Andrew Lunde: The Technology Boom - Atlanta BitPlebs (EVNT006)

Dive into an insightful event recording discussing the technological paradigm shifts as presented in Jeff Booth's 'Price of Tomorrow,' focusing on chapters three and four. From the evolution of computational power, exemplified by Moore's Law, to the implications of self-driving cars and 3D printing, Andrew Lunde covers how new technologies can disrupt existing industries. Learn about the challenges of thinking differently, historical examples of significant cognitive shifts, and the potential future technologies that might surpass even quantum computing. This discussion also explores how technology can create an abundance that challenges traditional economic models based on continuous credit expansion.

Chapters

• 00:00 Introduction to Future Technologies
• 00:40 Event Recording and Podcast Information
• 01:11 Sponsor Spotlight: ATL BitLab
• 02:13 Book Discussion: 'The Price of Tomorrow'
• 03:56 Challenges of Thinking Differently
• 08:30 Understanding Psychological Biases
• 13:55 Innovator's Dilemma and Corporate Challenges
• 19:40 Exponential Thinking and Technology Boom
• 24:32 Exploring the Known and Unknown Universes
• 24:48 Understanding Moore's Law and Its Implications
• 28:20 The Future of AI and Technological Adoption
• 31:02 Self-Driving Cars: Revolutionizing Transportation
• 37:15 Virtual and Augmented Reality: A New Frontier
• 39:26 Additive Manufacturing and 3D Printing
• 41:54 The Coming Sonic Boom and Economic Implications
• 45:22 Q&A and Final Thoughts

Links

• Andrew Lunde
• The Price of Tomorrow by Jeff Booth
• Jeff Booth's Website
• Jeff Booth on Nostr
• The Structure o Scientific Revolutions by Thomas S. Kuhn

Transcript

Andrew Lunde: [00:00:00] There's a lot of implications of how this technology can change. What's the next technology beyond quantum computing?

Well, if we could really control the transfer between matter and energy. Then effectively we can transport matter or create matter from other matter.

It's like, oh, gimme a martini. Martini. There's a, you know, ice cream sundae. If we had that technology, what would that change? I mean, no grocery store, no cow. There's a lot, lot to think about.

Stephen DeLorme: This podcast episode is an event recording. If you're listening to the audio version, you might be missing some context from the speaker's visuals. You can find the video version at atlbitlab. com. That's A T L B I T L A B dot com. There might also be audience questions or other background chatter that's not [00:01:00] audible.

Look, event recordings are never perfect, but we're sharing it here because we think you're going to find something valuable in it. Let's talk a little bit about our sponsors first, and then we'll get onto the show.

This episode is sponsored by ATL BitLab. ATL BitLab is Atlanta's freedom tech hacker space. We have co working desks, conference rooms, event space, maker tools, and tons of coffee. There is a very active community here in the lab. Every Wednesday night is Bitcoin night here in Atlanta. We also have meetups for cybersecurity, artificial intelligence, decentralized identity, product design, and more.

We offer day passes and nomad passes for people who need to use the lab only occasionally, as well as memberships for people who plan to use the lab more regularly, such as myself. One of the best things about having a BitLab membership isn't the amenities, it's the people. Surrounding yourself with the community helps you learn faster and helps you build better.

Your creativity becomes amplified when you work in this space. That's what I think at least. [00:02:00] If you're interested in becoming a member or supporting the space, please visit us at atlbitlab. com. That's A T L B I T L A B dot com. All right, on to our show.

Andrew Lunde: So you probably seen me before round. Um, we're covering, uh, Jeff Booth price of tomorrow, chapters three and four. The, the book is quite short. I don't know. I was gonna guess what, about 150? No, 200, 213 or so pages. Um, you can get on audio, it's like running times about five and a half hours. I like had it had listened to it about two years ago and put it on when I was doing some yard work the other day, just to kind of refresh myself and I was like, oh, it's over.

So it's not that big a deal. So let's get into it. And so who am I, Andrew, if anyone hasn't met me before, uh, been around, uh, doing [00:03:00] development in various, um, incarnations from mobile all the way up to enterprise stuff you wanna know about all that, just tap on me lately or later. And, uh, lately I've been doing more bitcoin Lightning trying to get into the community, trying to.

Flex a little bit in the, uh, in that realm and try to contribute a bit. Um, sound money got me closer to this sort of realm, so my roots go in that direction a little bit. And, uh, decentralized stuff, money media naming. And id, if you're interested in naming an id, decentralized stuff, you can find me later as well.

So let's get into it. Alright, so as I mentioned, just uh, two chapters gonna be easy. They're pretty short chapters, so I added a little bit of fluff. I felt I, I could, so let's just go ahead and take a look. So in chapter three, he talks [00:04:00] about why is it so hard to think differently? And I think it's a really interesting topic, the fact that kind of begged I to let me do this part.

