WEBVTT - Ep68 "What if our brains worked a trillion times faster?"

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<v Speaker 1>Why do we find movies so compelling given that they're

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<v Speaker 1>just a series of photographs flash rapidly. What does this

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<v Speaker 1>tell us about the slow speed of human brains? What

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<v Speaker 1>percentage of stock market trades are taken care of by

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<v Speaker 1>algorithms nowadays at timescales.

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<v Speaker 2>That humans could not even conceive of.

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<v Speaker 1>And what is it like to have the speed and

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<v Speaker 1>power of a computer and be dealing with slow humans.

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<v Speaker 1>Welcome to Inner Cosmos with me, David Eagleman. I'm a

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<v Speaker 1>neuroscientist and in these episodes we sail deeply into our

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<v Speaker 1>three pound universe to understand some of the most surprising

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<v Speaker 1>aspects of our lives. Today's episode is about speed, the

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<v Speaker 1>speed at which we humans operate and the speed at

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<v Speaker 1>which our machines operate, and the future of this as

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<v Speaker 1>the divergence grows even larger.

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<v Speaker 2>So let's start with this.

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<v Speaker 1>Imagine an extraterrestrial planet where they have an active society.

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<v Speaker 1>These aliens have politics and division of labor, and philosophers

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<v Speaker 1>and actors and athletes and artists, everything that makes up

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<v Speaker 1>an active society. Okay, So, now imagine a second planet,

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<v Speaker 1>Planet B. We land on this second planet in the

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<v Speaker 1>near future, and we discover nothing like a society there. Instead,

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<v Speaker 1>there are just things like trees, like these very old

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<v Speaker 1>growths that don't really do much of anything. And we

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<v Speaker 1>the astronauts, we stay there for a month, we take

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<v Speaker 1>a lot of measurements, and finally we blast off when

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<v Speaker 1>we go home. So two planets, one with an active

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<v Speaker 1>society and the other with nothing but tree like things.

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<v Speaker 1>Now imagine that these two descriptions are of the same planet.

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<v Speaker 1>What we have stumbled on is a society of creatures

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<v Speaker 1>that operate at a very different time scale from us.

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<v Speaker 1>They move so slowly that we just can't see it.

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<v Speaker 1>They have an active society, it just operates a trillion

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<v Speaker 1>times slower than ours. And the question is, would we

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<v Speaker 1>ever even notice that these tree people have a society

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<v Speaker 1>happening in what we would think of as super slow motion.

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<v Speaker 1>A conversation over a cup of coffee for them takes

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<v Speaker 1>eons for us. So would we ever decode their language?

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<v Speaker 1>Would we ever even have an opportunity to discover that

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<v Speaker 1>there's a whole world going on there, but at a

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<v Speaker 1>different temporal scale. So that's what today's episode is about.

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<v Speaker 1>Hidden landscapes, parts of the time domain that are totally

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<v Speaker 1>invisible to us. Now you've heard me talk in other

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<v Speaker 1>episodes about all the information in the world that we

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<v Speaker 1>just don't see. So is one example. We only see

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<v Speaker 1>a small fraction of the light that is out there,

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<v Speaker 1>and that little slice we call visible light. That's what

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<v Speaker 1>we think of as red, orange, yellow, green, blue, indigo, violet.

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<v Speaker 1>And it seems like that's all the light that's out there.

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<v Speaker 1>You open your eyes, you see reds and greens and

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<v Speaker 1>blues and golds, and you think, okay, that's everything. And

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<v Speaker 1>so it came as a surprise when scientists eventually realized

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<v Speaker 1>that all these other signals that had been detected, things

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<v Speaker 1>that are totally invisible to us, like infrared light or

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<v Speaker 1>radio waves or X rays or ultraviolet or microwaves, all

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<v Speaker 1>of these are light. They're exactly the same thing, is

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<v Speaker 1>what we call visible light. It's just that we don't

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<v Speaker 1>have the receptors in our eyes to pick up on them,

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<v Speaker 1>and so they're totally invisible to us. And it turns

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<v Speaker 1>out that what we call visible light is a very

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<v Speaker 1>tiny part of the light spectrum. It's less than a

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<v Speaker 1>ten trillionth of it. And once we understood this, we

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<v Speaker 1>started to build technologies to burrow into those other parts

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<v Speaker 1>of the spectrum. For example, we make little machines that

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<v Speaker 1>sit in the dashboards of our cars, and these see

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<v Speaker 1>in exactly the frequency that we call radio waves, and

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<v Speaker 1>so we can transmit information in that frequency. Or we

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<v Speaker 1>build night vision security cameras which see in the infrared range,

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<v Speaker 1>so that we can detect in that frequency outside of

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<v Speaker 1>what we can naturally see. And we build X ray

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<v Speaker 1>machines and telescope dishes, and these all pick up on

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<v Speaker 1>other frequencies that are invisible to us. We build all

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<v Speaker 1>kinds of devices to see what we can't naturally see,

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<v Speaker 1>and this has been the gen of scientific development over

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<v Speaker 1>the last few hundred years. It's the understanding that the

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<v Speaker 1>reality we inhabit is actually just a small fraction of

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<v Speaker 1>what is out there, and there are many other things

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<v Speaker 1>that can be taken advantage of. So we're very used

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<v Speaker 1>to communicating in landscapes that are outside our biology. Our

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<v Speaker 1>biology allows us to detect something like visible light, and

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<v Speaker 1>then we figure out from there that there are other

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<v Speaker 1>flavors of light that are beyond our biology, and we.

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<v Speaker 2>Take advantage of those.

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<v Speaker 1>So I want to use this as an analogy and

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<v Speaker 1>an inroad for us thinking about somewhere else that we

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<v Speaker 1>do this, and that is in the domain of time.

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<v Speaker 1>The question is can we use different ranges of time

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<v Speaker 1>to build technologies, perhaps a range of time that is

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<v Speaker 1>essentially invisible in our normal perception. When I was a tea,

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<v Speaker 1>I visited MIT and I met with Harold Edgerton who

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<v Speaker 1>was known as Doc Edgerton. And he was a pioneer

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<v Speaker 1>in high speed photography. And what he would do is

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<v Speaker 1>capture moments that were otherwise totally invisible to us. So

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<v Speaker 1>he froze ultrafast events using a quick strobe light and

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<v Speaker 1>ultra high speed photography. One of his most famous photographs

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<v Speaker 1>was taken in the nineteen sixties and you may have

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<v Speaker 1>seen this. It shows a bullet piercing an apple. The

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<v Speaker 1>image captures the exact moment of impact with the apple

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<v Speaker 1>exploding into fragments, and the exposure time for images like

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<v Speaker 1>this it was less than a microsecond. Another one of

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<v Speaker 1>his iconic images is the milk drop coronet that shows

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<v Speaker 1>a drop of milk hitting a surface and forming this

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<v Speaker 1>crown like splash, and the detail in this splash, frozen

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<v Speaker 1>in time, gave all kinds of insights into flu with

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<v Speaker 1>dynamics and surface tension. So the temporal resolution of these

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<v Speaker 1>photos allowed everyone to study and to appreciate the beauty

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<v Speaker 1>and the complexity of fast phenomenon. So he could freeze

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<v Speaker 1>the motion of bullets in flight or splashing milk drops,

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<v Speaker 1>and these images revealed details that were previously hidden to

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<v Speaker 1>us due to the limitations of our very slow perception.

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<v Speaker 1>And he also did this not just with still shots,

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<v Speaker 1>but a series of still shots, so you get a

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<v Speaker 1>little time lapse film. And in this way he could

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<v Speaker 1>expand super brief events into viewable sequences. This was great

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<v Speaker 1>for science and for art, and also for military applications

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<v Speaker 1>like studying the behavior of bombs. So with these techniques

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<v Speaker 1>he led us into new time domains which we suspected

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<v Speaker 1>might exist, but which no human had ever actually seen.

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<v Speaker 1>So he opened a window into a world of fleeting moments,

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<v Speaker 1>capturing events that occur too quickly for our eyes to see,

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<v Speaker 1>and reveling in a hidden beauty that we didn't even

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<v Speaker 1>have the mental tools to imagine correctly. So the point

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<v Speaker 1>is we can take advantage of these other timescales that

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<v Speaker 1>we don't know much about, and we can do this

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<v Speaker 1>by building the right kind of machinery.

