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Speaker 1: Could you learn to fly a helicopter not by practicing,

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Speaker 1: but instead by uploading the information directly into your brain?

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Speaker 1: What would society do if kids no longer had to

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Speaker 1: go to school? And what does any of this have

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Speaker 1: to do with suntan booths or nano robots or torking

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Speaker 1: over a presidential address or what a cowboy on a

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Speaker 1: hill is simply not able to see. Welcome to Inner

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Speaker 1: Cosmos with me David Eagleman. I'm a neuroscientist and author

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Speaker 1: at Stanford and in these episodes we sail deeply into

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Speaker 1: our three pound universe to understand why and how our

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Speaker 1: lives look the way they do. Today's episode is about

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Speaker 1: the potability of really coming to understand the tangled forest

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Speaker 1: of eighty six billion neurons in your head and the

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Speaker 1: trillions of connections between them. And if we could do that,

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Speaker 1: could we upload information directly into your brain? Could we

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Speaker 1: speed up education this way? Now? At the moment, this

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Speaker 1: is all pure fantasy because we simply don't have the

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Speaker 1: technology to allow us to do that. But the question

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Speaker 1: we're going to ask today is whether this is theoretically

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Speaker 1: possible and something we can look forward to around the

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Speaker 1: corner of the next century, and what are the caveats,

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Speaker 1: the things to watch out for, and the unexpected complexities here.

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Speaker 1: So let's get started some hundreds of years ago and

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Speaker 1: still in many impoverished places in the world, children of

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Speaker 1: the species Homo sapiens reproduce by the time they are

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Speaker 1: young teens. But this situation is it's totally different in

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Speaker 1: modern times and modern societies. Now, young people go to

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Speaker 1: school for their first eighteen years or twenty one years,

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Speaker 1: and increasingly twenty five or twenty six years for an

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Speaker 1: advanced degree, and in fields like medicine, they take another

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Speaker 1: several years of internship and residency. And in a field

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Speaker 1: like neuroscience research people do a postdoctoral fellowship and then

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Speaker 1: they hope to become an assistant professor, and then an

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Speaker 1: associate professor and finally a full professor. And most people

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Speaker 1: are in their forties by the time they get there.

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Speaker 1: So what accounts for this recent historical change. Why do

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Speaker 1: we do so much schooling for so much of our

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Speaker 1: lives now? Well, it's because we are a runaway species.

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Speaker 1: We've gone off in a totally different direction than all

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Speaker 1: our animal cousins, and we have made thousands of important

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Speaker 1: discoveries about our world and produced so much art invarious forms,

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Speaker 1: And as a result, there's so much to learn, and

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Speaker 1: so we need to spend decades in institutions of learning,

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Speaker 1: not to mention, reading books and listening to podcasts to

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Speaker 1: understand what millions of humans have devoted their lives to

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Speaker 1: figuring out. But what if there were a way that

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Speaker 1: we didn't have to do that? What if there were

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Speaker 1: a way to simply upload the information, in other words,

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Speaker 1: to put the information directly into your brain. So let's

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Speaker 1: harken back to this great scene in The Matrix where

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Speaker 1: Neo and Trinity are being hotly pursued by the antagonist,

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Speaker 1: agent Smith, and our two heroes end up on top

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Speaker 1: of a building, and there they spy a helicopter parked

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Speaker 1: on the roof, and Neo asks Trinity do you know

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Speaker 1: how to fly that? And she replies not yet, And

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Speaker 1: she flips open her phone and she calls Tank, the operator,

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Speaker 1: and she says, I need a pilot program for a

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Speaker 1: B two twelve helicopter, And we see the operator rotate

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Speaker 1: his chair in front of his bank of computers and

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Speaker 1: he quickly types out a bunch of commands, and she

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Speaker 1: closes her eyes and one second later she turns confidently

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Speaker 1: to Neo and says, let's go. So what happened is

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Speaker 1: that Tank the operator had taken the expertise, the complicated

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Speaker 1: know how of flying a B two twelve helicopter and

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Speaker 1: just uploaded it to her brain. So the question we're

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Speaker 1: going to ask today is is that theoretically possible from

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Speaker 1: a neuroscience perspective, and what will make that straightforward? And

