Welcome back to the Deep Dive. So you've brought
us a pretty dense stack of sources today. We've
got historical timelines, economic analysis,
some really deep engineering reports, and they're
all trying to get their arms around, well, what
might be the single most transformative era in
human history? The information age. It's a huge
topic and it's one we're still, you know, living
right in the middle of. We call it so many things.
the digital age, the computer age. Some people
even call it the third industrial revolution.
But to really understand it, you have to step
back. You have to treat it like any other major
historical epoch. And that's exactly our mission
for this deep dive. We're going to try and track
a revolution that completely flipped the script
on what has economic value. I mean, the central
question is, how did society pull off this massive,
incredibly rapid shift from an economy all about
atoms, you know, physical stuff, factories, land,
one that's now centered almost purely on bits?
How did information go from being a support tool
to the main event? That is the core question.
We define the information age as a pretty distinct
historical period. It starts right around the
mid -20th century. And it's characterized by
this incredible acceleration of information technology
and the shift away from that old industrial age
economy to one built on knowledge and data. Right.
And your sources are, I mean, they're incredibly
comprehensive. They cover everything from the
atomic physics of a semiconductor all the way
up to these huge macro level sociological changes.
So our deep dive today is designed to trace that
entire path from a single critical invention
back in 1947, right up to the global, mobile,
always on world we have today. And by the time
we're done, you, the listener, should walk away
with the critical context for just how fast and
how profoundly our world was remade. Okay, let's
get into this history. And I think to really
appreciate the sheer speed of the information
age, we have to start with what came before.
We need a baseline. Absolutely. I mean, for thousands
of years, humans have been trying to find better
ways to calculate and manage data. It's a fundamental
need. For millennia, we relied on purely mechanical
aids, things like the abacus, the astrolabe,
the slide rule. Tools that help a single person
think faster. Exactly. But the Industrial Revolution,
especially in the 1800s, that's when we see the
first real steps toward automating data processing
on a larger scale. Which brings us to someone
like Herman Hollerith and his punch card system.
It's easy to forget now, but that was a monumental
shift. It wasn't just about counting faster.
It was a revolution in information management.
It absolutely was. Hollerith's devices, which
he developed for the 1890 U .S. Census, were
electromechanical. They used electrical currents
to sense where holes were punched into these
standardized cards. This took a process tabulating
the census that used to take years of painstaking
manual labor. mechanized it. It was essential
for handling large -scale data well before we
had a true electronic computer. It proved you
could standardize information and process it
with a machine. Okay, so that sets a kind of
baseline for mechanical data processing. Then
we jump forward to the World War II era, and
you get these massive, specialized analog computers.
We're talking about room -sized vacuum tube behemoths.
The ENIAC, the Z3, incredible engineering, but
they had some pretty severe limitations. Oh,
massive limitations. That's the crucial point.
Those machines, while you could call them digital
in concept, were fundamentally constrained by
the physics of their parts. They were hot, they
consumed staggering amounts of electricity, and
the vacuum tubes were so fragile they'd burn
out constantly. You had teams of people just
running around replacing tubes to keep the thing
running. So they were one -off, custom -built.
Multi -million dollar projects. You couldn't
scale them down. You couldn't mass produce them
for, you know, an office or a home. You couldn't.
We needed a completely new kind of component
to break through that size and power barrier.
And that component arrived in 1947. Your sources
pinpoint this as the official starting gun, the
critical catalyst that truly kicks off the information
age. We're talking about the transistor. Precisely.
It was 1947 at Bell Labs. John Bardeen and Walter
Hauser Bratton, working in a group led by William
Shockley, they demonstrated the first working
point contact transistor. It was made of germanium.
And it is... Truly hard to overstate the seismic
shift this one little device represented. So
explain that for us. Why was this tiny piece
of solid material so much more revolutionary
than the entire room full of vacuum tubes it
was designed to replace? Because it solved all
those existential physical problems in one go.
A vacuum tube works by heating a filament boiling
off electrons. It needs high voltage and it gets
incredibly hot. All that heat is wasted energy
and it's what makes them burn out. The transistor
is solid state. There are no... moving parts,
no vacuum, no filament. It operates on low voltage,
generates very little heat, and it's incredibly
small and durable. Just instantly vaporize the
power and size barrier. And the sources you brought
make this explicit, right? The UN Public Administration
Network points directly to this invention. They
do. They cite this breakthrough, the one that
enabled computer miniaturization, as the single
key driving force for modernized information
systems and the social evolution that followed.