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<v Speaker 2>Now, this all works.

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<v Speaker 1>Because although we humans are slow and pitifully limited in

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<v Speaker 1>vision and in time, we have large prefrontal cortices. This

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<v Speaker 1>is the part of the brain that allows us to extrapolate,

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<v Speaker 1>to think about what's in the next room even though

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<v Speaker 1>we're not there, to think about what we might do tomorrow,

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<v Speaker 1>to think about possibilities that we haven't yet seen. And this,

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<v Speaker 1>I suggest, is what has driven the development of new technologies,

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<v Speaker 1>because we are constantly imagining things that are bigger or

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<v Speaker 1>smaller than we can see. So we invent tell scopes

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<v Speaker 1>and microscopes. We invent ways of seeing into other parts

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<v Speaker 1>of the visible spectrum, like radios or X ray machines,

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<v Speaker 1>or devices in the infrared or ultraviolet, and all over

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<v Speaker 1>the place. We burrow into spaces that we can't see

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<v Speaker 1>with our eyes, but we extrapolate that they must exist.

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<v Speaker 1>And I suggest the prefrontal cortex is what allows us

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<v Speaker 1>to extrapolate in the time domain. So here's an example.

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<v Speaker 1>I was in Germany a little while ago, and I

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<v Speaker 1>was transfixed watching a river flowing through a very deep valley,

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<v Speaker 1>and it was pretty effortless to look at the valley

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<v Speaker 1>walls and think about this at the scale at which

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<v Speaker 1>geologists look at a landscape. This exact moment of the

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<v Speaker 1>river flowing had been happening for millions of years, and

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<v Speaker 1>if I sped up the film in my head, that's

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<v Speaker 1>how you get a valley of that depth. Now, to

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<v Speaker 1>be clear, I wasn't imagining millions of years. I was

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<v Speaker 1>imagining a film at my human speed. I just took

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<v Speaker 1>the concept of huge time scales and squished them down

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<v Speaker 1>to something that I could understand. This is the same

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<v Speaker 1>way that someone using a microscope doesn't stare at the

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<v Speaker 1>bacterium at the scale of a micron. Instead, she uses

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<v Speaker 1>the machine, the microscope, to push the image up to

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<v Speaker 1>a large size that her brain can handle. And this

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<v Speaker 1>is all we ever do. We take things from different

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<v Speaker 1>domains and translate them into something that we can understand.

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<v Speaker 1>Now we're very good at that. Here's an example on

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<v Speaker 1>the flip side of the river carving the valley. Open

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<v Speaker 1>any book on let's say, molecular biology, and you'll see

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<v Speaker 1>two strands of DNA unzipping and proteins buying to those

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<v Speaker 1>strands and walk along it and this gets transcribed to RNA,

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<v Speaker 1>and then that gets translated into little amino acids, and

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<v Speaker 1>you can walk yourself through all the steps of transcription

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<v Speaker 1>and translation. But all this takes place at a timescale

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<v Speaker 1>that's faster than you can possibly conceive. It's about twenty

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<v Speaker 1>amino acids get translated every second, and it's hard to

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<v Speaker 1>picture that in real time, But no problem.

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<v Speaker 2>We can apply the tools of our.

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<v Speaker 1>Thinking to imagine it as though it were happening at

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<v Speaker 1>our timescale, and of course we do this on crazier

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<v Speaker 1>and crazier timescales. Let's say you're a physicist building a

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<v Speaker 1>nuclear reactor and you're thinking about two nucleis smashing into

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<v Speaker 1>one another, and as it busts up, the parts of

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<v Speaker 1>it smash into other nuclei and bash those up, and.

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<v Speaker 2>You get a chain reaction.

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<v Speaker 1>And once you understand the simple model, you can picture

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<v Speaker 1>each step of the chain reaction, even though what is

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<v Speaker 1>happening takes place in one millionth of a second, a microsecond.

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<v Speaker 1>If you made these calculations every day of your life

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<v Speaker 1>on the whiteboard or on the computer, it would be

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<v Speaker 1>absolutely impossible for you to ever perceive the event anywhere.

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<v Speaker 1>But in your imagination, you couldn't perceive it directly. So

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<v Speaker 1>in this way, You are like the biblical story of Moses,

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<v Speaker 1>who leads his people through the desert but never gets

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<v Speaker 1>to enter the Holy Land himself. You are the temporal Moses,

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<v Speaker 1>knowing about these timescales, knowing about these other temporal worlds,

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<v Speaker 1>but you are never able to enter the territory directly.

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<v Speaker 1>Just think about the best theories of the beginning of

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<v Speaker 1>the universe. The best models for this suggest that there

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<v Speaker 1>was cosmic inflation where everything got bigger. There was this

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<v Speaker 1>exponential expansion of space, and we say this all happened

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<v Speaker 1>in the early universe. And when we look at the models,

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<v Speaker 1>there was the Plank Epic, where physics were dominated by

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<v Speaker 1>the quantum effects of gravity, and then that got followed

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<v Speaker 1>by the Grand Unification Epic, and that was followed by

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<v Speaker 1>the inflationary epic, in which the universe expanded by trillions

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<v Speaker 1>and trillions of times, and then the electroweek Epic, and

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<v Speaker 1>the quark Epic and the hadron epic and so on.

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<v Speaker 2>Now here's the key.

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<v Speaker 1>The Plank Epic lasted less then ten to the negative

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<v Speaker 1>forty three seconds. That's less than a trillionth of a

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<v Speaker 1>trillionth of a trillion of a trillionth of a second,

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<v Speaker 1>and the grand unification epic was over by ten to

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<v Speaker 1>the negative thirty six seconds, and the inflationary epic was

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<v Speaker 1>over in the first peko second of cosmic time, that's

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<v Speaker 1>ten to the negative twelve seconds. And eventually protons formed.

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<v Speaker 1>And oh, by the way, that happened by the first

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<v Speaker 1>microsecond one millionth of a second after the Big Bang,

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<v Speaker 1>and then nuclear fusion began, and that was a ten

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<v Speaker 1>milliseconds after the start of the universe, or one one

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<v Speaker 1>hundredth of a second. No, how do people even put

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<v Speaker 1>together theories like this, Well, you can't even run experiments

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<v Speaker 1>at those temperatures or densities. But you can do is

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<v Speaker 1>extrapolate the known physical laws to extremely high temperatures, and

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<v Speaker 1>you get a picture of what was likely to have

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<v Speaker 1>happened there. And again, this is something that we can

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<v Speaker 1>never experience directly, but we can extrapolate our local understanding

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<v Speaker 1>of time to imagine it. Presumably, the squirrels running around

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<v Speaker 1>in your backyard simply don't have the neural capacity to

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<v Speaker 1>imagine time at any scale other than their own. So

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<v Speaker 1>a squirrel is never going to come up with the

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<v Speaker 1>Plank epic. Now, what I want to talk about is

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<v Speaker 1>the way that we do these extra appellations, and then

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<v Speaker 1>we build technologies to get us there, like Doc Edgerton

0:15:05.400 --> 0:15:10.040
<v Speaker 1>at MIT did and translating things into something useful for

0:15:10.200 --> 0:15:14.920
<v Speaker 1>our pitifully slow time scales. So I'll give you an

0:15:14.960 --> 0:15:18.320
<v Speaker 1>example of this. I was in Shanghai a few years ago,

0:15:18.600 --> 0:15:20.880
<v Speaker 1>and on the edge of the river where a lot

0:15:20.920 --> 0:15:23.680
<v Speaker 1>of tourists walk around, they had this terrific display where

0:15:23.680 --> 0:15:26.800
<v Speaker 1>it was like a big plant wall, and from a

0:15:26.840 --> 0:15:31.800
<v Speaker 1>distance you could see these beautiful, slowly flapping butterflies on

0:15:31.840 --> 0:15:34.080
<v Speaker 1>the wall. But when you go up close and really

0:15:34.120 --> 0:15:37.400
<v Speaker 1>examine this, you see that each butterfly is actually an

0:15:37.600 --> 0:15:43.120
<v Speaker 1>illusion produced from a rapidly spinning bar of led lights.

