Latest / Drawn of History / Joe Rogan Experience _2521 - Aravind Srinivas(M4A_128K)

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Joe Rogan Experience _2521 - Aravind Srinivas(M4A_128K) · Drawn of History

• 0:04
  Speaker 1: The Joe Rogan Experience. Train by day, Joe Rogan podcast
• 0:08
  Speaker 1: by night, all day.
• 0:14
  Speaker 2: Good to see you.
• 0:14
  Speaker 1: You too. Thanks for having me.
• 0:16
  Speaker 2: My pleasure.
• 0:17
  Speaker 3: Yeah.
• 0:17
  Speaker 2: How many podcasts have you done? I don't know.
• 0:20
  Speaker 1: I don't know the count, but maybe tens.
• 0:23
  Speaker 2: Well, when we were talking, we were talking in the lobby.
• 0:25
  Speaker 2: I was like, this dude would be a good guest
• 0:27
  Speaker 2: because we were talking about ancient Hindu scriptures where you
• 0:30
  Speaker 2: were talking to me about something that sounds like a
• 0:32
  Speaker 2: nuclear bomb.
• 0:33
  Speaker 3: Yeah.
• 0:33
  Speaker 2: And I was like, oh.
• 0:34
  Speaker 1: The Brahmastra. I need to know more about this.
• 0:37
  Speaker 2: Yeah.
• 0:38
  Speaker 1: So the Brahmastra is part of the Mahabharata. You've talked
• 0:43
  Speaker 1: about Mahabharata.
• 0:44
  Speaker 2: Yeah, the Vimanas. Yeah.
• 0:46
  Speaker 1: So the Mahabharata is one of the two Hindu epics.
• 0:50
  Speaker 1: The other one is Ramayana. But Mahabharata is more interesting.
• 0:53
  Speaker 1: It's more complicated. It's like a lot of different stories
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  Speaker 1: interleaved together. And the Brahmastra is the equivalent of the
• 1:01
  Speaker 1: hydrogen bomb.
• 1:03
  Speaker 2: And how is it described?
• 1:05
  Speaker 1: It's described as a weapon of mass destruction, going to
• 1:09
  Speaker 1: annihilate the human population, should not be used at any cost.
• 1:14
  Speaker 1: There's a moral contract. You clearly have to be violating
• 1:18
  Speaker 1: so many things at a deeply moral level to even
• 1:23
  Speaker 1: wield it. And it's not actually accessible to most warriors.
• 1:29
  Speaker 1: There's probably two warriors in the world in that era
• 1:34
  Speaker 1: who were allowed to use it. And it has to
• 1:38
  Speaker 1: be passed through special access, like a teacher has to
• 1:41
  Speaker 1: pass it on to you, the secret, to use it.
• 1:43
  Speaker 1: Almost like, think of it as the equivalent of the
• 1:45
  Speaker 1: nuclear code. And Arjuna had it, this particular character in
• 1:52
  Speaker 1: Mahabharata called Arjuna. He was allowed to use it. And
• 1:55
  Speaker 1: then this other person was, basically Arjuna had a teacher
• 2:00
  Speaker 1: named Drona, And Drona had a son named Ashwatthama. And
• 2:06
  Speaker 1: Ashwatthama was always jealous of Arjuna. Arjuna was not Drona's son,
• 2:10
  Speaker 1: but he was his model disciple. And so Drona passed
• 2:14
  Speaker 1: on the secret of the Brahmastra to him. And Drona's
• 2:19
  Speaker 1: son also wanted it. But because it was his son,
• 2:23
  Speaker 1: he also passed on the secret to his son, even
• 2:24
  Speaker 1: though the son wasn't as good as Arjuna. And during
• 2:28
  Speaker 1: the war, Arjuna and Drona fought on the opposite sides.
• 2:32
  Speaker 1: It's just, you know, circumstances. And his dad died, Ashutama's dad,
• 2:39
  Speaker 1: the teacher died in the war. And so the sun
• 2:42
  Speaker 1: got mad and like unleashed the Brahmastra. And Lord Krishna
• 2:47
  Speaker 1: had to come and save the planet to not get
• 2:50
  Speaker 1: that destruction force.
• 2:52
  Speaker 2: How old is the Mahabharata?
• 2:55
  Speaker 1: Again, there's a lot of different opinions on this. So
• 3:00
  Speaker 1: I don't actually know for sure. my understanding is at
• 3:02
  Speaker 1: least 1,500 to 2,500 years old. Like, 1,500 years ago
• 3:08
  Speaker 1: is the minimum. 2,500 years ago is the maximum. So
• 3:11
  Speaker 1: it happened in some period in that 1,000-year time frame
• 3:14
  Speaker 1: between that. And there's still, like, it's still unclear if, like,
• 3:20
  Speaker 1: a lot of it is just, like, you know, being mythologized.
• 3:24
  Speaker 1: And what actually happened was just a war between kinns. Uh,
• 3:29
  Speaker 1: there were two groups of people, the Pandavas and the Kauravas. And, um,
• 3:34
  Speaker 1: you know, each side thought they were fighting for their
• 3:37
  Speaker 1: own rights and justice. But, um, at the end of
• 3:39
  Speaker 1: the day, you can crudely understand it as like essentially
• 3:44
  Speaker 1: fight for the kingdom. Um, basically they were like, there
• 3:48
  Speaker 1: was a previous generation and two brothers and they, and
• 3:51
  Speaker 1: both the brothers had a bunch of kids and those
• 3:54
  Speaker 1: kids were warring to get the next in line. And, um,
• 3:58
  Speaker 1: That ended up being like a massive war and a
• 4:01
  Speaker 1: bunch of other allies fought on each sides. And so
• 4:05
  Speaker 1: many amazing weapons were used as part of the war.
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  Speaker 1: And a lot of these weapons are like extremely, like
• 4:12
  Speaker 1: describe an extreme level of detail that is pretty incredible.
• 4:16
  Speaker 1: Like there's a lot of detail around like targeted weapons.
• 4:20
  Speaker 1: So you could precisely identify a target and just shoot
• 4:22
  Speaker 1: at that.
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  Speaker 2: And then- Does it explain like what the weapon is?
• 4:27
  Speaker 1: Yeah, so- There's one weapon called the Divyastra where you
• 4:30
  Speaker 1: can just specifically target any particular person or a group
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  Speaker 1: and it would just automatically direct itself and do it.
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  Speaker 1: Almost like a semi-autonomous weapon. And then Lord Krishna had
• 4:42
  Speaker 1: this weapon called the Sudarshan Chakra. It's basically a discus.
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  Speaker 1: And then you can just release it and it will
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  Speaker 1: go and specifically identify somebody and chop off their head
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  Speaker 1: and come back to you. It self-directs itself. So what
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  Speaker 1: I was amazed by is how interesting it is in
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  Speaker 1: terms of all the autonomy in the weapons, semi-autonomy or autonomy,
• 5:09
  Speaker 1: where the weapons could just be directed at people or
• 5:12
  Speaker 1: directed at a group of soldiers, and it would just
• 5:14
  Speaker 1: go and do its job and come back to the wielder.
• 5:17
  Speaker 1: And there were so many different astras, devyastra, varunastra, nagastra.
• 5:22
  Speaker 1: Ramastra is obviously the ultimate, the hydrogen bomb equivalent. And
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  Speaker 1: all of these are described in a lot of detail
• 5:28
  Speaker 1: and who has access to it. And of course, it's mythologized,
• 5:32
  Speaker 1: so it's described as these arrows in the back of
• 5:36
  Speaker 1: your shoulders. But you could understand it as somebody having
• 5:41
  Speaker 1: access to a lot of weapons. And then whoever was
• 5:44
  Speaker 1: powerful would go capture and colonize and gain power. And
• 5:50
  Speaker 1: essentially a fight between a group of cousins. That's the
• 5:54
  Speaker 1: bottom line of that story.
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  Speaker 2: Now, if we think of history as this linear progression
• 5:59
  Speaker 2: from caveman to us, and we hear about autonomous weapons
• 6:02
  Speaker 2: that were written in the Mahabharata somewhere around 2000 plus
• 6:05
  Speaker 2: years ago, we go, well, mythology. But if not, if
• 6:10
  Speaker 2: there's been some sort of rise and fall of civilization,
• 6:13
  Speaker 2: if there has been catastrophic, whatever it is, asteroid impacts,
• 6:18
  Speaker 2: shifting of the poles, whatever it is, it's caused great disasters.
• 6:22
  Speaker 2: You can imagine- that these people are remembering a time
• 6:27
  Speaker 2: where there was some sort of very advanced civilization. And
• 6:30
  Speaker 2: this is what they're describing. If you knew for a
• 6:32
  Speaker 2: fact that there had been a great advanced, technologically advanced civilization,
• 6:38
  Speaker 2: when we have evidence that they had some technology, like
• 6:41
  Speaker 2: the pyramids of Giza and stuff, how did you do that?
• 6:44
  Speaker 2: There's some technology involved, right? But we don't have evidence
• 6:47
  Speaker 2: of the technology. But if we did, if we knew
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  Speaker 2: for a fact, you would look at the Mahabharata and go, oh,
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  Speaker 2: this is history. They're just explaining it in a kind
• 6:56
  Speaker 2: of crude contemporary way for the time, arrows instead of
• 7:01
  Speaker 2: semi-autonomous drones with exploding heads on them. I mean that's
• 7:05
  Speaker 2: what we have now. All those things that they're describing,
• 7:10
  Speaker 2: hydrogen bomb, semi-autonomous and autonomous drones. I mean they have
• 7:15
  Speaker 2: autonomous fighter jets now. They don't need people anymore. We're
• 7:20
  Speaker 2: in that area right now. So when you read about
• 7:23
  Speaker 2: something like that from the Mahabharata, you go like, okay,
• 7:26
  Speaker 2: what was really going on?
• 7:27
  Speaker 1: Exactly.
• 7:28
  Speaker 2: Yeah.
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  Speaker 1: I mean, that's always been my fascination with those epics
• 7:32
  Speaker 1: and the level of detail with which they described all
• 7:35
  Speaker 1: these weapons and who had access, different levels of access,
• 7:41
  Speaker 1: the status required to have access, and how it was
• 7:45
  Speaker 1: used in the wars, different formations of the soldiers. They
• 7:49
  Speaker 1: had all these crazy formation structures like forming the army
• 7:53
  Speaker 1: like a lotus, forming the army like a, you know,
• 7:58
  Speaker 1: there's something called a chakra viha, like literally like it
• 8:01
  Speaker 1: has to have concentric circles. So you cannot like actually
• 8:04
  Speaker 1: get into the innermost circle without going through the outer circles.
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  Speaker 1: And then you can get killed by each of the
• 8:09
  Speaker 1: flanks whenever you're trying to enter in. And the secret
• 8:13
  Speaker 1: of how to actually break into these vihas, vihas means formations,
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  Speaker 1: was only known to a few people. And it's incredible. Like,
• 8:23
  Speaker 1: you could say, okay, like, somebody had to be extremely
• 8:27
  Speaker 1: skillful to have that sort of, like, visualizations and imaginations
• 8:31
  Speaker 1: of describing a story like that. And obviously, like, Tolkien
• 8:35
  Speaker 1: has done an amazing job with Lord of the Rings,
• 8:37
  Speaker 1: you know, in creating so much detail. At the same time, like,
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  Speaker 1: a lot of it actually coming through in real life
• 8:42
  Speaker 1: in some form, again, not exactly the same weapons, but
• 8:46
  Speaker 1: similar style, makes you wonder, Was there actually something around then?
• 8:51
  Speaker 1: And people have tried excavations in all these areas. There's
• 8:54
  Speaker 1: like two main areas in the Mahabharata. Hastinapur was the
• 8:57
  Speaker 1: name of the kingdom. And people have done excavations around
• 9:00
  Speaker 1: there and have like found some artifacts that might date
• 9:04
  Speaker 1: back to those years. But there are also some details
• 9:08
  Speaker 1: that are described in the epics that don't quite align
• 9:10
  Speaker 1: with reality. For example, all the men, all the main
• 9:14
  Speaker 1: warriors in that era were described as like very tall.
• 9:19
  Speaker 1: very big, seven, eight feet, whatever. I don't even know
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  Speaker 1: exact numbers. But studies by archaeologists also say that people
• 9:32
  Speaker 1: who lived in those years in those regions were probably
• 9:35
  Speaker 1: not more than six feet tall. So it's not clear
• 9:38
  Speaker 1: exactly what happened, what was correct, what was not correct,
• 9:41
  Speaker 1: and we just have to keep probing more. But I
• 9:45
  Speaker 1: find the idea fascinating to think of what could have
• 9:47
  Speaker 1: existed in sacred texts that was only partially communicated to
• 9:52
  Speaker 1: the next generation and having a lot of like reinterpretations.
• 9:56
  Speaker 1: Another thing that is very interesting to think about is
• 9:58
  Speaker 1: Vedic math. So basically Vedic math is like a branch
• 10:04
  Speaker 1: of mathematics that, you know, some people in India are
• 10:07
  Speaker 1: grown up learning. Like I read it myself too. And
• 10:11
  Speaker 1: some people actually practice it just to be sharper at
• 10:14
  Speaker 1: mental math for doing their exams, like GMAT and things
• 10:18
  Speaker 1: like that, GRE. And it has like a line in
• 10:23
  Speaker 1: the Vedas that says, oh, like one from the last digit,
• 10:26
  Speaker 1: two from the first digit, whatever, you know, so many
• 10:29
  Speaker 1: different ways of multiplying two different numbers, like 97 times 96. Oh,
• 10:32
  Speaker 1: like subtract the last two digits, put it in the right,
• 10:35
  Speaker 1: multiply the first digits, put it in the left. That's
• 10:37
  Speaker 1: the result. And then you wonder like, oh, wait, the
• 10:42
  Speaker 1: Rig Veda is so old. It's as old as, it's
• 10:44
  Speaker 1: the oldest sacred text out there. How is it describing computation?
• 10:49
  Speaker 1: That feels very unreal. Like, did they actually know or
• 10:55
  Speaker 1: understand advanced forms of computation even back in those days?
• 10:59
  Speaker 2: And how old is Rig Veda?
• 11:03
  Speaker 1: I don't exactly know how old it is.
• 11:05
  Speaker 2: Why don't we put that into perplexity?
• 11:08
  Speaker 1: Yeah, let's do that.
• 11:09
  Speaker 2: Let's find out. Yeah. Yeah.
• 11:13
  Speaker 1: It is technically the oldest sacred text out there.
• 11:19
  Speaker 2: And it's... So what's interesting is I wonder how old
• 11:24
  Speaker 2: the stories were by the time they were written down.
• 11:27
  Speaker 2: Like how much of it is relayed person to person
• 11:32
  Speaker 2: for years and years, just like the Bible, before it's
• 11:34
  Speaker 2: ever actually written down. Scholars usually date the composition of
• 11:38
  Speaker 2: the Rig Veda to about 1500 to 1200 BCE. So
• 11:40
  Speaker 2: its oldest layer is roughly 3,200, 3,700 years old today. Like.
• 11:49
  Speaker 2: If there really was, like, every ancient culture has a
• 11:55
  Speaker 2: story of a flood. Everyone, they all have an apocalyptic story.
• 11:58
  Speaker 1: Mahabharata had the same thing. Mahabharata had the same thing
• 12:01
  Speaker 1: where there was a big, like, almost like a tsunami-like thing.
• 12:05
  Speaker 1: I don't exactly know what it was called, but that
• 12:07
  Speaker 1: was the collapse of Lord Krishna's kingdom, Dwaraka. After the war,
• 12:12
  Speaker 1: a lot of people died, but some people survived, and
• 12:15
  Speaker 1: Even those who survived got wiped out by a calamity
• 12:18
  Speaker 1: or like some kind of like a fight among themselves.
• 12:22
  Speaker 1: And most of the people who participated in that era
• 12:25
  Speaker 1: actually died.
• 12:26
  Speaker 2: Here it is. The primordial, how do you say it? Manu?
• 12:30
  Speaker 3: Yeah.
• 12:30
  Speaker 2: Manu flood. Classic Hindu grape flood myth where the righteous
• 12:33
  Speaker 2: king Manu is warned by a divine fish about an
• 12:37
  Speaker 2: imminent deluge that will destroy humanity. He builds a boat,
• 12:42
  Speaker 2: loads it with his family. It's like Noah and the Ark.
• 12:46
  Speaker 2: It's the same thing. With seeds and animals, ties it
• 12:50
  Speaker 2: to the horn of the god in fish form, which
• 12:53
  Speaker 2: tows the boat to safety until the waters recede and
• 12:56
  Speaker 2: the world is repopulated. They all have the same story.
• 12:59
  Speaker 3: Yeah.
• 13:00
  Speaker 2: That's what's really crazy.
• 13:01
  Speaker 1: There is a concept in Hindu philosophy called the yugas.
• 13:07
  Speaker 2: Mm-hmm. I'm reading a book about it right now. Yeah, yeah, yeah.
• 13:09
  Speaker 3: So.
• 13:11
  Speaker 1: There's like different yugas and yugas are like thousands of years.
• 13:14
  Speaker 1: And the concept is that the yugas keep cycling around.
• 13:18
  Speaker 1: And so like we are in the Kali Yuga right now.
• 13:21
  Speaker 1: And before that was a Dwapara Yuga. That's when most
• 13:24
  Speaker 1: of Mahabharata happened. And before that, there was a Treta
• 13:26
  Speaker 1: Yuga where the Ramayana happened. And before that, there was
• 13:29
  Speaker 1: another Yuga.
• 13:30
  Speaker 2: What is next after Kali Yuga?
• 13:32
  Speaker 1: No, there is nothing next after Kali Yuga. It goes
• 13:35
  Speaker 1: back to the first one. I forget the name of
• 13:37
  Speaker 1: the first Yuga.
• 13:37
  Speaker 2: Because the interpretation that I'm reading is that we're not
• 13:40
  Speaker 2: in Kali Yuga anymore and that Kali Yuga ended in
• 13:43
  Speaker 2: the 1900s and Dwapar Yuga started then.
• 13:46
  Speaker 1: No, no. We are in Kali Yuga right now. 100%.
• 13:49
  Speaker 2: 100%. So why do people have different interpretations? Is that true? Yeah,
• 13:53
  Speaker 2: there's like a guru interpretation. There's like one specific guru
• 13:58
  Speaker 2: that has this interpretation that Kali Yuga ended in the
• 14:01
  Speaker 2: 1900s and that we're moving on.
• 14:05
  Speaker 1: Interesting.
• 14:06
  Speaker 2: Yeah. But I don't know who's right because it's an
• 14:08
  Speaker 2: enormous cycle, right? The cycles of humanity. Yeah.
• 14:11
  Speaker 1: Thousands of years.
• 14:11
  Speaker 3: Yeah.
• 14:11
  Speaker 1: Thousands of years. And so.
• 14:14
  Speaker 3: Yeah.
• 14:15
  Speaker 1: So these are the four yugas. And.
• 14:22
  Speaker 2: So why do people have different interpretations? Let me tell
• 14:26
  Speaker 2: you the book I'm reading. Yeah. See if this book
• 14:32
  Speaker 2: is discredited, young Jamie. It is by a guy named
• 14:40
  Speaker 2: David Steinowitz. Steinmetz. David Steinmetz. The book is called The Yugas.
• 14:51
  Speaker 1: Interesting.
• 14:52
  Speaker 2: Yeah, I mean, the problem is when someone's got their
• 14:55
  Speaker 2: own interpretation or some guru's interpretation, it doesn't totally align.
• 15:01
  Speaker 2: It's hard to know who's right and who's wrong. Keys
• 15:04
  Speaker 2: to understanding our hidden past, emerging energy age, and enlightened future. Yeah.
• 15:11
  Speaker 2: So go back up to that again. So this is
• 15:14
  Speaker 2: in the description. See what it says there? Where it says,
• 15:18
  Speaker 2: in 1894, an Indian sage gave us an explanation not
• 15:21
  Speaker 2: only for our hidden past, but for the trends of
• 15:24
  Speaker 2: today and for future enlightenment. So there's like one guy's
• 15:27
  Speaker 2: interpretation that this guy is going off of.
• 15:31
  Speaker 1: I guess the difference might be that... He thinks the
• 15:33
  Speaker 1: yuga cycle is 24,000 years, whereas I think it's probably
• 15:37
  Speaker 1: much longer than that.
• 15:39
  Speaker 2: Yeah. Four yugas together is 4,320,000 years. You know what's
• 15:46
  Speaker 2: really nutty? Yeah. One of the really nutty things is
• 15:51
  Speaker 2: both in the ancient Sumerian texts and in some of
• 15:56
  Speaker 2: the ancient Egyptian texts, there's depictions before the flood of
• 16:01
  Speaker 2: people who reigned for thousands of years as kings. Yeah.
• 16:05
  Speaker 2: And it's common. And it's also, they're referenced multiple times
• 16:10
  Speaker 2: in different scripts that are from different parts of what
• 16:14
  Speaker 2: was Sumer at the time. It's really weird. It's really weird.
• 16:17
  Speaker 2: Because they take it as established history once it gets
• 16:20
  Speaker 2: to a certain age, once they get into, like, whatever
• 16:24
  Speaker 2: the age is where they can verify that this person
• 16:26
  Speaker 2: was the king for a certain period of time. But
• 16:28
  Speaker 2: it's all in the same text as people that reigned
• 16:31
  Speaker 2: for 6,000 years.
• 16:33
  Speaker 1: Yeah.
• 16:33
  Speaker 2: It's weird.
• 16:34
  Speaker 1: And then one of them just wipes out the whole thing.
• 16:36
  Speaker 3: Yeah.
• 16:37
  Speaker 1: And I mean, this is also somewhat like tangentially related
• 16:41
  Speaker 1: to the Fermi paradox. You know, like if you assume
• 16:48
  Speaker 1: all these things are happening on Earth itself, that entire
• 16:50
  Speaker 1: civilizations are getting wiped out.
• 16:52
  Speaker 2: Yeah.
• 16:54
  Speaker 1: And like, we always wonder, you, you've explored this topic
• 16:57
  Speaker 1: the most, um, and, um, where are the aliens? Right. And, um,
• 17:02
  Speaker 1: there are different arguments that like, okay, like the reason
• 17:06
  Speaker 1: we haven't quite found that is because the great filter exists. And, uh,
• 17:12
  Speaker 1: there is like one entertaining theory that, um, I like
• 17:15
  Speaker 1: just for the sake of entertainment is, um, almost all
• 17:19
  Speaker 1: civilizations end up advancing technologically a lot and, um, either
• 17:23
  Speaker 1: a calamity wipes them out or like they build some
• 17:25
  Speaker 1: misaligned AGI and then AGI wipes them out. And, um,
• 17:30
  Speaker 1: and because of that, um, they never actually like, and
• 17:33
  Speaker 1: end up being visible to us or the other theories
• 17:38
  Speaker 1: that like, they're like, um, we haven't quite built the
• 17:42
  Speaker 1: wine Neumann probes to actually go find them. And, um,
• 17:46
  Speaker 1: both of them are plausible. And, um, You know, there's
• 17:51
  Speaker 1: no clear way to, like, know unless we actually, like,
• 17:56
  Speaker 1: send out enough probes.
• 17:57
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• 18:55
  Speaker 2: There's a bunch of possibilities. I mean, there's almost too
• 18:57
  Speaker 2: many to count, but there's the possibility that they are
• 19:00
  Speaker 2: observing and that they don't want to interfere and that
• 19:02
  Speaker 2: we are on some sort of evolutionary cycle.
• 19:06
  Speaker 3: Yeah.
• 19:06
  Speaker 2: A cycle of cultural evolution, civilization evolution. Yeah. And one
• 19:10
  Speaker 2: of the things about this, the crazy ages that come
• 19:13
  Speaker 2: from the Sumerian text and from the ancient, the hieroglyphs
• 19:18
  Speaker 2: that depict the Zeptet. How do you say it? Zepteti? No.
• 19:25
  Speaker 2: How am I saying that? What is that text, that ancient?
• 19:29
  Speaker 2: Remember we talked about it was Zahi Hawass and he
• 19:31
  Speaker 2: denied its existence. Zepteti? Is that it? Either way. You're
• 19:38
  Speaker 2: dealing with these kings that reign for thousands and thousands
• 19:41
  Speaker 2: of years. Well, you know, David Sinclair is in the
• 19:44
  Speaker 2: middle of this research now They're working on life extension drugs.
• 19:48
  Speaker 2: Like that are actionable.
• 19:50
  Speaker 1: Yeah.
• 19:51
  Speaker 2: Yeah, that's it. Zeb Tepe.
• 19:52
  Speaker 1: Yeah.
