see flying taxis in the 20s. And we know we will because they're already being built. The question will be what cost, where will they start first? But the first will come drones for freight. This

53:32 is a big deal It won't mean that everybody will be doing just that. But in the 20s, it will start to make a difference. The kind of other kind of machines that are big deal, my favorite machines

53:43 are robots. I mean, we've imagined robots for a very, very long time. But by robot, I mean anthropomorphic machines, like blocking dogs and people. And the stuff I robot kind of robots. Turns

53:54 out that's really hard to do too. You don't have to be a forecaster to use the Google machine to see plenty of videos of pretty cool anthropomorphic robots these days The big question is not whether

54:08 people would want one. I think a lot of businesses would use one. A lot of people would own one, frankly. I mean it, sounds sort of spooky. It sounds science-fiction-y. But we all are getting

54:19 older. We all have older parents. If you could imagine the

54:25 anthropomorphic - let's use the spot mini from Boston Dynamics as a sort of architect, because it's commercially available, as it were.

54:34 follow your mom or dad around in the environment they live in. We have robots can't do that. So robots to be useful to us in sort of daily life have to be operate in our environment. They have to

54:46 be operate in our environment where we walk and go and not bump into us and not hurt us. And then they can report to you or me that, you know, mom has fallen down or dad is asking, they could

54:56 carry the groceries or open the door. All these things that for let's just say, I don't know what the number is, 80 of the assisted living tasks could in principle be done by cost effective robot.

55:08 The really difficult medical ones, obviously somebody's incapacitated are different. But often a lot of what happens, a cost effective robot could do and be very helpful. How much would that cost?

55:21 And will it get cheaper? Well, they cost a lot right now. Will they get cheaper? Well, come on. I mean, this is kind of like saying it's 1890 some 1900 and a car in today's dollars costs.

55:35 hundred thousand dollars, how many people are going to buy one? Not many. I mean, Elon must sell 100 dollars cars, but there's a percentage, it's a few percent. But when the car became 10, 000

55:46 in today's dollars, 15, a lot of people bought them. Robots are in the same trajectory. It's a slower trajectory than Moore's law because we're in the world of atoms, not just bits, but that's

55:58 coming. It's not just the automation that we've looked at, which is the in automobiles where you have the same thing being manufactured by automated machines, quote robots, that can do the same

56:10 task over and over again. We're talking about multi-dimensional tasking, which is very difficult. It's computing is very difficult. So I offload the computing task out of the robot's brain into

56:21 the network, into the cloud, into the local cloud. Don't make the robot have to carry around a supercomputer. That's silly. The robot can borrow a supercomputer when it has a task. It has to

56:30 figure out. Obviously that task, you can't have the robot stop. take five minutes to figure out open the door for grammar, and then open the door, right? So that it has to do that analytic task

56:42 quickly. If that requires offloading to a supercomputer in the cloud, that's a speed question on the networks, which we now know we have. That's what 5G is, by the way, even though it's been

56:52 hype. That's what 5G allows, 'cause I can connect in real time into the cloud, the super computing nearby. Anyway, you can imagine, I'm picking sort of simplistic mildly goofy scenarios, but

57:05 they illustrate the fact that that's a class machine. That's what's coming. What other kinds of machines? Well, the machines that build machines,

57:14 the kinds of things, when I worked in a factory, in any factory, you measure how, what kind of product you can make, and what price enough fast by how capable the machines are to do the making.