It's a simple truth. If you can't make the machine
small, You can't make it personal. And if you
can't make it personal, you certainly can't make
it global. Okay, so the hardware is suddenly
tiny and efficient. But that's just one piece.
It's like building a faster highway. You still
need traffic laws to manage all the new cars.
That is a perfect analogy. And that's where the
second pillar of this revolution comes in, from
Claude Shannon. A year later, in 1948, Shannon,
who was a brilliant mathematician also working
at Bell Labs, publishes a paper called A Mathematical
Theory of Communication. Now, for anyone listening
who might not be familiar with that paper, break
down what Shannon's theory actually provided.
What was the traffic law? It provided the entire
theoretical bedrock for digitalization. He's
the one who figured out how to mathematically
quantify information in bits, binary digits.
But crucially, his work also laid out the principles
of data compression and error correction. He
showed the fundamental limits of how much information
you could reliably send over a noisy channel.
Without that framework, Digital communication
would be a mess. Every time you copied a file,
it would get corrupted. The whole system breaks
down. His theory made it economical and, more
importantly, reliable. So once you have Shannon's
theory, the software, so to speak, and the transistor,
the hardware, the race was on, it wasn't just
about building one transistor anymore. It was
about figuring out how to cram thousands and
then millions and now billions of them together.
And the acceleration was just phenomenal. The
1950s became this decade of rapid integration.
In 1958, Jack Kilby at Texas Instruments creates
the first integrated circuit, the IC. He basically
figured out how to put multiple components onto
a single block of semiconductor material. Right
on his heels, Robert Noyce at Fairchild Semiconductor
invented the monolithic IC chip in 1959, which
made it much easier to manufacture. But the sources
you have really stress... That the real pivot
point, the thing that unlocked mass production,
wasn't just the IC in general. It was a very
specific type of transistor. Yes, and this is
the kind of critical detail that a lot of general
histories just gloss over. We're talking about
the MOSFET. the metal oxide semiconductor field
effect transistor. It was invented in 1960 by
Muhammad Atala and Anand Kong, again at Bell
Labs. The MOSFET was the absolute game changer
for scaling up. Okay, so why? What made the MOSFET
so much better for building these complex circuits
than the earlier bipolar ICs from Kilby and Noyce?
It came down to two things, really. Density and
the cost of manufacturing. MOSFETs were just
significantly easier to miniaturize. They consumed
less power and were simpler to fabricate in these
huge high -density arrays on a silicon wafer.
So this technology allowed chip makers to just
cram more and more logic gates into the same
small space, which drove down the cost per function.
This is what enabled what we call LSI, or large
-scale integration. By the late 1960s, you had
LSI chips holding hundreds of transistors. It
paved the way for the microprocessor. So if you
trace that arc, it's just astonishing. About
24 years, we go from a fragile, glowing vacuum
tube to a tiny, manufacturable chip that could
hold the entire brain of a computer. That's the
narrative. And that new capability, that incredible
rate of growth it unleashed, it demanded a new
set of, well, laws to even describe what was
happening. Right. So if the transistor was the
spark, then these exponential laws that governed
its replication, they were the engine. the engine
that drove the information age forward at a speed
humanity had just never seen before. And to get
it, you really have to look at two fundamental
forces that are completely intertwined, computation
power and storage capacity. Let's start with
computation, which is pretty much defined by
that famous observation Gordon Moore made back
in 1965. We all know it as Moore's Law. It states
that the number of transistors you can fit on
a dense integrated circuit doubles approximately
every two years. And what's amazing about Moore's
Law is that it wasn't just a prediction. It became
a self -fulfilling prophecy. It became the roadmap
for the entire semiconductor industry. Engineers
at Intel, at Texas Instruments, they used Moore's
Law as their target. And because everyone was
pushing for that same goal, this persistent,
dedicated doubling of density just drove the
cost of computing power through the floor year
after year. A task that would have cost thousands
of dollars on a mainframe in the 70s became practically
free 20 years later. Exactly. And that continuous
cost erosion is what made digital tools accessible,
first to businesses and then to everyone, everywhere.
