Right now, without even realizing it, your brain
is actively hallucinating parallel universes.
Just to help you make sense of this sentence.
Yeah, it's completely invisible to us. We tend
to treat human logic like a calculator, you know?
Like, we just add up facts and spit out conclusions.
Right, but behind the scenes, your mind is constantly
taking entirely unrelated realities, stripping
them for parts, and... Well, smashing them together.
To create mutant ideas. And you don't even notice
you're doing it. No, not at all. I mean, we treat
a sudden realization or the understanding of
a complex metaphor like a magic trick. The rabbit
just appears out of the hat. Precisely. And we
rarely stop to ask how that rabbit was actually
engineered in the dark. Well, today we are going
into the dark. Welcome to the deep dive. For
this one, we are exploring a single beautifully
dense source, a comprehensive Wikipedia article
on a cognitive linguistics theory known as conceptual
blending. It's a fascinating topic. Our mission
today is to pull back the curtain on that invisible
machinery. We're going to map out the hidden
architecture of human creativity and reasoning,
and hopefully give you a completely new way to
look at your own mind. And what's truly fascinating
here is that we aren't just examining a neat
little psychological quirk. We are looking at
the foundational processes of how you think.
How human beings communicate. Exactly. And honestly,
how we build entire civilizations. This theory
attempts to decode the underlying software of
everyday thought. Okay, let's unpack this. Our
source refers to this theory as conceptual blending,
but also conceptual integration or view application.
It was formally developed by Gilles Fauconnier
and Mark Turner back in 1993. Yes, though Fourconier
and Turner explicitly point back to a 1964 book.
Oh, right, by Arthur Koestler. Right, The Act
of Creation. Koestler observed a common pattern
across art, science, and humor. He called it
the bisociation of matrices. Which is quite a
mouthful. It is. But he essentially argued that
the human mind has this unique ability to take
two completely unrelated frameworks, or matrices,
and suddenly snap them together to create something
entirely novel. I have to admit, by association
of matrices, sounds like an incredibly dry math
concept. When I was reading the source, the analogy
I kept coming back to was mental genetic engineering.
Oh, I like that. is conceptual blending, basically
taking the DNA, like the specific traits from
completely different ideas, and subconsciously
splicing them together in a lab to create a brand
new mutant idea, one that somehow survives and
makes sense to us. That is a highly accurate
way to look at it. And the crucial word you use
there is subconsciously. Because we don't feel
it happening. Right. Foucault and Turner argued
that this splicing process isn't reserved for
brilliant inventors or poets. It is absolutely
ubiquitous. You were doing it constantly, effortlessly,
every single time you speak. Give me an example.
Well, think about a common everyday phrase, like
telling someone they are digging their own grave
when they make a really bad financial decision.
Right, because I'm not literally picturing my
friend holding a shovel in a cemetery. No, of
course not. I'm taking the concept of financial
ruin, and I'm splicing it with the concept of
physical death and burial, and my brain just
instantly understands the severity of what's
happening. Without actually believing your friend
is a gravedigger. Exactly. You splice the DNA
of those two realities together to understand
a complex concept. Focconi and Turner view this
theory as an attempt to create a unitary account
of how cultural ideas are transmitted. So it's
kind of like memetics. It's very much akin to
memetics, yeah. How ideas spread, mutate, and
evolve across human history. Our sources even
mentioned that researchers like George Lakoff
and Rafael Núñez used this exact theory to argue
that the splicing is literally where mathematics
comes from. Yes, the cognitive science of mathematics.
Now that understanding math isn't just about
recognizing universal truths floating in space.
It actually requires the mastery of these extensive
metaphorical blends. Precisely. Mathematics isn't
just out there in the ether waiting to be discovered.
