March 13, 2025 • 47 mins
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.
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
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Andrew Lunde (00:00):
There's a lot of implications of how
(00:02):
this technology can change.
What's the next technologybeyond quantum computing?
Well, if we could really control thetransfer between matter and energy.
Then effectively we can transport matteror create matter from other matter.
It's like, oh, gimme a martini.
(00:22):
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 (00:40):
This podcast episode is an event recording.
If you're listening to the audioversion, you might be missing some
context from the speaker's visuals.
You can find the videoversion at atlbitlab.
com.
That's A T L B I T L A B dot com.
There might also be audiencequestions or other background
chatter that's not audible.
Look, event recordings are neverperfect, but we're sharing it here
(01:03):
because we think you're going tofind something valuable in it.
Let's talk a little bit about our sponsorsfirst, and then we'll get onto the show.
This episode is sponsored by ATL BitLab.
ATL BitLab is Atlanta'sfreedom tech hacker space.
We have co working desks,conference rooms, event space,
maker tools, and tons of coffee.
(01:25):
There is a very activecommunity here in the lab.
Every Wednesday night isBitcoin night here in Atlanta.
We also have meetups for cybersecurity,artificial intelligence, decentralized
identity, product design, and more.
We offer day passes and nomad passesfor people who need to use the lab only
occasionally, as well as membershipsfor people who plan to use the lab
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One of the best things abouthaving a BitLab membership isn't
the amenities, it's the people.
Surrounding yourself with thecommunity helps you learn faster
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Your creativity becomes amplifiedwhen you work in this space.
That's what I think at least.
If you're interested in becominga member or supporting the space,
please visit us at atlbitlab.
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(02:05):
That's A T L B I T L A B dot com.
All right, on to our show.
Andrew Lunde (02:13):
So you probably seen me before round.
Um, we're covering, uh, Jeff Booth priceof 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 likerunning times about five and a half hours.
(02:37):
I like had it had listened to itabout two years ago and put it on
when I was doing some yard work theother 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 anyonehasn't met me before, uh, been around,
(02:59):
uh, doing development in various, um,incarnations from mobile all the way up
to enterprise stuff you wanna know aboutall that, just tap on me lately or later.
And, uh, lately I've been doingmore bitcoin Lightning trying to
get into the community, trying to.
Flex a little bit in the, uh, in thatrealm and try to contribute a bit.
(03:19):
Um, sound money got me closer tothis sort of realm, so my roots
go in that direction a little bit.
And, uh, decentralizedstuff, money media naming.
And id, if you're interested innaming an id, decentralized stuff,
you can find me later as well.
So let's get into it.
(03:40):
Alright, so as I mentioned, justuh, 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'sjust go ahead and take a look.
So in chapter three, he talks aboutwhy is it so hard to think differently?
(04:02):
And I think it's a really interestingtopic, the fact that kind of
begged I to let me do this part.
Uh, but, uh, he talks about, uh, howreally hard it is to change your, your.
Mode of thought and, and your modelof what you're thinking about.
And he mentions the, the, uh,the, of course example of Galileo.
I mean, before that point everybodythought that all that stuff all up in
(04:28):
the sky, the moon, the side, all the,even those funky things that didn't
move like we thought they should, werejust 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 causeda lot of consternation in his time.
Right?
And you can imagine, well, it would behard to imagine what really thinking about
(04:54):
the world prior to that really meant.
But, uh, we know from historythat uh, he had a real hard
time with the church about that.
And, uh, and.
You know, that was, that wasdefinitely a, a, a tough thing.
Uh, witches mentions witches that atthe, you know, turn of, uh, I guess
(05:15):
around the 14th, 1400, 1500 timeframe,even in the, the new colonies, a lot
of suspicion around what witches werein, 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 amodel of thinking about this.
(05:36):
They trusted the authorities and historyhas shown that they really, uh, we're
misguided in so many ways in that way.
Uh, he also then mentions a goodbit 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, Imean, everybody should have an equal right
(05:58):
to vote, but it's really a recent thing.
I mean, until the completeadoption of the 19th Amendment.
Uh, women couldn't vote, didn'thave the same say in government.
Uh, you know, and, and even thoughthey were really lobbying for it for
quite a long time in the lead up tothe 19th Amendment being ratified,
it's, uh, it just, it just wasn'tpart of the makeup of who decided what
(06:23):
was gonna go on in the government.
So those are pretty significant shifts.
The next part, um, is about weakfoundations and what does he mean by this?
So he makes a case abouthow our brains work.
Going back a little bit to physiology,I mean, I'm sure everybody's heard the
(06:47):
story about, well, thinking about backto Neanderthal Man and what's, uh.
What do you do if you see that orhear some rustling in the bushes?
It's like, do you like run away?
Do you like investigate?
It's like, is that just the windin the brush, in the, in the reeds,
or is that a tiger back there?
So as humans, we have to absorbso much information from our
(07:11):
environment all the time.
I mean, just if you think about what yougo through and experience, all the things
you're smelling, all the things you'rehearing, all the things you're seeing as
you go through life, it's, it's a lot.
So we've developed these mechanismsto filter out this information, this
deluge of information, and thosetake the form of biases really.
(07:35):
So, you know, if you have an instinctto run away from that rustling
sound in the bush, it's because.
You know, you're part of the gene poolthat survived and wasn't eaten by a tiger.
Whereas the other folks that likedecided, oh, I wonder what's going on
in that bush over there and then goteaten by a tiger, they didn't live long
enough to propagate their gene pool.
Right?
So we have this natural filteringmechanism that our brains go through.
(08:00):
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'mtalking, just throw your hand
up and I, we'll stop and chat.
I don't need to hold everything untilthe end of the, the talk, although
I have a little q and a at the be.
And if you want to justjump in, please do.
There's a microphone over there,over there by Chad, so if you
(08:21):
want to jump in, just let me know.
Alright.
We got a few more folkstrickling in, which is great.
We just got started, soyou haven't missed much.
So anyway, um, as you mentioned,there's a lot of sort of filtering
and bias judging, and a lot ofthis comes in the form of the, uh.
S basically these biases.
(08:42):
Now, if you ever go on Wikipediaand look, look at all the
psychological biases, you'd be amazed.
There's like, like listsand lists of biases.
Different biases, and youmight think, ah, that's crazy.
I'm sure are some of these just bullshit?
But you read each one and you're like,oh yeah, I can kind of see why that is.
(09:03):
And I just mentioned a few of them here.
So anchoring like just like oncesomething'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, thenthere's a consolidation chop, and
(09:25):
then there's a explosion with a bull.
You know?
It's like, well, yeah, butthat's recency bias, right?
That's like pat, or looking at a patternand 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.
(09:48):
It's like, uh, you know, that's, that'ssome 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 taken justindependently, those pieces of information
may have equal weighting, but youalready have dismissed one and used
the other one to bolster your case.
(10:09):
Uh, another one, if you'rein development or paying for
anything sunk cost bias, right?
It's like, how often arewe 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 Idon't, you know, once you've kind of
(10:32):
expanded time and energy and resources.
You don't wanna change direction to whereall the decision making that brought you
there and got you to spend money on stuff.
And time and energy getsdiscounted or thrown away.
Nobody wants to throwaway their, their energy.
Um, he also talks about, as an example,kind of talking about why it's so
(10:55):
hard to think differently about the,uh, this situation of Eastman Kodak.
Most people probably don't know,but, uh, they were starting in
1888, so they've been around a longtime 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,
(11:17):
first commercial camera availablein 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 thedigital camera employee of Eastman Kodak.
So here it is that he's got his,um, his right hand on this blue
(11:37):
thing and that whole stack ofstuff is the digital camera.
I think the one on his other hand islike 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 theindustry that was changing.
Does everybody remember thoselittle, um, stands that you'd drive
(12:01):
up to and drop your rolls to filmon those little photo like booths?
Like there was like a person there andthen you'd go back like a week later
and then they'd like rummage througha bunch of envelopes and give you one
and you'd like open it up and you'dsay, oh, that that was a bad picture.
That's a bad picture.