But all that processing power is useless if you
have nowhere to put the results. You need somewhere
to store all those bits. Which brings us to the
counterpart law for storage capacity, often called
Crider's Law. Right. Crider's Law describes that
same... Right. And there's this fascinating calculation
from Fremont Rider in 1945. He figured out that
the capacity of university libraries was doubling
roughly every 16 years. Just think about that.
16 years to double the physical space for books.
You're limited by land, by bricks, by mortar.
Compare that slow physical doubling to what happened
with digital storage. And to do that, we have
to start talking in these almost incomprehensible
units. Exabytes and zettabytes. An exabyte is
a billion gigabytes. A zettabyte is a thousand
exabytes. The numbers are just staggering. Let's
look at the stats from the sources to show the
explosion. In 1986, the world's total technological
capacity to store information was just 2 .6 exabytes.
And that's if it was optimally compressed. 2
.6 exabytes, that sounds like a lot, but what
does that actually mean on a per -person basis
back in 1986? It means that the entire world's
stored information was equivalent to less than
one single 730 megabyte CD -ROM per person. Wait,
less than one CD for every person on the planet?
That's everything? All government records, all
libraries, all business data? Everything. It
just shows you how information poor we were,
technologically speaking. Now, let's do the jump.
Fast forward just 21 years to 2007. World storage
capacity had exploded to 295 exatic. Okay, what's
the new per person equivalent? It's equivalent
to almost 61 CD -ROMs per person. Not per year,
per day. That's just an insane leap. Okay, what
about 2014? By 2014, the scale just defies any
normal physical comparison. It reached 5 zettabytes.
The sources offer this analogy. The informational
equivalent of 5 zettabytes is 4 ,500 stacks of
printed books, stretching from the Earth all
the way to the sun. 4 ,500 stacks of books from
here to the sun. I mean, at that point, the physical
world is just irrelevant as a measure. The information
has been completely dematerialized. That's the
profound realization. The digital shift wasn't
cragable. It was, as you said, a hostile takeover
of information storage. In the late 1980s, less
than 1 % of the world's stored information was
digital. By 2007, it was 94%. By 2014, over 99%.
The physical constraints, the atoms, were just
gone. And the computation speed ran in parallel
with this, right? Let's talk MIPS. Millions of
instructions per second. The growth there is
just as mind -bending. The capacity of human
-guided, general -purpose computers went from
about 3 times 10 to the 8 MIPS in 1986 to 6 .4
times 10 to the 12 MIPS in 2007. Okay, and this
is where we hit what I think is one of the most
critical and... In terms of raw operations per
second, yes. Vastly exceeded it. It's a staggering
moment in history. And it happened, you know,
more than a decade ago. The tools are now running
the race for us. And the storage is similar.
It's a similar story. Estimates put the storage
capacity of a single human brain at around one
terabyte, maybe a bit more. Given the five zettabytes
available in 2014, our global digital storage
now matches that individual capacity on a per
capita basis. we have effectively built an external
collective brain, both in terms of speed and
memory. And the beauty of Shannon's information
theory is that it wasn't just limited to computers.
It started to be applied to biology itself, treating
life as a form of data. Precisely. After DNA
sequencing was invented in the late 70s, genetic
code became just another data stream to be rendered
and manipulated. And you see the same exponential
growth there. The amount of sequence data in
GenBank, the public DNA database, has doubled
roughly every 18 months. The information age
isn't just about silicon chips. It's about applying
digital principles to all forms of knowledge,
including our own biology. OK, so the stage is
completely set. The transistor gives us the hardware.
Moore's law and Crater's law give us the scale.
But now, how did this massive new capacity actually
get out of the research labs and into the hands
of billions of people? It required that foundational
change, the conversion of everything from analog
to digital. And that conversion is the absolute
prerequisite for the world we live in now. As
we mentioned, it allows information to be copied
perfectly without any degradation. For most people,
their first real experience with this was in
the 1980s when CDs replaced vinyl records and
cassette tapes. That was the first time the public
got to experience the benefit of digital, quality
-perfect sound every time that you could easily
copy and share. So let's trace this journey to
ubiquity. The sources break it down into three
pretty distinct phases of public access. Let's
start with phase one, from roughly 1969 to 1989.
The rise of home computing. It's funny. This
phase actually began with a military project.
