Stanford Neuroscientist: Can’t Remember Your Dreams? Your Brain May Be Warning You!

Full Transcript

https://www.youtube.com/watch?v=m-nnyNZ0TQ0

[00:00] After many many decades of people debating this, you might have figured out the reason why we dream.
[00:05] Yes.
[00:05] And it's a simple answer.
[00:07] So if you go blind, the visual cortex in the back of the brain gets taken over by hearing and by touch and by other things.
[00:13] In fact, our colleagues at Harvard did an experiment where they blindfolded normally cighted people.
[00:18] And you could start seeing that takeover happening after 60 minutes.
[00:21] And that's when we realized, wow, the purpose of dreaming is to defend the visual territory from takeover from the other senses.
[00:29] But what fascinates me about brain plasticity and what I've devoted my career to is figuring out the way that we can be the sculptors of our own brains and how it gives us an opportunity to become the kind of person we would like to be.
[00:40] And can we do that?
[00:42] Yes.
[00:42] Here's the thing.
[00:44] Your brain peaked at the age of two.
[00:47] Okay.
[00:47] So at the beginning you've got fluid intelligence, meaning you could learn anything.
[00:51] But now that you have grown up in this world, you've got crystallized intelligence, meaning you know how to drive a car.
[00:55] You know how to operate a cell phone.
[00:57] You know how to run a business.
[00:58] And so your brain doesn't require as much change which means that
[01:02] require as much change which means that the structure of the brain is always
[01:04] the structure of the brain is always degenerating.
[01:05] degenerating.
[01:06] So what are the set of actions that will fundamentally change my brain and make me that type of person who's motivated and disciplines and who has high agency and attacks the world.
[01:13] So this is something I've studied in my lab for decades now.
[01:18] And the key is that
[01:18] and what about AI and the social media debate as it relates to brain development?
[01:22] Well, I happen to be a cyber optimist for young people.
[01:25] I think it's going to make them much smarter than the generation that came before.
[01:28] And here's why.
[01:33] Interesting.
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[02:33] Dr. David Eagleman, what made you so fascinated about the brain? And why should everybody listening be fascinated about the brain as well?
[02:38] Here's what I think it is.
[02:40] When I was 8 years old, I fell off of the roof of a house that was under construction and I fell 12 feet and broke my nose on the floor below.
[02:48] But the whole thing seemed to take a long time.
[02:52] I did the calculation and figured out that it only took 6 of a second to get from the top to the bottom.
[02:56] And I couldn't figure out why it seemed to have taken so long.
[02:59] So I think that got me really interested in perception and the machinery by which we
[03:05] perception and the machinery by which we view the world and taken in and what is
[03:07] view the world and taken in and what is actually real versus what's a
[03:10] actually real versus what's a construction of the brain.
[03:12] construction of the brain. And that's how what I've devoted my career to is
[03:13] how what I've devoted my career to is figuring out how the brain which is
[03:15] figuring out how the brain which is locked inside the skull. It's about
[03:18] locked inside the skull. It's about three pounds. How it constructs this
[03:20] three pounds. How it constructs this model of the world and which things we
[03:22] model of the world and which things we can take as reality and which things we
[03:25] can take as reality and which things we shouldn't.
[03:26] shouldn't. >> I think most people don't even know they
[03:27] I think most people don't even know they have a there's a brain there almost. It
[03:29] have a there's a brain there almost. It sounds like a strange thing to say, but
[03:31] sounds like a strange thing to say, but we've never really most of us haven't
[03:32] we've never really most of us haven't really seen our own brains at all. We've
[03:34] really seen our own brains at all. We've never been able to touch our own brains
[03:35] never been able to touch our own brains at all. So, it's it's easy to fall into
[03:38] at all. So, it's it's easy to fall into the trap of thinking that everything I
[03:41] the trap of thinking that everything I experience is true and is reality. So,
[03:43] experience is true and is reality. So, I'm wondering how a deeper understanding
[03:45] I'm wondering how a deeper understanding of all this stuff can help me live a
[03:46] of all this stuff can help me live a better life.
[03:47] better life. >> Yeah. One of the things that I started
[03:50] Yeah. One of the things that I started writing about years ago is that I think
[03:51] writing about years ago is that I think we're not I think we often think of
[03:55] we're not I think we often think of ourselves as individuals, meaning not
[03:57] ourselves as individuals, meaning not divisible into other things. But really,
[04:01] divisible into other things. But really, you are a team of rivals. So, you've got
[04:04] you are a team of rivals. So, you've got all these neural networks that have
[04:06] all these neural networks that have different drives making different suggestions to you.
[04:09] suggestions to you.
[04:09] What's a neural network?
[04:10] What's a neural network?
[04:10] Um, so in the brain, you've got 86 billion cells called neurons.
[04:12] And these are communicating with each other at a blindingly fast rate.
[04:15] Many of these cells are hooked up in networks.
[04:17] So, they're, you know, this guy's talking to this guy and this guy, and they're all in particular networks.
[04:20] The thing is, you can actually get competing networks.
[04:25] So, for example, Stephen, if I drop some chocolate chip cookies in front of you, part of your brain wants to eat it.
[04:29] It's a good energy source.
[04:31] Part of your brain says, "Don't eat it. I'll gain weight."
[04:33] Part of you says, "Okay, I'll eat one, but I'll go to the gym tonight."
[04:34] The point is you are arguing with yourself.
[04:35] You are conflicted.
[04:37] This is what makes humans so interesting is that we have all these voices trying to drive us to different conclusions about our behavior.
[04:38] The way that your ship of state moves depends on the vote of the neural parliament at any time.
[04:41] So understanding this I think is really critical to navigating our own lives because all of
[05:06] navigating our own lives because all of us do things where retrospectively we regret it.
[05:08] us do things where retrospectively we regret it.
[05:10] We say I shouldn't have eaten that whole bag of chips or done the you know the alcohol or the drugs or what like everybody has regrets all the time with things and it's because you have different voices in charge at different times.
[05:13] that whole bag of chips or done the you know the alcohol or the drugs or what like everybody has regrets all the time with things and it's because you have different voices in charge at different times.
[05:15] like everybody has regrets all the time with things and it's because you have different voices in charge at different times.
[05:17] with things and it's because you have different voices in charge at different times.
[05:20] different voices in charge at different times.
[05:22] Okay.
[05:24] times. Okay.
[05:26] Part of what this leads to is what we call the Ulisses contract.
[05:30] So a Ulisses contract is where you do something now to prevent yourself from behaving badly in the near future.
[05:31] contract is where you do something now to prevent yourself from behaving badly in the near future.
[05:33] to prevent yourself from behaving badly in the near future.
[05:36] Just as an example, you know, when people go to Alcoholics Anonymous, the first thing they're told is clear all the alcohol out of the house.
[05:38] you know, when people go to Alcoholics Anonymous, the first thing they're told is clear all the alcohol out of the house.
[05:39] Anonymous, the first thing they're told is clear all the alcohol out of the house.
[05:41] is clear all the alcohol out of the house.
[05:43] Because even if you feel like, look, I'm in a moment of sober reflection.
[05:43] look, I'm in a moment of sober reflection.
[05:46] I don't want to ever drink again.
[05:47] If you have alcohol in the house, you're going to bust into that cabinet at some point on a festive Saturday night or a lonely Sunday night or whatever.
[05:49] have alcohol in the house, you're going to bust into that cabinet at some point on a festive Saturday night or a lonely Sunday night or whatever.
[05:50] on a festive Saturday night or a lonely Sunday night or whatever.
[05:53] So, what you do is you constrain your future behavior by setting things up in the right way so your future uh the future you can't behave badly.
[05:55] do is you constrain your future behavior by setting things up in the right way so your future uh the future you can't behave badly.
[05:58] by setting things up in the right way so your future uh the future you can't behave badly.
[06:01] your future uh the future you can't behave badly.
[06:03] We naively think, okay,
[06:06] behave badly.
[06:06] We naively think, okay, well, I know who I am.
[06:08] I'm just one person.
[06:10] But but you're not.
[06:10] And under different circumstances, you're tempted by different things and you'll do different kinds of behavior.
[06:16] So having a sense of what's going on under the hood gives us an opportunity to be more closely aligned with the kind of person we would like to be
[06:24] because it feels like there's just one well I do argue with myself in my head sometimes but it feels like there is just one me
[06:32] and so when I hear that voice say Steve you should have that cookie and it's 1:00 a.m.
[06:37] And then the other voice says, "No, you shouldn't."
[06:38] I think it's kind of the same person just tussling with himself,
[06:41] right?
[06:43] Well, but that tustling with himself implies different political parties that are all battling it out.
[06:47] You know, when you look at a parliament, you've got all these political parties that all love their country.
[06:50] They just have different ideas of how to steer it.
[06:53] And this is what's going on uh in in the brain all the time.
[06:57] So, what does one do about that?
[06:58] How do I make do I do I have to make a list contract?
[07:03] I think it's very useful to make that sort of thing.
[07:05] But also just understanding oneself.
[07:05] I mean part of
[07:07] understanding oneself.
[07:08] I mean part of the you know there was this Greek admonition to know thyself.
[07:11] This was a sign they had in various places, various temples and stuff.
[07:15] But I think that becomes know thyelves.
[07:19] And the better we know ourselves, the more we can get rid of the illusion that we are one person.
[07:23] Because all any of us need to do is look back on our behavior to say, "Oh yeah, in some circumstances I would do that.
[07:29] and other circumstances I think is a terrible idea.
[07:33] So this is all to the goal of understanding who you are.
[07:36] What are the big misconceptions about the brain that people have gone through their life believing?
[07:40] I mean that's one of them.
[07:41] Something that is true that kind of could fall in place of that is just this fundamental idea that our brains are plastic or sort of adaptable.
[07:50] Because when I found out that I could change my brain by what I do, I found that to be really really inspiring.
[07:56] Yes, that that's exactly right.
[07:58] So brain plasticity, if someone hasn't heard that term before, it sounds like a weird term, but the reason it came about 100 years ago is because the great psychologist William James pointed out
[08:07] psychologist William James pointed out that, you know, if you take a piece of plastic,
[08:09] you know, if you take a piece of plastic, what we like about that plastic,
[08:10] what we like about that material that we call plastic is that material that we call plastic is that you can mold it into a shape and it'll hold that shape.
[08:14] And that's what your brain does.
[08:16] So if I ask you the name of your third grade teacher, you can remember that name even though it's been a long time because your neural networks changed and held on to that piece of information.
[08:25] Okay?
[08:27] Well, our whole lives our brains are changing every moment.
[08:30] So now we have certain doors that close at different times.
[08:33] So just as an example, um you need to learn language in the first several years of your life.
[08:36] If you don't learn language, you can never get the concept of language.
[08:39] Your brain will never figure that out.
[08:48] >> You're not saying you can't learn a new language as an adult.
[08:49] You're saying the concept of >> the concept of language, the concept that I can name things and I can ask for things and so on.
[08:53] Just that never clicks in the brain.
[08:55] For example, in Romania at the fall of Chuchescu, there were tens of thousands of kids in the orphanages because their parents had been killed.
[09:05] It was too many kids.
[09:06] And so the staff
[09:09] It was too many kids.
[09:09] And so the staff there said, "Look, the kids will get, you know, clingy if you pay too much attention to them.
[09:13] So here's what we're going to do.
[09:14] We're going to feed the kids, but we're not going to hold them and we're not going to talk to them.
[09:18] And all these children grew up with real cognitive deficits as a result.
[09:20] Here's the thing about brain plasticity.
[09:23] Human beings have a a similar brain to all our neighbors in the animal kingdom.
[09:25] If you compare our brain to a horse brain, a dog brain, anything like that, it's the same general structures and stuff.
[09:33] But what we have is much more of the wrinkly outer bit called the cortex.
[09:38] It's the outer 3 mm.
[09:40] And maybe we'll come back to why that matters so much.
[09:43] But the other thing that mother nature tweaked with us, it's small genetic tweaks.
[09:46] But we have much more plasticity, adaptability such that when a horse drops into the world, it's doing the same thing that horses did 100,000 years ago.
[09:50] It's just, you know, eat mate.
[09:53] But when a human drops in the world, we learn everything that's happened before us.
[09:56] And then we springboard off the top of that.
[09:57] So we living in the 21st century, we say, "Oh
[10:11] living in the 21st century, we say, "Oh great, you know, physics, math, this, that, art, blah, blah, great.
[10:13] We got that, art, blah, blah, great.
[10:14] We got everything that's happened before us.
[10:15] Now let's do our own thing."
[10:17] And that's what's so special about the plasticity of the human brain, the adaptability of it.
[10:19] The downside, the gamble is that mother nature drops human brains into the world kind of halfbaked and we then get to absorb everything.
[10:25] But in the rare circumstance where you're not getting the right input, then then that ends up really in trouble because it's only halfbaked.
[10:37] So when it comes to language, we can learn multiple languages when we're young.
[10:41] That's very easy, but it gets harder and harder as that goes along.
[10:43] And various other things become harder.
[10:44] And here's why.
[10:46] It's because I I mentioned this earlier, but the job of the brain is to make a model of the world so it can operate within it.
[10:48] So, for example, you're an entrepreneur and you love doing business.
[10:50] So, you get it.
[10:53] You okay, here's how, you know, here's how you structure business.
[10:55] Here's how you hire.
[10:57] Well, here's how you set up a board.
[11:00] Well, you're doing everything because
[11:11] Well, you're doing everything because you've got a really rich internal model of how to structure a business.
[11:15] That's what the brain wants to do is get that stuff right.
[11:21] As a result, if you suddenly ended up, you know, taking a trip to Mars and there's a whole very different society there that does businesses very differently, you would have to relearn stuff really quickly.
[11:32] So, here's the thing.
[11:35] You went from having a brain that had high fluid intelligence to now having a brain that has high crystallized intelligence.
[11:42] What that means is at the beginning you can learn anything.
[11:46] You could learn any language.
[11:47] You could have dropped into any area.
[11:49] You could have dropped into 13th century Japan when I was young.
[11:51] When you were young, when you were a baby, if you had dropped out of the womb in, you know, 10th century Mongolia, you would have said like, "Okay, cool. Learn lang."
[12:01] You would you would be a 10th century Mongolian.
[12:03] But as it happens, you dropped into this era, you know, a certain place and time and neighborhood and culture and family.
[12:07] And so you learn that that's who you become is that
[12:11] that that's who you become is that person.
[12:14] We often think that plasticity diminishes as you age.
[12:17] But it's not simply that it's diminishing.
[12:19] It's that you are getting the right answers about how to operate in the world.
[12:24] And so you don't have to change as much.
[12:26] Your brain doesn't require as much change.
[12:28] What if I want to change?
[12:30] Yes.
[12:32] So it turns out you still can change.
[12:35] That's the key is that the reason brains change less and less is because they don't have to.
[12:40] But when things get upside down, just as one example, everything about the pandemic really stunk, except for one thing, I think the tiny silver lining is that all of us had to reassess.
[12:54] Oh my gosh, wait, how is the world working?
[12:55] I thought I knew how the world worked, but now I don't know if there's going to be toilet paper at the store.
[12:59] I don't know if the bank's going to be open.
[13:00] I don't know if I can get coffee at the coffee shop.
[13:04] Like, everything was different.
[13:06] As awful as it was, it's really useful to challenge your internal model of the world and get to do that as an adult.
[13:11] We
[13:13] world and get to do that as an adult.
[13:13] We don't usually get to.
[13:15] don't usually get to.
[13:15] So, if I want to change, what would you recommend that I do?
[13:16] So, if I want to change, what would you recommend that I do?
[13:18] If I want to if I want to change who I am, say I'm stubborn, I'm not motivated,
[13:20] want to change who I am, say I'm stubborn, I'm not motivated,
[13:22] um, and I want to be a different person.
[13:24] um, and I want to be a different person.
[13:24] The key is challenge.
[13:24] The key is seeking challenge.
[13:26] The key is challenge.
[13:26] The key is seeking challenge.
[13:28] So, it turns out that where we always want to be is in between the levels of frustrating but achievable.
[13:31] we always want to be is in between the levels of frustrating but achievable.
[13:33] and you want to take on new tasks.
[13:33] You want to seek novelty to find yourself in that zone and push yourself to do things that you just haven't done before.
[13:35] and you want to take on new tasks.
[13:37] You want to seek novelty to find yourself in that zone and push yourself to do things that you just haven't done before.
[13:40] that you just haven't done before.
[13:40] And one of the things that's so wonderful about the modern world, you know, everyone's got complaints about the internet and social media and stuff like that, but the good news is it deep it exposes you to so much more than you ever even knew was out there.
[13:42] And one of the things that's so wonderful about the modern world, you know, everyone's got complaints about the internet and social media and stuff like that, but the good news is it deep it exposes you to so much more than you ever even knew was out there.
[13:44] one of the things that's so wonderful about the modern world, you know,
[13:46] about the modern world, you know, everyone's got complaints about the internet and social media and stuff like that, but the good news is it deep it exposes you to so much more than you ever even knew was out there.
[13:47] everyone's got complaints about the internet and social media and stuff like that, but the good news is it deep it exposes you to so much more than you ever even knew was out there.
[13:48] internet and social media and stuff like that, but the good news is it deep it exposes you to so much more than you ever even knew was out there.
[13:51] that, but the good news is it deep it exposes you to so much more than you ever even knew was out there.
[13:53] exposes you to so much more than you ever even knew was out there.
[13:53] The key is to actively seek those challenges and seek new things and seek to become expert in various sorts of fields.
[13:56] The key is to actively seek those challenges and seek new things and seek to become expert in various sorts of fields.
[13:58] to actively seek those challenges and seek new things and seek to become expert in various sorts of fields.
[14:00] seek new things and seek to become expert in various sorts of fields.
[14:00] And I think the key is that once you become good at something, you you have to drop that and take on something you're not good at.
[14:02] And I think the key is that once you become good at something, you you have to drop that and take on something you're not good at.
[14:04] and I think the key is that once you become good at something, you you have to drop that and take on something you're not good at.
[14:07] become good at something, you you have to drop that and take on something you're not good at.
[14:08] to drop that and take on something you're not good at.
[14:08] This is the best thing that you can do for your brain.
[14:10] This is the best thing that you can do for your brain.
[14:12] thing that you can do for your brain.
[14:12] The reason is because what you're doing
[14:14] The reason is because what you're doing is you're constantly building new roadways and pathways in the brain.
[14:17] There's a study that's been going on for for decades now called the religious orders study where a bunch of Catholic nuns agreed to donate their brains for autopsy when they passed away.
[14:26] What the researchers discovered when they look at the brain carefully is that some fraction of these nuns had Alzheimer's disease.
[14:37] Their brains were physically degenerating with the ravages of of this dementia, but they didn't show any of the cognitive deficits that one normally has.
[14:45] They didn't seem to be having memory problems and so on.
[14:49] It turns out it's because all these nuns lived in these convents till the day they died.
[14:55] They had social challenges and they had fights with their fellow sisters and they played games with their fellow sisters and they were they had chores and responsibilities and they were doing stuff.
[15:05] What that means is even as the tissue the brain tissue was physically degenerating, they were making new roadways and bridges all the time.
[15:15] And so that's what kept them cognitively healthy.
[15:15] We call that cognitive reserve.
[15:17] healthy.
[15:17] We call that cognitive reserve.
[15:19] Contrast this with with people who retire at 65 and they go home and they
[15:21] watch television and their social
[15:23] circles shrink and so on.
[15:25] That's when you've really got concerns because
[15:27] you're not building the new pathways.
[15:29] Is there data to support that that when you
[15:31] retire, if you retire early or if you
[15:33] retire say in your 60s, it increases
[15:36] your probability of an earlier death or
[15:38] cognitive decline?
[15:41] Almost certainly with cognitive decline because you're just
[15:43] not getting the challenge at that point.
[15:45] You're just coasting on your internal
[15:47] model.
[15:48] this.
[15:50] It's tragic, but what happens often is that people's hearing gets
[15:51] worse.
[15:53] And so by the time they retire, let's say in their mid-60s, it's not
[15:55] really that fun for them to go out to
[15:56] parties and restaurants anymore because
[15:58] they can't quite hear.
[16:00] And so there there all these converging reasons why
[16:02] their social lives shrink.
[16:04] But it turns out social life is one of the most
[16:07] important things that we can do for our
[16:08] brains because there's an expression we
[16:11] sometimes use in neuroscience, which is
[16:12] that nothing is as hard for the brain as
[16:14] other people.
[16:14] because you never know
[16:15] other people.
[16:17] because you never know what the other person's going to say and what the other person's going to say and do and how they'll react emotionally and so on.
[16:19] do and how they'll react emotionally and so on.
[16:21] So, you're constantly on your toes with other people.
[16:22] And if you're not doing that anymore, that ends up being a problem.
[16:25] being a problem.
[16:27] >> H interesting.
[16:31] And as a as a I'm 33 years old, so if you were to plot where my brain is on like a graph of decline,
[16:33] old, so if you were to plot where my brain is on like a graph of decline,
[16:37] I is it the case that I should be doing as much as I can now to build as many pathways I can so that when I'm 80, my decline sort of levels out in a in a better place?
[16:38] as much as I can now to build as many pathways I can so that when I'm 80, my decline sort of levels out in a in a better place?
[16:44] pathways I can so that when I'm 80, my decline sort of levels out in a in a better place?
[16:46] decline sort of levels out in a in a better place?
[16:49] Oh yeah, for for sure. But this is true for many reasons actually.
[16:51] this is true for many reasons actually.
[16:53] Okay, so look, the truth is your brain peaked at two at the age of two because that's when you get the most connections between neurons, between these cells in the brain.
[16:56] peaked at two at the age of two because that's when you get the most connections between neurons, between these cells in the brain.
[16:58] between neurons, between these cells in the brain.
[17:00] You get this, at first you're born with these 86 billion neurons and they connect and connect and connect and it finally becomes like a overgrown garden at the age of two and from there you're pruning.
[17:03] at first you're born with these 86 billion neurons and they connect and connect and connect and it finally becomes like a overgrown garden at the age of two and from there you're pruning.
[17:05] born with these 86 billion neurons and they connect and connect and connect and it finally becomes like a overgrown garden at the age of two and from there you're pruning.