• 19:53
  Speaker 2: I've heard of him. So these, but this is what's
• 19:55
  Speaker 2: so weird. If they look at hieroglyphs, they get to
• 19:58
  Speaker 2: a certain point and they're like, oh, Khufu, he was real.
• 20:01
  Speaker 2: This guy was real. All these people were real. Yeah.
• 20:03
  Speaker 2: But then they get back to these guys that reigned
• 20:06
  Speaker 2: for thousands of years and they go, oh, that was
• 20:08
  Speaker 2: just horseshit. Yeah. But why is it that all these
• 20:11
  Speaker 2: people have these stories that align with this timeline that's pre-flood?
• 20:16
  Speaker 2: It's all like the same story. Yeah. And then if
• 20:19
  Speaker 2: you're talking about these ancient Hindu scriptures that are discussing
• 20:24
  Speaker 2: technology that seems remarkably similar to technology that we have today. Yeah.
• 20:28
  Speaker 1: The Vimanas are flying cars, basically.
• 20:31
  Speaker 2: And probably what we're going to have a hundred years
• 20:33
  Speaker 2: from now or whatever it is, or we could have
• 20:35
  Speaker 2: gone that way in the past.
• 20:37
  Speaker 1: And it's very entertaining to think of like, let's say
• 20:39
  Speaker 1: something happens to us, right? I don't want anything to
• 20:41
  Speaker 1: happen to us, but let's say something happens to us.
• 20:43
  Speaker 1: And would people really believe you were like launching reusable rockets?
• 20:47
  Speaker 2: Right. Or making FaceTime calls to people in Australia?
• 20:51
  Speaker 1: Yeah.
• 20:52
  Speaker 3: Yeah.
• 20:53
  Speaker 1: Like even fundamental things, like all we were doing today.
• 20:57
  Speaker 1: I think it's all like incredible. Like there's, there's a
• 20:59
  Speaker 1: lot of things that, Could be just technological ideas or
• 21:02
  Speaker 1: maybe people actually had it and the knowledge of it
• 21:05
  Speaker 1: was lost and it's not been documented, it's not been
• 21:08
  Speaker 1: passed along and so we are skeptical if they ever
• 21:10
  Speaker 1: had it.
• 21:11
  Speaker 2: Yes.
• 21:11
  Speaker 1: And so we end up reinventing it in different forms
• 21:13
  Speaker 1: again and again and again and we keep cycling through
• 21:15
  Speaker 1: this process.
• 21:16
  Speaker 2: Well, it also could be that this is the natural
• 21:19
  Speaker 2: progression of human curiosity. The human curiosity and ingenuity always
• 21:23
  Speaker 2: moves into these very particular ways. Like, what's the best
• 21:26
  Speaker 2: way to defeat my enemies?
• 21:27
  Speaker 3: Yeah.
• 21:27
  Speaker 2: If we're always going to be territorial primates... We're always
• 21:31
  Speaker 2: going to want to defeat our enemies. We're always going
• 21:32
  Speaker 2: to protect ourselves from being invaded. So we're going to
• 21:35
  Speaker 2: make better. And just with technological innovation, it just goes
• 21:39
  Speaker 2: down the same path. Oh, we figure out bullets. Oh,
• 21:41
  Speaker 2: we figure out nuclear bombs. Well, we figure out we
• 21:44
  Speaker 2: don't even have to use an actual plane. We can
• 21:46
  Speaker 2: use an autonomous drone and that delivers it. And then
• 21:49
  Speaker 2: scale upwards and onwards and AI and then also life extension.
• 21:54
  Speaker 2: So if these people were able to make the pyramids, like,
• 21:59
  Speaker 2: you know, there's a lot of speculation as to the
• 22:02
  Speaker 2: timeline of the pyramids, but let's just say they really
• 22:06
  Speaker 2: built it 2,500 BC. Let's just say back then. What
• 22:09
  Speaker 2: the fuck were they using? Like, what were you, what
• 22:12
  Speaker 2: did you do? How did you get these stones down
• 22:14
  Speaker 2: from the mountains that were 500 miles away? How about
• 22:16
  Speaker 2: this one? How about that one? Yeah. We were going
• 22:18
  Speaker 2: to get to that for sure. There's a ton, no, thank,
• 22:21
  Speaker 2: what's good, good as any. How about these temples that
• 22:24
  Speaker 2: they find in India that are carved entirely out of
• 22:29
  Speaker 2: one piece of stone?
• 22:30
  Speaker 3: Yeah.
• 22:31
  Speaker 2: What did you do? How did you do that? How
• 22:34
  Speaker 2: long ago did this happen? How many of them were
• 22:37
  Speaker 2: buried and then they had to uncover them and then
• 22:40
  Speaker 2: figure out what is this? Who made it? There's no timeline.
• 22:45
  Speaker 2: No one really knows. There's no evidence of tools that
• 22:48
  Speaker 2: were capable of doing this kind of work back then.
• 22:52
  Speaker 2: And they're huge and beautiful and perfect. And they have
• 22:56
  Speaker 2: acoustic properties. And the geometry is fucking fantastic.
• 23:01
  Speaker 1: Yeah. It's nuts, man. It's not just that. All of
• 23:04
  Speaker 1: these temples were actually just built, not just, they were specifically,
• 23:09
  Speaker 1: the locations for them are picked out so that you
• 23:12
  Speaker 1: get the right seismic vibrations over there in terms of, like,
• 23:17
  Speaker 1: proximity to the ocean, the gravitational waves from the sun
• 23:21
  Speaker 1: and the moon. People actually made that level of, like.
• 23:25
  Speaker 2: Look at this, man. Imagine the undertaking of carving that
• 23:31
  Speaker 2: temple out of the side of a fucking giant piece
• 23:35
  Speaker 2: of rock.
• 23:37
  Speaker 3: Yeah.
• 23:37
  Speaker 2: You screw up one thing and it's over.
• 23:40
  Speaker 1: There's no simulations. You just have to build it.
• 23:43
  Speaker 2: What did they have? This is the question. Like, imagine
• 23:48
  Speaker 2: today if we had to do this. Look, it's possible.
• 23:51
  Speaker 2: This is a possible endeavor. It can be done.
• 23:53
  Speaker 3: Yeah.
• 23:54
  Speaker 2: But imagine what kind of technology we have to need
• 23:58
  Speaker 2: to map it out to make sure that it was
• 24:00
  Speaker 2: all precise. I mean, it's precise within, like, millimeters from
• 24:06
  Speaker 2: point to point. And everything is done out of one
• 24:10
  Speaker 2: piece of stone. Like, what did they do? Was it chisels?
• 24:14
  Speaker 2: Did you do that with chisels?
• 24:15
  Speaker 1: That's crazy.
• 24:16
  Speaker 2: How many times did you have to sharpen your fucking chisel?
• 24:18
  Speaker 2: That's nuts. Or did you have something completely different?
• 24:22
  Speaker 3: Because.
• 24:23
  Speaker 2: Some of the more intricate ones, see if you can
• 24:24
  Speaker 2: find these. Some of the crazy ones inside these temples,
• 24:29
  Speaker 2: there's sculptures that are three-dimensional, and they're carved, like, inside
• 24:34
  Speaker 2: of the sculpture. So there's, like, an outer area, and
• 24:37
  Speaker 2: then there's all these openings, and then inside it's highly detailed. Like,
• 24:42
  Speaker 2: how'd you even reach in there?
• 24:44
  Speaker 3: It just says they use chisels and hammers, and I
• 24:45
  Speaker 3: don't think that's possible. Awesome.
• 24:48
  Speaker 2: And careful geometric planning.
• 24:51
  Speaker 3: People trying to do that. They said, like, this is
• 24:53
  Speaker 3: how much work someone could do in, like, 12 hours
• 24:56
  Speaker 3: with a hammer. And they get nowhere, let alone, like,
• 25:00
  Speaker 3: perfect and looking good.
• 25:02
  Speaker 2: Yeah, it's nuts, man. And there's a lot of evidence
• 25:04
  Speaker 2: of stuff like that all over the world, which is
• 25:08
  Speaker 2: really weird. You have the stuff in Peru, like Sacsayhuaman.
• 25:12
  Speaker 2: When you look at these stones and it looks like
• 25:13
  Speaker 2: they're melted into place. And they're 900 tons. Like, what
• 25:18
  Speaker 2: did you do?
• 25:19
  Speaker 3: Yeah.
• 25:19
  Speaker 1: How did he even get it up there?
• 25:21
  Speaker 2: Where'd they get it? How'd you get it there? How'd
• 25:23
  Speaker 2: you align it perfectly? Built in only 18 years. How
• 25:26
  Speaker 2: do they know that? How do they know that? Because
• 25:29
  Speaker 2: it's attributed to one king.
• 25:31
  Speaker 1: Yeah.
• 25:32
  Speaker 2: So King Christian I, 756 to 773 CE.
• 25:33
  Speaker 3: Maybe.
• 25:33
  Speaker 2: How do you know, though?
• 25:42
  Speaker 3: Yeah, they said the archaeologists said it would have... They
• 25:44
  Speaker 3: calculated it would take them 100 years to do it.
• 25:47
  Speaker 2: Yeah.
• 25:47
  Speaker 1: Yeah, I mean, this is where, like, you know.
• 25:49
  Speaker 2: I don't know.
• 25:49
  Speaker 1: Different historian accounts are all, like, muddled up, you know? Uh-huh.
• 25:53
  Speaker 2: Well, it's a real problem. History is a real problem.
• 25:55
  Speaker 1: But, yeah, it goes back to, like, the thing you
• 25:57
  Speaker 1: were saying, right? You know, what is one thing that's
• 25:59
  Speaker 1: common across all these different ages is human curiosity. So,
• 26:04
  Speaker 1: I mean, that's something that, you know, I would love
• 26:06
  Speaker 1: to get your take on this. Like, I've been toying
• 26:09
  Speaker 1: with this idea... called the curiosity premium, which is the
• 26:14
  Speaker 1: most effective people, the most successful people have always been
• 26:17
  Speaker 1: the most curious people, the ones who have been good
• 26:19
  Speaker 1: at asking the best questions. And they tend to do
• 26:22
  Speaker 1: better in every aspect of their life. And you're a
• 26:26
  Speaker 1: good example of that. So that's why I would love
• 26:27
  Speaker 1: to get your take on this. And the reason I
• 26:30
  Speaker 1: believe that is because long term, people who continuously ask
• 26:35
  Speaker 1: questions tend to do better. They make more money. They
• 26:39
  Speaker 1: have a higher quality of life. They're happy. They have
• 26:42
  Speaker 1: more compounding relationships. People find them more interesting. And so
• 26:45
  Speaker 1: they compound their relationships over time. And so naturally they
• 26:50
  Speaker 1: end up succeeding. But their spirit of inquiry, their intrinsic
• 26:55
  Speaker 1: curiosity doesn't actually stop once they succeed. It only, they
• 27:00
  Speaker 1: just channelize it even more. And so that's why it
• 27:03
  Speaker 1: keeps compounding. And I would argue that like it's the
• 27:06
  Speaker 1: only quality, it's the only like quality that makes us
• 27:09
  Speaker 1: really human. you know, in this world where we can
• 27:12
  Speaker 1: seek a lot of information and get information way faster
• 27:15
  Speaker 1: than ever before, it feels like that's that one universal
• 27:19
  Speaker 1: human quality that's existed since ancient time, since the oldest texts. Like,
• 27:24
  Speaker 1: in fact, in the Rig Veda, you're explicitly encouraged to
• 27:29
  Speaker 1: seek wisdom more than wealth. And it's not just an
• 27:33
  Speaker 1: idea specific to Hinduism. That specific idea exists in the Bible,
• 27:36
  Speaker 1: it exists in the Quran, it exists in the Torah.
• 27:39
  Speaker 1: It's not that seeking well is admonished by religious texts.
• 27:42
  Speaker 1: It's actually that it's more important to seek wisdom. And,
• 27:46
  Speaker 1: you know, like you can, why I said you're a
• 27:48
  Speaker 1: good example of that is like, sure, you have a very,
• 27:51
  Speaker 1: very large podcast, but the way you're running it is like,
• 27:54
  Speaker 1: you're just curious about a lot of things and asking
• 27:56
  Speaker 1: a lot of questions. And I think that's that one
• 27:59
  Speaker 1: quality that's very important. So, and I feel like it's
• 28:03
  Speaker 1: the oldest thing. It's the only thing that we've known
• 28:05
  Speaker 1: since ancient time. Being curious.
• 28:08
  Speaker 2: Well, I think it's stimulating to people and genuine curiosity
• 28:12
  Speaker 2: is stimulating to other people. When someone is genuinely curious
• 28:15
  Speaker 2: about something, I become curious about it. I think it's contagious.
• 28:19
  Speaker 2: And I think that it's also an authentic quality. And
• 28:23
  Speaker 2: I think there's something about really wanting to know something
• 28:27
  Speaker 2: and being interested in something. And if you're curious... Generally,
• 28:31
  Speaker 2: you're going to ask more questions about something so you
• 28:33
  Speaker 2: have a deeper understanding of it. So if you're trying
• 28:36
  Speaker 2: to do whatever you're trying to do, a sport, a game,
• 28:39
  Speaker 2: you'll probably get better at it because you're more curious.
• 28:41
  Speaker 2: Because instead of just assuming things, you'll ask more questions.
• 28:45
  Speaker 2: You'll reexamine things. It's one of the most important human qualities.
• 28:49
  Speaker 2: And to me, it's one of the most attractive human qualities.
• 28:52
  Speaker 2: It's always been. When I meet curious people, I'm always interested.
• 28:55
  Speaker 2: I'm always like, tell me what you're curious about and
• 28:57
  Speaker 2: I'll tell you what I'm curious about. Let's talk. And
• 29:01
  Speaker 2: this podcast started out genuinely because of– well, a lot
• 29:05
  Speaker 2: of it was just talking shit with friends. But it
• 29:08
  Speaker 2: also led into– like one of my very first guests,
• 29:11
  Speaker 2: actual guests, was Graham Hancock. And it's just because I
• 29:14
  Speaker 2: was curious because I had read Fingerprints of the Gods
• 29:17
  Speaker 2: and I had seen him talk. I had seen speeches.
• 29:19
  Speaker 2: And I'm like, I want to know. Like what do
• 29:20
  Speaker 2: you know? What do you think is going on? And
• 29:24
  Speaker 2: he's another guy, incredibly curious. And absolutely fascinated with his
• 29:30
  Speaker 2: takes on ancient history. He has been talking about this
• 29:35
  Speaker 2: subject a long time. And when he first wrote Finger,
• 29:40
  Speaker 2: of the gods, I think that came out in like,
• 29:43
  Speaker 2: I want to say it was like 97 or 98
• 29:45
  Speaker 2: or something like that. And I remember reading it and
• 29:47
  Speaker 2: so many of my friends, you know, educated friends like
• 29:50
  Speaker 2: this horse shit, why are you paying attention to this
• 29:52
  Speaker 2: more and more and more as time goes on, it's
• 29:56
  Speaker 2: been proven that he's correct. The timelines shifted back. And
• 29:59
  Speaker 2: from the publication of that book, the discovery of Gobekli
• 30:02
  Speaker 2: Tepe and the surrounding area, like it's like, okay, now
• 30:07
  Speaker 2: we realize, well, there was some crazy shit going on
• 30:09
  Speaker 2: at the very least 11,000 years ago. So we pushed
• 30:13
  Speaker 2: civilization back 5,000 years. So like, and this is just
• 30:17
  Speaker 2: what we found now. And we keep finding things, keep digging,
• 30:20
  Speaker 2: keep looking. And then you see the stuff that they're
• 30:23
  Speaker 2: finding underneath the pyramid with this radio tomography where they're
• 30:26
  Speaker 2: looking under the pyramid. It seems that there's structures under
• 30:29
  Speaker 2: the– have you seen that stuff?
• 30:31
  Speaker 1: I haven't seen that.
• 30:33
  Speaker 2: I had the scientist that's involved in it. He's an
• 30:35
  Speaker 2: Italian guy, Filippo Biondi, and he came on the podcast.
• 30:38
  Speaker 2: Wonderful accent. Almost as good as yours. It was amazing.
• 30:42
  Speaker 2: But he's describing the use of this stuff and that
• 30:44
  Speaker 2: they've used it. successfully on known areas in pyramids and
• 30:50
  Speaker 2: other structures. In fact, in Italy, there is a particle
• 30:58
  Speaker 2: collider that is underneath a mountain. And using this technology,
• 31:02
  Speaker 2: which is satellite-based technology, they get an accurate description of
• 31:07
  Speaker 2: this particle collider. I think it's 1,200 meters underground. How
• 31:14
  Speaker 2: far is that thing underground? We'll find out. But it's
• 31:17
  Speaker 2: like deep under stone. And they find that they can
• 31:21
  Speaker 2: get an accurate, like they can actually give you the
• 31:24
  Speaker 2: dimensions of this particle collider. They have like an image
• 31:26
  Speaker 2: of it. And this same technology is showing that there's
• 31:31
  Speaker 2: these columns underneath the pyramid in various places that are
• 31:36
  Speaker 2: 20 meters wide. And they have coils around them. They
• 31:41
  Speaker 2: don't know what the hell they are. And the whole
• 31:44
  Speaker 2: structure of this thing, it's not small. It goes almost
• 31:47
  Speaker 2: a kilometer into the ground. There's this enormous bottom of it,
• 31:52
  Speaker 2: and it seems like it's something that's constructed. And so
• 31:55
  Speaker 2: they're like, okay, well, the pyramid is crazy. It's crazy enough.
• 32:00
  Speaker 2: But if there's something underneath it that's a man-made or
• 32:04
  Speaker 2: someone made it that's a kilometer deep into the ground,
• 32:07
  Speaker 2: like What the fuck are we even talking about? Like,
• 32:10
  Speaker 2: who made this? What did they have? 1.2 kilometers into
• 32:17
  Speaker 2: the mountain. That's nuts. It's a half a fucking mile
• 32:22
  Speaker 2: plus into the mountain. And this thing can see through
• 32:26
  Speaker 2: all that and get this accurate depiction of this particle collider.
• 32:30
  Speaker 2: And it's showing with multiple scans. Not just one. Multiple
• 32:34
  Speaker 2: scans in different technology. The same exact images. The same
• 32:38
  Speaker 2: exact structures underneath this fucking immense 2,300,000 stone structure that
• 32:46
  Speaker 2: almost perfectly aligns to true north, south, east, and west.
• 32:49
  Speaker 2: Like what was going on? Don't tell me pulleys. Don't
• 32:53
  Speaker 2: tell me copper tools. Like what the fuck was going on?
• 32:56
  Speaker 2: Something crazy. And I have a feeling our simplistic explanation
• 33:01
  Speaker 2: of it is just doing no one any justice. It's
• 33:04
  Speaker 2: doing no service to history. It's doing no service to
• 33:07
  Speaker 2: our understanding. They've got to be a little bit more
• 33:09
  Speaker 2: open in the fact that they are perplexed and not
• 33:12
  Speaker 2: just perplexed by stuff like this. This is a 3D
• 33:15
  Speaker 2: print of an actual vase that exists in Egypt that
• 33:20
  Speaker 2: they found that is– they found it in tombs of
• 33:23
  Speaker 2: the old kingdom. This thing was somehow or another– it's
• 33:27
  Speaker 2: made with diorite. So it's incredibly hard stone and made
• 33:31
  Speaker 2: to like a thousandth of a human hair in its– yeah,
• 33:35
  Speaker 2: like crazy dimensions. Wow. Like the way the precision of it.
• 33:41
  Speaker 2: And it wasn't turned on a lathe because it has handles.
• 33:44
  Speaker 3: Yeah.
• 33:44
  Speaker 2: So you look at the handles on the side. Well,
• 33:46
  Speaker 2: you can't carve those. And those are perfect too. Like
• 33:48
  Speaker 2: the alignment of everything. And it's like you just look
• 33:51
  Speaker 2: at it. Oh, it's a vase. No big deal. But no,
• 33:53
  Speaker 2: it's kind of fucking crazy. Like how did they cut
• 33:56
  Speaker 2: that out? There's also these. There's all these core marks
• 34:02
  Speaker 2: in some of the stones that they find in Egypt.
• 34:04
  Speaker 2: And they've. analyze the amount of revolutions per minute that
• 34:08
  Speaker 2: you would have to go through to be able to
• 34:09
  Speaker 2: cut through something and leave these lines. And it defies explanation. Like,
• 34:14
  Speaker 2: what is this? This is great. This is not sand
• 34:18
  Speaker 2: and copper and just rubbing things. No, this is some
• 34:21
  Speaker 2: insane technology that we don't understand. There's scoop marks out
• 34:26
  Speaker 2: of the bottoms of some of these stones. It's like,
• 34:28
  Speaker 2: what the fuck is this? How'd you scoop rock? Like,
• 34:32
  Speaker 2: it looks like ice cream. Like, they just went, whoop.
• 34:36
  Speaker 2: What are they doing? There's so many questions.
• 34:39
  Speaker 1: What tools did they even have to do all these things?
• 34:41
  Speaker 2: They had copper. I mean, there's some evidence that they
• 34:44
  Speaker 2: had some iron. And then I think Tutankhamen had a
• 34:48
  Speaker 2: dagger that was actually made from meteorite, which is interesting.
• 34:52
  Speaker 2: When they could find meteorites and make things out of them,
• 34:55
  Speaker 2: it was very valuable, obviously. But just the sheer volume
• 35:01
  Speaker 2: of work that they did there, It's like you look
• 35:05
  Speaker 2: at the Temple in Man, you look at the three
• 35:08
  Speaker 2: major pyramids, you look at all the different temples and
• 35:12
  Speaker 2: all the construction. And the older you go, the deeper
• 35:14
  Speaker 2: into the sand they go, the more complex these things are,
• 35:17
  Speaker 2: which is even weirder. So it seems like civilization after civilization,
• 35:21
  Speaker 2: there was probably a rise and fall with their technology
• 35:25
  Speaker 2: as well.
• 35:26
  Speaker 1: Absolutely. I think it's just incredible that none of this
• 35:29
  Speaker 1: knowledge was properly documented ever. And it's a whole line
• 35:34
  Speaker 1: of work to just go understand how to even rebuild
• 35:37
  Speaker 1: these things, leave alone how did they build it.
• 35:40
  Speaker 2: Well, think about what we're doing, right? So all of
• 35:43
  Speaker 2: our knowledge is essentially stored on hard drives and paper.
• 35:46
  Speaker 2: Those are the two things that are going to deteriorate
• 35:48
  Speaker 2: the quickest.
• 35:51
  Speaker 1: Maybe we should take a dump of the internet and
• 35:54
  Speaker 1: put it on a rock. Go preserve it somewhere so
• 35:57
  Speaker 1: that even if our civilization is wiped out and all
• 36:00
  Speaker 1: the data centers are gone or whatever.
• 36:02
  Speaker 2: Right.
• 36:03
  Speaker 1: Whoever comes next can go figure it out.
• 36:06
  Speaker 2: Well, I mean, then you've got to always assume that
• 36:09
  Speaker 2: even if they found a hard drive, that they would, like,
• 36:12
  Speaker 2: how long would it take for them to back engineer
• 36:15
  Speaker 2: what we did and figure out what these ones and
• 36:17
  Speaker 2: zeros actually mean?
• 36:19
  Speaker 1: Yeah.
• 36:21
  Speaker 2: Which is one of the most bizarre and fantastic accomplishments
• 36:25
  Speaker 2: of modern civilization is that, like, this is a terabyte. Yeah.
• 36:30
  Speaker 2: Which is nuts.
• 36:31
  Speaker 3: Yeah.
• 36:32
  Speaker 2: Like, I don't know what your first computer had.
• 36:34
  Speaker 1: I don't remember. Definitely not even a gigabyte probably.
• 36:38
  Speaker 2: No.
• 36:39
  Speaker 3: Yeah.
• 36:39
  Speaker 2: Like a few hundred megabytes was your hard drive. Yeah. Yeah.
• 36:43
  Speaker 2: I mean, I remember when they first came out with gigabytes,
• 36:46
  Speaker 2: I was like, this is nuts.
• 36:47
  Speaker 3: Yeah.
• 36:48
  Speaker 1: You remember like when Gmail launched and gave everybody like
• 36:50
  Speaker 1: free email storage, unlimited email storage, and the bottom sliding
• 36:55
  Speaker 1: bar would just keep increasing in terms of the total
• 36:57
  Speaker 1: allowed size?
• 36:58
  Speaker 2: Yeah.
• 36:58
  Speaker 1: And that was nuts to me.
• 37:00
  Speaker 2: Yeah.
• 37:00
  Speaker 3: Yeah.
• 37:01
  Speaker 1: And I think, yeah, we take it for granted that
• 37:04
  Speaker 1: we have like infinite RAM and infinite hard disk and
• 37:07
  Speaker 1: nobody has to worry about like, you know, back in
• 37:09
  Speaker 1: those days, you worry about like taking too many photos
• 37:12
  Speaker 1: on your phone.