Uh, but, uh, he talks about, uh, how really hard it is to change your, your. Mode of thought and, and your model of what you're thinking about. And he mentions the, the, uh, the, of course example of Galileo. I mean, before that point everybody thought that all that stuff all up in the sky, the moon, the side, all the, even those funky things that didn't move like we thought they should, were just out there rotating around us and that we were the center of everything.

And Galileo really stepped up and said, Hey, um, I think we're one of the, one of the spinning things, and that caused a lot of consternation in his time. Right? And you can imagine, well, it would be hard to imagine what really thinking about the world prior to that really meant. But, uh, we know from history that uh, [00:05:00] he had a real hard time with the church about that.

And, uh, and. You know, that was, that was definitely a, a, a tough thing. Uh, witches mentions witches that at the, you know, turn of, uh, I guess around the 14th, 1400, 1500 timeframe, even in the, the new colonies, a lot of suspicion around what witches were in, in, in, and how you found them and stuff were, and discerned what was, what, uh, was very, um, controversial.

And, but yet most folks had a model of thinking about this. They trusted the authorities and history has shown that they really, uh, we're misguided in so many ways in that way. Uh, he also then mentions a good bit of that chapter is talking about the, the 19th Amendment and, you know, women's right to vote.

It's like we think about how normal, I mean, everybody should have an equal right to vote, but it's [00:06:00] really a recent thing. I mean, until the complete adoption of the 19th Amendment. Uh, women couldn't vote, didn't have the same say in government. Uh, you know, and, and even though they were really lobbying for it for quite a long time in the lead up to the 19th Amendment being ratified, it's, uh, it just, it just wasn't part of the makeup of who decided what was gonna go on in the government.

So those are pretty significant shifts. The next part, um, is about weak foundations and what does he mean by this? So he makes a case about how our brains work. Going back a little bit to physiology, I mean, I'm sure everybody's heard the story about, well, thinking about back to Neanderthal Man and what's, uh.

What do you do if you see that or hear some rustling in the bushes? It's like, do you like run away? Do you like [00:07:00] investigate? It's like, is that just the wind in the brush, in the, in the reeds, or is that a tiger back there? So as humans, we have to absorb so much information from our environment all the time.

I mean, just if you think about what you go through and experience, all the things you're smelling, all the things you're hearing, all the things you're seeing as you go through life, it's, it's a lot. So we've developed these mechanisms to filter out this information, this deluge of information, and those take the form of biases really.

So, you know, if you have an instinct to run away from that rustling sound in the bush, it's because. You know, you're part of the gene pool that survived and wasn't eaten by a tiger. Whereas the other folks that like decided, oh, I wonder what's going on in that bush over there and then got eaten by a tiger, they didn't live long enough to propagate their gene pool.

Right? So we have this natural filtering mechanism that our brains [00:08:00] go through. Oh, and one thing I didn't, I didn't do at the beginning. I wanted to offer an invitation. If anybody has a question as I'm talking, just throw your hand up and I, we'll stop and chat. I don't need to hold everything until the end of the, the talk, although I have a little q and a at the be.

And if you want to just jump in, please do. There's a microphone over there, over there by Chad, so if you want to jump in, just let me know. Alright. We got a few more folks trickling in, which is great. We just got started, so you haven't missed much. So anyway, um, as you mentioned, there's a lot of sort of filtering and bias judging, and a lot of this comes in the form of the, uh.

S basically these biases. Now, if you ever go on Wikipedia and look, look at all the psychological biases, you'd be amazed. There's like, like lists and lists of biases. Different biases, and you might think, ah, that's crazy. I'm sure are some of these just bullshit? But you read each one and you're like, oh [00:09:00] yeah, I can kind of see why that is.

And I just mentioned a few of them here. So anchoring like just like once something's established, you don't question it anymore, right? That's anchoring bias, recency bias, you know, it's always been like this. It's always gonna be like this. This is how the world works, this is how this works. First, there's a bull run, then there's a consolidation chop, and then there's a explosion with a bull.

You know? It's like, well, yeah, but that's recency bias, right? That's like pat, or looking at a pattern and saying, okay, this pattern repeat. Uh, confirmation bias is a, is a big one. It's just our natural ability to say, with new information that comes in that counters what we already believe. It's like, uh, you know, that's, that's some that doesn't really fit or something that reinforces what we already believe.

You're like, oh yeah, of course. That's exactly, see, that proves my point. But it's like, when [00:10:00] taken just independently, those pieces of information may have equal weighting, but you already have dismissed one and used the other one to bolster your case. Uh, another one, if you're in development or paying for anything sunk cost bias, right?