[17:07] they connect and connect and connect and it finally becomes like a overgrown garden at the age of two and from there you're pruning.
[17:09] it finally becomes like a overgrown garden at the age of two and from there you're pruning.
[17:10] garden at the age of two and from there you're pruning.
[17:12] From there you're taking connections away.
[17:14] Now it happens that that's not a bad thing.
[17:16] that's not a bad thing.
[17:16] That's a good thing because that's how you're resonating with the world that you are in.
[17:21] you know, 21st century London and LA versus, you know, 10th century Mongolia because you're you're just strengthening those pathways that resonate and you're getting rid of everything else.
[17:32] Okay, fine.
[17:32] But over time, your brain cells die.
[17:36] You know, every time you hit your head on something or whatever, your brain cells are going down.
[17:40] Um, so in that sense, you've peaked.
[17:40] But your crystallized intelligence that you've been building your whole life, you know, that keeps going and you'll you'll have decades ahead of you where you can start doing stuff.
[17:51] But yes, the reason to learn everything you can is because all that stuff cashes out at various points in your life when you're starting your next business or you're, you know, wanting to do the next great thing where you're surfing the way web of AI.
[18:04] You know, you'll say, "Oh, I learned this thing when I was 16.
[18:06] I learned this thing when I was 22."
[18:07] And and these are these are paying off now.
[18:10] I think I heard Andrew Hubman say that one of the most fascinating discoveries of the last century is a particular part of the
[18:16] century is a particular part of the brain called the anterior mid-sul cortex.
[18:19] brain called the anterior mid-sul cortex and it links to what you were saying a second ago about challenge and doing things that are difficult.
[18:23] things that are difficult.
[18:25] Yeah, it turns out that area of the brain is involved and other networks as well because when you're doing something new and challenging and difficult, you have stress and anxiety.
[18:34] Your whole brain is active.
[18:37] Let's say I measured your brain even with something like EEG, electronphilography.
[18:42] That's where I stick electrodes on the outside.
[18:44] Let's say I measure your brain in my brain.
[18:45] We're doing something that let's say you're an expert at what's something you're really good at juggling.
[18:50] I don't know some physics.
[18:53] Let's go for juggling.
[18:54] Okay.
[18:55] Let's say you're an expert juggler.
[18:56] Let's say I've never juggled.
[18:58] Okay.
[18:59] If we're both juggling, you're going to be much better than I am.
[19:01] But your brain will be less active.
[19:04] You won't have as much activity in your brain.
[19:06] all my brain is on fire with activity because why I'm trying to figure out okay where do I put my hand how do I throw this and blah blah blah.
[19:13] so when I'm in novice at something my brain is using much more activity not
[19:18] brain is using much more activity not just the anterior made singulate but just the anterior made singulate but tons of activity all over because I'm tons of activity all over because I'm trying to figure out the rules I'm trying to figure out the rules I'm trying to figure out what's going on you trying to figure out what's going on you as an expert you know you got it you as an expert you know you got it you don't you don't need to burn much activity this is what the brain's goal activity this is what the brain's goal is is to say hey once I've practiced is is to say hey once I've practiced something along once I get something something along once I get something about the world I'm going to burn it about the world I'm going to burn it deeper and deeper into the circuitry So deeper and deeper into the circuitry So I don't have to burn a lot of energy on I don't have to burn a lot of energy on it.
[19:38] it.
[19:38] On this part of the brain, the anterior mid singular cortex, Andrew human was saying it's larger in people that do things that they basically don't want to do hard things.
[19:47] If you spend your life doing things you don't want to do, then it happens to be bigger.
[19:49] And so people have now thought of this part of the brain almost like the willpower muscle because for some reason those that are doing hard things have bigger ones and those that are not have smaller ones.
[19:58] I mean it wouldn't be so much the willpower of muscle.
[20:00] It would be some indication retrospectively of how hard you have worked.
[20:04] Look, the fact is you can see changes in brain size with lots of things.
[20:09] I'll give you an example.
[20:11] If you are a pianist, if you play piano, then we can actually see physical changes in your motor cortex.
[20:16] This is
[20:18] changes in your motor cortex. This is the part of the brain essentially
[20:20] the part of the brain essentially underneath where you would wear
[20:21] underneath where you would wear headphones. For those who are looking
[20:22] headphones. For those who are looking visually, it's this red part here. You
[20:25] visually, it's this red part here. You actually get a bigger loop of tissue
[20:28] actually get a bigger loop of tissue here than you do in a normal brain. Why?
[20:31] here than you do in a normal brain. Why? Because you're doing so much fine motor
[20:33] Because you're doing so much fine motor activity with your fingers with both
[20:35] activity with your fingers with both hands. Okay? In contrast, if you're a
[20:38] hands. Okay? In contrast, if you're a violinist,
[20:40] violinist, you're only really doing that kind of
[20:41] you're only really doing that kind of detailed activity with one hand. The
[20:42] detailed activity with one hand. The other hand is just boeing. And so you
[20:44] other hand is just boeing. And so you only get that activity here in one half
[20:47] only get that activity here in one half of the brain for violinists. So I can
[20:49] of the brain for violinists. So I can look at a brain and tell, hey, is the
[20:51] look at a brain and tell, hey, is the person a pianist or a violinist or an
[20:53] person a pianist or a violinist or an either? I can tell just by looking at
[20:54] either? I can tell just by looking at the visual cortex because you see
[20:56] the visual cortex because you see changes in the brain based on what you
[21:00] changes in the brain based on what you do. For example, jugglers, people who
[21:02] do. For example, jugglers, people who play music, even you can tell this with
[21:04] play music, even you can tell this with medical students who study for final
[21:05] medical students who study for final exams. You actually see changes in the
[21:07] exams. You actually see changes in the distribution of of their cortex.
[21:10] distribution of of their cortex. >> Why would it be getting bigger?
[21:12] >> Why would it be getting bigger? >> The reason is the brain's devoting more
[21:14] >> The reason is the brain's devoting more real estate to that. In this case, let's
[21:17] real estate to that. In this case, let's say we're talking about fingers on a
[21:18] say we're talking about fingers on a piano or a violin. The brain is devoting
[21:20] piano or a violin. The brain is devoting more there's more relevance to that and
[21:24] more there's more relevance to that and so it more real estate so that you can
[21:26] so it more real estate so that you can do it better in the future.
[21:28] do it better in the future. >> Exactly. The key about the cortex this
[21:30] >> Exactly. The key about the cortex this wrinkly outer part is that it is a
[21:32] wrinkly outer part is that it is a one-trick pony. This is often overlooked
[21:34] one-trick pony. This is often overlooked because even this brain that I'm holding
[21:36] because even this brain that I'm holding here uh is colorcoded so that we think
[21:39] here uh is colorcoded so that we think oh okay that's clearly labeled this
[21:40] oh okay that's clearly labeled this that's clearly labeled that and so on.
[21:42] that's clearly labeled that and so on. But in fact it's all the same stuff and
[21:45] But in fact it's all the same stuff and it can change. So for instance, if you
[21:47] it can change. So for instance, if you are born blind, then this area that we
[21:50] are born blind, then this area that we normally call the visual cortex gets
[21:52] normally call the visual cortex gets taken over by the rest of the brain. If
[21:54] taken over by the rest of the brain. If you're born deaf, then this part that we
[21:56] you're born deaf, then this part that we call the auditory cortex gets taken
[21:58] call the auditory cortex gets taken over. It gets devoted to other tasks.
[22:00] over. It gets devoted to other tasks. And so this whole system is very very
[22:03] And so this whole system is very very fluid. And this is what fascinates me
[22:04] fluid. And this is what fascinates me about brain plasticity is the way that
[22:07] about brain plasticity is the way that we can be the sculptors of our own
[22:09] we can be the sculptors of our own brains because we can devote ourselves
[22:13] brains because we can devote ourselves to particular things and have the brains
[22:16] to particular things and have the brains real estate get involved in that. So if
[22:19] real estate get involved in that. So if I was currently someone that couldn't
[22:20] I was currently someone that couldn't get out of bed, I didn't have a lot of
[22:22] get out of bed, I didn't have a lot of discipline or motivation and I wasn't
[22:25] discipline or motivation and I wasn't very good at committing myself to hard
[22:27] very good at committing myself to hard things.
[22:28] things. With everything you know about the
[22:29] With everything you know about the brain, is it possible to take a set of
[22:31] brain, is it possible to take a set of actions that will fundamentally change
[22:33] actions that will fundamentally change my brain and make me that type of person
[22:35] my brain and make me that type of person who runs marathons, who does hard
[22:38] who runs marathons, who does hard things, who's motivated and disciplines,
[22:39] things, who's motivated and disciplines, and who has high agency and attacks the
[22:41] and who has high agency and attacks the world.
[22:42] world. >> Yes. Yeah. But it's much more than
[22:44] >> Yes. Yeah. But it's much more than simply resolve because I mean just look
[22:47] simply resolve because I mean just look at New Year's resolutions. You know, by
[22:49] at New Year's resolutions. You know, by by February, most people have dropped
[22:50] by February, most people have dropped most of them. So, it's really a
[22:52] most of them. So, it's really a psychology problem about figuring out
[22:55] psychology problem about figuring out okay, what are the things that motivate
[22:57] okay, what are the things that motivate me? So, let's say you want to become a
[22:59] me? So, let's say you want to become a marathon runner. You've got that distant
[23:01] marathon runner. You've got that distant dream. You figure out like what actually
[23:03] dream. You figure out like what actually motivates me in the short term? Who am I
[23:05] motivates me in the short term? Who am I trying to impress? What am I trying to
[23:07] trying to impress? What am I trying to accomplish in my life? How can I
[23:10] accomplish in my life? How can I structure things like this Ulyses
[23:12] structure things like this Ulyses contract that I talked about earlier
[23:14] contract that I talked about earlier where I'm actually locking myself into a
[23:16] where I'm actually locking myself into a contract? Like, you know, I call Bob and
[23:19] contract? Like, you know, I call Bob and I say, "I will meet you every morning at
[23:21] I say, "I will meet you every morning at 7:00 and we're going to run until we
[23:23] 7:00 and we're going to run until we drop." Like once I've committed to those
[23:25] drop." Like once I've committed to those sorts of things, that's how you set
[23:27] sorts of things, that's how you set things up so that you do the right
[23:29] things up so that you do the right thing.
[23:29] thing. >> It's a bit of a cycle, right? Because
[23:30] >> It's a bit of a cycle, right? Because then my brain will adapt and then
[23:32] then my brain will adapt and then presumably that will make it easier for
[23:33] presumably that will make it easier for me to run.
[23:34] me to run. >> Yeah.
[23:35] >> Yeah. >> And then I'll run more and then my brain
[23:36] >> And then I'll run more and then my brain will adapt.
[23:37] will adapt. >> That's right.
[23:38] >> That's right. >> And the cycle continues.
[23:39] >> And the cycle continues. >> And it's not just your brain, of course.
[23:40] >> And it's not just your brain, of course. In this case, it's your body. You're
[23:41] In this case, it's your body. You're getting better. You're getting stronger.
[23:42] getting better. You're getting stronger. You don't get as out of breath. And so
[23:44] You don't get as out of breath. And so all these things help. Exactly. But in
[23:46] all these things help. Exactly. But in order to keep the cycle going, you need
[23:48] order to keep the cycle going, you need to figure out what is spinning this
[23:50] to figure out what is spinning this flywheel and what are the all the other
[23:52] flywheel and what are the all the other things in your life. Whether good
[23:54] things in your life. Whether good motivations or bad, it doesn't matter.
[23:56] motivations or bad, it doesn't matter. You just figure out what it is that you
[23:58] You just figure out what it is that you can do to to get there.
[24:00] can do to to get there. >> Are there certain physical exercises
[24:02] >> Are there certain physical exercises that are particularly good for the brain
[24:03] that are particularly good for the brain from what you've understood?
[24:05] from what you've understood? >> The general story is exercise is really
[24:08] >> The general story is exercise is really important for the brain. I'll give you
[24:09] important for the brain. I'll give you just one example of that, which is
[24:11] just one example of that, which is there's still this debate going on about
[24:13] there's still this debate going on about whether we get new neurons in the brain.
[24:16] whether we get new neurons in the brain. The general story has always been you're
[24:18] The general story has always been you're born with 86 billion neurons and those
[24:20] born with 86 billion neurons and those slowly die with time. But in rats, for
[24:24] slowly die with time. But in rats, for example, there is a little trickle of
[24:26] example, there is a little trickle of new cells, new brain cells. And there's
[24:29] new cells, new brain cells. And there's been a debate for a long time about
[24:30] been a debate for a long time about whether that little trickle happens in
[24:32] whether that little trickle happens in humans or not. Still unresolved. But in
[24:34] humans or not. Still unresolved. But in rats, what you can see is that exercise
[24:37] rats, what you can see is that exercise causes the trickle to increase. If you
[24:39] causes the trickle to increase. If you stick the rat on the wheel and it's
[24:41] stick the rat on the wheel and it's doing physical exercise, you get more
[24:43] doing physical exercise, you get more new brain cells. Now, we don't know for
[24:45] new brain cells. Now, we don't know for sure that this happens in humans, but
[24:48] sure that this happens in humans, but lots of things about physical fitness
[24:50] lots of things about physical fitness and exercise matter a lot to the brain.
[24:52] and exercise matter a lot to the brain. This is nothing new. Exercise, sleep,
[24:54] This is nothing new. Exercise, sleep, diet, these are really important things
[24:56] diet, these are really important things for keeping the health of this organ. Is
[24:58] for keeping the health of this organ. Is there anything else that's important to
[25:00] there anything else that's important to know for someone that is trying to
[25:02] know for someone that is trying to change and improve and keep their brain
[25:03] change and improve and keep their brain in a healthy state as they age that we
[25:05] in a healthy state as they age that we haven't touched on?
[25:07] haven't touched on? >> There is something that that all of us
[25:09] >> There is something that that all of us are thinking about which is about um
[25:11] are thinking about which is about um social media and the internet in
[25:13] social media and the internet in general. I do think one of the
[25:14] general. I do think one of the interesting things about the internet
[25:16] interesting things about the internet and social media is that if we were
[25:19] and social media is that if we were growing up in a village 500 years ago,
[25:22] growing up in a village 500 years ago, you just know the people in the village
[25:24] you just know the people in the village and what they can do and so on. But
[25:25] and what they can do and so on. But let's say no one in the village was an
[25:27] let's say no one in the village was an entrepreneur or a neuroscientist. And so
[25:31] entrepreneur or a neuroscientist. And so we we can't even picture that as a
[25:33] we we can't even picture that as a thing. We don't know anything about
[25:34] thing. We don't know anything about that. One thing that the internet has
[25:37] that. One thing that the internet has done for kids growing up in the digital
[25:39] done for kids growing up in the digital age is that you get a lot of more
[25:40] age is that you get a lot of more exposure to things. You you have so much
[25:42] exposure to things. You you have so much more exposure. I actually think this is
[25:44] more exposure. I actually think this is one of the positive things that I would
[25:46] one of the positive things that I would say about social media is that you not
[25:49] say about social media is that you not only get exposure, wow, that kind of
[25:51] only get exposure, wow, that kind of thing is possible and that kind of thing
[25:52] thing is possible and that kind of thing is possible, but you also have people
[25:54] is possible, but you also have people teaching you how to get there.
[25:56] teaching you how to get there. >> They say like, hey, I'm a fitness
[25:57] >> They say like, hey, I'm a fitness influencer and I'm going to show you
[25:58] influencer and I'm going to show you exactly how to do the thing. Or, you
[26:00] exactly how to do the thing. Or, you know, you say, "Hey, here's exactly how
[26:02] know, you say, "Hey, here's exactly how you start a business." Or I say, "Hey,
[26:03] you start a business." Or I say, "Hey, here's the the route that you go through
[26:05] here's the the route that you go through undergrad and grad school to become a
[26:07] undergrad and grad school to become a neuroscientist." And that's great. I
[26:08] neuroscientist." And that's great. I mean, there's just there's so much more
[26:11] mean, there's just there's so much more uh of a talent window now that that
[26:13] uh of a talent window now that that everyone gets exposed to. So, I think
[26:14] everyone gets exposed to. So, I think that makes a better brain.
[26:16] that makes a better brain. >> What are we doing to our children that
[26:18] >> What are we doing to our children that you think we probably shouldn't be doing
[26:19] you think we probably shouldn't be doing as it relates to brain development?
[26:22] as it relates to brain development? >> Here's the thing that's really important
[26:23] >> Here's the thing that's really important about this debate is that nobody really
[26:26] about this debate is that nobody really knows. And I'll tell you why. It's
[26:27] knows. And I'll tell you why. It's because to do anything in science when
[26:29] because to do anything in science when you're saying something about a group,
[26:31] you're saying something about a group, you need to have a control group that
[26:32] you need to have a control group that you're comparing against. And when it
[26:34] you're comparing against. And when it comes to asking the question of, hey,
[26:36] comes to asking the question of, hey, kids growing up now with social media or
[26:38] kids growing up now with social media or the internet, how do they compare to
[26:40] the internet, how do they compare to other brains of kids who don't grow up
[26:42] other brains of kids who don't grow up with that? Well, we don't have a control
[26:43] with that? Well, we don't have a control group unless you look at kids who are
[26:45] group unless you look at kids who are incredibly impoverished or let's say
[26:48] incredibly impoverished or let's say Quakers who don't believe in technology.
[26:51] Quakers who don't believe in technology. And with both those groups, there's a
[26:52] And with both those groups, there's a hundred other important differences. So,
[26:54] hundred other important differences. So, you can't just say, "Oh, look, I'm
[26:56] you can't just say, "Oh, look, I'm comparing to this kid who grew up
[26:57] comparing to this kid who grew up without food and and I'm going to say
[26:59] without food and and I'm going to say there's this difference." Who the heck
[27:00] there's this difference." Who the heck knows why the difference is there? even
[27:02] knows why the difference is there? even a generation ago. There's so many
[27:05] a generation ago. There's so many differences in terms of diet and
[27:06] differences in terms of diet and pollution and politics and blah blah
[27:08] pollution and politics and blah blah blah what like everything that you can't
[27:10] blah what like everything that you can't do it. So I I only mention this because
[27:13] do it. So I I only mention this because I think it's very important. A lot of
[27:14] I think it's very important. A lot of people pipe off with things about oh the
[27:15] people pipe off with things about oh the younger generation their brain this that
[27:17] younger generation their brain this that but we don't actually know and I will
[27:20] but we don't actually know and I will tell you that I happen to be a cyber
[27:23] tell you that I happen to be a cyber optimist on this point about what
[27:25] optimist on this point about what growing up with the internet does for
[27:27] growing up with the internet does for young people. I think it's going to make
[27:28] young people. I think it's going to make them much smarter than the generation
[27:30] them much smarter than the generation that came before. And here's why. It has
[27:32] that came before. And here's why. It has to do with the size of the intellectual
[27:36] to do with the size of the intellectual diet that they can bring in. So when I
[27:38] diet that they can bring in. So when I was a kid, I grew up pre- internet. You
[27:40] was a kid, I grew up pre- internet. You know, I wanted to know stuff. So my mom
[27:42] know, I wanted to know stuff. So my mom would drive me to the library, which was
[27:45] would drive me to the library, which was 25 minutes away, and I would pick up the
[27:46] 25 minutes away, and I would pick up the Encyclopedia Bratannica and I would flip
[27:48] Encyclopedia Bratannica and I would flip through it and hope they had an article
[27:50] through it and hope they had an article about the thing that I wanted to know
[27:51] about the thing that I wanted to know about. And that's how I was able to get
[27:53] about. And that's how I was able to get my little straw of knowledge. But now
[27:57] my little straw of knowledge. But now kids are growing up with access to
[28:00] kids are growing up with access to anything they're interested in. And this
[28:02] anything they're interested in. And this is so good for the brain. And from a
[28:04] is so good for the brain. And from a plasticity point of view, the reason
[28:06] plasticity point of view, the reason this matters is because change happens
[28:08] this matters is because change happens in the brain when you are curious about
[28:11] in the brain when you are curious about something. So when a kid asks a question
[28:13] something. So when a kid asks a question to Alexa or Siri or whatever and they
[28:15] to Alexa or Siri or whatever and they get the answer, that sticks because they
[28:18] get the answer, that sticks because they have the right cocktail of chemicals
[28:19] have the right cocktail of chemicals going on in their head. In contrast,
[28:21] going on in their head. In contrast, when I grew up, I learned tons of just
[28:23] when I grew up, I learned tons of just in case knowledge. I mean, that's all
[28:25] in case knowledge. I mean, that's all that the teachers could teach us is just
[28:27] that the teachers could teach us is just in case you ever need to know this fact,
[28:28] in case you ever need to know this fact, here it is. But kids are in a really
[28:31] here it is. But kids are in a really great situation now. So, there are pros
[28:33] great situation now. So, there are pros and cons to to all this stuff, but I
[28:35] and cons to to all this stuff, but I think I'm very optimistic about what
[28:38] think I'm very optimistic about what this means for the for the warehouse of
[28:41] this means for the for the warehouse of knowledge that that kids can build up
[28:42] knowledge that that kids can build up now. And by the way, I saw an interview
[28:44] now. And by the way, I saw an interview with Isaac Azimoff in 1988. He was the
[28:48] with Isaac Azimoff in 1988. He was the great science fiction writer who wrote
[28:50] great science fiction writer who wrote Foundation and so many other books. And
[28:52] Foundation and so many other books. And he was saying on this show in 1988, he
[28:55] he was saying on this show in 1988, he said, "Look, I envision a day when there
[28:59] said, "Look, I envision a day when there will be one central supercomput and
[29:01] will be one central supercomput and every house will have a cable running to
[29:03] every house will have a cable running to that supercomputer and you can ask any
[29:05] that supercomputer and you can ask any question you want and it knows the
[29:07] question you want and it knows the entirety of humankind's knowledge on
[29:09] entirety of humankind's knowledge on that computer." You know, what he was
[29:11] that computer." You know, what he was foreseeing here was the internet. He got
[29:12] foreseeing here was the internet. He got the details wrong, which doesn't matter.