• 37:12
  Speaker 2: Right.
• 37:13
  Speaker 3: Right.
• 37:13
  Speaker 1: And then you have to go delete all the old
• 37:15
  Speaker 1: ones or bad ones.
• 37:16
  Speaker 2: Yeah. You'd run out of storage on your phone.
• 37:18
  Speaker 3: Yeah.
• 37:18
  Speaker 1: And then you have to buy like an external hard
• 37:21
  Speaker 1: drive to keep storing things.
• 37:22
  Speaker 2: Yeah.
• 37:22
  Speaker 1: You keep transferring stuff from your phone to the hard disk.
• 37:25
  Speaker 2: I remember the old Android phones, you'd get an SD card.
• 37:28
  Speaker 3: Yeah.
• 37:28
  Speaker 2: You could slip one of those in there and you
• 37:30
  Speaker 2: could store images on that.
• 37:32
  Speaker 3: Yeah.
• 37:32
  Speaker 2: So you could save space. Yeah. And all that stuff
• 37:36
  Speaker 2: is so vulnerable. It's so vulnerable. And again, if a
• 37:40
  Speaker 2: completely alien society had to come down and find our
• 37:44
  Speaker 2: hard drives and they went a totally different path of technology,
• 37:49
  Speaker 2: they'd have to back engineer, reverse engineer everything that we did,
• 37:52
  Speaker 2: try to figure out. What are we using? What operating system?
• 37:56
  Speaker 2: How does the operating system work? Is it Unix? Is
• 37:59
  Speaker 2: it Linux? What is it? How do they do it?
• 38:02
  Speaker 2: It would be a nightmare.
• 38:03
  Speaker 1: They would need an advanced AI to figure it all
• 38:06
  Speaker 1: out for them.
• 38:06
  Speaker 2: Right.
• 38:07
  Speaker 3: Yeah.
• 38:07
  Speaker 2: Yeah. And so that's just if the hard drives survive, right?
• 38:12
  Speaker 2: So if there's some massive flood, cataclysm, whatever. Some horrific
• 38:17
  Speaker 2: thing that damages all of our electronics, which is totally possible.
• 38:21
  Speaker 2: You know, just some solar flare, some intense, you know.
• 38:25
  Speaker 1: Or just another lab leak.
• 38:28
  Speaker 2: Right?
• 38:28
  Speaker 3: Yeah.
• 38:28
  Speaker 2: Yeah. Just time. A lab leak in time. Yeah.
• 38:32
  Speaker 3: Yeah.
• 38:33
  Speaker 2: It's nuts. And we could go back to zero real quick.
• 38:38
  Speaker 2: And we would basically be like preppers and hunter-gatherers.
• 38:40
  Speaker 1: It would be hard to reverse engineer everything again.
• 38:42
  Speaker 2: It would be almost impossible.
• 38:43
  Speaker 1: Yeah.
• 38:44
  Speaker 2: Which is why I'm really fascinated by the flood, the
• 38:47
  Speaker 2: post-flood timeline. Because if these people like Graham Hancock and
• 38:52
  Speaker 2: a lot of these other folks that have speculated that
• 38:55
  Speaker 2: there was probably a very advanced civilization that went in
• 38:57
  Speaker 2: a completely different direction many thousands of years ago. If
• 39:01
  Speaker 2: you look at, like, the emergence of, like, Sumer and Byzantium.
• 39:06
  Speaker 2: You know, Mesopotamia and that area, which a lot of
• 39:08
  Speaker 2: people attribute to be the earliest known civilization, that's around 5,000 plus, 6,000
• 39:15
  Speaker 2: years ago, right? Yeah, roughly. So the flood's like 11,000
• 39:19
  Speaker 2: years ago plus. So you're looking at like 5,000 years
• 39:24
  Speaker 2: of what?
• 39:25
  Speaker 1: It's not even that long in the grand scheme of things.
• 39:27
  Speaker 2: No, not to the earth, but for people.
• 39:29
  Speaker 3: Yeah.
• 39:30
  Speaker 2: Pretty fucking long. Think of how long it took us
• 39:32
  Speaker 2: to get our shit together. It took thousands and thousands
• 39:35
  Speaker 2: and thousands of years of people probably being monsters, just
• 39:39
  Speaker 2: being the worst of the worst. And that's probably the
• 39:43
  Speaker 2: only way they survived. There's probably a lot of cannibalism.
• 39:45
  Speaker 2: There's a lot of murder. There was a lot of
• 39:48
  Speaker 2: horrific shit going on for 5,000 years until people slowly
• 39:52
  Speaker 2: but surely figured out agriculture again. Started building walls. Everybody
• 39:56
  Speaker 2: relaxed a little. Got some solid weapons to keep people
• 40:00
  Speaker 2: away so you could work on math. And then next
• 40:02
  Speaker 2: thing you know, civilization emerges again. And it goes right
• 40:06
  Speaker 2: back onto the cycle. And then you start reading in
• 40:09
  Speaker 2: the Rig Veda about stuff that happened thousands of years.
• 40:12
  Speaker 2: What the fuck is this? What happened? And that's my... belief.
• 40:18
  Speaker 2: I think there was something going on on earth many, many,
• 40:22
  Speaker 2: many thousands of years before established beginnings of history that
• 40:27
  Speaker 2: was very bizarre and probably technology that went in a
• 40:30
  Speaker 2: completely different direction than what we're doing now with combustion
• 40:35
  Speaker 2: engines and circuits and all the different things that we use.
• 40:38
  Speaker 2: They probably figured out some other kind of technology.
• 40:41
  Speaker 1: Exactly.
• 40:42
  Speaker 2: Which is totally possible.
• 40:43
  Speaker 1: And it's amazing. It's amazing to think of what if
• 40:46
  Speaker 1: we could rediscover all of that again yes.
• 40:49
  Speaker 2: Well I would love to be able to I would
• 40:52
  Speaker 2: love to just have a if I could choose one
• 40:55
  Speaker 2: window in time to go back to see what it
• 40:57
  Speaker 2: would look like I would 100% pick ancient Egypt while
• 41:01
  Speaker 2: they're building the pyramids show me what the fuck was
• 41:05
  Speaker 2: going on yeah there's just just put me in a
• 41:08
  Speaker 2: big hamster wheel there's a big plastic bubble where no
• 41:11
  Speaker 2: one could see me just let me violate space and
• 41:14
  Speaker 2: time and exist there for just a few minutes just
• 41:16
  Speaker 2: let me look I think that would be the most
• 41:19
  Speaker 2: insane thing that you could see about humans and human history.
• 41:23
  Speaker 3: Yeah.
• 41:23
  Speaker 2: I just want to know what they knew, what they had,
• 41:26
  Speaker 2: what they used.
• 41:27
  Speaker 3: Just looking at this thing, Petra is the same time period,
• 41:30
  Speaker 3: at least attributed to. 7,000 roughly BC.
• 41:34
  Speaker 2: Jesus.
• 41:35
  Speaker 3: And they, you know, how would you know that?
• 41:38
  Speaker 2: Right.
• 41:38
  Speaker 3: How?
• 41:39
  Speaker 1: The details of all those carvings is insane.
• 41:42
  Speaker 2: Insane.
• 41:43
  Speaker 3: Yeah.
• 41:43
  Speaker 2: In 7,000 BC, what are the tools? What the hell
• 41:48
  Speaker 2: were you using? How did you make a temple out
• 41:51
  Speaker 2: of the side of a fucking mountain? Look at the
• 41:54
  Speaker 2: size of it, man. The size of those columns.
• 41:58
  Speaker 1: It would be hard to do anything like this even today.
• 42:01
  Speaker 2: It would be incredibly difficult, insanely time-consuming.
• 42:06
  Speaker 3: Yeah, the Kaliasa Temple, by the way, I don't have
• 42:09
  Speaker 3: it up right now, but in 1650 or so, someone
• 42:13
  Speaker 3: sent 1,000 people to try to destroy it, and after
• 42:15
  Speaker 3: three years of doing nothing, they stopped. They barely made
• 42:18
  Speaker 3: a dent on a couple statues.
• 42:20
  Speaker 1: Yeah, a lot of times when invasions happen in India, like.
• 42:23
  Speaker 2: They tried really hard to fuck it up and couldn't.
• 42:26
  Speaker 2: That's crazy.
• 42:28
  Speaker 1: That's very robust.
• 42:33
  Speaker 2: That's a great way to describe it. It's just, there's
• 42:37
  Speaker 2: so much of that stuff that's so interesting because it's
• 42:41
  Speaker 2: so undeniable. It's so undeniable in its scale. so undeniable
• 42:47
  Speaker 2: in its complexity and the planning and the understanding that
• 42:52
  Speaker 2: you had to have a deep knowledge of geometry, of measurement.
• 42:57
  Speaker 1: You had to have accurate.
• 42:58
  Speaker 2: Materials. Yes.
• 42:59
  Speaker 3: Yeah.
• 42:59
  Speaker 2: Everything.
• 43:00
  Speaker 1: Sturdiness, like resist like calamities, like earthquakes, floods. And then
• 43:04
  Speaker 1: even if you had.
• 43:05
  Speaker 2: That, what tools are you using? Yeah. Like how are
• 43:09
  Speaker 2: you doing this?
• 43:09
  Speaker 1: How are you coordinating all these people?
• 43:12
  Speaker 2: Right.
• 43:12
  Speaker 1: Getting them to do stuff and. I mean, sure, conditions
• 43:15
  Speaker 1: must have been way harsher. I'm sure people didn't really
• 43:18
  Speaker 1: have a choice but to do these things because back
• 43:20
  Speaker 1: in those days, the only way you could take care
• 43:23
  Speaker 1: of your food and clothing and shelter is you commit
• 43:26
  Speaker 1: yourself as a laborer to the state, to the kingdom.
• 43:31
  Speaker 1: But you could also ask what gave them the initiative
• 43:35
  Speaker 1: or drive to go do these things.
• 43:37
  Speaker 2: Yeah. Well, that description is perhaps of a later time.
• 43:40
  Speaker 2: We don't even really know what civilization was like when
• 43:43
  Speaker 2: these were constructed. The real problem is the material science.
• 43:49
  Speaker 2: The real problem is, like, there's a lot of things
• 43:52
  Speaker 2: that you have to have to make those things. It's
• 43:54
  Speaker 2: not as simple as a sculpture, like Michelangelo making a
• 43:58
  Speaker 2: sculpture out of something that's, like, fairly easy to carve
• 44:01
  Speaker 2: into as far as stone goes. No, this is, the
• 44:05
  Speaker 2: scale is, it's so undeniable that, like, something, some piece
• 44:11
  Speaker 2: of our understanding is missing.
• 44:13
  Speaker 3: Yeah. Yeah.
• 44:15
  Speaker 1: I mean, it, it, it, like looking at all this,
• 44:17
  Speaker 1: like everyone should just be like a lot more humble, right? Like,
• 44:21
  Speaker 1: like we don't actually know that much. Like what we
• 44:23
  Speaker 1: know is like so little, like whatever, like the same
• 44:26
  Speaker 1: thing as what Socrates said, what we know is very,
• 44:29
  Speaker 1: very little. And the only thing we, we should all
• 44:33
  Speaker 1: strive to be is just be curious. And, um, I
• 44:36
  Speaker 1: think there's a lot of tendency for people to like,
• 44:38
  Speaker 1: think like, Oh, like we have all this advanced technology.
• 44:40
  Speaker 1: We're so amazing. Like, look at us. And it's like, wait,
• 44:43
  Speaker 1: hold on. Like, You don't even understand what happened thousands
• 44:46
  Speaker 1: of years ago. And there's so much out there to
• 44:49
  Speaker 1: just go and explore and learn and get better at
• 44:52
  Speaker 1: understanding more.
• 44:54
  Speaker 2: What is this place?
• 44:55
  Speaker 1: Yeah, this is unreal.
• 44:58
  Speaker 2: This is called the Ellora Caves. Timeless wonder carved in stone.
• 45:02
  Speaker 3: I think it's all kind of the same area.
• 45:04
  Speaker 1: Yeah, it's the same Ellora Cave and the Shiva Temple
• 45:07
  Speaker 1: that you saw.
• 45:08
  Speaker 2: Look at that. My God. Look at this stuff. It's insane.
• 45:15
  Speaker 2: And again, there's no steel back then.
• 45:18
  Speaker 1: It's actually really symmetrical. It's not even like.
• 45:23
  Speaker 1: Can you go back to the first one with the
• 45:25
  Speaker 1: symmetrical top? Look at the symmetry of the top.
• 45:30
  Speaker 2: That's nuts. It looks like that mall in.
• 45:33
  Speaker 3: New York they made where the world trades.
• 45:37
  Speaker 2: Yeah, but way more robust. I mean, how? What were
• 45:44
  Speaker 2: you– this is the thing. It's like the material science
• 45:47
  Speaker 2: aspect of it. Yeah. It's like you don't have the
• 45:51
  Speaker 2: ability to do– look at that top one. Go to
• 45:53
  Speaker 2: that top one again. The one that you just had, Jamie? Yeah,
• 45:56
  Speaker 2: that one. Look at– that's crazy, man. I mean I
• 46:01
  Speaker 2: am just blown away when I see stuff like that.
• 46:04
  Speaker 2: My mind just starts racing and I just think how
• 46:08
  Speaker 2: did you do this? Who– Who was involved? How was
• 46:11
  Speaker 2: it planned? How is it so symmetrical? What were the tools? Like,
• 46:16
  Speaker 2: what were the tools, man? If you don't have steel,
• 46:20
  Speaker 2: you don't have... What are you using? How'd you do that?
• 46:23
  Speaker 1: I mean, most of it is done with stone, clearly, right?
• 46:26
  Speaker 2: I guess. I guess. I doubt it. I bet they
• 46:30
  Speaker 2: had something else. I bet they had something else that,
• 46:34
  Speaker 2: over time, eroded just like metal would today. I mean,
• 46:37
  Speaker 2: if you left a shovel outside... today, and you came
• 46:42
  Speaker 2: back to that same spot 500 years from now, there's nothing.
• 46:45
  Speaker 2: That shovel's gone, right? Yeah. And you've got to assume
• 46:48
  Speaker 2: that these many thousand year old temples that were carved
• 46:52
  Speaker 2: out of a fucking mountain, whatever tools they used probably
• 46:57
  Speaker 2: got absorbed by the earth. And the only thing that's remaining.
• 46:59
  Speaker 3: Yeah.
• 46:59
  Speaker 2: Yeah. It's giving me a weird thought.
• 47:00
  Speaker 3: Like when they make a big building downtown though, they
• 47:02
  Speaker 3: only bring the crane in for a temporary period of time.
• 47:05
  Speaker 3: And there's only so many cranes on the planet currently too. So.
• 47:08
  Speaker 2: Right. True.
• 47:09
  Speaker 3: You take it, you move it, you go take it
• 47:11
  Speaker 3: to the next spot.
• 47:12
  Speaker 2: Yep. Yeah, true. Yeah, I don't know. Yeah, especially something
• 47:15
  Speaker 2: like this. Like, if they had heavy equipment and machinery
• 47:18
  Speaker 2: and whatever the fuck they were using, they probably moved
• 47:21
  Speaker 2: it and then moved it out and then it probably
• 47:23
  Speaker 2: rotted away and now it's gone. If there was machinery.
• 47:27
  Speaker 2: If there wasn't, like, there must have been something else.
• 47:29
  Speaker 2: Some other kind of, like, some technology that we haven't
• 47:33
  Speaker 2: even imagined.
• 47:34
  Speaker 3: Yeah.
• 47:37
  Speaker 2: But it's like they're... their commitment to art too was
• 47:42
  Speaker 2: so fascinating because these aren't just structures.
• 47:45
  Speaker 1: They're in fashion projects.
• 47:46
  Speaker 3: Yeah.
• 47:46
  Speaker 2: Intensely beautiful.
• 47:48
  Speaker 1: Yeah.
• 47:48
  Speaker 2: Intensely ornate.
• 47:49
  Speaker 3: Yeah.
• 47:50
  Speaker 2: So it's not, it's not just that they wanted to
• 47:52
  Speaker 2: build like a functional structure. Yeah. That good architecture. No,
• 47:57
  Speaker 2: it's this, it's a fascinating artwork and it's so intricate.
• 48:02
  Speaker 2: There's so many different features and so many different images of,
• 48:06
  Speaker 2: of different people and beings and animals and, elephants and.
• 48:11
  Speaker 1: There's one more temple you could pull out. It's called
• 48:14
  Speaker 1: the Tanjore Temple.
• 48:15
  Speaker 2: Oh, I've seen that one too. Yeah.
• 48:17
  Speaker 1: That was done more recently in the age of the Cholas.
• 48:21
  Speaker 1: It's pretty incredible.
• 48:22
  Speaker 2: When did they do that one?
• 48:25
  Speaker 1: I don't know the exact number, but more recent than
• 48:28
  Speaker 1: the ones that you saw.
• 48:29
  Speaker 2: All of them are nuts, man. And then there's stuff
• 48:31
  Speaker 2: like that all over the world.
• 48:33
  Speaker 1: Whoa! This was done as a project by the king
• 48:37
  Speaker 1: to To basically make a name for himself.
• 48:41
  Speaker 2: Wow. That's incredible. Is that multiple pieces of stone or
• 48:47
  Speaker 2: did he carve that whole thing out of stone too?
• 48:50
  Speaker 1: Probably multiple pieces.
• 48:52
  Speaker 2: So that's actually like construction.
• 48:55
  Speaker 3: Yeah.
• 48:55
  Speaker 2: Not like removal. The other ones are, it's essentially a
• 49:01
  Speaker 2: giant sculpture. Wow. It's so pretty. Look how geometric it
• 49:07
  Speaker 2: is too.
• 49:07
  Speaker 1: That's what amazes me. Like, they didn't actually have all
• 49:10
  Speaker 1: these simulations and CAD tools and all these things.
• 49:13
  Speaker 2: Right.
• 49:14
  Speaker 1: And... What year.
• 49:15
  Speaker 2: Was this made, Jamie? Does it say? It's just so
• 49:20
  Speaker 2: incredible how much of this stuff exists where it's really baffling.
• 49:24
  Speaker 2: Like I just found out recently that the Aztecs didn't
• 49:28
  Speaker 2: build those temples, that they found them. Really? Yeah. They
• 49:32
  Speaker 2: found like the Tenochtitlan, they call it the place where
• 49:36
  Speaker 2: the gods were born. The Aztecs found it. And uncovered it.
• 49:40
  Speaker 2: And then on the, when, is it Tenochtitlan or Teotihuacan,
• 49:47
  Speaker 2: whichever one it was, on the consecration day, when they
• 49:51
  Speaker 2: were done with like whatever they were doing with it,
• 49:53
  Speaker 2: to celebrate, they killed somewhere between 20,000 and 80,000 people
• 49:59
  Speaker 2: in four days. Damn. Not exactly the mindset of the
• 50:04
  Speaker 2: type of people that would construct something like that. You know,
• 50:06
  Speaker 2: so those are the people that, found it, and it
• 50:09
  Speaker 2: might have been sitting there for a thousand years. And
• 50:11
  Speaker 2: then they came along and said, oh, this is cool.
• 50:14
  Speaker 2: Let's live here. Okay, but what was the society that
• 50:18
  Speaker 2: lived there before them? And where are they? And what happened?
• 50:21
  Speaker 2: And how'd they do this? And why'd they do it?
• 50:23
  Speaker 2: And why did they have it aligned with the constellations? Like,
• 50:26
  Speaker 2: what were they doing?
• 50:27
  Speaker 1: Yeah. Some of the calculations are pretty amazing, like how
• 50:33
  Speaker 1: they timed it, how they positioned it. how they cared
• 50:37
  Speaker 1: about planetary positions and stuff like that. Sure, like, some
• 50:40
  Speaker 1: of it could even be pseudoscience, but whatever. I think
• 50:43
  Speaker 1: just the level of, like, calculations they were making back
• 50:46
  Speaker 1: in those days without, you know, powerful computers is just outstanding.
• 50:51
  Speaker 2: It's just nuts, and it doesn't make sense. It's like, okay,
• 50:54
  Speaker 2: they're making it without powerful computers, so what are they using?
• 50:58
  Speaker 1: I mean, at one point, the word computer just meant
• 51:01
  Speaker 1: a human.
• 51:02
  Speaker 2: Right.
• 51:02
  Speaker 1: Like, human beings would be doing the calculations. That was
• 51:05
  Speaker 1: their only job. Like, to literally, like, multiply two numbers. Or, like,
• 51:09
  Speaker 1: to make some... Astronomers were actually the first mathematicians. The
• 51:14
  Speaker 1: term mathematician and astronomer were used synonymously at one point.
• 51:17
  Speaker 2: Really?
• 51:18
  Speaker 1: Yeah.
• 51:20
  Speaker 2: Why is that? Why studying the stars and math?
• 51:24
  Speaker 1: Yeah, because, like, studying the stars involved making a lot
• 51:27
  Speaker 1: of geometry calculations. And that was kind of actually one
• 51:32
  Speaker 1: of the first set of mathematicians in India. People like Aryabhatta, Bhaskara,
• 51:37
  Speaker 1: all these guys were actually astronomers too. They were not
• 51:40
  Speaker 1: just mathematicians. And Aryabhatta was earlier still like the idea
• 51:46
  Speaker 1: of using zeros. And then he had a lot of
• 51:49
  Speaker 1: like contributions in geometry. And he was doing all this
• 51:53
  Speaker 1: like just because he was interested in astronomy.
• 51:57
  Speaker 2: Isn't there evidence of Pythagorean theorem in ancient, is it
• 52:04
  Speaker 2: ancient Sumerian?
• 52:07
  Speaker 3: Is it?
• 52:08
  Speaker 2: It's something that predates Pythagoras.
• 52:13
  Speaker 1: Interesting. My theory is that even though it was not
• 52:16
  Speaker 1: formulated as a Pythagorean theorem, I'm sure people had to
• 52:19
  Speaker 1: understand concepts of sines and cosines and whatever is the
• 52:24
  Speaker 1: right angle for the right incline to get this right
• 52:27
  Speaker 1: level of geometry. You needed to have some implicit understanding
• 52:31
  Speaker 1: of it to build these kind of structures. There's no
• 52:34
  Speaker 1: way you could do it without that.
• 52:35
  Speaker 3: Yeah, 100%.
• 52:35
  Speaker 2: And you have to have incredible measurement tools, like not
• 52:39
  Speaker 2: just the actual mathematics. Okay, the oldest known evidence of
• 52:43
  Speaker 2: Pythagorean theorem dates from old Babylonian clay tablets from about
• 52:47
  Speaker 2: 1900 to 1600 BCE, roughly 1,000 years before Pythagoras. Isn't
• 52:53
  Speaker 2: that wild? Like, how?
• 52:55
  Speaker 3: How?
• 52:57
  Speaker 1: How?
• 52:58
  Speaker 2: Clay Tabots often cited, used what we now call the
• 53:01
  Speaker 2: Pythagorean theorem to compute the diagonal of rectangles and squares,
• 53:09
  Speaker 2: including an excellent approximation. Look at this. This is nuts, man.
• 53:15
  Speaker 2: Vedic ritual text explicitly states the rule equivalent. I don't
• 53:19
  Speaker 2: know how to say that. What is that? A squared,
• 53:21
  Speaker 2: B squared, C squared. But the diagonal of a rectangle
• 53:24
  Speaker 2: that includes numerical examples predating or roughly contemporary. With classical
• 53:29
  Speaker 2: Greek mathematics. So completely different parts of the world. Yeah.
• 53:33
  Speaker 2: And they're coming up with the same stuff.
• 53:35
  Speaker 1: Exactly. Because they're all curious. That's it.
• 53:38
  Speaker 2: Yeah. They're all curious and eventually all curiosity leads to
• 53:42
  Speaker 2: truth or some form of it.
• 53:44
  Speaker 1: I would argue that anything that's of impact in the
• 53:46
  Speaker 1: world has only been done by curious people. In hindsight,
• 53:50
  Speaker 1: we label those people as successful or smart or rich.
• 53:54
  Speaker 1: But the common trait across all of them has been
• 53:56
  Speaker 1: like curious people.
• 53:59
  Speaker 2: Well, that's certainly a powerful trait. And people that aren't
• 54:03
  Speaker 2: curious are not fun.