According to this view, it is built by human
minds taking basic grounded concepts like physical
objects. Yeah, physical objects or grouping things
together in piles and then blending them over
and over again into increasingly abstract mental
spaces. I want to take this from the abstract
down into a concrete real -world application
because I want you, the listener, to actually
feel your brain doing this mental genetic splicing
in real time. It's one thing to talk about it,
but experiencing it is different. Right. To do
that, we are going to use Arthur Koestler's famous
riddle of the Buddhist monk. It's heavily featured
in the sources. Oh, it's one of the classic examples
used to demonstrate a blend. It perfectly forces
your brain to build the machinery we're talking
about. OK, so here is the middle. Picture this.
A Buddhist monk begins at dawn one day walking
up a mountain path. He reaches the top at sunset.
Okay. He meditates at the top for several days.
Then, at dawn on a new day, he begins to walk
back down that exact same mountain path, reaching
the foot of the mountain at sunset. And here
are the constraints for you listening. You can
make absolutely no assumptions about his starting
or stopping or about his pace during either trip.
Right, you could sprint for an hour, he could
crawl. He could take a three -hour nap on a rock.
We don't know. The riddle is this. prove that
there is a single place on the path that the
monk occupies at the exact same hour of the day
on both of those separate journeys. It's a tricky
one. When I first read this, my brain immediately
tried to draw a graph. I was trying to calculate
velocity and time, and it was incredibly frustrating.
I'm sure. The variables of his speed and his
breaks make a mathematical approach feel completely
impossible. It does feel impossible if you rely
strictly on monotonic linear logic. but your
brain has a shortcut. How did you find it? Well,
the only way to solve it easily is to abandon
reality. You have to imagine a completely fictional,
improbable scenario. Go on. You have to take
day one and day two and superimpose them. You
just picture two separate monks. One is at the
bottom of the mountain walking up. The other
is at the top of the mountain walking down. They
both start at dawn on the exact same day. And
what happens in your mind's eye when you watch
that play out? Oh, I see it immediately. If they
are on the exact same path, one going up and
one going down on the same day, they physically
have to collide at some point. They will cross
paths. And where they meet, that's the proof.
That is the spot on the path they occupy at the
exact same hour. It is so elegantly simple once
you see it. It is. But what really strikes me
here isn't the math. It's that To solve a completely
factual, logical problem, my brain naturally
generated a completely fictional world. You built
a new reality. We preserved the time of day.
We preserved the physical path. But we literally
cloned the monk. We hallucinated a parallel universe
with two monks just to make the logic work. And
you did it instantly. You didn't consciously
sit down and instruct your brain, OK, let us
now construct a parallel universe. You just blended
the scenarios. Right. So now that we've experienced
a firsthand, we need to dissect how the brain
just pulled it off. Yeah, if I picture my working
memory like an animation studio... What are the
actual layers I'm putting together to make that
final scene? The source is called these mental
spaces. Yes. Think of mental spaces as transparent
layers of animation cells being stacked on top
of each other. Okay, transparent layers. They
are small conceptual containers generated right
there in your working memory, but they pull knowledge
from your vast long -term memory. In a basic
integration network, there are at least four
of these interconnected transparent layers stacked
up. Four separate mental containers just to solve
the monk riddle. Let's reason through them. First,
you have the generic space. Right. The generic
space captures only the common structure shared
by your inputs. It's the barest of bones. So
no details. Exactly. In the riddle, the generic
space contains a mountain path, the abstract
concept of a day passing, and a person moving
along that path. Nothing specific. Just the rules
of the world. Then you need the actual material.
That's the two input spaces. Yeah. So input space
one is my first animation cell. Day one, the
monk walking up the mountain. Yes. Input space
two is my second cell. Day two, the monk walking
down the mountain. Exactly. And then the integration
happens in the fourth container, which is the
blended space. The final stack. This is where
all the transparent cells stack together. The
blended space takes the general structure from
the generic space and through a process called
selective projection. It pulls specific elements
from input one and input two. Wait, selective
projection. That means I'm not just mashing everything
together thoughtlessly. Right. Notice the word
selective. We keep the mountain path as one single
element. We keep the time of day as one single
element. We don't have two mountains or a 48
-hour day. Oh, I see. But we project the monk
twice. Because the motion's direction is different
in each input, your brain selectively decides
to create two separate monks in the blended space
to represent those two directions. But how does
the new reality actually start moving? I've got
my animation cells stacked up. Two monks, one
path, one day. How do the monks suddenly know
they're supposed to walk toward each other and
meet? That's where the three operations of blending
come in. This results in what the theory calls
an emergent structure. An emergent structure.