It's like, how often are we trapped by this one? It's like, oh man, I've already, I already paid for that license, so I guess I'll use that software. Or I already like, you know, um, bought the upgrade for my pickup truck, so I guess I'll get something el I don't, you know, once you've kind of expanded time and energy and resources.

You don't wanna change direction to where all the decision making that brought you there and got you to spend money on stuff. And time and energy gets discounted or thrown away. Nobody wants to throw away their, their energy. Um, he also talks about, as an example, kind of talking about why it's so hard to think differently about the, uh, this situation of Eastman [00:11:00] Kodak.

Most people probably don't know, but, uh, they were starting in 1888, so they've been around a long time and they shut their doors in 2012, which is not that long ago. And, you know, they really pioneered, they, they had the first camera, first commercial camera available in 1888 is what it looked like. And then this guy came along, he was, uh, I don't have his name handy, but um, he was the guy that invented the digital camera employee of Eastman Kodak.

So here it is that he's got his, um, his right hand on this blue thing and that whole stack of stuff is the digital camera. I think the one on his other hand is like another version of it when they started, you know, um, getting it, uh, brought down to size a little bit, but this was revolutionary. I mean, think of all the industry that was changing.

Does everybody remember those little, um, [00:12:00] stands that you'd drive up to and drop your rolls to film on those little photo like booths? Like there was like a person there and then you'd go back like a week later and then they'd like rummage through a bunch of envelopes and give you one and you'd like open it up and you'd say, oh, that that was a bad picture.

That's a bad picture. Uh, 20 good 20 bad pictures and two good pictures 'cause you, that was how long the feedback loop was. And just think about how taking a photo now, I mean, I take photos of. You know how wires are plugged in so that when I'm disassembling something, I'll remember how to put 'em back. You know?

So it's like, we don't even think about it. I'll take pictures of, you know, just inane things, just as a reference, just to like remember that I saw something, not that I even care about the picture, it's just like a little point in time for me. So this guy, they could have owned it. They could have had the traditional film, the film industry.

They could have had the whole future electronic film and, uh, [00:13:00] digital photograph photography industry. But they, uh, they blew, they blew it. They just didn't see that the digital was the way it was gonna go, and they didn't adapt. And, um, I grabbed, this is a picture of some recent Samsung phone, uh, on the back.

It's got like five camera lenses. It's like you've got this thing that's

that

thin. It's like, and you've got five different aperture in focal length camera lenses running on the back. It's like, just that alone is a pretty big significant, uh, you know, change in, in how we think about photography. And you can argue, yeah.

Oh, a film cra can give you so much better picture. And it does in a lot of ways, but the convenience and the immediacy is like far outweighs that in so many cases. Um, I threw this in here, this, uh, book by Clayton [00:14:00] Christensen. Uh, if you're familiar with it, the Innovator's Dilemma kind of fits in both chapters.

I threw it here and there's an honorable mention in the other chapter, but, uh, if you ever are interested, this, uh, author goes and talks about why it is that established corporations have such a hard time innovating. And to give you the short of it is the new innovations almost always cannibalize. The existing company's revenue streams in some form.

And once a new innovation starts appearing and looks like it's gonna challenge the status, uh, a quo that the company's built up and that revenue stream, then there's like antibodies that get released in the company and just kills it. So, uh, it's very difficult. This is why startups can run circles around established companies.

Uh, when it comes to innovating. It's a, it's a really interesting book. I recommend it, but that's not what we're talking about. Uh, two speed thinking. So, um, [00:15:00] I thought I had some more. Hang on a second. Uh, here we go. These are all the, uh, the subsections. I'm not clicking fast enough. Yeah. A second. All right.

I'm gonna get to back to these other topics here in a second. Another, um, when I was reading this chapter, it really, um, another book that I had read in college really, uh, popped into my mind and I brought it along. How's that, sir? Has anyone seen this book before?

(Audience 4): Excellent.

Andrew Lunde: Yes. Um, no one else. So it's by a guy named Thomas Kuhn.

I think it was published originally in 61, maybe 65, something like that. It's pretty early. Uh, let's see, 62, and I read this in, uh, college philosophy class and I really liked [00:16:00] it. Uh, I still have the sticker from the, uh, engineer's bookstore used at, uh, 5 95. And uh, this book really goes through the Galileo use case goes through a bunch of other similar.

Uh, use cases of how technology and specific scientific technology really is hard to change, why it's so hard to change, thinking about what's going on, whether it's in biology, and it goes through a bunch of different examples. But the short of this book is really before a new paradigm of thinking takes over.