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Speaker 1: what will make that not straightforward to accomplish someday. Now,

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Speaker 1: in some ways, the whole idea sounds crazy because it

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Speaker 1: seems like we always have to earn things if we

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Speaker 1: want changes to our brains or body. You can't just

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Speaker 1: get something for free. But of course, people for decades

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Speaker 1: have been climbing in into suntan booths instead of spending

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Speaker 1: days outside, and people get botox, which binds to receptors

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Speaker 1: the ends of peripheral nerves and changes the wrinkliness of

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Speaker 1: your face. And people are increasingly doing things to not

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Speaker 1: have to go to the gym but instead to have

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Speaker 1: your abdominal muscles built for you with electrical stimulation. You

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Speaker 1: just lie on the table and your muscles contract over

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Speaker 1: and over and The idea is that your muscles can

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Speaker 1: grow stronger and look better without you having to do

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Speaker 1: a single sit up. You just lie there. So what

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Speaker 1: would be the equivalent in the realm of education? Can

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Speaker 1: we imagine a time when you don't have to bury

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Speaker 1: yourself in a book to master some domain, where you

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Speaker 1: don't have to spend hundreds of hours sitting in a

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Speaker 1: flight simulator, but instead you hook something up to your

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Speaker 1: brain and then it is as though you already knew

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Speaker 1: quantum mechanics or electrical engineering, or Persian history, or how

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Speaker 1: to serve for hang glide or repair that model of

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Speaker 1: dishwasher or whatever. Now, how would you push information to

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Speaker 1: the brain? We currently do this by sitting down dozens

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Speaker 1: of children in front of someone who already has the

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Speaker 1: information in their brain, and that person uses words or pictures,

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Speaker 1: and the students attend to those stimuli and try to

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Speaker 1: translate those words or pictures into changes in their own

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Speaker 1: private jungle of billions of neurons. They try to convert

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Speaker 1: what they're hearing or seeing into storage in their own

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Speaker 1: internal model in a way that makes sense to them.

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Speaker 1: What learning means is that you very finely change the

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Speaker 1: networks in your head. That's it. That's what we pay

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Speaker 1: lots of tuition for and go off to college for

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Speaker 1: to get someone who already has information in their network

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Speaker 1: to translate it through the low bandwidth channel of language

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Speaker 1: over to your network. So, just to be clear on this,

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Speaker 1: before you know some factor concept, your network is configured

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Speaker 1: in some way, and then I tell you, oh, that

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Speaker 1: dog's name is Nebula, and then you encode that information.

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Speaker 1: This connection in your brain gets strengthened and this one

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Speaker 1: gets weakened, and this synapse unplugs, it replugs over there,

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Speaker 1: and this happens over millions of synapses, and then you

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Speaker 1: know something that you did not know before. And for

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Speaker 1: deeper knowledge, like flying a B two twelve helicopter, this

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Speaker 1: requires not just the memory of a fact, but of

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Speaker 1: a procedure. And so those changes happen in different brain

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Speaker 1: areas and they're more widespread. But what is required in

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Speaker 1: all these forms of learning are simply changes in the

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Speaker 1: patterns of your network, presumably just the synaptic connections, but

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Speaker 1: maybe other details as well, like which neurotransmitter receptors are

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Speaker 1: being expressed on the membranes and whatever. But that's it,

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Speaker 1: that's what it means. To learn something. So is there

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Speaker 1: any way to implement those changes besides the old fashioned

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Speaker 1: way of sitting for a semester in a classroom or

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Speaker 1: spending hours in the helicopter flight simulator. Well, there's been

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Speaker 1: a lot of excitement about brain machine interfaces, such as

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Speaker 1: the brain electrodes that are implanted robotically by the company Neurallink.