Yes. This is a structure or a realization that
did not exist in either of the original inputs.
So the meaning of the monks is the emergent structure.
Exactly. The first operation to get there is
composition. This is simply the act of bringing
the elements together onto the same cell. You
compose the scene by putting both monks on the
same path on the same day. Setting the stage.
Got it. What's next? Second is completion. This
is where your brain reaches into its long -term
memory and passes on additional background meaning
to the blend. Like the laws of physics. Exactly.
Your brain already knows how physical space works.
It knows that two solid objects moving toward
each other on a single path will eventually collide.
You don't have to relearn physics every time
you think. Your brain automatically completes
the logic of the scene. And the third operation.
Elaboration. This is the dynamic running of the
blend. You press play on the animation. Ah, okay.
You watch the two monks walk in your mind's eye
and you watch them meet. The meeting only exists
in the blend. but it solves your real -world
problem. It's incredible when you break it down
into mechanics like that. But the sources are
quick to point out that this monk riddle is just
one specific type of blend. The theory categorizes
the vast chaos of human thought into four main
types of integration network. Oh yes, and moving
through these four networks really shows how
scalable this theory is. The Buddhist monk riddle
we just did is an example of a mirror network.
Because the two inputs mirror each other. Because
there is a shared organizing frame present in
all the mental spaces. In all the spaces, you
have a man making a journey on a mountain path.
The core activity mirrors itself. But not all
blends are that symmetrical. Right. The sources
list three others. Let's try to ground these.
The most basic one is the simplex network. A
simplex network is essentially just dropping
values into a predefined frame. Like filling
in a blank. Basically, if I say Paul is the father
of Sally, You have a frame for family roles,
a father and a daughter. That's one input. The
other input is just the specific people, Paul
and Sally. And you blend them together? And you
instantly understand their relationship. No parallel
universes required. Okay, simple enough. Then
there's the single scope network. The sources
say this is where you have two totally different
frames, but only one gets projected into the
blend to organize it. A perfect example of a
single -scope blend is how you understand a computer
desktop. Oh, interesting. You have an input space
for a physical office, environment desks, folders,
trash cans. You have another input space for
digital computer code and file directories. Oh,
wow. I see it. We don't organize our screens
by reading raw code. We project the organizing
frame of the physical office onto the digital
space. Yes. We literally drag a digital file
into a digital trash can. It's two completely
different realities, but the physical office
frame organizes the blended space. Precisely.
And that brings us to the most complex one, the
double -scope network. This is where you pull
parts of the organizing frames from both inputs
to create something really wild, often resulting
in frame clashes. This would be like a computer
virus, right? Yes. You have the biological frame
of a virus, an organism that infects, replicates,
and destroys a host, and you have the computer
frame of software code. Right. You pull the replication
and infection from biology and you pull the digital
environment from the computer and you create
a mutant idea. malicious code that acts like
a biological pathogen. Exactly. Double -scope
networks are the engine of high -level human
creativity. And navigating all these different
networks, whether it's a computer virus or the
monk riddle, requires us to manipulate what the
theory calls vital relations. Okay, I really
want to push back on this idea of vital relations
because it seems like the cheat code that makes
the whole theory work. In the monk riddle, time
was completely manipulated. We compressed two
separate days into a single day so the monk could
walk up and down simultaneously. But if we are
constantly blending realities, we must be manipulating
other things besides just time. Right. What other
rules of reality are we subconsciously bending
to our will? Well, time compression is the most
obvious, but the sources list several vital relations
we manipulate constantly. We manipulate cause
effect. We manipulate change, how an entity transforms
over time. We manipulate space, compressing vast
geographic distances so we can compare things
side by side in our minds. Like saying New York
is breathing down London's neck in a financial
context. We compress an ocean of space to create
a physical race. Yes. Perfect example. We also
manipulate identity and role. Think about when
someone says, if I were you, I would quit that
job. Right. You are blending your identity with
their role. You maintain your own decision -making
logic, but you project it into their life circumstances.