Uh, 20 good 20 bad pictures andtwo good pictures 'cause you, that
(12:22):
was how long the feedback loop was.
And just think about how taking aphoto now, I mean, I take photos of.
You know how wires are plugged in sothat when I'm disassembling something,
I'll remember how to put 'em back.
You know?
So it's like, we don'teven think about it.
I'll take pictures of, you know, justinane things, just as a reference, just
(12:44):
to like remember that I saw something, notthat 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 traditionalfilm, the film industry.
They could have had the whole futureelectronic film and, uh, digital
photograph photography industry.
But they, uh, they blew, they blew it.
(13:04):
They just didn't see that thedigital was the way it was
gonna go, and they didn't adapt.
And, um, I grabbed, thisis 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
(13:25):
that
thin.
It's like, and you've got fivedifferent aperture in focal length
camera lenses running on the back.
It's like, just that alone is a prettybig significant, uh, you know, change
in, in how we think about photography.
And you can argue, yeah.
Oh, a film cra can giveyou so much better picture.
(13:46):
And it does in a lot of ways, but theconvenience and the immediacy is like
far outweighs that in so many cases.
Um, I threw this in here, this,uh, book by Clayton Christensen.
Uh, if you're familiar withit, the Innovator's Dilemma
kind of fits in both chapters.
I threw it here and there's an honorablemention in the other chapter, but,
(14:09):
uh, if you ever are interested, this,uh, author goes and talks about why
it is that established corporationshave such a hard time innovating.
And to give you the short of it is thenew innovations almost always cannibalize.
The existing company'srevenue streams in some form.
(14:30):
And once a new innovation starts appearingand looks like it's gonna challenge the
status, uh, a quo that the company'sbuilt up and that revenue stream, then
there's like antibodies that get releasedin the company and just kills it.
So, uh, it's very difficult.
This is why startups can run circlesaround established companies.
Uh, when it comes to innovating.
(14:50):
It's a, it's a really interesting book.
I recommend it, but that'snot what we're talking about.
Uh, two speed thinking.
So, um, 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.
(15:11):
Yeah.
A second.
All right.
I'm gonna get to back to theseother topics here in a second.
Another, um, when I was reading thischapter, it really, um, another book that
I had read in college really, uh, poppedinto my mind and I brought it along.
(15:36):
How's that, sir? Has anyoneseen this book before?
(Audience 4) (15:39):
Excellent.
Andrew Lunde (15:39):
Yes.
Um, no one else.
So it's by a guy named Thomas Kuhn.
I think it was published originallyin 61, maybe 65, something like that.
It's pretty early.
Uh, let's see, 62, and I readthis in, uh, college philosophy
class and I really liked it.
(16:00):
Uh, I still have the sticker from the, uh,engineer's bookstore used at, uh, 5 95.
And uh, this book really goesthrough the Galileo use case goes
through a bunch of other similar.
Uh, use cases of how technology andspecific scientific technology really
is hard to change, why it's so hard tochange, thinking about what's going on,
(16:22):
whether it's in biology, and it goesthrough a bunch of different examples.
But the short of this book isreally before a new paradigm
of thinking takes over.
The folks that embodythe old one have to die.
And it's kind of a, a brutal truth, butthat's really, yes, there's always people
that bridge between the old schools ofthought and, and create new ground for the
(16:45):
new school of thoughts and have to dealwith a little bit of both sides of things.
But for things really to take holdin a broader sense in society, the,
the existing folks have to die.
And I thought that waspretty harsh, but true.
Um, when I bought this book, I was doinga little, I. Uh, calculator of inflation.
(17:08):
So according to, um, CPI, this is aBureau of Labor Statistics, uh, at 5 95.
It's now around 1634.
But if you go and, uh, look at theShadow Stats Index, which is a guy who
does these, uh, in, uh, 1980 methodologyindex of, of pricing, according to
(17:30):
him and his data, this book would'vewould be worth 106 bucks right now,
which I think is a little crazy.
But anyway, thought thatwould be kind of fun.
If you go looking for thisbook 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 littlebit, but same book, all another
fellow really restated the same thing.
(17:53):
Uh, max Planck, uh, said you in 1950.
So 1950, the new scientific truthdoes not triumph by convincing its
opponents and making them see the light.
But rather because its opponentseventually die and a new generation
grows up that is familiar with it.
So kinda restating the same premise.
(18:14):
Um, the next section, uh, aboutthe technology booms, uh, well,
before I go on questions Go ahead.
(Audience 5) (18:23):
I was just gonna comment.
Maybe we should consider,uh, outlawing life extension.
Andrew Lunde (18:29):
Outlawing life extension.
(Audience 5) (18:31):
Yeah.
Is that a problem now?
It's a slow
Andrew Lunde (18:37):
You mean like genic cryogenics?
Is that what you're saying?
(Audience 5) (18:41):
No, I mean, people that are trying to extend their life to be
150 years old or whatever, we shouldn'tdo that if it's gonna stop progress
for the people that come after it.
Right?
Andrew Lunde (18:49):
That's true.
If, if you follow this premise, thatwould, uh, be counteracting principle.
Any anybody else?
So it's really, it's really tryingto lay out this, this premise that,
you know, when you're thinkingabout things and there's a new
paradigm of thought that's emerging.
Just to understand just how horribly hardit is to really change at the, at a root
(19:12):
level, how you think about things andexpect that society will have lots and
lots of resistance to that new thought.
So as Bitcoiners, we're, we'rewell aware of this, right?
Because, uh, Bitcoin kind of getsaround a, a whole model of thought
around money and, uh, most people don'teven know what the money they have is.
And, uh, you know, so you gotta start bybacking up and explaining a lot before
(19:38):
you even get to the Bitcoin topic.
Uh, in chapter four, uh, calledTechnology Boom, he starts out with,
uh, a bit of a few examples, uh, whichwe'll go over here in a little bit.
So if, uh, he talks about a situationwhere his folks, uh, when he was
young, uh, asked like, would yourather have a million dollars now?
(19:59):
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 (20:20):
Shitload
Andrew Lunde (20:21):
A lot, right?
Also, he talks about, uh,well I'll go through that.
So,
so a penny doubled 31 times gives you10 million, $737,418 and 24 cents.
So as a kid you can imaginethat, you know, oh yeah,
(20:45):
I'll take a million dollars.
Right?
How much is a penny doubling?
Oh, maybe 20, 30 bucks mightbe your, your first thought.
So yeah, this is, um, this is where thenumbers get really hard to fathom, right.
Another story it relates is, um, theguy, the, the guy that invented the
game board chess, and he was, uh,I'm not sure if this was in China
(21:09):
or back in some Arabia somewhere.
And, uh, the king that of the timewas 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 grainof rice as my payment and the, uh,
(21:30):
but every, for every square on thechess board, I want to double it.
And, uh, there's 64, uh,squares on the chess board.
And a rice, a typical grain of riceis 0.029 grams per grain, which is, I
believe that's quadrillion 18 quadrillion.
Well, you can see the number.
(21:51):
It, it ends up being 1.2 tons of, of rice.
So the story, uh, as he was tellingit is that, uh, once the king kind
of figured out that this was gettingoutta hand, he had the guy executed.
So, go ahead Jordan.
(Audience 6) (22:07):
I think it's 18
Andrew Lunde (22:08):
Pentillion.
Okay.
Yeah, I had a Wow.
(Audience 6) (22:11):
Yeah.
Andrew Lunde (22:12):
That's crazy.
Um, so, uh, the third exampleis a piece of sheet of paper.
Yeah.
And folding it.
How, uh, if you f if you couldfold a sheet of paper 50 times
is actually impossible given thephysical constraints of paper.
If you could fold it 50 times,how high, how thick would it be?
(22:33):
And uh, yeah.
So the answer as you see here, is 149,uh, million kilometers, which is about
roughly the distance between the earth tothe sun, which is pretty crazy to think.
I mean, there's not enough paper, right?
So, um, the whole point of this is toillustrate that thinking exponentially
(22:57):
for humans is, is very hard, right?
I mean, we think we're doing good.