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Speaker 1: So I'll just take a quick moment to clarify the

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Speaker 1: landscape of electrodes in the brain. Even though neuralink hit

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Speaker 1: the news recently. The first thing to note is that

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Speaker 1: these brain machine interfaces have been around for many decades

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Speaker 1: since people started inserting electrodes. These are just thin metal

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Speaker 1: wires into the brain. The idea is that you just

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Speaker 1: insert this electrode into the neural tissue and you listen

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Speaker 1: to the electrical activity of the cells. And researchers pretty

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Speaker 1: quickly figured out that if you send a little bit

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Speaker 1: of electricity down the wire down this electrode, you can

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Speaker 1: stimulate the cell to make it active where it pops

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Speaker 1: off its own little electrical spikes that travel around. So

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Speaker 1: you put in some electricity and it goes And this

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Speaker 1: is the technology behind, for example, deep brain stimulation you

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Speaker 1: might have heard of this. Take Parkinson's disease. There's a

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Speaker 1: tiny brain region called the subthalamic nucleus, and it was

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Speaker 1: discovered starting from work in the nineteen seventies that you

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Speaker 1: can insert your electrode into this area and zap it

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Speaker 1: with a bit of electricity and you get these amazing

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Speaker 1: effects of the movement problems of Parkinson's essentially disappearing. And

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Speaker 1: by the way, the reason you can stick an electrode

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Speaker 1: into the brain is because the brain doesn't have any

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Speaker 1: pain receptors, so you can just dunk the little metal

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Speaker 1: wire right in there after you've opened a little portal

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Speaker 1: in the skull. So what's happening when you put these

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Speaker 1: little bursts of electricity in is that the cells fire,

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Speaker 1: which has effects on the rest of the network that

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Speaker 1: those cells are connected to, and it also changes the

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Speaker 1: electrical oscillations. And why this works so well in Parkinson's

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Speaker 1: is still a bit of a mystery, but you get

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Speaker 1: what you want out of it, and people have been

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Speaker 1: using this sort of brain stimulation for all kinds of purposes.

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Speaker 1: For example, my colleague Helen Mayberg puts electrodes directly into

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Speaker 1: a very specific area near the singulate gyrus, and she

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Speaker 1: stimulates and can pull people out of deep clinical depression

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Speaker 1: this way. So there are many labs and clinics using

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Speaker 1: the technique of stimulating individual cells in the brain, and

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Speaker 1: the direction of the technology over the past couple of

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Speaker 1: decades has been getting more and more electrodes implanted, so

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Speaker 1: that you're not just hitting one or a few cells

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Speaker 1: at the tip of the electrode, but you're instead exciting

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Speaker 1: tens or hundreds or eventually thousands of cells by using

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Speaker 1: a whole specific collection of electrodes. And companies like Neuralink

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Speaker 1: have become famous in the public eye because of the

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Speaker 1: idea of sewing these electrodes very finely into the brain

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Speaker 1: and getting a thousand of them and soon more than that.

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Speaker 1: And in all these cases, the electrodes can read and write,

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Speaker 1: in other words, they can record the activity in the

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Speaker 1: brain cells, but they can also stimulate the brain cells

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Speaker 1: to put activity in there. So once you have the

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Speaker 1: electrodes in there, could you just send in the right

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Speaker 1: zaps of electricity in just the right pattern, spread over

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Speaker 1: millions of neurons with precise timing of your patterns in

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Speaker 1: such a way that you shape the network so that

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Speaker 1: you can fly a helicopter. Now, all that sounds pretty

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Speaker 1: exciting as a theoretical possibility, but I think there are

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Speaker 1: two major technical hurdles here to be able to stimulate

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Speaker 1: lots and lots of cells in the brain in the

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Speaker 1: way that you might want to upload helicopter instructions. The

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Speaker 1: first is simply a physical challenge. The brain is very delicate,

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Speaker 1: and so Mother Nature has surrounded it in the armored

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Speaker 1: plating of the skull. So it's very very hard to

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Speaker 1: get at this fragile, delicate tissue of the brain, and

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Speaker 1: so if you want to insert an electrode, you have

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Speaker 1: to actually drill a small hole in the skull to

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Speaker 1: expose the brain and then you can put your electrode in.

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Speaker 1: The difficulty is that there are eighty six billion neurons,

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Speaker 1: and at the moment, even with our fanciest technology, we

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Speaker 1: can only get to say a thousand of these at

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Speaker 1: any time, and so that is useless in terms of

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Speaker 1: actually having access to the whole system. It would be

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Speaker 1: equivalent to if you really wanted to say something to

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Speaker 1: all eight billion people on the planet, but you only

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Speaker 1: had one hundred followers on social media. The huge majority

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Speaker 1: of the world will have no idea that you've ever

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Speaker 1: said anything, or that you even exist. And that's the situation.