The folks that embody the old one have to die. And it's kind of a, a brutal truth, but that's really, yes, there's always people that bridge between the old schools of thought and, and create new ground for the new school of thoughts and have to deal with a little bit of both sides of things. But for things really to take hold in a broader sense in society, the, the existing folks have to die.

And I [00:17:00] thought that was pretty harsh, but true. Um, when I bought this book, I was doing a little, I. Uh, calculator of inflation. So according to, um, CPI, this is a Bureau of Labor Statistics, uh, at 5 95. It's now around 1634. But if you go and, uh, look at the Shadow Stats Index, which is a guy who does these, uh, in, uh, 1980 methodology index of, of pricing, according to him and his data, this book would've would be worth 106 bucks right now, which I think is a little crazy.

But anyway, thought that would be kind of fun. If you go looking for this book today on, on Amazon, you won't see it with this cover. You'll see it with this other cover. They, they've updated it a little bit, but same book, all another fellow really restated the same thing. Uh, max Planck, uh, said you in 1950.

So 1950, the new scientific truth [00:18:00] does not triumph by convincing its opponents and making them see the light. But rather because its opponents eventually die and a new generation grows up that is familiar with it. So kinda restating the same premise. Um, the next section, uh, about the technology booms, uh, well, before I go on questions Go ahead.

(Audience 5): I was just gonna comment. Maybe we should consider, uh, outlawing life extension.

Andrew Lunde: Outlawing life extension.

(Audience 5): Yeah. Is that a problem now? It's a slow

Andrew Lunde: You mean like genic cryogenics? Is that what you're saying?

(Audience 5): No, I mean, people that are trying to extend their life to be 150 years old or whatever, we shouldn't do that if it's gonna stop progress for the people that come after it. Right?

Andrew Lunde: That's true. If, if you follow this premise, that would, uh, be counteracting principle.

Any anybody else?

So it's really, it's really trying to lay out this, this premise that, you [00:19:00] know, when you're thinking about things and there's a new paradigm of thought that's emerging. Just to understand just how horribly hard it is to really change at the, at a root level, how you think about things and expect that society will have lots and lots of resistance to that new thought.

So as Bitcoiners, we're, we're well aware of this, right? Because, uh, Bitcoin kind of gets around a, a whole model of thought around money and, uh, most people don't even know what the money they have is. And, uh, you know, so you gotta start by backing up and explaining a lot before you even get to the Bitcoin topic.

Uh, in chapter four, uh, called Technology Boom, he starts out with, uh, a bit of a few examples, uh, which we'll go over here in a little bit. So if, uh, he talks about a situation where his folks, uh, when he was young, uh, asked like, would you rather have a million dollars now? [00:20:00] Or would rather have a penny? And have it double every day for 31 days.

So who wants a million dollars? A million dollars. Oh, come on. I know you. Okay, we got it. One taker. How much, uh, is a penny when doubled? 31 days every time. The amount doubled.

Audience: Shitload

Andrew Lunde: A lot, right? Also, he talks about, uh, well I'll go through that. So, so a penny doubled 31 times gives you 10 million, $737,418 and 24 cents.

So as a kid you can imagine that, you know, oh yeah, I'll take a million dollars. Right? How much is a penny doubling? Oh, maybe 20, 30 bucks might be your, your first thought. So yeah, this is, um, this is where the numbers get really hard to fathom, right. Another [00:21:00] story it relates is, um, the guy, the, the guy that invented the game board chess, and he was, uh, I'm not sure if this was in China or back in some Arabia somewhere.

And, uh, the king that of the time was so impressed by the game of chess. He's like, chess was offering the, the inventor like, what do you, what do you want as a reward for, for making this beautiful game? He said, I'll, I'll take a grain of rice as my payment and the, uh, but every, for every square on the chess board, I want to double it.

And, uh, there's 64, uh, squares on the chess board. And a rice, a typical grain of rice is 0.029 grams per grain, which is, I believe that's quadrillion 18 quadrillion. Well, you can see the number. It, it ends up being 1.2 tons of, of rice. So the story, uh, as he was telling it [00:22:00] is that, uh, once the king kind of figured out that this was getting outta hand, he had the guy executed.

So, go ahead Jordan.

(Audience 6): I think it's 18

Andrew Lunde: Pentillion. Okay. Yeah, I had a Wow.

(Audience 6): Yeah.

Andrew Lunde: That's crazy.

Um, so, uh, the third example is a piece of sheet of paper.

Yeah. And folding it. How, uh, if you f if you could fold a sheet of paper 50 times is actually impossible given the physical constraints of paper. If you could fold it 50 times, how high, how thick would it be? And uh, yeah. So the answer as you see here, is 149, uh, million kilometers, which is about roughly the distance between the earth to the sun, which is pretty crazy to think.