[29:14] the details wrong, which doesn't matter. The idea is he saw how this would be so
[29:17] The idea is he saw how this would be so incredible for education
[29:20] incredible for education because he pointed out look in any
[29:21] because he pointed out look in any classroom it's going too fast for half
[29:23] classroom it's going too fast for half the kids too slow for the other half of
[29:24] the kids too slow for the other half of the kids and if you could just pursue
[29:27] the kids and if you could just pursue the sphere of humankind's knowledge if
[29:29] the sphere of humankind's knowledge if you could enter in whatever door you
[29:32] you could enter in whatever door you wanted to that's the way to do it
[29:34] wanted to that's the way to do it because you'll be motivated now he
[29:36] because you'll be motivated now he wasn't talking about brain plasticity or
[29:38] wasn't talking about brain plasticity or anything but this is exactly what I'm
[29:39] anything but this is exactly what I'm saying from a brain plasticity point of
[29:41] saying from a brain plasticity point of view really matters
[29:43] view really matters I I'll just mention something which is a
[29:46] I I'll just mention something which is a lot of people are concerned that oh with
[29:48] lot of people are concerned that oh with with AI we're going to get lazy. We
[29:50] with AI we're going to get lazy. We won't you know know how to do anything
[29:51] won't you know know how to do anything anymore because we can outsource it. It
[29:53] anymore because we can outsource it. It just so happens that I I love doing home
[29:54] just so happens that I I love doing home improvement. I'm always fixing my house.
[29:56] improvement. I'm always fixing my house. I have 3xed myself in the last half year
[30:00] I have 3xed myself in the last half year because of AI because I take a picture
[30:02] because of AI because I take a picture of something. I say hey I've never seen
[30:03] of something. I say hey I've never seen this kind of thing before. How does this
[30:04] this kind of thing before. How does this work? Whatever. And chat GPT says oh you
[30:07] work? Whatever. And chat GPT says oh you do this and you take this out and here's
[30:08] do this and you take this out and here's the bolt and blah blah. It's not me
[30:10] the bolt and blah blah. It's not me outsourcing it. It's me being curious
[30:12] outsourcing it. It's me being curious about something and so I remember how to
[30:14] about something and so I remember how to do everything now. I know how to do much
[30:16] do everything now. I know how to do much more than I used to because I like it.
[30:19] more than I used to because I like it. >> What about the you there's been a couple
[30:21] >> What about the you there's been a couple of studies that have come out that say
[30:22] of studies that have come out that say things like your brain's going to
[30:23] things like your brain's going to atrophy if you don't continue to write
[30:25] atrophy if you don't continue to write or um if you just defer all of your
[30:27] or um if you just defer all of your learning to things like chatgbt or other
[30:29] learning to things like chatgbt or other AI models. Um, one I guess one of the
[30:32] AI models. Um, one I guess one of the areas that I think in one of the
[30:34] areas that I think in one of the studies, was it a Stanford study that
[30:36] studies, was it a Stanford study that everyone was talking about where the the
[30:38] everyone was talking about where the the participants used Google and AI and then
[30:41] participants used Google and AI and then they'd learned something themselves.
[30:43] they'd learned something themselves. >> But one of the things I've wondered is
[30:46] >> But one of the things I've wondered is if I'm going through my business life
[30:48] if I'm going through my business life and I'm encountering hard problems and
[30:50] and I'm encountering hard problems and every time I encounter a hard problem, I
[30:51] every time I encounter a hard problem, I drop it into an AI. The AI spits out a
[30:54] drop it into an AI. The AI spits out a textbased answer. I copy and paste that
[30:56] textbased answer. I copy and paste that and send it as my response. presumably
[30:59] and send it as my response. presumably there's some kind of important part of
[31:01] there's some kind of important part of the learning cycle or the you know
[31:03] the learning cycle or the you know neurological development that I'm like
[31:05] neurological development that I'm like foregoing there I'm missing that I
[31:08] foregoing there I'm missing that I probably should you know you said
[31:09] probably should you know you said earlier about doing hard things what I'm
[31:11] earlier about doing hard things what I'm doing there is I'm avoiding the hard
[31:12] doing there is I'm avoiding the hard thing which is like thinking about it
[31:13] thing which is like thinking about it and trying to understand it
[31:15] and trying to understand it >> yeah here's I think the really important
[31:17] >> yeah here's I think the really important distinction there's vicious friction in
[31:20] distinction there's vicious friction in our lives and there's virtuous friction
[31:22] our lives and there's virtuous friction so vicious friction is all the stupid
[31:25] so vicious friction is all the stupid stuff that you have to do like hey
[31:27] stuff that you have to do like hey Stephen for your business I need you to
[31:28] Stephen for your business I need you to cop copy this spreadsheet over here and
[31:30] cop copy this spreadsheet over here and fill in all these cells and and do your
[31:32] fill in all these cells and and do your taxes and whatever. Okay, that if we can
[31:35] taxes and whatever. Okay, that if we can push that off to AI is massively
[31:37] push that off to AI is massively important for for improving human lives.
[31:40] important for for improving human lives. There's really not benefit in vicious
[31:41] There's really not benefit in vicious friction. But virtuous friction is, hey
[31:45] friction. But virtuous friction is, hey Stephen, I really want you to think
[31:46] Stephen, I really want you to think about what is the optimal way to do this
[31:49] about what is the optimal way to do this business. What is the best structure for
[31:51] business. What is the best structure for this? How do we actually go DT to C? How
[31:54] this? How do we actually go DT to C? How do we go B2B on this? What's the what's
[31:56] do we go B2B on this? What's the what's the approach here that we're going to
[31:58] the approach here that we're going to take that you haven't done before that
[32:00] take that you haven't done before that would be amazing? That's virtuous
[32:03] would be amazing? That's virtuous friction because you're really using
[32:04] friction because you're really using your brain to learn stuff that way. So
[32:06] your brain to learn stuff that way. So that's the first distinction that
[32:08] that's the first distinction that matters is get rid of all the busy work.
[32:10] matters is get rid of all the busy work. There's no honor in that. I mean I'll
[32:13] There's no honor in that. I mean I'll just mention in the 1990s there was this
[32:16] just mention in the 1990s there was this big debate about whether we should have
[32:17] big debate about whether we should have kids use desk calculators or not. And
[32:20] kids use desk calculators or not. And thank god that finally got resolved and
[32:21] thank god that finally got resolved and we let kids use calculators so that we
[32:23] we let kids use calculators so that we can learn, you know, couple we can spend
[32:25] can learn, you know, couple we can spend a couple days learning long division,
[32:26] a couple days learning long division, but you don't have to spend six months
[32:27] but you don't have to spend six months on it because who cares? With the
[32:29] on it because who cares? With the virtuous friction, there's real
[32:31] virtuous friction, there's real opportunity to surf the wave of AI so
[32:35] opportunity to surf the wave of AI so that you are figuring out these tough
[32:37] that you are figuring out these tough problems with the aid of somebody who
[32:40] problems with the aid of somebody who cares about your problem and is willing
[32:42] cares about your problem and is willing to talk with you 247 and never gets
[32:44] to talk with you 247 and never gets tired of talking to you about it. And so
[32:46] tired of talking to you about it. And so you are not just copying and pasting,
[32:48] you are not just copying and pasting, but you're working with the AI to come
[32:51] but you're working with the AI to come up with ideas that were beyond what you
[32:53] up with ideas that were beyond what you would have come up with. Because I
[32:55] would have come up with. Because I mentioned earlier about internal models,
[32:57] mentioned earlier about internal models, we have pretty narrow fence lines and
[32:59] we have pretty narrow fence lines and you can think of all these things, but
[33:01] you can think of all these things, but you don't even know what you don't know.
[33:02] you don't even know what you don't know. So, if you can have somebody who's
[33:04] So, if you can have somebody who's willing to talk with you, an expert in
[33:06] willing to talk with you, an expert in all of humankind's knowledge, willing to
[33:08] all of humankind's knowledge, willing to talk with you about it as much as you
[33:10] talk with you about it as much as you want, there's a real opportunity there
[33:12] want, there's a real opportunity there to have a synergy where collectively you
[33:16] to have a synergy where collectively you both come up with a better idea than
[33:18] both come up with a better idea than either of you could have alone. But is
[33:19] either of you could have alone. But is there a way for that relationship to
[33:21] there a way for that relationship to take place so that I actually benefit?
[33:22] take place so that I actually benefit? Because, you know, in the example I
[33:23] Because, you know, in the example I gave, I'm just I take the question I was
[33:25] gave, I'm just I take the question I was asked, I put it into an AI, it gives me
[33:27] asked, I put it into an AI, it gives me an answer, I copy and paste it back to
[33:28] an answer, I copy and paste it back to the person that asked me the question.
[33:30] the person that asked me the question. that would happen if you really didn't
[33:32] that would happen if you really didn't care about the person asking you the
[33:33] care about the person asking you the question or the question. I mean
[33:35] question or the question. I mean >> I mean this is what a lot of people are
[33:36] >> I mean this is what a lot of people are doing like I get so many email because
[33:37] doing like I get so many email because you know we interview a lot of
[33:38] you know we interview a lot of candidates who join the business and so
[33:39] candidates who join the business and so I see tens of thousands of emails
[33:41] I see tens of thousands of emails sometimes a week that I mean I don't see
[33:43] sometimes a week that I mean I don't see all of them but the ones that I see I
[33:44] all of them but the ones that I see I often know that you know because we've
[33:46] often know that you know because we've sent them five questions or a task and I
[33:49] sent them five questions or a task and I look at it and go this is I can almost
[33:51] look at it and go this is I can almost predict the exact model that sent it to
[33:53] predict the exact model that sent it to me because they all have a different
[33:55] me because they all have a different personality so I go oh this one the
[33:56] personality so I go oh this one the person put into Gemini or this one the
[33:58] person put into Gemini or this one the person put it into chatbt. Yeah,
[34:00] person put it into chatbt. Yeah, exactly. And it's full of contrastive
[34:02] exactly. And it's full of contrastive constru construction like
[34:04] constru construction like >> it's not this, it's that. Yeah, exactly.
[34:06] >> it's not this, it's that. Yeah, exactly. And then the M dashes. Exactly.
[34:07] And then the M dashes. Exactly. >> I'm really asking like is the person
[34:09] >> I'm really asking like is the person that did that benefiting from from it?
[34:11] that did that benefiting from from it? >> No.
[34:12] >> No. >> Well, no, but for a couple reasons. One
[34:13] >> Well, no, but for a couple reasons. One is that, you know, you and it it
[34:16] is that, you know, you and it it triggers your red flag and so that does
[34:18] triggers your red flag and so that does not do anyone any good. see so many of
[34:20] not do anyone any good. see so many of my colleagues posting on LinkedIn these
[34:22] my colleagues posting on LinkedIn these very obvious AI things and it irritates
[34:25] very obvious AI things and it irritates me because I feel like I'm not going to
[34:26] me because I feel like I'm not going to spend my time reading that because of I
[34:30] spend my time reading that because of I call this this the effort phenomenon
[34:32] call this this the effort phenomenon which is um in in psychology we care a
[34:35] which is um in in psychology we care a lot about things that seemed like they
[34:37] lot about things that seemed like they took a lot of effort and there's
[34:38] took a lot of effort and there's something about seeing an AI post that's
[34:40] something about seeing an AI post that's just irritating because it's so
[34:42] just irritating because it's so obviously AI
[34:43] obviously AI >> that's a really interesting idea the
[34:44] >> that's a really interesting idea the effort phenomenon
[34:45] effort phenomenon >> yeah I've been I've been writing about
[34:47] >> yeah I've been I've been writing about this for a while because um it turns out
[34:48] this for a while because um it turns out there are psychology ology studies where
[34:50] there are psychology ology studies where if I offer you two pieces of art and one
[34:52] if I offer you two pieces of art and one of them looks like, you know, let's say
[34:53] of them looks like, you know, let's say it's a a red dot in the middle of a
[34:55] it's a a red dot in the middle of a white canvas and the other one is, you
[34:57] white canvas and the other one is, you know, bottle caps stacked up and glued
[35:00] know, bottle caps stacked up and glued in this great shape or whatever, you'll
[35:02] in this great shape or whatever, you'll pay you'll pay much more for the thing
[35:03] pay you'll pay much more for the thing that looks like it took a lot of effort.
[35:05] that looks like it took a lot of effort. People will pay more for a real diamond
[35:08] People will pay more for a real diamond than a synthetic lab grown diamond,
[35:10] than a synthetic lab grown diamond, which is exactly the same thing. It's
[35:12] which is exactly the same thing. It's just carbon in the matrix. But they feel
[35:14] just carbon in the matrix. But they feel like, oh well, mother nature took
[35:15] like, oh well, mother nature took hundreds of millions of years of effort
[35:17] hundreds of millions of years of effort on this one, but not over here. It just
[35:19] on this one, but not over here. It just took a few days in the lab. So, there's
[35:21] took a few days in the lab. So, there's a million ways where we care about that
[35:23] a million ways where we care about that a lot. When it comes to this AI thing,
[35:26] a lot. When it comes to this AI thing, um, yes, anybody who's just popping back
[35:28] um, yes, anybody who's just popping back something to you, it just feels like,
[35:30] something to you, it just feels like, all right, they took the the path of
[35:31] all right, they took the the path of least resistance, and I'm not so
[35:33] least resistance, and I'm not so interested.
[35:33] interested. >> I want to know from a neuroscience
[35:35] >> I want to know from a neuroscience perspective whether they benefit.
[35:37] perspective whether they benefit. >> Presumably, they don't benefit too much
[35:38] >> Presumably, they don't benefit too much either. I mean, it's hard to know
[35:40] either. I mean, it's hard to know exactly how many times they went back
[35:41] exactly how many times they went back and forth with it. They could have said,
[35:43] and forth with it. They could have said, "Hey, Chad GPT, thank you for this, but
[35:46] "Hey, Chad GPT, thank you for this, but I'm kind of this more of this person.
[35:47] I'm kind of this more of this person. When I really think about it, this is
[35:49] When I really think about it, this is the thing that inspires me." Not not
[35:51] the thing that inspires me." Not not what you suggested. So, so somebody
[35:52] what you suggested. So, so somebody could put effort into it. It's just that
[35:54] could put effort into it. It's just that we can't know that when we get the AI
[35:56] we can't know that when we get the AI response. It seems to be a pretty
[35:58] response. It seems to be a pretty consistent principle of life generally
[35:59] consistent principle of life generally that like when you do something hard or
[36:02] that like when you do something hard or when you put in effort, as you say, you
[36:03] when you put in effort, as you say, you tend to get back like an equal and
[36:05] tend to get back like an equal and opposite return like relatively. So I I
[36:08] opposite return like relatively. So I I would think that if I fought through,
[36:11] would think that if I fought through, you know, maybe even using AI as a
[36:13] you know, maybe even using AI as a companion, but I fought then to write it
[36:15] companion, but I fought then to write it out myself instead of just copying and
[36:17] out myself instead of just copying and pasting.
[36:18] pasting. >> Yeah.
[36:19] >> Yeah. >> One of the things I've learned from
[36:20] >> One of the things I've learned from doing this podcast and all these
[36:20] doing this podcast and all these episodes is everything is a trade-off.
[36:24] episodes is everything is a trade-off. >> Yeah.
[36:25] >> Yeah. >> And and if you don't know what the trade
[36:26] >> And and if you don't know what the trade you're making, then you're often at
[36:29] you're making, then you're often at great risk. And so like some of my
[36:31] great risk. And so like some of my friends will say, "Oh, I take this pill
[36:32] friends will say, "Oh, I take this pill and it's amazing. It does all these
[36:33] and it's amazing. It does all these things for me. It's the most amazing
[36:34] things for me. It's the most amazing thing ever. I can just focus for 24
[36:36] thing ever. I can just focus for 24 hours a day and I'm so productive now.
[36:38] hours a day and I'm so productive now. And I go, "What's the what's the
[36:39] And I go, "What's the what's the downside?" And they go, "Oh, there's no
[36:41] downside?" And they go, "Oh, there's no downside." And I go, "Hm." Like, so
[36:43] downside." And I go, "Hm." Like, so that's what I mean. It's even worse when
[36:45] that's what I mean. It's even worse when you don't you don't know the trade
[36:46] you don't you don't know the trade you're making. And so with AI, I go,
[36:47] you're making. And so with AI, I go, "Okay, if it's making me wildly more
[36:50] "Okay, if it's making me wildly more efficient or productive, what trade am I
[36:53] efficient or productive, what trade am I making?" I think understanding this it's
[36:56] making?" I think understanding this it's probably not two categories but a
[36:58] probably not two categories but a spectrum from vicious friction to
[37:00] spectrum from vicious friction to virtuous friction but really paying
[37:02] virtuous friction but really paying attention to what is virtuous friction
[37:04] attention to what is virtuous friction what would make me a better person if I
[37:07] what would make me a better person if I actually put the effort into this that
[37:09] actually put the effort into this that matters a lot and I will say for us as
[37:12] matters a lot and I will say for us as professors for you looking for job
[37:15] professors for you looking for job candidates we need to change how we're
[37:17] candidates we need to change how we're asking the questions if we just say hey
[37:19] asking the questions if we just say hey write answer these five questions of
[37:21] write answer these five questions of course everyone's going to use it for
[37:22] course everyone's going to use it for example in my classes is at Stanford. I
[37:24] example in my classes is at Stanford. I I don't have people turn in a final
[37:26] I don't have people turn in a final paper anymore. That was from previous
[37:29] paper anymore. That was from previous life before AI. Now I have them do
[37:32] life before AI. Now I have them do projects as their final thing where
[37:33] projects as their final thing where they're uh you know running an
[37:35] they're uh you know running an experiment on something. And of course
[37:36] experiment on something. And of course they use AI to help them generate some
[37:39] they use AI to help them generate some of the issues, but they have to deal
[37:40] of the issues, but they have to deal with other people and look at the data
[37:42] with other people and look at the data and figure out what's wrong and that
[37:43] and figure out what's wrong and that kind of stuff. I worry that it's getting
[37:44] kind of stuff. I worry that it's getting into the age of, you know, the whole
[37:46] into the age of, you know, the whole calculator thing you said where maybe
[37:48] calculator thing you said where maybe actually it is now you need to assess
[37:50] actually it is now you need to assess them on their ability to use the AI,
[37:52] them on their ability to use the AI, >> not to succeed without it.
[37:55] >> not to succeed without it. >> Yeah, agreed. This is the whole game for
[37:57] >> Yeah, agreed. This is the whole game for all of us, I think, is figuring out how
[37:58] all of us, I think, is figuring out how to surf this wave of AI where it can
[38:00] to surf this wave of AI where it can make us super human. We can just be
[38:02] make us super human. We can just be better, so much better than anything we
[38:04] better, so much better than anything we ever were doing before because we have
[38:07] ever were doing before because we have immediate access to knowledge and facts
[38:09] immediate access to knowledge and facts that either we had forgotten or we never
[38:11] that either we had forgotten or we never knew existed. And so we should be
[38:13] knew existed. And so we should be surfing that wave. So I I I totally
[38:15] surfing that wave. So I I I totally agree with you on that point. If you can
[38:16] agree with you on that point. If you can figure out how to change your interview
[38:18] figure out how to change your interview questions so that you're seeing, hey,
[38:19] questions so that you're seeing, hey, can this person really get the speed?
[38:21] can this person really get the speed? With everything you know about learning
[38:23] With everything you know about learning and neuroplasticity and expanding one's
[38:25] and neuroplasticity and expanding one's brain, is there a anything else you can
[38:28] brain, is there a anything else you can say to the audience about how they
[38:30] say to the audience about how they should use AI so that they become a
[38:32] should use AI so that they become a superhum?
[38:33] superhum? >> Interesting. I you know, look, I I have
[38:35] >> Interesting. I you know, look, I I have been talking to my friends about this
[38:36] been talking to my friends about this issue a lot lately and I I mentioned how
[38:38] issue a lot lately and I I mentioned how I've become so much better at home
[38:40] I've become so much better at home improvement stuff. I just know so much
[38:42] improvement stuff. I just know so much more. Each one of my friends has
[38:44] more. Each one of my friends has something like that where like, hey, you
[38:45] something like that where like, hey, you know what? I've actually gotten so much
[38:47] know what? I've actually gotten so much better at this super random thing that I
[38:49] better at this super random thing that I never even thought I, you know, I never
[38:51] never even thought I, you know, I never thought about it explicitly, but because
[38:53] thought about it explicitly, but because I'm always asking AI questions about
[38:55] I'm always asking AI questions about that and it's giving me the answers.
[38:57] that and it's giving me the answers. It's not simply that it gives me the
[38:59] It's not simply that it gives me the answers and I forget it. It gives me the
[39:01] answers and I forget it. It gives me the answers and I remember it. I become
[39:03] answers and I remember it. I become better and better because it's like the
[39:04] better and better because it's like the way that Alexander the Great had
[39:06] way that Alexander the Great had Aristotle as his tutor and could ask him
[39:09] Aristotle as his tutor and could ask him anything and learn great stuff from him.
[39:11] anything and learn great stuff from him. We've all got Aristotle in our pocket
[39:12] We've all got Aristotle in our pocket now and we can become better at the
[39:15] now and we can become better at the things that we want to do, the things
[39:17] things that we want to do, the things that resonate with us for whatever
[39:18] that resonate with us for whatever reason. If everyone's got Aristotle in
[39:20] reason. If everyone's got Aristotle in their pocket, how does one create an
[39:22] their pocket, how does one create an edge?
[39:23] edge? >> I think it has to do with we're all just
[39:25] >> I think it has to do with we're all just going to be running faster. In the same
[39:27] going to be running faster. In the same way that when Steve Jobs introduced
[39:28] way that when Steve Jobs introduced Apple computers, he said this is like a
[39:30] Apple computers, he said this is like a bicycle for the mind. What he meant by
[39:32] bicycle for the mind. What he meant by that was that for millions of years
[39:34] that was that for millions of years we've been walking bipedily and then
[39:37] we've been walking bipedily and then just in the last nancond of evolution we
[39:39] just in the last nancond of evolution we invented the bicycle and suddenly humans
[39:42] invented the bicycle and suddenly humans can move faster because of the bicycle
[39:44] can move faster because of the bicycle and he said having a personal computer
[39:46] and he said having a personal computer is like a bicycle for the mind and I
[39:49] is like a bicycle for the mind and I think of AI now as like a motorcycle for
[39:51] think of AI now as like a motorcycle for the mind it's it allows us to move so
[39:55] the mind it's it allows us to move so much faster so now it's a motorcycle
[39:56] much faster so now it's a motorcycle race and there will be people who are
[39:58] race and there will be people who are much faster than other people because
[40:01] much faster than other people because they're really using that optimally.