Oh, I do that all the time. We all do. These
vital relations are the threads that allow us
to stitch different mental spaces together without
our brains glitching out. And speaking of glitching
out, if we've managed to map out human thought
so systematically, literally breaking it down
into four interconnected mental containers, three
operations, and specific vital relations, it
raises a massive obvious question. I think I
know where you're going with this. Here's where
it gets really interesting. If we have the blueprint,
why can't we just code this into a computer?
The artificial intelligence question. If conceptual
blending is truly the architecture of thought,
can we build an artificial brain with the same
architecture? Our sources actually dive deep
into this. The attempt to model this mathematically
isn't new at all. Even before conceptual blending
was fully formalized by Fauconnier and Turner,
an early computational model of a closely related
process called view application was implemented
in the 1980s. Yes, by a researcher named Jeff
Schrager. Right, at Carnegie Mellon University.
He applied it to causal reasoning about complex
devices. But modern AI has struggled profoundly
with this. They are trying to build what sources
call non -monotonic reasoning into AI systems
to handle complex human -like concept combinations.
Okay, let's pause there because non -monotonic
reasoning sounds incredibly dense. From my understanding,
normal machine logic is monotonic. It builds
up in a straight, irreversible line. Yes. If
A is true and B is true, they just add together.
But human logic is non -monotonic, meaning we
can learn a new fact that completely contradicts
and erases an old conclusion. We can rewrite
the rules on the fly. That is a brilliant way
to explain it. In monotonic logic, adding new
facts only builds up a conclusion. In non -monotonic
logic, a new piece of information might force
you to completely withdraw a previous assumption.
And the classic example cited in our sources
for this computational hurdle in AI is the famous
pet fish problem. I love the pet fish problem
because it perfectly illustrates the gap between
human blending and machine logic. It really does.
If you tell an AI about a pet, it activates a
frame. Pets are furry, they live in houses, they're
affectionate, they seek attention like a dog
or a cat. Right. And if you tell that same AI
about a fish, it activates a completely different
frame. Fish live in the ocean. They are scaly.
They are cold -blooded. They're often caught
for food, like a salmon or a shark. But if you
say the words pet fish together, a human being
instantly creates a blended space. We don't picture
a furry, affectionate salmon living on our living
room couch. And we don't picture a cuddly great
white shark. No, we don't. We instantly generate
an emergent structure. A small goldfish living
in a glass bowl. And we effortlessly discard
the irrelevant parts of the pet frame. the fur,
the cuddling, and we discard the irrelevant parts
of the fish frame, the ocean, the food aspect.
We selectively project only what works. But an
AI naturally wants to strictly add the two frames
together. It wants monotonic logic. A pet is
furry plus a fish is a fish equals a furry fit.
Exactly. Teaching a machine to selectively project
and create an emergent structure that is completely
different from its original inputs is computationally
agonizing. It requires immense creativity frameworks.
And honestly, the fact that a supercomputer crashes
trying to imagine a goldfish in a ball brings
up a glaring issue with this whole theory. It
acts as a perfect transition into the philosophical
pushbacks. Yes, the critiques. If conceptual
blending is so hard to program, is it actually
a rigid predictive science, or is it merely a
descriptive framework? Let's bring in the critics,
because they have a lot to say. They certainly
do. The main skepticism comes from Raymond W.
Gibbs Jr., who published a heavy critique in
2000. Gibbs essentially points out a major flaw
that you, the listener, might already be sensing.