If we can think linearly, it'slike, okay, number go up, right?
Well, what's the, people willstart say, well, okay, it's a
Bitcoin's at a hundred thousand.
Maybe it'll be 140,000 by the endof the year or 150, or maybe 200.
Okay.
Well, last year it wasthis, so now it's this.
(23:18):
So next year it should be, uh, youknow, maybe I'll add 50% just to
kind of be optimistic or something.
But when you're talking about changesof thought, changes of, of technology,
changes of, of systems, they don'tnecessarily grow in a linear fashion.
(23:39):
They often will grow exponentially.
I mean, what's the time it takesto con to transmit a message
between here and England?
It's a fraction of a second, butbefore you had to write a letter.
Put it in the envelope, put a stampon it, give it to the post guy.
(24:00):
He had to go give it to the sorter.
I mean, got some point, it got on acruise ship, went across the ocean.
So, I mean, that's the kind ofdifferences that we're talking about,
(Audience 6) (24:11):
Andrew.
Andrew Lunde (24:11):
Yeah, sure.
(Audience 6) (24:12):
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'smore possible hashes than there
are atoms in the known universe,
Andrew Lunde (24:32):
right?
And that's hard to think about.
I guess you could say.
Well, that's the known universe, and maybewhat 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.
(24:54):
So everybody familiar with Moore's Law?
Pretty much?
Yes.
It's, this is a, a graph I found, andif 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 in1970, all the way up to about 2020.
(25:15):
And these are, uh, I knowit's tiny, you can't read it.
I don't expect you to, but these arelike literally all the processes, all
the CPUs that have been invented andkind of where they fit on this graph.
And even though that the, uh, it's alogarithmic on the left side, you can see
that it forms pretty much a straight line.
So this is really a doublingevery year of compute power.
And it has pretty much followed thatMoore's law, which is pretty astounding
(25:39):
that it's still, still in effect today.
And I've seen the same graph where afew 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 howthat is a, um, is similar to this
sigmoid function curve of technology.
(26:01):
And I couldn't find this anelectronic way, but I had to
snap it out of the book here.
But if you look at this, it's maybe alittle hard to see, but on the left,
the, the legend is performance goingup and then cost coming down, and
then time to the right on that axis.
And this first ssha sortof curve is Moore's law.
So what we just looked at, like at um.
(26:24):
On that last graph, which is astraight 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'spetering out, quantum technology
(26:47):
will be taking off, right?
Mm-hmm.
And then he's got a third one that hestarted here called the Third Technology.
So anyone wanna hazardto guess at the what?
The third, what's, what's thenext technology that's gonna
supplant, uh, quantum technology?
Audience (27:01):
Bitcoin.
Andrew Lunde (27:03):
Not Bitcoin.
Yes.
Audience (27:06):
It gotta be something.
Ai.
Ai.
Andrew Lunde (27:10):
No, no.
Ai.
Audience (27:11):
We use the quantum computers to simulate our own universes.
And then the, uh, inhabitantsof those universes.
Create their own computers withthe materials in those universes.
Andrew Lunde (27:22):
42, right?
Everybody know something relatedwith the our own, uh, body, right?
Like it might, it might, I mean,
Audience (27:36):
you have an answer.
Andrew Lunde (27:38):
I don't have an answer.
No.
It's an open question.
Um, sure.
We you know, the fact that we sittinghere, while we're probably just
barely grasping what quantum reallymeans, an entanglement means, and
the ability for these things tocompute states at immense speeds means
(28:00):
barely understanding that, tryingto put our brain into a mode where
we are thinking about the nextthing that, that supplants that is.
Really difficult from wherewe're sitting right now.
Right?
Um, but if history playsitself out, then there will be
something that does take over.
So when I saw that, it's remindedme of this, which is, um, the,
(28:27):
uh, the Gartner Hype Curve.
Uh, is anyone relationfamiliar with this one?
Audience (28:34):
Looks kinda
like the Dunning Kruger curve.
Andrew Lunde (28:36):
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 ofthinking 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 ROMtechnology, telephone technology.
(28:57):
Of course, the one everyone wants to lookat right now is the AI technology one.
Um, and where are we?
Where are we on this graph?
If this is kind of how things goin terms of technological adoption?
Um, I'm, I'm hearing more and more thatwe're over the peak of AI expectation.
Would it, are, would people think that,or you think we're still on the up forward
(29:20):
curve going up the, uh, rollercoasterwith 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 theexpectations or are we kind of, eh,
maybe it's not as, does doesn't doeverything that we want or, or not.
(29:44):
Doug,
Audience (29:45):
Give you my opinion.
I think on the general AI front, maybewe're potentially a little ahead of you.
Fully general AI in terms of likechat bots and do, but I think we're
way underestimated the impact ofreal world AI think is coming.
It's gonna be a much bigger deal.
Right?
(30:06):
Yeah.
From there we're talking about, youknow, robots and autonomous AI brains
and how they're gonna change, notthinking enough about how that's going.
Andrew Lunde (30:18):
Right.
So for those that probably won't hearhim on the recording, so Doug was saying
that I think we're kind of maxing outwhere the chat, the chat ai sort of is
getting us and that's, uh, what we'lleventually see is more, um, AI used
in, in, in broader techno technologies.
And this is where kind ofthe disillusionment happens.
(30:41):
Everybody's like, ah, isn't everything wethought it was gonna be, but through all
this discovery process, we get some reallygood, uh, examples that come out of it.
And then the slope of enlightenment whereyou 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 businessesthat are hanging onto it.
(31:02):
So,
so he talks a little, there's quite abit of, uh, discussion about self-driving
cars, and I'm not gonna get into allthe details, but he describes from
level zero, which is you drive thecar 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
(31:25):
how, you know, how it was pretty good.
I mean, things could, the car couldpark itself initially pretty decently.
And then it was driving around andon freeways pretty good and now it's
pretty much handling all situations.
He talks a little bit aboutlike how the, now we see go,
the companies built around it.
Uber and Lyft are big examplesof this, but he asks, you know.
(31:47):
Is that gonna, are they gonnacontinue to be able to make a, a good
business model and margin out of it?
Uh, when more and more cars and thecars that are typically owned be have
more and more capabilities, right?
Are smarter and smarter.
He also talks about, like, becausewe're in the habit of having everybody
(32:08):
having a car, then the amount of parkingthat's necessary is pretty large.
Uh, in terms of actual utilizationof the car, uh, really 5%.
We could only need 5% of the parkingthat we actually have to build now,
just because if there nobody had a carand everybody was running around on, in
like, you know, uh, automatic cars, thenthat would free up a lot of resources.
(32:30):
So it's another way of thinkingof 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 carinsurance is about you're insuring the
(32:50):
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 gonna make a mistake.
So how does that affectthe insurance industry?
And he even theorized that, wellreally they should just self-insure.
Like we as a company ensure that ourproducts aren't gonna run anybody over.
(33:13):
So there's no fault,there's no potential damage.
The point of it is, is to, while youthink about the car and it's cool and
the technology, the fact that it cansee the road and objects and react and
drive properly is really cool technology.
What about these secondary effects?
What about these secondary industriesand how are they gonna change around
(33:35):
the primary technology change?
And then I threw thislast one up in there.
'cause I thought years ago it's like.
Wouldn't it be nice to go ona vacation like out west or
someplace and have your own car?
You don't have to rent a car, you don'thave to, you got a plane ticket, you
don't have to like deal with baggageclaim, you know, I just wanna like pack
(33:58):
my car, jump in it, put the seat back andlike, say, wake me up when we get there.
Or I'll wake up, we have to, youknow, take a little biological
break or something and just like,alright, time to get off the freeway.
But how many people would like trust thecar so that you could like completely
fall asleep in it and know that it's notgonna like, run under a semi or something
(34:21):
or come skidding off the road if itstarts snowing or something like that.
I mean, do we trust theself-driving stuff that much yet?
Probably, probably not quite yet.
So, but I mean, if you see theimprovements, what's to think?
We can't get there.
I don't know.
