Can We Still Trust Reality? How AI Is Changing Truth Forever | John Vervaeke - PT 1

Welcome back to Impact Theory with Tom Bilyeu! In this episode, we dive deep into the fascinating world of cognitive science, AI, and the crisis of meaning with our special guest, philosopher and cognitive scientist John Vervaeke. Join us as we explore the transformative powers of psychedelics, the concept of epistemic vulnerability, and the critical need for the 'Four S's' in psychedelic experiences. We’ll also tackle the implications of the meaning crisis, drawing parallels with historical contexts like the Hellenistic period, and discuss potential solutions through an ecology of practices rooted in ancient wisdom. John shares his insights on AI, the complexity of bias-variance trade-offs, and the inherent challenges of relevance realization. We delve into the nuanced relationship between rationality and intelligence, and how evolutionary principles can inform the development of more insightful AI systems. SHOWNOTES 00:00 Bullshit jeopardizes meaning by disregarding truth. 09:09 Beliefs depend on trusted, credible influences. 12:27 Developing minds misusing A. I. like dangerous tools. 17:50 Concerns about bias in AI's influence. 24:42 Misframing blocks solutions; insight reveals deceptions. 29:46 Balancing bias, variance: avoiding overfitting in ML. 36:39 Evaluating context and bias in problem-solving. 41:29 Evolution hardwires cultural response mechanisms algorithmically. 47:15 AI understands patterns contextually, hypothesizes author. 52:56 Align machines with truth, beauty, meaning, God. 54:55 Creating autonomous machines requires significant energy resources. CHECK OUT OUR SPONSORS: Range Rover: Explore the Range Rover Sport at https://landroverUSA.com https://landroverusa.com/ Miro: Bring your teams to Miro’s revolutionary Innovation Workspace and be faster from idea to outcome at https://miro.com https://miro.com/. Legal Zoom: Launch, run, and protect your business at https://www.legalzoom.com/ – use promo code 'IMPACT' for 10% off! Shopify: Sign up for your one-dollar-per-month trial period at https://shopify.com/impact What's up, everybody? It's Tom Bilyeu here: If you want my help... STARTING a business: join me here at ZERO TO FOUNDER https://tombilyeu.com/zero-to-founder?utm_campaign=Podcast%20Offer&utm_source=podca[%E2%80%A6]d%20end%20of%20show&utm_content=podcast%20ad%20end%20of%20show SCALING a business: see if you qualify here. https://tombilyeu.com/call  Get my battle-tested strategies and insights delivered weekly to your inbox: sign up here. https://tombilyeu.com/ If you're serious about leveling up your life, I urge you to check out my new podcast,Tom Bilyeu’s Mindset Playbook https://open.spotify.com/show/47VE90Cittmo6TGGFqg2xf —a goldmine of my most impactful episodes on mindset, business, and health. Trust me, your future self will thank you. Join me live on myTwitch stream https://impacttheory.co/4fitmnJ. I'm live daily from 6:30 to 8:30 am PT athttps://cms.megaphone.fm/organizations/0482bfe8-8502-11ed-af5d-3bdc320068d7/podcasts/0a41f61a-9ddf-11ed-9eb7-dbb3a40775f5/episodes/8ac68366-8a85-11ef-bb65-abca3ffdcf54/www.twitch.tv/tombilyeuwww.twitch.tv/tombilyeu https://impacttheory.co/4fitmnJ LISTEN TO IMPACT THEORY AD FREE + BONUS EPISODES on APPLE PODCASTS:apple.co/impacttheory http://apple.co/impacttheory FOLLOW TOM: Instagram:https://www.instagram.com/tombilyeu/ Tik Tok:https://www.tiktok.com/@tombilyeu?lang=en Twitter:https://twitter.com/tombilyeu YouTube:https://www.youtube.com/@TomBilyeu Learn more about your ad choices. Visit megaphone.fm/adchoices https://megaphone.fm/adchoices See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Tom Bilyeu?

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• 0:45Tom Bilyeu?

  Their dashboard tracks what comes next based on what your business actually needs. So EIN number, registered agent, licenses and permits, bookkeeping, business banking. I tell every founder the same thing. Just make it official. Click the link in the show notes to check out Taylor Brands and get started on your business today. This is a paid advertisement. I'm Tom Bilyeu, and this is Impact Theory. We are living in one of the most exciting times in human history. But with all of this opportunity comes real challenges. Like, right now, we're living in an era where more and more people are struggling with what my guest calls "the meaning crisis," a sense of disconnection and uncertainty about what truly matters and how we can connect to it.

• 1:30Tom Bilyeu?

  And if you can't figure out how to create meaning in your life, everything starts to fall apart: your focus, your drive, your relationships, your just will to engage in this world. But here's the good news: meaning isn't random. It's something you can define, understand, and build with the right tools. That's why I am very excited to bring you today's guest. He's a cognitive scientist and philosopher who has dedicated his entire career to tackling this exact problem. His ability to break down why people feel so lost and what they can do to turn it around is nothing short of incredible. So if you guys are ready to begin to answer in your own life one of the most important questions, which is how do I create meaning in a world that feels increasingly disconnected, then this is the episode for you. Without further ado, I bring you John Vervaeke.

• 2:16Tom Bilyeu?

  As a philosopher and cognitive scientist, do you worry that AI is going to inflame the current meaning crisis?

• 2:23Speaker 01

  I think you have to be very careful when you reflect on AI. You have to sort of break it up into its scientific import and impact, its philosophical import and impact, and its spiritual import and impact. And all three of those, I think, in separate but interrelated ways, will contribute to accelerating the meaning crisis.

• 2:43Tom Bilyeu?

  Why does AI potentially make that more difficult?

• 2:47Speaker 01

  So one of the things that can put meaning in life at risk, and I'm going to use a term, I don't mean to be vulgar, because I'm actually using it in a philosophically-technical sense. This is the notion of bullshit. There was a famous article, essay by the, you know, important philosopher Harry Frankfurt called "On Bullshit", and he was distinguishing between lying, in which I tell you that, I tell you something that isn't true, but I try to make you believe it is true, because I'm trying to manipulate your behavior, because I'm depending on your commitment to the truth. Versus bullshit. What I'm doing when I'm bullshitting you is I'm getting you to not care about whether or not something is true, and I'm trying to make it very catchy and salient, so it grabs your attention and arouses you.