The public's first real introduction to the concept
of a network was when the first message was sent
over ARPANET in 1969. But for the average person,
the revolution didn't show up as a network. It
showed up as a box on their desk. Right. The
1970s brought the home computer. I mean, you
had to load programs from cassette tapes. The
interaction was all through a command line. But
that era was so formative. It was defined by
what's often called the 1977 Trinity, the Apple
II, the Commodore PE 2001, and the TRS -80. And
you cannot forget the Commodore 64. When that
came out in 1982, it hit a price point and a
usability level that achieved true mass market
penetration. It's often cited as the best -selling
single computer model of all time. I think the
sources say 17 million units sold through 1994.
It made computing accessible, even if it was
still mostly a hobby for enthusiasts. And the
adoption numbers from that time really reflect
that early niche status. The U .S. Census data
shows that in 1984, only 8 .2 % of American households
owned a PC. But here's the important detail,
that adoption was generational. If you looked
only at households with children, the ownership
rate was almost double, at 15 .3%. You can see
parents buying these machines for their kids,
for education, for games. They were seeding the
next generation of users. By the end of this
phase, in 1989, about 15 % of all U .S. households
had a PC. The machines were starting to get out
there, but the crucial piece, the connectivity,
just wasn't there yet for the public. Which brings
us right to phase two, 1989 to 2005. This is
the era of mainstreaming the Internet. This is
Web 1 .0. This is when the network finally breaks
out of its academic and government silo. And
you really have to give tremendous credit to
Tim Berners -Lee. He invented the World Wide
Web in 1989, and it became publicly accessible
in 1991. It created a standardized way for anyone
with a computer to connect and share information.
But the early web was still pretty clunky for
the average person, right? Mostly text -based,
hard to navigate. What was the thing that unlocked
its mass appeal? Usability. It was all about
usability. And the breakthrough was the Mosaic
browser in 1993, created by Marc Andreessen and
Eric Bina. It was the first browser that could
display images in line with the text. It sounds
so simple now, but it was revolutionary. It gave
the web a visual, intuitive feel, and the commercial
world jumped on it instantly. By 1994, Stanford
Federal Credit Union was the first bank to offer
online internet banking. The digital economy
was being born. But we have to pause here and
really emphasize the connectivity hurdle of the
90s. The sources remind us that just getting
online was still a really complicated and often
painful experience. Oh, it was excruciating by
today's standards. You had to configure modems.
You had to deal with service providers like AOL
or CompuServe. And most critically, you were
on dial -up. Anyone over a certain age remembers
that sound, that screeching handshake of the
modem connecting. And it tied up your only phone
line. And the speed was just a crawl, topping
out around 56 kilobits per second. It severely
limited what you could do. But even with those
hurdles, adoption was incredibly fast. By 1999,
nearly half of all Americans were using the Internet
regularly. By 2000, a majority of U .S. households
had a PC, and a year later, a majority had Internet
access. And this is when the revolution started
to become truly global. Which sets the stage
perfectly for Phase 3. 2005 to the present. This
is the age of ubiquity and mobile. This is Web
2 .0. This phase is all about constant access
everywhere. The metrics for this final phase
are just, they're colossal. The global internet
population hits 1 billion in late 2005. By 2012,
that number doubles to over 2 billion people.
And mobile just takes over everything. By the
end of the 2000s, 3 billion people worldwide
were using cell phones. But the launch of the
smartphone was the real catalyst. It put a powerful,
connected computer in everyone's pocket. By 2013,
a majority of Americans owned a smartphone. Let's
bring those numbers right up to today for the
listener because it really drives the point home.
As of 2023, the vast majority of humanity is
participating. There are 6 .31 billion cell phone
subscribers. That's 78 percent of the entire
world population. And 5 .4 billion Internet users,
which is 67 percent of the world. The information
age is now, without a doubt, a planetary phenomenon.
And the underlying infrastructure had to completely
transform to handle that kind of volume. We saw
digital TV replace analog broadcasting. Broadband
became the standard connection in homes. And
all of the speed and capacity enabled the next
wave of service. like cloud computing, which
really hit the mainstream in the early 2010s.
But we have to talk about the unsung hero that
allowed all of this to happen. We talk about
chips and computers, but the true circulatory
system of the modern internet is optical networking,
fiber optic cable. Okay, expand on that. Why
was harnessing light for data so critical? Why
couldn't we just keep using copper cables? Because
copper has immense resistance over long distances.