So,
Uh, another thing I always dreamedof is like, why is it that my car
(34:44):
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 know, that's a lot ofair drag, but okay, if these cars are
so smart, then why can't you like doan ad hoc sort of train of cars such
(35:08):
that they're all like drafting on eachother and like, you know, and, and so
you, they all know how to flock swarmand figure out how to come in together.
And like when they're on a stretchof highway where you got 10 cars all
like bumper to bumper flying downthe freeway and you're optimizing the
air resistance, then you can get evenmore efficiency and get there faster.
(35:30):
And why not?
Right?
(Audience 4) (35:34):
Are we just, um, Andrew, I wanted to ask about, uh, Moore's Law.
Andrew Lunde (35:37):
Yeah.
(Audience 4) (35:38):
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 (35:48):
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 startgetting three and sub three that they
start running into, you know, differentphysics, electromagnetism, interference.
Like, we're starting to like, deal withthe properties of the matter itself.
(36:10):
Right.
I dunno, you, uh, Stephen'sgot maybe a thought here.
I
Audience (36:14):
Mean, yeah, I think we've been hitting that for a long time now.
Just in terms of like, we're getting downto the point where you just, it's not even
physically, it's, it's becoming physicallyharder to fit as much onto the chip.
Right.
We're, we're brushing upagainst the walls of physics.
However, there's also other advances,um, in processor technology that's
(36:35):
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 likeadding more cores and things like that.
These kinds of optimizations, whilethey're not the same as doubling
the number of transistors on thechip, they have the same net effect
(36:56):
expected outcome of picking thechip better, faster, more efficient.
So even if Moore's Law does breakapart in terms of we're not literally
putting more transistors on the chip, Ithink it sometimes seems as though the
intended outcome still holds and thatthe CPUs keep getting better and better.
They're just gettingbetter through other means.
Andrew Lunde (37:13):
All right, moving on.
Um, so gets into a section on virtualand 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 yearsold, I think was the first published,
(37:35):
let's see, checking, checking 2020.
Working.
Working 2020.
Okay.
So five years, which intechnology terms is a lot.
Right?
But he was talking about, uh, beingable to go to one of these labs
where he got to, uh, I think it wasApple Lab, where he could, uh, use of
virtual re uh, reality technology and.
(37:56):
And I, and, uh, now maybe it wasTesla and he got to do a simulation of
traveling to Mars and like running aroundon 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 tophysically travel to another place in
order to perform something, whether it'sa surgery or a mechanical operation,
(38:20):
'cause we can just, you know, operatea 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 whatexactly that means in so many ways for us.
Um, he also kind of posits into section.
It's like, well, if we can so easilykind of recreate a reality for ourselves,
(38:44):
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 ancientssince there's a philosopher that said,
if you could, if you could convinceyourself there's some, like demonic
being that's like intercepting allyour senses, then you can prove guy.
(39:06):
I can't remember whichphilosopher that was.
Kant, is that okay?
Kant?
Yeah.
So in a way, the whole idea of asimulation and like the Plato's cave
analogy kind of hints at that, right?
Audience (39:15):
Sorry, Descarte.
Andrew Lunde (39:16):
Descarte, sorry.
Okay.
So, uh, I just had one philosophy coursein college, so I didn't, anyway, um,
that's kind of fun and interesting.
He mentions that.
Um, and then, uh, there's a sectionon additive manufacturing and 3D
printing and, um, it really does kindof bogle the mind to think about.
(39:38):
It's like, well, we only do, if weonly need something and can create it
as needed, then that changes the wholesupply chain inventory, like moving
stuff around how you design stuff.
I mean.
The materials for doing 3D printingare getting better and better.
I've seen like steel composites,I've seen 3D printing with glass.
(39:59):
I've seen 3D printing with concretewhole buildings and houses, 3D printed.
I mean, it's pretty amazingwhat's possible these days.
Um, and like the cost savings and liketransportation logistics of all that
material and how, how much fabricationneeds to be done and for just to
get the material into a place likemaking bricks or paint or whatever.
(40:22):
It's like there's a lot ofimplications 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 ofextended this myself a little
bit with the whole concept.
And this really, if we go back tothe, what's the next technology
beyond quantum computing.
(40:45):
Well, if we could really control thetransfer between matter and energy.
Then effectively we cantransport matter or create matter
from other matter or energy.
And this really is what StarTrek was talking about in terms
of the technology that they had.
(41:06):
So in a way, we can, by virtue oflike 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 theplanet, they beam back up, they beam
to the middle, the under the surfaceof the planet sometimes, and then
they beam stuff that's there back up.
(41:28):
And whenever they are in the cantinaon the ship, they're like rolling
up to the, uh, the little doorwayright 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 thattechnology, what would that change?
How would our, I mean,no grocery store, no cow.
(41:48):
I mean, I don't know.
There's a lot, lot to think about.
And then, uh, the last sectionis the coming sonic boom.
And where he is going here withthis is comparing the, the cycle.
And he really kind of brings it backto this whole concept of abundance.
(42:10):
And currently today he laysout the case that, that we are
in a continuous credit expansionsystem where more money is created
and is to drive more production andmore output, more GDP more money.
And it's the whole Keynesian thing.
(42:31):
This is where we are kind of crankingand cranking and is it ever going to end?
Is there a natural limitto where this goes?
Uh, and the reason this works,he posits is because even though
technology is driving the priceand the cost of things down.
Down and down and down.
We have this countervailingforce of money creation that's
(42:52):
inflating things up and up and up.
So as long as there's more moneyproduction and credit expansion, it'll
seem like prices are always going up,even though they should be going down.
And effectively we're, we're justkicking the can down the road.
Now, a lot, I've been hearing a lotmore, and I threw this other part of
it in, is, you know, stable coins.
(43:14):
I'm not lightning yet.
One more way to kick the can downthe road a little more and maybe
we'd have a, a few thoughts onthat, but I can definitely see that.
I mean, currently I think, uh, tetheris the fourth largest consumer of US
treasuries or purchaser of US treasuries.
So if there's no purchaser ofUS treasuries at, if they went
(43:36):
away and stopped purchasing,what would that do to the dollar?
It's something to think about, right?
And, uh, and, and that for thatmatter, any other national state,
you know, sovereign currency could beaffected by effectively, where the,
the traditional monetary rails have acertain cost and latency and lag effect.
(43:58):
By putting everything on lightning, you'regonna 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 levelof thinking about the implications here.
(44:18):
So he, again, he brings it back tothe analogy of a sonic boom with
an airplane reaching the soundbarrier and pushing through it.
And when that happens, suddenly you seethe airplane and then the boom hits.
It's like, it's not hownature is supposed to react.
You're used to having it react where youhear something before it comes to you and.
(44:38):
Where he is going with this is thatthis 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'rewe'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 isthat it allows for an abundance without
(44:59):
the same amount of jobs and income.
Basically, the abundance should continueand benefit us and, uh, force prices
down such that we don't have to spendas much time and working and we don't
have to have as much income because ofthe abundance that technology should
be affording it if it wasn't forthis pesky monetary inflation thing.
(45:22):
So with that, I believe that's it.
Any q and a?
Anyone?
Anyone?
Bueller?
Anyone?
Alright?
Yes, we should have coordinated a, acertain, a teaser, um, for next time.
So that's all I got.
Um, again, this is me, Andrew, da da da.
(45:42):
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 (45:51):
Costco,
Andrew Lunde (45:52):
right?
Yeah.
So why, why do they put the TVs at thebeginning when you first walk into Costco?
'Audience: Cause they're not $20,000 anymore.
That's right.
So when you look at an 86 inch ultra highdensity AI, thin Q TV for 8 99, 99, you
(46:13):
might not buy it, but you walk by andyou go, man, that is brilliant picture.
That's like a pretty decent cost.
I remember when I spent seven grandon a plasma not too very long ago,
and it's on the curb, and then yougo 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.
(46:35):
Oh, well, it's 19.
All right.
Throw that in there.
It's like you really don't check pricesthat 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 (46:49):
They're giving you the, the deflation of the electronics,
right, so that you don't notice theinflation of the, of everything else.