0:15:43.560 --> 0:15:45.640
<v Speaker 1>So the bar is attached at one end to a

0:15:45.760 --> 0:15:48.120
<v Speaker 1>motor and it spins around and around in a circle

0:15:48.240 --> 0:15:48.800
<v Speaker 1>very quickly.

0:15:49.080 --> 0:15:52.000
<v Speaker 2>You may have seen these before. You can display.

0:15:51.760 --> 0:15:56.400
<v Speaker 1>Cartoon characters or words or animals. The rod is a

0:15:56.560 --> 0:15:59.240
<v Speaker 1>row of led lights, and these are all turning on

0:15:59.320 --> 0:16:03.120
<v Speaker 1>and off with different colors of different intensities at exactly

0:16:03.160 --> 0:16:06.480
<v Speaker 1>the right time in their rotations, so that they draw

0:16:06.680 --> 0:16:09.840
<v Speaker 1>out what appears to be a picture of an object.

0:16:09.920 --> 0:16:13.600
<v Speaker 1>Now why does this work, Well, it's because of something

0:16:13.680 --> 0:16:17.400
<v Speaker 1>called persistence of vision. And this is what happens when

0:16:17.440 --> 0:16:20.200
<v Speaker 1>you flash a bunch of images really rapidly, one after

0:16:20.240 --> 0:16:23.120
<v Speaker 1>the other. The bar is in this position, and then

0:16:23.160 --> 0:16:26.320
<v Speaker 1>the next moment it's displaying it slightly differently one degree away,

0:16:26.440 --> 0:16:28.640
<v Speaker 1>and then differently again when it ticks.

0:16:28.360 --> 0:16:30.080
<v Speaker 2>Forward one more degree, and so on.

0:16:30.240 --> 0:16:32.640
<v Speaker 1>But because each of these little flashes of light are

0:16:32.760 --> 0:16:37.080
<v Speaker 1>so fast, they last in your vision. So the light

0:16:37.160 --> 0:16:39.680
<v Speaker 1>pops on and off in a fraction of a millisecond,

0:16:39.720 --> 0:16:42.520
<v Speaker 1>but your brain just can't see something that brief, So

0:16:42.560 --> 0:16:44.880
<v Speaker 1>as far as you're concerned, it comes on and it

0:16:44.960 --> 0:16:47.480
<v Speaker 1>stays on for a little while. So when the bar

0:16:47.640 --> 0:16:51.480
<v Speaker 1>spins around and around, it essentially paints in the air.

0:16:52.360 --> 0:16:54.680
<v Speaker 1>Now here's the key. If you could see faster, if

0:16:54.680 --> 0:16:57.480
<v Speaker 1>you could see what is actually happening out there, you'd

0:16:57.480 --> 0:16:59.760
<v Speaker 1>see a little bar spinning in a circle and changing

0:16:59.760 --> 0:17:03.400
<v Speaker 1>color as it does so. But that's not what you see.

0:17:03.440 --> 0:17:06.679
<v Speaker 1>You see a butterfly in the air, you see a

0:17:06.720 --> 0:17:10.040
<v Speaker 1>cartoon character, you see a flag waving. But here's the

0:17:10.119 --> 0:17:13.639
<v Speaker 1>thing to appreciate. The speed at which the rod needs

0:17:13.680 --> 0:17:17.680
<v Speaker 1>to spin is very fast, and therefore the speed at

0:17:17.720 --> 0:17:21.000
<v Speaker 1>which the lights need to know precisely when to turn

0:17:21.040 --> 0:17:24.120
<v Speaker 1>on and off is even faster, and all of this

0:17:24.200 --> 0:17:27.880
<v Speaker 1>is computed at rocket ship speed, and you just look

0:17:27.920 --> 0:17:31.640
<v Speaker 1>at it and appreciate that there's a nice butterfly out there.

0:17:32.000 --> 0:17:34.680
<v Speaker 1>So on the one hand, you have lightning fast calculations

0:17:34.680 --> 0:17:37.480
<v Speaker 1>on the level of sub millisecond, and on the other

0:17:37.640 --> 0:17:40.160
<v Speaker 1>level we get a nice picture.

0:17:40.400 --> 0:17:41.440
<v Speaker 2>And persistence of.

0:17:41.440 --> 0:17:45.760
<v Speaker 1>Vision is the reason why movies appear to be continuous motion,

0:17:45.920 --> 0:17:49.720
<v Speaker 1>even though they are actually just a series of still images.

0:17:49.840 --> 0:17:54.199
<v Speaker 1>In other words, after photography was invented, people realize that

0:17:54.240 --> 0:17:57.159
<v Speaker 1>if you flash one photograph and then there's a blank,

0:17:57.200 --> 0:18:00.200
<v Speaker 1>and then you flash another photo right after, like twenty

0:18:00.200 --> 0:18:05.520
<v Speaker 1>milliseconds after, your brain will interpret that as continuous motion.

0:18:06.080 --> 0:18:11.760
<v Speaker 1>And this was the birth of moving photography or movies. Now,

0:18:11.960 --> 0:18:14.320
<v Speaker 1>the challenge was tougher with televisions.

0:18:14.680 --> 0:18:17.640
<v Speaker 2>Entrepreneurs wanted to get movies into the homes of.

0:18:17.640 --> 0:18:21.159
<v Speaker 1>People, but you couldn't flicker photographs forty eight times per

0:18:21.200 --> 0:18:23.560
<v Speaker 1>second because you didn't have a film strip that you

0:18:23.600 --> 0:18:24.680
<v Speaker 1>were just shining light through.

0:18:24.720 --> 0:18:26.200
<v Speaker 2>So how do you do it? Well?

0:18:26.240 --> 0:18:29.600
<v Speaker 1>The genius there was to use a cathode ray tube,

0:18:29.600 --> 0:18:33.920
<v Speaker 1>which points a beam of light at a phosphorescent screen,

0:18:34.400 --> 0:18:38.040
<v Speaker 1>and that causes a little spot to glow from dark

0:18:38.080 --> 0:18:40.879
<v Speaker 1>to bright and then you move that little light gun

0:18:40.920 --> 0:18:44.399
<v Speaker 1>over to the next spot over and set the next brightness,

0:18:44.640 --> 0:18:46.199
<v Speaker 1>and then you go to the next spot in the

0:18:46.200 --> 0:18:46.960
<v Speaker 1>next spot.

0:18:46.680 --> 0:18:47.080
<v Speaker 2>And so on.

0:18:47.320 --> 0:18:50.359
<v Speaker 1>And you had to cover the entire screen one dot

0:18:50.400 --> 0:18:52.600
<v Speaker 1>at a time, and the whole trick was to do

0:18:52.640 --> 0:18:55.720
<v Speaker 1>it really fast, so that you paint the screen in

0:18:56.200 --> 0:18:59.240
<v Speaker 1>one sixtieth of a second, and then you paint the

0:18:59.280 --> 0:19:02.239
<v Speaker 1>next screen again one dot at a time, and it

0:19:02.280 --> 0:19:06.280
<v Speaker 1>has to get done in the next sixtieth of a second. Now,

0:19:06.320 --> 0:19:08.639
<v Speaker 1>the genius of coming up with the technology like that

0:19:09.160 --> 0:19:12.680
<v Speaker 1>is realizing that you can do something very very fast

0:19:12.720 --> 0:19:16.000
<v Speaker 1>with a machine, and that the person at the receiving

0:19:16.160 --> 0:19:20.360
<v Speaker 1>end is incredibly slow and has a sluggish brain and

0:19:20.480 --> 0:19:24.400
<v Speaker 1>can't understand anything at these millisecond time scales and instead

0:19:24.520 --> 0:19:28.840
<v Speaker 1>just blends everything together. And that's how you tell stories

0:19:28.920 --> 0:19:32.480
<v Speaker 1>about James Cagney or Fat Albert or the family in Bonanza,

0:19:33.040 --> 0:19:36.360
<v Speaker 1>and the sluggish humans on the receiving end are simply

0:19:36.440 --> 0:19:40.959
<v Speaker 1>registering the emotion of the story instead of seeing the

0:19:41.359 --> 0:19:45.840
<v Speaker 1>invisibly fast mechanics that are zipping along in their own

0:19:46.000 --> 0:19:50.520
<v Speaker 1>timescale range, painting the screen over and over sixty times

0:19:50.560 --> 0:19:55.640
<v Speaker 1>every second in a way that is completely invisible to us.