The electrical signal degrades, it picks up noise,
and there's a hard limit to how much data you
can push through it. Light... Traveling through
these incredibly pure glass fibers loses very
little signal and can carry exponentially more
information. But the real magic was the engineering
that let us multiply the light within a single
fiber. It's a technology called dense wavelength
division multiplexing, or DWDM. All right, break
down DWDM in simple terms for us. Think of a
single fiber optic cable as a long garden hose.
Yeah. With copper, you can only send one stream
of water through it. DWDM is a technology that's
like being able to send hundreds of different
colors of water, red, green, blue, yellow, all
through that same hose at the same time without
them mixing. Each color or wavelength of light
is a separate data channel. This massive multiplication
of capacity is why a tiny fiber optic cable can
carry more data than a copper cable as thick
as your arm. And the results of that technology
are what enable our modern world. Absolutely.
By 2018, these optical networks were hitting
record data transfer rates, 30 .4 terabits per
second over a single pair of fibers. That's enough
data to stream 1 .2 million 4K HD videos simultaneously.
That is the speed, that is the capacity that
underpins global virtual media, e -commerce,
and the cloud services billions of us use every
single day. So we've traced the tech, we've traced
the hardware. But the most profound impact, really,
is what all this did to society and to the economy.
This revolution didn't just give us faster computers.
It completely changed the conceptual model of
what has value in the world. It absolutely redefines
the concept of value. And we can go back to Norbert
Wiener, who wrote in his 1948 book, Cybernetics,
that information is information, not matter or
energy. And it's a profound statement. He was
proposing that information is a third constituent
part of the universe, right alongside matter
and energy. So if that's the theoretical model,
then the core theory of the information revolution
is that information's role fundamentally shifts.
It becomes both a factor of production like capital,
labor, and land, and maybe more importantly,
a commercial product in its own right. That's
the economic paradigm shift. Before, information
might help you produce something like a recipe
helps a baker. Now, the information is the valuable
thing. a software license, a stream of market
data, a patented genetic sequence. This idea
led the economist Fritz Machlup, as early as
1962, to talk about the knowledge industry, claiming
it already made up 29 % of the US GNP. He was
seeing the beginning of a whole new information
sector in the economy. Okay, let's tackle the
most visible, and I think for many people, the
most painful consequence of this shift, the great
labor transformation. What happened to jobs,
income, and job security? The information age
has created enormous wealth and incredible winners,
but it has also put tremendous strain on traditional
labor models across the globe. And you can see
the strain in two parallel forces. The first
is just straight up automation displacement.
Any task that involves routine calculation, repetitive
decision making or predictable physical movements.
It's vulnerable. Computers and robots just do
those jobs faster, cheaper and with perfect accuracy.
So jobs like data entry clerks, assembly line
workers, even some mid -level management roles
that are really just about routing information.
Those workers are forced to find something new
to do. Which creates huge pressure. It creates
immense pressure. The market starts demanding
that workers shift into what the sources call
indispensable professions. These are roles that
require things machines aren't good at yet. Creativity,
complex human interaction, high level engineering,
scientific discovery, subjective consulting.
They're high skill, high wage roles that can
compete on a global stage. The brutal logic is
if you're not indispensable, you're replaceable.
And compounding that automation pressure is the
second. force outsourcing because of that global
fiber optic network we just talked about. A programmer
or an accountant in a developed country is now
competing directly with a skilled professional
in India or Eastern Europe. Exactly. That digital
infrastructure. dramatically increases the global
supply of labor for many of these traditionally
middle class jobs. And the result in developed
nations is either wage stagnation for those who
remain in those jobs, or they're forced to settle
for low skill, low wage service jobs that can't
be easily automated or outsourced. But the other
side of that coin is that the same infrastructure
is a massive benefit for developing economies.
It's a path to higher wages for them. It is a
phenomenal engine of opportunity for the developing
world. The Internet allows workers there to plug
directly into markets they were completely excluded
from before. And that translates directly into
higher wages and better opportunities, lifting
millions of people out of poverty by giving them
access to the global economy. Let's go back to
that U .S. manufacturing example from the sources,
because it just perfectly encapsulates this tension
between creating value and employing people.