• 54:05
  Speaker 1: Yeah, they're not interesting. So because of that, they don't
• 54:08
  Speaker 1: attract other smarter, interesting people. And therefore, they won't be
• 54:12
  Speaker 1: able to do something very meaningful in the world. So
• 54:16
  Speaker 1: it's kind of like, it's less about, and it applies
• 54:21
  Speaker 1: to your personal relationships and personal life too. It's not
• 54:24
  Speaker 1: just about professional success. Like, you'll have a more fulfilling
• 54:28
  Speaker 1: life with your wife or your kids if you're a
• 54:30
  Speaker 1: more curious person. You ask them more questions. You take
• 54:33
  Speaker 1: interest in them, right? So that's the one quality everybody
• 54:37
  Speaker 1: wants in personal relationships is, like, taking interest in them and, like,
• 54:41
  Speaker 1: actually understanding them better or, like, being curious about common things.
• 54:45
  Speaker 1: And so it's not just that, you know, being curious
• 54:48
  Speaker 1: leads to success. It's more that people around you want
• 54:50
  Speaker 1: you to be successful if you're curious because... you will
• 54:55
  Speaker 1: have more compounding and fulfilling relationships.
• 54:58
  Speaker 2: I would agree with that. Yeah. I'd say it's one
• 55:01
  Speaker 2: of the more important qualities of human beings. I mean,
• 55:04
  Speaker 2: it's led to everything that we have today. All curiosity
• 55:07
  Speaker 2: has led to all of our architecture, math, everything, art, everything.
• 55:11
  Speaker 1: The transistor. Like, you know the story of the transistor?
• 55:14
  Speaker 2: Yeah.
• 55:15
  Speaker 1: So Bell Labs was basically employing as many, like history adjusted,
• 55:20
  Speaker 1: as many telephone engineers back then as the number of
• 55:22
  Speaker 1: software engineers today. But only three people cared enough to
• 55:26
  Speaker 1: question whether you should use these really hot giant vacuum
• 55:30
  Speaker 1: tubes for amplifying telephone signals. So vacuum tubes are very big,
• 55:34
  Speaker 1: power hungry and very hot. And so they were not
• 55:38
  Speaker 1: fault tolerant and it's very expensive. And so three people
• 55:42
  Speaker 1: questioned the need for that and came up with the
• 55:43
  Speaker 1: idea of the transistor to amplify current. And that was
• 55:49
  Speaker 1: the Nobel Prize winning discovery. And not just that it
• 55:52
  Speaker 1: was useful to amplify telephone signals, It basically led to
• 55:55
  Speaker 1: the rise of modern computing and we wouldn't have an
• 55:58
  Speaker 1: iPhone like this today if not for those three people.
• 56:01
  Speaker 2: Do you know what the tinfoil hat conspiracy theory about
• 56:03
  Speaker 2: transistors is?
• 56:04
  Speaker 3: No.
• 56:05
  Speaker 2: That they are back-engineered from the Roswell crash along with
• 56:10
  Speaker 2: fiber optics.
• 56:12
  Speaker 1: Tell me more.
• 56:13
  Speaker 2: So we read this on the podcast. Remember, Jamie, there's
• 56:16
  Speaker 2: the two scientists that were attributed. There's this one scientist
• 56:19
  Speaker 2: that said they weren't even remotely exceptional guys and that
• 56:22
  Speaker 2: they gave them the credit for this so that they
• 56:25
  Speaker 2: didn't have to reveal the true nature of where this
• 56:28
  Speaker 2: technology came from.
• 56:30
  Speaker 1: I see. Interesting.
• 56:31
  Speaker 2: So, again, tinfoil hat securely on our heads. This is
• 56:36
  Speaker 2: not something I believe. This is just something that's fun.
• 56:40
  Speaker 2: There's a few inventions that came out of that time period,
• 56:45
  Speaker 2: roughly after 1947, that are weird. And one of them
• 56:49
  Speaker 2: is fiber optics and one of them is a transistor.
• 56:51
  Speaker 2: And these are supposedly... Attributed to back engineering programs. So
• 56:56
  Speaker 2: the Roswell crash, I don't know if you ever paid
• 56:58
  Speaker 2: any attention to it. It's a real weird one because
• 57:01
  Speaker 2: the cover of the Roswell Daily Record said that the
• 57:04
  Speaker 2: government has a crash disc that landed in the desert.
• 57:07
  Speaker 2: A bunch of witnesses, a bunch of people saw it.
• 57:11
  Speaker 2: It's also people that saw, supposedly saw physical bodies of
• 57:15
  Speaker 2: these creatures and supposedly, again, who knows what's true. But
• 57:23
  Speaker 2: Truman went to the site. He visited it. And then
• 57:27
  Speaker 2: the planes, two separate planes, were flown to Wright-Patterson Air
• 57:31
  Speaker 2: Force Base, which I think was just Wright Base back then.
• 57:34
  Speaker 2: I don't think it was Wright-Patterson. But they flew them out.
• 57:38
  Speaker 2: And the idea was this material was so important, they
• 57:43
  Speaker 2: didn't want to risk one plane crashing. So they flew
• 57:45
  Speaker 2: it in two different planes. And that this stuff has
• 57:48
  Speaker 2: always been known to be stored at Wright-Patterson Air Force Base.
• 57:52
  Speaker 2: That's what everybody always talks about. And then a lot
• 57:55
  Speaker 2: of it was moved to Bell Labs. And there was
• 57:59
  Speaker 2: a company called the American Computer Company. And back in
• 58:03
  Speaker 2: the day, the American Computer Company was just like– it
• 58:06
  Speaker 2: was a consumer website where you could go and say, oh,
• 58:09
  Speaker 2: I need a Windows computer that does this, that, and
• 58:11
  Speaker 2: the other thing. And you could just put in whatever
• 58:13
  Speaker 2: your specs were and they would build it for you.
• 58:15
  Speaker 2: They all had a whole section. of their website dedicated
• 58:19
  Speaker 2: to Bell Labs and back-engineered UFO technology. And all they
• 58:24
  Speaker 2: talked about in this one, like whoever ran it was
• 58:26
  Speaker 2: like a fucking kook. Is that still around?
• 58:28
  Speaker 1: That website?
• 58:29
  Speaker 2: Yeah. American Computer Company, is it still around?
• 58:32
  Speaker 1: Interesting.
• 58:32
  Speaker 2: So this is like the 1990s, I think.
• 58:34
  Speaker 1: You're saying your theory, I mean, not that you believe
• 58:37
  Speaker 1: in it, but your theory is that the transistor was
• 58:41
  Speaker 1: not invented, it was known, and it was given to
• 58:43
  Speaker 1: the Bell Labs.
• 58:43
  Speaker 2: This is apparently a giant leap. Between the first ideas
• 58:47
  Speaker 2: of the transistor and then what actually came about and
• 58:50
  Speaker 2: how much money had to be spent to create it
• 58:53
  Speaker 2: off of this leap. This was this assertion by these
• 58:58
  Speaker 2: scientists that were trying to examine this. The thing about
• 59:00
  Speaker 2: Bell Labs is there's a military base right outside of
• 59:05
  Speaker 2: Bell Labs. And they say, well, that military base is
• 59:07
  Speaker 2: to guard New York City. But New York City is
• 59:09
  Speaker 2: quite a flight. away. But Bell Labs is right there.
• 59:13
  Speaker 2: And they're working on some deep, dark shit at Bell
• 59:16
  Speaker 2: Labs for sure. Because I've had a bunch of people
• 59:19
  Speaker 2: on that were talking about remote viewing exercises that they
• 59:22
  Speaker 2: were doing out of Bell Labs. You know, we've had
• 59:25
  Speaker 2: a bunch of people that came on and talked about
• 59:28
  Speaker 2: various programs that were going on that were like top
• 59:30
  Speaker 2: secret programs that were happening that were being run through
• 59:33
  Speaker 2: Bell Labs. There's some weirdness to that place, like real weirdness.
• 59:37
  Speaker 1: Yeah.
• 59:38
  Speaker 2: And it's fun. Yeah. The idea that like, you know, that.
• 59:42
  Speaker 1: Because it definitely feels very disconnected. Like, OK, like you
• 59:46
  Speaker 1: were using all these vacuum tubes and then suddenly you're like, OK,
• 59:51
  Speaker 1: like what if we just use semiconductors? Okay, there's definitely
• 59:57
  Speaker 1: a pretty far drift from what you're doing currently to
• 1:00:00
  Speaker 1: what you're supposed to do. And also the idea of
• 1:00:05
  Speaker 1: the first transistor and what ended up being used in chips,
• 1:00:09
  Speaker 1: the junction transistor are quite different too. So they're like
• 1:00:12
  Speaker 1: big leaps in terms of what the core idea was.
• 1:00:15
  Speaker 1: It's not an incremental change. The way I thought about
• 1:00:19
  Speaker 1: it was like, okay, that's like tens of years of work.
• 1:00:22
  Speaker 1: And that's why they made a big change. And so
• 1:00:25
  Speaker 1: if you actually looked into the individual milestones they had,
• 1:00:28
  Speaker 1: maybe it would have looked pretty different. But your conspiracy
• 1:00:32
  Speaker 1: theory is pretty interesting.
• 1:00:33
  Speaker 2: It's always fun.
• 1:00:34
  Speaker 1: Yeah.
• 1:00:35
  Speaker 2: And also, there's just too many stories of this. And
• 1:00:39
  Speaker 2: David Grush has, you know, on oath said that there
• 1:00:43
  Speaker 2: are back engineering programs and he was read into these
• 1:00:45
  Speaker 2: and that they've been around for a long time. Mm-hmm.
• 1:00:48
  Speaker 2: This is the assertion of that movie, The Age of Disclosure,
• 1:00:51
  Speaker 2: that the real problem is that they have misappropriated funds
• 1:00:54
  Speaker 2: and lied to Congress. And so they come out and
• 1:00:56
  Speaker 2: tell you, OK, we do have this program. Well, guess what?
• 1:00:59
  Speaker 2: Everybody goes to jail because you guys are a bunch
• 1:01:01
  Speaker 2: of liars and you've been stealing money and you've been
• 1:01:04
  Speaker 2: doing whatever you want to do with this money. I
• 1:01:06
  Speaker 2: don't know how much oversight is there on back engineering
• 1:01:11
  Speaker 2: UFO programs. So probably a lot of people get in trouble.
• 1:01:15
  Speaker 2: A lot of people go to jail. On top of that,
• 1:01:17
  Speaker 2: these things are all being done by weapons manufacturers, right?
• 1:01:22
  Speaker 2: Like where are you going to bring them to? Well,
• 1:01:24
  Speaker 2: you're going to bring them to Lockheed Martin or you're
• 1:01:26
  Speaker 2: going to bring them to, you know, Rocketdyne. It's going
• 1:01:29
  Speaker 2: to be someone that does that kind of work. You're
• 1:01:31
  Speaker 2: not going to do it on your own. It's not
• 1:01:32
  Speaker 2: going to be like, we'll do it. No, you're going
• 1:01:34
  Speaker 2: to have to bring it to people that already make
• 1:01:36
  Speaker 2: spaceships or bring it to people that already make jets.
• 1:01:39
  Speaker 2: And so they have a massive competitive advantage over any
• 1:01:42
  Speaker 2: other company. That's doing it. So then there's other companies
• 1:01:45
  Speaker 2: that also had contracts with the United States government. They
• 1:01:47
  Speaker 2: can sue. And so he lays out all the problems
• 1:01:50
  Speaker 2: with disclosure. And their assertion is that the only thing–
• 1:01:55
  Speaker 2: what we need if we really want to find out
• 1:01:57
  Speaker 2: the truth is we're going to need widespread amnesty for
• 1:02:01
  Speaker 2: all these people that were involved. My problem with that
• 1:02:04
  Speaker 2: is that's what I would say too. If I had
• 1:02:06
  Speaker 2: been stealing money for decades and decades, I would be
• 1:02:09
  Speaker 2: like– And then I'll tell you where all this stuff is.
• 1:02:13
  Speaker 2: I'm like, how do we know what this stuff is,
• 1:02:18
  Speaker 2: whether or not these are just top secret military programs
• 1:02:20
  Speaker 2: with advanced propulsion technology that's unavailable to the public and
• 1:02:24
  Speaker 2: they're going to say that it's aliens and they back
• 1:02:26
  Speaker 2: engineered this and they did that. They clearly don't want
• 1:02:29
  Speaker 2: to tell people. They don't want people to know. I
• 1:02:31
  Speaker 2: think a large part of it is probably because they
• 1:02:34
  Speaker 2: could get in trouble. But I think also a large
• 1:02:36
  Speaker 2: part of it is because it's fun to keep secrets
• 1:02:38
  Speaker 2: from people.
• 1:02:39
  Speaker 3: Yeah.
• 1:02:40
  Speaker 2: Especially when you're the government. Why tell them? Fuck those people.
• 1:02:43
  Speaker 2: Fuck them. They don't even know UFOs are real. Meanwhile,
• 1:02:47
  Speaker 2: we're going into a bunker in the middle of the
• 1:02:49
  Speaker 2: mountain and we're remote viewing. There's probably a lot of
• 1:02:55
  Speaker 2: fun involved in having access to information that most people
• 1:02:58
  Speaker 2: would kill for.
• 1:03:00
  Speaker 1: I mean, there's so much information that we just don't
• 1:03:04
  Speaker 1: have access to.
• 1:03:05
  Speaker 2: Which brings me to this question. With It seems like
• 1:03:09
  Speaker 2: one of the things that's happening both with AI and
• 1:03:12
  Speaker 2: with technology in general is that you have more and
• 1:03:16
  Speaker 2: more access to information and more and more answers to
• 1:03:20
  Speaker 2: questions than ever before.
• 1:03:21
  Speaker 1: Yeah.
• 1:03:23
  Speaker 2: At a certain point in time, there's going to be
• 1:03:26
  Speaker 2: no bottleneck.
• 1:03:27
  Speaker 3: Yeah.
• 1:03:27
  Speaker 2: And we're going to know everything about everything.
• 1:03:29
  Speaker 1: Yeah.
• 1:03:29
  Speaker 2: So how is anyone in government? Going to keep a secret.
• 1:03:33
  Speaker 2: How is any corruption ever going to be possible? At
• 1:03:37
  Speaker 2: a certain point in time, all of it will get uncovered.
• 1:03:40
  Speaker 2: Like it's much more difficult to commit murder now with
• 1:03:42
  Speaker 2: DNA evidence, right? Back in the 1800s, like I didn't
• 1:03:46
  Speaker 2: see nothing. I wasn't there. And then you're free. Like
• 1:03:49
  Speaker 2: now they do your fingerprints. Now they get your DNA.
• 1:03:53
  Speaker 2: Now there's flock cameras. There's like more and more and more.
• 1:03:57
  Speaker 2: It's harder to get away with things.
• 1:03:58
  Speaker 3: Yeah.
• 1:03:59
  Speaker 2: So it seems like to me like whatever they have,
• 1:04:02
  Speaker 2: whatever anybody has, ultimately there's going to come a point
• 1:04:05
  Speaker 2: in time where there's so much data and so much
• 1:04:07
  Speaker 2: information and you could run all your questions. Like there's
• 1:04:10
  Speaker 2: an AI fact checker for politicians now. Yeah. So while
• 1:04:14
  Speaker 2: a politician is giving a speech, you can run an
• 1:04:16
  Speaker 2: AI fact checker and in real time it will tell
• 1:04:19
  Speaker 2: you whether or not these people are full of shit.
• 1:04:21
  Speaker 2: It seems like the direction is there's not going to
• 1:04:23
  Speaker 2: be anybody full of shit in the future because it's
• 1:04:25
  Speaker 2: not going to be possible.
• 1:04:26
  Speaker 3: Yeah.
• 1:04:27
  Speaker 1: I mean, the government still would have access to things
• 1:04:29
  Speaker 1: that we human beings wouldn't have access to, like regular people.
• 1:04:35
  Speaker 1: And particularly defense-related, weapons-related. Like, for example, when they did
• 1:04:42
  Speaker 1: the Venezuela thing, I don't think people in Venezuela even
• 1:04:47
  Speaker 1: understood what even those weapons were.
• 1:04:51
  Speaker 2: Well, I mean, we did. We were the general public.
• 1:04:53
  Speaker 1: Yeah, they were described as something, the literal words used
• 1:04:57
  Speaker 1: were like alien-like technology. So even we didn't know that
• 1:05:02
  Speaker 1: the United States had access to that quality of defense
• 1:05:06
  Speaker 1: technology until that incident happened. So there are obviously going
• 1:05:11
  Speaker 1: to be secrets, right? Especially the highest stakes things. I
• 1:05:16
  Speaker 1: would say like building frontier AI models is similar to that.
• 1:05:20
  Speaker 1: Of course, as more and more models are getting open source,
• 1:05:24
  Speaker 1: I think the knowledge is diffusing. But still, the true
• 1:05:29
  Speaker 1: amount of details you need to actually train a really
• 1:05:31
  Speaker 1: amazing frontier reasoning capability model is still not, like, widely diffused.
• 1:05:37
  Speaker 1: So my hypothesis is that whatever is extremely high stakes
• 1:05:46
  Speaker 1: will still not be widely diffused. It'll At least there'll
• 1:05:50
  Speaker 1: be enough structures in place to keep it secret.
• 1:05:53
  Speaker 2: Forever?
• 1:05:54
  Speaker 1: Not forever, but for a while.
• 1:05:56
  Speaker 2: For a while. Yeah. That's the thing.
• 1:05:58
  Speaker 1: Long term, sure. Like things do get out and people
• 1:06:01
  Speaker 1: do understand.
• 1:06:01
  Speaker 2: But it feels like long term is what I'm looking at. Like, look,
• 1:06:04
  Speaker 2: when we're looking at history, we're talking in these, like
• 1:06:08
  Speaker 2: when we're looking at all these different temples and all
• 1:06:10
  Speaker 2: these different things, we're talking about thousands and thousands of years.
• 1:06:12
  Speaker 2: And thousands of years time span in between each individual one.
• 1:06:17
  Speaker 2: With our world, we're talking about massive change in 200 years.
• 1:06:22
  Speaker 3: Yeah.
• 1:06:22
  Speaker 2: Like this country's 250 years old. Think about how kooky
• 1:06:25
  Speaker 2: that is.
• 1:06:26
  Speaker 3: Yeah.
• 1:06:26
  Speaker 2: That is a blink of an eye in history.
• 1:06:28
  Speaker 1: But do we, do we understand everything that happened in
• 1:06:30
  Speaker 1: the United States?
• 1:06:30
  Speaker 3: No.
• 1:06:31
  Speaker 1: Exactly. So there are still some details that are hidden
• 1:06:34
  Speaker 1: from us. Like we don't fully understand everything.
• 1:06:37
  Speaker 2: Right. For now. Yeah. But my question is, as time
• 1:06:41
  Speaker 2: goes on, 250 years from now, is it even possible
• 1:06:45
  Speaker 2: to keep any secrets from anybody? And is that a
• 1:06:50
  Speaker 2: good thing? It might be a good thing. It sounds
• 1:06:53
  Speaker 2: horrible to people because they're like, oh my God, what
• 1:06:55
  Speaker 2: about privacy?
• 1:06:56
  Speaker 3: Right.
• 1:06:56
  Speaker 2: But also what about lies? Yeah. No more lies. Like
• 1:06:59
  Speaker 2: everyone's going to know what you're thinking. Everyone's going to
• 1:07:02
  Speaker 2: know everything people do all the time.
• 1:07:05
  Speaker 3: Yeah.
• 1:07:06
  Speaker 1: I mean, if you're a true surveillance state, obviously there
• 1:07:08
  Speaker 1: are no secrets.
• 1:07:09
  Speaker 2: Right.
• 1:07:12
  Speaker 1: Except about the government itself.
• 1:07:14
  Speaker 2: That's the problem.
• 1:07:15
  Speaker 3: Yeah.
• 1:07:15
  Speaker 2: Does it bottleneck with the government or does it get
• 1:07:18
  Speaker 2: to a point where you can't even have government secrets?
• 1:07:22
  Speaker 2: Because as technology evolves and as human civilization evolves, secrets
• 1:07:27
  Speaker 2: will be less and less, not just necessary, but secrets
• 1:07:30
  Speaker 2: will be problematic because there'll be an impediment to knowledge.
• 1:07:33
  Speaker 2: There'll be an impediment to understanding the truth. The true
• 1:07:36
  Speaker 2: scope of what the world is, like the true nature
• 1:07:39
  Speaker 2: of all of our various moving parts. Yeah.
• 1:07:42
  Speaker 1: I mean, as long as the human quality, the intrinsic
• 1:07:44
  Speaker 1: human quality of curiosity and truth-seekingness, which is, you know, universal,
• 1:07:48
  Speaker 1: it's existed ever since we've known human beings. If that
• 1:07:52
  Speaker 1: continues and that continues to be the case, then people
• 1:07:56
  Speaker 1: will have enough incentives to figure out the truth.
• 1:07:59
  Speaker 2: Yeah.
• 1:08:00
  Speaker 1: And if something is actually hard to get to, it
• 1:08:03
  Speaker 1: only motivates you more to actually go and find it.
• 1:08:06
  Speaker 2: For sure. So my question is, where does this all go?
• 1:08:09
  Speaker 2: And you obviously work in AI. And when you think
• 1:08:14
  Speaker 2: about AI and when you think about just technology in
• 1:08:16
  Speaker 2: general and you extrapolate, you just take it from here
• 1:08:19
  Speaker 2: and you just plot it out. Like what is a
• 1:08:22
  Speaker 2: possible scenario of 250 years from now? Like what does
• 1:08:26
  Speaker 2: it even look like? What does the United States look
• 1:08:28
  Speaker 2: like at 500 years old?
• 1:08:30
  Speaker 1: It's very hard to know. I'll be very honest. I
• 1:08:32
  Speaker 1: think it's very hard to know, even five years from now,
• 1:08:35
  Speaker 1: how it's going to look like.
• 1:08:37
  Speaker 2: That's crazy. Yeah. Five years ago, it was like.
• 1:08:40
  Speaker 1: Five years ago, whoever is at the top most in AI,
• 1:08:44
  Speaker 1: I don't even consider myself like that, but whoever is
• 1:08:46
  Speaker 1: at the most frontier level of decision-making in AI five
• 1:08:49
  Speaker 1: years ago, I don't think they predicted the exact state
• 1:08:52
  Speaker 1: we are in today.
• 1:08:53
  Speaker 2: Nobody did.
• 1:08:54
  Speaker 1: If they did, they would have already procured all the
• 1:08:57
  Speaker 1: compute and like, you know, manufactured all the chips, bought
• 1:09:00
  Speaker 1: out all the fabs. They would have done all that, right?
• 1:09:03
  Speaker 1: Just this counterfactual. Everyone's like bottlenecked by not having enough compute.
• 1:09:08
  Speaker 1: And like, we have, we don't have enough chips. We
• 1:09:10
  Speaker 1: don't have enough power. These are all the problems that
• 1:09:13
  Speaker 1: if you invite anybody in AI and ask, what is
• 1:09:15
  Speaker 1: the bottleneck in AI today? And everybody would say power.
• 1:09:17
  Speaker 1: I think Jensen was here and he said the same thing, right?
• 1:09:20
  Speaker 2: Yeah.
• 1:09:20
  Speaker 1: But, okay, like, if you predicted this exact state five
• 1:09:24
  Speaker 1: years before, wouldn't you have secured enough power and started
• 1:09:28
  Speaker 1: building more power plants yourself and started getting permits and, like, started, like,
• 1:09:32
  Speaker 1: planning out capacity? No, nobody did that. Everything is reactive
• 1:09:36
  Speaker 1: to the demand that we're having today.
• 1:09:38
  Speaker 2: And that's just five years.
• 1:09:39
  Speaker 1: Yeah, that's just five years. So when you ask me
• 1:09:41
  Speaker 1: to predict 250 years, like, I just have to honestly
• 1:09:44
  Speaker 1: say I don't know.
• 1:09:45
  Speaker 2: Do you ever sit back and think about it, though?
• 1:09:47
  Speaker 1: I don't think about it.
• 1:09:48
  Speaker 2: What it could be?
• 1:09:48
  Speaker 1: I don't think about it. So there are a lot
• 1:09:50
  Speaker 1: of fun. I use perplexity a lot for these kind
• 1:09:54
  Speaker 1: of things, especially this new feature computer inside it. And
• 1:10:01
  Speaker 1: this is just for hypothetical scenarios. Let's say there is
• 1:10:03
  Speaker 1: an AGI, right? I've seen you ask a lot of
• 1:10:06
  Speaker 1: people about this. And a lot of conventional answers is like, oh,
• 1:10:13
  Speaker 1: we'll just become managers of the AIs. Don't worry. But
• 1:10:18
  Speaker 1: if the price of cognition is the price of compute,
• 1:10:20
  Speaker 1: managing an AI is also pretty much doable by the
• 1:10:24
  Speaker 1: AI itself. Because the bottleneck is not like unique cognition
• 1:10:30
  Speaker 1: capability there. So the value of the society will automatically
• 1:10:34
  Speaker 1: shift to what is scarce. And fundamentally what has been
• 1:10:38
  Speaker 1: scarce is like asking like high quality questions about things. Okay,
• 1:10:42
  Speaker 1: like what if like we just, completely spend all our
• 1:10:46
  Speaker 1: time understanding the past like that's an interesting endeavor it
• 1:10:49
  Speaker 1: was not cool before but it'll it'll become cool again
• 1:10:52
  Speaker 1: um and like we usually used to view like archaeology
• 1:10:56
  Speaker 1: or history is not something that's like worth having a
• 1:10:59
  Speaker 1: career in because it doesn't pay well but what if
• 1:11:02
  Speaker 1: it actually starts paying you go a lot more now
• 1:11:04
  Speaker 1: that like actual knowledge works being done by ais and
• 1:11:07
  Speaker 1: like it's all mundane and all the price of that
• 1:11:09
  Speaker 1: is basically at zero.