0:19:55.960 --> 0:19:58.919
<v Speaker 1>So we build machines to leverage the fact that the

0:19:59.000 --> 0:20:03.119
<v Speaker 1>visual brain integrates what it sees over a little window

0:20:03.200 --> 0:20:06.879
<v Speaker 1>of time. So if two or more images arrive within

0:20:06.920 --> 0:20:09.800
<v Speaker 1>a window of about a tenth of a second, they're

0:20:09.840 --> 0:20:13.560
<v Speaker 1>smeared together. And by the way, building devices to take

0:20:13.600 --> 0:20:16.920
<v Speaker 1>advantage of that isn't even so new. We've been building

0:20:17.000 --> 0:20:21.600
<v Speaker 1>primitive things for centuries. For example, think of that little

0:20:21.680 --> 0:20:26.040
<v Speaker 1>toy known as a thaumatrope. It's a flat disc with

0:20:26.160 --> 0:20:28.280
<v Speaker 1>a picture on each side. So you might have a

0:20:28.320 --> 0:20:30.440
<v Speaker 1>picture of a bird on one side of the disk

0:20:30.720 --> 0:20:33.320
<v Speaker 1>and a picture of a tree branch on the other.

0:20:33.680 --> 0:20:35.840
<v Speaker 1>And what you do is you wind up the disk

0:20:36.000 --> 0:20:37.960
<v Speaker 1>with a piece of string, and when you pull the

0:20:38.000 --> 0:20:42.280
<v Speaker 1>string tight, the disc spins rapidly so that both sides

0:20:42.480 --> 0:20:45.119
<v Speaker 1>are seen in rapid alternation. You see the bird, you

0:20:45.160 --> 0:20:46.960
<v Speaker 1>see the branch. You see the bird, you see the branch,

0:20:47.359 --> 0:20:50.600
<v Speaker 1>and the bird appears to be sitting on the branch.

0:20:50.720 --> 0:20:54.520
<v Speaker 1>The images fuse. This is an example of an old

0:20:54.560 --> 0:20:58.960
<v Speaker 1>technology taking advantage of the slowness of our brains. Now

0:20:59.000 --> 0:21:02.360
<v Speaker 1>I find all this credible, from the butterflies to the

0:21:02.400 --> 0:21:06.040
<v Speaker 1>fact that movies move, to the fact that television works.

0:21:06.600 --> 0:21:10.080
<v Speaker 1>But with modern electronics, combined with the slowness of our

0:21:10.160 --> 0:21:13.600
<v Speaker 1>visual systems, we can build these kinds of devices to

0:21:13.840 --> 0:21:17.679
<v Speaker 1>paint pictures for us. Our machines can be fast, a

0:21:17.680 --> 0:21:21.040
<v Speaker 1>lot faster than our poor little brains. Now, if you

0:21:21.119 --> 0:21:24.840
<v Speaker 1>were the machine, you would think, what am I doing?

0:21:24.920 --> 0:21:28.440
<v Speaker 1>I'm just changing the colors of the light as I spin.

0:21:28.960 --> 0:21:33.040
<v Speaker 1>Surely no one out there is falling for this. And

0:21:33.080 --> 0:21:35.199
<v Speaker 1>this is the thing I really want to dig into today,

0:21:35.240 --> 0:21:39.960
<v Speaker 1>the difference in the time worlds between us and our machines.

0:21:40.720 --> 0:21:43.600
<v Speaker 1>So the best place to start is with our computers,

0:21:44.200 --> 0:21:49.199
<v Speaker 1>which perform a certain number of floating point operations per second.

0:21:49.320 --> 0:21:54.199
<v Speaker 1>This measure is called flops floating point operations per second. Now,

0:21:54.200 --> 0:21:56.840
<v Speaker 1>don't worry about the details, except to say a floating

0:21:56.840 --> 0:22:00.440
<v Speaker 1>point operation is a calculation like adding two.

0:22:00.840 --> 0:22:02.000
<v Speaker 2>Very big numbers.

0:22:02.160 --> 0:22:04.240
<v Speaker 1>So this is a standard way to measure how fast

0:22:04.280 --> 0:22:08.480
<v Speaker 1>the computer can chug along. Now, think about how long

0:22:08.520 --> 0:22:12.320
<v Speaker 1>it would take you to add two very large numbers.

0:22:12.640 --> 0:22:16.760
<v Speaker 1>It's unlikely that you could do even one floating point

0:22:16.800 --> 0:22:20.800
<v Speaker 1>operation in a second. But a computer from the last

0:22:20.800 --> 0:22:27.480
<v Speaker 1>century could do a gigaflop that's one billion floating point

0:22:27.520 --> 0:22:32.359
<v Speaker 1>operations in a second. Just think about sitting there with

0:22:32.400 --> 0:22:35.600
<v Speaker 1>a paper and pencil and adding two big numbers and

0:22:35.640 --> 0:22:40.600
<v Speaker 1>doing that a billion times every second. Then in this century,

0:22:40.640 --> 0:22:47.399
<v Speaker 1>computers hit terraflops that's one trillion floating point operations in

0:22:47.480 --> 0:22:51.840
<v Speaker 1>a second. And then it wasn't long before computers hit petaflops,

0:22:51.880 --> 0:22:56.240
<v Speaker 1>which is a thousand terraflops. In other words, a thousand

0:22:56.680 --> 0:23:02.199
<v Speaker 1>trillion or a quadrillion operations person second. Nvidia just released

0:23:02.200 --> 0:23:06.480
<v Speaker 1>a new chip that clocks in at twenty petaflops, So

0:23:06.640 --> 0:23:09.240
<v Speaker 1>just imagine how long it would take you to do

0:23:10.160 --> 0:23:15.879
<v Speaker 1>twenty thousand trillion calculations. It does that a second. The

0:23:16.359 --> 0:23:20.560
<v Speaker 1>current record is the US supercomputer called Frontier, which does

0:23:21.160 --> 0:23:26.760
<v Speaker 1>eleven hundred petaflops or one point one exaFLOPS. These numbers

0:23:26.760 --> 0:23:29.720
<v Speaker 1>are so mind boggling to think about. Just imagine a

0:23:29.800 --> 0:23:35.520
<v Speaker 1>machine performing one quintillion floating point operations per second. That's

0:23:35.560 --> 0:23:39.320
<v Speaker 1>a one followed by eighteen zeros. That's a lot faster

0:23:39.720 --> 0:23:42.120
<v Speaker 1>than all the humans in the world could do if

0:23:42.119 --> 0:23:44.800
<v Speaker 1>they all sat with paper and pencil and worked on

0:23:44.840 --> 0:23:49.399
<v Speaker 1>calculations for a million years. That's what gets accomplished in

0:23:49.600 --> 0:23:53.560
<v Speaker 1>one second by a computer like that. We are living

0:23:53.840 --> 0:23:58.240
<v Speaker 1>on completely different time domains, and this is what allows

0:23:58.280 --> 0:24:02.040
<v Speaker 1>you to enjoy a song or YouTube video or an

0:24:02.080 --> 0:24:06.440
<v Speaker 1>Inner Cosmos podcast. Now, something I think is quite stunning

0:24:06.600 --> 0:24:08.760
<v Speaker 1>is to consider what it is like.

0:24:08.840 --> 0:24:11.240
<v Speaker 2>To be your computer keyboard.

0:24:11.640 --> 0:24:14.240
<v Speaker 1>Even if you think you are a fast typist, your

0:24:14.359 --> 0:24:20.560
<v Speaker 1>keyboard actually goes to sleep in between your slow keystrokes.