[40:03] they're really using that optimally. >> And that's what I mean. It's like how do
[40:04] >> And that's what I mean. It's like how do I create an edge versus my whoever I'm
[40:06] I create an edge versus my whoever I'm competing with in whatever industry I'm
[40:07] competing with in whatever industry I'm in.
[40:08] in. >> Well, for sure the people who are just
[40:09] >> Well, for sure the people who are just copying and pasting the AI slop that'll
[40:12] copying and pasting the AI slop that'll be easy to beat that crowd. But
[40:15] be easy to beat that crowd. But otherwise, I think it's just a matter
[40:16] otherwise, I think it's just a matter of, hey, these are the newest things.
[40:18] of, hey, these are the newest things. It's like in history when the new sword
[40:20] It's like in history when the new sword gets invented or the new gun or the new
[40:22] gets invented or the new gun or the new cannon, you know, you have to keep
[40:24] cannon, you know, you have to keep improving and and using that. And that's
[40:27] improving and and using that. And that's what's going on now with AI
[40:28] what's going on now with AI >> and with from a neuroscience
[40:29] >> and with from a neuroscience perspective. If I wanted to use AI to
[40:33] perspective. If I wanted to use AI to based on all these things you've told me
[40:34] based on all these things you've told me about novelty and all these other points
[40:36] about novelty and all these other points that expand the the connections across
[40:38] that expand the the connections across my brain and give me a big cognitive
[40:40] my brain and give me a big cognitive reserve.
[40:41] reserve. What might I I install as a practice
[40:43] What might I I install as a practice every week when I'm speaking to my AI?
[40:46] every week when I'm speaking to my AI? Oh, ask it questions that you're curious
[40:47] Oh, ask it questions that you're curious about about anything. Just asking
[40:50] about about anything. Just asking questions. Here's one thing I do all the
[40:52] questions. Here's one thing I do all the time. I'll say, "Hey, I've been thinking
[40:54] time. I'll say, "Hey, I've been thinking about this. You know, I on my podcast, I
[40:56] about this. You know, I on my podcast, I do a lot of monologues and so I'll start
[40:59] do a lot of monologues and so I'll start talking to it and I'll say, "Hey, I've
[41:01] talking to it and I'll say, "Hey, I've got this idea that I'm thinking about.
[41:02] got this idea that I'm thinking about. What if blah blah blah blah." And then
[41:03] What if blah blah blah blah." And then I'll say, "Here's my idea. Give me pros
[41:05] I'll say, "Here's my idea. Give me pros and cons." You know, tell me why this is
[41:08] and cons." You know, tell me why this is wrong. And I do that pretty much with
[41:10] wrong. And I do that pretty much with everything that I ask it if I'm
[41:12] everything that I ask it if I'm proposing some, you know, stupid seed of
[41:14] proposing some, you know, stupid seed of an idea and it really gives me the
[41:16] an idea and it really gives me the counter arguments and I really engage
[41:18] counter arguments and I really engage with it. That is the important part, I
[41:21] with it. That is the important part, I think. And by the way, I just want to
[41:22] think. And by the way, I just want to say I think for the next generation that
[41:24] say I think for the next generation that we're teaching this, there really only
[41:27] we're teaching this, there really only two things we can teach because all the
[41:29] two things we can teach because all the details of, you know, hey, let's teach
[41:31] details of, you know, hey, let's teach computer programming or something,
[41:32] computer programming or something, that's probably already gone as a useful
[41:34] that's probably already gone as a useful thing. So what we can teach is critical
[41:37] thing. So what we can teach is critical thinking and creativity. That's it. I
[41:41] thinking and creativity. That's it. I think that's such an important point,
[41:42] think that's such an important point, this point about asking your AI why you
[41:44] this point about asking your AI why you might be wrong.
[41:45] might be wrong. >> Yeah. I I think I've had most of my
[41:47] >> Yeah. I I think I've had most of my paradigm shifting moments when I've come
[41:49] paradigm shifting moments when I've come to an AI model that I was using with a
[41:52] to an AI model that I was using with a very with very high conviction. And the
[41:54] very with very high conviction. And the prompt that always I think is most sort
[41:56] prompt that always I think is most sort of expansive in terms of my intellectual
[41:59] of expansive in terms of my intellectual knowledge is when I say to it, be
[42:02] knowledge is when I say to it, be brutally honest about your opinion.
[42:04] brutally honest about your opinion. Think for yourself and be objective and
[42:06] Think for yourself and be objective and tell me where my blind spots are.
[42:09] tell me where my blind spots are. There's something innate with within us
[42:10] There's something innate with within us all where we don't actually want to be
[42:14] all where we don't actually want to be wrong. We often I think as a natural
[42:16] wrong. We often I think as a natural reflex and this is why people get really
[42:17] reflex and this is why people get really sort of trapped in echo chambers of
[42:18] sort of trapped in echo chambers of political opinion and you know Leon
[42:20] political opinion and you know Leon Fesser talked about this idea of
[42:21] Fesser talked about this idea of cognitive dissonance when something you
[42:23] cognitive dissonance when something you believe contrasts with new information
[42:26] believe contrasts with new information and how it makes you feel uncomfortable
[42:28] and how it makes you feel uncomfortable there's something when I type that out
[42:29] there's something when I type that out when I when I love the idea or the thing
[42:31] when I when I love the idea or the thing I've written or the memo I've written
[42:32] I've written or the memo I've written this new idea and I go on tell me why
[42:35] this new idea and I go on tell me why I'm completely completely wrong and it
[42:36] I'm completely completely wrong and it eviscerates me it is both uncomfortable
[42:40] eviscerates me it is both uncomfortable but it feels incredibly important
[42:42] but it feels incredibly important because then then it's like I've I've
[42:44] because then then it's like I've I've grown. But these AIs, they're they're
[42:47] grown. But these AIs, they're they're programmed almost to like kiss my ass.
[42:49] programmed almost to like kiss my ass. >> Yes. Although, you know, Chatupati
[42:52] >> Yes. Although, you know, Chatupati released a very sickopantic version, I
[42:54] released a very sickopantic version, I don't know, maybe a year ago. Meaning it
[42:56] don't know, maybe a year ago. Meaning it compliments you. You give some idea and
[42:58] compliments you. You give some idea and it says, "Oh, Stephen, that's the best
[43:00] it says, "Oh, Stephen, that's the best idea I've ever heard. You're a genius
[43:01] idea I've ever heard. You're a genius and blah blah." And that didn't last
[43:03] and blah blah." And that didn't last very long, that model, because nobody
[43:05] very long, that model, because nobody actually liked it. So, you're exactly
[43:07] actually liked it. So, you're exactly right. And and I'm sure most listeners
[43:09] right. And and I'm sure most listeners know this, but you can tell your AI to
[43:12] know this, but you can tell your AI to be brutally honest with you all the
[43:14] be brutally honest with you all the time. You can tell them to do that all
[43:15] time. You can tell them to do that all the time and it'll do that. So you can
[43:18] the time and it'll do that. So you can you can establish the kind of person
[43:19] you can establish the kind of person that you're talking to. Here's the
[43:21] that you're talking to. Here's the thing. You're right. Of course, people
[43:22] thing. You're right. Of course, people don't like to be wrong. It can be
[43:24] don't like to be wrong. It can be socially embarrassing. It can be
[43:25] socially embarrassing. It can be uncomfortable. And yet, there's
[43:27] uncomfortable. And yet, there's something very different when you're
[43:28] something very different when you're talking to your AI. It's a very private
[43:30] talking to your AI. It's a very private thing. And you say, "Hey, tell me why
[43:31] thing. And you say, "Hey, tell me why I'm brutally wrong." And when it tells
[43:33] I'm brutally wrong." And when it tells you, you think, "Oh, thank God it's
[43:34] you, you think, "Oh, thank God it's telling me that instead of like a real
[43:36] telling me that instead of like a real human." So I I think a lot of that is
[43:39] human." So I I think a lot of that is alleviated with AI. We we don't feel as
[43:43] alleviated with AI. We we don't feel as bad about being wrong there.
[43:44] bad about being wrong there. >> As you were saying that, I just went on
[43:45] >> As you were saying that, I just went on chat and I typed this in. Is my joke
[43:49] chat and I typed this in. Is my joke funny? And the joke I typed in is knock.
[43:51] funny? And the joke I typed in is knock. Who's there? A letter. Let us who? Let
[43:54] Who's there? A letter. Let us who? Let us in and I'll tell you.
[43:56] us in and I'll tell you. >> Okay. You didn't laugh. I didn't laugh.
[43:58] >> Okay. You didn't laugh. I didn't laugh. >> Okay.
[43:58] >> Okay. >> Chapati said, "Yes, it works as a joke.
[44:00] >> Chapati said, "Yes, it works as a joke. solid structure, uses the classic pun
[44:03] solid structure, uses the classic pun payoff, which is exactly how most not
[44:05] payoff, which is exactly how most not jokes land. And then it's done a
[44:06] jokes land. And then it's done a laughing emoji. I then said, "Be
[44:08] laughing emoji. I then said, "Be brutally honest and completely
[44:10] brutally honest and completely objective. Was that funny?" It said,
[44:13] objective. Was that funny?" It said, "It's not very funny."
[44:16] "It's not very funny." Interesting. You know, but but that's
[44:18] Interesting. You know, but but that's interesting because it depends, right? A
[44:20] interesting because it depends, right? A little child actually finds that joke
[44:22] little child actually finds that joke funny and and for a little child, they
[44:24] funny and and for a little child, they then get to repeat that to their
[44:26] then get to repeat that to their classmate. They're learning how to do a
[44:28] classmate. They're learning how to do a joke and so on. So I'm not I'm not sure
[44:31] joke and so on. So I'm not I'm not sure I think there's a single answer to
[44:32] I think there's a single answer to whether that can be funny or not.
[44:34] whether that can be funny or not. >> But the interesting thing is it just
[44:36] >> But the interesting thing is it just reinforcing what I already believed. And
[44:38] reinforcing what I already believed. And therefore when we think about growth or
[44:40] therefore when we think about growth or having a growth mindset if someone's
[44:42] having a growth mindset if someone's just always reinforcing what you already
[44:44] just always reinforcing what you already believe and know I don't know if it's
[44:46] believe and know I don't know if it's ever going to be a growth mindset. I
[44:47] ever going to be a growth mindset. I mean I just asked it again. I said be
[44:49] mean I just asked it again. I said be really honest and it said it's
[44:50] really honest and it said it's absolutely not funny.
[44:52] absolutely not funny. >> Yeah. But but remember all it's doing is
[44:55] >> Yeah. But but remember all it's doing is it's just it's a statistical parrot. And
[44:57] it's just it's a statistical parrot. And so when you say be brutally honest, it
[44:59] so when you say be brutally honest, it it thinks that's what it should answer.
[45:02] it thinks that's what it should answer. >> Also, be even more honest. It says it's
[45:03] >> Also, be even more honest. It says it's basically not funny at all and you
[45:05] basically not funny at all and you shouldn't say that to people.
[45:06] shouldn't say that to people. >> Okay.
[45:06] >> Okay. >> And it says comedic originality 1 out of
[45:09] >> And it says comedic originality 1 out of 10. Likelihood of real laughter 1 out of
[45:10] 10. Likelihood of real laughter 1 out of 10.
[45:11] 10. >> Well, that's that's quite good. That's
[45:12] >> Well, that's that's quite good. That's quite accurate. Um, here's the thing.
[45:15] quite accurate. Um, here's the thing. I've been thinking about this issue a
[45:16] I've been thinking about this issue a lot about whether AI can be funny. And
[45:19] lot about whether AI can be funny. And at the moment, it can't be. It It's
[45:22] at the moment, it can't be. It It's great at repeating jokes, but it doesn't
[45:24] great at repeating jokes, but it doesn't understand humor on its own. what it
[45:27] understand humor on its own. what it knows if you ask it to make up a new
[45:29] knows if you ask it to make up a new joke, what it'll do is it'll have, you
[45:31] joke, what it'll do is it'll have, you know, the first guy walks in the bar,
[45:32] know, the first guy walks in the bar, then the second guy walks in the bar and
[45:34] then the second guy walks in the bar and does X, and that establishes the
[45:36] does X, and that establishes the pattern, but then the third guy, it'll
[45:38] pattern, but then the third guy, it'll have break that pattern, which is the
[45:39] have break that pattern, which is the structure of a joke, but it doesn't know
[45:42] structure of a joke, but it doesn't know how to break the pattern in a way that's
[45:44] how to break the pattern in a way that's funny. It's just the third guy does some
[45:45] funny. It's just the third guy does some random thing. So AI as it stands now,
[45:48] random thing. So AI as it stands now, the way it's structured with what's
[45:49] the way it's structured with what's called a transformer model, doesn't know
[45:52] called a transformer model, doesn't know how to think of the punchline and then
[45:54] how to think of the punchline and then go back and make the joke lead to that
[45:56] go back and make the joke lead to that punchline.
[45:57] punchline. >> A lot of people don't either.
[45:59] >> A lot of people don't either. >> Do you know what I mean? Like I say that
[46:01] >> Do you know what I mean? Like I say that not in an offense way, but just to say
[46:02] not in an offense way, but just to say that like
[46:03] that like >> I don't know. I often hear the claim
[46:04] >> I don't know. I often hear the claim that AI could never be creative.
[46:06] that AI could never be creative. >> It's massively creative. Here's why.
[46:09] >> It's massively creative. Here's why. Creativity in the brain, all creativity
[46:12] Creativity in the brain, all creativity is is you absorb your world. the whole
[46:14] is is you absorb your world. the whole world around you, every experience
[46:15] world around you, every experience you've ever had. And then you're bending
[46:17] you've ever had. And then you're bending and breaking and blending those
[46:19] and breaking and blending those cognitive concepts into new remixes.
[46:22] cognitive concepts into new remixes. That's all creativity is. And you're
[46:24] That's all creativity is. And you're doing that all the time. Whether you're
[46:26] doing that all the time. Whether you're just trying to think of what to say next
[46:27] just trying to think of what to say next or what recipe to make next or what
[46:29] or what recipe to make next or what patent to do or what company to start,
[46:31] patent to do or what company to start, you're just remixing the stuff that you
[46:33] you're just remixing the stuff that you already know. And that's why, you know,
[46:36] already know. And that's why, you know, I don't know, take Beethoven, he could
[46:38] I don't know, take Beethoven, he could have written any kind of music that was
[46:41] have written any kind of music that was being done anywhere in the world. But of
[46:42] being done anywhere in the world. But of course, he didn't. like that's what he
[46:43] course, he didn't. like that's what he grew up with was the music and his local
[46:45] grew up with was the music and his local culture and so on. What we have now is a
[46:48] culture and so on. What we have now is a much broader diet as I mentioned before
[46:50] much broader diet as I mentioned before where we can get everything going in.
[46:52] where we can get everything going in. But the point I want to make here is
[46:54] But the point I want to make here is that AI that's what it does. It remixes
[46:57] that AI that's what it does. It remixes stuff that's come in. So AI is massively
[46:59] stuff that's come in. So AI is massively creative. The part of creativity that AI
[47:01] creative. The part of creativity that AI can't do right now is selection. Meaning
[47:05] can't do right now is selection. Meaning it can generate a 100 pictures but it
[47:07] it can generate a 100 pictures but it doesn't know which one to pick. It
[47:08] doesn't know which one to pick. It doesn't know which one is going to be
[47:09] doesn't know which one is going to be the most appealing to you. But it can
[47:12] the most appealing to you. But it can remix beautifully.
[47:13] remix beautifully. >> But neither do humans, right? So if I
[47:15] >> But neither do humans, right? So if I asked an intern to make me 100 pictures,
[47:18] asked an intern to make me 100 pictures, I mean, I could get my AI to pick one,
[47:19] I mean, I could get my AI to pick one, but it wouldn't know what the intern or
[47:21] but it wouldn't know what the intern or the AI wouldn't know which one I loved.
[47:23] the AI wouldn't know which one I loved. >> The intern would have a much better shot
[47:25] >> The intern would have a much better shot at it. And as the intern is there for a
[47:27] at it. And as the intern is there for a while, he or she becomes quite good at
[47:29] while, he or she becomes quite good at getting, oh, okay, I get Steven's taste.
[47:31] getting, oh, okay, I get Steven's taste. It would be this one.
[47:32] It would be this one. >> And the AI can't learn that what my
[47:33] >> And the AI can't learn that what my taste is. I don't think the AI could
[47:35] taste is. I don't think the AI could learn that about visual images because
[47:37] learn that about visual images because when it generates the pixels, it's doing
[47:39] when it generates the pixels, it's doing this, you know, this magical stuff under
[47:40] this, you know, this magical stuff under the hood where it's deciding which
[47:42] the hood where it's deciding which pixels and how they diffuse together
[47:43] pixels and how they diffuse together and, you know, mix the image, but it
[47:45] and, you know, mix the image, but it doesn't know how to read that image
[47:47] doesn't know how to read that image like, oh yeah, the way this is and blah
[47:50] like, oh yeah, the way this is and blah blah that'll really appeal to Steve. It
[47:52] blah that'll really appeal to Steve. It does it it's not seeing the image except
[47:54] does it it's not seeing the image except as a bunch of pixels. Hm. Hm.
[47:56] as a bunch of pixels. Hm. Hm. >> You need to be a human for that
[47:58] >> You need to be a human for that >> cuz I feed um I was doing an experiment
[48:01] >> cuz I feed um I was doing an experiment recently where I took our my behind the
[48:02] recently where I took our my behind the scenes channel which is a 30 minute long
[48:04] scenes channel which is a 30 minute long video. I dropped it into Gemini and I'd
[48:06] video. I dropped it into Gemini and I'd say things to it like predict where
[48:07] say things to it like predict where people would drop off on the video and
[48:10] people would drop off on the video and then we upload the video to YouTube. we
[48:12] then we upload the video to YouTube. we get the retention data back and Gemini
[48:14] get the retention data back and Gemini uh in the last two times that I've done
[48:16] uh in the last two times that I've done it has a 100% record of knowing that at
[48:18] it has a 100% record of knowing that at minute 7 where insert person talked for
[48:22] minute 7 where insert person talked for too long and might have been a bit more
[48:24] too long and might have been a bit more sight might have tried to sell a hoodie
[48:26] sight might have tried to sell a hoodie for example in that part it would say
[48:29] for example in that part it would say you're going to lose people here and it
[48:30] you're going to lose people here and it would and it very accurately say why it
[48:32] would and it very accurately say why it would say because there's you talked for
[48:34] would say because there's you talked for 74 seconds and it was jarring versus the
[48:38] 74 seconds and it was jarring versus the the the moment that came before it and
[48:40] the the moment that came before it and when I feed the AI I don't let's say
[48:41] when I feed the AI I don't let's say thumbnails and say which thumbnail is
[48:43] thumbnails and say which thumbnail is going to perform the best. We did a test
[48:45] going to perform the best. We did a test recently where we put four thumbnail
[48:47] recently where we put four thumbnail test results that we knew the answer to
[48:49] test results that we knew the answer to into Gemini and said which one's going
[48:50] into Gemini and said which one's going to win on YouTube AB testing and it got
[48:53] to win on YouTube AB testing and it got 100% accuracy of predicting on data we
[48:56] 100% accuracy of predicting on data we already had which one would win. And so
[48:59] already had which one would win. And so now I I don't know I I keep having these
[49:02] now I I don't know I I keep having these paradigm shifting moments where only
[49:03] paradigm shifting moments where only humans could could do that. But
[49:05] humans could could do that. But increasingly the the AIs that we're
[49:08] increasingly the the AIs that we're experimenting with are making better
[49:10] experimenting with are making better creative decisions than now I can make
[49:12] creative decisions than now I can make myself as if the outcome of that
[49:14] myself as if the outcome of that creative decision is which one is people
[49:15] creative decision is which one is people going to prefer.
[49:16] going to prefer. >> Yeah.
[49:16] >> Yeah. >> I'd say a year ago that wasn't the case.
[49:18] >> I'd say a year ago that wasn't the case. >> Okay. So I totally agree with you. But
[49:19] >> Okay. So I totally agree with you. But but let me just mention one thing which
[49:21] but let me just mention one thing which is fascinating which is that often the
[49:24] is fascinating which is that often the way it's doing it is not at all the way
[49:25] way it's doing it is not at all the way that a human would do it which might be
[49:27] that a human would do it which might be fine for our purposes but the data and
[49:30] fine for our purposes but the data and the way that it's picking up on it. It
[49:32] the way that it's picking up on it. It might be something about you know how
[49:33] might be something about you know how much I'm making this up you how much
[49:35] much I'm making this up you how much green was in the YouTube thumbnail image
[49:37] green was in the YouTube thumbnail image or how much red or whatever whatever the
[49:40] or how much red or whatever whatever the thing is or just noticing that there's
[49:42] thing is or just noticing that there's big font versus smaller font or
[49:44] big font versus smaller font or whatever. the next time you try it, it
[49:47] whatever. the next time you try it, it says, "Oh, yeah, this thumbnail is going
[49:48] says, "Oh, yeah, this thumbnail is going to be great." And it's some ridiculous
[49:50] to be great." And it's some ridiculous thumbnail that doesn't make any sense to
[49:51] thumbnail that doesn't make any sense to you as a human, nor to your fellow
[49:53] you as a human, nor to your fellow humans, but it might say, "Oh, yeah,
[49:55] humans, but it might say, "Oh, yeah, this would be great." Because it's
[49:57] this would be great." Because it's judging things on very weird dimensions
[49:59] judging things on very weird dimensions that we can't always see. You know, the
[50:00] that we can't always see. You know, the example you gave about maybe it's cuz
[50:02] example you gave about maybe it's cuz the text is bigger or the color red, but
[50:04] the text is bigger or the color red, but those are the same factors we think
[50:05] those are the same factors we think about as a human. We think if we know
[50:08] about as a human. We think if we know that if the font is bigger, it performs
[50:10] that if the font is bigger, it performs better. We know that red performs better
[50:11] better. We know that red performs better than green.