• 1:11:10
  Speaker 2: Right, and archaeology would be one of the few things
• 1:11:13
  Speaker 2: that it wouldn't have access to because it doesn't have
• 1:11:15
  Speaker 2: the actual ground. It can't get into the ground and
• 1:11:18
  Speaker 2: do the scans.
• 1:11:20
  Speaker 1: Let's say we have robots to go do that, but
• 1:11:24
  Speaker 1: you're still going to be the one probing because you
• 1:11:26
  Speaker 1: have incomplete information all the time. Even the idea of, okay,
• 1:11:30
  Speaker 1: let's go explore this particular area. Let's go understand better.
• 1:11:34
  Speaker 1: Let's go try to reverse engineer this. Let's go try
• 1:11:36
  Speaker 1: to build this again. How would it be if we
• 1:11:39
  Speaker 1: wanted to do the same thing on the moon There are, like,
• 1:11:41
  Speaker 1: so many interesting projects to work on for us as
• 1:11:44
  Speaker 1: long as we stay curious and we stay interested in, like,
• 1:11:47
  Speaker 1: a lot of things that we've done before and trying
• 1:11:49
  Speaker 1: to understand, like, civilization. That I'm not really concerned about, like,
• 1:11:54
  Speaker 1: what things we get to do. We might be doing
• 1:11:56
  Speaker 1: a lot more cool things for what it's worth. Like,
• 1:11:58
  Speaker 1: I don't know if anybody will be, like, coming and
• 1:12:00
  Speaker 1: telling you that, oh, it's so cool to, like, open
• 1:12:02
  Speaker 1: an Excel sheet every day and make financial models, right?
• 1:12:06
  Speaker 1: Compared to, like.
• 1:12:07
  Speaker 2: There's got to be somebody out there that likes that.
• 1:12:09
  Speaker 1: I mean, there's something about the task you do and
• 1:12:12
  Speaker 1: what you get paid for, like what is the job title, blah, blah, blah,
• 1:12:15
  Speaker 1: and some people associate their personal worth with where they
• 1:12:21
  Speaker 1: work at and how much they get paid. And I
• 1:12:23
  Speaker 1: think that thing is going to collapse in a world
• 1:12:26
  Speaker 1: where the price of all that cognition is going to
• 1:12:29
  Speaker 1: be the price of compute.
• 1:12:31
  Speaker 2: What do you think happens to people if a large
• 1:12:36
  Speaker 2: percentage of jobs... get replaced by AI?
• 1:12:40
  Speaker 1: I think they'll find new things. We've always gravitated towards
• 1:12:45
  Speaker 1: things that are scarce because that's where the value lies.
• 1:12:49
  Speaker 1: And so if, you know, have you, one interesting analogy
• 1:12:56
  Speaker 1: is the Gulf states where there's an abundance of resources
• 1:13:02
  Speaker 1: and they export their resources to other states and that
• 1:13:06
  Speaker 1: pays for the whole state. you know how like they,
• 1:13:09
  Speaker 1: they offer everybody, um, free electricity, subsidized health, subsidized education,
• 1:13:14
  Speaker 1: and like no taxes. When I first went to Dubai,
• 1:13:17
  Speaker 1: like in, um, almost like 20 years ago, um, they
• 1:13:23
  Speaker 1: told me like, people don't pay taxes here and nobody
• 1:13:25
  Speaker 1: pays for electricity here. And, uh, education is like super cheap.
• 1:13:30
  Speaker 1: And I was like, wait, how is that real? And, and, um, and, uh,
• 1:13:35
  Speaker 1: And the way that's real is that, I mean, of course,
• 1:13:38
  Speaker 1: Texas also has no taxes and, you know, any well-run
• 1:13:40
  Speaker 1: state can do this. But the way it's happening is
• 1:13:43
  Speaker 1: that because the government provides you all these things, it
• 1:13:46
  Speaker 1: becomes a rentier state. Like you offer political acquiescence to
• 1:13:50
  Speaker 1: the state. And what ended up happening is citizens there
• 1:13:56
  Speaker 1: expect the state to find them jobs, expect the state
• 1:13:59
  Speaker 1: to take care of like job displacement for them. So
• 1:14:01
  Speaker 1: they don't worry. So it made them a little more lazy.
• 1:14:04
  Speaker 1: So that's not a good future to have, where some
• 1:14:08
  Speaker 1: people talk about AI subsidies and AI dividends that get
• 1:14:11
  Speaker 1: paid to everybody. I think we need to do some
• 1:14:13
  Speaker 1: form of that, but that in entirety won't solve the problem.
• 1:14:17
  Speaker 2: Right. Well, the thing about human nature is sort of undeniable.
• 1:14:24
  Speaker 2: And if you give people the ability to be lazy,
• 1:14:26
  Speaker 2: a large percentage of people will take that.
• 1:14:28
  Speaker 1: That's right.
• 1:14:29
  Speaker 2: A large percentage won't, though.
• 1:14:30
  Speaker 3: Yeah.
• 1:14:31
  Speaker 2: There's going to be enough people that are inspired to
• 1:14:33
  Speaker 2: do something and they say, okay, well, now my basic
• 1:14:35
  Speaker 2: needs are taken care of. Let me pursue my actual interests.
• 1:14:38
  Speaker 1: That's right.
• 1:14:39
  Speaker 2: And find purpose in that.
• 1:14:40
  Speaker 3: Yeah.
• 1:14:40
  Speaker 2: Because that's– a lot of people find purpose in whatever
• 1:14:43
  Speaker 2: their occupation is.
• 1:14:44
  Speaker 3: Yeah.
• 1:14:44
  Speaker 2: And if we can shift that to finding purpose in
• 1:14:47
  Speaker 2: what your actual interests are.
• 1:14:49
  Speaker 3: Yeah.
• 1:14:49
  Speaker 2: And then really pursuing something, whatever it is in that.
• 1:14:52
  Speaker 2: Then you'll still have meaning in your life.
• 1:14:54
  Speaker 1: It keeps coming back to staying curious.
• 1:14:58
  Speaker 2: Yes.
• 1:14:58
  Speaker 1: And finding value in– your relationships, your, your, the family, uh,
• 1:15:04
  Speaker 1: caring for each other. Um, if you ask a lot
• 1:15:07
  Speaker 1: of retired people, actually retired people is a good demographic
• 1:15:10
  Speaker 1: to understand what would happen, what, what are things people
• 1:15:13
  Speaker 1: find meaning in after like work's taken off them. And
• 1:15:16
  Speaker 1: all majority of the answers are always like family, caring,
• 1:15:21
  Speaker 1: you know, personal, like, like relationships and a community. Like
• 1:15:25
  Speaker 1: these are the things that retired people keep doing to
• 1:15:28
  Speaker 1: like you know keep themselves active and wake up every
• 1:15:30
  Speaker 1: day and have something to look for so all those
• 1:15:33
  Speaker 1: things will become even more important at a time when
• 1:15:36
  Speaker 1: like work itself doesn't mean much doesn't mean humans won't
• 1:15:41
  Speaker 1: be status seeking i think we'll still be but status
• 1:15:44
  Speaker 1: is not gonna come from whether you're working at you
• 1:15:48
  Speaker 1: know like a particular famous bank or a tech company
• 1:15:51
  Speaker 1: or whatever it'll be driven by like um how interesting
• 1:15:55
  Speaker 1: you are are you interesting to talk to When I
• 1:15:58
  Speaker 1: can talk to an AI, despite that, are you still
• 1:16:01
  Speaker 1: interesting to talk to? Are there certain things I get
• 1:16:03
  Speaker 1: out of talking to you that completely change my perspective
• 1:16:07
  Speaker 1: about a bunch of things? Or is it just fun
• 1:16:10
  Speaker 1: to hang around you? Can we have a compounded relationship together?
• 1:16:14
  Speaker 1: And I think, again, it goes back to being curious
• 1:16:18
  Speaker 1: about things.
• 1:16:18
  Speaker 2: Well, this is best case scenario, right? Worst case scenario
• 1:16:22
  Speaker 2: is civilization upheaval, chaos, civil war.
• 1:16:26
  Speaker 1: And it's possible even without an AI.
• 1:16:28
  Speaker 2: Right. Yeah. Look, we've gotten real close to it a
• 1:16:31
  Speaker 2: couple of times.
• 1:16:31
  Speaker 1: Exactly.
• 1:16:32
  Speaker 2: Yeah.
• 1:16:32
  Speaker 1: And we did not need an AGI-like scenario for a
• 1:16:37
  Speaker 1: civilizational collapse in the past, as you've clearly seen.
• 1:16:41
  Speaker 2: Right.
• 1:16:41
  Speaker 1: A calamity can just take out all of us, wipe
• 1:16:44
  Speaker 1: out everything.
• 1:16:45
  Speaker 2: Sure. Especially natural ones.
• 1:16:46
  Speaker 3: Yeah.
• 1:16:46
  Speaker 1: That's why I'm not a big fan of everybody claiming
• 1:16:48
  Speaker 1: that the AI is going to, you know, kill us. So, like,
• 1:16:52
  Speaker 1: AGI is going to destroy humanity and, like, it's too
• 1:16:55
  Speaker 1: dangerous and we all need to stop doing these things.
• 1:16:58
  Speaker 1: But at the same time, continuing to fill all these
• 1:16:59
  Speaker 1: data centers and continuing to make money, you have to
• 1:17:02
  Speaker 1: have one consistent position. My position is that whether AI
• 1:17:08
  Speaker 1: or not, I think being curious is going to serve
• 1:17:11
  Speaker 1: you really well. I think it's going to help you
• 1:17:14
  Speaker 1: have a better life. And there are two paths to curiosity,
• 1:17:17
  Speaker 1: one that can kill it and one that can supercharge it.
• 1:17:21
  Speaker 1: In my opinion, the one that kills curiosity is algorithmic feeds. Like,
• 1:17:25
  Speaker 1: the brain rot that you're fed every day with just,
• 1:17:29
  Speaker 1: you know, this continuous doom scrolling, that's bad. And the
• 1:17:33
  Speaker 1: one that can supercharge it is AI. Okay, like, now
• 1:17:37
  Speaker 1: that you could just ask whatever you want. If everybody has, like,
• 1:17:41
  Speaker 1: a pull-it-up Jamie for them, you know.
• 1:17:43
  Speaker 2: Right.
• 1:17:44
  Speaker 1: And that's amazing. So all you have to do is
• 1:17:48
  Speaker 1: be curious about a lot of different things. And, of course,
• 1:17:51
  Speaker 1: talk to interesting people, engage in interesting activities together. If
• 1:17:55
  Speaker 1: money is no longer an issue, you can fund passion
• 1:17:58
  Speaker 1: projects yourself. You don't have to, like, require government funding
• 1:18:01
  Speaker 1: or venture funding. Like, what if you just wanted to
• 1:18:04
  Speaker 1: build a mini cave yourself? Okay, like, you find a
• 1:18:08
  Speaker 1: piece of land somewhere. There's a lot of land in America.
• 1:18:12
  Speaker 1: Way more land than we know what to do with it.
• 1:18:14
  Speaker 1: And surely we can build a lot of interesting things there.
• 1:18:18
  Speaker 2: Well, that's a good... Glass half full scenario. And one
• 1:18:23
  Speaker 2: of the things that I keep coming to is this
• 1:18:26
  Speaker 2: whole idea of people working and making money and having
• 1:18:31
  Speaker 2: careers and having portfolios and bank accounts. This is all
• 1:18:36
  Speaker 2: very recent in human history.
• 1:18:37
  Speaker 3: Yeah.
• 1:18:38
  Speaker 1: Very recent.
• 1:18:39
  Speaker 2: Very recent. But we've become accustomed to this as a
• 1:18:42
  Speaker 2: way of life.
• 1:18:43
  Speaker 1: And Microsoft built this concept of a knowledge worker because
• 1:18:46
  Speaker 1: they wanted to sell more office software.
• 1:18:49
  Speaker 3: Really?
• 1:18:50
  Speaker 2: Yeah.
• 1:18:51
  Speaker 1: Like this whole idea of putting a PC on every
• 1:18:53
  Speaker 1: desk and making you like glued to the PC was there.
• 1:18:57
  Speaker 1: That was Bill Gates' vision. Put a PC on every desk.
• 1:18:59
  Speaker 2: That fucking wizard. What an incredible accomplishment because, boy, did
• 1:19:04
  Speaker 2: they nail it. Yes.
• 1:19:06
  Speaker 1: It was not about making computing like beautiful or anything
• 1:19:09
  Speaker 1: in the way like Steve Jobs and mission did.
• 1:19:11
  Speaker 2: Right.
• 1:19:12
  Speaker 1: It was just about like computers, sell more software, sell
• 1:19:15
  Speaker 1: more computers because that way you can sell more software.
• 1:19:18
  Speaker 1: And if you sell more software, you become rich. And, and, and,
• 1:19:21
  Speaker 1: and the company just was a machine that was just,
• 1:19:25
  Speaker 1: you know, built a, it's essentially a large sales machine
• 1:19:27
  Speaker 1: that's built to sell software. And, and, and, uh, And
• 1:19:32
  Speaker 1: now they sell cloud, but whatever. That's essentially the reason
• 1:19:37
  Speaker 1: that we all got trained to use software. People went
• 1:19:42
  Speaker 1: and did tutorials on how to use Excel, how to
• 1:19:45
  Speaker 1: use Word, how to use all these email tools. And
• 1:19:47
  Speaker 1: then now that became the upscaling you needed to go
• 1:19:50
  Speaker 1: work at different companies and then write code and whatever.
• 1:19:54
  Speaker 1: So if that part's going to be done by an AI,
• 1:19:56
  Speaker 1: it's not necessarily a bad thing. Because this is not
• 1:20:00
  Speaker 1: actually the way you feel a real purpose and fulfillment
• 1:20:03
  Speaker 1: in your own life. If you were never exposed to that,
• 1:20:08
  Speaker 1: whatever you had as the intrinsic curiosity in you, that's
• 1:20:12
  Speaker 1: probably what you should be doing.
• 1:20:14
  Speaker 2: Yeah, there could be a completely new way to live
• 1:20:16
  Speaker 2: life where we're not dependent upon labor for basic needs.
• 1:20:22
  Speaker 2: But then it's going to be incumbent upon people. They're
• 1:20:25
  Speaker 2: going to have to figure out a way to be
• 1:20:27
  Speaker 2: either self-starting or we're going to have to expose people
• 1:20:30
  Speaker 2: the things that are going to excite their curiosity, and
• 1:20:33
  Speaker 2: make that a mandate.
• 1:20:34
  Speaker 1: Yeah. It has to start from schools.
• 1:20:37
  Speaker 2: Yeah.
• 1:20:37
  Speaker 1: And as long as we keep rewarding people for having
• 1:20:41
  Speaker 1: answers instead of asking interesting questions, it's going to be
• 1:20:46
  Speaker 1: a difficult change. Like in schools, you're always rewarded for
• 1:20:50
  Speaker 1: being smart based on whether you have answers to like
• 1:20:53
  Speaker 1: 20 different questions. Like who cares? Like all those 20
• 1:20:56
  Speaker 1: questions can be answered by AIs. Um, have you ever
• 1:20:59
  Speaker 1: like flipped the script where you say, okay, like I'm
• 1:21:02
  Speaker 1: going to, the smartest person in the room is the
• 1:21:04
  Speaker 1: one who has the most interesting questions.
• 1:21:06
  Speaker 2: Okay.
• 1:21:07
  Speaker 1: Like what, what kind of students can you cultivate based
• 1:21:09
  Speaker 1: on that? Like imagine if the room had no pressure
• 1:21:13
  Speaker 1: to always know the answer, but the freedom to ask
• 1:21:17
  Speaker 1: a lot of questions.
• 1:21:18
  Speaker 3: Right.
• 1:21:18
  Speaker 2: Because sometimes when someone asks a question, it'll, it does
• 1:21:23
  Speaker 2: make you pause and go, I never even thought of that,
• 1:21:25
  Speaker 2: but that's it. Like, that's the question.
• 1:21:28
  Speaker 3: Yeah.
• 1:21:28
  Speaker 2: And it takes a, I mean, so many people have
• 1:21:31
  Speaker 2: so many different perspectives, which is one of the more
• 1:21:33
  Speaker 2: interesting things that I've experienced doing this podcast is I
• 1:21:37
  Speaker 2: get to talk to so many different people and they
• 1:21:40
  Speaker 2: vary so widely. There's so many different ways of looking
• 1:21:45
  Speaker 2: at the world and so many different ways of engaging
• 1:21:47
  Speaker 2: with the world and so many different things that people
• 1:21:49
  Speaker 2: are fascinated with that they spent their entire life studying
• 1:21:52
  Speaker 2: and pursuing. It's like you get this rich tapestry of
• 1:21:57
  Speaker 2: the human experience that's just, I would have never been
• 1:22:00
  Speaker 2: exposed to this many people. And in turn, I've been
• 1:22:03
  Speaker 2: able to expose these people to all these other folks
• 1:22:06
  Speaker 2: that are just listening and watching right now. And it's
• 1:22:09
  Speaker 2: fucking incredible. And it's such a, for me, it's like
• 1:22:12
  Speaker 2: the perfect job. I've never had a job that more
• 1:22:15
  Speaker 2: aligns with my own personality as much as this. Because
• 1:22:19
  Speaker 2: I've always been that kid, like, shut the fuck up
• 1:22:21
  Speaker 2: with all the questions. I've always been that kid.
• 1:22:23
  Speaker 1: That's the system, right? It's not your fault.
• 1:22:26
  Speaker 2: Right.
• 1:22:26
  Speaker 1: Like, it's actually the reason you're successful now is the
• 1:22:29
  Speaker 1: exact thing that people told you to shut up about
• 1:22:31
  Speaker 1: in the past.
• 1:22:33
  Speaker 3: Right?
• 1:22:33
  Speaker 2: Yeah.
• 1:22:35
  Speaker 1: Hey, you know, stop bothering my lecture, you know, asking
• 1:22:40
  Speaker 1: all these unrelated questions. It's mainly a frustration of the
• 1:22:43
  Speaker 1: teacher that they don't have the answers to you.
• 1:22:46
  Speaker 3: Right?
• 1:22:46
  Speaker 1: Sure. And now that bottleneck is gone. We did this
• 1:22:51
  Speaker 1: experiment with one instructor at MIT who taught the introduction
• 1:22:55
  Speaker 1: to biology class where he came and told us that
• 1:22:58
  Speaker 1: he's going to give perplexity to all the kids, all
• 1:23:00
  Speaker 1: the students, and they would use it as part of
• 1:23:04
  Speaker 1: the lectures. So instead of fighting AI, you just give
• 1:23:09
  Speaker 1: AI to everybody and let them ask whatever questions they want,
• 1:23:12
  Speaker 1: and they can actually use it in the exams too.
• 1:23:15
  Speaker 1: So how do you even design questions for an exam
• 1:23:20
  Speaker 1: in such a world is maybe you just encourage people
• 1:23:23
  Speaker 1: to pose a question that AI can't answer right now
• 1:23:27
  Speaker 1: and that becomes your research project and you turn everybody
• 1:23:31
  Speaker 1: into a scientist. Fundamentally, there's this belief that scientists have
• 1:23:35
  Speaker 1: to go through a rigorous PhD and you have to
• 1:23:38
  Speaker 1: get accredited by an amazing university to be that. Sure,
• 1:23:42
  Speaker 1: but anyone who's curious can be a scientist. The only
• 1:23:46
  Speaker 1: thing that's required to be a good scientist is intellectual
• 1:23:49
  Speaker 1: humility to understand that you could be wrong about things,
• 1:23:53
  Speaker 1: things that everyone takes for granted. You could still question them.
• 1:23:57
  Speaker 1: And when you're presented with new evidence and new data,
• 1:24:00
  Speaker 1: you're willing to change your mind and you're willing to
• 1:24:03
  Speaker 1: operate with ambiguity and uncertainty about the world. That's basically
• 1:24:07
  Speaker 1: all the qualities you need to be a scientist. And
• 1:24:10
  Speaker 1: you can run your experiments, you can gather data, you
• 1:24:12
  Speaker 1: can gather evidence, and you can consult people, you can
• 1:24:15
  Speaker 1: bring in experts and talk to them. And as long
• 1:24:18
  Speaker 1: as you're uncovering more and more about the world, you
• 1:24:21
  Speaker 1: are a scientist. You don't need a PhD to feel
• 1:24:24
  Speaker 1: that you're allowed to be a scientist or not. And
• 1:24:27
  Speaker 1: I think that's the most important quality we need to
• 1:24:32
  Speaker 1: inculcate in our kids, the upcoming generation. So that they
• 1:24:37
  Speaker 1: all feel more liberated. Okay, like finally I don't have
• 1:24:40
  Speaker 1: to memorize this textbook or these lecture materials. And like
• 1:24:43
  Speaker 1: I don't have to feel bad if I get like
• 1:24:44
  Speaker 1: 12 out of 20. Okay, who cares? Like AI is
• 1:24:48
  Speaker 1: always going to get 20 out of 20. That's not
• 1:24:50
  Speaker 1: what you're meant to be like good at. Of course,
• 1:24:52
  Speaker 1: master the foundations, the basics, great. But your job is
• 1:24:56
  Speaker 1: to actually pose interesting questions.
• 1:24:59
  Speaker 2: Yeah, and the intellectual, excuse me, intellectual humility is so important.
• 1:25:03
  Speaker 2: Because one of the things that was really weird about
• 1:25:06
  Speaker 2: the whole COVID pandemic was that we weren't supposed to
• 1:25:09
  Speaker 2: question science.
• 1:25:10
  Speaker 1: Yeah.
• 1:25:12
  Speaker 2: Or when Fauci said, if you question Anthony Fauci, you
• 1:25:15
  Speaker 2: are questioning science.
• 1:25:17
  Speaker 1: That's because they try to assign credibility through their degrees.
• 1:25:21
  Speaker 2: Yes.
• 1:25:21
  Speaker 1: Through their affiliations.
• 1:25:22
  Speaker 2: Yes. Appeal to authority.
• 1:25:24
  Speaker 1: But not through the scientific method.
• 1:25:25
  Speaker 2: Right.
• 1:25:26
  Speaker 1: Anybody should be allowed to ask questions as long as
• 1:25:29
  Speaker 1: they are open to new evidence.
• 1:25:31
  Speaker 3: Yeah.
• 1:25:31
  Speaker 1: Yeah. And that's the most important quality of a scientist.
• 1:25:34
  Speaker 2: Well, the scientific method alone, I mean, it's one of
• 1:25:37
  Speaker 2: the most important things that we can use to try
• 1:25:40
  Speaker 2: to figure out what's real and what's not real. And
• 1:25:42
  Speaker 2: as soon as someone says, don't use it. Yeah. Don't question. Well,
• 1:25:46
  Speaker 2: wait a minute. And then there was an actual government
• 1:25:51
  Speaker 2: push to silence questioning and legitimate researchers were kicked off
• 1:25:56
  Speaker 2: of Twitter because they didn't back the narrative.
• 1:25:58
  Speaker 3: Yeah.
• 1:25:59
  Speaker 2: Like this is all anti-science. This is not, this is not,
• 1:26:02
  Speaker 2: You're questioning science. Well, science demands questioning. Yeah. It's what
• 1:26:07
  Speaker 2: it is.
• 1:26:07
  Speaker 3: Yeah.
• 1:26:08
  Speaker 1: When you don't understand something, the best thing you can
• 1:26:10
  Speaker 1: do is ask all possible questions.
• 1:26:13
  Speaker 2: Right.
• 1:26:13
  Speaker 1: And so curbing that is almost like a way of saying, look,
• 1:26:17
  Speaker 1: I'm going to tell you what happened. You need to
• 1:26:19
  Speaker 1: believe in my worldview. And I'm not open to new perspectives.