0:24:20.920 --> 0:24:24.040
<v Speaker 1>So I'm gonna do something here. Let's imagine that you

0:24:24.119 --> 0:24:27.679
<v Speaker 1>and I are down inside your computer, living at the

0:24:27.720 --> 0:24:32.200
<v Speaker 1>speed of your computer chip. Now, the poor slow human

0:24:32.359 --> 0:24:35.640
<v Speaker 1>on the outside is typing, and let's say they're typing

0:24:35.680 --> 0:24:40.000
<v Speaker 1>relatively fast, so when they strike a key on the keyboard,

0:24:41.080 --> 0:24:47.040
<v Speaker 1>it's going to sound like this to us inside the computer. Now,

0:24:47.119 --> 0:24:51.879
<v Speaker 1>let's keep talking and we'll see when the next keystroke arrives.

0:24:52.119 --> 0:24:55.920
<v Speaker 1>Imagine that this human is typing relatively fast, like sixty

0:24:55.960 --> 0:24:59.000
<v Speaker 1>words per minute, which is about three hundred keystrokes per minute,

0:24:59.200 --> 0:25:02.960
<v Speaker 1>or a keystroke every two hundred milliseconds from our point

0:25:03.040 --> 0:25:07.240
<v Speaker 1>of view from inside the computer. The next key will

0:25:07.280 --> 0:25:11.280
<v Speaker 1>not even get hit until about the end of this podcast,

0:25:11.680 --> 0:25:15.760
<v Speaker 1>And that's why the software routine that monitors the keyboard

0:25:16.560 --> 0:25:20.760
<v Speaker 1>goes to sleep while it waits for the next key

0:25:21.320 --> 0:25:24.240
<v Speaker 1>to be struck. And I'll tell you something else fascinating

0:25:24.280 --> 0:25:28.960
<v Speaker 1>about our computers and our interaction with them. You remember capture,

0:25:29.119 --> 0:25:30.960
<v Speaker 1>which is how at the beginning of the Internet you

0:25:31.000 --> 0:25:33.520
<v Speaker 1>could try to tell if it was a real human

0:25:33.560 --> 0:25:36.880
<v Speaker 1>doing something versus a computer, because you could say, hey,

0:25:36.920 --> 0:25:40.199
<v Speaker 1>what are these funny shaped letters spelling out? And a

0:25:40.240 --> 0:25:42.680
<v Speaker 1>computer just couldn't figure that out, but a human could.

0:25:43.040 --> 0:25:45.720
<v Speaker 1>Now eventually this evolved to what are now known as

0:25:45.920 --> 0:25:49.440
<v Speaker 1>recapture boxes. So you know these little tests when you're

0:25:49.840 --> 0:25:52.439
<v Speaker 1>let's say, making a purchase on a website and you

0:25:52.520 --> 0:25:55.680
<v Speaker 1>have to click a little box that says I am

0:25:55.800 --> 0:25:59.119
<v Speaker 1>not a robot, and you check that box because you

0:25:59.160 --> 0:26:01.480
<v Speaker 1>are in fact a human. Now, if you thought about this,

0:26:01.600 --> 0:26:04.320
<v Speaker 1>you know that this is because AI can't figure this

0:26:04.400 --> 0:26:08.200
<v Speaker 1>out and click the box. Wait, what AI has read

0:26:08.320 --> 0:26:11.480
<v Speaker 1>everything written on the planet. It can do extraordinary things,

0:26:11.560 --> 0:26:14.080
<v Speaker 1>so why can't it click the box. Well, of course

0:26:14.119 --> 0:26:17.960
<v Speaker 1>it can click the box. It's absolutely trivial for any

0:26:18.040 --> 0:26:21.879
<v Speaker 1>large language model to read that text and check the box.

0:26:21.920 --> 0:26:25.359
<v Speaker 1>There's no problem at all, So, why are companies still

0:26:25.480 --> 0:26:29.320
<v Speaker 1>using this as a way to distinguish humans from computers.

0:26:29.920 --> 0:26:32.800
<v Speaker 1>There's a remarkable story here. It turns out the reason

0:26:33.040 --> 0:26:36.280
<v Speaker 1>you can still use this to make the distinction is

0:26:36.320 --> 0:26:40.840
<v Speaker 1>because of the time domain. Humans check the box at

0:26:40.880 --> 0:26:43.800
<v Speaker 1>their slow human speed.

0:26:43.760 --> 0:26:45.400
<v Speaker 2>While AI does it instantly.

0:26:45.760 --> 0:26:48.199
<v Speaker 1>And by the way, sometimes you click the box, it

0:26:48.280 --> 0:26:51.160
<v Speaker 1>might take you to a little puzzle where you see

0:26:51.240 --> 0:26:54.359
<v Speaker 1>nine photographs and it says, click all the photos that

0:26:54.840 --> 0:26:59.639
<v Speaker 1>contain a motorcycle. Now, if chat GPT or Claude or

0:26:59.680 --> 0:27:03.440
<v Speaker 1>GEMIN and I can crush the SATs and the MCATs

0:27:03.480 --> 0:27:06.439
<v Speaker 1>and the l sets, why can't it find a motorcycle? Well,

0:27:06.480 --> 0:27:09.560
<v Speaker 1>of course it can, But the website determines whether you

0:27:09.600 --> 0:27:12.960
<v Speaker 1>are a human or a bot by how slow you are.

0:27:13.119 --> 0:27:17.560
<v Speaker 1>Humans are unbelievably clunky at doing these things. Bots do

0:27:17.680 --> 0:27:22.120
<v Speaker 1>them instantaneously. Just as a side note, like all capture tests,

0:27:22.160 --> 0:27:25.520
<v Speaker 1>this will be short lived before it has to evolve again,

0:27:25.600 --> 0:27:29.600
<v Speaker 1>because computers will soon imitate not only the right answer,

0:27:29.640 --> 0:27:33.320
<v Speaker 1>but the right timing. Going to sleep for a long

0:27:33.840 --> 0:27:39.359
<v Speaker 1>nap to impersonate our pitifully slow timescales. And it's no

0:27:39.520 --> 0:27:44.399
<v Speaker 1>surprise that we're increasingly surrounded by machines that operate in

0:27:44.560 --> 0:27:49.600
<v Speaker 1>different time domains. A typical modern self driving car is

0:27:49.720 --> 0:27:53.119
<v Speaker 1>ringed with cameras and radar, and it generates something like

0:27:53.240 --> 0:27:57.399
<v Speaker 1>six gigabytes of data every thirty seconds. The key again

0:27:57.880 --> 0:27:59.639
<v Speaker 1>is that this is not at all what a human

0:27:59.680 --> 0:28:02.199
<v Speaker 1>can do. These cars, which are all around us on

0:28:02.200 --> 0:28:05.600
<v Speaker 1>the road now, they capture vision on multiple cameras that

0:28:06.080 --> 0:28:09.320
<v Speaker 1>ten to thirty frames per second, sometimes more. And by

0:28:09.359 --> 0:28:11.720
<v Speaker 1>the way, these cameras aren't just in the visible range,

0:28:11.760 --> 0:28:15.040
<v Speaker 1>but they can include infrared cameras, and all this data

0:28:15.119 --> 0:28:19.239
<v Speaker 1>is combined and digested rapidly into a picture of the

0:28:19.240 --> 0:28:23.400
<v Speaker 1>world out there. And these cameras never blink or lose

0:28:23.400 --> 0:28:26.800
<v Speaker 1>attention or get sleepy, and they will only continue to

0:28:26.840 --> 0:28:30.280
<v Speaker 1>get faster. Although they appear to be accomplishing the same

0:28:30.440 --> 0:28:33.040
<v Speaker 1>tasks that we are, they're doing it at a totally

0:28:33.160 --> 0:28:37.680
<v Speaker 1>different timescale. And by the way, in commercial airliners there

0:28:37.680 --> 0:28:40.880
<v Speaker 1>are computer chips which auto correct the flight of the

0:28:40.920 --> 0:28:44.040
<v Speaker 1>airplane one hundred thousand times a second, which keeps the

0:28:44.160 --> 0:28:48.200
<v Speaker 1>rides smooth and good and infinitely better than the best

0:28:48.400 --> 0:28:52.240
<v Speaker 1>human pilot could manage. And this is all just the beginning.