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Speaker 1: When you zap a few hundred neurons, the other tens

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Speaker 1: of billions of neurons don't even know that you're knocking

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Speaker 1: on the door. So to actually insert information into the brain,

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Speaker 1: you'd somehow need to access all or at least most

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Speaker 1: of the neurons to make any meaningful change. Now, I'm

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Speaker 1: not yet addressing how you would know what you want

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Speaker 1: to change, where I'll come back to that in a moment.

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Speaker 1: Let's just imagine for now that you know exactly what

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Speaker 1: you want to tweak in the brain. Now, I do

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Speaker 1: think that in the future there may be a very

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Speaker 1: different solution besides electrodes to this issue of manipulating the network,

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Speaker 1: because I don't think the idea of dunking electrodes in

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Speaker 1: there is ever going to be a long term solution.

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Speaker 1: When I squint into the future, I think the solution

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Speaker 1: is something like nano robots. So what are nano robots.

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Speaker 1: The idea is that you use atomically precise three D

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Speaker 1: printing to make little molecular machines out of atoms. Essentially,

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Speaker 1: you make little robots that carry out some functions, so

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Speaker 1: they're like little robots, but they're microscopically small, built out

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Speaker 1: of individual atoms, by the way, which is what proteins are. Anyway,

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Speaker 1: you could make these super durable, for example by printing

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Speaker 1: them out of carbon, making them diamond robots. The idea,

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Speaker 1: and this is probably not for several decades. The idea

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Speaker 1: is that you swallow a pill with tens of billions

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Speaker 1: of these little nano robots in there, and they float

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Speaker 1: through your bloodstream and you give them the right FedEx

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Speaker 1: labels to pass the blood brain barrier, and once they're

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Speaker 1: in there in the brain, they wiggle their way into

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Speaker 1: your neurons where they can read the activity and they

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Speaker 1: can cause the cell to spike to fire signal whenever

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Speaker 1: they need to. So, with proper signaling between the nanobots,

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Speaker 1: using for example, mesh networking, you could in theory generate

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Speaker 1: whatever patterns you needed to across the entire brain, and

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Speaker 1: if your science is really advanced, then you hit the

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Speaker 1: correct brain wide patterns that will cement in the knowledge

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Speaker 1: of how to fly a B two twelve. Now, although

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Speaker 1: this is not happening anytime soon, it certainly seems plausible

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Speaker 1: that this could be in our future. But wait, there's

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Speaker 1: actually a difficult twist to this story. I said before

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Speaker 1: there are two technical hurdles, and here comes the second.

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Speaker 1: And that hurdle is that there won't be a single

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Speaker 1: program for flying a B two twelve helicopter. Why not,

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Speaker 1: because the brain inside each of us is totally unique.

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Speaker 1: We each have a massive forest of eighty six billion

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Speaker 1: euro on each with ten thousand connection points reaching out

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Speaker 1: and interacting with other trees. And it's a living forest

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Speaker 1: such as each connection, every twig on every branch finds

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Speaker 1: its place in life based on the exact details of

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Speaker 1: what you have seen and heard and experienced in your life.

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Speaker 1: You born in your hometown, with your family, your neighborhood,

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Speaker 1: your culture, your moment in history. All those things determine

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Speaker 1: the exact wiring of your brain. And your brain has

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Speaker 1: a network that is different from his brain over there,

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Speaker 1: and her brain over there, and everyone else's brain on

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Speaker 1: the planet. And the exact wiring is what makes you you.