[50:12] than green. >> Quite possibly. But here's the
[50:13] >> Quite possibly. But here's the interesting thing. Human art constantly
[50:15] interesting thing. Human art constantly evolves and all AI is trained on is what
[50:18] evolves and all AI is trained on is what has been done before and what has
[50:19] has been done before and what has worked. And so if I asked it, let's say
[50:23] worked. And so if I asked it, let's say we composed five different songs and
[50:25] we composed five different songs and said, "Hey AI, which song is going to be
[50:27] said, "Hey AI, which song is going to be better?" It's going to say something
[50:28] better?" It's going to say something that's right in the middle of the
[50:29] that's right in the middle of the distribution of popular songs. But
[50:31] distribution of popular songs. But that's not what actually makes it next
[50:33] that's not what actually makes it next year and the year after. It's new
[50:35] year and the year after. It's new things. It's new twists that that nobody
[50:37] things. It's new twists that that nobody has seen before. That's what we love.
[50:39] has seen before. That's what we love. That's what we seek as consumers. And so
[50:41] That's what we seek as consumers. And so because AI can only be trained up on
[50:44] because AI can only be trained up on what already exists, it's never going to
[50:46] what already exists, it's never going to get the new thing at the edge.
[50:48] get the new thing at the edge. >> But if if the AI was asked to cuz I
[50:51] >> But if if the AI was asked to cuz I think the reason why a new song would
[50:52] think the reason why a new song would break out, let's say, you know, a new
[50:55] break out, let's say, you know, a new Drake song comes out and it's a smash
[50:57] Drake song comes out and it's a smash hit. If we think about that distribution
[50:59] hit. If we think about that distribution curve, so like if I draw on the GR,
[51:01] curve, so like if I draw on the GR, you're saying that um this middle
[51:02] you're saying that um this middle section here is what sort of AI will aim
[51:04] section here is what sort of AI will aim at because it's the popular in the
[51:06] at because it's the popular in the known. Well, if I tell AI to make a
[51:10] known. Well, if I tell AI to make a million songs, which is kind of what I
[51:11] million songs, which is kind of what I guess is what's going on every day um
[51:13] guess is what's going on every day um around the world, if you scattered them
[51:16] around the world, if you scattered them on on this graph at like, you know,
[51:18] on on this graph at like, you know, >> Absolutely.
[51:19] >> Absolutely. >> And then the AI's most unusual song ends
[51:22] >> And then the AI's most unusual song ends up taking off. But it's just because
[51:23] up taking off. But it's just because there's so many of them.
[51:24] there's so many of them. >> Quite right. But that's the human
[51:26] >> Quite right. But that's the human selection part that we're seeing over
[51:28] selection part that we're seeing over there. If you asked, okay, out of all
[51:30] there. If you asked, okay, out of all these dots, which do you think AI is
[51:32] these dots, which do you think AI is going to be best? It's going to have to
[51:33] going to be best? It's going to have to tell you the middle of the curve. But
[51:35] tell you the middle of the curve. But the surprising part is the part that you
[51:37] the surprising part is the part that you circled there, which is the one on the
[51:38] circled there, which is the one on the edge is the one that humans like. Why?
[51:40] edge is the one that humans like. Why? Because we're constant novelty seekers.
[51:43] Because we're constant novelty seekers. We care about the things that are new. I
[51:45] We care about the things that are new. I think the the point I'm getting at is
[51:47] think the the point I'm getting at is that um the creation of it, the creative
[51:51] that um the creation of it, the creative process is still the same, which is like
[51:53] process is still the same, which is like >> totally
[51:53] >> totally >> AI or humans just trying a bunch of
[51:56] >> AI or humans just trying a bunch of and then the world going, "Ooh, that
[51:58] and then the world going, "Ooh, that one."
[51:59] one." >> Oh. Oh, yeah. I totally agree. This is
[52:00] >> Oh. Oh, yeah. I totally agree. This is consistent with what I was saying, which
[52:01] consistent with what I was saying, which is that AI can be massively creative in
[52:03] is that AI can be massively creative in terms of the generation of something,
[52:05] terms of the generation of something, but you need humans to do the selection.
[52:07] but you need humans to do the selection. I'm only arguing the point that AI is
[52:09] I'm only arguing the point that AI is not good at saying, okay, I've generated
[52:11] not good at saying, okay, I've generated a 100 songs. This is the one humans will
[52:13] a 100 songs. This is the one humans will choose. We end up saying, hey, wait,
[52:16] choose. We end up saying, hey, wait, this one is just weird and unique enough
[52:18] this one is just weird and unique enough that I really like that. It's
[52:20] that I really like that. It's interesting because when you um when you
[52:21] interesting because when you um when you speak to like record labels about music,
[52:24] speak to like record labels about music, what they're often doing is getting a
[52:28] what they're often doing is getting a format of a song that they know will
[52:31] format of a song that they know will work. So they're like, "Right, so it's
[52:33] work. So they're like, "Right, so it's got to be eight bars here. It's got to
[52:34] got to be eight bars here. It's got to be this here. You got to have a chorus
[52:35] be this here. You got to have a chorus that's like hookie. It's got to come
[52:36] that's like hookie. It's got to come back around. It's got to build up pace.
[52:38] back around. It's got to build up pace. And there's like a rough format to it."
[52:40] And there's like a rough format to it." And it's no surprise that Ed Sheer
[52:42] And it's no surprise that Ed Sheer someone like Ed Sheeran has written so
[52:44] someone like Ed Sheeran has written so many songs for so many people.
[52:45] many songs for so many people. >> Yeah. When I spent some time working
[52:47] >> Yeah. When I spent some time working with Sony, they had a brand new boy band
[52:49] with Sony, they had a brand new boy band in the wake of One Direction. And when I
[52:51] in the wake of One Direction. And when I sat with the boy band um and was
[52:53] sat with the boy band um and was introducing myself, they said they said
[52:54] introducing myself, they said they said to me, "Oh yeah, so um here are their
[52:55] to me, "Oh yeah, so um here are their his the boy band's first three songs and
[52:58] his the boy band's first three songs and um Ed Sheeran has written all of them."
[53:00] um Ed Sheeran has written all of them." And I was like, "What?" I thought I
[53:02] And I was like, "What?" I thought I thought like they're like, "No, Ed Ed
[53:03] thought like they're like, "No, Ed Ed Sheeran's written all of them." And then
[53:05] Sheeran's written all of them." And then what we do is we give them to the boy
[53:06] what we do is we give them to the boy band and then the boy band sing them and
[53:09] band and then the boy band sing them and they're pretty much guaranteed to be
[53:10] they're pretty much guaranteed to be hits because Ed Sheeran has like a
[53:11] hits because Ed Sheeran has like a formula. the way he writes is really in
[53:15] formula. the way he writes is really in like vogue right now. You people tend to
[53:17] like vogue right now. You people tend to think a lot that the songs that are
[53:19] think a lot that the songs that are number one in the charts are there
[53:21] number one in the charts are there because just because someone had
[53:23] because just because someone had creative genius and of course that is
[53:24] creative genius and of course that is the case sometimes but there is a lot of
[53:26] the case sometimes but there is a lot of this writing going on and then handing
[53:28] this writing going on and then handing the formula over because someone has
[53:30] the formula over because someone has cracked the code of a hit,
[53:31] cracked the code of a hit, >> right? But here's the thing and you know
[53:33] >> right? But here's the thing and you know that we all know this which is that the
[53:34] that we all know this which is that the code never lasts. So humans have this
[53:38] code never lasts. So humans have this pull where they're always seeking things
[53:41] pull where they're always seeking things between novelty and familiarity. So we
[53:44] between novelty and familiarity. So we like things where we recognize the brand
[53:46] like things where we recognize the brand and we recognize what the singer has
[53:48] and we recognize what the singer has done before. But there has to be novelty
[53:50] done before. But there has to be novelty or else we're not going to go for it.
[53:52] or else we're not going to go for it. We're not going to listen to that boy
[53:53] We're not going to listen to that boy band for the next 10 years doing the
[53:55] band for the next 10 years doing the same song over and over. So you're of
[53:57] same song over and over. So you're of course right that we, you know, we want
[53:59] course right that we, you know, we want a bit of familiarity. We want to be
[54:01] a bit of familiarity. We want to be anchored, but we definitely seek the
[54:03] anchored, but we definitely seek the new. This is what humans always do. This
[54:05] new. This is what humans always do. This is why car companies always release the
[54:07] is why car companies always release the next model even though the current model
[54:09] next model even though the current model is perfectly fine. This is why haircuts
[54:11] is perfectly fine. This is why haircuts evolve. This is why fashion evolves
[54:12] evolve. This is why fashion evolves through the years. Um because we always
[54:15] through the years. Um because we always care about novelty. And the other thing
[54:17] care about novelty. And the other thing in the music industry that I think is is
[54:19] in the music industry that I think is is also creating a hit is I was reading
[54:21] also creating a hit is I was reading many years ago about some psychology
[54:23] many years ago about some psychology which you'll probably know much more
[54:24] which you'll probably know much more about that says exactly what you just
[54:26] about that says exactly what you just said which is we love something when it
[54:28] said which is we love something when it is familiar but new.
[54:31] is familiar but new. >> Exactly. So the way that the record
[54:33] >> Exactly. So the way that the record industry and the radio industry make
[54:35] industry and the radio industry make something familiar is they blast the
[54:37] something familiar is they blast the same song at you on every radio station
[54:40] same song at you on every radio station for a long period of time until it
[54:42] for a long period of time until it breaks past being just novel, just new
[54:45] breaks past being just novel, just new and it becomes familiar. And like I saw
[54:48] and it becomes familiar. And like I saw this graph which shows that the a song
[54:50] this graph which shows that the a song that you'll love is right there in the
[54:52] that you'll love is right there in the middle of like it's new enough that
[54:55] middle of like it's new enough that you're still into it but it's um
[54:57] you're still into it but it's um familiar now because you've heard it so
[54:59] familiar now because you've heard it so many times that you love it and you'll
[55:01] many times that you love it and you'll if anyone listening the first time you
[55:03] if anyone listening the first time you hear a song you might not love it as
[55:04] hear a song you might not love it as much as once you've heard it like 20
[55:06] much as once you've heard it like 20 times
[55:07] times >> and then at some point you've heard it
[55:08] >> and then at some point you've heard it too much.
[55:09] too much. >> Yeah.
[55:10] >> Yeah. >> And it comes back down the other side of
[55:11] >> And it comes back down the other side of the cover where it's now too familiar.
[55:13] the cover where it's now too familiar. >> Yeah. That's exactly right. And so we're
[55:15] >> Yeah. That's exactly right. And so we're always seeking that tension in the
[55:17] always seeking that tension in the middle. And yeah, companies run into
[55:19] middle. And yeah, companies run into this all the time. Like sometimes they
[55:21] this all the time. Like sometimes they try things that are too novel that just
[55:24] try things that are too novel that just completely fail. You know, Coca-Cola
[55:25] completely fail. You know, Coca-Cola tried this a long time ago with
[55:26] tried this a long time ago with introducing new Coke and no one liked
[55:28] introducing new Coke and no one liked it, whatever. Um, and other companies
[55:29] it, whatever. Um, and other companies like what was that company? Blackberry
[55:31] like what was that company? Blackberry with the the little thumb things that
[55:33] with the the little thumb things that you can press the physical keyboard on
[55:34] you can press the physical keyboard on the phone. They failed because they
[55:36] the phone. They failed because they wouldn't change fast enough. But anyway,
[55:38] wouldn't change fast enough. But anyway, companies that make it are always
[55:39] companies that make it are always staying in that uh sweet spot.
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[57:47] When you think about the brain and how
[57:48] When you think about the brain and how it's built and then you think about the
[57:50] it's built and then you think about the exact technology that they've used to
[57:53] exact technology that they've used to create AI, isn't it very very similar?
[57:55] create AI, isn't it very very similar? And if so, if it is similar, what does
[57:58] And if so, if it is similar, what does that say about humans role in the
[58:00] that say about humans role in the future? It's similar, but it's not the
[58:02] future? It's similar, but it's not the same. Which is why with AI, you get what
[58:04] same. Which is why with AI, you get what what we call jagged intelligence,
[58:06] what we call jagged intelligence, meaning that it can do something so
[58:09] meaning that it can do something so extraordinarily smart and then in the
[58:10] extraordinarily smart and then in the next moment give an answer that's weird
[58:12] next moment give an answer that's weird and doesn't make any sense. AI still is
[58:15] and doesn't make any sense. AI still is doing this. It's not it's not yet
[58:16] doing this. It's not it's not yet thinking like we think. Okay. Why? It's
[58:18] thinking like we think. Okay. Why? It's because
[58:20] because AI as we think about it now really
[58:22] AI as we think about it now really started of course decades and decades
[58:24] started of course decades and decades ago where people said look you've got
[58:26] ago where people said look you've got all these billions of cells neurons in
[58:28] all these billions of cells neurons in the brain that are connected to each
[58:30] the brain that are connected to each other. What if we ignore all that
[58:32] other. What if we ignore all that complexity and we just say look imagine
[58:34] complexity and we just say look imagine that you have units that are connected
[58:35] that you have units that are connected to each other. We're going to forget
[58:36] to each other. We're going to forget about you know a single cell in the
[58:38] about you know a single cell in the brain is as complicated as a city. It's
[58:40] brain is as complicated as a city. It's got the entire human genome. It's
[58:42] got the entire human genome. It's trafficking millions of proteins. Let's
[58:43] trafficking millions of proteins. Let's put all that aside. Just imagine it's a
[58:45] put all that aside. Just imagine it's a circle and it's connected to other cells
[58:47] circle and it's connected to other cells and each connection has a certain
[58:48] and each connection has a certain strength and that's what we call an
[58:50] strength and that's what we call an artificial neural network. Now that went
[58:53] artificial neural network. Now that went off in its own direction and the kind of
[58:55] off in its own direction and the kind of amazing surprising part is how
[58:57] amazing surprising part is how successful it's been to just get rid of
[58:59] successful it's been to just get rid of all the detail but it's still super
[59:02] all the detail but it's still super different than what human brains are
[59:03] different than what human brains are like. So just an example uh this thing I
[59:07] like. So just an example uh this thing I mentioned at the very beginning about
[59:08] mentioned at the very beginning about how we're a team of rivals under the
[59:10] how we're a team of rivals under the hood. You got all these different
[59:11] hood. You got all these different competing neural networks that are
[59:13] competing neural networks that are trying to drive your behavior and so on.
[59:15] trying to drive your behavior and so on. The fact that we're emotional, the fact
[59:17] The fact that we're emotional, the fact that we are driven by different
[59:20] that we are driven by different appetites, whether food or sexuality or
[59:22] appetites, whether food or sexuality or whatever it is, but you know, you're a
[59:24] whatever it is, but you know, you're a your chat GPT, you don't want that in
[59:26] your chat GPT, you don't want that in the chat GPT. So, it's just an
[59:27] the chat GPT. So, it's just an artificial neural network many layers
[59:29] artificial neural network many layers deep and it's extraordinary at what it
[59:31] deep and it's extraordinary at what it does, but it's so different than a
[59:32] does, but it's so different than a human. For example, the fact that it's
[59:34] human. For example, the fact that it's read everything on the planet and
[59:35] read everything on the planet and remembers it and you haven't, you would
[59:38] remembers it and you haven't, you would need to lead a thousand lifetimes to
[59:40] need to lead a thousand lifetimes to read that much. And of course, you
[59:41] read that much. And of course, you wouldn't remember much of it. It It's
[59:43] wouldn't remember much of it. It It's very different is the point I'm making.
[59:45] very different is the point I'm making. They both have converged on something
[59:48] They both have converged on something that we would call intelligence, but
[59:49] that we would call intelligence, but it's a pretty different structure. Even
[59:51] it's a pretty different structure. Even though AI was inspired by the brain,
[59:53] though AI was inspired by the brain, that's what Jeffrey Hinton was telling
[59:54] that's what Jeffrey Hinton was telling me. He was telling me that like much of
[59:56] me. He was telling me that like much of the the breakthroughs that have made AI
[59:58] the the breakthroughs that have made AI what it is today came from understanding
[01:00:00] what it is today came from understanding how the brain works.
[01:00:02] how the brain works. >> Yeah. But that's interesting because
[01:00:04] >> Yeah. But that's interesting because Hinn isn't is incentivized to say that.
[01:00:07] Hinn isn't is incentivized to say that. But a neuroscientist
[01:00:09] But a neuroscientist >> incentivized to say that
[01:00:10] >> incentivized to say that >> people doing AI of course are paying a
[01:00:13] >> people doing AI of course are paying a lot of attention to how this is
[01:00:15] lot of attention to how this is structured like the brain because before
[01:00:17] structured like the brain because before that people would do things like
[01:00:19] that people would do things like probability theory or rules or you know
[01:00:22] probability theory or rules or you know they were trying to do AI by trying to
[01:00:24] they were trying to do AI by trying to say okay if this then do that but when
[01:00:27] say okay if this then do that but when people started doing artificial neural
[01:00:29] people started doing artificial neural networks that led to a lot of success
[01:00:31] networks that led to a lot of success I'm only pointing out that the
[01:00:32] I'm only pointing out that the artificial neural network looks a lot
[01:00:34] artificial neural network looks a lot like the brain on the surface You say,
[01:00:37] like the brain on the surface You say, "Hey, you've got units and you've got
[01:00:38] "Hey, you've got units and you've got connections, but beyond that, there's a
[01:00:40] connections, but beyond that, there's a lot of differences."
[01:00:41] lot of differences." >> And why are those differences
[01:00:43] >> And why are those differences significant as it relates to what's
[01:00:44] significant as it relates to what's possible?
[01:00:45] possible? >> Because what we've developed is this a
[01:00:48] >> Because what we've developed is this a new species essentially that is
[01:00:50] new species essentially that is incredibly impressive, but it ain't a
[01:00:52] incredibly impressive, but it ain't a human brain. It's different than a human
[01:00:54] human brain. It's different than a human brain. There may be all kinds of
[01:00:56] brain. There may be all kinds of similarities, things that we even come
[01:00:57] similarities, things that we even come to understand are similar, but there are
[01:00:59] to understand are similar, but there are so many differences. Here's an example.
[01:01:02] so many differences. Here's an example. You know, we humans do one trial
[01:01:03] You know, we humans do one trial learning all the time. Meaning if I say
[01:01:06] learning all the time. Meaning if I say or when you were a kid and and your mom
[01:01:07] or when you were a kid and and your mom said, "Hey, Stephen, this is a
[01:01:09] said, "Hey, Stephen, this is a pomegranate." You say, "Okay,
[01:01:10] pomegranate." You say, "Okay, pomegranate. Got it." But you can't when
[01:01:13] pomegranate. Got it." But you can't when you're training up a an artificial
[01:01:15] you're training up a an artificial neural network like at OpenAI or Gemini
[01:01:18] neural network like at OpenAI or Gemini or Anthropic, you have to give thousands
[01:01:21] or Anthropic, you have to give thousands or millions of examples of everything
[01:01:23] or millions of examples of everything for it to learn anything. There's no one
[01:01:24] for it to learn anything. There's no one trial learning on those uh systems. And
[01:01:28] trial learning on those uh systems. And they have to be trained at the cost of
[01:01:29] they have to be trained at the cost of billions of dollars. then they can do a
[01:01:31] billions of dollars. then they can do a run where you ask a question and and it
[01:01:33] run where you ask a question and and it answers the question. But brains in the
[01:01:36] answers the question. But brains in the real world don't have that luxury of
[01:01:38] real world don't have that luxury of having a training phase and then an
[01:01:40] having a training phase and then an action phase. We have to learn on the
[01:01:42] action phase. We have to learn on the fly. It's very different.
[01:01:43] fly. It's very different. >> So I guess the the pertaining question
[01:01:45] >> So I guess the the pertaining question is
[01:01:47] is does it change what's possible for the
[01:01:49] does it change what's possible for the brain versus the artificial neural
[01:01:53] brain versus the artificial neural networks we see in AI? like is there
[01:01:55] networks we see in AI? like is there some limitation based on what you've
[01:01:57] some limitation based on what you've just said that means the this brain in
[01:01:59] just said that means the this brain in front of me, this human brain in front
[01:02:00] front of me, this human brain in front of me will always be better than the AI
[01:02:02] of me will always be better than the AI at something because I'm trying to track
[01:02:04] at something because I'm trying to track forward about what this means for the
[01:02:05] forward about what this means for the future of humans.
[01:02:06] future of humans. >> Yeah.
[01:02:07] >> Yeah. >> Um
[01:02:07] >> Um >> I think it's an interesting question um
[01:02:09] >> I think it's an interesting question um that we'll have to see. But it's clearly
[01:02:12] that we'll have to see. But it's clearly the case that we know what it is to be a
[01:02:15] the case that we know what it is to be a human from the inside. And when I'm
[01:02:17] human from the inside. And when I'm making a model of you and who you are
[01:02:19] making a model of you and who you are and you're making a model of me, we have
[01:02:21] and you're making a model of me, we have assumptions about what it is like to be
[01:02:23] assumptions about what it is like to be a human. AI only watches human behavior
[01:02:26] a human. AI only watches human behavior from the outside. And so it can tell a
[01:02:28] from the outside. And so it can tell a lot of great stuff, but it doesn't
[01:02:30] lot of great stuff, but it doesn't really know what it is to be a human. So
[01:02:33] really know what it is to be a human. So if I ask it some question about what
[01:02:35] if I ask it some question about what would it be like if this or that
[01:02:37] would it be like if this or that happened, it can answer based on
[01:02:39] happened, it can answer based on observing lots of things, but it can
[01:02:41] observing lots of things, but it can only ever know from the outside
[01:02:42] only ever know from the outside >> in terms of why that matters.