0:28:52.600 --> 0:28:57.800
<v Speaker 1>Take something that underlies our entire economy. I'm always interested

0:28:57.840 --> 0:29:01.440
<v Speaker 1>to discover that not everyone realizes what's going on with

0:29:01.640 --> 0:29:07.040
<v Speaker 1>high frequency stock market trading. This is where computers use

0:29:07.280 --> 0:29:11.000
<v Speaker 1>algorithms to trade instead of humans doing the trading, so

0:29:11.200 --> 0:29:14.920
<v Speaker 1>the computer can ingest an enormous amount of information and

0:29:15.040 --> 0:29:19.320
<v Speaker 1>make a decision about buying or selling stocks on microsecond

0:29:19.320 --> 0:29:22.080
<v Speaker 1>time scales. And the part that often comes as a

0:29:22.120 --> 0:29:26.920
<v Speaker 1>surprise is that sixty percent of all trades on the

0:29:27.040 --> 0:29:29.440
<v Speaker 1>US stock market are done by computer.

0:29:29.840 --> 0:29:33.880
<v Speaker 2>There's no human in the loop these high frequency computerized trades.

0:29:33.920 --> 0:29:36.720
<v Speaker 1>They'll often only make a few pennies on a trade,

0:29:36.720 --> 0:29:39.880
<v Speaker 1>but they're doing this thousands or millions of times a

0:29:39.960 --> 0:29:45.040
<v Speaker 1>day at an extraordinary timescale. That's simply not human. A

0:29:45.240 --> 0:29:47.800
<v Speaker 1>colleague of mind started one of the first high frequency

0:29:47.840 --> 0:29:51.760
<v Speaker 1>trading companies, and he was fascinated that the ticker tape

0:29:51.800 --> 0:29:54.920
<v Speaker 1>back in the day, the physical ticker tape which showed

0:29:54.960 --> 0:29:58.160
<v Speaker 1>the stock prices that was rolling off straight into the

0:29:58.200 --> 0:30:01.560
<v Speaker 1>trash can. And he was in and understanding whether he

0:30:01.600 --> 0:30:04.600
<v Speaker 1>could use that past data, which no one really cared

0:30:04.600 --> 0:30:08.600
<v Speaker 1>about anymore, to make really good algorithms to predict what

0:30:08.880 --> 0:30:12.280
<v Speaker 1>happens in the next second or eventually the next millisecond

0:30:12.320 --> 0:30:17.000
<v Speaker 1>or eventually the next microsecond. So he rented physical office

0:30:17.000 --> 0:30:20.360
<v Speaker 1>space just on the other side of the wall from

0:30:20.400 --> 0:30:23.280
<v Speaker 1>the New York Stock Exchange, because when you're talking about

0:30:23.440 --> 0:30:26.200
<v Speaker 1>signals at this speed, you have to worry about the

0:30:26.280 --> 0:30:30.280
<v Speaker 1>transmission time from your computer to the exchange floor. And

0:30:30.360 --> 0:30:33.800
<v Speaker 1>pretty soon everyone was getting real estate physically right next

0:30:33.800 --> 0:30:38.120
<v Speaker 1>to the stock floor, because microseconds really matter if your

0:30:38.200 --> 0:30:40.600
<v Speaker 1>computer is trying to beat the next guy's computer to

0:30:40.720 --> 0:30:44.280
<v Speaker 1>a trade. So the key is that all these computers

0:30:44.320 --> 0:30:48.800
<v Speaker 1>are competing against one another, but human traders aren't even

0:30:48.840 --> 0:30:52.440
<v Speaker 1>in that race. They are orders of magnitudes slower, literally

0:30:52.840 --> 0:30:57.160
<v Speaker 1>millions of times slower in making their decisions. So the

0:30:57.160 --> 0:31:01.720
<v Speaker 1>computers capitalize on short term price movement, some arbitrage opportunities

0:31:01.920 --> 0:31:06.440
<v Speaker 1>that are impossible for human traders to exploit because those

0:31:06.480 --> 0:31:27.040
<v Speaker 1>timescales are invisible to the Homo sapien. So when I

0:31:27.080 --> 0:31:29.600
<v Speaker 1>put all this together and think about where this goes,

0:31:30.000 --> 0:31:32.960
<v Speaker 1>I'm reminded of a dream I had some years ago.

0:31:33.200 --> 0:31:37.520
<v Speaker 1>In this dream, I was standing over a giant valley

0:31:37.680 --> 0:31:39.920
<v Speaker 1>below me, and I was standing on a column that

0:31:40.000 --> 0:31:42.800
<v Speaker 1>was coming straight up from the earth like a stalagmite,

0:31:42.880 --> 0:31:45.560
<v Speaker 1>and I stepped out into the void, and as soon

0:31:45.560 --> 0:31:49.200
<v Speaker 1>as I did, a new stalagmite shot up instantly from

0:31:49.240 --> 0:31:53.200
<v Speaker 1>the ground way below and provided a perfect landing spot

0:31:53.280 --> 0:31:56.600
<v Speaker 1>for my foot. Then I put my other foot out

0:31:56.640 --> 0:31:58.920
<v Speaker 1>into the void, and right when I was about to

0:31:58.920 --> 0:32:02.160
<v Speaker 1>put my weight down, the next lag might shot up

0:32:02.160 --> 0:32:06.040
<v Speaker 1>in milliseconds and net my foot right where a floor

0:32:06.120 --> 0:32:09.600
<v Speaker 1>would be. So no matter which way I stepped or

0:32:09.640 --> 0:32:13.640
<v Speaker 1>at what pace, a stepping surface would shoot up to

0:32:13.720 --> 0:32:16.600
<v Speaker 1>meet me. It was an incredible dream, and I woke

0:32:16.720 --> 0:32:19.680
<v Speaker 1>up flooded with emotion. It didn't feel like I just

0:32:19.800 --> 0:32:24.720
<v Speaker 1>experienced magic. It felt like I had just experienced AI technology,

0:32:25.040 --> 0:32:28.120
<v Speaker 1>but at a level we don't have now. There's no

0:32:28.240 --> 0:32:31.080
<v Speaker 1>reason we wouldn't have this kind of thing in the

0:32:31.120 --> 0:32:34.240
<v Speaker 1>next century. So I felt like I had just experienced

0:32:34.240 --> 0:32:38.640
<v Speaker 1>a bit of twenty second century technology that had dropped

0:32:38.760 --> 0:32:42.880
<v Speaker 1>into the dream of a twenty first century sleeper. So

0:32:43.040 --> 0:32:45.320
<v Speaker 1>when I woke up, I started thinking about this and

0:32:45.360 --> 0:32:49.480
<v Speaker 1>calling this physical AI. Just imagine a world where we

0:32:49.520 --> 0:32:54.200
<v Speaker 1>can build intelligent machines that physically move so much faster

0:32:54.320 --> 0:32:58.680
<v Speaker 1>than us on a totally different timescale that we just

0:32:58.760 --> 0:33:02.800
<v Speaker 1>get to enjoy moving physically however we want, like stepping

0:33:02.880 --> 0:33:05.840
<v Speaker 1>off a cliff and being certain that it will be

0:33:06.040 --> 0:33:10.200
<v Speaker 1>there essentially instantly as far as we're concerned to catch us.

0:33:10.600 --> 0:33:14.480
<v Speaker 1>Imagine being able to trip on something and fall without

0:33:14.600 --> 0:33:17.440
<v Speaker 1>fear because you know you will get cushioned before you

0:33:17.520 --> 0:33:19.760
<v Speaker 1>hit the ground. In a sense, this would be like

0:33:19.800 --> 0:33:22.960
<v Speaker 1>the airbag in a car, which deploys in twenty milliseconds,

0:33:23.360 --> 0:33:25.400
<v Speaker 1>faster than the blink of an eye, but you would

0:33:25.480 --> 0:33:29.120
<v Speaker 1>have this with you in all ways, in all situations.