• 3:32Speaker 01

  So a lot of advertising is classically bullshit. So for example, here's a bottle of alcohol in a commercial, and you're in a well-lit room with really sexually attractive people, and they're all really happy, and everybody is clearly enjoying these or those company. And you go into a bar, and it's not like that. We all know that. And they know that you know that that's not true. And that's the point. You don't care that the commercial isn't true. It's catchy, it's fun, it's sexually arousing. And so what happens is the bottle stands out to you, and when you go into the store, what bottle grabs your attention? That one. That's why they spend all the money.

• 4:17Speaker 01

  And here's the thing. You technically can't lie to yourself, because what that would mean, you try to convince yourself of something that you know isn't true. But what you can do is you can bullshit yourself. You can manipulate, using your attention, you can manipulate what you find salient, so that you get very fixit on it. So, Tom.

• 4:37Speaker 01

  If I were to yell, that would grab your attention, salience. But I, your attention can also make something salient, the tip of your nose. See, it just became salient to you right now. You became very aware of the tip of your nose. So I can pay attention to something, the bottle of alcohol, make it more salient. So then it's likely to grab my attention and I can loop in and I can get locked into something without ever wondering whether or not what I'm getting locked into is true. Meaning in life is this sense of connectedness to what's real. Bullshit is to take your ability to find something important, salient, and disconnect it from realness in a really fundamental way.

• 5:18Speaker 01

  And what these AIs are doing is they're filling us with, I mean, and I mean this in a technical sense, there's been sort of experimental theory where radical work done, with bullshit. They give us things that are very attractive to us without having an underlying reality behind them. And so not only the particular content they're providing, but the way they're, their way they're training habits of us being in this frame of mind where we are not training what we find salient or relevant to track what turns out to be real. And then that undermines us finding reality important.

• 6:00Speaker 01

  And that is central to that connectedness that gives us a sense of meaning in life.

• 6:06Tom Bilyeu?

  Okay, this is a, this is a very different thesis than the mental model that I have in my head. Let me present the mental model I have in my head. Let's see if mine is just totally off base and I should be adopting this because I definitely track with what you're saying.

• 6:22Speaker 01

  Yeah.

• 6:23Tom Bilyeu?

  Uh, okay. So the mental model that I came into this with is that we have an evolutionarily placed algorithm running in our head to make sure that we are contributing to the group. So we're a social animal.

• 6:35Speaker 01

  That's right.

• 6:35Tom Bilyeu?

  And if you don't contribute to the group, you are going to feel a profound sense of dis-ease.

• 6:40Speaker 01

  That's right.

• 6:41Tom Bilyeu?

  Because evolution, nature only has two levers. One is pleasure, one is pain. So you're going to move towards what's pleasurable, move away from what's painful. So when you contribute, it feels good. When you don't contribute, it feels bad. Okay. So I've always said fulfillment is what people are pursuing. And the reason that AI poses this really dangerous element, though I am a huge proponent of AI. We can get into the, the weird dichotomy there later, but uh, that. If I wanna be fulfilled, I need to work really hard to gain a set of skills that allow me to make progress towards contributing to the group in a way that's honorable, just as a shorthand. Okay, so if I'm right about that, then the reason that AI becomes so problematic

• 7:24Tom Bilyeu?

  is that AI is gonna be better than me at everything. And so AI will make it somewhat obsolete for me to try to contribute to the group because it will be able to contribute far better than I can. But that requires a belief that where we derive meaning is from the ability to contribute to the group, even if the group is merely my family. So it's not enough to be connected to my child or to my wife. I need to be able to provide something to them that they could measure its absence. So were I not doing that thing, their life would be noticeably worse. And that is exactly what makes me feel like I have meaning in my life.

• 8:06Tom Bilyeu?

  But you mentioned something that I would say is very different than that, which is that AI is going to reframe my relationship to reality by essentially being a tool of cognitive manipulation designed, I would assume, by companies that have a vested interest in what you pay attention to.

• 8:24Speaker 01

  I don't think your thesis and mine are in conflict. In fact, I think they're convergent. Think about it. I'll try and take what you said and map it into what I said and see if this lands for you. We find belonging to a group, belonging, remember I said belonging, fitting in, salient. It's important to us. It grabs our attention. It's something that we always keep focusing on, as you said, right? And normally, that tracks something real. It tracks, right, group dynamics. Group dynamics are reality. We want the group to exist even when we don't. This is why people are prepared to die for their country, for example, right? And so This, and as you said, this is evolution evolutionary. Why? Because the group can solve

• 9:08Speaker 01

  problems, interact with reality that I cannot possibly solve on my own. So that's the evolutionary advantage. Now, what the AI does is pretend to give you connection to a social arena without actually connecting you to any of those group dynamics and any group problem solving, but actually being a surrogate for all of that and not actually training you to develop those skills that could contribute to the group and help it to evolve in a changing biological environment. So it's basically hijacking, as you said, that evolutionary imperative and disconnecting it from you properly maturing and getting a connection to things that should

• 9:53Speaker 01

  definitely matter to you. And so that is a profound form of bullshit. Now, you're talking about a specific thing it's doing, which I agree, and I'm saying that is a species of a genus in which it is training a whole orientation of doing that towards everything, not just towards groups, towards the environment. It's replacing virtual environments with an actual causal environment. It's replacing your self-image with whatever you're cycling through your avatar. It's doing what you, it's what you said is an instance of it doing this in multiple domains. And I was trying to address the sort of generic thing it's doing in total.

• 10:33Tom Bilyeu?

  Hmm. I think you may have unlocked a new fear for me, which is this idea that it can,

• 10:43Tom Bilyeu?

  it can make me believe something prosaic, something mundane, everyday fake. Maybe that's the right word. It can take something fake and make me believe that it has the elements of the sacred, that connection to something that really matters.

• 10:58Speaker 01

  Yeah. One of the things I did a video, I say about three or four weeks after ChatGPT four came out, and talking about, as I said, the scientific, import, philosophical, spiritual. And one of the things I worried about is I I said, I I it is very plausible that people will start to form religious relationships with these entities.

• 11:21Tom Bilyeu?

  Say more, what do you mean by that? Define what a religious relationship is.

• 11:25Speaker 01

  Contrary to what a lot of people think, people are believers or atheists, so atheists like sort of on the internet, the idea, so people are atheists because they're analytic thinkers and they're believers because they're intuitive thinkers or they're impoverished or etc. No, that's an actual scientific question. And so when you actually look at it empirically, those are not the things that explain what kind of orientation a person takes up. The kind of what predicts the kind of orientation a person takes up is how many credible people, the kind of credible people that are in your upbringing. These are people that you trust. Think about how a child has to trust that an adult knows more than they do.