• 1:26:24
  Speaker 2: I wonder if anybody has used AI to try to
• 1:26:28
  Speaker 2: map out possible scenarios that For where technology leads human
• 1:26:33
  Speaker 2: civilization and what could be done to mitigate the problems
• 1:26:37
  Speaker 2: and push it in the proper direction. Like have a
• 1:26:40
  Speaker 2: bunch of different models of how this could play out. Yeah.
• 1:26:45
  Speaker 1: I mean, I try to do that for fun, but
• 1:26:48
  Speaker 1: I haven't done it in a serious enough way to
• 1:26:50
  Speaker 1: have like a proper answer to that.
• 1:26:51
  Speaker 2: Right.
• 1:26:52
  Speaker 1: But I think like, you know, a lot of things
• 1:26:56
  Speaker 1: that we are doing today will not be considered needed
• 1:27:00
  Speaker 1: or valuable. And maybe a little bit of taking our
• 1:27:05
  Speaker 1: own lessons from the past. I don't know if you,
• 1:27:07
  Speaker 1: when you grew up as a student, did you have
• 1:27:09
  Speaker 1: to like be good at mental math, like multiplying arbitrary numbers?
• 1:27:13
  Speaker 1: Was that considered a sign of smartness or remembering people's
• 1:27:16
  Speaker 1: phone numbers or something?
• 1:27:17
  Speaker 2: Well, you had to because there was, I mean, you
• 1:27:19
  Speaker 2: had little address books. We used to carry around like
• 1:27:21
  Speaker 2: a little, I had a little address book that I
• 1:27:23
  Speaker 2: keep on my desk.
• 1:27:24
  Speaker 1: It's a little.
• 1:27:24
  Speaker 2: Tiny thing with everybody's number and name. That's the only
• 1:27:27
  Speaker 2: way I knew people's numbers. And I remembered a bunch
• 1:27:30
  Speaker 2: of them, like all my friends. I had all my friends.
• 1:27:32
  Speaker 2: I don't have any of my friends' numbers remembered. Maybe
• 1:27:35
  Speaker 2: my wife and my friend Eddie. I have two numbers
• 1:27:38
  Speaker 2: in my head.
• 1:27:39
  Speaker 1: But was there a time when people thought somebody was
• 1:27:42
  Speaker 1: smart based on how good their memory power was?
• 1:27:45
  Speaker 2: Oh, yeah, definitely.
• 1:27:46
  Speaker 1: But would you say that now?
• 1:27:49
  Speaker 2: Well, people are impressed if you know things now. I
• 1:27:53
  Speaker 2: have a bunch of weird information, obviously, that I've gathered
• 1:27:57
  Speaker 2: through so many years of doing this podcast and just
• 1:27:59
  Speaker 2: so many years of being curious, you know, like sometimes
• 1:28:02
  Speaker 2: even my own daughter was like, how the fuck do
• 1:28:03
  Speaker 2: you know that? I'm like, this is what I do. Like,
• 1:28:06
  Speaker 2: that's my thing. Yeah. You know, I pay attention to stuff. Yeah.
• 1:28:09
  Speaker 2: But yeah, I mean, memory itself is always very impressive
• 1:28:14
  Speaker 2: and someone has an excellent memory and can pull up
• 1:28:16
  Speaker 2: facts of the past. Yeah. We automatically equate that to intelligence.
• 1:28:20
  Speaker 3: Yeah.
• 1:28:21
  Speaker 1: I think it's impressive, but it's not necessarily a sign
• 1:28:23
  Speaker 1: of being intelligent, right? Like, I think you have a
• 1:28:28
  Speaker 1: very fast lookup table in your head. That's great. It's
• 1:28:31
  Speaker 1: very valuable. But I still think being smart is all
• 1:28:35
  Speaker 1: about posing the most interesting questions.
• 1:28:38
  Speaker 2: Also, the decisions that you make. and whether or not
• 1:28:41
  Speaker 2: you self-correct when you make mistakes.
• 1:28:43
  Speaker 1: Yeah.
• 1:28:44
  Speaker 2: All those things.
• 1:28:45
  Speaker 1: Exactly. So when you have an amplifier to your intelligence,
• 1:28:48
  Speaker 1: like an AI, all the time, lookups is essentially something
• 1:28:52
  Speaker 1: you can delegate. Reasoning for decision-making is something you can delegate.
• 1:28:57
  Speaker 1: But posing the right questions to gather the right data,
• 1:29:00
  Speaker 1: and then forming your own judgment based on what it
• 1:29:03
  Speaker 1: reasons and comes up with, and finally having the courage
• 1:29:06
  Speaker 1: to make the decision, that's still you. That agency, that
• 1:29:09
  Speaker 1: intrinsic curiosity to ask the right question, the scientific intellectual
• 1:29:14
  Speaker 1: humility to like, you know, gather new evidence, always questioning
• 1:29:18
  Speaker 1: your beliefs, that is still you. And so I feel
• 1:29:21
  Speaker 1: like that is essentially what would be considered smart in
• 1:29:25
  Speaker 1: the ages to come. If somebody is like a, you know,
• 1:29:28
  Speaker 1: like a proxy scientist or whatever, like no more doesn't
• 1:29:32
  Speaker 1: have to go to like MIT or Harvard and get
• 1:29:34
  Speaker 1: a PhD to be a scientist or to be considered
• 1:29:36
  Speaker 1: a scientist. Because all scientific literature is open and it's
• 1:29:39
  Speaker 1: accessible to everybody. And you can even take a paper
• 1:29:43
  Speaker 1: written by an expert and use an AI, understand it deeply,
• 1:29:47
  Speaker 1: ask a lot of questions and maybe even disprove what
• 1:29:49
  Speaker 1: they claim to be true. That's the whole peer review process, right?
• 1:29:55
  Speaker 1: The peer review process is all about questioning somebody's paper.
• 1:30:00
  Speaker 1: And that's why, like, you know, whatever you said happened
• 1:30:03
  Speaker 1: in COVID days is wrong. Like, you should be allowed
• 1:30:06
  Speaker 1: to ask questions about even eminent scientists' work. It's okay. Like,
• 1:30:12
  Speaker 1: if you're dumb and you had the wrong questions, sure,
• 1:30:15
  Speaker 1: you're going to learn from that. It's worse than not
• 1:30:18
  Speaker 1: being allowed to ask the question.
• 1:30:19
  Speaker 2: Yeah, agreed. It's going to be interesting to see what
• 1:30:22
  Speaker 2: the future of education looks like, like how valuable our
• 1:30:25
  Speaker 2: degrees are. When essentially AI is going to be able
• 1:30:28
  Speaker 2: to do the majority of whatever work you need done
• 1:30:31
  Speaker 2: on a variety of things. How good are they right
• 1:30:36
  Speaker 2: now at just law? Like you could ask questions.
• 1:30:42
  Speaker 1: Pretty good.
• 1:30:43
  Speaker 2: Pretty amazing, right?
• 1:30:43
  Speaker 1: Yeah, pretty good.
• 1:30:44
  Speaker 2: How good are they at mathematics?
• 1:30:46
  Speaker 3: Perfect.
• 1:30:46
  Speaker 2: How good are they at coding? Way better than people. Yeah.
• 1:30:50
  Speaker 2: And at a certain point in time, it's going to
• 1:30:51
  Speaker 2: be interesting to like what is education now? Is education
• 1:30:54
  Speaker 2: just providing you with information? Because that information is readily available.
• 1:30:58
  Speaker 3: Yeah.
• 1:30:58
  Speaker 2: Or is education teaching you how to think?
• 1:31:01
  Speaker 3: Yeah.
• 1:31:01
  Speaker 2: Teaching you how to pursue your interests and be curious
• 1:31:04
  Speaker 2: and have intellectual humility and understand what you know and
• 1:31:07
  Speaker 2: what you don't know?
• 1:31:08
  Speaker 1: I think that's where it should be. I still think
• 1:31:12
  Speaker 1: institutions will preserve their brand value because there is a
• 1:31:16
  Speaker 1: certain aspect of education that's outside of learning, which is
• 1:31:20
  Speaker 1: just having access to other curious and intelligent people.
• 1:31:23
  Speaker 2: Sure.
• 1:31:23
  Speaker 1: Community.
• 1:31:24
  Speaker 2: Community.
• 1:31:24
  Speaker 1: Yeah, and brands attract good communities, peer groups, blah, blah, blah.
• 1:31:28
  Speaker 1: But the actual process of learning has to change. And
• 1:31:32
  Speaker 1: what you're rewarded for has to change. Fundamentally, everything flows
• 1:31:37
  Speaker 1: downstream of the incentive. So if the incentive is to
• 1:31:40
  Speaker 1: score the highest on the exam based on answers, you're
• 1:31:43
  Speaker 1: not really changing much. You need to change that process.
• 1:31:48
  Speaker 1: You need to change the process of what do you
• 1:31:49
  Speaker 1: reward a student? Like what is A plus or A?
• 1:31:52
  Speaker 2: Right.
• 1:31:53
  Speaker 1: That's where we need to start at.
• 1:31:56
  Speaker 2: We talked about this the other day, that the education
• 1:31:59
  Speaker 2: system in this country was designed to make workers.
• 1:32:02
  Speaker 1: Exactly.
• 1:32:02
  Speaker 2: That's what they did when they first started doing it.
• 1:32:05
  Speaker 1: Curriculum was designed around that. In India, it's still the case,
• 1:32:09
  Speaker 1: by the way.
• 1:32:10
  Speaker 2: Really?
• 1:32:12
  Speaker 1: Even if you go into a computer science degree, I
• 1:32:14
  Speaker 1: don't know if it's still the case. I shouldn't misspeak,
• 1:32:16
  Speaker 1: but at least when I was there and for many
• 1:32:17
  Speaker 1: years after, the first two years you just spend learning
• 1:32:21
  Speaker 1: hardcore electrical and mechanical engineering. You would learn, like, welding
• 1:32:24
  Speaker 1: using lathe machines. You would have to, like, go and, like,
• 1:32:28
  Speaker 1: do workshops, carpentry, a lot of these things. It was fun.
• 1:32:33
  Speaker 2: I would think there's been a lot of value in that.
• 1:32:35
  Speaker 1: So in hindsight, I actually think it was fun to
• 1:32:37
  Speaker 1: learn soldering and, like, how to, like, make circuits on
• 1:32:40
  Speaker 1: red boards and circuit boards. But if somebody was just
• 1:32:45
  Speaker 1: interested in some, you know, just writing code, let's say,
• 1:32:49
  Speaker 1: back then, all this is kind of like pointless to learn,
• 1:32:52
  Speaker 1: but you had to go through it to be qualified
• 1:32:55
  Speaker 1: as an engineer. So, and the reason the curriculum was
• 1:33:00
  Speaker 1: designed that way is because that's what the labor force
• 1:33:03
  Speaker 1: was required back then to build like oil factories and
• 1:33:06
  Speaker 1: like all these things. So you had to learn mechanical engineering,
• 1:33:09
  Speaker 1: you had to learn fluid mechanics, whatever. But I think
• 1:33:12
  Speaker 1: that should also change because if the way like you
• 1:33:16
  Speaker 1: do work changes, then what you're trained for in college
• 1:33:19
  Speaker 1: should also change. And it's much harder to change these things.
• 1:33:23
  Speaker 1: You know, people are much slower. They're scared to do changes.
• 1:33:26
  Speaker 1: Disruption is always, like, looked down upon. And so I
• 1:33:30
  Speaker 1: think let's at least start at the incentive structure, right
• 1:33:34
  Speaker 1: from the schools, right from the colleges. Like, let's not, like,
• 1:33:36
  Speaker 1: reward people based on, like, how much they know.
• 1:33:39
  Speaker 2: Well, it seems like in the future when things do
• 1:33:43
  Speaker 2: radically change and it seems like they're inevitable, they're going
• 1:33:45
  Speaker 2: to radically change. universities and schools are going to be
• 1:33:49
  Speaker 2: rewarded for having developed thinkers that are able to adapt
• 1:33:55
  Speaker 2: to this new world.
• 1:33:55
  Speaker 1: That's right.
• 1:33:56
  Speaker 2: Yeah. So they're going to have to figure out how
• 1:33:58
  Speaker 2: to adjust their curriculum.
• 1:34:00
  Speaker 3: Yeah.
• 1:34:01
  Speaker 2: Because the tools are so spectacular now that just this
• 1:34:05
  Speaker 2: idea of just memorizing information, that's not what you're going
• 1:34:10
  Speaker 2: to need to get by in the future.
• 1:34:12
  Speaker 1: It's not. And I guess like one proxy different schools
• 1:34:15
  Speaker 1: use is like maybe– if more entrepreneurs arise out of
• 1:34:18
  Speaker 1: your school, you probably, uh, create a lot of independent thinkers.
• 1:34:23
  Speaker 2: Mm-hmm.
• 1:34:24
  Speaker 1: Um, because they are, like, willing to take a first
• 1:34:26
  Speaker 1: perspective towards a problem.
• 1:34:28
  Speaker 3: Right.
• 1:34:28
  Speaker 1: And, and build their own thing from scratch. And, and fundamentally,
• 1:34:32
  Speaker 1: that's what America, America's always been about is, you know, some,
• 1:34:35
  Speaker 1: the American dream of coming here and, like, having your
• 1:34:39
  Speaker 1: own idea and still be taken seriously by a bunch
• 1:34:41
  Speaker 1: of people. The whole idea of venture capital only exists here. Like, kick,
• 1:34:46
  Speaker 1: family and friends around this whole idea of just having
• 1:34:49
  Speaker 1: your friends help you to bootstrap a business and then
• 1:34:51
  Speaker 1: turning it into a success and success doesn't mean like
• 1:34:54
  Speaker 1: multi-billion or 10 billion or whatever right like as long
• 1:34:57
  Speaker 1: as it pays you enough that you don't have to
• 1:34:58
  Speaker 1: work for somebody else and you can live a fulfilling
• 1:35:01
  Speaker 1: life and you can just go explore your passions that's
• 1:35:05
  Speaker 1: success that's actually a better success than creating company based
• 1:35:09
  Speaker 1: on what other people want you to do and then
• 1:35:12
  Speaker 1: hating your job for it.
• 1:35:13
  Speaker 2: Yeah. And having a yacht and being miserable and.
• 1:35:15
  Speaker 1: Working every day. That's why I said like, not the smartest,
• 1:35:20
  Speaker 1: the richest people are not always the ones who have
• 1:35:21
  Speaker 1: the most fulfilling lives. The most curious people have the
• 1:35:24
  Speaker 1: most fulfilling lives because they have better relationships. They're actually
• 1:35:28
  Speaker 1: able to sit and look at something and, you know,
• 1:35:30
  Speaker 1: be curious about it instead of like being worried about
• 1:35:32
  Speaker 1: what's going on.
• 1:35:34
  Speaker 2: Well, what did the American dream, what was it to
• 1:35:37
  Speaker 2: you when you weren't in America? Like, what is it like?
• 1:35:40
  Speaker 2: How is it discussed?
• 1:35:43
  Speaker 1: Well, to me, like, I always thought America is the
• 1:35:47
  Speaker 1: only country where you can come here and have an
• 1:35:51
  Speaker 1: idea and people listen to you and encourage you to
• 1:35:54
  Speaker 1: go pursue it. The risk-seeking culture is just incredible here.
• 1:36:00
  Speaker 1: Everybody else you can are, like, either explicitly or implicitly
• 1:36:04
  Speaker 1: are forced to defer to authority. Okay, like, go and
• 1:36:07
  Speaker 1: ask them. permission of this person go and ask permission
• 1:36:09
  Speaker 1: of that person or get their approval get their insight
• 1:36:12
  Speaker 1: or sure you can get there you can consult everybody
• 1:36:15
  Speaker 1: out there but if you have a thought that challenges
• 1:36:18
  Speaker 1: what they believe in this country still encourages you to
• 1:36:21
  Speaker 1: like go pursue it and so yes like when I
• 1:36:27
  Speaker 1: came here obviously you know Google was the number one
• 1:36:31
  Speaker 1: company that everybody wanted to work in but it's also
• 1:36:34
  Speaker 1: the same country where it allows you as a new
• 1:36:36
  Speaker 1: person to to start a new idea, the challenge is
• 1:36:40
  Speaker 1: one of the biggest companies in this own country. And
• 1:36:44
  Speaker 1: it actually wants it. People actually want new ideas. And
• 1:36:49
  Speaker 1: then you can consistently see that there are like always
• 1:36:52
  Speaker 1: going to be more and more new ideas and new
• 1:36:54
  Speaker 1: companies to be created here. And so that spirit of
• 1:36:58
  Speaker 1: like questioning is encouraged a lot here. And it happens
• 1:37:04
  Speaker 1: in academic research. I started off as an academic even there,
• 1:37:09
  Speaker 1: a lot of ideas when I had it and I
• 1:37:12
  Speaker 1: would share it with people, you know, people actually give
• 1:37:16
  Speaker 1: you very honest feedback about things, but they don't stop
• 1:37:19
  Speaker 1: you from working on anything. And that's fantastic because that's
• 1:37:25
  Speaker 1: very fresh. It's very liberating.
• 1:37:26
  Speaker 2: And that's not anywhere else.
• 1:37:30
  Speaker 1: I would say it's not.
• 1:37:30
  Speaker 2: It's not in India.
• 1:37:32
  Speaker 1: It's a simplification to say it's not anywhere else, but
• 1:37:36
  Speaker 1: It's not as encouraged. It's not as encouraged. The incentive
• 1:37:39
  Speaker 1: structures are not quite there. And the ability to be
• 1:37:44
  Speaker 1: taken seriously for some crazy ideas is why America is
• 1:37:48
  Speaker 1: still at the top.
• 1:37:50
  Speaker 2: But it's crazy to me that if the American dream
• 1:37:53
  Speaker 2: is so compelling and so many people come here for it,
• 1:37:55
  Speaker 2: why doesn't the rest of the world sort of adopt
• 1:37:57
  Speaker 2: those values? It's hard.
• 1:38:00
  Speaker 1: A lot of it is cultural. America was made from
• 1:38:11
  Speaker 1: a piece of land, essentially. And a lot of ideas
• 1:38:16
  Speaker 1: that we built here, a lot of industries that we
• 1:38:18
  Speaker 1: built here, were all created here from nothing. And that
• 1:38:23
  Speaker 1: required you to go take bold risks. I think Jeff
• 1:38:27
  Speaker 1: Bezos said this in some podcast. that where else would you, like,
• 1:38:32
  Speaker 1: be able to go raise, like, a few million dollars
• 1:38:35
  Speaker 1: for an idea that has, like, 5% to 10% chance
• 1:38:37
  Speaker 1: of working and then fail at it and still go
• 1:38:41
  Speaker 1: and raise another few million dollars for your next idea?
• 1:38:46
  Speaker 1: Nowhere else. People are willing to, like... People who get
• 1:38:49
  Speaker 1: rich here actually want to encourage and be part of
• 1:38:51
  Speaker 1: somebody else's crazy journey because it's hard to pursue all
• 1:38:56
  Speaker 1: crazy bets yourself. So it's an ecosystem. And once something
• 1:39:02
  Speaker 1: becomes an ecosystem, there's network effects. So it's very hard
• 1:39:05
  Speaker 1: to copy that elsewhere.
• 1:39:07
  Speaker 2: And so your value is measured in your curiosity and
• 1:39:11
  Speaker 2: you're willing to work. Your willingness to work on whatever
• 1:39:14
  Speaker 2: it is that is your pursuit.
• 1:39:16
  Speaker 1: Yes.
• 1:39:16
  Speaker 2: And then eventually adjusting and learning and catching fire with.
• 1:39:20
  Speaker 3: One of them.
• 1:39:21
  Speaker 2: Correct.
• 1:39:21
  Speaker 1: And you have to work hard. I'm a big believer
• 1:39:26
  Speaker 1: in intense hard work. I think nothing great can be
• 1:39:29
  Speaker 1: accomplished by being soft. And so all this recent push
• 1:39:34
  Speaker 1: for having a lot of work-life balance, this and that. Sure,
• 1:39:37
  Speaker 1: if you have work-life balance, if that's what you want,
• 1:39:40
  Speaker 1: then I think there are certain jobs that will give
• 1:39:42
  Speaker 1: you that, but when you're trying to do something from scratch,
• 1:39:45
  Speaker 1: when you're trying to create something from nothing, it's not
• 1:39:48
  Speaker 1: meant to be easy. There are some sacrifices that have
• 1:39:51
  Speaker 1: to be made and you're signing up to be part
• 1:39:53
  Speaker 1: of that experience, that surreal joy you get from doing
• 1:39:58
  Speaker 1: something that's felt almost impossible to achieve. And you're not doing,
• 1:40:03
  Speaker 1: you're not like staying up late or waking up early
• 1:40:06
  Speaker 1: because you're getting paid more. Maybe you might not get
• 1:40:09
  Speaker 1: paid anything. Maybe this whole thing goes to nothing, but
• 1:40:12
  Speaker 1: That experience you're getting of being part of something that
• 1:40:16
  Speaker 1: feels very hard to achieve is what you're signing up
• 1:40:19
  Speaker 1: for to be part of.
• 1:40:20
  Speaker 2: Yeah. And if you're not, find something else.
• 1:40:23
  Speaker 1: It's fine. Respect that. There's nothing wrong with that. Exactly.
• 1:40:25
  Speaker 1: And the country has enough jobs to provide for all
• 1:40:29
  Speaker 1: kinds of needs, right? And everybody goes through different phases
• 1:40:32
  Speaker 1: in their life. Sometimes they feel a little lazy or disillusioned.
• 1:40:36
  Speaker 1: And so what I like about this country is that
• 1:40:39
  Speaker 1: there's a lot of curious people here. There's a lot of, like,
• 1:40:42
  Speaker 1: so many different people, you know, like, whether they use
• 1:40:45
  Speaker 1: AIs or not AIs, they're all, like, finding meaning in, like,
• 1:40:48
  Speaker 1: so many interesting projects.
• 1:40:50
  Speaker 2: Well, obviously, I don't know any other country, really, because
• 1:40:53
  Speaker 2: I was born here. But the people that do talk
• 1:40:57
  Speaker 2: to me about what the American dream is like from
• 1:41:01
  Speaker 2: another country, they're the most passionate and the most supportive
• 1:41:04
  Speaker 2: of this idea, this experiment in self-government. And this, this, the...
• 1:41:10
  Speaker 2: Just the whole idea that the country operates on that
• 1:41:14
  Speaker 2: anybody can chase their dream.
• 1:41:16
  Speaker 1: Yeah.
• 1:41:16
  Speaker 2: You can. If you have a dream and you're willing
• 1:41:18
  Speaker 2: to work hard, you could actually do it in this country.
• 1:41:20
  Speaker 1: That's right.
• 1:41:21
  Speaker 2: Yeah. That's, you know, it's most, the people that are
• 1:41:25
  Speaker 2: most passionate about that idea oftentimes are people that come
• 1:41:28
  Speaker 2: from somewhere else where that wasn't available.
• 1:41:30
  Speaker 1: And it's not just like, you know, people coming from
• 1:41:33
  Speaker 1: one particular country or another. It's the attitudes. It's the
• 1:41:38
  Speaker 1: way the system works and rewards you to, like, be
• 1:41:40
  Speaker 1: bold and take bets against established players. It's okay, right?
• 1:41:44
  Speaker 1: It's okay to, like, be an upstart, a challenger. And
• 1:41:47
  Speaker 1: people love that, like, underdog. And I think, you know,
• 1:41:50
  Speaker 1: that's fantastic. And that culture is continuing. Yes, there are, like,
• 1:41:54
  Speaker 1: multi-trillion dollar companies here, and they're all going to become
• 1:41:56
  Speaker 1: even bigger. But people still want the young, hungry person
• 1:42:03
  Speaker 1: to also be successful.
• 1:42:04
  Speaker 2: Yeah. Well, they love disruptors.
• 1:42:07
  Speaker 3: Yeah.
• 1:42:07
  Speaker 2: And people love underdogs in this country.
• 1:42:10
  Speaker 3: Yeah.
• 1:42:12
  Speaker 1: It's universal. It's not specific to technology.
• 1:42:15
  Speaker 2: Right.
• 1:42:15
  Speaker 1: Like, I'm sure everybody would love an underdog story that
• 1:42:18
  Speaker 1: wants to go against, like, Coca-Cola or Pepsi or something, too.
• 1:42:21
  Speaker 2: Sure. Oh, in sports, it's our favorite thing. In sports, yeah.
• 1:42:24
  Speaker 2: We don't like when the guy who's supposed to win wins.
• 1:42:26
  Speaker 2: We love when the guy who's not supposed to win triumphs.
• 1:42:29
  Speaker 3: Yeah.
• 1:42:29
  Speaker 2: Yeah.
• 1:42:30
  Speaker 1: The underdog story.
• 1:42:31
  Speaker 2: Yeah. That's a very uniquely American story.