[01:02:44] >> in terms of why that matters. >> Yeah. Because you know if I ask my AI my
[01:02:47] >> Yeah. Because you know if I ask my AI my fiance's been like this today or if I
[01:02:49] fiance's been like this today or if I ask my best friend my fiance's been like
[01:02:50] ask my best friend my fiance's been like this today. If it both of them give me
[01:02:52] this today. If it both of them give me the same useful answer it doesn't really
[01:02:54] the same useful answer it doesn't really matter what's
[01:02:54] matter what's >> I agree with you. I agree it may I I I'm
[01:02:57] >> I agree with you. I agree it may I I I'm actually writing a new podcast on this
[01:02:58] actually writing a new podcast on this about what you can tell from the outside
[01:03:00] about what you can tell from the outside and what you can tell from the inside
[01:03:02] and what you can tell from the inside and whether that difference matters.
[01:03:04] and whether that difference matters. Look an example is you know I last year
[01:03:06] Look an example is you know I last year got a Tesla with full self-driving and I
[01:03:09] got a Tesla with full self-driving and I was watching as it was full
[01:03:10] was watching as it was full self-driving. I was coming up on a very
[01:03:12] self-driving. I was coming up on a very complicated traffic situation. And I
[01:03:13] complicated traffic situation. And I thought, well, what's my car going to do
[01:03:14] thought, well, what's my car going to do here? How's it possibly going to
[01:03:15] here? How's it possibly going to understand? But what it did is it slowed
[01:03:17] understand? But what it did is it slowed down and came to a stop, which was
[01:03:18] down and came to a stop, which was exactly the right thing. And I thought,
[01:03:20] exactly the right thing. And I thought, oh, that's interesting. Algorithmically,
[01:03:22] oh, that's interesting. Algorithmically, it might think of it very differently
[01:03:24] it might think of it very differently than I am thinking about the situation.
[01:03:26] than I am thinking about the situation. Doesn't matter. It comes to the same
[01:03:28] Doesn't matter. It comes to the same conclusion, ends up in the same place.
[01:03:29] conclusion, ends up in the same place. Yeah, I agree. We have yet to see where
[01:03:32] Yeah, I agree. We have yet to see where these differences matter and and what it
[01:03:35] these differences matter and and what it is to be a human. But I can tell you one
[01:03:37] is to be a human. But I can tell you one thing. We care about other humans. So
[01:03:40] thing. We care about other humans. So here's my little prediction is that
[01:03:41] here's my little prediction is that there's going to be actually a
[01:03:42] there's going to be actually a renaissance in things like live theater
[01:03:44] renaissance in things like live theater and live performances. When when things
[01:03:47] and live performances. When when things first came out like Napster, everyone
[01:03:49] first came out like Napster, everyone thought, okay, that's the death of
[01:03:51] thought, okay, that's the death of concerts. Like who's that's the death of
[01:03:53] concerts. Like who's that's the death of musicians, right? But in fact, you look
[01:03:55] musicians, right? But in fact, you look at a a Taylor Swift concert, gajillions
[01:03:57] at a a Taylor Swift concert, gajillions of people there paying lots of money.
[01:03:59] of people there paying lots of money. Like everyone loves the the thing. Why?
[01:04:02] Like everyone loves the the thing. Why? Because they're going to see the real
[01:04:03] Because they're going to see the real Taylor Swift in person. And I have
[01:04:05] Taylor Swift in person. And I have noticed I give a lot of talks on the
[01:04:06] noticed I give a lot of talks on the road. I have noticed an increase in the
[01:04:08] road. I have noticed an increase in the number of talks since AI came out a few
[01:04:11] number of talks since AI came out a few years ago. The first thing that my
[01:04:13] years ago. The first thing that my friend said to me is hey did you know
[01:04:15] friend said to me is hey did you know David that you can you know use uh 11
[01:04:18] David that you can you know use uh 11 labs and hey Jen and you know you can
[01:04:20] labs and hey Jen and you know you can make an avatar of yourself and you can
[01:04:22] make an avatar of yourself and you can use your voice and and use chat to
[01:04:24] use your voice and and use chat to generate what you're going to say and
[01:04:25] generate what you're going to say and have a fully virtual version of you. He
[01:04:28] have a fully virtual version of you. He said my friend who gives talks too he
[01:04:30] said my friend who gives talks too he said maybe we can start doing this and
[01:04:31] said maybe we can start doing this and do virtual talks. I said nobody's going
[01:04:33] do virtual talks. I said nobody's going to want that. In fact, what's happened
[01:04:35] to want that. In fact, what's happened is more people want to fly us across the
[01:04:38] is more people want to fly us across the country to have us stand there in person
[01:04:41] country to have us stand there in person because it really matters to see fellow
[01:04:43] because it really matters to see fellow humans. And I think that's only going to
[01:04:45] humans. And I think that's only going to increase.
[01:04:46] increase. >> I completely agree with you. I think I
[01:04:48] >> I completely agree with you. I think I think it's so funny. I did a post on
[01:04:49] think it's so funny. I did a post on LinkedIn the other day saying that maybe
[01:04:52] LinkedIn the other day saying that maybe the like interesting paradox or
[01:04:54] the like interesting paradox or interesting outcome of AI is that every
[01:04:58] interesting outcome of AI is that every other iteration of technology made us
[01:05:01] other iteration of technology made us less human. And maybe the intelligence
[01:05:04] less human. And maybe the intelligence now has gotten to a point where
[01:05:07] now has gotten to a point where >> it's now forcing us to be more human
[01:05:10] >> it's now forcing us to be more human because that is all that kind of remains
[01:05:12] because that is all that kind of remains in a way that maybe the the technology
[01:05:14] in a way that maybe the the technology has gotten so good like social media
[01:05:16] has gotten so good like social media didn't make us more human in any
[01:05:18] didn't make us more human in any capacity. But maybe this is the moment
[01:05:19] capacity. But maybe this is the moment where it goes we've got this now
[01:05:21] where it goes we've got this now >> go do what only you as a human can do
[01:05:23] >> go do what only you as a human can do which is like go out there Taylor Swift
[01:05:25] which is like go out there Taylor Swift and sing in front of people IRL.
[01:05:27] and sing in front of people IRL. >> Go and do something in the real world.
[01:05:28] >> Go and do something in the real world. Even for like nurses um and doctors,
[01:05:30] Even for like nurses um and doctors, maybe they shouldn't be filling out
[01:05:31] maybe they shouldn't be filling out admin and paperwork anymore. Maybe they
[01:05:33] admin and paperwork anymore. Maybe they should be holding your hand and giving
[01:05:34] should be holding your hand and giving you, you know, in real life care that
[01:05:37] you, you know, in real life care that only a human could do.
[01:05:39] only a human could do. >> I totally agree.
[01:05:40] >> I totally agree. >> And so maybe that's the like the the
[01:05:41] >> And so maybe that's the like the the positive upside to all of this is um
[01:05:44] positive upside to all of this is um finally, you know, we've been on this
[01:05:45] finally, you know, we've been on this journey with technology and finally it's
[01:05:46] journey with technology and finally it's delivered upon its promise.
[01:05:48] delivered upon its promise. >> I totally agree. And by the way, you
[01:05:49] >> I totally agree. And by the way, you know, AI relationships, by one estimate,
[01:05:52] know, AI relationships, by one estimate, there's a billion people having
[01:05:53] there's a billion people having relationships with AI, like a girlfriend
[01:05:55] relationships with AI, like a girlfriend or boyfriend kind of thing.
[01:05:57] or boyfriend kind of thing. >> Okay? And so for people like us who grew
[01:06:00] >> Okay? And so for people like us who grew up before that existed, we think, "Oh my
[01:06:02] up before that existed, we think, "Oh my gosh, that's weird." But in fact, I
[01:06:04] gosh, that's weird." But in fact, I think it might become helpful because it
[01:06:06] think it might become helpful because it can be a sandbox as long as we have the
[01:06:08] can be a sandbox as long as we have the proper feedback. In the end, we have
[01:06:11] proper feedback. In the end, we have millions of years of evolution driving
[01:06:12] millions of years of evolution driving us towards being with the person you
[01:06:15] us towards being with the person you love, touching another human being,
[01:06:16] love, touching another human being, watching the stars, taking her out to
[01:06:19] watching the stars, taking her out to dinner with your parents, like all you
[01:06:21] dinner with your parents, like all you know, we care about that. And so this
[01:06:23] know, we care about that. And so this worry that people sometimes talk about
[01:06:25] worry that people sometimes talk about about oh people are just going to be on
[01:06:26] about oh people are just going to be on their phone with their AI relationship I
[01:06:28] their phone with their AI relationship I don't think is realistic for almost
[01:06:29] don't think is realistic for almost everybody because it gives us the chance
[01:06:33] everybody because it gives us the chance to you know hopefully sandbox some
[01:06:35] to you know hopefully sandbox some things about relationships and get over
[01:06:36] things about relationships and get over some dumb things with relationships and
[01:06:38] some dumb things with relationships and then we can actually be with our fellow
[01:06:40] then we can actually be with our fellow humans. counterargument would be that
[01:06:42] humans. counterargument would be that maybe there's going to be a bifocation,
[01:06:43] maybe there's going to be a bifocation, a splitting of society where some people
[01:06:46] a splitting of society where some people are going to become even more addicted
[01:06:48] are going to become even more addicted to the technology because the AI is now
[01:06:51] to the technology because the AI is now much smarter at retention. Like I know
[01:06:53] much smarter at retention. Like I know exactly what I need to say to you based
[01:06:56] exactly what I need to say to you based on your brain, Dr. David, to make you
[01:07:00] on your brain, Dr. David, to make you not put this device down. Yes. But
[01:07:03] not put this device down. Yes. But fundamentally, I want to be in contact
[01:07:06] fundamentally, I want to be in contact with my wife. I mean, that's that's the
[01:07:09] with my wife. I mean, that's that's the evolution
[01:07:11] evolution of hundreds of millions of years is that
[01:07:13] of hundreds of millions of years is that I want to make babies. I want to go and
[01:07:16] I want to make babies. I want to go and eat dinner with somebody. And and as
[01:07:19] eat dinner with somebody. And and as much as I might find my phone appealing,
[01:07:20] much as I might find my phone appealing, I'm not going to sit it across from me
[01:07:22] I'm not going to sit it across from me at a nice Italian restaurant and sit
[01:07:24] at a nice Italian restaurant and sit there like that. So, I a lot of people
[01:07:27] there like that. So, I a lot of people do.
[01:07:28] do. >> Me and my me and my friends are at
[01:07:29] >> Me and my me and my friends are at restaurants cuz we have a rule where we
[01:07:31] restaurants cuz we have a rule where we don't touch our phones when we're at
[01:07:32] don't touch our phones when we're at date night. And I have to look around
[01:07:33] date night. And I have to look around and I'm like, "Oh my god, like how is
[01:07:35] and I'm like, "Oh my god, like how is how are all these guys getting away with
[01:07:37] how are all these guys getting away with this?" Like, but do you see what I'm
[01:07:38] this?" Like, but do you see what I'm saying? Like some some people they just
[01:07:40] saying? Like some some people they just have a different sort of proclivity or
[01:07:42] have a different sort of proclivity or they have a different wiring which means
[01:07:44] they have a different wiring which means that you know instead of doing the hard
[01:07:46] that you know instead of doing the hard thing of going out there and going on a
[01:07:47] thing of going out there and going on a first date and being rejected,
[01:07:49] first date and being rejected, pornography or a virtual uh wife might
[01:07:52] pornography or a virtual uh wife might be a substitute for that.
[01:07:54] be a substitute for that. >> Yeah. No, I agree with you. There will
[01:07:55] >> Yeah. No, I agree with you. There will be bifurcations. One question I don't
[01:07:57] be bifurcations. One question I don't know the answer to, but one question is
[01:07:59] know the answer to, but one question is what would that person have done in
[01:08:02] what would that person have done in previous generations? You know, is it
[01:08:05] previous generations? You know, is it really the case that person would have
[01:08:06] really the case that person would have gone out and had a great successful
[01:08:08] gone out and had a great successful relationship or would they always have
[01:08:09] relationship or would they always have had troubles relating to people?
[01:08:12] had troubles relating to people? >> Yeah, I sat with um a few
[01:08:14] >> Yeah, I sat with um a few neuroscientists and experts that are
[01:08:16] neuroscientists and experts that are studied dopamine. Dr. Anna LMK was one.
[01:08:19] studied dopamine. Dr. Anna LMK was one. >> Yeah, she's my colleague.
[01:08:20] >> Yeah, she's my colleague. >> She's your colleague. Yeah. And uh she
[01:08:22] >> She's your colleague. Yeah. And uh she talks a lot about how we all have
[01:08:24] talks a lot about how we all have different types of addictive substances
[01:08:28] different types of addictive substances and like you know we will think like
[01:08:30] and like you know we will think like heroin's addictive for everybody and
[01:08:31] heroin's addictive for everybody and alcohol's addictive and I used to think
[01:08:33] alcohol's addictive and I used to think of it on a spectrum but actually she
[01:08:35] of it on a spectrum but actually she said like for her addiction was romantic
[01:08:38] said like for her addiction was romantic erotic novels.
[01:08:39] erotic novels. >> Yeah. and she she almost ruined her
[01:08:40] >> Yeah. and she she almost ruined her relationship because of erotic novels,
[01:08:42] relationship because of erotic novels, which is something that I would read and
[01:08:43] which is something that I would read and just throw in the bit like but so maybe
[01:08:46] just throw in the bit like but so maybe this new technology is particularly
[01:08:49] this new technology is particularly addictive to a certain type of person.
[01:08:51] addictive to a certain type of person. >> Yeah, I I think that's exactly right.
[01:08:53] >> Yeah, I I think that's exactly right. And I think we're going to see that with
[01:08:54] And I think we're going to see that with everything. I mean,
[01:08:55] everything. I mean, >> the wild part about human society is
[01:08:57] >> the wild part about human society is that there's so little that we have in
[01:09:00] that there's so little that we have in common, meaning everybody is really
[01:09:03] common, meaning everybody is really different. And this is something I've
[01:09:04] different. And this is something I've studied in my lab for for decades is
[01:09:06] studied in my lab for for decades is this issue about what are the subtle
[01:09:08] this issue about what are the subtle differences from person to person. Not
[01:09:10] differences from person to person. Not big things like oh this person is a
[01:09:13] big things like oh this person is a psychopath or this person has
[01:09:14] psychopath or this person has schizophrenia but the more subtle
[01:09:16] schizophrenia but the more subtle things. I'll just give you an example
[01:09:18] things. I'll just give you an example like if I ask you to imagine to
[01:09:21] like if I ask you to imagine to visualize let's say an ant on a purple
[01:09:25] visualize let's say an ant on a purple and white tablecloth uh crawling towards
[01:09:28] and white tablecloth uh crawling towards a jar of red jelly. Do you see that in
[01:09:32] a jar of red jelly. Do you see that in your head like a movie or do you have
[01:09:34] your head like a movie or do you have like no particular picture at all or
[01:09:36] like no particular picture at all or somewhere in between? What what do you
[01:09:38] somewhere in between? What what do you experience?
[01:09:38] experience? >> An ant crawling towards a jar of jelly.
[01:09:40] >> An ant crawling towards a jar of jelly. >> Yes.
[01:09:42] >> Yes. >> Yeah. I see a big black ant and then
[01:09:44] >> Yeah. I see a big black ant and then this jar of jelly is like overflowing
[01:09:46] this jar of jelly is like overflowing down the sides with a wooden lid on top
[01:09:48] down the sides with a wooden lid on top of it and the ant is almost there.
[01:09:50] of it and the ant is almost there. >> Oh wow. Okay. So you have a Okay. So
[01:09:52] >> Oh wow. Okay. So you have a Okay. So what you have I'm just guessing where
[01:09:55] what you have I'm just guessing where you are but you are on the end of the
[01:09:56] you are but you are on the end of the spectrum that we call hyperfantasia
[01:09:58] spectrum that we call hyperfantasia which means you have very rich
[01:10:00] which means you have very rich visualization. You're like seeing it
[01:10:02] visualization. You're like seeing it like a picture or a movie. Is that is
[01:10:04] like a picture or a movie. Is that is that accurate? Okay. I happen to be at
[01:10:06] that accurate? Okay. I happen to be at the other end of that spectrum called
[01:10:07] the other end of that spectrum called aphantasia where I don't have any visual
[01:10:10] aphantasia where I don't have any visual images at all. There's no I I don't see
[01:10:12] images at all. There's no I I don't see things visually in any way.
[01:10:14] things visually in any way. >> And it turns out the whole population is
[01:10:16] >> And it turns out the whole population is spread evenly along this spectrum. I'll
[01:10:18] spread evenly along this spectrum. I'll just give a quick side note which is
[01:10:20] just give a quick side note which is that for many years I've been talking
[01:10:22] that for many years I've been talking with Ed Catmull about this. He's the guy
[01:10:24] with Ed Catmull about this. He's the guy who started Pixar films. So he's got all
[01:10:26] who started Pixar films. So he's got all the patents on how to do ray tracing and
[01:10:28] the patents on how to do ray tracing and how to make these beautiful animated
[01:10:29] how to make these beautiful animated characters, right? Ed Catmull is
[01:10:31] characters, right? Ed Catmull is afantasic like I am. And when he learned
[01:10:34] afantasic like I am. And when he learned about this, he got really interested and
[01:10:35] about this, he got really interested and he gave the questionnaire to everybody
[01:10:37] he gave the questionnaire to everybody at Pixar. And it turns out many of his
[01:10:38] at Pixar. And it turns out many of his best animators and directors are
[01:10:40] best animators and directors are aphantasic. They don't picture anything
[01:10:42] aphantasic. They don't picture anything inside their heads. Now this seems
[01:10:45] inside their heads. Now this seems surprising and strange, right? But it
[01:10:47] surprising and strange, right? But it turns out that if you are an aphantasia
[01:10:49] turns out that if you are an aphantasia kid, you're going to become better at
[01:10:50] kid, you're going to become better at drawing because you have to really pay
[01:10:52] drawing because you have to really pay attention to the subject out there and
[01:10:54] attention to the subject out there and really have a dialogue with the page
[01:10:56] really have a dialogue with the page with your pencil. Whereas a kid who's
[01:10:58] with your pencil. Whereas a kid who's hyperfantasic might say, "Oh, I know
[01:10:59] hyperfantasic might say, "Oh, I know what a horse looks like." And just draws
[01:11:01] what a horse looks like." And just draws it. Okay. So anyway,
[01:11:02] it. Okay. So anyway, >> got tracks.
[01:11:03] >> got tracks. >> Yeah. Yeah. So it turns out there's a
[01:11:06] >> Yeah. Yeah. So it turns out there's a real spectrum across the population,
[01:11:07] real spectrum across the population, meaning inside your head and my head,
[01:11:09] meaning inside your head and my head, we're having pretty different
[01:11:10] we're having pretty different experiences. But I've studied this along
[01:11:13] experiences. But I've studied this along dozens of different axes and everyone's
[01:11:15] dozens of different axes and everyone's got different things going on. Just as
[01:11:17] got different things going on. Just as one example, do you know about
[01:11:18] one example, do you know about synesthesia? Have you ever heard of
[01:11:19] synesthesia? Have you ever heard of this? Forget is that forgetting or
[01:11:20] this? Forget is that forgetting or something?
[01:11:21] something? >> No. Sesthesia is having a blending of
[01:11:23] >> No. Sesthesia is having a blending of the senses. So someone with sesthesia
[01:11:25] the senses. So someone with sesthesia might look at letters and it triggers a
[01:11:27] might look at letters and it triggers a color experience in their head. So they
[01:11:28] color experience in their head. So they look at J and that triggers green and
[01:11:29] look at J and that triggers green and they look at M and that triggers blue
[01:11:31] they look at M and that triggers blue and whatever. It's different for each
[01:11:33] and whatever. It's different for each person. Or you might hear music and it
[01:11:34] person. Or you might hear music and it triggers a visual experience. Or you
[01:11:36] triggers a visual experience. Or you might taste something, it puts a feeling
[01:11:38] might taste something, it puts a feeling on your fingertips or whatever. It's
[01:11:39] on your fingertips or whatever. It's just it's a blending of the senses. At
[01:11:41] just it's a blending of the senses. At least 3% of the population has this.
[01:11:44] least 3% of the population has this. It's not a disease or a disorder. It's
[01:11:45] It's not a disease or a disorder. It's just an alternative perceptual reality.
[01:11:49] just an alternative perceptual reality. So if you have aphantasia, does that
[01:11:51] So if you have aphantasia, does that mean that you can't picture your kids?
[01:11:53] mean that you can't picture your kids? >> It means that the way I picture them is
[01:11:55] >> It means that the way I picture them is not visually. I mean there's sort of a
[01:11:59] not visually. I mean there's sort of a very g but for me it's more motoric
[01:12:02] very g but for me it's more motoric imagery and you know I I and audio
[01:12:05] imagery and you know I I and audio imagery. Like I'm I'm imagining talking
[01:12:07] imagery. Like I'm I'm imagining talking to them and being with them and being
[01:12:08] to them and being with them and being close to them and probably some old
[01:12:10] close to them and probably some old factory imagery meaning you how they
[01:12:12] factory imagery meaning you how they smell and the whole thing like I have a
[01:12:14] smell and the whole thing like I have a very rich notion of what it is to be
[01:12:16] very rich notion of what it is to be with my kids but it's a pretty terrible
[01:12:18] with my kids but it's a pretty terrible visual picture. Not much there.
[01:12:20] visual picture. Not much there. >> So I imagine people at home have done
[01:12:22] >> So I imagine people at home have done that same experiment while they were
[01:12:24] that same experiment while they were listening. Could they picture an ant
[01:12:26] listening. Could they picture an ant walking towards a jar of jam and if they
[01:12:28] walking towards a jar of jam and if they find themselves on the aphantas I can't
[01:12:31] find themselves on the aphantas I can't remember the two.
[01:12:32] remember the two. >> Aphantasagasic. Yeah. Or hyperfantasic.
[01:12:34] >> Aphantasagasic. Yeah. Or hyperfantasic. So hyperfantasia is you can picture it,
[01:12:36] So hyperfantasia is you can picture it, aphantasia because you can't.
[01:12:37] aphantasia because you can't. >> Yes.
[01:12:38] >> Yes. >> What does that potentially suggest about
[01:12:41] >> What does that potentially suggest about nothing? Now here's the interesting
[01:12:42] nothing? Now here's the interesting part. So we've done lots of studies
[01:12:44] part. So we've done lots of studies about what this translates to in terms
[01:12:46] about what this translates to in terms of your capacities in the world.