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Speaker 1: So in the proposed future of the Matrix, the operator

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Speaker 1: Tank would have to specify that he wants a program

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Speaker 1: to pilot a B two twelve helicopter that is specified

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Speaker 1: exact exactly for Trinity's brain, that is bespoke for her

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Speaker 1: neural network only. And if Tank tried to upload the

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Speaker 1: same program to Neo's brain or Morpheus's brain, who knows

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Speaker 1: what that would result in. Because if the program alters

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Speaker 1: the way that neuron nineteen million, three hundred fifty six

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Speaker 1: three hundred and two is talking to its neighbors, and

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Speaker 1: it does this over a million other neurons with high specificity,

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Speaker 1: that might teach Trinity how to fly a helicopter, but

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Speaker 1: it certainly would not work for someone else whose brain

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Speaker 1: is different. So how do we get around that problem,

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Speaker 1: the problem of everyone having a unique neural network. Well,

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Speaker 1: the answer will have to rely on what is called

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Speaker 1: system identification. This is an engineering approach where you have

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Speaker 1: some complicated dynamic system and you measure lots of input

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Speaker 1: output pairs, as in, when I put this in, what happens? Okay,

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Speaker 1: now it happens if I put that in. So imagine

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Speaker 1: you find a really complicated machine and you don't know

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Speaker 1: exactly what it does. So you tap one of the

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Speaker 1: keys and you see how it moves, and then you

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Speaker 1: tap three of the keys at the same time, and

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Speaker 1: you look at what it does as its output, and

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Speaker 1: then you hit a series of the keys and you

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Speaker 1: see what results. And you do this over and over

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Speaker 1: and over to try to figure out what is the

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Speaker 1: structure under the hood. This system identification approach is used

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Speaker 1: in lots of fields. For example, in economics, let's say

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Speaker 1: you want to figure out the guts of the stock market.

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Speaker 1: So you take lots of inputs like gross domestic product

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Speaker 1: and inflation and unemployment and interest rates and blah blah blah,

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Speaker 1: and you look at all these as inputs and you

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Speaker 1: look at the reaction of the market this way, and

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Speaker 1: you develop better and better mathematical models of what the

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Speaker 1: machinery of the stock market is doing, even though you

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Speaker 1: can't see it. Okay, So the question is, could you

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Speaker 1: do system identification on a human brain. No one's ever

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Speaker 1: really done this because there's no purpose for it now,

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Speaker 1: but someday it might make sense. So the idea is

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Speaker 1: you go into a super futuristic brain scanner and you

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Speaker 1: get lots of inputs, and this sophisticated brain imaging device

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Speaker 1: measures the outputs, in other words, which cells in your

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Speaker 1: brain are responding. So you see a rapid series of

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Speaker 1: images and you hear words, and you feel touches on

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Speaker 1: your body, and you smell smells, and you run through

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Speaker 1: thousands or maybe millions of little micro experiences while your

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Speaker 1: brain is getting measured. And in theory, this is how

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Speaker 1: a scientist could say, Aha, Trinity's brain is organized like this,

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Speaker 1: while Neo's brain is laid out like that, and Morpheus's

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Speaker 1: brain has a slightly different pattern, And you might find

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Speaker 1: that for teaching the operation of a B two twelve helicopter,

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Speaker 1: in his brain thinks about it in analogy to riding

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Speaker 1: a horse and controlling it, which let's say she grew

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Speaker 1: up riding horses, while Neo's brain would learn the helicopter

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Speaker 1: in analogy to the way a motorcycle feels, which is,

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Speaker 1: let's say how he grew up. And for Morpheus, the

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Speaker 1: actions of piloting emerge from his deep knowledge of surfing,

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Speaker 1: which is how he grew up and what is stored

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Speaker 1: in his brain. Now, it's not clear how many inputs

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Speaker 1: you'd have to ping in there to get high enough

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Speaker 1: resolution to make all the little changes you need, but

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Speaker 1: presumably that would get figured out with enough experimentation. Okay,

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Speaker 1: so let's say we as a society grow to a

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Speaker 1: point where we can do system identification on an individual's

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Speaker 1: brain and then use nanobots to upload knowledge of helicopter piloting.

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Speaker 1: I need to emphasize that this is not right around

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Speaker 1: the corner, but it certainly seems the theoretically plausible. Another

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Speaker 1: century of advancement, and suddenly the network that makes you

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Speaker 1: can get directed and shaped in a bespoke manner. And

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Speaker 1: if we come to a point where we can do it,

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Speaker 1: that's possibly the biggest societal change. I can imagine you

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Speaker 1: say to your three year old kid, Okay, we're gonna

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Speaker 1: upload first grade now. Great, Now, go play outside for

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Speaker 1: an hour, and then we're gonna upload second grade after lunch.