The data is just shocking. Between 1972 and 2010,
the number of manufacturing jobs in the United
States fell by 6 million, a massive drop. But,
and this is the critical part, during that exact
same period, the value of U .S. manufacturing,
the actual output, rose by 270%. So that's the
core paradox. We're producing way more value
with far fewer people. So where is all that new
wealth going? Why isn't it translating into higher
wages or more security for the workers who are
left? Well, the sources suggest the value is
accruing primarily to the owners of the information
capital, the owners of the robots, the proprietary
software, the patents, the algorithms that drive
that productivity. Industry has become more information
intensive and less labor intensive. The value
of the technology itself goes up while the relative
value of traditional human. labor goes down.
This changes the entire model of how you even
launch a successful company. It changes the role
of capital itself. This is where the lean startup
model comes from. Yeah. Contrast the old economic
model where to succeed, you needed huge upfront
investments in physical and human capital, you
know, building the giant factory, hiring thousands
of workers, getting massive loans. Contrast that
with a digital paradigm. It's now possible for
a small, inexperienced group with almost no initial
capital like Mark Zuckerberg in his dorm room
to create something that achieves planetary scale
and success almost overnight. The required capital
isn't physical anymore. It's intellectual and
informational. The leverage you get from software
that can be copied for free and distributed globally,
it just fundamentally changes the game. It proves
that in this new age, controlling the unique
information asset is far more valuable than controlling
the physical means of production. So let's wrap
this up by looking at the broader societal and
cultural impact. Beyond the economy, what does
this constant ubiquitous access to information
mean for us as human beings? Well, there are
two very different views on this. The sociologist
Manuel Castells sees this as a profound transformation
leading to a new society in the making. He talks
about the autonomy of culture from its material
basis. Because information flows so freely, culture
and knowledge can now evolve and spread independent
of geography or traditional economic power. That
sounds pretty optimistic. It suggests we're building
a smarter, more connected, more knowledgeable
global society because all of human knowledge
is at our fingertips. That's the potential. And
it's also the paradox. Because while Castells
sees that possibility, others, like the writer
Thomas Chatterton Williams, offer a really strong
counterpoint. He warns about the very real dangers
of anti -intellectualism in the information age.
The sheer volume of information is just overwhelming.
And a lot of it is superficial, irrelevant, or
just plain wrong. So their argument is that the
speed and volume lead to a sort of shallow engagement
with knowledge. Exactly. The culture starts to
value speed over expertise. Why would you read
a dense, difficult book when you can watch a
two -minute video summary? The greatest thoughts
and works in human history are all available
instantly. Yet there's this societal tendency
to dismiss deep expertise and critical thinking
as sort of pointless in favor of quick, easily
digestible content. We're basically drowning
in information while starving for wisdom. This
has been an incredible deep dive covering seven
decades of just radical world altering change.
We started with that spark in 1947, the transistor.
We watched it ignite the exponential engines
of Moore's and Crider's laws. We charted its
incredibly swift journey through those three
phases of adoption from military networks to
the global mobile network we have now, all running
on the unbelievable speed of light through fiber
optics. And we've seen how it redefined information
as the core economic asset, causing this ongoing
massive structural change to labor and capital.
all over the world. The single defining characteristic
when you look at it all is just the speed. The
Neolithic revolution, which gave us agriculture
that took thousands of years to spread across
the globe. The industrial age took hundreds of
years. The information age achieved planetary
saturation in just a few decades. That pace of
change is completely unparalleled and it presents
challenges that, frankly, humanity has never
faced before. Which brings us back to our final
provocative thought for you, the listener, to
take away from all this. We talked about that
cognitive benchmark, how by 2007 our computers
had already surpassed the collective processing
power of every human brain on Earth, and how
our global digital storage capacity now matches
the storage capacity of an individual human brain
on a per -person basis. So what are the philosophical
and practical implications for human relevance
when our own tools can not only remember more
than us, but can compute faster? than our collective
minds. The sources suggest the next great challenge
of this age is shifting our focus away from just
acquiring raw information machines do that better
than we ever could to generating actionable knowledge.
The future you could argue belongs to the age
of algorithms. Algorithms designed specifically
to convert this overwhelming universe of existing
information into meaningful, useful actions.
The question then becomes, how do we make sure
that human wisdom is guiding the machine's incredible
processing speed? That is the ultimate question
of relevance moving forward. Thank you for joining
us for this deep dive into the structure and
history of the information age. We hope you walk
away better equipped to navigate the dense sea
of bits that we all swim in every day. Continue
your own deep dive and we'll see you next time.