I mean, there's not enough paper, right? So, um, the whole point of this is to illustrate that thinking exponentially for humans is, is very hard, right? I mean, we think [00:23:00] we're doing good. If we can think linearly, it's like, okay, number go up, right? Well, what's the, people will start say, well, okay, it's a Bitcoin's at a hundred thousand.

Maybe it'll be 140,000 by the end of the year or 150, or maybe 200. Okay. Well, last year it was this, so now it's this. So next year it should be, uh, you know, maybe I'll add 50% just to kind of be optimistic or something. But when you're talking about changes of thought, changes of, of technology, changes of, of systems, they don't necessarily grow in a linear fashion.

They often will grow exponentially. I mean, what's the time it takes to con to transmit a message between here and England? It's a fraction of a second, but before you had to write a letter. Put it in the envelope, put a stamp on it, give it to the post [00:24:00] guy. He had to go give it to the sorter. I mean, got some point, it got on a cruise ship, went across the ocean.

So, I mean, that's the kind of differences that we're talking about,

(Audience 6): Andrew.

Andrew Lunde: Yeah, sure.

(Audience 6): One of the fun examples of this is the SHA 2 56 algorithm, right? There's 256 bits, uh, worth of possibilities. Every time you hash something that's more possible hashes than there are atoms in the known universe,

Andrew Lunde: right?

And that's hard to think about. I guess you could say. Well, that's the known universe, and maybe what about all the unknown universes? But hey, still a lot. It's hard, it's hard to like think about. Right? Uh, the next section is. Subsection is called doubling up, and he's talking in this case, uh, primarily about Moore's Law.

So everybody familiar with Moore's Law? Pretty much? Yes. It's, this is [00:25:00] a, a graph I found, and if you look on the left side, it's, I think it's an exponential, uh, uh, legend or you'd say a logarithmic. And, uh, the year starting in 1970, all the way up to about 2020. And these are, uh, I know it's tiny, you can't read it.

I don't expect you to, but these are like literally all the processes, all the CPUs that have been invented and kind of where they fit on this graph. And even though that the, uh, it's a logarithmic on the left side, you can see that it forms pretty much a straight line. So this is really a doubling every year of compute power.

And it has pretty much followed that Moore's law, which is pretty astounding that it's still, still in effect today. And I've seen the same graph where a few of the, uh, quantum things or dots are starting to get placed up here. So it's pretty crazy. So, um, he also, um, talks about how that is a, um, is similar to this sigmoid [00:26:00] function curve of technology.

And I couldn't find this an electronic way, but I had to snap it out of the book here. But if you look at this, it's maybe a little hard to see, but on the left, the, the legend is performance going up and then cost coming down, and then time to the right on that axis. And this first ssha sort of curve is Moore's law.

So what we just looked at, like at um. On that last graph, which is a straight line, but since this left, um, axis is not, is a linear access, it becomes more of a a s shape. And then he puts this hypothetical, next one, next technology, kind of that would supplant it. And in this case he's saying, oh, this potentially is quantum.

So as Moore's technology, maybe he's petering out, quantum technology will be taking off, right? Mm-hmm. And then he's got a third one that he started here called the Third Technology. So anyone wanna hazard to guess at the what? The third, what's, what's the next technology that's gonna supplant, uh, [00:27:00] quantum technology?

Audience: Bitcoin.

Andrew Lunde: Not Bitcoin. Yes.

Audience: It gotta be something. Ai. Ai.

Andrew Lunde: No, no. Ai.

Audience: We use the quantum computers to simulate our own universes. And then the, uh, inhabitants of those universes. Create their own computers with the materials in those universes.

Andrew Lunde: 42, right? Everybody know something related with the our own, uh, body, right?

Like it might, it might, I mean,

Audience: you have an answer.

Andrew Lunde: I don't have an answer. No. It's an open question. Um, sure. We you know, the fact that we sitting here, while we're probably just barely grasping what quantum really means, an entanglement means, and the ability for these things to compute states at immense speeds means [00:28:00] barely understanding that, trying to put our brain into a mode where we are thinking about the next thing that, that supplants that is.

Really difficult from where we're sitting right now. Right? Um, but if history plays itself out, then there will be something that does take over. So when I saw that, it's reminded me of this, which is, um, the, uh, the Gartner Hype Curve. Uh, is anyone relation familiar with this one?

Audience: Looks kinda

like the Dunning Kruger curve.

Andrew Lunde: Yeah. So this is, uh, and I brought it out 'cause I, I think it's like important to kind of, in the same context of thinking about things, things, there's a lot of expectation, a lot of, there's all sorts of variants of this graph for various, uh, technologies. It could be like CD ROM technology, telephone technology.