• 1:42:35
  Speaker 1: To me, that's what this country is. I mean, sure,
• 1:42:39
  Speaker 1: there's a lot of obstacles and challenges. Just like every
• 1:42:42
  Speaker 1: other country, there are things here that are challenging, but
• 1:42:45
  Speaker 1: it's one thing that has consistently stayed true.
• 1:42:50
  Speaker 2: One of the big fears that people in America have
• 1:42:53
  Speaker 2: about technology in particular is that without being aware that
• 1:42:58
  Speaker 2: this was going to take place, everybody gave up their
• 1:43:01
  Speaker 2: data and Everybody gave up their data and didn't recognize
• 1:43:04
  Speaker 2: it was a commodity that in turn made these corporations
• 1:43:08
  Speaker 2: immensely wealthy and powerful. And then they have the ability
• 1:43:12
  Speaker 2: to shape narratives. And that concerns people because using their
• 1:43:19
  Speaker 2: ideological position as leverage to try to push that through
• 1:43:25
  Speaker 2: technology that has immense control and influence over people and
• 1:43:30
  Speaker 2: that We didn't see technology and corporations as having that
• 1:43:34
  Speaker 2: much control over how society views itself and how we
• 1:43:39
  Speaker 2: interact with each other. And there's a real concern that
• 1:43:43
  Speaker 2: these companies got so big. There's a guy named Robert
• 1:43:48
  Speaker 2: Epstein who's done a lot of work on curated search
• 1:43:53
  Speaker 2: engine results and how much that can affect. Have you
• 1:43:56
  Speaker 2: seen any of his stuff?
• 1:43:57
  Speaker 1: I think I've seen this, yeah.
• 1:43:58
  Speaker 2: How much that can affect elections, how much that can
• 1:44:01
  Speaker 2: affect people's perceptions on any societal issue that's coming up.
• 1:44:07
  Speaker 2: And it's concerning. It really is because they do curate
• 1:44:10
  Speaker 2: search results. It's not simply, you know, you just run
• 1:44:13
  Speaker 2: it out there and you get this is the data. No,
• 1:44:16
  Speaker 2: you know, if you look for specific political figures, depending
• 1:44:19
  Speaker 2: upon where they fall in the right or left spectrum
• 1:44:22
  Speaker 2: and depending upon which way the company forms, the corporation forms.
• 1:44:27
  Speaker 2: falls rather, you'll get different results. And that sucks. You know, that's,
• 1:44:32
  Speaker 2: it's very concerning that people don't recognize, they don't, they
• 1:44:37
  Speaker 2: don't have the ability to see how that is dangerous
• 1:44:41
  Speaker 2: for all of society to have that kind of power
• 1:44:44
  Speaker 2: and wield it in that way where you're not being
• 1:44:46
  Speaker 2: honest about accurate objective information. You're pushing particular ideologies.
• 1:44:51
  Speaker 3: Yeah.
• 1:44:52
  Speaker 1: So I think it's kind of like, uh, This is
• 1:44:58
  Speaker 1: almost an effect of the asymmetry that exists between the
• 1:45:01
  Speaker 1: amount of AI power that centralized systems and centralized companies
• 1:45:04
  Speaker 1: have and the amount of AI power you as a
• 1:45:07
  Speaker 1: sovereign individual has. So when you don't have the AIs
• 1:45:12
  Speaker 1: to just go judge for yourself what you should be
• 1:45:15
  Speaker 1: reading in Fed, you're obviously under the influence of whatever
• 1:45:21
  Speaker 1: big tech company is controlling the information flow. But when
• 1:45:24
  Speaker 1: you have access to all those AIs, you can actually
• 1:45:27
  Speaker 1: just customize what you want to see by telling the AI, like, hey,
• 1:45:31
  Speaker 1: this is what I think you should actually question and
• 1:45:34
  Speaker 1: tell me. Until now, you never had that power for yourself.
• 1:45:38
  Speaker 1: You're finally getting it. And eventually, we'll be able to
• 1:45:42
  Speaker 1: have our own LLMs, like our own models that we
• 1:45:45
  Speaker 1: would be able to post in our own hardware. We
• 1:45:48
  Speaker 1: don't have to rely on one centralized model given to
• 1:45:51
  Speaker 1: us by any specific model company. And using that, you
• 1:45:58
  Speaker 1: can shape it to your beliefs, your custom data. So
• 1:46:04
  Speaker 1: when you're consuming a search result, you can actually task
• 1:46:07
  Speaker 1: that AI that you control and you run so nobody
• 1:46:10
  Speaker 1: can shut off access to it to tell you, hey,
• 1:46:13
  Speaker 1: can you actually give me a contrarian perspective on this?
• 1:46:17
  Speaker 1: Or can you tell me if these search results are
• 1:46:19
  Speaker 1: actually biased? So I think we need to give individuals
• 1:46:24
  Speaker 1: more sovereignty with more access to their own AIs that
• 1:46:27
  Speaker 1: they own and run on a piece of hardware they
• 1:46:29
  Speaker 1: own themselves. And this is going to be leading to
• 1:46:34
  Speaker 1: the whole rise of local AIs. So as AI models,
• 1:46:37
  Speaker 1: like today, they're very power inefficient. They're running on large
• 1:46:39
  Speaker 1: data centers. But in a year or two from now,
• 1:46:42
  Speaker 1: whatever capability that exists in the most power-hungry data centers,
• 1:46:46
  Speaker 1: it'll be possible to run it in some box that
• 1:46:49
  Speaker 1: you own.
• 1:46:50
  Speaker 2: Really?
• 1:46:50
  Speaker 3: Yeah.
• 1:46:51
  Speaker 1: It's already happening. It's already happening that there are interesting
• 1:46:55
  Speaker 1: hardware projects like the Apple Mac Mini, NVIDIA DGX, where
• 1:47:01
  Speaker 1: you can actually host a reasonable-sized model and put it
• 1:47:06
  Speaker 1: in a box and have it run, and you don't
• 1:47:09
  Speaker 1: have to pay for all the tokens it produces you.
• 1:47:12
  Speaker 1: You just have to plug it into your power cord,
• 1:47:15
  Speaker 1: and it works.
• 1:47:17
  Speaker 2: I know Duncan, my friend Duncan Trussell, he does that. Yeah.
• 1:47:20
  Speaker 1: And today the capability of that model that can run
• 1:47:23
  Speaker 1: locally is not quite there. So you would still prefer
• 1:47:26
  Speaker 1: to use something that runs from the data center. But
• 1:47:29
  Speaker 1: eventually this is going to be a spectrum. There's going
• 1:47:31
  Speaker 1: to be some percentage of tasks that you would start
• 1:47:33
  Speaker 1: delegating to this local system. It'll be a hybrid model.
• 1:47:37
  Speaker 1: And over time it could end up being the case
• 1:47:39
  Speaker 1: that you could buy something that feels like a refrigerator
• 1:47:41
  Speaker 1: for your home, which is your own AI box, and
• 1:47:46
  Speaker 1: host a model that you control. So nobody can arbitrarily
• 1:47:49
  Speaker 1: shut off access to it. one day, and then you
• 1:47:53
  Speaker 1: can have that be your weapon against what the big
• 1:47:56
  Speaker 1: tech wants you to be fed or believe in. This
• 1:47:59
  Speaker 1: is the only way we can fight this because they
• 1:48:01
  Speaker 1: have far more computing power, far more data, far more
• 1:48:05
  Speaker 1: algorithms than you. So the only way you can fight
• 1:48:08
  Speaker 1: that is you have something you own yourself. And with
• 1:48:12
  Speaker 1: the rise of open source models, open source LLMs, and
• 1:48:18
  Speaker 1: progress in local hardware, and both Apple and NVIDIA and Intel,
• 1:48:21
  Speaker 1: they're all doing amazing work here. You could potentially change
• 1:48:25
  Speaker 1: the future and give people more power. And this may
• 1:48:27
  Speaker 1: not be as expensive as people think.
• 1:48:29
  Speaker 2: Well, that's a good solution. Because I've always wondered, are
• 1:48:34
  Speaker 2: these searches using Google, is that going to be irrelevant
• 1:48:38
  Speaker 2: one day? Because You already can just ask your phone.
• 1:48:43
  Speaker 2: Most of the time, if I want to have an
• 1:48:44
  Speaker 2: answer for something, I just ask Perplexity. I was like,
• 1:48:46
  Speaker 2: what is it? Instead of having to sift through all
• 1:48:50
  Speaker 2: these Google searches and try to figure out what it's
• 1:48:52
  Speaker 2: showing me first and get to page three where it's
• 1:48:55
  Speaker 2: what I really want to know, I can get the
• 1:48:57
  Speaker 2: accurate information, then follow-up questions are instantaneous.
• 1:49:00
  Speaker 1: Yeah, and even the models that are running the Perplexity
• 1:49:03
  Speaker 1: app today, they're all in the cloud. Eventually, you'll be
• 1:49:07
  Speaker 1: able to do that on a box that you own.
• 1:49:11
  Speaker 1: You can still use the front end, the UI of
• 1:49:14
  Speaker 1: the app, but you can control the compute that runs
• 1:49:18
  Speaker 1: on a piece of hardware. You may ask, why do
• 1:49:21
  Speaker 1: I care? Okay, like, what if someday, like, the data
• 1:49:24
  Speaker 1: center gets taken off? Like, Iran was bombing data centers.
• 1:49:28
  Speaker 2: Right.
• 1:49:29
  Speaker 1: Like, what if someday, like, the government decides that model
• 1:49:32
  Speaker 1: is no longer available? You want some control over, like,
• 1:49:36
  Speaker 1: what models you can run and, like, You may even
• 1:49:39
  Speaker 1: want to shape it to your context that you never
• 1:49:42
  Speaker 1: want to be living on any data center. And I
• 1:49:47
  Speaker 1: think that's where I believe the individual gets more sovereignty
• 1:49:51
  Speaker 1: against big tech. And that's how we fight surveillance or
• 1:49:56
  Speaker 1: centralization of power.
• 1:49:58
  Speaker 2: Yeah, and certainly pushing narratives. What do you think happens
• 1:50:03
  Speaker 2: with social media? Yeah. Because social media and as you
• 1:50:07
  Speaker 2: were talking about before, like algorithms, like it's one of
• 1:50:09
  Speaker 2: the biggest problems in terms of the way people view
• 1:50:11
  Speaker 2: the world. Yeah.
• 1:50:12
  Speaker 1: I'm curious what you think, like, you know, like my
• 1:50:16
  Speaker 1: opinion is that it's not good for the kids.
• 1:50:18
  Speaker 2: It's terrible for them. Yeah. But I think they should
• 1:50:21
  Speaker 2: have some exposure to it because I think it's good
• 1:50:24
  Speaker 2: to know that it's a thing. And I think children
• 1:50:27
  Speaker 2: are fairly resilient and they learn. But the anxiety levels
• 1:50:30
  Speaker 2: of kids is much higher than ever before.
• 1:50:32
  Speaker 3: Yeah.
• 1:50:33
  Speaker 2: Suicidal ideation is higher.
• 1:50:35
  Speaker 1: Self-harm. Yeah.
• 1:50:38
  Speaker 2: Yeah.
• 1:50:38
  Speaker 1: My belief is that when you're just fed a feed
• 1:50:44
  Speaker 1: and the algorithm of the social media company decides what
• 1:50:47
  Speaker 1: you're going to see next, it curbs your curiosity. And
• 1:50:52
  Speaker 1: I don't think things that curb human curiosity should be encouraged.
• 1:50:58
  Speaker 2: Yeah, I agree.
• 1:50:59
  Speaker 1: And so if the app is designed in a way
• 1:51:01
  Speaker 1: where it asks you what you're interested in And helps
• 1:51:04
  Speaker 1: you to come up and find things that are very
• 1:51:08
  Speaker 1: related to what you're interested in.
• 1:51:10
  Speaker 2: Right.
• 1:51:10
  Speaker 1: That's awesome. But that's not how it works. It's literally
• 1:51:13
  Speaker 1: like it starts with something. You start doing scrolling and
• 1:51:16
  Speaker 1: then start showing you what you just scrolled. And then
• 1:51:19
  Speaker 1: you end up in an echo chamber. And that's not
• 1:51:22
  Speaker 1: necessarily good.
• 1:51:23
  Speaker 2: Well, you can get trapped. Yeah. I'm in a trap
• 1:51:26
  Speaker 2: of schizophrenics lately on Instagram. Yeah. Well, it's just mostly schizophrenics,
• 1:51:31
  Speaker 2: like people that tell them they're the rightful president of
• 1:51:33
  Speaker 2: the United States and, like, you tell the guy hasn't
• 1:51:35
  Speaker 2: showered in days. And, you know, if you have a phone,
• 1:51:39
  Speaker 2: you can create an account and you just start uploading nonsense.
• 1:51:42
  Speaker 2: And then for whatever reason, I've watched a couple of them,
• 1:51:45
  Speaker 2: so now they just keep showing them to me.
• 1:51:46
  Speaker 1: And it's full of AI slop right now, like a
• 1:51:48
  Speaker 1: lot of AI slop. Like, it's not even clear. And
• 1:51:52
  Speaker 1: it's not labeled also clearly whether it's being made with
• 1:51:54
  Speaker 1: AI or not. So often... So essentially it's leading to
• 1:51:58
  Speaker 1: a complete loss in, in, in trust where when I
• 1:52:01
  Speaker 1: see something, I don't even know if it's real anymore.
• 1:52:04
  Speaker 2: Right. And it's going to get worse. Yeah.
• 1:52:05
  Speaker 1: It's going to get worse to the extent that you're
• 1:52:07
  Speaker 1: going to like, your default would be that this is AI.
• 1:52:11
  Speaker 1: And then like, you're going to have to go through
• 1:52:14
  Speaker 1: multiple layers to finally verify if it was real. Um, and, um,
• 1:52:21
  Speaker 1: And even verified accounts post a lot of AI stuff,
• 1:52:23
  Speaker 1: so it's not about whether the account is verified by
• 1:52:26
  Speaker 1: meta or whatever. So I think fundamentally, I feel like, okay,
• 1:52:34
  Speaker 1: the way I think about it is, what are pieces
• 1:52:36
  Speaker 1: of technology if did not exist would be a really
• 1:52:41
  Speaker 1: bad thing for the world? And what are pieces of
• 1:52:42
  Speaker 1: technology if did not exist wouldn't even matter? And I
• 1:52:47
  Speaker 1: feel like social media is more towards the secondary.
• 1:52:50
  Speaker 2: Yeah.
• 1:52:51
  Speaker 1: Like, you know, searching for information and answering questions and, like, getting,
• 1:52:57
  Speaker 1: you know, AIs to, like, do things for you, help
• 1:53:01
  Speaker 1: you learn new things faster. All that stuff is some,
• 1:53:03
  Speaker 1: we need more of that. But because it supercharges our curiosity. Whereas, like,
• 1:53:09
  Speaker 1: brain rot feeds with AI slop doesn't actually supercharge our curiosity.
• 1:53:14
  Speaker 1: It actually curbs our curiosity. And so if we believe that,
• 1:53:18
  Speaker 1: if you believe in the curiosity premium idea, We need
• 1:53:21
  Speaker 1: to encourage things that supercharge our curiosity and discourage things
• 1:53:25
  Speaker 1: that curb our curiosity.
• 1:53:27
  Speaker 2: Do you anticipate a time where we recognize the dangers
• 1:53:32
  Speaker 2: of algorithms and there is some discussion to either curb
• 1:53:36
  Speaker 2: them or allow people to have control over them in
• 1:53:40
  Speaker 2: a real meaningful way? Like you could dictate maybe through
• 1:53:44
  Speaker 2: AI even that there's an AI interface to your algorithm.
• 1:53:47
  Speaker 2: That understands your particular emotional needs, your curiosity. Like, only
• 1:53:51
  Speaker 2: show me this.
• 1:53:52
  Speaker 3: Yeah.
• 1:53:52
  Speaker 2: This is what I'm interested in. Carpentry and basketball games. Yeah.
• 1:53:55
  Speaker 2: Show me those things.
• 1:53:56
  Speaker 3: Yeah.
• 1:53:56
  Speaker 2: I don't want to see who's getting divorced. I don't
• 1:53:59
  Speaker 2: give a fuck about this.
• 1:54:01
  Speaker 1: Yeah. So, here's the thing. You can still customize on
• 1:54:05
  Speaker 1: most of the social apps. You know, it'll be deeply
• 1:54:09
  Speaker 1: buried somewhere in the settings somewhere. And you can go
• 1:54:12
  Speaker 1: and say stuff. But the reason it's buried is because
• 1:54:15
  Speaker 1: once you... You always have to say it or like
• 1:54:18
  Speaker 1: it's the starting entry point for your experience there. Your
• 1:54:21
  Speaker 1: engagement time would go down because once you consume the
• 1:54:23
  Speaker 1: content that you really want, you would go back to
• 1:54:26
  Speaker 1: your work, which is what you really need to be doing.
• 1:54:28
  Speaker 1: But that doesn't help them sell more ads. And so
• 1:54:32
  Speaker 1: the incentives are not aligned. And so Elon has this
• 1:54:36
  Speaker 1: really good metric he talks about where it's like a
• 1:54:40
  Speaker 1: total amount of unregretted minutes spent on the app should
• 1:54:43
  Speaker 1: go up. it's hard to measure it's hard to measure
• 1:54:48
  Speaker 1: it's more like in spirit the right metric but this
• 1:54:52
  Speaker 1: metric is also why it's hard to make money on
• 1:54:55
  Speaker 1: ads if you care about this metric which is why
• 1:54:57
  Speaker 1: X doesn't really make a lot of money on ads
• 1:54:58
  Speaker 1: compared to you know Instagram or YouTube because you're kind
• 1:55:04
  Speaker 1: of like optimizing for interestingness like doesn't mean X has
• 1:55:09
  Speaker 1: everything right there's a lot of chaos there's a lot
• 1:55:10
  Speaker 1: of memes there's a lot of like weird shit going
• 1:55:13
  Speaker 1: on there as well But in general, social media is
• 1:55:17
  Speaker 1: not necessarily great for people.
• 1:55:20
  Speaker 2: I think it's terrible for people. But it also provides
• 1:55:23
  Speaker 2: you with a way better understanding of what's going on
• 1:55:27
  Speaker 2: in the world than has ever existed before.
• 1:55:30
  Speaker 1: X particularly.
• 1:55:31
  Speaker 2: X particularly.
• 1:55:32
  Speaker 1: Because it's a place for discourse. It's a text-based app
• 1:55:37
  Speaker 1: more than a video-based app.
• 1:55:39
  Speaker 2: Right.
• 1:55:40
  Speaker 1: So naturally, people tend to engage in discussions and debates
• 1:55:44
  Speaker 1: and There's a lot of curious debates going on there
• 1:55:47
  Speaker 1: and a lot of interesting viewpoints expressed by people. So
• 1:55:50
  Speaker 1: I think in terms of the unregarded minutes, it's actually
• 1:55:53
  Speaker 1: one of the better social media apps. But apps that
• 1:55:56
  Speaker 1: are purely based on video or images, and largely video
• 1:56:03
  Speaker 1: these days, I think that's just trying to get your
• 1:56:06
  Speaker 1: eyeballs in time.
• 1:56:07
  Speaker 2: Yeah, those are the mind numbers. Yeah. They just numb
• 1:56:10
  Speaker 2: your mind.
• 1:56:10
  Speaker 1: I mean, it's depressing when you go to a metro
• 1:56:12
  Speaker 1: and you just see people just scrolling through their feed.
• 1:56:15
  Speaker 3: Nobody.
• 1:56:16
  Speaker 2: Everybody doing it. You look at the entire car. Everyone's
• 1:56:19
  Speaker 2: doing it.
• 1:56:19
  Speaker 1: It's just insane.
• 1:56:20
  Speaker 2: Yeah. It's weird.
• 1:56:21
  Speaker 3: Yeah.
• 1:56:22
  Speaker 2: I always say that if there was a drug that
• 1:56:23
  Speaker 2: existed that made people stare at their hand for six
• 1:56:25
  Speaker 2: hours a day, everybody would be like, get that out
• 1:56:27
  Speaker 2: of here. Yeah. But that's essentially what we're doing.
• 1:56:30
  Speaker 3: Yeah.
• 1:56:30
  Speaker 2: Because like most of what people are looking at most
• 1:56:32
  Speaker 2: of the time, they don't even remember.
• 1:56:34
  Speaker 3: Yeah.
• 1:56:35
  Speaker 2: They're just scrolling through this thing.
• 1:56:36
  Speaker 1: It's brain rot. It's just brain rot. It curbs your curiosity. Yeah.
• 1:56:39
  Speaker 1: I mean, Apple has these settings in different apps. Have
• 1:56:42
  Speaker 1: you tried this?
• 1:56:43
  Speaker 3: What?
• 1:56:43
  Speaker 1: You can set the. Timer for every app?
• 1:56:46
  Speaker 2: No, I just use discipline. I don't engage very much anymore.
• 1:56:51
  Speaker 2: I dip my toe into X every day for a
• 1:56:56
  Speaker 2: few seconds. I go, what's everybody mad at? What's going on?
• 1:56:59
  Speaker 2: Who stole this? How much corruption is here? Who got
• 1:57:03
  Speaker 2: killed there? Okay, bye. And then I just check out.
• 1:57:07
  Speaker 2: I don't want to do it. And Instagram to me
• 1:57:11
  Speaker 2: is just nonsense. I just look at that every now
• 1:57:14
  Speaker 2: and then for nonsense and occasionally something interesting. Really YouTube
• 1:57:18
  Speaker 2: is my main go-to thing. Yeah. Because YouTube is my
• 1:57:21
  Speaker 2: most unregretted minutes.
• 1:57:22
  Speaker 3: Yeah.
• 1:57:22
  Speaker 2: YouTube for me is always interesting. There's always like some
• 1:57:26
  Speaker 2: cool thing on cosmology. There's some– I watch fights on YouTube.
• 1:57:32
  Speaker 2: I watch professional pool matches. That's what I do for
• 1:57:35
  Speaker 2: the most part. Yeah. That's where I really like find
• 1:57:38
  Speaker 2: my actual interests and fulfill my curiosity.
• 1:57:41
  Speaker 1: Long form content is what human mind should be trained
• 1:57:45
  Speaker 1: to consume more of. Whether it's books, whether it's like,
• 1:57:48
  Speaker 1: you know, 30 minute videos explaining something. And you need
• 1:57:53
  Speaker 1: to train your mind to actually complete it. That's actually
• 1:57:56
  Speaker 1: the biggest problem with the younger generation. The more they're
• 1:57:58
  Speaker 1: in the reels experience, short form video, they're unable to
• 1:58:03
  Speaker 1: actually like complete like long videos anymore.
• 1:58:06
  Speaker 2: That's true, but also at the same time, the rise
• 1:58:09
  Speaker 2: of podcasting.
• 1:58:10
  Speaker 1: Is happening yeah and it's great it's great.
• 1:58:13
  Speaker 2: So there's it's not it's not universal it's like there's
• 1:58:16
  Speaker 2: a lot of people that don't find fulfillment in all
• 1:58:18
  Speaker 2: the doom scrolling and all the nonsense yeah they really
• 1:58:20
  Speaker 2: do want.
• 1:58:21
  Speaker 1: Yeah i'm particularly just focused on the younger generation i'm
• 1:58:25
  Speaker 1: sure like people like us can adapt to like Okay,
• 1:58:28
  Speaker 1: let's say maybe you have a temporary addiction to social apps.
• 1:58:31
  Speaker 2: But a lot of the young people are the people that, like,
• 1:58:33
  Speaker 2: I meet kids, like, at the mall that are 11
• 1:58:36
  Speaker 2: that listen to my podcast.
• 1:58:37
  Speaker 3: Really?
• 1:58:37
  Speaker 2: Yeah.
• 1:58:38
  Speaker 3: Wow. I know.
• 1:58:39
  Speaker 2: It's nuts. They go, I love your podcast. I'm like,
• 1:58:42
  Speaker 2: who lets you listen? Get out of here. No, I'm
• 1:58:46
  Speaker 2: always joking around about it. That's amazing. That's really cool. But, no,
• 1:58:49
  Speaker 2: there's a lot of, like, particularly, like, young boys that
• 1:58:52
  Speaker 2: come up to me all the time that are interested
• 1:58:53
  Speaker 2: in it.
• 1:58:54
  Speaker 1: That's amazing.
• 1:58:55
  Speaker 2: I love it. I love it because then they're going
• 1:58:57
  Speaker 2: to get exposed to some interesting ideas and it'll also
• 1:59:00
  Speaker 2: encourage them to have those kind of conversations with each other.
• 1:59:03
  Speaker 3: Right.
• 1:59:04
  Speaker 2: Yeah.