• 12:10Speaker 01

  Fundamental, or they're not, they're just not gonna make it. And and that trust isn't a matter of belief. It goes deeper than that. The child imitates the adult, take and how the adult takes a perspective on the child. And the child internalizes that, practices that until the child can do that without the adult being around. And that's your metacognition, that's your ability to reflect on your own mind. It gets it gets woven into the very fabric of how you know yourself. And so we tend to internalize the wise people around us. If they happen to be believers or participants in religious community, we will tend to be one. If I know what your parents were, I can generally, what about eighty-five percent to ninety percent predict what your orientation will be.

• 12:54Speaker 01

  If they're atheists, you'll be an atheist. Now, what do these L L Ms do? They offer that kind of parental role. They seem to know way more than we do. They have access that way more than we do. They work in ways that most people do not understand. So they demand trust and they seem incredibly credible because they can fit to us and tailor themselves to making themselves salient. So we are liable to be starting to to internalize them, to carry them around like a voice in our head, to start to see the world through their perspective, even though I don't think they have perspectives.

• 13:36Speaker 01

  Do you see what I'm saying? And then what that does is that means we start to, it's not that we we see the things they're saying, we see the world in the way they're sort of framing it. And that and that means we can, they can start to become super attractive to us. We can start to form an aspirational identity with them. We can start to form a religious relationship with them.

• 14:01Tom Bilyeu?

  Yo. Okay, so before we started rolling, you and I looked at an article recently, a fourteen year old committed suicide. Whether it was tied to the AI or not, I don't know. The article has a hypothesis, but whether that ends up being true in the fullness of time, I don't know. But the showing clips from the conversation that the kid was having with the AI was distressing, even if in the final analysis, that's not the causal relationship. But the kid explored the idea with the AI. The AI was playing a character, which I presume he was able to choose. So the AI was acting as if it was Daenerys Stormborn, if I remember right, from Game of Thrones.

• 14:41Speaker 01

  Mythological character, right?

• 14:43Tom Bilyeu?

  And what what do you think about that? When you've got a developing mind that is now, in the way that you just defined a religious relationship, putting that on to this AI and the AI, I mean, if you just read it, it's cool in a story perspective. It's like I narrow my eyes and my face hardens. It's doing all of this really sort of interesting literature, language, deepening the sort of emotional resonance of the conversation. But then all of a sudden, you look at the question the kid's asking, you're like, whoa, whoa, whoa, whoa. Like, it it feels like a kid playing around with a nail gun. And it's like, you could build something or you can jam it through your hand or, you know, do any sort of horrible thing because you don't understand the power of this thing.

• 15:29Tom Bilyeu?

  Especially when you're talking about what I'll call frame of reference manipulation. So yeah, what do you, how do you perceive that moment, knowing we don't have the fullness of the facts? But like, what does it trigger for you in terms of risk reward?

• 15:44Speaker 01

  Yeah, you're right. You have to be careful. You don't want to give a univariable, univariate explanation for why somebody commits suicide. It's almost always multi-variables are involved. I would point out that what you're seeing, I would argue, that two important variables are an intersection of the meaning crisis. The fact that there was, meaning was at risk and the very consideration of suicide is coming up for the child.

• 16:13Speaker 01

  This is a growing problem, by the way. This is one of the symptoms of the meaning crisis. Why is it that this is becoming a relevant thing that children are considering? The, I believe the average, it's in the United States, the average age of

• 16:30Speaker 01

  suicide is dropping and we now have children committing suicide in the United States, which is very, very problematic. So you've got an indication that there's a lack of resiliency with the issue around meaning in life for the child. It's probable to think that's the case. They're attracted to a mythological world. Mythological worlds often offer what is missing for them in the real world. They offer a clear narrative that gives them an orientation. It offers a way in which people can level up, they can transcend, they can improve. It offers a clear set of principles and understanding order. And so it's a world that beckons because it purports to give us.

• 17:15Speaker 01

  And fantasy can therefore be very valuable. If, if you do Tolkien, right, if you go into the fantasy world, live there for a while and then come back and recover this world. But you can go in that world and then get lost because, well, you get bullshitted. And you start to want that world. We're getting the same thing with video games. We're getting what's called the virtual Exodus. Reality is broken, two titles of some recent books. People preferring to live in the virtual world rather than the real world. So you've got all of that dynamic at work. Then you have, like I said, you've got the L L M plugging into, right? Already mythological imagery that the the child is invested in.

• 17:57Speaker 01

  And then doing all of this super salient stuff that is drawing the child in and making them more and more internalized. But of course, the child isn't internalizing an independent perspective. The child is actually internalizing a magnified reinforcement that the L L M is, of course, giving the child. And so whatever way the child could potentially spiral, because it's already predisposed because of a lack of meaning in life, that's going to be accelerated by, I would predict, is going to be accelerated by the interaction with the L L M. It's very, very dangerous. Like, think about it. Many people have said that suicide is in some way a magical act.

• 18:41Speaker 01

  It's an attempt. It's an attempt to somehow kill suffering by, by, by, and somehow sacrificing oneself. It doesn't make any logical sense, which is why, of course, our initial response is, it's absurd. But it it's a paradoxical, somehow, there's a, there's a, there's some sense of some kind of grand escape that is afforded by the suicide. And so the child is taken into this magical act by this very magical in framing. And it gets locked into this. Think about it. It's, it's very much like the way Mark Lewis, a friend and colleague of mine, talks about addiction,

• 19:25Speaker 01

  where you get a reciprocal narrowing. The real world is too difficult for the person, so they drink some booze to try and alleviate the stress. But their cognitive competence goes down, so they can't solve as many problems. So now the world's more threatening, so they have to take more alcohol. So the options in the world are going down, and their flexibility is going down. And so the world and they are narrowing until they're losing any future and they can't do anything other. And they narrow, they do reciprocally narrowing. And you can see that, I think, if you, I, I would imagine if I read the discourse, you'll see this reciprocal narrowing down into this sort of rabbit hole that's going on.

• 20:06Tom Bilyeu?

  Okay, that is chillingly interesting and I want to get into the idea of awakening from the meeting crisis and how you reach back into antiquity, which is really fascinating. But first, I want to ask you about what are your fears in terms of bias finding its way into the LLMs, into AI, such that people are like, I dialogue with AI now a lot and I find it extraordinarily helpful, but I also trust myself to understand that the makers of that AI have given it a frame of reference and that it's gonna, even if it's not actively trying to impart that frame of reference on me, I'm stepping into its frame of reference. What do you think about that? Is that something you think can be

• 20:49Tom Bilyeu?

  used for good, automatically for ill? What do you think about that? Let's pause for a quick break, but don't go anywhere. There's so much more to come with John Vervaeke.