57:25 Those are the machines we don't see in day to day life. It's 3D printers, or, but we have two classes of machines are really different today, one are 3D printers, the other are called

57:35 nanofabricators. Machines that can create parts at literally the atomic level. The precision is no longer do I measure it to the thousands of an inch, which used to be a really big deal. You make

57:47 engines by making sure all your tolerances are the same. The parts won't fit together if they aren't made to the same tolerance of thousands of an inch or so far, thinner than a human hair. That

57:59 was a big deal to do that. That's what happened in the 20th century Now we're making machines, literally, that manufacture things at atomic layers. This is revolutionary. We can make all kinds of

58:12 novel things that way. And 3D printing to where you started, easy to explain about a 3D printer. The printer that we all use for our computer. That was the nicest I've ever become been called a

58:25 dummy before, by the way But

58:29 where you started, Chuck, it's very simple to explain No, you know, it's really privacy. Sound, you're right, that weird. But the way a printer works is it layers ink on a piece of paper and

58:40 it layers it in actually three dimensions, left, right. But if there's no vertical dimension, that's the ink you're depositing on the paper. But you don't deposit very much. You deposit

58:52 infinitesimal layers measured in thousands and millions of an inch. But you'll build

59:01 a vertical layer. So you built a 3D thing that way just scanning and depositing. Obviously what a 3D printer does is just keeps scanning higher up instead of just stopping at the linear thing, just

59:11 keep layering up. And you do that with other materials instead of ink, with metals, you do it plastics. So then you go from a drawing to a product printed. People were very excited about it when

59:23 they were first invented. And then it's typical with new stuff. They got other other skis predicting star trek-like manufacturing of every product in your house in 10 years You'd have a 3D printer

59:33 on your - desk and you don't buy a toothbrush, you just hit print. I need a toothbrush. OK, you can print toothbrushes. They're actually pretty easy to print because they're plastic. They're

59:42 simple. But it's actually easier to ejection mold a toothbrush. So it's kind of the equivalent of - I don't know - the discovery of plastic, if you had said, oh, we're never going to use stone

59:54 and brick again because plastic is better. And for a lot of things, plastic is far better than brick or stone. Last I checked, most buildings are built out of brick and stone,

1:00:07 and they're all plastic. Because it's better. Yeah, so OK, so it's interesting. And I do think nature repeats itself. And so we've got three buckets. They're converging. And I can definitely

1:00:19 see where we're leading kind of to our roaring 20s, you know, NBA basketball teams now have to have big - or ease if they want to win the championship. The Cowboys had the big three of Emmett Smith,

1:00:32 Michael Urban and Troy back in the

1:00:35 day. The one thing that's interesting in the epilogue of the book, I believe you actually overlaid government on top of this and definitely made a case of the United States ain't dead yet. And so

1:00:49 I'd love to hear, I'd love to hear you talk about that 'cause I found that fascinating and actually reassuring, believe it or not, but I do have a big question to end on after you lay that out -

1:01:01 Sure, I mean, I also begin with, but I end most strongly with the obvious admonition

1:01:09 that governance of politics matter. This is not a book about politics and government, but politics and government matter. We can't, it is possible to Sovietize an economy. It's possible to

1:01:20 destroy economies. Governments can do that, they've done it And so the 1920s to the year 2000. Americans did much better in every measure than the Russians did. I mean, it's not disputable. I

1:01:34 love Russia and Russians people. I just, I mean, that ones I known and that they're no different than Americans or Russians, right? Well, what happened? Well, they had access to all the same

1:01:44 inventions that America had. What happened? Obviously what happened there, they got the politics wrong. I mean, Putin might disagree with that, but most of us would agree they got their politics

1:01:53 wrong. So getting politics right matters So I pick in the hypertrophy extreme because governments do go to extremes. It can happen. So I'm not, and I'm not a Pollyanna that we can't have bad

1:02:05 governance. Things can't go wrong. I don't believe when we're going through trials like we're going through now. I think we're going through a trial and I don't mean this about our current

1:02:13 president or the past president. I just mean, it's a tumultuous time like it was in the 1920s. But we get through these things. I think I'm very optimistic out of America. I immigrated to America

1:02:22 as a Canadian because it's a great country I think we will resolve it. I think our system and our cultures make these things get resolved and I'm optimistic it will. Not without hard work,

1:02:35 everybody's part. So I didn't want to ignore that. But the bigger question up towards the state of America in the world is to claim that China is the

1:02:46 ascendant power. It's certainly ascended a lot. And that America is the receding power in the world stage. I think all of the factors where the epicenter of technologies lie, the epicenter of