(Applause)
Stephen DeLorme (47:04):
Hey, thanks for listening.
I hope you enjoyed this episode.
If you want to learn more aboutanything that we discussed, you can
look for links in the show notesthat should be in your podcast
player, or you can go to atlbitlab.
com slash podcast on a final note.
If you found this information usefuland you want to help support us, you
can always send us a tip in Bitcoin.
(47:25):
Your support really helps us that wecan keep bringing you content like this.
All right.
Catch you later.
There's a lot of implications of how
(00:02):
this technology can change.
What's the next technologybeyond quantum computing?
Well, if we could really control thetransfer between matter and energy.
Then effectively we can transport matteror create matter from other matter.
It's like, oh, gimme a martini.
(00:22):
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 (00:40):
This podcast episode is an event recording.
If you're listening to the audioversion, you might be missing some
context from the speaker's visuals.
You can find the videoversion at atlbitlab.
com.
That's A T L B I T L A B dot com.
There might also be audiencequestions or other background
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Look, event recordings are neverperfect, but we're sharing it here
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because we think you're going tofind something valuable in it.
Let's talk a little bit about our sponsorsfirst, and then we'll get onto the show.
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All right, on to our show.
Andrew Lunde (02:13):
So you probably seen me before round.
Um, we're covering, uh, Jeff Booth priceof 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 likerunning times about five and a half hours.
(02:37):
I like had it had listened to itabout two years ago and put it on
when I was doing some yard work theother 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 anyonehasn't met me before, uh, been around,
(02:59):
uh, doing development in various, um,incarnations from mobile all the way up
to enterprise stuff you wanna know aboutall that, just tap on me lately or later.
And, uh, lately I've been doingmore bitcoin Lightning trying to
get into the community, trying to.
Flex a little bit in the, uh, in thatrealm and try to contribute a bit.
(03:19):
Um, sound money got me closer tothis sort of realm, so my roots
go in that direction a little bit.
And, uh, decentralizedstuff, money media naming.
And id, if you're interested innaming an id, decentralized stuff,
you can find me later as well.
So let's get into it.
(03:40):
Alright, so as I mentioned, justuh, 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'sjust go ahead and take a look.
So in chapter three, he talks aboutwhy is it so hard to think differently?
(04:02):
And I think it's a really interestingtopic, the fact that kind of
begged I to let me do this part.
Uh, but, uh, he talks about, uh, howreally hard it is to change your, your.
Mode of thought and, and your modelof what you're thinking about.
And he mentions the, the, uh,the, of course example of Galileo.
I mean, before that point everybodythought that all that stuff all up in
(04:28):
the sky, the moon, the side, all the,even those funky things that didn't
move like we thought they should, werejust 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 causeda lot of consternation in his time.
Right?
And you can imagine, well, it would behard to imagine what really thinking about
(04:54):
the world prior to that really meant.
But, uh, we know from historythat uh, he had a real hard
time with the church about that.
And, uh, and.
You know, that was, that wasdefinitely a, a, a tough thing.
Uh, witches mentions witches that atthe, you know, turn of, uh, I guess
(05:15):
around the 14th, 1400, 1500 timeframe,even in the, the new colonies, a lot
of suspicion around what witches werein, 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 amodel of thinking about this.
(05:36):
They trusted the authorities and historyhas shown that they really, uh, we're
misguided in so many ways in that way.
Uh, he also then mentions a goodbit 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, Imean, everybody should have an equal right
(05:58):
to vote, but it's really a recent thing.
I mean, until the completeadoption of the 19th Amendment.
Uh, women couldn't vote, didn'thave the same say in government.
Uh, you know, and, and even thoughthey were really lobbying for it for
quite a long time in the lead up tothe 19th Amendment being ratified,
it's, uh, it just, it just wasn'tpart of the makeup of who decided what
(06:23):
was gonna go on in the government.
So those are pretty significant shifts.
The next part, um, is about weakfoundations and what does he mean by this?
So he makes a case abouthow our brains work.
Going back a little bit to physiology,I mean, I'm sure everybody's heard the
(06:47):
story about, well, thinking about backto Neanderthal Man and what's, uh.
What do you do if you see that orhear some rustling in the bushes?
It's like, do you like run away?
Do you like investigate?
It's like, is that just the windin the brush, in the, in the reeds,
or is that a tiger back there?
So as humans, we have to absorbso much information from our
(07:11):
environment all the time.
I mean, just if you think about what yougo through and experience, all the things
you're smelling, all the things you'rehearing, all the things you're seeing as
you go through life, it's, it's a lot.
So we've developed these mechanismsto filter out this information, this
deluge of information, and thosetake the form of biases really.
(07:35):
So, you know, if you have an instinctto run away from that rustling
sound in the bush, it's because.
You know, you're part of the gene poolthat survived and wasn't eaten by a tiger.
Whereas the other folks that likedecided, oh, I wonder what's going on
in that bush over there and then goteaten by a tiger, they didn't live long
enough to propagate their gene pool.
Right?
So we have this natural filteringmechanism that our brains go through.
(08:00):
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'mtalking, just throw your hand
up and I, we'll stop and chat.
I don't need to hold everything untilthe end of the, the talk, although
I have a little q and a at the be.
And if you want to justjump in, please do.
There's a microphone over there,over there by Chad, so if you
(08:21):
want to jump in, just let me know.
Alright.
We got a few more folkstrickling in, which is great.
We just got started, soyou haven't missed much.
So anyway, um, as you mentioned,there's a lot of sort of filtering
and bias judging, and a lot ofthis comes in the form of the, uh.
S basically these biases.
(08:42):
Now, if you ever go on Wikipediaand look, look at all the
psychological biases, you'd be amazed.
There's like, like listsand lists of biases.
Different biases, and youmight think, ah, that's crazy.
I'm sure are some of these just bullshit?
But you read each one and you're like,oh yeah, I can kind of see why that is.
(09:03):
And I just mentioned a few of them here.
So anchoring like just like oncesomething'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, thenthere's a consolidation chop, and
(09:25):
then there's a explosion with a bull.
You know?
It's like, well, yeah, butthat's recency bias, right?
That's like pat, or looking at a patternand 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.
(09:48):
It's like, uh, you know, that's, that'ssome 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 taken justindependently, those pieces of information
may have equal weighting, but youalready have dismissed one and used
the other one to bolster your case.
(10:09):
Uh, another one, if you'rein development or paying for
anything sunk cost bias, right?
It's like, how often arewe 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 Idon't, you know, once you've kind of
(10:32):
expanded time and energy and resources.
You don't wanna change direction to whereall the decision making that brought you
there and got you to spend money on stuff.
And time and energy getsdiscounted or thrown away.
Nobody wants to throwaway their, their energy.
Um, he also talks about, as an example,kind of talking about why it's so
(10:55):
hard to think differently about the,uh, this situation of Eastman Kodak.
Most people probably don't know,but, uh, they were starting in
1888, so they've been around a longtime 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,
(11:17):
first commercial camera availablein 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 thedigital camera employee of Eastman Kodak.
So here it is that he's got his,um, his right hand on this blue
(11:37):
thing and that whole stack ofstuff is the digital camera.
I think the one on his other hand islike 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 theindustry that was changing.
Does everybody remember thoselittle, um, stands that you'd drive
(12:01):
up to and drop your rolls to filmon those little photo like booths?
Like there was like a person there andthen you'd go back like a week later
and then they'd like rummage througha bunch of envelopes and give you one
and you'd like open it up and you'dsay, oh, that that was a bad picture.
That's a bad picture.
Uh, 20 good 20 bad pictures andtwo good pictures 'cause you, that
(12:22):
was how long the feedback loop was.
And just think about how taking aphoto now, I mean, I take photos of.
You know how wires are plugged in sothat when I'm disassembling something,
I'll remember how to put 'em back.
You know?
So it's like, we don'teven think about it.
I'll take pictures of, you know, justinane things, just as a reference, just
(12:44):
to like remember that I saw something, notthat 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 traditionalfilm, the film industry.