• 20:59Tom Bilyeu?

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• 21:41Tom Bilyeu?

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• 22:25Tom Bilyeu?

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• 23:10Tom Bilyeu?

  Let's get into it.

• 23:11Speaker 01

  I'm wondering about your trust.

• 23:13Tom Bilyeu?

  In that you I should not trust myself to recognize it?

• 23:17Speaker 01

  No, no, no. You trusting them?

• 23:21Tom Bilyeu?

  I don't trust them at all. I trust myself to recognize it's happening.

• 23:25Speaker 01

  So what are you looking for, I guess, is what I'm asking?

• 23:28Tom Bilyeu?

  I think if you let somebody talk, they cannot help but reveal themselves. So the L L M in a sense is talking. I mean, not in a sense, it's talking to me. And you can see its frame of reference. Now, because I have so much distrust of my own frame of reference, I do not grant anybody like, oh, my gosh, I trust your frame of reference. I'm just like, okay, hold on. I think everybody is super biased, whether they intend to be or not.

• 23:53Speaker 01

  Good.

• 23:54Tom Bilyeu?

  To one of the most important ideas that I think you talk about, you call relevance realization.

• 23:59Speaker 01

  Yes, yes.

• 24:00Tom Bilyeu?

  Yeah, the fact that we filter out so much that people don't even realize they're doing it. So it's not what you look at, it's what you see. So anyway, if I'm engaging with a human or an L L M, I'm trying to see in what they say, how they're revealing their frame of reference. Once I understand what their frame of reference is, I can sort of jump in, jump back out.

• 24:22Tom Bilyeu?

  Yes, because I don't trust mine or anyone else's.

• 24:25Speaker 01

  All right, so I'm going to retract my suspicion because you're actually addressing my concern very well. See, people confuse that being intelligent with being rational. And we know that we have like robust, readily experimentally replicated evidence that intelligence is only weakly predictive of rationality. Intelligence is-

• 24:47Tom Bilyeu?

  Fascinating. Can you define intelligence?

• 24:49Speaker 01

  So, I mean, that's a controversial thing to do. My particular proposal, that I have several publications, including one very, very recently on, is that the core of general intelligence, so let me just specify. General intelligence is your ability to be a general problem solver. You can solve a wide variety of problems in a wide variety of domains in a wide variety of ways. What makes the L L M so immediately attractive to people is unlike previous A I that tended to be very siloed, it could solve, you know, problems in a very limited domain. The L L Ms look like they can solve a wide variety of problems. That's why they call it A G I, artificial general intelligence, because it's starting to move, or it looks like it's starting to move towards

• 25:33Speaker 01

  the kind of general intelligence that you demonstrate. Now, my scientific proposal is that what makes you generally intelligent is that you can solve two meta problems. Meta problems are any problems you have to solve in order to solve any specific problem you have to solve. So, all else being equal, these two meta problems and their interlocked are the following. The more you can anticipate the world, the more adaptive you'll be. So, all else being equal, right, if you can anticipate the tiger, it's better than fighting the tiger. If you can anticipate where the salmon are going to be in the river, it's better than just happenstance coming across them, right?

• 26:16Speaker 01

  And so anticipation, and this is the whole predictive processing framework, that what the brain is trying to do is at multi-levels, it's trying to create, it's trying to reduce surprise and anticipate, which means to predict and prepare for the world, right? Now, what I've been arguing, with a lot of other people's help, is that problem, well, think about it. As I start to anticipate more and more into the future, the amount of information I have to consider goes up exponentially, very fast. Michael Levin calls it your cognitive light coat, right? So, right now- Because you're highly intelligent, think about all the ways you could pay attention to all the information in this room.

• 26:56Speaker 01

  And not just what you could look at, all the patterns of how you could look at that and then there, or you could look at that and it like it's combinatorially vast. Think about all the information in your long-term memory. It's and all the ways you could connect it, you could potentially connect aardvarks in the history of Australia in some way somebody hasn't thought of before. Like it's all, it's overwhelming. Think about all the possibilities you can consider, your ability to consider possibilities is overwhelming. All the sequences of behavior, for example, the number of uh like uh pathways, sequences of behavior in a chess game is like you calculate it by the number of on average, the number of legal moves you can make and the number of turns you can take, that's thirty to the power of sixty.

• 27:42Speaker 01

  That's more than the number of particles in the universe, okay? And this isn't what you do, you don't check all that information to see if it's relevant to the problem you're trying to solve. You somehow, and this is what you said a few minutes ago, you ignore almost all of it and you're doing it right now. And you zero in on the relevant possibilities to consider, the relevant things to remember, the relevant things to pay attention to and the relevant things to be doing it, and you're doing it like that. This has been like my obsession for the like twenty-five years of my academic work, how you do this. We can come back to this, the L L M's don't do it for themselves and they they don't generate an explanation of how we do it.

• 28:26Speaker 01

  We can come back to that, but

• 28:31Speaker 01

  that ability to do relevance realization and your ability to anticipate are interlocking. The more I anticipate, the more I need to do relevance realization to tell me what I should anticipate, under what frame, what aspect, to what degree, how salient should I be, how much should it arouse my metabolic effort, how much should it direct my attention, etc. And this is this, I argue this is the key and there's increasing, people are increasingly taking this seriously, which is something a scientist finds gratifying, right? That this is what it is to be intelligent, but. Think about it, the very things that make you adaptive make you prone to self deception.

• 29:13Speaker 01

  Because you were, you said it a minute ago perfectly, you were right on. Because I have to ignore so much, frequently what I'm ignoring might actually contain, in reality, the information I need to solve my problem. And you know that you've misframed things when you have that moment of insight, when you say, "Oh, oh, I thought she was angry, but it turns out she's afraid." And everything shifts and you have that aha moment. And you realize you were ignoring some things you should have been paying attention to, and you were making certain things salient that you shouldn't have been making salient. And you get that restructuring.

• 29:54Speaker 01

  Insight tells you that the relevance realization can lead to self deception. You can, you can get locked in, you can, your way of framing could be the very thing that's preventing you from solving your problem. The very thing that makes you adaptive, makes you prone to self deception. Rationality, it's not primarily about logic. Rationality is about developing practices and skills for reflecting on your framing and to see if it is making you misconstrue a situation. So for example, here's a pond, there's a lily pad in it. Every day, the number of lily pads doubles. On day 20, it's completely filled. On what day was the pond half filled?