1:02:57 invention lies, the epicenter of research lies, and the economic fluidity and adaptability reside, which is extremely important when the world's changing, where the political freedoms lie on net

1:03:12 and where demographic trends are profoundly in our favor. It's very bullish for America. China's going to grow. This is not, say China's not going to grow. Maybe the most important single fact,

1:03:26 as you know, I put in the epilogue. is if you look at the percentage of the population that is in the working age, that is between 20 and 55, the United States will have a higher percentage of the

1:03:38 working age a decade from now than that will China. And their population is shrinking, already started shrinking and ours are still growing. But if you think about immigration, I'm not gonna go

1:03:47 that rabbit hole, but America's always grown with immigration legal and otherwise. We've gone through these kinds of fights about immigration before, and as immigrant, I'm very aware, I was a

1:03:59 documented alien, but it doesn't matter. I'm an immigrant, right? So I make the case immigration's good. I think it's be managed, and most people would agree with that. But I think it's a good

1:04:10 thing. That plus our birth rates, which are down, are still higher than the other Western nations. We are on track, America is on track to have a population greater than China's before the

1:04:24 centuries out. So this is pretty interesting. sort of the same, call it the same size of population, 'cause they're shrinking. That can't be reversed for centuries. And we're gonna have a

1:04:37 younger working force, even though we're aging, we're gonna be younger 'cause they did that goofy one child policy, we would say, relaxed. That combination and their system just don't bode well

1:04:47 for them being the ascended power. They'll be powerful, but all the macros are on the American side And so I'm very bullish about the United States for the next century. And therefore for the

1:05:00 rising Gen Z, they live up the most exciting time in the country since, well, I'll say it, the roaring twice -

1:05:10 And I'm glad to hear all this, 'cause I'll go put down the money line bed on the United States and not even ask for points to take the United States over China. The one thing I do worry about, and

1:05:25 very fair comment back. to say to me is Chuck, take off your tinfoil hat or Chuck, get rid of your conspiracy theories. But the one big thing I had reading your book is we had the right system in

1:05:39 the United States, the rugged individual free market type system. And I think every innovation along the way,

1:05:49 if you looked at it, in some way, shape or form gave the individual more power vis-a-vis the government. I mean, you get a car all of a sudden, if I want to go from Houston to Michigan, I can do

1:06:01 it and the government can't tell me no, sure, the police can pull me over. But you definitely picked up more power, the individual versus the government. And what I worry about with the cloud is

1:06:13 when we think about the cloud, I mean, it's really three companies, right? It's Google, it's Amazon, it's Microsoft, and here's the tinfoil hat part. They work with our government There's no

1:06:24 question they do. Have we actually given our government finally the tools to read everything we text, read every bit of information we store, all of our communications? Have we given the

1:06:38 government a tool whereby they're going to have power over us and does that change the playing field? Ie. we don't have the roaring 20s because we've moved more towards the Chinese or the Russian

1:06:53 system vis-a-vis than what we lived in. That's a fair question. It's really a book under itself because just as I said when we started, one could and I may write a book about how we get innovation.

1:07:08 Others have written books like that. Matt really just has a new book out on that. A lot of fun. Good book. How do you get innovation? The other is what do we do

1:07:21 with governance with respect? to the inevitable migration to big corporations with a lot of power, market power and government power, to the government's inevitable instinct to cooperate and vice

1:07:33 versa with the big players, they will say for the public good, that's what they always say, and sometimes it's true, often it's true, I'll give, let's just say I'll give the often it's true,

1:07:44 but it's not always true. So

1:07:48 let me put this in the two separate buckets One is, is this time different in terms of the technology, and is this time different in terms of what the government can and can't do? So that's why I

1:08:02 said politics matters. I mean, whatever the technology enables, the capacity for governments to intrude in our life, to dictate things as opposed to, but guardrails around things. We all know

1:08:16 why government exists. Government exists for a variety of reasons most people can agree on, then you get down to the tangential things. almost everybody understands why some regulations matter,

1:08:27 safety regulations matter, standards matter, railroads would never work if everybody had a different gauge, famous example back from the 19th century. So government has a role. And getting the

1:08:41 politics right is always about where we lie in the spectrum from, we'll call it, anarchy and no government to stateism and dictatorial government And people don't have to be fascists and socialists

1:08:56 and statists to find themselves drifting unintentionally towards status controls because they're often saying the things that they wanna have happened are good.