[01:12:48] of your capacities in the world. Nothing. Why does it translate to
[01:12:49] Nothing. Why does it translate to nothing? It's because you can
[01:12:52] nothing? It's because you can accomplish tasks in a hundred different
[01:12:55] accomplish tasks in a hundred different ways. And so some people are doing this
[01:12:56] ways. And so some people are doing this very visually. Other people are doing it
[01:12:59] very visually. Other people are doing it where they're like picturing it with
[01:13:01] where they're like picturing it with their motor systems. Others are doing
[01:13:03] their motor systems. Others are doing it, you know, as I mentioned, with sound
[01:13:05] it, you know, as I mentioned, with sound or smell or whatever, or others are
[01:13:06] or smell or whatever, or others are doing it just purely conceptually, just
[01:13:08] doing it just purely conceptually, just thinking through how the steps would go.
[01:13:11] thinking through how the steps would go. But there's nothing there's nothing
[01:13:12] But there's nothing there's nothing obvious other than this thing I
[01:13:14] obvious other than this thing I mentioned about visual artists often
[01:13:16] mentioned about visual artists often being aphantasic.
[01:13:18] being aphantasic. Um, otherwise you can kind of accomplish
[01:13:20] Um, otherwise you can kind of accomplish anything.
[01:13:21] anything. >> I run multiple companies that have
[01:13:23] >> I run multiple companies that have multiple sales teams. And one of the
[01:13:24] multiple sales teams. And one of the things as a founder of a company that's
[01:13:26] things as a founder of a company that's often confusing is you find it hard to
[01:13:28] often confusing is you find it hard to figure out where sales are. So about 10
[01:13:30] figure out where sales are. So about 10 years ago, I started using Pipe Drive in
[01:13:32] years ago, I started using Pipe Drive in my former company and it's also the
[01:13:34] my former company and it's also the reason why I switched over all of my
[01:13:35] reason why I switched over all of my commercial teams in my current media
[01:13:37] commercial teams in my current media company called Steven.com to use Pipe
[01:13:38] company called Steven.com to use Pipe Drive as well. Not only do they sponsor
[01:13:40] Drive as well. Not only do they sponsor this show, but they've been an
[01:13:41] this show, but they've been an incredibly effective way of scaling our
[01:13:43] incredibly effective way of scaling our sales engine over the years. Pipe Drive
[01:13:44] sales engine over the years. Pipe Drive is an easy to use intelligent CRM. And
[01:13:47] is an easy to use intelligent CRM. And at its very core, it makes your sales
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[01:14:20] I'll see you over there. This is
[01:14:22] I'll see you over there. This is something that I've made for you. I
[01:14:24] something that I've made for you. I realized that the diio audience are
[01:14:26] realized that the diio audience are striv
[01:14:29] goals that we want to accomplish. And
[01:14:31] goals that we want to accomplish. And one of the things I've learned is that
[01:14:33] one of the things I've learned is that when you aim at the big big goal, it can
[01:14:36] when you aim at the big big goal, it can feel incredibly psychologically
[01:14:38] feel incredibly psychologically uncomfortable because it's kind of like
[01:14:40] uncomfortable because it's kind of like being stood at the foot of Mount Everest
[01:14:42] being stood at the foot of Mount Everest and looking upwards. The way to
[01:14:43] and looking upwards. The way to accomplish your goals is by breaking
[01:14:45] accomplish your goals is by breaking them down into tiny small steps. And we
[01:14:48] them down into tiny small steps. And we call this in our team the 1%. And
[01:14:50] call this in our team the 1%. And actually this philosophy is highly
[01:14:52] actually this philosophy is highly responsible for much of our success
[01:14:54] responsible for much of our success here. So what we've done so that you at
[01:14:56] here. So what we've done so that you at home can accomplish any big goal that
[01:14:58] home can accomplish any big goal that you have is we've made these 1% diaries
[01:15:01] you have is we've made these 1% diaries and we released these last year and they
[01:15:03] and we released these last year and they all sold out. So I asked my team over
[01:15:05] all sold out. So I asked my team over and over again to bring the diaries back
[01:15:07] and over again to bring the diaries back but also to introduce some new colors
[01:15:08] but also to introduce some new colors and to make some minor tweaks to the
[01:15:10] and to make some minor tweaks to the diary. So now we have a better range for
[01:15:14] diary. So now we have a better range for you. So if you have a big goal in mind
[01:15:17] you. So if you have a big goal in mind and you need a framework and a process
[01:15:18] and you need a framework and a process and some motivation, then I highly
[01:15:21] and some motivation, then I highly recommend you get one of these diaries
[01:15:22] recommend you get one of these diaries before they all sell out once again. And
[01:15:25] before they all sell out once again. And you can get yours at the diary.com.
[01:15:27] you can get yours at the diary.com. And if you want the link, the link is in
[01:15:29] And if you want the link, the link is in the description below.
[01:15:31] the description below. I heard that you might have after many,
[01:15:34] I heard that you might have after many, many decades of people debating this,
[01:15:36] many decades of people debating this, you might have figured out the reason
[01:15:38] you might have figured out the reason why we dream.
[01:15:39] why we dream. >> Yeah. Yeah, it's actually after
[01:15:41] >> Yeah. Yeah, it's actually after millennia of people debating this. This
[01:15:43] millennia of people debating this. This is the cool part. So, okay, remember I
[01:15:45] is the cool part. So, okay, remember I mentioned earlier that if you go blind,
[01:15:49] mentioned earlier that if you go blind, the visual cortex of the back of the
[01:15:50] the visual cortex of the back of the brain gets taken over by hearing and by
[01:15:53] brain gets taken over by hearing and by touch and by other things and it's no
[01:15:54] touch and by other things and it's no longer visual cortex. Well, what we
[01:15:56] longer visual cortex. Well, what we realized is that because we live on a
[01:16:00] realized is that because we live on a planet that rotates into darkness for
[01:16:02] planet that rotates into darkness for half the time, the visual cortex, the
[01:16:05] half the time, the visual cortex, the visual part of your brain is at a
[01:16:07] visual part of your brain is at a disadvantage. So what I realized is that
[01:16:10] disadvantage. So what I realized is that the purpose of dreaming is to defend the
[01:16:12] the purpose of dreaming is to defend the visual territory from takeover from the
[01:16:16] visual territory from takeover from the other senses. So every 90 minutes you've
[01:16:18] other senses. So every 90 minutes you've got these um you've got this very
[01:16:21] got these um you've got this very ancient thing in your midbrain that
[01:16:24] ancient thing in your midbrain that shoots random activity into the visual
[01:16:26] shoots random activity into the visual system and only the visual system only
[01:16:28] system and only the visual system only this very tiny part of the visual
[01:16:30] this very tiny part of the visual system. Every 90 minutes you just blast
[01:16:31] system. Every 90 minutes you just blast random activity in here and the reason
[01:16:33] random activity in here and the reason is you are just defending that territory
[01:16:36] is you are just defending that territory against takeover. Now, the reason that
[01:16:38] against takeover. Now, the reason that all this came together is because our
[01:16:40] all this came together is because our colleagues at Harvard did an experiment
[01:16:41] colleagues at Harvard did an experiment where they took normally cighted people
[01:16:44] where they took normally cighted people and they blindfolded them tightly for 60
[01:16:46] and they blindfolded them tightly for 60 minutes. And it turns out that 60
[01:16:47] minutes. And it turns out that 60 minutes was sufficient for the visual
[01:16:50] minutes was sufficient for the visual cortex to start responding to sound and
[01:16:53] cortex to start responding to sound and to touch. You could start seeing that
[01:16:55] to touch. You could start seeing that takeover happening after 60 minutes. And
[01:16:57] takeover happening after 60 minutes. And that's when we realized, wow, this this
[01:17:00] that's when we realized, wow, this this part of the brain really needs a way of
[01:17:02] part of the brain really needs a way of defending itself now because the brain
[01:17:05] defending itself now because the brain is a natural storyteller. If you blast
[01:17:07] is a natural storyteller. If you blast random activity in there, it'll, you
[01:17:09] random activity in there, it'll, you know, put that together in some sort of
[01:17:10] know, put that together in some sort of visual story about what's happening,
[01:17:12] visual story about what's happening, mostly based on what connections are hot
[01:17:14] mostly based on what connections are hot from the day. But that's why we dream.
[01:17:18] from the day. But that's why we dream. So we we dream to stop the other parts
[01:17:20] So we we dream to stop the other parts of our brain overtaking the visual part
[01:17:24] of our brain overtaking the visual part of our brain, um, overpowering it, and I
[01:17:27] of our brain, um, overpowering it, and I guess ultimately making us go blind.
[01:17:29] guess ultimately making us go blind. >> Yeah, that's exactly right. If we lived
[01:17:30] >> Yeah, that's exactly right. If we lived on a different kind of planet that did
[01:17:32] on a different kind of planet that did not rotate into darkness, then we would
[01:17:35] not rotate into darkness, then we would we presumably wouldn't dream.
[01:17:37] we presumably wouldn't dream. >> Would we even need to close our eyes? I
[01:17:38] >> Would we even need to close our eyes? I mean,
[01:17:38] mean, >> not necessarily. Yeah. It may be that in
[01:17:41] >> not necessarily. Yeah. It may be that in the sleeping state, in the state of deep
[01:17:43] the sleeping state, in the state of deep sleep, the brain is doing particular
[01:17:45] sleep, the brain is doing particular things like taking out the trash and
[01:17:47] things like taking out the trash and cleaning some things up. That might be
[01:17:49] cleaning some things up. That might be necessary. Who knows? But yeah, I don't
[01:17:51] necessary. Who knows? But yeah, I don't think we would need to dream. We
[01:17:52] think we would need to dream. We wouldn't need to blast random activity
[01:17:54] wouldn't need to blast random activity in there. um you know if if if our eyes
[01:17:57] in there. um you know if if if our eyes were always open for example and it was
[01:17:58] were always open for example and it was always light out
[01:17:59] always light out >> are there other examples in the animal
[01:18:01] >> are there other examples in the animal kingdom which support this?
[01:18:04] kingdom which support this? >> Yes, thank you for asking that. It's
[01:18:06] >> Yes, thank you for asking that. It's this is why this new theory about why we
[01:18:08] this is why this new theory about why we dream is taking off because we can make
[01:18:09] dream is taking off because we can make quantitative predictions across animal
[01:18:12] quantitative predictions across animal species. So for example in our last
[01:18:13] species. So for example in our last paper we looked at 25 different species
[01:18:16] paper we looked at 25 different species of primates, apes and monkeys and we
[01:18:19] of primates, apes and monkeys and we looked at how plastic their brains are.
[01:18:21] looked at how plastic their brains are. In other words, how flexible the whole
[01:18:23] In other words, how flexible the whole circuitry was and how much they dream at
[01:18:25] circuitry was and how much they dream at night, which you can tell by looking at
[01:18:27] night, which you can tell by looking at rapid eye movements. You know, when you
[01:18:28] rapid eye movements. You know, when you dream at night, your eyes are shooting
[01:18:30] dream at night, your eyes are shooting back and forth like that. It's called
[01:18:31] back and forth like that. It's called REM, rapid eye movement sleep. So, you
[01:18:33] REM, rapid eye movement sleep. So, you can measure that in other animals, their
[01:18:34] can measure that in other animals, their eyes moving back and forth. So, we
[01:18:37] eyes moving back and forth. So, we correlated how plastic the brain is and
[01:18:40] correlated how plastic the brain is and how much dream sleep you have. And it
[01:18:42] how much dream sleep you have. And it correlates perfectly, which is to say,
[01:18:44] correlates perfectly, which is to say, humans, which are the most plastic, have
[01:18:47] humans, which are the most plastic, have dream sleep all the time. And by the
[01:18:49] dream sleep all the time. And by the way, when you're an infant, you sleep
[01:18:50] way, when you're an infant, you sleep for you have dream sleep for half of
[01:18:52] for you have dream sleep for half of your sleep time, 50% of the time. As you
[01:18:54] your sleep time, 50% of the time. As you get older, you get less and less dream
[01:18:56] get older, you get less and less dream sleep because you just don't need it as
[01:18:57] sleep because you just don't need it as much anymore. But anyway, when we look
[01:18:58] much anymore. But anyway, when we look across species, it correlates perfectly
[01:19:00] across species, it correlates perfectly if you're a monkey that drops into the
[01:19:02] if you're a monkey that drops into the world sort of already fully baked and
[01:19:04] world sort of already fully baked and you don't need to have much plasticity.
[01:19:06] you don't need to have much plasticity. You don't have much dream sleep either.
[01:19:07] You don't have much dream sleep either. Interesting.
[01:19:11] Seems like a very strange thing. It
[01:19:12] Seems like a very strange thing. It sounds like it's a very strange thing
[01:19:13] sounds like it's a very strange thing for the for the brain to do, but it also
[01:19:16] for the for the brain to do, but it also is perfectly plausible based on
[01:19:17] is perfectly plausible based on everything you've said.
[01:19:18] everything you've said. >> Yeah. And by the way, I just want to
[01:19:19] >> Yeah. And by the way, I just want to mention dreaming is across the animal
[01:19:21] mention dreaming is across the animal kingdom. Everybody dreams. All animals
[01:19:23] kingdom. Everybody dreams. All animals dream at night. Even like animals at the
[01:19:25] dream at night. Even like animals at the bottom of the ocean. Uh, yes. It's
[01:19:27] bottom of the ocean. Uh, yes. It's harder to measure stuff all the way at
[01:19:28] harder to measure stuff all the way at the bottom of the ocean. But fish do
[01:19:30] the bottom of the ocean. But fish do have what is equivalent to dream sleep
[01:19:33] have what is equivalent to dream sleep where you're just zapping activity in
[01:19:34] where you're just zapping activity in there. And by the way, even animals that
[01:19:36] there. And by the way, even animals that have gone blind, like there's a there's
[01:19:38] have gone blind, like there's a there's a mammal called the blind mole rat,
[01:19:40] a mammal called the blind mole rat, which lives in darkness and has eyes,
[01:19:43] which lives in darkness and has eyes, but they're blind because over
[01:19:44] but they're blind because over evolutionary time, they've lost vision.
[01:19:46] evolutionary time, they've lost vision. But they still dream because the dream
[01:19:49] But they still dream because the dream circuitry is so ancient. This is so
[01:19:51] circuitry is so ancient. This is so ancient that all animals have to defend
[01:19:54] ancient that all animals have to defend themselves against the darkness by
[01:19:56] themselves against the darkness by keeping their visual systems going. And
[01:19:58] keeping their visual systems going. And so even though the animal went blind,
[01:20:00] so even though the animal went blind, the rest of the brain didn't catch up. I
[01:20:02] the rest of the brain didn't catch up. I mean, that's how evolution goes.
[01:20:03] mean, that's how evolution goes. >> Funny. It's funny because it's kind of
[01:20:05] >> Funny. It's funny because it's kind of like that evolution gave us this TV
[01:20:10] like that evolution gave us this TV that comes on at nighttime when the real
[01:20:12] that comes on at nighttime when the real TV, our real life turns off and it just
[01:20:14] TV, our real life turns off and it just puts on this fake TV set to keep that
[01:20:16] puts on this fake TV set to keep that part of the brain doing something so
[01:20:18] part of the brain doing something so that it doesn't deteriorate and um
[01:20:21] that it doesn't deteriorate and um atrophy.
[01:20:22] atrophy. >> It's exactly right. Yeah, it's exactly
[01:20:24] >> It's exactly right. Yeah, it's exactly right. Which means dreams are quite
[01:20:26] right. Which means dreams are quite pointless outside of just protecting our
[01:20:29] pointless outside of just protecting our neurological matter.
[01:20:31] neurological matter. >> I suspect so. It might be that the
[01:20:34] >> I suspect so. It might be that the particular pathways that could travel
[01:20:35] particular pathways that could travel down, you know, maybe there's some
[01:20:38] down, you know, maybe there's some meaning there. I my own suspicion is
[01:20:40] meaning there. I my own suspicion is that it's like if I went to your
[01:20:41] that it's like if I went to your bookshelf and I picked picked a random
[01:20:43] bookshelf and I picked picked a random book up and I flipped to a random page
[01:20:45] book up and I flipped to a random page and picked a random sentence. I might
[01:20:48] and picked a random sentence. I might find some meaning in that. I might say,
[01:20:49] find some meaning in that. I might say, "Oh, that was just the sentence that I
[01:20:51] "Oh, that was just the sentence that I needed to hear." But it's not really.
[01:20:53] needed to hear." But it's not really. It's just that it has some meaning to
[01:20:54] It's just that it has some meaning to me. Anyway, the point is if you blast
[01:20:55] me. Anyway, the point is if you blast random activity in there, I might dream
[01:20:57] random activity in there, I might dream about something where I wake up and say,
[01:20:58] about something where I wake up and say, "Oh, that was pretty useful." But the
[01:21:01] "Oh, that was pretty useful." But the thing that I think gets overlooked is
[01:21:03] thing that I think gets overlooked is that most dreams are totally useless and
[01:21:05] that most dreams are totally useless and bizarre. Dr. David, what is the most
[01:21:07] bizarre. Dr. David, what is the most important thing we haven't talked about
[01:21:08] important thing we haven't talked about that we should have talked about as it
[01:21:09] that we should have talked about as it specifically relates to people that are
[01:21:12] specifically relates to people that are trying to improve their lives, get
[01:21:15] trying to improve their lives, get better at whatever their subjective
[01:21:16] better at whatever their subjective mission is and the brain.
[01:21:20] mission is and the brain. There are probably a lot of things, but
[01:21:22] There are probably a lot of things, but I got to say the thing that I've been
[01:21:23] I got to say the thing that I've been thinking about so much lately is just
[01:21:25] thinking about so much lately is just about our political uh interfacing with
[01:21:29] about our political uh interfacing with one another. And so I do feel that
[01:21:32] one another. And so I do feel that really learning the skills of dialogue
[01:21:35] really learning the skills of dialogue with our fellow humans where we listen
[01:21:38] with our fellow humans where we listen to what they're saying and try to better
[01:21:39] to what they're saying and try to better understand what their internal model is.
[01:21:42] understand what their internal model is. It's not equivalent to agreeing with
[01:21:43] It's not equivalent to agreeing with them. But it is saying, "Hey, somebody
[01:21:45] them. But it is saying, "Hey, somebody is coming from this perspective. Let me
[01:21:48] is coming from this perspective. Let me see if I can understand that." I think
[01:21:49] see if I can understand that." I think that matters a lot. And I also think
[01:21:52] that matters a lot. And I also think that because we're so highly predisposed
[01:21:55] that because we're so highly predisposed for in-groups and outgroups, it's really
[01:21:57] for in-groups and outgroups, it's really useful to figure out how to complexify
[01:22:00] useful to figure out how to complexify those relationships. Meaning, how do you
[01:22:02] those relationships. Meaning, how do you figure out the all the things that cross
[01:22:05] figure out the all the things that cross cut in the relationship so that you say,
[01:22:07] cut in the relationship so that you say, "Hey, you know what? I shouldn't dismiss
[01:22:08] "Hey, you know what? I shouldn't dismiss this person as a member of my out group
[01:22:10] this person as a member of my out group right away because actually
[01:22:13] right away because actually they belong to the same group I do and
[01:22:15] they belong to the same group I do and they love surfing as much as I do and
[01:22:17] they love surfing as much as I do and they love golden retriever dogs and they
[01:22:19] they love golden retriever dogs and they you know grew up in my hometown and
[01:22:21] you know grew up in my hometown and whatever. Like finding those things uh
[01:22:24] whatever. Like finding those things uh explicitly helps the brain to keep these
[01:22:28] explicitly helps the brain to keep these circuits on that are involved in seeing
[01:22:30] circuits on that are involved in seeing another person as a person. We have we
[01:22:33] another person as a person. We have we have all this social circuitry that is
[01:22:36] have all this social circuitry that is all about understanding other people and
[01:22:39] all about understanding other people and when things get dehumanized that
[01:22:42] when things get dehumanized that actually gets dialed way down. When we
[01:22:44] actually gets dialed way down. When we look at you know let's say a homeless
[01:22:46] look at you know let's say a homeless person or a drug addict or someone who
[01:22:49] person or a drug addict or someone who we think of as our enemy or an out group
[01:22:51] we think of as our enemy or an out group that gets dialed down so we don't think
[01:22:53] that gets dialed down so we don't think of them as a person anymore. We think of
[01:22:55] of them as a person anymore. We think of them as an object to to get around. Mhm.
[01:22:58] them as an object to to get around. Mhm. So, this is what I think is really
[01:22:59] So, this is what I think is really important is figuring out what we can do
[01:23:02] important is figuring out what we can do to keep that social circuitry still
[01:23:04] to keep that social circuitry still going, which includes the things like
[01:23:06] going, which includes the things like eye contact and conversation. And this
[01:23:09] eye contact and conversation. And this is this is one of the most important
[01:23:10] is this is one of the most important things we can do as citizens in a
[01:23:13] things we can do as citizens in a rapidly changing world as it relates to
[01:23:17] rapidly changing world as it relates to things like dementia, which I know is a
[01:23:20] things like dementia, which I know is a fear that a lot of people have. A lot of
[01:23:21] fear that a lot of people have. A lot of people are suffering with dementia, I
[01:23:23] people are suffering with dementia, I think increasingly. In fact, if I was
[01:23:25] think increasingly. In fact, if I was trying to save off dementia, what advice
[01:23:27] trying to save off dementia, what advice would you give me, David?
[01:23:28] would you give me, David? >> Yeah, keep your brain active. Keep it
[01:23:30] >> Yeah, keep your brain active. Keep it active till the day you die. Take on new
[01:23:32] active till the day you die. Take on new challenges. And as soon as you get good
[01:23:34] challenges. And as soon as you get good at something like, you know, sudoku,
[01:23:37] at something like, you know, sudoku, drop it and pick up some that you're not
[01:23:39] drop it and pick up some that you're not good at.
[01:23:40] good at. >> And in simple terms, why?