Of course, the one everyone wants to look at right now is the [00:29:00] AI technology one. Um, and where are we? Where are we on this graph? If this is kind of how things go in terms of technological adoption? Um, I'm, I'm hearing more and more that we're over the peak of AI expectation. Would it, are, would people think that, or you think we're still on the up forward curve going up the, uh, rollercoaster with the ratcheting looking at the sky.

It's all blue sky ahead. It's gonna be great. AI is gonna do everything for us. General AI is coming around the corner. It's gonna keep going. Are we still kind of climbing the expectations or are we kind of, eh, maybe it's not as, does doesn't do everything that we want or, or not. Doug,

Audience: Give you my opinion.

I think on the general AI front, maybe we're potentially a little ahead of you. Fully general AI in terms of like chat bots and do, but I think we're [00:30:00] way underestimated the impact of real world AI think is coming. It's gonna be a much bigger deal. Right? Yeah. From there we're talking about, you know, robots and autonomous AI brains and how they're gonna change, not thinking enough about how that's going.

Andrew Lunde: Right. So for those that probably won't hear him on the recording, so Doug was saying that I think we're kind of maxing out where the chat, the chat ai sort of is getting us and that's, uh, what we'll eventually see is more, um, AI used in, in, in broader techno technologies. And this is where kind of the disillusionment happens.

Everybody's like, ah, isn't everything we thought it was gonna be, but through all this discovery process, we get some really good, uh, examples that come out of it. And then the slope of enlightenment where you kind of keep crawling back up to like, okay, now we know what it could really do. Let's put it to work.

Let's make some money. Let's build some businesses that are [00:31:00] hanging onto it. So, so he talks a little, there's quite a bit of, uh, discussion about self-driving cars, and I'm not gonna get into all the details, but he describes from level zero, which is you drive the car all the way up to level five, where it drives completely by itself.

And he talks about it in the context of, of, you know, what Tesla has done and how, you know, how it was pretty good. I mean, things could, the car could park itself initially pretty decently. And then it was driving around and on freeways pretty good and now it's pretty much handling all situations. He talks a little bit about like how the, now we see go, the companies built around it.

Uber and Lyft are big examples of this, but he asks, you know. Is that gonna, are they gonna continue to be able to make a, a good business model and margin out of it? Uh, when more and more cars and the cars that are typically owned be have more and more [00:32:00] capabilities, right? Are smarter and smarter. He also talks about, like, because we're in the habit of having everybody having a car, then the amount of parking that's necessary is pretty large.

Uh, in terms of actual utilization of the car, uh, really 5%. We could only need 5% of the parking that we actually have to build now, just because if there nobody had a car and everybody was running around on, in like, you know, uh, automatic cars, then that would free up a lot of resources. So it's another way of thinking of where this, the, um, you know, where the optimizations are.

Um, he even further talks about, uh, how Tesla and Waymo are actually, because they're self-driving. AI is so good. That. And really the whole thing about car insurance is about you're insuring the person making a mistake driving the car. So if the car's not making a mistake, then why should you have to insure it?

'cause it's not [00:33:00] gonna make a mistake. So how does that affect the insurance industry? And he even theorized that, well really they should just self-insure. Like we as a company ensure that our products aren't gonna run anybody over. So there's no fault, there's no potential damage. The point of it is, is to, while you think about the car and it's cool and the technology, the fact that it can see the road and objects and react and drive properly is really cool technology.

What about these secondary effects? What about these secondary industries and how are they gonna change around the primary technology change? And then I threw this last one up in there. 'cause I thought years ago it's like. Wouldn't it be nice to go on a vacation like out west or someplace and have your own car?

You don't have to rent a car, you don't have to, you got a plane ticket, you don't have to like deal with baggage claim, you know, I just wanna like pack my car, jump in it, [00:34:00] put the seat back and like, say, wake me up when we get there. Or I'll wake up, we have to, you know, take a little biological break or something and just like, alright, time to get off the freeway.

But how many people would like trust the car so that you could like completely fall asleep in it and know that it's not gonna like, run under a semi or something or come skidding off the road if it starts snowing or something like that. I mean, do we trust the self-driving stuff that much yet? Probably, probably not quite yet.

So, but I mean, if you see the improvements, what's to think? We can't get there. I don't know. So,

Uh, another thing I always dreamed of is like, why is it that my car is limited to like 80 miles an hour? It's like if I'm driving to California, I don't want to take four days. I wanna take one day. Why can't it drive 200 miles an hour? So it's like. If, and, and you [00:35:00] know, that's a lot of air drag, but okay, if these cars are so smart, then why can't you like do an ad hoc sort of train of cars such that they're all like drafting on each other and like, you know, and, and so you, they all know how to flock swarm and figure out how to come in together.