1:09:08 And they may be, and again, I'll just be, you know, unsinical, they probably believe in me in that. There are those who don't, but let's just say they do. But they don't know the consequences.

1:09:19 That's why I get in the politics rights matter. And it doesn't really matter what the technology is. It doesn't matter what's the car, an airplane, or a computer, the cloud, or pharmaceutical,

1:09:29 getting the government governance right matters in terms of whether companies become, dog chemical became big. GM became huge. Remember that famous infamous line of what's good for GM is good for

1:09:40 America? Which by the way, is not what he said. If you use the magic Google machine, you'll find out he actually said the inverse. Literally said the inverse of testimony before Congress It was

1:09:52 deliberately maliciously turned into coin a phrase, fake news, buy newspaper at the day, which happened to be a paper still around. And he just decided not to fight it anymore. Just said, you

1:10:05 know what, whatever. But for his whole life Smith fought that. But the point of that is that IBM had 70 market share in computers in 1978.

1:10:17 Pretty powerful, right?

1:10:19 So I don't think for a moment that it's guaranteed that any of the giants, the fangs exist 50 years from now. I would bet a bunch of them will, just like IBM actually exists more than a century

1:10:31 later after starting making calculating machines. But Wang doesn't exist, Dak doesn't exist, Burroughs doesn't exist, Univak doesn't exist. I mean, we can go to a list of automobile companies

1:10:41 where 300 automobile companies in

1:10:45 1910, there were 30 by 1930, and there's what, half a dozen now So, and they're different ones. Tassle didn't exist before. So I think there's a lot of churn in that inevitably, but to your

1:10:59 point, it does matter to get this right. So what's different this time is not the idea. It's what, you know, this time is different. What's not different is we don't want heavy-handed intrusion

1:11:13 over things that we consider important essential to our lives. Going from state to state without being told have to stop at every state. I have a border crossing. I have so many measure how far I

1:11:21 drove, monitor my car. And there are people who still want to do that. Control, not just are you competent to drive a car, but whether or not there are other things about your life and background

1:11:32 allow you to drive a car. We didn't do any of those things with cars. We don't want that kind of thing to happen with the cloud and information.

1:11:39 That's what's going on in Iran and China with regard to the cloud and North Korea. That's how they use

1:11:46 it. We don't want to be the direction It doesn't mean they can't have a cloud and use it for some purposes. I don't think that there's anything unique about the potential danger of what could use

1:11:59 the the the invective of our overlords, getting overreaching and getting their hands into our pockets or our lives. I don't think that's a 10-fold hat danger. It's a real danger. And what's

1:12:12 different about it is how they're going to do it this time. We have a different tool. Is it a more powerful tool? Yeah What was the countervailing tool? You know, we'll get Apple credit for this.

1:12:21 The way they've designed their OS and Blackberry, my old Canadian buddies, most secure form of email you could use at the moment, I believe is still Blackberry. It's possible to build systems to

1:12:32 make them secure in which you, the consumer, me, the person have control over it. There's a lot of market for that. I think businesses that create those things will get a lot of consumers who

1:12:44 most of which want those kind of protections That's not perfect, government can still

1:12:51 classify certain kinds of devices as illegal. So you can't have that, or we have to have a backdoor. Those are the political fights. But I know it sounds simplistic to say, I think yes, it's

1:13:01 different. It's a different technology toolkit this time. And yes, it's more powerful because it's a case I make, which is why I would say it's even more important to get the politics right

1:13:10 because the power, it's kind of like it matters more that we not have a war with nuclear bombs and not because they're actually more powerful. This is true.