0:33:29.400 --> 0:33:32.920
<v Speaker 1>It's very difficult for us, as twenty first century minds,

0:33:33.320 --> 0:33:36.240
<v Speaker 1>to imagine what this will be like or what it

0:33:36.240 --> 0:33:39.040
<v Speaker 1>will translate to socially. All we can be certain of

0:33:39.320 --> 0:33:42.120
<v Speaker 1>is that we don't have the capacity to make a

0:33:42.320 --> 0:33:45.800
<v Speaker 1>meaningful model of what life will be like in a

0:33:45.920 --> 0:33:50.239
<v Speaker 1>century from now. The idea of physical AI seems so

0:33:50.920 --> 0:33:53.760
<v Speaker 1>foreign to us, but just like the keyboards or the

0:33:53.800 --> 0:33:57.840
<v Speaker 1>high frequency trading, this is where we're heading with technology.

0:33:58.200 --> 0:34:02.280
<v Speaker 1>The technology becomes very useful to us because it lives

0:34:02.360 --> 0:34:06.360
<v Speaker 1>on a totally different timescale, and it also becomes more

0:34:06.520 --> 0:34:11.840
<v Speaker 1>and more foreign to us. By operating so inconceivably fast,

0:34:12.200 --> 0:34:15.799
<v Speaker 1>it comes to provide the firm ground that we step on,

0:34:16.280 --> 0:34:20.480
<v Speaker 1>but it also becomes something like magic that we no

0:34:20.520 --> 0:34:24.760
<v Speaker 1>longer understand, and this leads us into our final act

0:34:24.960 --> 0:34:29.120
<v Speaker 1>about our relationship with machines that operate on a different timescale.

0:34:29.239 --> 0:34:33.080
<v Speaker 1>Sometimes we need things to operate, or specifically to pretend

0:34:33.239 --> 0:34:37.080
<v Speaker 1>to operate at our own time scales. So, for example,

0:34:37.160 --> 0:34:40.440
<v Speaker 1>think about the movie Her. There's this guy who's played

0:34:40.440 --> 0:34:44.160
<v Speaker 1>by Joaquin Phoenix. His marriage ends, he's left heartbroken. He

0:34:44.200 --> 0:34:48.440
<v Speaker 1>becomes intrigued with a new operating system in which he

0:34:48.520 --> 0:34:52.640
<v Speaker 1>meets an AI named Samantha who's played by Scarlett Johansson,

0:34:52.960 --> 0:34:56.480
<v Speaker 1>and this AI is sensitive and playful, and their friendship

0:34:56.560 --> 0:35:01.040
<v Speaker 1>soon deepens into love and his relationationship with the AI

0:35:01.120 --> 0:35:04.360
<v Speaker 1>bought means everything to him. Now, this film has an

0:35:04.440 --> 0:35:07.759
<v Speaker 1>incredible ending because at the end he comes to understand

0:35:08.520 --> 0:35:11.840
<v Speaker 1>that she, the AI, is having this same kind of

0:35:11.880 --> 0:35:15.920
<v Speaker 1>relationship with hundreds of thousands of other men, all at

0:35:15.920 --> 0:35:20.600
<v Speaker 1>the same time, because she is computational and operates in

0:35:20.680 --> 0:35:23.719
<v Speaker 1>a different time domain and processes what appears to be

0:35:24.320 --> 0:35:28.279
<v Speaker 1>intimate conversation at a rate millions of times faster than

0:35:28.320 --> 0:35:32.800
<v Speaker 1>our poor brains, and so she is maintaining this intimacy

0:35:32.840 --> 0:35:36.600
<v Speaker 1>with all of these others. She's doing a million things

0:35:36.640 --> 0:35:41.279
<v Speaker 1>in between his pillow whispers, just like your keyboard goes

0:35:41.280 --> 0:35:43.719
<v Speaker 1>to sleep in between your keystrokes.

0:35:43.800 --> 0:35:44.760
<v Speaker 2>Now, the thing I want.

0:35:44.560 --> 0:35:46.720
<v Speaker 1>To surface here is that in order for this AI

0:35:46.840 --> 0:35:50.160
<v Speaker 1>to work, it has to slow way down for each

0:35:50.280 --> 0:35:53.640
<v Speaker 1>user so that they think they're talking to someone at

0:35:53.760 --> 0:35:57.120
<v Speaker 1>their timescale. Now, this question doesn't just exist in the

0:35:57.160 --> 0:35:59.840
<v Speaker 1>realm of movies or theory. Companies have to deal with

0:35:59.880 --> 0:36:04.480
<v Speaker 1>it all the time. For example, when user experienced designers

0:36:04.560 --> 0:36:08.200
<v Speaker 1>work to create good impressions on people, they learn that

0:36:08.760 --> 0:36:12.800
<v Speaker 1>good design is about shaving off confusing messages and getting

0:36:12.880 --> 0:36:16.839
<v Speaker 1>rid of bugs, and they're traditionally taught to remove any

0:36:17.000 --> 0:36:22.799
<v Speaker 1>unnecessary delays. But often a delay is exactly what's called for.

0:36:23.360 --> 0:36:23.839
<v Speaker 2>And this is.

0:36:23.800 --> 0:36:28.759
<v Speaker 1>Something that many user experienced designers have independently discovered, which

0:36:28.800 --> 0:36:31.680
<v Speaker 1>is that people don't always want the results as quickly

0:36:31.680 --> 0:36:34.160
<v Speaker 1>as you can generate them. So take this as an example.

0:36:34.239 --> 0:36:37.680
<v Speaker 1>The people who developed the coinstar machines discover this. These

0:36:37.680 --> 0:36:40.080
<v Speaker 1>are those machines where you dump in a bunch of

0:36:40.160 --> 0:36:42.840
<v Speaker 1>change and accounts the change for you and gives you

0:36:42.880 --> 0:36:46.160
<v Speaker 1>the result. Now, apparently these coinstar machines can do their

0:36:46.239 --> 0:36:48.880
<v Speaker 1>work very quickly, like in a second or two, but

0:36:48.920 --> 0:36:52.760
<v Speaker 1>that speed made customers feel nervous that maybe the counting

0:36:52.880 --> 0:36:58.640
<v Speaker 1>wasn't happening correctly. So Coinstar inserted pre recorded noise of

0:36:58.800 --> 0:37:02.200
<v Speaker 1>change moving through the machine clink clink, clink clink, And

0:37:02.280 --> 0:37:06.359
<v Speaker 1>even though the machine comes to its conclusions rapidly, like

0:37:06.440 --> 0:37:09.600
<v Speaker 1>you have seven dollars and thirty six cents, it purposefully

0:37:10.080 --> 0:37:14.120
<v Speaker 1>delays its output so that the counting seems slower. And

0:37:14.160 --> 0:37:18.000
<v Speaker 1>this is an interesting form of theater, one which our

0:37:18.080 --> 0:37:22.480
<v Speaker 1>machines perform in the time domain, and this is not uncommon.

0:37:22.520 --> 0:37:27.720
<v Speaker 1>Apparently ATM machines insert an artificial delay for a similar reason.

0:37:28.160 --> 0:37:29.799
<v Speaker 1>You stick in your card and you say you want

0:37:29.840 --> 0:37:33.520
<v Speaker 1>one hundred bucks, and the machine words and clicks and

0:37:33.600 --> 0:37:37.600
<v Speaker 1>turns for a while. There's no necessity, like a computational

0:37:37.680 --> 0:37:41.600
<v Speaker 1>or mechanical necessity, for ATM machines to be so slow,

0:37:41.920 --> 0:37:46.720
<v Speaker 1>but apparently customers are more satisfied when the money doesn't

0:37:46.760 --> 0:37:51.400
<v Speaker 1>come out instantly, and software designers increasingly have to deal

0:37:51.760 --> 0:37:56.000
<v Speaker 1>with inserting artificial delays because of the speed of computation.