[01:23:42] >> And in simple terms, why? >> It's because you're forcing your brain
[01:23:43] >> It's because you're forcing your brain to make changes. Otherwise, your brain
[01:23:45] to make changes. Otherwise, your brain says, "Okay, I got this. I got the
[01:23:47] says, "Okay, I got this. I got the world. I understand what's going on.
[01:23:49] world. I understand what's going on. There's no real particular need for me
[01:23:50] There's no real particular need for me to change." And the fact is that the
[01:23:52] to change." And the fact is that the structure of the brain is always
[01:23:54] structure of the brain is always degenerating. And when you get something
[01:23:56] degenerating. And when you get something like a disease like Alzheimer's disease,
[01:23:58] like a disease like Alzheimer's disease, it degenerates much faster. And what you
[01:24:00] it degenerates much faster. And what you want to always be doing is building new
[01:24:02] want to always be doing is building new roadways and fashioning new paths that
[01:24:05] roadways and fashioning new paths that had not been walked before.
[01:24:06] had not been walked before. >> So that there's more to degenerate,
[01:24:09] >> So that there's more to degenerate, which gives me more left over once that
[01:24:12] which gives me more left over once that degeneration begins.
[01:24:14] degeneration begins. >> Yeah, I that's Yeah, I think that's a
[01:24:16] >> Yeah, I that's Yeah, I think that's a good way to look at it. your pathways
[01:24:18] good way to look at it. your pathways are falling apart and if you can build
[01:24:20] are falling apart and if you can build new pathways which requires effort you
[01:24:22] new pathways which requires effort you have to actually care and pursue and do
[01:24:24] have to actually care and pursue and do the thing even as parts of the thing
[01:24:26] the thing even as parts of the thing have fallen apart you still have ways of
[01:24:28] have fallen apart you still have ways of getting from A to B
[01:24:29] getting from A to B >> what do I need to stay away from in
[01:24:31] >> what do I need to stay away from in terms of chemicals or supplement I don't
[01:24:33] terms of chemicals or supplement I don't know or food I don't know
[01:24:35] know or food I don't know >> yeah obviously there's just been a lot
[01:24:36] >> yeah obviously there's just been a lot more emphasis on getting good sleep and
[01:24:38] more emphasis on getting good sleep and good diet and this stuff really matters
[01:24:40] good diet and this stuff really matters I think that's really useful for the
[01:24:42] I think that's really useful for the brain I mean it's fascinating to watch
[01:24:44] brain I mean it's fascinating to watch what's happened in the latest generation
[01:24:46] what's happened in the latest generation in terms of alcohol ol consumption. I
[01:24:48] in terms of alcohol ol consumption. I live up in Silicon Valley and there's a
[01:24:49] live up in Silicon Valley and there's a lot of people who have wineries just
[01:24:52] lot of people who have wineries just north of me and they're like selling
[01:24:53] north of me and they're like selling half their acorage. It's absolutely
[01:24:55] half their acorage. It's absolutely fascinating to see what's happening
[01:24:56] fascinating to see what's happening there. I will say I have a friend who's
[01:24:59] there. I will say I have a friend who's who's in her 20s who said that she's in
[01:25:02] who's in her 20s who said that she's in favor of bringing drinking back. Why?
[01:25:05] favor of bringing drinking back. Why? Because she said we go to parties and
[01:25:07] Because she said we go to parties and everything's so awkward and no one knows
[01:25:08] everything's so awkward and no one knows how to talk to one another. And so
[01:25:10] how to talk to one another. And so they're missing something else. they're
[01:25:12] they're missing something else. they're missing the the dumb mistakes category
[01:25:14] missing the the dumb mistakes category that we all got to enjoy growing up. So,
[01:25:17] that we all got to enjoy growing up. So, it it is a really interesting balance of
[01:25:20] it it is a really interesting balance of of how abstious one wants to become.
[01:25:23] of how abstious one wants to become. >> David, we have a closing tradition where
[01:25:24] >> David, we have a closing tradition where the last guest leaves a question, the
[01:25:25] the last guest leaves a question, the next guest, not knowing who they're
[01:25:26] next guest, not knowing who they're leaving it for.
[01:25:27] leaving it for. >> Question left for you is, what do you
[01:25:29] >> Question left for you is, what do you wish most for our planet over the next
[01:25:33] wish most for our planet over the next 10 years?
[01:25:38] >> Well, the whole list are the top 10.
[01:25:40] >> Well, the whole list are the top 10. >> Yeah. um can't be world peace.
[01:25:44] >> Yeah. um can't be world peace. >> You know, I think I would come back to
[01:25:45] >> You know, I think I would come back to this piece about the complexification of
[01:25:47] this piece about the complexification of relationships, which is to say, if we
[01:25:50] relationships, which is to say, if we could just get a little bit smarter
[01:25:53] could just get a little bit smarter about understanding people out groups as
[01:25:58] about understanding people out groups as being humans with lives with their own
[01:26:00] being humans with lives with their own thing going on. doesn't mean we have to
[01:26:03] thing going on. doesn't mean we have to love them or agree with them, but if we
[01:26:06] love them or agree with them, but if we can just get to that point, I don't
[01:26:08] can just get to that point, I don't think we'll ever hit world peace, but at
[01:26:10] think we'll ever hit world peace, but at least we'd have slightly less
[01:26:11] least we'd have slightly less polarization. So, I'm I'm definitely in
[01:26:13] polarization. So, I'm I'm definitely in favor of that and I do think it's
[01:26:14] favor of that and I do think it's possible and I do think AI can help us
[01:26:16] possible and I do think AI can help us get there by challenging us on these
[01:26:18] get there by challenging us on these points and saying, "Hey, that group that
[01:26:21] points and saying, "Hey, that group that you've already dismissed as an out
[01:26:23] you've already dismissed as an out group, what if I told you this story
[01:26:25] group, what if I told you this story about this person? What if I introduced
[01:26:27] about this person? What if I introduced you to this person?" That kind of stuff.
[01:26:29] you to this person?" That kind of stuff. and you know having there's all kinds of
[01:26:31] and you know having there's all kinds of social movements that have sprung up
[01:26:33] social movements that have sprung up that allow people of different political
[01:26:35] that allow people of different political opinions to come together in a room and
[01:26:37] opinions to come together in a room and talk with one another again it's not
[01:26:38] talk with one another again it's not that anyone has to change their mind but
[01:26:40] that anyone has to change their mind but they can say hey you know what I really
[01:26:42] they can say hey you know what I really like that person I thought that was a
[01:26:44] like that person I thought that was a cool person a sweet person nice person
[01:26:46] cool person a sweet person nice person and and now I understand that somebody
[01:26:48] and and now I understand that somebody who I have seen with my own eyes has a
[01:26:49] who I have seen with my own eyes has a different opinion on this than idea
[01:26:51] different opinion on this than idea >> is that wishful thinking to some degree
[01:26:52] >> is that wishful thinking to some degree >> I don't think so because these things
[01:26:54] >> I don't think so because these things are happening all over the place and and
[01:26:57] are happening all over the place and and >> the macro is is division isn't it It's
[01:26:59] >> the macro is is division isn't it It's polarization echo chambers. There's now
[01:27:01] polarization echo chambers. There's now I think there's now 20 social networks
[01:27:03] I think there's now 20 social networks or some crazy number that have more than
[01:27:04] or some crazy number that have more than 20 million people on them which means
[01:27:06] 20 million people on them which means that social networks are splintering off
[01:27:08] that social networks are splintering off into niches and interests and you know
[01:27:10] into niches and interests and you know there's like Rumble and Bumble and then
[01:27:12] there's like Rumble and Bumble and then there's like threads and X and Facebook
[01:27:14] there's like threads and X and Facebook snap Instagram and and what we're seeing
[01:27:16] snap Instagram and and what we're seeing is more and more
[01:27:18] is more and more >> interest group and also the other thing
[01:27:19] >> interest group and also the other thing with algorithms is we went from having
[01:27:22] with algorithms is we went from having like a social graph where if I had a
[01:27:24] like a social graph where if I had a thousand people follow me those thousand
[01:27:26] thousand people follow me those thousand people would see my stuff to now these
[01:27:27] people would see my stuff to now these interest graphs where it doesn't matter
[01:27:29] interest graphs where it doesn't matter if I have one follower or million
[01:27:30] if I have one follower or million followers, the algorithm is going to
[01:27:32] followers, the algorithm is going to decide who's interested in that thing
[01:27:34] decide who's interested in that thing and it's going to serve it to them
[01:27:35] and it's going to serve it to them because that's the most retentive thing
[01:27:36] because that's the most retentive thing if you're a publicly listed company
[01:27:38] if you're a publicly listed company that's driven by ad revenue. So, you've
[01:27:40] that's driven by ad revenue. So, you've got this algorithm that's actually
[01:27:41] got this algorithm that's actually forcing you into what you know into this
[01:27:43] forcing you into what you know into this into tighter and tighter and tighter
[01:27:44] into tighter and tighter and tighter echo chambers. And even as someone
[01:27:46] echo chambers. And even as someone that's been on social media 15 years and
[01:27:47] that's been on social media 15 years and ran social media companies, this is one
[01:27:48] ran social media companies, this is one of the great things I've noticed is when
[01:27:50] of the great things I've noticed is when I had a million followers back in the
[01:27:51] I had a million followers back in the day, I would reach those people because
[01:27:53] day, I would reach those people because they'd hit follow or subscribe. Now,
[01:27:56] they'd hit follow or subscribe. Now, even on our YouTube channel, 61% of you
[01:27:59] even on our YouTube channel, 61% of you don't subscribe. Um, and please
[01:28:02] don't subscribe. Um, and please subscribe. Um, and that's in part
[01:28:04] subscribe. Um, and that's in part because the algorithm is now doing the
[01:28:06] because the algorithm is now doing the work of deciding who to show it to, who
[01:28:09] work of deciding who to show it to, who it will
[01:28:10] it will >> on the basis of who will be retained.
[01:28:12] >> on the basis of who will be retained. >> Yeah. Here's what I would say. There's
[01:28:14] >> Yeah. Here's what I would say. There's absolutely nothing new about echo
[01:28:16] absolutely nothing new about echo chambers because it was always the case
[01:28:18] chambers because it was always the case that your neighbors and your community
[01:28:20] that your neighbors and your community and whatever, that's what you thought
[01:28:22] and whatever, that's what you thought was reality. I'm actually quite
[01:28:24] was reality. I'm actually quite optimistic about the existent the mere
[01:28:25] optimistic about the existent the mere existence of the internet because at
[01:28:27] existence of the internet because at least we are exposed to the fact that
[01:28:29] least we are exposed to the fact that there are lots of different points of
[01:28:30] there are lots of different points of view. It used to be in places like the
[01:28:32] view. It used to be in places like the USSR, they controlled the media tightly
[01:28:35] USSR, they controlled the media tightly so that everything you saw was a news um
[01:28:37] so that everything you saw was a news um approved story, but now you see all the
[01:28:40] approved story, but now you see all the points of view. Now, many of them might
[01:28:42] points of view. Now, many of them might drive you crazy and whatever, but at
[01:28:43] drive you crazy and whatever, but at least you know that there are people out
[01:28:45] least you know that there are people out there that believe in that. And I think
[01:28:47] there that believe in that. And I think that's really useful. If I had to decide
[01:28:49] that's really useful. If I had to decide between state control where there's a
[01:28:50] between state control where there's a single story or seeing the whole messy
[01:28:53] single story or seeing the whole messy spectrum of opinions, I'd rather see the
[01:28:56] spectrum of opinions, I'd rather see the latter.
[01:28:57] latter. >> What about the middle? You know, they
[01:28:58] >> What about the middle? You know, they always one of the phrases that's again a
[01:29:00] always one of the phrases that's again a principle that's helped me think is that
[01:29:01] principle that's helped me think is that the truth is in the middle. And
[01:29:03] the truth is in the middle. And generally I try understand what the
[01:29:04] generally I try understand what the middle looks like. So you've got state
[01:29:06] middle looks like. So you've got state controlled over here. You've got
[01:29:08] controlled over here. You've got aggressive algorithm that's sort of
[01:29:09] aggressive algorithm that's sort of reinforcing whatever you currently
[01:29:11] reinforcing whatever you currently believe.
[01:29:12] believe. >> Is there not some kind of middle ground
[01:29:13] >> Is there not some kind of middle ground where
[01:29:15] where um the algorithms have to let up a
[01:29:17] um the algorithms have to let up a little bit and of course we're not going
[01:29:18] little bit and of course we're not going to go for state controlled. Here's my
[01:29:20] to go for state controlled. Here's my prediction in 2026 is that there is a
[01:29:23] prediction in 2026 is that there is a market opportunity for a new social
[01:29:25] market opportunity for a new social media company to come along because
[01:29:27] media company to come along because everybody is aware of exactly this
[01:29:29] everybody is aware of exactly this problem that you're pointing out.
[01:29:30] problem that you're pointing out. Everyone hates when they surf and they
[01:29:33] Everyone hates when they surf and they get served exactly what they're supposed
[01:29:34] get served exactly what they're supposed to get served and they get off after an
[01:29:36] to get served and they get off after an hour or two and they feel like they've
[01:29:38] hour or two and they feel like they've wasted their lives. I think there's a
[01:29:40] wasted their lives. I think there's a real opportunity for a social media
[01:29:41] real opportunity for a social media company to come along and say, you know
[01:29:42] company to come along and say, you know what, we're not building our algorithm
[01:29:44] what, we're not building our algorithm like the other guys. It's not about just
[01:29:46] like the other guys. It's not about just trying to get engagement at any cost
[01:29:47] trying to get engagement at any cost with, you know, um, incendiary posts,
[01:29:51] with, you know, um, incendiary posts, but instead we're looking for ways to
[01:29:54] but instead we're looking for ways to connect people. So, if you and I both
[01:29:57] connect people. So, if you and I both love this particular thing, this
[01:30:00] love this particular thing, this particular cuisine or or location or
[01:30:03] particular cuisine or or location or whatever it is, we get connected. We see
[01:30:05] whatever it is, we get connected. We see each other's stuff and the algorithm
[01:30:08] each other's stuff and the algorithm carefully, temporally sequences things
[01:30:10] carefully, temporally sequences things so that we come to have a certain
[01:30:12] so that we come to have a certain connection threshold before we find out,
[01:30:15] connection threshold before we find out, whoa, you have a totally different
[01:30:16] whoa, you have a totally different political opinion than I do on on
[01:30:18] political opinion than I do on on subject X. Wow, I didn't know that, but
[01:30:20] subject X. Wow, I didn't know that, but I really like Stephen, so I'm going to
[01:30:22] I really like Stephen, so I'm going to lean in and listen a little bit more. I
[01:30:24] lean in and listen a little bit more. I think this is very easy to do and I
[01:30:26] think this is very easy to do and I think it can actually be part of the
[01:30:27] think it can actually be part of the selling point of the media company is
[01:30:29] selling point of the media company is saying hey we are here not to enrage you
[01:30:32] saying hey we are here not to enrage you but to to actually build connection
[01:30:35] but to to actually build connection >> sounds like how social media started
[01:30:37] >> sounds like how social media started >> yeah it's a return
[01:30:39] >> yeah it's a return >> I think there's probably a neuroscience
[01:30:42] >> I think there's probably a neuroscience basis as to why we ended up yeah
[01:30:45] basis as to why we ended up yeah >> no it's an economics basis
[01:30:47] >> no it's an economics basis >> but the fact is there's now an economic
[01:30:49] >> but the fact is there's now an economic opportunity now that everyone sees the
[01:30:51] opportunity now that everyone sees the landscape
[01:30:51] landscape >> what I'm trying to say is that that
[01:30:53] >> what I'm trying to say is that that social network wouldn't be that
[01:30:54] social network wouldn't be that retentive by design because it wouldn't
[01:30:56] retentive by design because it wouldn't trigger my dopamine. It wouldn't be a
[01:30:58] trigger my dopamine. It wouldn't be a slot machine like in Tik Tok is a slot
[01:31:00] slot machine like in Tik Tok is a slot machine. Ping ping randomized returns.
[01:31:03] machine. Ping ping randomized returns. Ping ping ping. Dopamine hit. Ping ping
[01:31:05] Ping ping ping. Dopamine hit. Ping ping ping. So this other social network that
[01:31:07] ping. So this other social network that wasn't playing with my dopamine in such
[01:31:09] wasn't playing with my dopamine in such a way. I don't know whether I'd be
[01:31:11] a way. I don't know whether I'd be addicted enough to return. Therefore,
[01:31:12] addicted enough to return. Therefore, they wouldn't sell their ads the
[01:31:13] they wouldn't sell their ads the economic return. Therefore, they
[01:31:14] economic return. Therefore, they wouldn't do very well.
[01:31:16] wouldn't do very well. >> Here's the thing. I don't know if the
[01:31:17] >> Here's the thing. I don't know if the story is that simple that we all want to
[01:31:19] story is that simple that we all want to do slot machines all the time.
[01:31:21] do slot machines all the time. >> Exactly. Because the fact is that a lot
[01:31:24] >> Exactly. Because the fact is that a lot of people go to Las Vegas and do slot
[01:31:25] of people go to Las Vegas and do slot machines sometime, but we don't do that
[01:31:28] machines sometime, but we don't do that all the time. It's kind of rare
[01:31:29] all the time. It's kind of rare actually. What we really desire are
[01:31:31] actually. What we really desire are meaningful connections. We really desire
[01:31:34] meaningful connections. We really desire feeling like, hey, you know what? I met
[01:31:36] feeling like, hey, you know what? I met this person online that I'm following
[01:31:37] this person online that I'm following and he's following me and we really
[01:31:40] and he's following me and we really connect on all these points and oh by
[01:31:43] connect on all these points and oh by the way, I then found out interestingly
[01:31:45] the way, I then found out interestingly he's got a totally different opinion
[01:31:46] he's got a totally different opinion about Iran or abortion or whatever than
[01:31:48] about Iran or abortion or whatever than I do, but that's cool. Now we're we're
[01:31:50] I do, but that's cool. Now we're we're listening to each other. It kind of goes
[01:31:52] listening to each other. It kind of goes back to your point earlier about at the
[01:31:53] back to your point earlier about at the very start where we're talking about,
[01:31:54] very start where we're talking about, you know, the brain having an internal
[01:31:56] you know, the brain having an internal battle like, do I want the cookie or do
[01:31:58] battle like, do I want the cookie or do I want the salad?
[01:31:59] I want the salad? >> And unfortunately in the world we live
[01:32:00] >> And unfortunately in the world we live in, you know, this the cookie is going
[01:32:02] in, you know, this the cookie is going to give me a dopamine hit.
[01:32:04] to give me a dopamine hit. >> Yes. But we don't eat cookies all the
[01:32:05] >> Yes. But we don't eat cookies all the time. This is the point. We do eat
[01:32:07] time. This is the point. We do eat salads much of the time because we're
[01:32:10] salads much of the time because we're not just unconscious automaton that are
[01:32:12] not just unconscious automaton that are doing the cookies.
[01:32:13] doing the cookies. >> Dr. David Eagleman, thank you so much
[01:32:15] >> Dr. David Eagleman, thank you so much for the work that you do. I'm going to
[01:32:16] for the work that you do. I'm going to link your book below um so everyone can
[01:32:18] link your book below um so everyone can read this book. You've got a new book on
[01:32:20] read this book. You've got a new book on the way which I'm very excited about as
[01:32:21] the way which I'm very excited about as well. What's that book going to be about
[01:32:22] well. What's that book going to be about and when is that out?
[01:32:23] and when is that out? >> That's about the Ulisses contract and
[01:32:24] >> That's about the Ulisses contract and that'll come out in 2027.
[01:32:26] that'll come out in 2027. >> June. Okay. Um for anyone that wants to
[01:32:27] >> June. Okay. Um for anyone that wants to know how to change your life by changing
[01:32:29] know how to change your life by changing your brain, I think this is the perfect
[01:32:31] your brain, I think this is the perfect book to read. It's a New York Times
[01:32:32] book to read. It's a New York Times bestselling um author. Um and the book
[01:32:36] bestselling um author. Um and the book is absolutely fascinating. It was
[01:32:38] is absolutely fascinating. It was actually learning about this subject
[01:32:39] actually learning about this subject matter in LiveWire that helped me to um
[01:32:43] matter in LiveWire that helped me to um pursue more of a growth mindset and just
[01:32:44] pursue more of a growth mindset and just a growth mentality across my life and to
[01:32:46] a growth mentality across my life and to realize that if I'm not something now,
[01:32:48] realize that if I'm not something now, it doesn't mean that I can't be
[01:32:49] it doesn't mean that I can't be tomorrow. So, thank you so much for the
[01:32:51] tomorrow. So, thank you so much for the work that you do, David. And, um, it's
[01:32:53] work that you do, David. And, um, it's been truly illuminating, and I'm sure my
[01:32:55] been truly illuminating, and I'm sure my my neural pathways have expanded in
[01:32:57] my neural pathways have expanded in really important ways because of this.
[01:32:59] really important ways because of this. Great. Thank you, Stephen.
[01:33:01] Great. Thank you, Stephen. >> YouTube have this new crazy algorithm
[01:33:02] >> YouTube have this new crazy algorithm where they know exactly what video you
[01:33:04] where they know exactly what video you would like to watch next based on AI and
[01:33:07] would like to watch next based on AI and all of your viewing behavior. And the
[01:33:08] all of your viewing behavior. And the algorithm says that this video is the
[01:33:12] algorithm says that this video is the perfect video for you. It's different
[01:33:13] perfect video for you. It's different for everybody looking right now. Check
[01:33:15] for everybody looking right now. Check this video out and I bet you you might
[01:33:17] this video out and I bet you you might love

https://www.youtube.com/watch?v=m-nnyNZ0TQ0

Summary

TL;DR — The human brain is highly adaptable and can be sculpted through conscious effort and challenge, even as we age. While our brains peak in fluid intelligence early on, crystallized intelligence grows, and engaging in novel, challenging activities is key to maintaining plasticity and cognitive health throughout life. AI, while a powerful tool, should be used to augment human capabilities rather than replace the crucial process of learning through effort and critical thinking.

Key points

• Brain plasticity allows us to shape our brains throughout life by seeking new challenges and experiences.

• Our brains transition from fluid intelligence (early learning) to crystallized intelligence (accumulated knowledge), but can still adapt.

• The brain is a