The theory lacks testable hypotheses. Which is
a big problem. If a psychological theory is going
to be treated as hard science, it needs to be
able to predict behavior. Gibbs argued that blending
theory is really just a framework. It's a way
of describing things after the fact, not a single
testable theory that predicts what someone will
think next. The analogy that came to mind when
I read Gibbs's critique was baking a cake. How
so? Gibbs is essentially arguing that inferring
how a mental process works just by looking at
the final product is deeply flawed. It's like
looking at a fully baked chocolate cake and claiming
you know exactly, with 100 % certainty, the exact
order the baker added the eggs, the flour, and
the sugar. That's a great way to put it. We can
look at the final blend in your head, the goldfish
or the monk, but we can't actually prove your
brain used four separate distinct mental containers
to get there. It's a devastating critique. We
can guess the recipe, but we don't really know
what happened in the bowl. Gibbs even suggested
that other linguistic theories might be equally
effective at explaining these cognitive phenomena
without requiring this incredibly specific architecture
of mental spaces. And I want to jump on another
criticism here from David Ritchie in 2004, who
argued against the unnecessary complexity of
the theory. Right, the Occam's razor approach.
Exactly. Ritchie brings Occam's razor to the
table. He asks, does every single metaphor we
use really require this massive invisible machinery?
Think back to our earlier example of digging
your own grave or just basic trash talk. Yeah.
Are we really generating a generic space, two
input spaces and a blended space running three
distinct operations? and manipulating vital relations
just to understand a simple insult. Ritchie argues
that it is highly possible we are overcomplicating
what might be a much simpler, faster cognitive
process. Even with the Buddhist monk riddle,
Ritchie argues there are alternative, simpler
interpretations for how human beings solve it
without needing the complex mirror network model.
But what I find most telling in all of our sources
is the philosophical boundary drawn by Mark Turner
himself, one of the literal creators of the theory.
Yes. In his book, The Literary Mind, Turner makes
a really fascinating admission that seems to
agree with the critics on some level. He does.
Turner states that conceptual blending is undoubtedly
a fundamental instrument of the everyday mind.
But he clarifies that the insights obtained from
it, the metaphors, the solutions, are the products
of creative thinking. The products. Yes, and
this is the key limitation. He admits that conceptual
blending theory is not in itself a complete theory
of creativity. Because it can't explain inspiration.
Turner admits that blending provides the terminology
for describing how we combine realities, but
it has absolutely nothing to say about where
the inputs to a blend originate in the first
place. It explains the mechanics of the mashup.
It explains how the DNA is spliced. but it doesn't
explain where the DNA came from. So what does
this all mean for us? We've journeyed from the
spark of an idea through the bisociation of matrices.
We have. We've walked up and down the mountain
with our cloned Buddhist monk. We've watched
artificial intelligence struggle to understand
a goldfish. And we've waded into the philosophical
critiques of whether this is hard science or
just a really good metaphor for thought. It means
that whether it actually takes four distinct
mental animation cells, or whether it's a much
simpler process as Occam's razor suggests, the
undeniable truth is that your brain is constantly
performing high -level conceptual gymnastics.
Every single day. You are continuously pulling
frames from your memory, selectively projecting
elements and running dynamic simulations just
to make sense of a simple conversation or solve
a daily problem at work. You are quite literally
a walking talking engine of conceptual integration.
But I would like to leave you with a final thought
to mull over. Lay it on us. If conceptual blending
only provides the terminology for how we mix
and match existing inputs, if it only explains
the recipe but not the ingredients, then where
does the very first spark of a truly original
idea actually come from before it is ever blended?
What generates the input before the input? Wow.
That is a deeply haunting question to end on.
Where does the original thought come from? Well,
thank you so much for joining us on this deep
dive. As you go about your day today, pay attention
to your own thoughts. Notice the hidden blends
in your conversations, the metaphors you use
without thinking, and the fictional realities
you construct just to navigate the factual world.
Keep questioning the invisible machinery. We'll
catch you next time.