They could have had the whole futureelectronic film and, uh, digital
photograph photography industry.
But they, uh, they blew, they blew it.
(13:04):
They just didn't see that thedigital was the way it was
gonna go, and they didn't adapt.
And, um, I grabbed, thisis 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
(13:25):
that
thin.
It's like, and you've got fivedifferent aperture in focal length
camera lenses running on the back.
It's like, just that alone is a prettybig significant, uh, you know, change
in, in how we think about photography.
And you can argue, yeah.
Oh, a film cra can giveyou so much better picture.
(13:46):
And it does in a lot of ways, but theconvenience and the immediacy is like
far outweighs that in so many cases.
Um, I threw this in here, this,uh, book by Clayton Christensen.
Uh, if you're familiar withit, the Innovator's Dilemma
kind of fits in both chapters.
I threw it here and there's an honorablemention in the other chapter, but,
(14:09):
uh, if you ever are interested, this,uh, author goes and talks about why
it is that established corporationshave such a hard time innovating.
And to give you the short of it is thenew innovations almost always cannibalize.
The existing company'srevenue streams in some form.
(14:30):
And once a new innovation starts appearingand looks like it's gonna challenge the
status, uh, a quo that the company'sbuilt up and that revenue stream, then
there's like antibodies that get releasedin the company and just kills it.
So, uh, it's very difficult.
This is why startups can run circlesaround established companies.
Uh, when it comes to innovating.
(14:50):
It's a, it's a really interesting book.
I recommend it, but that'snot what we're talking about.
Uh, two speed thinking.
So, um, 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.
(15:11):
Yeah.
A second.
All right.
I'm gonna get to back to theseother topics here in a second.
Another, um, when I was reading thischapter, it really, um, another book that
I had read in college really, uh, poppedinto my mind and I brought it along.
(15:36):
How's that, sir? Has anyoneseen this book before?
(Audience 4) (15:39):
Excellent.
Andrew Lunde (15:39):
Yes.
Um, no one else.
So it's by a guy named Thomas Kuhn.
I think it was published originallyin 61, maybe 65, something like that.
It's pretty early.
Uh, let's see, 62, and I readthis in, uh, college philosophy
class and I really liked it.
(16:00):
Uh, I still have the sticker from the, uh,engineer's bookstore used at, uh, 5 95.
And uh, this book really goesthrough the Galileo use case goes
through a bunch of other similar.
Uh, use cases of how technology andspecific scientific technology really
is hard to change, why it's so hard tochange, thinking about what's going on,
(16:22):
whether it's in biology, and it goesthrough a bunch of different examples.
But the short of this book isreally before a new paradigm
of thinking takes over.
The folks that embodythe old one have to die.
And it's kind of a, a brutal truth, butthat's really, yes, there's always people
that bridge between the old schools ofthought and, and create new ground for the
(16:45):
new school of thoughts and have to dealwith a little bit of both sides of things.
But for things really to take holdin a broader sense in society, the,
the existing folks have to die.
And I thought that waspretty harsh, but true.
Um, when I bought this book, I was doinga little, I. Uh, calculator of inflation.
(17:08):
So according to, um, CPI, this is aBureau of Labor Statistics, uh, at 5 95.
It's now around 1634.
But if you go and, uh, look at theShadow Stats Index, which is a guy who
does these, uh, in, uh, 1980 methodologyindex of, of pricing, according to
(17:30):
him and his data, this book would'vewould be worth 106 bucks right now,
which I think is a little crazy.
But anyway, thought thatwould be kind of fun.
If you go looking for thisbook 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 littlebit, but same book, all another
fellow really restated the same thing.
(17:53):
Uh, max Planck, uh, said you in 1950.
So 1950, the new scientific truthdoes not triumph by convincing its
opponents and making them see the light.
But rather because its opponentseventually die and a new generation
grows up that is familiar with it.
So kinda restating the same premise.
(18:14):
Um, the next section, uh, aboutthe technology booms, uh, well,
before I go on questions Go ahead.
(Audience 5) (18:23):
I was just gonna comment.
Maybe we should consider,uh, outlawing life extension.
Andrew Lunde (18:29):
Outlawing life extension.
(Audience 5) (18:31):
Yeah.
Is that a problem now?
It's a slow
Andrew Lunde (18:37):
You mean like genic cryogenics?
Is that what you're saying?
(Audience 5) (18:41):
No, I mean, people that are trying to extend their life to be
150 years old or whatever, we shouldn'tdo that if it's gonna stop progress
for the people that come after it.
Right?
Andrew Lunde (18:49):
That's true.
If, if you follow this premise, thatwould, uh, be counteracting principle.
Any anybody else?
So it's really, it's really tryingto lay out this, this premise that,
you know, when you're thinkingabout things and there's a new
paradigm of thought that's emerging.
Just to understand just how horribly hardit is to really change at the, at a root
(19:12):
level, how you think about things andexpect that society will have lots and
lots of resistance to that new thought.
So as Bitcoiners, we're, we'rewell aware of this, right?
Because, uh, Bitcoin kind of getsaround a, a whole model of thought
around money and, uh, most people don'teven know what the money they have is.
And, uh, you know, so you gotta start bybacking up and explaining a lot before
(19:38):
you even get to the Bitcoin topic.
Uh, in chapter four, uh, calledTechnology Boom, he starts out with,
uh, a bit of a few examples, uh, whichwe'll go over here in a little bit.
So if, uh, he talks about a situationwhere his folks, uh, when he was
young, uh, asked like, would yourather have a million dollars now?
(19:59):
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 (20:20):
Shitload
Andrew Lunde (20:21):
A lot, right?
Also, he talks about, uh,well I'll go through that.
So,
so a penny doubled 31 times gives you10 million, $737,418 and 24 cents.
So as a kid you can imaginethat, you know, oh yeah,
(20:45):
I'll take a million dollars.
Right?
How much is a penny doubling?
Oh, maybe 20, 30 bucks mightbe your, your first thought.
So yeah, this is, um, this is where thenumbers get really hard to fathom, right.
Another story it relates is, um, theguy, the, the guy that invented the
game board chess, and he was, uh,I'm not sure if this was in China
(21:09):
or back in some Arabia somewhere.
And, uh, the king that of the timewas 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 grainof rice as my payment and the, uh,
(21:30):
but every, for every square on thechess board, I want to double it.
And, uh, there's 64, uh,squares on the chess board.
And a rice, a typical grain of riceis 0.029 grams per grain, which is, I
believe that's quadrillion 18 quadrillion.
Well, you can see the number.
(21:51):
It, it ends up being 1.2 tons of, of rice.
So the story, uh, as he was tellingit is that, uh, once the king kind
of figured out that this was gettingoutta hand, he had the guy executed.
So, go ahead Jordan.
(Audience 6) (22:07):
I think it's 18
Andrew Lunde (22:08):
Pentillion.
Okay.
Yeah, I had a Wow.
(Audience 6) (22:11):
Yeah.
Andrew Lunde (22:12):
That's crazy.
Um, so, uh, the third exampleis a piece of sheet of paper.
Yeah.
And folding it.
How, uh, if you f if you couldfold a sheet of paper 50 times
is actually impossible given thephysical constraints of paper.
If you could fold it 50 times,how high, how thick would it be?
(22:33):
And uh, yeah.
So the answer as you see here, is 149,uh, million kilometers, which is about
roughly the distance between the earth tothe sun, which is pretty crazy to think.
I mean, there's not enough paper, right?
So, um, the whole point of this is toillustrate that thinking exponentially
(22:57):
for humans is, is very hard, right?
I mean, we think we're doing good.
If we can think linearly, it'slike, okay, number go up, right?
Well, what's the, people willstart say, well, okay, it's a
Bitcoin's at a hundred thousand.
Maybe it'll be 140,000 by the endof the year or 150, or maybe 200.
Okay.
Well, last year it wasthis, so now it's this.
(23:18):
So next year it should be, uh, youknow, maybe I'll add 50% just to
kind of be optimistic or something.
But when you're talking about changesof thought, changes of, of technology,
changes of, of systems, they don'tnecessarily grow in a linear fashion.