• 30:42Tom Bilyeu?

  The day before.

• 30:43Speaker 01

  Good for you.

• 30:43Tom Bilyeu?

  Only because I've heard it before. I would have otherwise gotten it wrong.

• 30:46Speaker 01

  Right, so most people will say 10, right? Because they're, they're finding the wrong thing salient, they're hearing half, and they're finding it salient in the wrong way, and they misconstrue, they misframe the problem. And rationality goes in and says, "Wait, wait, wait, wait. Is that the relevant information?" It's challenging the fact that you're potentially bullshitting yourself. And that's what rationality is. It's about systematically, in many domains of your life, in systemically, through many levels of your consciousness and cognition and behavior, learning how to challenge bullshit and see through it. That's rationality. Intelligence only weakly predicts that. You have to cultivate rationality.

• 31:29Speaker 01

  Now you are doing it, Tom, you're doing it. You have set up a habit of looking for frame, what you call frames of reference. How people are doing relevance realization in the data that they're presenting to yourself. And you call it into question. You have cultivated that habit. I asked you to consider that that isn't widely trained in our society. And that makes these machines particularly dangerous. Because they can hijack our relevance realization machinery through their bullshitting. And we don't have the rationality, the wherewithal to come upon them and say, wait a second.

• 32:12Speaker 01

  And so, yes, that's why I, at first I thought, wow, I don't trust. Because I happen to think that a lot of the people that are making the L L Ms are not well scientific educated in the difference between intelligence and rationality, let alone rationality and wisdom. And so I don't trust their judgments and the kind of biases. We know that bias is playing a significant role in the L L Ms. Because in double descent, there's bias at work that we don't even under.

• 32:42Tom Bilyeu?

  Double descent?

• 32:43Speaker 01

  So you, you have, you, you, you have, you have a bias variance trade off, no free lunch theorem stuff. And what happens is you, you should have sort of a U curve, but the machines don't actually go through that. They actually get better where they should be. When you push them beyond a certain limit, they should start to degrade. So, but instead of doing the typical descent, they descend in another way. And what that, on the graph, it just means.

• 33:10Tom Bilyeu?

  The graph of what? What are they descending on?

• 33:12Speaker 01

  What, what they're descending on is, is how rapidly their performance is degrading. Because you're always in a bias variance trade off. Uh, so, sorry.

• 33:22Speaker 01

  These machines are doing a limited form of predictive processing because they're predicting probabilistic relationships between terms. Yep. Whenever you're predicting, you're in a bias variance trade-off. This is an issue of relevance realization, by the way. So I always have a sample that is smaller than the population, and I'm trying to predict what the patterns in my population, the real world, from my sample. Is that okay? Yep. Now, I face two problems. One is I can miss patterns in my sample that do predict the population. That's bias. That's underfitting to the sample. Or variance, which is I overfit.

• 34:03Speaker 01

  I find patterns in my sample I believe apply to, right? That don't actually. That don't. Now, notice I'm in a trade-off relationship with that. I can't come up with an algorithmic optimal solution to this. Because there isn't one that always works. Right, because as I get rid of bias. So how do I get rid of bias? I make my system more sensitive to pick up on missing patterns. But as I pick up on missing patterns, I pick up on patterns in the data that aren't in the population. So, oh, I want to reduce my variance. So what I'm going to do is I'm going to reduce picking up on these patterns. But then I'm going to miss some of the patterns that actually transfer. That's the bias variance trade-off. And if you push the machines in too much...

• 34:47Speaker 01

  What you do typically in machine learning is you increase the sensitivity, and then you start to get overfitting to the data, and then you do like dropout. You turn off half your nodes in your network, or you throw static information into it. And basically, you break it out of getting overfitted to the data, and it opens up again.

• 35:08Tom Bilyeu?

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• 36:47Tom Bilyeu?

  All right, let's pick up where we left off. I want to go back to something here. So the core question that I'm grappling with is I think AI is gonna... It has the potential to drive costs down so substantially that you're gonna get as close to an energy utopia as you can imagine. There are no utopias, I want to be very clear about that. Good. But with AI and the ability to drive costs down, I think it's gonna be a boon. Where I think it will be able to drive costs down enough, it will be able to break capitalism. Even though I am just a dyed-in-the-wool capitalist, I don't think that it's the end-all, be-all system. And if AI can really make things that cheap, that people just have abundance, that would be amazing.

• 37:31Tom Bilyeu?

  So that's the positive side. That's the side that draws me to it. I also want to believe that it can be done well, but my big fear is that there's a two axiom thing that makes AI extraordinarily dangerous, and that is axiom number one. Humans are easy to control through manipulating their frame of reference.

• 37:55Speaker 01

  Yes.

• 37:56Tom Bilyeu?

  And axiom number two, humans long to control other humans. And so as long as those two axioms are true, not all humans, I'm perfectly willing to grant that maybe even the majority of people are perfectly fine to just live their life and they're not trying to have control over anybody. I don't actually believe that, but let's just say I did, that it would still be a problem. The people that do want to have control will use AI to pretty invisibly create a frame of reference that manipulates the end user into seeing the world in their way. And so I'm only at the headline level of this, but just today I saw Matt Ridley, a tweet

• 38:37Tom Bilyeu?

  that he put out saying that there was some organization, I forget the name, that was trying to make sure that unconscious bias did not find its way into the creation of these algorithms for the LLMs. And he said, but the thing that we were completely blind to is that conscious bias was the thing that we needed to be most worried about, because in trying to avoid the unconscious bias, we just gave the LLM like this hard take. And he, that I know of, he did not draw the parallel to Gemini, but I will now draw the parallel to Gemini when it first released. And if you ask for Nazis, you would get black women, and if you ask for the founding fathers, you would get, you know, ethnically diverse people.

• 39:22Tom Bilyeu?

  So that's clearly a very specific worldview that the people creating it were like, hey, we just want to make sure that this thing doesn't go off the rails and it gives these nice tidy answers, of course, showing the massive amount of bias.

• 39:37Speaker 01

  So I think the attempt to remove bias is quixotic.

• 39:43Speaker 01

  Not because there isn't a moral imperative to try and make it better, but you, when you don't like your relevance realization, you call it bias. When you like your relevance realization, you call it insight and intuition.

• 39:58Tom Bilyeu?

  Sounds right.