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Speaker 1: Imagine that by the end of the week, your three

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Speaker 1: year old knows as much as a full professor does. Now,

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Speaker 1: so what becomes of society and the way we run

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Speaker 1: it now? You may think the analogy here is to

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Speaker 1: look at super smart, genius kids in our current world,

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Speaker 1: But these kids often go off to attend college at

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Speaker 1: twelve years old, and they very often end up lonely

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Speaker 1: and socially misplaced, because really what they want is to

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Speaker 1: play with their colleagues other kids their age, But they

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Speaker 1: get stuck with a bunch of older kids who have

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Speaker 1: gone through puberty and are running deeply carved evolutionary programs

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Speaker 1: that cause their brains to be taken over by sexuality,

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Speaker 1: and that software hasn't yet turned on in the heads

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Speaker 1: of these young genuses, and as a result, they can't

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Speaker 1: mesh with what is happening around them, and they can

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Speaker 1: feel very lonely in these contexts. But the future scenario

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Speaker 1: of uploading knowledge is totally different because now every single

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Speaker 1: kid can stay among colleagues. But the question is if

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Speaker 1: education is uploaded, what do the kids do all day?

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Speaker 1: Do they launch startups at the age of six, do

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Speaker 1: they write epic novels by the time they're eight years old?

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Speaker 1: Do they return to reproducing as teenagers like their distant

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Speaker 1: ancestors did? And is it dangerous that they have all

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Speaker 1: the knowledge of decades of schooling but without the maturity.

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Speaker 1: The most slowly developing part of the brain is the

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Speaker 1: prefrontal cortex, and this underlies our ability to simulate possible

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Speaker 1: futures and think about consequences. So imagine a kid with

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Speaker 1: an undeveloped prefederal cortex who has all the knowledge that

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Speaker 1: Albert Einstein commanded at midlife. But this child lacks the

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Speaker 1: ability to simulate consequences, so they think something like, wouldn't

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Speaker 1: it be hilarious to build a small nuclear bomb and

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Speaker 1: blow up my neighbor's porch, Or wouldn't it be a

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Speaker 1: crackup to disrupt the presidential broadcast by hijacking the frequency

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Speaker 1: and imposing a video of me twerking or whatever? Because

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Speaker 1: children don't yet have a fully developed profederal cortex that

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Speaker 1: can't simulate consequences the way an adult can, and this

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Speaker 1: is why it could be dangerous to inject the knowledge

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Speaker 1: of an adult into a child's brain. Now, perhaps I'm

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Speaker 1: being shortsighted here, and we could somehow upload maturity as well.

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Speaker 1: We could figure out the learning that translates to morally

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Speaker 1: complex situations and simulate those over and over do the

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Speaker 1: synaptic equivalent of working through the possibilities and feeling the consequences.

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Speaker 1: Maybe you could massively speed up emotional learning that way.

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Speaker 1: After all, as my father would always tell me, the

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Speaker 1: wise person learns from experience, but the wiser person learns

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Speaker 1: from the experience of others. So maybe there could be

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Speaker 1: enough uploaded knowledge where a kid understands various possible scenarios

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Speaker 1: and outcomes, and the good decision making simply results from

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Speaker 1: a deep knowledge of previous examples, things that have happened

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Speaker 1: to other people, all of which have been uploaded. So

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Speaker 1: maybe the maturity problem could be taken care of, but

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Speaker 1: still we're looking at massive societal shifts that would render

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Speaker 1: our current civilization totally unrecognizable. Now, we all like to

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Speaker 1: be very thoughtful about the future, but it doesn't matter

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Speaker 1: what we speculate about it, because we are guaranteed to

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Speaker 1: be wrong. We can only envision what we're capable of,

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Speaker 1: in this case, a cartoonish version of a bunch of

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Speaker 1: super intelligent kids running around while their parents go off

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Speaker 1: to their jobs. But the world is likely to be

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Speaker 1: very different by then. Presuming that everything is massively sped

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Speaker 1: up by artificial intelligence, it seems very possible that society

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Speaker 1: is going to evolve exponentially faster at a pace that

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Speaker 1: we really can't conceive of here in the first third

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Speaker 1: of the twenty first century. I mean, just imagine that

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Speaker 1: AI knocks down scientific problems rapidly, such that we move

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Speaker 1: from our current state of pretty wide spread ignorance to perfect,

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Speaker 1: wonderful models of everything in the cosmos. Just think about

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Speaker 1: the incredibly slow pace between the Stone Age and the

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Speaker 1: Bronze Age, and then the Bronze Age to the Silver Age.