And like when they're on a stretch of highway where you got 10 cars all like bumper to bumper flying down the freeway and you're optimizing the air resistance, then you can get even more efficiency and get there faster. And why not? Right?

(Audience 4): Are we just, um, Andrew, I wanted to ask about, uh, Moore's Law.

Andrew Lunde: Yeah.

(Audience 4): So aren't we, I heard a couple years ago that we were approaching like the upper threshold.

So with regards to like. Uh, CPU chip size manufacturing.

Andrew Lunde: Yeah. I think, um, most chips, the, the higher end chips are running at four nanometer, uh, d size. And that there's, they say when they start [00:36:00] getting three and sub three that they start running into, you know, different physics, electromagnetism, interference.

Like, we're starting to like, deal with the properties of the matter itself. Right. I dunno, you, uh, Stephen's got maybe a thought here. I

Audience: Mean, yeah, I think we've been hitting that for a long time now. Just in terms of like, we're getting down to the point where you just, it's not even physically, it's, it's becoming physically harder to fit as much onto the chip.

Right. We're, we're brushing up against the walls of physics. However, there's also other advances, um, in processor technology that's not just how many transistors. There's like stuff like hyperthreading, uh, multithreading and stuff like that, like being able to run. Um. More, uh, CPU threads in parallel and like adding more cores and things like that.

These kinds of optimizations, while they're not the same as doubling the number of transistors on the chip, they have the same net effect expected outcome of picking the chip better, faster, more [00:37:00] efficient. So even if Moore's Law does break apart in terms of we're not literally putting more transistors on the chip, I think it sometimes seems as though the intended outcome still holds and that the CPUs keep getting better and better.

They're just getting better through other means.

Andrew Lunde: All right, moving on. Um, so gets into a section on virtual and augmented reality and, um, I didn't really, I mean, he gets into like how he, uh, was able to do, and you gotta remember this book is what's about 10 years old, I think was the first published, let's see, checking, checking 2020.

Working. Working 2020. Okay. So five years, which in technology terms is a lot. Right? But he was talking about, uh, being able to go to one of these labs where he got to, uh, I think it was Apple Lab, where he could, uh, use of virtual re uh, reality technology and. And I, and, uh, now maybe it was Tesla [00:38:00] and he got to do a simulation of traveling to Mars and like running around on Mars and interacting with things.

And, um, he uh, said, you know, that alone is another mental leap. It's like when we don't have to physically travel to another place in order to perform something, whether it's a surgery or a mechanical operation, 'cause we can just, you know, operate a robot that's remote or something. Again, it's another leap of technology.

It's a way of thinking. It's, you know, hard to conceive what exactly that means in so many ways for us. Um, he also kind of posits into section. It's like, well, if we can so easily kind of recreate a reality for ourselves, are we in a reality ourselves already? I mean, so he gets, he, he po he posits it. I mean, this goes back this.

Premise has been around for ancients since there's a philosopher that said, if you could, [00:39:00] if you could convince yourself there's some, like demonic being that's like intercepting all your senses, then you can prove guy. I can't remember which philosopher that was. Kant, is that okay? Kant? Yeah. So in a way, the whole idea of a simulation and like the Plato's cave analogy kind of hints at that, right?

Audience: Sorry, Descarte.

Andrew Lunde: Descarte, sorry. Okay. So, uh, I just had one philosophy course in college, so I didn't, anyway, um, that's kind of fun and interesting. He mentions that. Um, and then, uh, there's a section on additive manufacturing and 3D printing and, um, it really does kind of bogle the mind to think about. It's like, well, we only do, if we only need something and can create it as needed, then that changes the whole supply chain inventory, like moving stuff around how you design stuff.

I mean. The materials for doing 3D printing are getting better and better. I've seen like steel composites, I've seen 3D printing with glass. I've [00:40:00] seen 3D printing with concrete whole buildings and houses, 3D printed. I mean, it's pretty amazing what's possible these days. Um, and like the cost savings and like transportation logistics of all that material and how, how much fabrication needs to be done and for just to get the material into a place like making bricks or paint or whatever.

It's like there's a lot of implications of how this technology can, you know, imp uh, change. I mean, what is Amazon? I mean, if you can make things. Um, and then I kind of extended this myself a little bit with the whole concept. And this really, if we go back to the, what's the next technology beyond quantum computing.

Well, if we could really control the transfer between matter and energy. Then effectively we can transport matter or create matter from other matter or energy. And this [00:41:00] really is what Star Trek was talking about in terms of the technology that they had. So in a way, we can, by virtue of like watching Old Star Trek, we can kind of see how things did.