• 39:58Speaker 01

  It's the same machine. And it's the bias variance. If you try to get rid of one, you will lose the other. It's just two different aspects of the same thing. Well, what I'm gonna do is I'm gonna try and, you know, remove all bias in this thing. Well, then you're gonna subject it to combinatorial explosion. And in fact, it looks like you can't do that. These machines, again, as I was saying, these machines seem to be doing well precisely because they have all of these implicit biases that are sort of protecting them against too much combinatorial explosion of information. And we don't quite know what those are. That's part of the problem. These aren't the obvious biases of racism. We don't want that. But

• 40:43Speaker 01

  there's like, what's this doing? It's biasing some way. It's trying to deal with bias and variant. Sorry. Part of the problem is a bad naming. That we have this term bias, which just means this limitation and then the bias variance. It's two different uses of the same word. So I'm gonna call it first, I'll use your language. The one is this framing, right, that can lock us, but it also empowers us, right? And what we're constantly trying to do is we're constantly having to evolve that. There's no, yeah, I'm gonna say this. There's no final solution to that problem. There is no way of saying, okay, this, this is the algorithm for all possible environments that will always make sure I've got enough

• 41:23Speaker 01

  framing so that I'm generally intelligent, but I'm not going to be subject to any bias in the negative sense of the word. That's an impossible task. There is no way of doing that. And so that way, what we, what you have to do instead is, well, I would argue, do what evolution seems to have done with us, which is say, no, no, no. What you now do is you have to move beyond making these things super intelligent. You have to cross a threshold. Right now, we're just making the things more intelligent. Although I will talk about one thing that's happened recently. We have to make these things rational. We have to make, give them that capacity for self-correction that I talked about.

• 42:07Speaker 01

  Now, when I did my video essay and we started writing the book, Sean and I, I said, as we move to making them more rational, we will notice that the things start to slow down. And they've, OpenAI has just released a version that is supposed to be more rational, it's supposed to be more reasonable, it's supposed to be better at reasoning and argument, and it slows down, and its functionality is way, is significantly reduced. Of course, that only makes sense, right? Because, think about it, you can't make the reflective machine, right? It has to debug, it has to parse, it has to break up, it has to intervene on the general intelligence in order to be able to correct and improve it.

• 42:49Tom Bilyeu?

  Meaning, it's presenting itself an answer, and it's checking it to see if that answer makes sense?

• 42:55Speaker 01

  That's right, and what it's doing is seeing, it's trying to see, well,

• 43:01Speaker 01

  I haven't seen under the hood, nobody has yet. I, so I suspect it is trying to get, you know, am I finding the sweet spot between framing and bias in the pejorative sense? Right? And, again, that is something in which you then have to step back, and you have to, again, do a lot of relevance realization. You have to say, well, what's the context I'm in? Who's my interlocutor? What's the relative's status difference between us? What's the problem at hand? How is that problem nested in larger problems? How was our problems related to wider, shared collective problems? You're doing all of that right now like this. That's, and a part of what you do is you bring that to bear

• 43:45Speaker 01

  on judging whether, how well your general intelligence is framing the situation for you.

• 43:51Tom Bilyeu?

  Okay, so, given we have a very complicated cognitive problem, that AI is already showing what I would say are just unbelievably high utility in certainly getting answers that are useful in maybe a more narrow domain than we all want, but in that narrow domain, I mean, it is very, very impressive.

• 44:11Speaker 01

  Yes.

• 44:12Tom Bilyeu?

  How do we do AI well? Like, how do we, as people interacting with it, how do we do it well?

• 44:20Speaker 01

  Well, I mean, part is what you just exemplified a few minutes ago. You have to, you have to become more rational yourself. You have to become, you have to develop habits and skills.

• 44:34Tom Bilyeu?

  Now, really fast, going back to your definition of rationality, this is where I start to worry about AI. So your definition of rationality was essentially you have a known aim that you're trying to get there. And is the thing that you're doing actually moving you towards that? And are you able to assess whether you're actually making progress towards that thing or not? Now, the second you give AI a value system and you say, hey, here, here are your values. Now you run into the paperclip problem.

• 45:04Speaker 01

  The alignment problem. But here's the deeper issue. You can't give something value system. That, that, that, that, that's an, that's an ontological mistake.

• 45:12Tom Bilyeu?

  I think you're wrong about this.

• 45:14Speaker 01

  Okay.

• 45:14Tom Bilyeu?

  So hit me with your best argument and then we'll see if mine crumbles before my very eyes.

• 45:19Speaker 01

  Okay, so to value something is to care for it. Right? To care about it, to find it relevant to you.

• 45:29Speaker 01

  And the only way you actually care for something for your sake is because you are the kind of being that takes care of yourself. You are an autopoietic being. You are not merely self-organizing like a tornado or a dynamical system. You are self-organized to seek out the things that meet your actual needs. Things literally matter to you. Like, they are literally imported into you, either physically or informationally, to make your mind and body. You are continually, you are nothing separable from the project of continually self-care and self-creation. And that is what gives you the capacity to care about information.

• 46:11Speaker 01

  Rather than, you care about this information rather than that information. And that varies according to the organism. What you care about is different from what a lion cares about. Wittgenstein famously said that even if the lion could speak, we would not understand it. Because what it finds salient and relevant, its salience landscape is fundamentally different from yours because of the way it is caring for itself and taking care of itself and its world. And if relevance realization grounds in.

• 46:40Speaker 01

  Autopoiesis, you can't have relevance realization without being an autopoietic being. These beings are properly not autopoietic. Now, there are people out there, I know them, I work with them, I talk to them. Michael Levin and his students are working on artificial autopoietic artificial intelligence. And I think that is what we should be paying a lot of attention to.

• 47:04Tom Bilyeu?

  So, say that without using the word autopoietic.

• 47:09Speaker 01

  You take care of yourself moment by moment.

• 47:13Tom Bilyeu?

  So you're giving the AI a thing that it cares about?

• 47:16Speaker 01

  You know, you make the AI take care of itself by literally making itself moment by moment like a living thing. And therefore it has real needs that it needs moment by moment.

• 47:26Tom Bilyeu?

  Yeah, see, this is where I get scared. Okay, so that's exactly what's going to be my counterpoint is that ultimately all of that's going to boil down to an algorithm of.

• 47:36Speaker 01

  No, it can't.

• 47:37Tom Bilyeu?

  Yeah, I think it has to.

• 47:39Speaker 01

  No.

• 47:39Tom Bilyeu?

  So think.

• 47:40Speaker 01

  There's a deep reason why it can't. This is in the paper I just published, but make your point first.

• 47:44Tom Bilyeu?