(23:39):
They often will grow exponentially.
I mean, what's the time it takesto con to transmit a message
between here and England?
It's a fraction of a second, butbefore you had to write a letter.
Put it in the envelope, put a stampon it, give it to the post guy.
(24:00):
He had to go give it to the sorter.
I mean, got some point, it got on acruise ship, went across the ocean.
So, I mean, that's the kind ofdifferences that we're talking about,
(Audience 6) (24:11):
Andrew.
Andrew Lunde (24:11):
Yeah, sure.
(Audience 6) (24:12):
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'smore possible hashes than there
are atoms in the known universe,
Andrew Lunde (24:32):
right?
And that's hard to think about.
I guess you could say.
Well, that's the known universe, and maybewhat 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.
(24:54):
So everybody familiar with Moore's Law?
Pretty much?
Yes.
It's, this is a, a graph I found, andif 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 in1970, all the way up to about 2020.
(25:15):
And these are, uh, I knowit's tiny, you can't read it.
I don't expect you to, but these arelike literally all the processes, all
the CPUs that have been invented andkind of where they fit on this graph.
And even though that the, uh, it's alogarithmic on the left side, you can see
that it forms pretty much a straight line.
So this is really a doublingevery year of compute power.
And it has pretty much followed thatMoore's law, which is pretty astounding
(25:39):
that it's still, still in effect today.
And I've seen the same graph where afew 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 howthat is a, um, is similar to this
sigmoid function curve of technology.
(26:01):
And I couldn't find this anelectronic way, but I had to
snap it out of the book here.
But if you look at this, it's maybe alittle hard to see, but on the left,
the, the legend is performance goingup and then cost coming down, and
then time to the right on that axis.
And this first ssha sortof curve is Moore's law.
So what we just looked at, like at um.
(26:24):
On that last graph, which is astraight 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'spetering out, quantum technology
(26:47):
will be taking off, right?
Mm-hmm.
And then he's got a third one that hestarted here called the Third Technology.
So anyone wanna hazardto guess at the what?
The third, what's, what's thenext technology that's gonna
supplant, uh, quantum technology?
Audience (27:01):
Bitcoin.
Andrew Lunde (27:03):
Not Bitcoin.
Yes.
Audience (27:06):
It gotta be something.
Ai.
Ai.
Andrew Lunde (27:10):
No, no.
Ai.
Audience (27:11):
We use the quantum computers to simulate our own universes.
And then the, uh, inhabitantsof those universes.
Create their own computers withthe materials in those universes.
Andrew Lunde (27:22):
42, right?
Everybody know something relatedwith the our own, uh, body, right?
Like it might, it might, I mean,
Audience (27:36):
you have an answer.
Andrew Lunde (27:38):
I don't have an answer.
No.
It's an open question.
Um, sure.
We you know, the fact that we sittinghere, while we're probably just
barely grasping what quantum reallymeans, an entanglement means, and
the ability for these things tocompute states at immense speeds means
(28:00):
barely understanding that, tryingto put our brain into a mode where
we are thinking about the nextthing that, that supplants that is.
Really difficult from wherewe're sitting right now.
Right?
Um, but if history playsitself out, then there will be
something that does take over.
So when I saw that, it's remindedme of this, which is, um, the,
(28:27):
uh, the Gartner Hype Curve.
Uh, is anyone relationfamiliar with this one?
Audience (28:34):
Looks kinda
like the Dunning Kruger curve.
Andrew Lunde (28:36):
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 ofthinking 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 ROMtechnology, telephone technology.
(28:57):
Of course, the one everyone wants to lookat right now is the AI technology one.
Um, and where are we?
Where are we on this graph?
If this is kind of how things goin terms of technological adoption?
Um, I'm, I'm hearing more and more thatwe're over the peak of AI expectation.
Would it, are, would people think that,or you think we're still on the up forward
(29:20):
curve going up the, uh, rollercoasterwith 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 theexpectations or are we kind of, eh,
maybe it's not as, does doesn't doeverything that we want or, or not.
(29:44):
Doug,
Audience (29:45):
Give you my opinion.
I think on the general AI front, maybewe're potentially a little ahead of you.
Fully general AI in terms of likechat bots and do, but I think we're
way underestimated the impact ofreal world AI think is coming.
It's gonna be a much bigger deal.
Right?
(30:06):
Yeah.
From there we're talking about, youknow, robots and autonomous AI brains
and how they're gonna change, notthinking enough about how that's going.
Andrew Lunde (30:18):
Right.
So for those that probably won't hearhim on the recording, so Doug was saying
that I think we're kind of maxing outwhere the chat, the chat ai sort of is
getting us and that's, uh, what we'lleventually see is more, um, AI used
in, in, in broader techno technologies.
And this is where kind ofthe disillusionment happens.
(30:41):
Everybody's like, ah, isn't everything wethought it was gonna be, but through all
this discovery process, we get some reallygood, uh, examples that come out of it.
And then the slope of enlightenment whereyou 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 businessesthat are hanging onto it.
(31:02):
So,
so he talks a little, there's quite abit of, uh, discussion about self-driving
cars, and I'm not gonna get into allthe details, but he describes from
level zero, which is you drive thecar 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
(31:25):
how, you know, how it was pretty good.
I mean, things could, the car couldpark itself initially pretty decently.
And then it was driving around andon freeways pretty good and now it's
pretty much handling all situations.
He talks a little bit aboutlike how the, now we see go,
the companies built around it.
Uber and Lyft are big examplesof this, but he asks, you know.
(31:47):
Is that gonna, are they gonnacontinue to be able to make a, a good
business model and margin out of it?
Uh, when more and more cars and thecars that are typically owned be have
more and more capabilities, right?
Are smarter and smarter.
He also talks about, like, becausewe're in the habit of having everybody
(32:08):
having a car, then the amount of parkingthat's necessary is pretty large.
Uh, in terms of actual utilizationof the car, uh, really 5%.
We could only need 5% of the parkingthat we actually have to build now,
just because if there nobody had a carand everybody was running around on, in
like, you know, uh, automatic cars, thenthat would free up a lot of resources.
(32:30):
So it's another way of thinkingof 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 carinsurance is about you're insuring the
(32:50):
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 gonna make a mistake.
So how does that affectthe insurance industry?
And he even theorized that, wellreally they should just self-insure.
Like we as a company ensure that ourproducts aren't gonna run anybody over.
(33:13):
So there's no fault,there's no potential damage.
The point of it is, is to, while youthink about the car and it's cool and
the technology, the fact that it cansee the road and objects and react and
drive properly is really cool technology.
What about these secondary effects?
What about these secondary industriesand how are they gonna change around
(33:35):
the primary technology change?
And then I threw thislast one up in there.
'cause I thought years ago it's like.
Wouldn't it be nice to go ona vacation like out west or
someplace and have your own car?
You don't have to rent a car, you don'thave to, you got a plane ticket, you
don't have to like deal with baggageclaim, you know, I just wanna like pack
(33:58):
my car, jump in it, put the seat back andlike, say, wake me up when we get there.
Or I'll wake up, we have to, youknow, take a little biological
break or something and just like,alright, time to get off the freeway.
But how many people would like trust thecar so that you could like completely
fall asleep in it and know that it's notgonna like, run under a semi or something
(34:21):
or come skidding off the road if itstarts snowing or something like that.
I mean, do we trust theself-driving stuff that much yet?
Probably, probably not quite yet.
So, but I mean, if you see theimprovements, what's to think?
We can't get there.
I don't know.
So,
Uh, another thing I always dreamedof is like, why is it that my car
(34:44):
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 know, that's a lot ofair drag, but okay, if these cars are
so smart, then why can't you like doan ad hoc sort of train of cars such
(35:08):
that they're all like drafting on eachother and like, you know, and, and so
you, they all know how to flock swarmand figure out how to come in together.
And like when they're on a stretchof highway where you got 10 cars all
like bumper to bumper flying downthe freeway and you're optimizing the
air resistance, then you can get evenmore efficiency and get there faster.