Now they use a shuttle once in a while, but how much of the time they just beam down, like they beam down to the planet, they beam back up, they beam to the middle, the under the surface of the planet sometimes, and then they beam stuff that's there back up. And whenever they are in the cantina on the ship, they're like rolling up to the, uh, the little doorway right in the side of the wall.

It's like, oh, gimme a martini. Martini. There's a, you know, ice cream sundae. It's like, if we had that technology, what would that change? How would our, I mean, no grocery store, no cow. I mean, I don't know. There's a lot, lot to think about. And then, uh, the last section is the coming sonic boom. And where he is [00:42:00] going here with this is comparing the, the cycle.

And he really kind of brings it back to this whole concept of abundance. And currently today he lays out the case that, that we are in a continuous credit expansion system where more money is created and is to drive more production and more output, more GDP more money. And it's the whole Keynesian thing.

This is where we are kind of cranking and cranking and is it ever going to end? Is there a natural limit to where this goes? Uh, and the reason this works, he posits is because even though technology is driving the price and the cost of things down. Down and down and down. We have this countervailing force of money creation that's inflating things up and up and up.

So as long as there's more money production and credit expansion, it'll seem like [00:43:00] prices are always going up, even though they should be going down. And effectively we're, we're just kicking the can down the road. Now, a lot, I've been hearing a lot more, and I threw this other part of it in, is, you know, stable coins.

I'm not lightning yet. One more way to kick the can down the road a little more and maybe we'd have a, a few thoughts on that, but I can definitely see that. I mean, currently I think, uh, tether is the fourth largest consumer of US treasuries or purchaser of US treasuries. So if there's no purchaser of US treasuries at, if they went away and stopped purchasing, what would that do to the dollar?

It's something to think about, right? And, uh, and, and that for that matter, any other national state, you know, sovereign currency could be affected by effectively, where the, the traditional monetary rails have a certain cost and latency and lag effect. By putting everything on lightning, you're gonna [00:44:00] minimize that to, uh, very small costs and very instant payments and very, and potentially sub cent payments, right?

So new. It's definitely, um, a new kind of level of thinking about the implications here. So he, again, he brings it back to the analogy of a sonic boom with an airplane reaching the sound barrier and pushing through it. And when that happens, suddenly you see the airplane and then the boom hits. It's like, it's not how nature is supposed to react.

You're used to having it react where you hear something before it comes to you and. Where he is going with this is that this really is changing the rules. It's a paradigm shift. It's a big cognitive shift. It's very difficult. And this is where we're we're, um, where we're headed. And, uh, just to round this out, um, a quote here at the very end of the chapter, A simple power of technology is that it allows for an abundance without the same amount of [00:45:00] jobs and income.

Basically, the abundance should continue and benefit us and, uh, force prices down such that we don't have to spend as much time and working and we don't have to have as much income because of the abundance that technology should be affording it if it wasn't for this pesky monetary inflation thing. So with that, I believe that's it.

Any q and a? Anyone? Anyone? Bueller? Anyone?

Alright? Yes, we should have coordinated a, a certain, a teaser, um, for next time. So that's all I got. Um, again, this is me, Andrew, da da da. This is how you get ahold of me. I got, if you need, uh, references. I got a few things here. Um, I took this picture the other day. Anyone know where This is

Audience: Costco,

Andrew Lunde: right?

Yeah. So why, why do they put the TVs at the beginning when you first walk into Costco? '

Audience: [00:46:00] Cause they're not $20,000 anymore.

Andrew Lunde: That's right. So when you look at an 86 inch ultra high density AI, thin Q TV for 8 99, 99, you might not buy it, but you walk by and you go, man, that is brilliant picture. That's like a pretty decent cost.

I remember when I spent seven grand on a plasma not too very long ago, and it's on the curb, and then you go and pick up a bag of peanuts. It's like 18 bucks. Ah, it's not so bad. Throw it in the cart, you know, side of salmon. Oh, well, it's 19. All right. Throw that in there. It's like you really don't check prices that accurately kind of, once you've been conditioned from walking through the door.

I don't know. It's a little conspiracy theory. So

Audience: They're giving you the, the deflation of the electronics, right, so that you don't notice the inflation of the, of everything else.

[00:47:00] (Applause)

Stephen DeLorme: Hey, thanks for listening. I hope you enjoyed this episode. If you want to learn more about anything that we discussed, you can look for links in the show notes that should be in your podcast player, or you can go to atlbitlab. com slash podcast on a final note. If you found this information useful and you want to help support us, you can always send us a tip in Bitcoin.

Your support really helps us that we can keep bringing you content like this. All right. Catch you later.