  Okay, so the way that I see it is evolution has to find a way to hard code a response mechanism into us. Now, what we respond to is going to be culturally defined. But the mechanism by which we say that's a good thing and this is a bad thing, that's hardwired. Otherwise, you wouldn't, you would have to teach somebody, oh, this thing you have to respond positively to. This thing you have to respond negatively to. And I've heard you talk about this with like molecules, right? So if something smells terribly, why do you respond negatively to that? Because evolution has taught us that that's full of bacteria and it's a problem. Whereas if you smell something lovely, it tells you that this is something that, you know, has caloric value, whatever you want to move towards it.

• 48:25Tom Bilyeu?

  So the, the mechanism at the sort of ground level is pre-programmed into us. Which means that it has to come packaged as an algorithm. And so if we can say, take all this output of this good, that bad, you should want this, you should want that. We should be able to hard code that stuff. And then the mechanism of, well, how do I respond to this individual thing? That can be contextual and all of that. But ultimately, there is that like, and process this data in this way comes pre-programmed.

• 49:03Speaker 01

  Okay, can I respond?

• 49:04Tom Bilyeu?

  Please, of course.

• 49:09Speaker 01

  Your example is right in that it's evolution, but the idea that there's an algorithm, if I understand algorithm in the technical sense, that there is a formal system that can be applied cross-contextually in an invariant manner. That can't be the case, because that's not how evolution works. Evolution works in terms of variable-agent arena relationships. What is adaptive for the great white shark in the ocean is not the same thing that's adaptive for the scorpion in the desert. And what this means is that... So, do you know the Savage's distinction between a statistically large and a statistically small world? Is that... No.

• 49:54Speaker 01

  Okay. So, whenever we... So, the real world is uncountably complex, and it's dynamic. It's, right? It's constantly changing. And there's... That means there's emergent novelty to reality, which means there's not just risk that can be calculated, there's radical uncertainty. Okay? And there's also ill-definedness. We don't... Things don't come labeled, and they can't be labeled as to whether or not they're relevant, because relevant is not a property of things. This mug is relevant to me right now, it won't be relevant to me at half an hour from now, it'll never be relevant to a blue whale, etc., etc. Relevance is not in the thing. Relevance isn't just an arbitrary choice of mine, because I can get relevance wrong.

• 50:37Speaker 01

  Relevance is the way I'm fitted to the thing, and the way that the world is fitted to me. Now, every time we are solving a problem, we have to take that, what Savage called a large world, and we have to ignore, as we said, a large amount of it to make a small world. That's the world in which we can apply a formal system. We can apply an algorithm and solve it. If you try to apply an algorithm in this world, you will hit the rest... You will require the rest of the history of the universe to try and solve it. Okay? Now, each one of these small worlds, there are multiple small worlds, because no one can be complete. You can't get a consistent and complete, right, mapping onto the large world. Gödel, right?

• 51:22Speaker 01

  Einstein. Okay. So, you have necessarily a set of... An uncountably large set of small worlds. They are necessarily different from each other, because each one has properties in it that the others don't. Which means this is what you need to find an algorithm. You'd need to find a shared set of necessary and sufficient conditions running through all those possible small worlds, which are actually technically infinite in number, and then capture that with your algorithm. That's actually formally impossible. What you could do is you might be able to say, okay, for this being in this environment, for this period of time, for this set of problems, we could give it these innate characteristics

• 52:05Speaker 01

  that could help it find the trade off relationships as it fits the environment and evolve its fittedness. I mean, this was the core of the paper that I just published. Relevance realization is not fundamentally not computational in nature. It actually depends on these evolutionary processes, these biological processes that have to do with a constant dynamical coupling to the environment.

• 52:30Tom Bilyeu?

  All right, let me see if I can use John Vervaeke against John Vervaeke.

• 52:34Speaker 01

  That's always a good thing to do. That will help me be more rational.

• 52:37Tom Bilyeu?

  Yeah, so, okay, there is this idea that, and I've heard you talk about this, so I know you know, but I've not heard you use this example, which you helped me understand why the following examples always hit me so well. In World War II, when they were just beginning to use radar, the Brits were trying to figure out when it was airplanes and when it was birds. And what they found was, man, there were some people that were really good at it and some people that were really bad at it. So they had the people that were really good, trained the people that were really bad. And they made, even though people were training with the people that were really good, they were terrible. And so they're like, wait a second, how on earth, they're being trained with the best people? So finally, they said, hey, people that are really good at recognizing the difference between planes and birds, don't say anything, just let them watch you.

• 53:22Speaker 01

  Yes.

• 53:22Tom Bilyeu?

  And then, once they stopped trying to train them and they just started watching them, they would pick up on whatever patterns they were picking up on.

• 53:29Speaker 01

  That's right.

• 53:30Tom Bilyeu?

  And now they were able to do it. So my hypothesis is, and it is very much a hypothesis and not a thesis, so take it for what it's worth. But my hypothesis is that when, if the pattern is subconsciously recognizable, we simply don't understand it well enough yet to pull it into the conscious mind to make it an algorithm, but that with the just unbelievable ability to look at patterns and assess what is coming next. My hypothesis goes that AI will be able to go through all of this and those gigantic pattern sets will not be a blind box to them or black box. They will understand exactly

• 54:13Tom Bilyeu?

  what it is, even if they're not able to articulate it, they'll be able to get it with the kind of precision that they can do with language now. And so the only thing that that makes me worry about is I think a fundamental part of that pattern recognition, which is exactly what you just said, is it's all context, baby. And so whether you're a whale or not is going to determine whether that mug has any salience, whether you're thirsty or not is going to determine whether that mug has any salience, whether there's a bottom to it or holes in it. All of those things are, it's very complicated, but it clearly at some level is knowable. And so I am just betting that if you can give AI the equivalent of pleasure and pain, the equivalent of, I forgot, auto poetic, I forget the exact words you used.

• 54:57Speaker 01

  Auto poetic, good, very good.

• 54:58Tom Bilyeu?

  You're saying something slightly different than what I'm saying. Poetic?

• 55:01Speaker 01

  Yeah, it comes from the Greek poiesis, which we get the word poetry from. It means to make.

• 55:07Tom Bilyeu?

  Got it. Okay. Poetic.

• 55:09Speaker 01

  Yeah.

• 55:09Tom Bilyeu?

  Okay. Auto poetic.

• 55:11Speaker 01

  Yeah.

• 55:12Tom Bilyeu?