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Speaker 1: Now imagine this pace goes up by a thousandfold or

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Speaker 1: a millionfold. So we find ourselves a few decades from

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Speaker 1: now in the Diamond Age, where we can manipulate carbon

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Speaker 1: atoms however we like. And then a few years later

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Speaker 1: we're past that and into a new era where we

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Speaker 1: can entangle photons and find ourselves in the quantum age

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Speaker 1: and so on. Like everyone, I love to speculate about

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Speaker 1: the future, but the truth is that it is impossible

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Speaker 1: to picture what things will become and how quickly. And

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Speaker 1: I want to share an example. Last month here in

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Speaker 1: Silicon Valley, I saw a black and white photograph from

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Speaker 1: nineteen forty. It was a man on horseback ambling up

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Speaker 1: a dirt road on a hills and there was nothing

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Speaker 1: particularly special about this sandy hill with its scrubbrush. So

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Speaker 1: I was intrigued to read the caption and find out

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Speaker 1: that this little dirt road was sand Hill Road. Now

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Speaker 1: you may know that sand Hill Road is nowadays a

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Speaker 1: road almost as famous as Wall Street in New York.

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Speaker 1: Sand Hill Road is where many of the world's most

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Speaker 1: elite venture capitalists do their business. They invest hundreds of billions.

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Speaker 1: This road is the mecca for startups who are seeking investment. Now,

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Speaker 1: the thing that was so striking to me is that

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Speaker 1: for the horseman sauntering up this sandy hillside in nineteen

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Speaker 1: forty in the hot sun, there's no way he could

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Speaker 1: have imagined that the lonely hoof prints he was leaving

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Speaker 1: would in just sixty years mark this spot of one

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Speaker 1: of the world's economic engines. And there's no way he

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Speaker 1: could have envisioned what advances would get funded on that spot.

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Speaker 1: The worldwide light speed network that allows anyone on the

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Speaker 1: planet to effortlessly communicate to anyone else, or rectangles that

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Speaker 1: everyone would carry in their pocket like a handkerchief or

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Speaker 1: a tobacco tin. But these rectangles would contain the accumulated

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Speaker 1: knowledge of all humankind. Or satellites or quantum computers or

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Speaker 1: blockchain cryptocurrencies, or large language models that could read every

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Speaker 1: book ever written. None of these would be even vaguely

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Speaker 1: imaginable to the cowboy in nineteen forty, moving slowly up

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Speaker 1: the hill. We are blind to the future. I often

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Speaker 1: wish I could talk to whoever is listening to this

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Speaker 1: historical podcast in the year twenty eighty four, because the

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Speaker 1: world will be so different by then, and I am

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Speaker 1: incapable of imagining it. And it's not just that we

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Speaker 1: are not being creative about extrapolating technology curves into the future.

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Speaker 1: It's that there will be new technologies and novel sciences

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Speaker 1: and new convergences that will make it intrinsically unpredictable. There

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Speaker 1: will be serendipitous discoveries and socioeconomic changes and geopolitical events.

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Speaker 1: While we always make guesses based on our current trends

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Speaker 1: and research, the future is shaped by hundreds of things

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Speaker 1: we just can't see. Not only that, but you've heard

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Speaker 1: me speak before about our limited perspective, our inability to

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Speaker 1: see past the fence line of what we already know.