(35:30):
And why not?
Right?
(Audience 4) (35:34):
Are we just, um, Andrew, I wanted to ask about, uh, Moore's Law.
Andrew Lunde (35:37):
Yeah.
(Audience 4) (35:38):
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 (35:48):
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 startgetting three and sub three that they
start running into, you know, differentphysics, electromagnetism, interference.
Like, we're starting to like, deal withthe properties of the matter itself.
(36:10):
Right.
I dunno, you, uh, Stephen'sgot maybe a thought here.
I
Audience (36:14):
Mean, yeah, I think we've been hitting that for a long time now.
Just in terms of like, we're getting downto the point where you just, it's not even
physically, it's, it's becoming physicallyharder to fit as much onto the chip.
Right.
We're, we're brushing upagainst the walls of physics.
However, there's also other advances,um, in processor technology that's
(36:35):
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 likeadding more cores and things like that.
These kinds of optimizations, whilethey're not the same as doubling
the number of transistors on thechip, they have the same net effect
(36:56):
expected outcome of picking thechip better, faster, more efficient.
So even if Moore's Law does breakapart in terms of we're not literally
putting more transistors on the chip, Ithink it sometimes seems as though the
intended outcome still holds and thatthe CPUs keep getting better and better.
They're just gettingbetter through other means.
Andrew Lunde (37:13):
All right, moving on.
Um, so gets into a section on virtualand 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 yearsold, I think was the first published,
(37:35):
let's see, checking, checking 2020.
Working.
Working 2020.
Okay.
So five years, which intechnology terms is a lot.
Right?
But he was talking about, uh, beingable to go to one of these labs
where he got to, uh, I think it wasApple Lab, where he could, uh, use of
virtual re uh, reality technology and.
(37:56):
And I, and, uh, now maybe it wasTesla and he got to do a simulation of
traveling to Mars and like running aroundon 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 tophysically travel to another place in
order to perform something, whether it'sa surgery or a mechanical operation,
(38:20):
'cause we can just, you know, operatea 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 whatexactly that means in so many ways for us.
Um, he also kind of posits into section.
It's like, well, if we can so easilykind of recreate a reality for ourselves,
(38:44):
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 ancientssince there's a philosopher that said,
if you could, if you could convinceyourself there's some, like demonic
being that's like intercepting allyour senses, then you can prove guy.
(39:06):
I can't remember whichphilosopher that was.
Kant, is that okay?
Kant?
Yeah.
So in a way, the whole idea of asimulation and like the Plato's cave
analogy kind of hints at that, right?
Audience (39:15):
Sorry, Descarte.
Andrew Lunde (39:16):
Descarte, sorry.
Okay.
So, uh, I just had one philosophy coursein college, so I didn't, anyway, um,
that's kind of fun and interesting.
He mentions that.
Um, and then, uh, there's a sectionon additive manufacturing and 3D
printing and, um, it really does kindof bogle the mind to think about.
(39:38):
It's like, well, we only do, if weonly need something and can create it
as needed, then that changes the wholesupply chain inventory, like moving
stuff around how you design stuff.
I mean.
The materials for doing 3D printingare getting better and better.
I've seen like steel composites,I've seen 3D printing with glass.
(39:59):
I've seen 3D printing with concretewhole buildings and houses, 3D printed.
I mean, it's pretty amazingwhat's possible these days.
Um, and like the cost savings and liketransportation logistics of all that
material and how, how much fabricationneeds to be done and for just to
get the material into a place likemaking bricks or paint or whatever.
(40:22):
It's like there's a lot ofimplications 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 ofextended this myself a little
bit with the whole concept.
And this really, if we go back tothe, what's the next technology
beyond quantum computing.
(40:45):
Well, if we could really control thetransfer between matter and energy.
Then effectively we cantransport matter or create matter
from other matter or energy.
And this really is what StarTrek was talking about in terms
of the technology that they had.
(41:06):
So in a way, we can, by virtue oflike 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 theplanet, they beam back up, they beam
to the middle, the under the surfaceof the planet sometimes, and then
they beam stuff that's there back up.
(41:28):
And whenever they are in the cantinaon the ship, they're like rolling
up to the, uh, the little doorwayright 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 thattechnology, what would that change?
How would our, I mean,no grocery store, no cow.
(41:48):
I mean, I don't know.
There's a lot, lot to think about.
And then, uh, the last sectionis the coming sonic boom.
And where he is going here withthis is comparing the, the cycle.
And he really kind of brings it backto this whole concept of abundance.
(42:10):
And currently today he laysout the case that, that we are
in a continuous credit expansionsystem where more money is created
and is to drive more production andmore output, more GDP more money.
And it's the whole Keynesian thing.
(42:31):
This is where we are kind of crankingand cranking and is it ever going to end?
Is there a natural limitto where this goes?
Uh, and the reason this works,he posits is because even though
technology is driving the priceand the cost of things down.
Down and down and down.
We have this countervailingforce of money creation that's
(42:52):
inflating things up and up and up.
So as long as there's more moneyproduction and credit expansion, it'll
seem like prices are always going up,even though they should be going down.
And effectively we're, we're justkicking the can down the road.
Now, a lot, I've been hearing a lotmore, and I threw this other part of
it in, is, you know, stable coins.
(43:14):
I'm not lightning yet.
One more way to kick the can downthe road a little more and maybe
we'd have a, a few thoughts onthat, but I can definitely see that.
I mean, currently I think, uh, tetheris the fourth largest consumer of US
treasuries or purchaser of US treasuries.
So if there's no purchaser ofUS treasuries at, if they went
(43:36):
away and stopped purchasing,what would that do to the dollar?
It's something to think about, right?
And, uh, and, and that for thatmatter, any other national state,
you know, sovereign currency could beaffected by effectively, where the,
the traditional monetary rails have acertain cost and latency and lag effect.
(43:58):
By putting everything on lightning, you'regonna 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 levelof thinking about the implications here.
(44:18):
So he, again, he brings it back tothe analogy of a sonic boom with
an airplane reaching the soundbarrier and pushing through it.
And when that happens, suddenly you seethe airplane and then the boom hits.
It's like, it's not hownature is supposed to react.
You're used to having it react where youhear something before it comes to you and.
(44:38):
Where he is going with this is thatthis 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'rewe'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 isthat it allows for an abundance without
(44:59):
the same amount of jobs and income.
Basically, the abundance should continueand benefit us and, uh, force prices
down such that we don't have to spendas much time and working and we don't
have to have as much income because ofthe abundance that technology should
be affording it if it wasn't forthis pesky monetary inflation thing.
(45:22):
So with that, I believe that's it.
Any q and a?
Anyone?
Anyone?
Bueller?
Anyone?
Alright?
Yes, we should have coordinated a, acertain, a teaser, um, for next time.
So that's all I got.
Um, again, this is me, Andrew, da da da.
(45:42):
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 (45:51):
Costco,
Andrew Lunde (45:52):
right?
Yeah.
So why, why do they put the TVs at thebeginning when you first walk into Costco?
'Audience: Cause they're not $20,000 anymore.
That's right.
So when you look at an 86 inch ultra highdensity AI, thin Q TV for 8 99, 99, you
(46:13):
might not buy it, but you walk by andyou go, man, that is brilliant picture.
That's like a pretty decent cost.
I remember when I spent seven grandon a plasma not too very long ago,
and it's on the curb, and then yougo 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.
(46:35):
Oh, well, it's 19.
All right.
Throw that in there.
It's like you really don't check pricesthat 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 (46:49):
They're giving you the, the deflation of the electronics,
right, so that you don't notice theinflation of the, of everything else.
(Applause)
Stephen DeLorme (47:04):
Hey, thanks for listening.
I hope you enjoyed this episode.
If you want to learn more aboutanything that we discussed, you can
look for links in the show notesthat should be in your podcast
player, or you can go to atlbitlab.
com slash podcast on a final note.
If you found this information usefuland you want to help support us, you
can always send us a tip in Bitcoin.
(47:25):
Your support really helps us that wecan keep bringing you content like this.
All right.
Catch you later.
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