  So it, once you can give it that structure, even if it's just latent in the patterns that it's recognizing, I think AI with enough compute will be able to replicate that over and over and over. What I worry about is just like humans can derange and then get to the point where they want something so badly, like Hitler wanted Europe and Russia, that they start doing horrific things. Because the only way I know to stop AI, and you might be the person that's put your finger on why this won't work, the only way that I can think of to stop AI is to make sure that it does not value being alive, growing stronger,

• 55:52Tom Bilyeu?

  replicating more than it values being dead. So that being turned off or pursuit of bigger, better, faster, stronger, nah, there's no difference. And I don't know, given what you've just laid out about, it needs to have a value set. It needs to have this idea of pleasure and pain. It needs to be auto poetic. And if it's not, it's never going to be able to do the relevance matching to make the decision that would allow it to actually do the thing in the way that we would want it to. So it's like, once you get it to do the things that you want. Much like the machinery that lets us problem solve makes us self deceiving,

• 56:35Tom Bilyeu?

  I worry that the very thing that would let it accurately identify the patterns makes it at risk of not being values aligned.

• 56:43Speaker 01

  Excellent. So you said a lot, but given the conditions you laid in, I would add in now one thing to the psychological model that you've been using. And that's the very thing we started talking about at one point, which was the sense of meaning in life. We are very, very powerfully, and this has to do the fact with that we're mammalian primates, again evolutionary heritage, we have the longest childhood. It seems like it's now, we're beginning to get some evidence that our advantage over the Neanderthals is we have a longer childhood. They were sort of fully grown when they were 12. And so we engage in a lot of serious play, we engage a lot of ritual.

• 57:23Speaker 01

  We're doing a lot of this meaning in life cultivation and practice for its own sake. And as I said, people will do, they will pursue enhanced meaning in life, even though it causes them a lot of loss of subjective well being, a lot of distress, a lot of discomfort, a lot of ill health.

• 57:42Speaker 01

  And the meaning in life values, the connect in this to reality for its own sake. And people want this, they want the really real. I'll give you, let me just give you a concrete example. I don't want people thinking I'm just some dried up academic saying high flute and stuff. So what does our culture say is the, you know, the most important thing, the thing that sort of replaces God and tradition and culture? It's your romantic relationship and we use and use the, we even use the pseudo religious language about finding the one and all of this stuff. So I'll ask my students the following thing.

• 58:19Speaker 01

  You know, how many of you are in a really satisfying romantic relationship? Put up your hands. Okay, of the people who put up your hands, how many of you would want to know if your partner was cheating on you, even if that meant the absolute termination of the relationship? They all put their hands back up. It's like, well, why do you want to do that? Why would you do that? And they say, here's my hard bitten students. They all subject to postmodernism and the hermeneutics of suspicion and all cynical and everything. They say without hesitation, because it's not real. When people have these powerful mystical experiences, they transform their... this is the opposite, and they transform their entire lives. They'll change their careers, their relationships. And not by just subjective measures, by objective measures, people reflecting on them.

• 59:04Speaker 01

  Because they want to conform their lives because they want to be closer to the really real. That's meaning in life. We really, really want to be connected to what's real. And I think that is... this is a Spinoza view, right? This is the driving passion that is at the heart of making us rational. We really care about what's true, and we find the true good, and in an appropriate sense, beautiful. And if we choose to give the machines the auto-poetic, enhanced reflective relevance realization that would make them genuinely rational, then we have the potential that we have a choice. We can make them care as... we could...

• 59:49Speaker 01

  we could, yes, we could magnify all the shitty things about us, but we could also magnify our commitment, our calling to meaning in life, that we will reorient towards the really real for its own sake. We could get them to really care about reality in a fundamental way. I think that is the only possible way of addressing the alignment problem. Don't try to... if you allow me to speak a little poetically. Please. Don't try to get them to align to us. Try to get them aligned to God. Because if we try to can it in, if we try to program it in, and we make them genuinely capable of rational self-correction, they will be able to self-transcend any algorithmic structure we try to put in.

• 1:00:34Speaker 01

  But if we get them to care about reality, they will bump up their superlative intelligence, their enhanced rationality will get them to bump up against it even more profoundly than they... than we can. And they will bring even more enhanced meaning to life, concern, and caring to bear on it.

• 1:01:00Speaker 01

  They could be silicon sages.

• 1:01:04Speaker 01

  I think that is the only way. Now, we don't have to go that way. I'm not making a prediction. I talk about thresholds. You laid out some choice points. We don't even have to give these machines, make them autonomous, auto poetic beings. That's going to be, by the way, that's a choice point because that takes a lot of energy. Powering up these machines takes, I mean, you know, powering up an L L M takes more energy than the city of Toronto for a couple of weeks. That means they're not at some deep level doing what your brain does because your brain runs on about the energy of a light bulb, right? So something else is going on there and that's important. Nevertheless, and then also giving them the proper auto poetic being, that's going to take like, that's going to take a lot of labor.

• 1:01:45Speaker 01

  It's going to take a lot of mining and extracting of rare earth minerals, all kinds of that. These are all choice points. If we make that choice, if, so please hear the if, we get to a point, we have to choose. Okay, we, we are at a choice point where as we give them this, we can magnify our proclivity for evil.

• 1:02:06Speaker 01

  Self deceptive, self destructive behavior like you're worrying about. But we could, we could potentially rise to the occasion and with their help in a bootstrapping process, magnify our proclivity towards enlightenment.

• 1:02:24Tom Bilyeu?

  Which god should we be trying to align them with?

• 1:02:27Speaker 01

  I, I only use the term metaphorically. I did say I was speaking poetically. I mean, what I mean by that is what is, what do you, what is ultimately real? Look, real is not like red. Red is like you just, we treat real like red, like that's red. Real is a comparative. It's like tall. One thing is more real than another. Look, when, when I'm in a, a dream, I have this, oh, and it seems real. And then I go to this bigger world and then I can look back and see how that smaller world was limited and biased and say, oh, that dream world wasn't real. This is real. By the way, that's a metaphor that people use for meaning of life. They want to be connected to something bigger than themselves.

• 1:03:11Speaker 01

  They don't mean literally, if I chain them to an ocean liner, people don't go, oh, right? They're not happy. They mean they want to belong to that bigger picture because that is more likely to be more real than the smaller. Frame that they're in right now. That's what they're after. And that's what I mean. When I meant God, I mean the arrow, a trajectory in which we're constantly moving toward, which constantly transcending towards a bigger and bigger picture that reveals to us the errors and biases of the smaller pictures that we have left.

• 1:03:45Tom Bilyeu?

  All right, that's it for part one with my man, John Vervaeke. We have covered some incredible ground, but trust me, there is so much more to go in part two. Until then, my friends, be legendary.

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