1:13:20 Will we have wars again? Yeah, fortunately as I write on my book, people, technology can't fix stupid. I just can't. Just can't. But can I

1:13:31 protect people better with the technologies we have, both from cyber sense and physical sense? Yeah.

1:13:39 The kind of instincts to control information that are, which is a lot of what we're talking about, 'cause of the elections and because of debates are going on about everything during the lockdowns.

1:13:50 That's an important debate to be having. We've had this debate before, but we haven't had it for a long time. What are people allowed to say, and how are they allowed to say it? That's a really,

1:14:01 really important debate. It's an debate we had at the dot of newspapers and yellow journalism, and we had that debate with radio and TV, and when the book was invented. But we don't have those

1:14:12 debates very often, 'cause there aren't very many, we use the expression step changes in that field. We've just We've just gone through a step change. We're having the debate again. I'm fighting

1:14:23 on the side of freedom personally, and I'm betting that the freedom fighters will go. Not, we'll let you take your 10-file hat off, but I think you should keep it on for a while just to be sure -

1:14:35 Wait, exactly - We went to fight - Well, Mark, this is your second time on the Chuck Yates needs a job podcast and usually sequels suck, but I wanna say this has been really fascinating. I really

1:14:50 appreciate you coming on and everybody, the cloud revolution, how the convergence of new technologies will unleash the next economic boom and a roaring 20s. You should get the book. It really is a

1:15:05 fascinating read. I enjoyed it, Mark - Thanks, Chuck. That's great if you have the autumn. I'm honored to get the second bite at the apple, thanks

1:15:14 You should aspire to more. Thank you.

1:15:19 Hey, thanks for doing that - Thank you -

1:15:23 That was cool - I appreciate it - Good question - Yeah, absolutely. The, yeah, no, I really did read the book and I really was taking notes kind of along the way and I tried not to ask the

1:15:36 questions where every answer from you would have been, well, no shit Sherlock. I mean, no idea about a lot of that stuff going on. I mean, it makes a lot of sense when you read it - Yeah,

1:15:49 that's sort of why I did it, the synthesize. 'Cause the whole point of the, as you saw, there are a lot of citations. The point of the citations was to visually drive home the idea that this is

1:16:00 not me

1:16:03 just making stuff up. I'm just harvesting the information that's it rent front of our eyes and synthesizing it - And oh, by the way, I'm doing what the cloud's doing for us and that's why it's

1:16:14 gonna be so cool - Yeah, it's kind of fun Let me know when you're ready. I mean, there's nothing that we did that I would, other than you got the technical side, that I'm worried about putting

1:16:25 out there. So when you're ready, let me know when it's gonna go - Is there a better time for you, as opposed to others? 'Cause I mean, I drop every Wednesday, so theoretically I could do it next

1:16:41 Wednesday if you wanted, or I could wait a week if that helped you -

1:16:46 No, when is this good? I think the book's out Wednesday. So it would be kind of fun if you're, you basically you can release the podcast on the release day, it'd be great - Perfect, yeah. No,

1:16:59 I'll have Jacob edit it. I know a couple of times my screen froze - Yep, I saw that - But that kind of happens and I don't think it, 'cause it records on the local computer So I've had that happen

1:17:17 before, but it doesn't show up in the - and Jacob's really good, so he'll run through it. And if there are any things like that, he'll edit them out - Yeah, I noticed it. You froze up, but I

1:17:29 assume then you're around the, what I was seeing in a video and it's all like, kids audio freeze would not, it's just an artifact of the transmission on my end - Yeah, no, I think that's what's

1:17:43 kind of proved out using Zencaster. So December 9th, do I see you in Denver - Yeah, I'm doing that one 'cause that doesn't conflict. They'll definitely be there - That sounds great. Let's make

1:17:56 Ryan and Jeremy buy us strings - Yeah, I think that's a good plan. We'll find a good Denver bar. Maybe do some Denver distilled quality licorice and the way we go - Sounds great. Thanks again,

1:18:15 Mark. Have a good weekend.