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Speaker 1: Our current knowledge understanding are based on the technologies and

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Speaker 1: paradigms that exist right now, so it's really hard for

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Speaker 1: us to anticipate breakthroughs or paradigm shifts that are going

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Speaker 1: to radically alter our society in the future. But this

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Speaker 1: idea of putting information directly into the brain, that's it

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Speaker 1: certainly seems like that could be a big shift. So

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Speaker 1: when we think about the future, it's more than just

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Speaker 1: adults like us riding around on a spaceship with a

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Speaker 1: robot or two. Things are guaranteed to be weirder than

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Speaker 1: we expect. While brain uploads our science fiction right now,

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Speaker 1: assuming we don't blow ourselves up, this inevitably seems like

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Speaker 1: it will become science fact. So let's wrap this up.

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Speaker 1: This episode is not about what's going to happen anytime soon,

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Speaker 1: but I think it is inevitably what will happen in

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Speaker 1: the future. After all, the brain is made of billions

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Speaker 1: of cells, each one of which is very complicated, and

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Speaker 1: each is connected in very complicated patterns. But fundamentally, learning

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Speaker 1: and memory take place in the changes of connectivity, and

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Speaker 1: as far as we can tell, that's all learning is.

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Speaker 1: So what we talked about is the way that the

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Speaker 1: jungle of neurons in your head is wired up differently

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Speaker 1: than in your friend's head because you have different genetic predispositions,

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Speaker 1: and more importantly, you have different experiences in life. So

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Speaker 1: in order to upload any changes into your network, we'd

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Speaker 1: have to know your brain in exquisitely fine detail, and

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Speaker 1: we'd have to know those patterns right now, because it's

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Speaker 1: just a little bit different than it was yesterday. But

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Speaker 1: in theory, if we had this information and understood the

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Speaker 1: language of the connections, we could dial knobs here and

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Speaker 1: there in a million other spots, strengthening or weakening synapta connections,

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Speaker 1: tickling the genome to express a little more neurotransmit or

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Speaker 1: receptor over here, a little less over there, and after

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Speaker 1: that you might be able to suddenly possess some knowledge

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Speaker 1: you didn't have before. Now, obviously, society will have to

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00:31:48,600 --> 00:31:52,160
Speaker 1: be very careful about this technology when that century comes,

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Speaker 1: because in theory, you could use it to implant false memories,

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Speaker 1: or to erase knowledge, or to do any number of

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Speaker 1: nefarious things. So we will enter a very strange time,

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Speaker 1: and like every technology, a whole raft of protections and

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00:32:09,680 --> 00:32:13,520
Speaker 1: legislation will grow up around it. Again, this is likely

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Speaker 1: impossible to achieve in our generation because of the size

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Speaker 1: of the problem. It would take about a zetabyte of

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Speaker 1: information to store the detailed structure of one human brain,

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Speaker 1: and that, by the way, would only tell you the

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Speaker 1: structure of the forest of neurons, but wouldn't even tell

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Speaker 1: you anything about their individual details, like which genes are

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Speaker 1: getting expressed and which proteins are getting put where. So

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Speaker 1: for us, the citizens of the twenty first century, this

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00:32:41,680 --> 00:32:46,120
Speaker 1: is likely to be an unsolvably huge problem to capture

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Speaker 1: a detailed description of an individual brain. But as a species,

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Speaker 1: we're in an interesting situation because we can see that

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Speaker 1: this is all coming, and we can speculate on the

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Speaker 1: size of the changes this will have on society writ large. Now,

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Speaker 1: what I find amazing is our guaranteed inability to correctly

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Speaker 1: picture this future world, even though it will be populated

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Speaker 1: by our own great grandchildren. Given all this, I think

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Speaker 1: the only specific prediction we can make is that we

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Speaker 1: have more in common with our ancestors two million years

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Speaker 1: ago than we do with our descendants two hundred years

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Speaker 1: from now. In the meantime, go to eagleman dot com

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Speaker 1: slash podcast for more information and to find further reading.

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Speaker 1: Send me an email at podcast at eagleman dot com

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Speaker 1: with questions for discussion, and check out and subscribe to

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00:33:49,200 --> 00:33:53,160
Speaker 1: Inner Cosmos on YouTube for videos of each episode and

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00:33:53,240 --> 00:33:57,000
Speaker 1: to leave comments. Until next time. I'm David Eagleman, and

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Speaker 1: this is Inner Cosmos. You and not you. You