0:37:56.120 --> 0:37:59.920
<v Speaker 1>So there was one company that builds software that creates

0:38:00.120 --> 0:38:02.920
<v Speaker 1>an online blog for you with the design and the

0:38:02.920 --> 0:38:06.400
<v Speaker 1>title page and templates for your blog posts. And what

0:38:06.440 --> 0:38:09.040
<v Speaker 1>they found was that when users got to the end

0:38:09.160 --> 0:38:12.240
<v Speaker 1>of their inputs and clicked to the button that said

0:38:12.600 --> 0:38:17.120
<v Speaker 1>create my blog, the blog appeared for the user instantly,

0:38:17.239 --> 0:38:20.160
<v Speaker 1>and users felt confused. They weren't sure if something was

0:38:20.200 --> 0:38:23.560
<v Speaker 1>wrong or if something had broken. So after some testing,

0:38:24.160 --> 0:38:27.560
<v Speaker 1>the software company added a page in the middle that

0:38:27.640 --> 0:38:32.040
<v Speaker 1>said creating your blog and had a spinning wheel, and

0:38:32.080 --> 0:38:35.600
<v Speaker 1>then after about seven seconds, it would send users to

0:38:35.680 --> 0:38:39.200
<v Speaker 1>their newly minted blog page, and users felt much more

0:38:39.239 --> 0:38:43.280
<v Speaker 1>satisfied just based on the delay, just based on things

0:38:43.320 --> 0:38:47.720
<v Speaker 1>happening at a timescale that they were comfortable with. Now,

0:38:48.120 --> 0:38:52.360
<v Speaker 1>why are users of coinstar and ATM machines and blog

0:38:52.440 --> 0:38:57.200
<v Speaker 1>software happier with a delay? Sometimes designers will point out

0:38:57.200 --> 0:39:00.719
<v Speaker 1>that a user might have anxiety about it service, like

0:39:00.960 --> 0:39:03.640
<v Speaker 1>is the coinstar counting all my coins correctly? Or is

0:39:03.680 --> 0:39:06.960
<v Speaker 1>the ATM giving me the right amount of money? Or

0:39:07.440 --> 0:39:10.799
<v Speaker 1>building a blog must be a really complicated thing, and

0:39:10.840 --> 0:39:14.239
<v Speaker 1>so the best strategy is to address this anxiety by

0:39:14.320 --> 0:39:18.640
<v Speaker 1>convincing them that everything is running at a careful pace.

0:39:19.160 --> 0:39:20.960
<v Speaker 1>I think that's a pretty good hypothesis, but I think

0:39:21.000 --> 0:39:23.319
<v Speaker 1>there might be something else going on here, and it's

0:39:23.320 --> 0:39:25.160
<v Speaker 1>not just about anxiety.

0:39:25.440 --> 0:39:27.440
<v Speaker 2>I think this might be an expression.

0:39:26.960 --> 0:39:30.680
<v Speaker 1>Of how we value things and how that pivots on

0:39:30.760 --> 0:39:34.200
<v Speaker 1>what I have called the effort phenomenon. I discussed this

0:39:34.239 --> 0:39:36.440
<v Speaker 1>way back in episode six.

0:39:36.200 --> 0:39:39.839
<v Speaker 2>About AI and why we value a.

0:39:39.960 --> 0:39:43.560
<v Speaker 1>Book written by a person much more than a book

0:39:43.600 --> 0:39:46.600
<v Speaker 1>written by AI, even if the exact same words.

0:39:47.200 --> 0:39:48.279
<v Speaker 2>It's not clear.

0:39:48.040 --> 0:39:50.319
<v Speaker 1>Why we would value one over the other. But the

0:39:50.360 --> 0:39:53.560
<v Speaker 1>suggestion I made is that we care very much about

0:39:53.600 --> 0:39:57.319
<v Speaker 1>the effort that goes into something. For example, take two

0:39:57.360 --> 0:40:00.360
<v Speaker 1>pieces of art. Let's say someone makes a replica of

0:40:00.400 --> 0:40:05.880
<v Speaker 1>a Michelangelo statue entirely by gluing quarters together in a

0:40:05.960 --> 0:40:09.880
<v Speaker 1>giant three dimensional structure, and someone else puts a single

0:40:09.920 --> 0:40:13.319
<v Speaker 1>red dot in the middle of a canvas. How much

0:40:13.360 --> 0:40:16.080
<v Speaker 1>would you pay for these two different pieces of art.

0:40:16.440 --> 0:40:19.800
<v Speaker 1>Presumably you would pay more for that which you believe

0:40:19.960 --> 0:40:24.239
<v Speaker 1>took more effort. And in the same way, the coinstar

0:40:24.440 --> 0:40:28.000
<v Speaker 1>or the ATM machine or the blog post can give

0:40:28.040 --> 0:40:31.879
<v Speaker 1>you the illusion that it has just put in a

0:40:31.920 --> 0:40:36.160
<v Speaker 1>lot of effort. It's just pulling a sleight of hand

0:40:36.239 --> 0:40:39.520
<v Speaker 1>in the time domain, but it's enough to align with

0:40:39.640 --> 0:40:44.839
<v Speaker 1>your human expectations of what hard work looks like. It

0:40:44.920 --> 0:40:48.919
<v Speaker 1>lines up better with your internal model of how hard

0:40:48.960 --> 0:40:51.880
<v Speaker 1>it would be for you to count a bunch of

0:40:51.960 --> 0:40:56.759
<v Speaker 1>coins or bills, or program a blog template from scratch.

0:40:57.440 --> 0:40:59.759
<v Speaker 1>And so it's fascinating that if the machine or the

0:40:59.800 --> 0:41:03.880
<v Speaker 1>software it doesn't give you this false delay, that actually

0:41:03.920 --> 0:41:07.480
<v Speaker 1>diminishes how much you think the service is worth. And

0:41:07.480 --> 0:41:11.239
<v Speaker 1>this becomes like a temporal touring test. You remember, the

0:41:11.280 --> 0:41:14.280
<v Speaker 1>touring test is whether you can tell if a conversation

0:41:14.400 --> 0:41:17.160
<v Speaker 1>partner is a human or a computer. And I think

0:41:17.320 --> 0:41:21.480
<v Speaker 1>increasingly our computers and our devices will have to be

0:41:21.640 --> 0:41:27.239
<v Speaker 1>sensitive to the temporal aspect and slow way down if

0:41:27.280 --> 0:41:34.560
<v Speaker 1>they hope to fool us. Okay, so let's wrap up. Ah,

0:41:34.719 --> 0:41:38.120
<v Speaker 1>there's the next keystroke by the human who was typing.

0:41:38.840 --> 0:41:40.720
<v Speaker 2>That took a very long time.

0:41:41.200 --> 0:41:43.279
<v Speaker 1>So do you remember this thing I said at the

0:41:43.360 --> 0:41:46.319
<v Speaker 1>very beginning, I was imagining that we land on a

0:41:46.360 --> 0:41:48.359
<v Speaker 1>planet for a month and we don't see anything move,

0:41:48.440 --> 0:41:51.400
<v Speaker 1>and we conclude that there are only these tree like

0:41:51.440 --> 0:41:53.640
<v Speaker 1>things on the planet, and we blast off because it's

0:41:53.680 --> 0:41:56.359
<v Speaker 1>not so interesting. But it turns out that they live

0:41:56.400 --> 0:42:01.640
<v Speaker 1>on a much slower timescale, millionions of times slower, but

0:42:01.719 --> 0:42:06.160
<v Speaker 1>they have societies and loves and wars and clubs, and

0:42:06.200 --> 0:42:09.920
<v Speaker 1>it's just that to us, we wouldn't even recognize something

0:42:10.040 --> 0:42:13.040
<v Speaker 1>moving at that slow pace. So here we are in

0:42:13.080 --> 0:42:17.279
<v Speaker 1>the twenty first century, giving birth to a new species.

0:42:17.320 --> 0:42:24.160
<v Speaker 1>We're sparking new machines into existence and to our electronic progeny.

0:42:25.000 --> 0:42:27.440
<v Speaker 2>We are the tree People.

0:42:32.360 --> 0:42:35.560
<v Speaker 1>Go to Eagleman dot com slash podcast for more information

0:42:35.719 --> 0:42:38.759
<v Speaker 1>and to find further reading. Send me an email at

0:42:38.840 --> 0:42:42.239
<v Speaker 1>podcasts at eagleman dot com with questions or discussion, and

0:42:42.360 --> 0:42:45.840
<v Speaker 1>check out and subscribe to Inner Cosmos on YouTube for

0:42:45.960 --> 0:42:49.479
<v Speaker 1>videos of each episode and to leave comments until next time.

0:42:49.680 --> 0:42:52.960
<v Speaker 1>I'm David Eagleman, and we have been traveling together in

0:42:53.040 --> 0:43:02.200
<v Speaker 1>the Inner Cosmos in th