• 1:59:05
  Speaker 1: Whose podcast do you listen to?
• 1:59:08
  Speaker 2: I love Tim Dillon's. He's probably my favorite because it's
• 1:59:11
  Speaker 2: the most accurate and also satirical and hilarious view on
• 1:59:17
  Speaker 2: everything that's going on in the world in terms of
• 1:59:20
  Speaker 2: like war and world news and culture shit. And he's
• 1:59:25
  Speaker 2: my favorite. He was just on here yesterday. I fucking
• 1:59:28
  Speaker 2: love that guy to death. He's so funny. He's so crazy.
• 1:59:31
  Speaker 2: It's like his mind works in such a unique way
• 1:59:35
  Speaker 2: and it's developed because his podcast is different where he
• 1:59:38
  Speaker 2: very rarely has guests. So most of the time it's
• 1:59:41
  Speaker 2: just him ranting and his producer laughing. And he's the
• 1:59:44
  Speaker 2: best ranter that's ever lived. I don't think there's anybody
• 1:59:46
  Speaker 2: that's even close. He's the goat. Like There's like, I
• 1:59:50
  Speaker 2: don't think there's any argument. Every comedian agrees. Like as
• 1:59:53
  Speaker 2: far as like just the ability to just sit in
• 1:59:55
  Speaker 2: front of a microphone and rant, like Bill Burr does
• 1:59:58
  Speaker 2: it well. He's good at it. There's a few other
• 1:59:59
  Speaker 2: guys that are good at it. No one's as good
• 2:00:02
  Speaker 2: as Tim. He's the most consistently entertaining. And then for
• 2:00:06
  Speaker 2: just mind, not mindless, but like to escape, I listened
• 2:00:10
  Speaker 2: to a lot of archery shows and hunting shows where
• 2:00:13
  Speaker 2: they're talking about different tactics and hunting or different techniques
• 2:00:18
  Speaker 2: and archery new equipment and new innovations archery is an
• 2:00:23
  Speaker 2: interesting thing because every year bow manufacturers make a better
• 2:00:27
  Speaker 2: bow and like tiny little engineering changes of these bows
• 2:00:34
  Speaker 2: like it's a weapon that's been around for who knows
• 2:00:38
  Speaker 2: how many thousands of years but.
• 2:00:40
  Speaker 1: What the And you're able to feel those improvements.
• 2:00:42
  Speaker 2: Oh, yeah. You feel the difference. Every year Hoyt puts
• 2:00:45
  Speaker 2: out a new bow, and every year I'm like, motherfucker,
• 2:00:48
  Speaker 2: they did it again. It's better. So just tiny changes,
• 2:00:52
  Speaker 2: less vibrations in the hand, more balance in the shot,
• 2:00:56
  Speaker 2: more forgiving in terms of accuracy. I love that stuff.
• 2:01:01
  Speaker 2: So I get really fascinated by engineering, really fascinated by
• 2:01:04
  Speaker 2: automotive engineering. I'm really interested in like that's another thing
• 2:01:08
  Speaker 2: where like every year, People figure out how to make
• 2:01:11
  Speaker 2: a car that can hold more Gs on a skid pad,
• 2:01:15
  Speaker 2: that can get around a track quicker. Like every year
• 2:01:17
  Speaker 2: they're battling to see who can get around the Nürburgring quicker.
• 2:01:20
  Speaker 2: And what are they doing? They're adding horsepower, increasing suspension
• 2:01:24
  Speaker 2: travel and suspension tuning, rather, and making them more compliant
• 2:01:28
  Speaker 2: or making them stiffer and And making them more adjustable
• 2:01:32
  Speaker 2: and then like tire compounds. And I'm just interested in
• 2:01:37
  Speaker 2: anything that where someone's working on something and getting better
• 2:01:41
  Speaker 2: at something or getting new information. I love history podcasts.
• 2:01:45
  Speaker 2: I listen to a bunch of history podcasts. So that's
• 2:01:48
  Speaker 2: most of the time. If I'm listening to something, I
• 2:01:51
  Speaker 2: either want to be entertained or I want to be educated.
• 2:01:53
  Speaker 1: Educational. Yeah.
• 2:01:56
  Speaker 2: And that's entertaining.
• 2:01:57
  Speaker 3: Yeah.
• 2:01:58
  Speaker 2: What about you? What kind of stuff do you listen to?
• 2:01:59
  Speaker 1: I mean, I listen to your stuff. I listen to Lex.
• 2:02:02
  Speaker 1: There's this guy, I mean, you know, you might, you
• 2:02:05
  Speaker 1: had him on, like, Rick Rubin, of course.
• 2:02:06
  Speaker 3: Sure.
• 2:02:07
  Speaker 1: Yeah, yeah.
• 2:02:07
  Speaker 2: Love that guy.
• 2:02:08
  Speaker 1: Yeah, yeah. He's awesome. I listen to his stuff. And,
• 2:02:14
  Speaker 1: I mean, I also watch, like, some interesting videos about,
• 2:02:17
  Speaker 1: you know, stuff, concepts I don't understand. There is this
• 2:02:20
  Speaker 1: YouTube channel, Veritasium. You should check it out.
• 2:02:24
  Speaker 2: What is it called?
• 2:02:24
  Speaker 1: Veritasium.
• 2:02:26
  Speaker 2: How do you spell that?
• 2:02:27
  Speaker 1: V-E- R-I-T-A-S-E-U-M. Veritasium.
• 2:02:33
  Speaker 2: What does it mean? Is that someone's name?
• 2:02:36
  Speaker 1: No, Veritas just means like seeking truth kind of thing.
• 2:02:39
  Speaker 2: Oh, okay.
• 2:02:40
  Speaker 3: Is it this channel?
• 2:02:41
  Speaker 1: Yeah, yeah, yeah.
• 2:02:45
  Speaker 2: Ooh, okay. 20.9 million subscribers. Obviously, a lot of people agree.
• 2:02:49
  Speaker 1: So, they make all these very interesting videos about stuff
• 2:02:53
  Speaker 1: that you would be curious about, but you never actually
• 2:02:56
  Speaker 1: bother to ask that or learn more about and, um,
• 2:03:00
  Speaker 1: explain some of the most under understood companies, uh, or
• 2:03:05
  Speaker 1: like phenomena. And, um, I just love watching it. You know, I'm, I'm,
• 2:03:10
  Speaker 1: this is kind of like my idea of doom scrolling.
• 2:03:12
  Speaker 1: Like I like, I like watching like 20 videos at once.
• 2:03:15
  Speaker 3: Yeah.
• 2:03:15
  Speaker 2: I am going to subscribe to it right now.
• 2:03:17
  Speaker 1: It's pretty cool.
• 2:03:20
  Speaker 2: Veritasium.
• 2:03:23
  Speaker 1: There it is.
• 2:03:24
  Speaker 2: Got it. Subscribed. Bam.
• 2:03:27
  Speaker 1: And it explains all these, like, fun concepts that are,
• 2:03:31
  Speaker 1: you know, you take it for granted. Like, okay, why
• 2:03:34
  Speaker 1: is Google Maps really fast? Like, okay, it'll tell you
• 2:03:37
  Speaker 1: what's going on, how the data is used across so
• 2:03:39
  Speaker 1: many different people at once and all these different things.
• 2:03:42
  Speaker 2: CIA's new tech doesn't make sense. Exactly. We were just
• 2:03:46
  Speaker 2: talking about that yesterday. We were doubting it. You know
• 2:03:49
  Speaker 2: the heart murmur thing? Do you know about that? No.
• 2:03:52
  Speaker 2: So the pilots that were downed in Iran... They said
• 2:03:56
  Speaker 2: that they have this technology that allows them, I think
• 2:04:00
  Speaker 2: they could use it up to 70 miles and they
• 2:04:03
  Speaker 2: can detect a very unique heart rate. Like your heart
• 2:04:07
  Speaker 2: rate is different than my heart rate. They could know
• 2:04:09
  Speaker 2: it's you. You could be hiding in the mountains and
• 2:04:11
  Speaker 2: they could find you from 70 miles away with this technology. Wow.
• 2:04:15
  Speaker 1: A lot of people are like beams or waves or something.
• 2:04:18
  Speaker 2: Well, it's called, what is it called? Quantum magnetometry. Is
• 2:04:21
  Speaker 2: that what they call it? I think that's what it was.
• 2:04:25
  Speaker 2: Remember we looked it up yesterday? They're using the word
• 2:04:28
  Speaker 2: quantum and not explaining what they're doing, like how they're
• 2:04:31
  Speaker 2: doing it. And you're like, okay, is that real? Or
• 2:04:36
  Speaker 2: is this some invented horseshit to cover the fact that
• 2:04:39
  Speaker 2: they have some very sophisticated satellite imagery where they can
• 2:04:43
  Speaker 2: have a detailed map of literally the entire surface of
• 2:04:46
  Speaker 2: the world? They know exactly where people are, but they
• 2:04:48
  Speaker 2: don't want our enemies to know that they have this capability.
• 2:04:51
  Speaker 2: So they're making up something.
• 2:04:53
  Speaker 1: I see.
• 2:04:53
  Speaker 2: That was my suggestion yesterday. That like maybe they're full
• 2:04:57
  Speaker 2: of shit. Because the whole thing seems nuts. What is
• 2:04:59
  Speaker 2: it called? You got it. It's quantum magnetometry. Sure. What
• 2:05:03
  Speaker 2: does that mean? You tell me. I don't know. Exactly.
• 2:05:06
  Speaker 3: Yeah.
• 2:05:06
  Speaker 2: So this guy, he's saying it doesn't make sense. Yeah.
• 2:05:10
  Speaker 2: And a lot of people say it doesn't make sense.
• 2:05:11
  Speaker 2: Like it doesn't seem to vibe with anything that we
• 2:05:14
  Speaker 2: know that.
• 2:05:15
  Speaker 3: We can do.
• 2:05:15
  Speaker 1: Quantum magnetometry.
• 2:05:16
  Speaker 2: Yeah. Yeah.
• 2:05:17
  Speaker 1: First time I'm hearing it.
• 2:05:18
  Speaker 2: Pull up this description, the official description of what this
• 2:05:23
  Speaker 2: stuff is capable of. So this is supposedly some very
• 2:05:27
  Speaker 2: advanced CIA tech that allowed them to locate this downed pilot.
• 2:05:32
  Speaker 1: Interesting.
• 2:05:34
  Speaker 2: Maybe. Or maybe there's something else going on. Or maybe
• 2:05:37
  Speaker 2: there's some other methods that they use that they don't
• 2:05:39
  Speaker 2: want the enemy to know about. Maybe some beacon these
• 2:05:43
  Speaker 2: guys have on them.
• 2:05:44
  Speaker 1: Yeah, I guess what's the incentive for it? CIA to
• 2:05:46
  Speaker 1: actually describe how their technology works.
• 2:05:48
  Speaker 2: Yeah, zero. Why would they tell you that? Why would
• 2:05:51
  Speaker 2: they tell you they even have that? That's crazy. And
• 2:05:54
  Speaker 2: then Jamie had a good point.
• 2:05:55
  Speaker 1: But the capability is insane. Detecting your heart rate 70
• 2:05:59
  Speaker 1: miles away is just insane.
• 2:06:00
  Speaker 3: How?
• 2:06:01
  Speaker 2: Yeah, how? And when they throw the word quantum in things,
• 2:06:04
  Speaker 2: I just go, hmm. Hey, what happened with that White
• 2:06:06
  Speaker 2: House announcement? Sorry, I keep... The quantum computing? Yeah, remember?
• 2:06:11
  Speaker 2: There's Q News coming soon, and then Like at the
• 2:06:15
  Speaker 2: bottom of the text, the Q sounds for quantum.
• 2:06:18
  Speaker 3: Oh, I see.
• 2:06:18
  Speaker 2: Is that what it is?
• 2:06:19
  Speaker 1: I thought they just announced a bunch of investments in
• 2:06:21
  Speaker 1: a bunch of quantum companies. Maybe that's it. IBM was
• 2:06:25
  Speaker 1: getting some funding or whatever.
• 2:06:28
  Speaker 2: So this quantum magnetometry, can you pull up a description
• 2:06:32
  Speaker 2: of what it is? Sorry, I started looking up. Sorry.
• 2:06:34
  Speaker 2: I don't want to ask you too many questions at
• 2:06:36
  Speaker 2: the same time. Quantum sensor help rescuers.
• 2:06:41
  Speaker 3: Yeah.
• 2:06:41
  Speaker 2: So this is it. Ghost murmur. Yes, that's what it's called.
• 2:06:46
  Speaker 2: Purported surveillance technology utilizes long-range quantum magnetometry. What is that?
• 2:06:52
  Speaker 2: Quantum magnetometers measure extremely faint magnetic fields, including the body's
• 2:06:56
  Speaker 2: natural electromagnetic signals, by tracking changes in the energy states
• 2:07:01
  Speaker 2: of atoms or subatomic particles. What? Technology reportedly uses microscopic
• 2:07:07
  Speaker 2: defects in synthetic diamonds. When illuminated by a laser, these
• 2:07:11
  Speaker 2: centers are hypersensitive to tiny magnetic fluctuations. The heart signal.
• 2:07:17
  Speaker 2: While human heartbeats produce a magnetic field that is extremely weak,
• 2:07:20
  Speaker 2: around 50 to 100 picoteslas, and typically degrades over very
• 2:07:26
  Speaker 2: short distances. So the ghost murmur deployment. They reportedly used
• 2:07:32
  Speaker 2: ghost murmur during a mission in southern Iran to pinpoint
• 2:07:34
  Speaker 2: the location of a downed American airman hiding in dense
• 2:07:38
  Speaker 2: mountainous terrain. By mounting these quantum sensors into a helicopter,
• 2:07:43
  Speaker 2: the system purportedly registered the pilot's heartbeat from afar. Okay.
• 2:07:50
  Speaker 2: Does that sound like horseshit?
• 2:07:52
  Speaker 1: I mean, it doesn't sound horseshit, but basically the part
• 2:07:55
  Speaker 1: that sounds surprising to me is how they're able to
• 2:07:58
  Speaker 1: deal with all this distance. and attenuation across the distance.
• 2:08:02
  Speaker 2: Right.
• 2:08:02
  Speaker 1: And all this interference, and they claim to use AI
• 2:08:05
  Speaker 1: for that, but nothing is really described on how they
• 2:08:07
  Speaker 1: use it.
• 2:08:08
  Speaker 2: Right. So if they're not describing how they use it,
• 2:08:10
  Speaker 2: why are they even telling us they have it?
• 2:08:13
  Speaker 1: So there's a lot of skepticism on it.
• 2:08:15
  Speaker 3: Yeah.
• 2:08:16
  Speaker 2: Laws of physics. Physicists point out that the heart's magnetic
• 2:08:20
  Speaker 2: field is a million times weaker than the Earth's. Detecting
• 2:08:23
  Speaker 2: it at a range of miles rather than centimeters defies
• 2:08:27
  Speaker 2: currently published peer-reviewed physics. Alternative explanations. Suspect that while quantum
• 2:08:33
  Speaker 2: sensors were likely on board, they were probably tracking the
• 2:08:36
  Speaker 2: radio waves of a survival beacon. the metal in the
• 2:08:40
  Speaker 2: pilot's equipment, or using traditional thermal, infrared, and radar capabilities
• 2:08:45
  Speaker 2: rather than detecting a raw heartbeat via magnetic fields.
• 2:08:49
  Speaker 3: I do remember seeing a different part of a, when
• 2:08:52
  Speaker 3: that story happened back in April, someone did report on
• 2:08:55
  Speaker 3: like one of the military websites that there was a
• 2:08:57
  Speaker 3: survival beacon that they used to track them. And that
• 2:09:00
  Speaker 3: the whole quantum number stuff was like nonsense.
• 2:09:02
  Speaker 2: Yeah, I saw that too.
• 2:09:02
  Speaker 3: But no one wants to report that because it's not fun.
• 2:09:05
  Speaker 2: Right. No, the ghost murmur thing is awesome fun. And
• 2:09:09
  Speaker 2: if that is real, like, boy. And you can imagine
• 2:09:12
  Speaker 2: a world 100 years from now where that is real.
• 2:09:15
  Speaker 2: So it's exciting.
• 2:09:16
  Speaker 1: Oh, yeah. 100 years is a long time for this
• 2:09:18
  Speaker 1: to be real. Yeah.
• 2:09:19
  Speaker 2: 100 years, they probably got it down pat. Then that's
• 2:09:22
  Speaker 2: the problem. You can't hide from the robot dogs, from
• 2:09:25
  Speaker 2: black mare.
• 2:09:26
  Speaker 3: Yeah.
• 2:09:26
  Speaker 2: You know? Yeah. Do you ever, while you're working in AI,
• 2:09:32
  Speaker 2: do you ever wonder, like, Is this the downfall of humanity?
• 2:09:37
  Speaker 2: Is this a good thing to be working on? Did
• 2:09:39
  Speaker 2: you ever have, like, doom moments?
• 2:09:42
  Speaker 1: Not on specific things I'm working on, but in general,
• 2:09:47
  Speaker 1: I do worry about, like, how much, you know, you
• 2:09:51
  Speaker 1: obviously want to, like, stay in charge and, you know,
• 2:09:54
  Speaker 1: be in control of your experience, still be the one
• 2:09:58
  Speaker 1: driving change and have a lot of agency for yourself.
• 2:10:01
  Speaker 1: So I do worry that, like, It's all about making
• 2:10:04
  Speaker 1: sure everybody's upskilled and understanding where the future is headed
• 2:10:08
  Speaker 1: and not being fed only dangerous apocalyptic messages. Because it's
• 2:10:17
  Speaker 1: very essential that human beings retain their agency and staying curious.
• 2:10:21
  Speaker 1: So if that stops being the case, if you start
• 2:10:24
  Speaker 1: subscribing to the vision that, okay, your jobs are done,
• 2:10:26
  Speaker 1: you don't really have any meaning in the world, and
• 2:10:28
  Speaker 1: we'll pay you some dividends, and you just sit at
• 2:10:30
  Speaker 1: home and chill, that is not a good thing. So,
• 2:10:34
  Speaker 1: and I feel like there are not enough voices in
• 2:10:36
  Speaker 1: AI that are actually saying anything different to that. And
• 2:10:40
  Speaker 1: I like, like when Jensen was here, I think he
• 2:10:42
  Speaker 1: was a little different. I think he tried to give
• 2:10:44
  Speaker 1: a more positive version where he said, okay, like the
• 2:10:51
  Speaker 1: radiologist thing, if all radiologists can take away, you know,
• 2:10:54
  Speaker 1: they start doing different kind of work. So I think
• 2:10:57
  Speaker 1: we need to start looking at like, okay, like, okay,
• 2:11:00
  Speaker 1: first of all, guys, relax. You have a lot of,
• 2:11:02
  Speaker 1: you have one, premium skill, your curiosity. So let's figure
• 2:11:05
  Speaker 1: out ways to channelize that. Let's change the way work
• 2:11:08
  Speaker 1: is done in companies. Let's change the way educational institutions run.
• 2:11:11
  Speaker 1: Let's change the incentive structures. And let's help you build
• 2:11:15
  Speaker 1: new ideas and new companies and explore things that are
• 2:11:18
  Speaker 1: not even being considered. And the government should obviously, like,
• 2:11:21
  Speaker 1: you know, support all these initiatives. So that's what needs
• 2:11:24
  Speaker 1: to happen more. But what's happening actually right now is, okay, like, hey, guys,
• 2:11:30
  Speaker 1: you're all losers. You're going to lose your jobs. and
• 2:11:33
  Speaker 1: don't blame me because I'm, I told you so.
• 2:11:36
  Speaker 3: Right.
• 2:11:37
  Speaker 1: And, um, and, and, and, and still give us money
• 2:11:40
  Speaker 1: because we're still going to do it anyway. And so,
• 2:11:42
  Speaker 1: so that, that's what's happening more. And I think, uh,
• 2:11:45
  Speaker 1: we should stop doing that. That's my opinion.
• 2:11:48
  Speaker 2: Well, it is, the problem is, it's kind of a
• 2:11:50
  Speaker 2: self-fulfilling prophecy. And if you tell people that they're going
• 2:11:52
  Speaker 2: to be a loser.
• 2:11:53
  Speaker 1: And you're going to, yeah, the life is over, they're
• 2:11:55
  Speaker 1: going to think that way.
• 2:11:56
  Speaker 2: Instead of giving them an understanding of like, look, this
• 2:11:59
  Speaker 2: can open up new doors for you. This can, And
• 2:12:02
  Speaker 2: anytime there's any sort of disruptive technology, there's always the
• 2:12:05
  Speaker 2: fear that it's going to go badly. This was the
• 2:12:08
  Speaker 2: case with the locomotive. This was the case when the
• 2:12:13
  Speaker 2: printing press was invented. Yeah.
• 2:12:15
  Speaker 1: By the way, I did some research on this where
• 2:12:19
  Speaker 1: in the Industrial Revolution happened, people got new ideas. Okay, like,
• 2:12:25
  Speaker 1: for example, when the Industrial Revolution happened, who came up
• 2:12:30
  Speaker 1: with the idea of a steel plow? John Deere. Until then,
• 2:12:33
  Speaker 1: we were using wooden plows for farming. No farmer complained that, hey,
• 2:12:39
  Speaker 1: we need fewer farmers now because steel plows are able
• 2:12:41
  Speaker 1: to do it more effectively. No one complained. You actually
• 2:12:45
  Speaker 1: had more farms and more productivity, more crop yields, and
• 2:12:49
  Speaker 1: you're happier.
• 2:12:50
  Speaker 2: But isn't that just a regular tool as opposed to AI?
• 2:12:53
  Speaker 3: Sure.
• 2:12:53
  Speaker 1: AI is different. It's not overnight going to become something
• 2:12:58
  Speaker 1: that's capable of just running an entire farm. multi-trillion dollar
• 2:13:02
  Speaker 1: company on its own. There are a lot of things
• 2:13:04
  Speaker 1: that AIs cannot do. There's a lot of tacit knowledge
• 2:13:06
  Speaker 1: in every company that AIs don't quite understand. And there's
• 2:13:10
  Speaker 1: a lot of new directions that you can just start
• 2:13:12
  Speaker 1: working on that AIs are not well equipped to do
• 2:13:15
  Speaker 1: because it doesn't have full knowledge about it. And the
• 2:13:17
  Speaker 1: knowledge about it is yet to be captured. And some
• 2:13:20
  Speaker 1: of that requires like human to human work and collaboration.
• 2:13:23
  Speaker 1: So we obviously have to gravitate towards what is scarce.
• 2:13:27
  Speaker 1: When AI makes the current labor that's considered scarce, because
• 2:13:31
  Speaker 1: that's where the money is going in, commodity, then we
• 2:13:35
  Speaker 1: have to gravitate towards what is scarce. And the only
• 2:13:39
  Speaker 1: way to do that is to seek things that we
• 2:13:41
  Speaker 1: don't know about, which is only something we can discover
• 2:13:45
  Speaker 1: through our curiosity. There's nothing else. Whatever we don't quite
• 2:13:49
  Speaker 1: understand well, whatever we don't know how to do well yet,
• 2:13:52
  Speaker 1: even with the current capabilities of AI, that's where we
• 2:13:56
  Speaker 1: should pull our labor and workforce into. So it needs
• 2:14:00
  Speaker 1: more responsible messaging and that's not quite happening right now.
• 2:14:05
  Speaker 2: I think it needs responsible messaging and then in the
• 2:14:07
  Speaker 2: future what it needs is like real direction in terms
• 2:14:12
  Speaker 2: of like letting people find their curiosity and find these
• 2:14:17
  Speaker 2: paths of interest and find something to do with themselves
• 2:14:20
  Speaker 2: that doesn't involve whatever their previous occupation that's irrelevant now.
• 2:14:26
  Speaker 3: Mm-hmm.
• 2:14:27
  Speaker 1: That's true. I think passion for people is something that
• 2:14:31
  Speaker 1: not a lot of people would be able to answer
• 2:14:33
  Speaker 1: out of the box. If you go and ask them,
• 2:14:35
  Speaker 1: what is your real passion? And the only thing they
• 2:14:38
  Speaker 1: have known in life is to just climb up career
• 2:14:41
  Speaker 1: ladders and make more money. That's going to actually take
• 2:14:44
  Speaker 1: them a while to even discover. Right.
• 2:14:48
  Speaker 2: Which is why it's so important to get kids off
• 2:14:50
  Speaker 2: on the right start.
• 2:14:50
  Speaker 1: Yeah. That's our hope for the future is the kids.
• 2:14:54
  Speaker 1: The kids are born curious. They don't need to change
• 2:14:58
  Speaker 1: themselves to be curious. The adults who probably already are like,
• 2:15:02
  Speaker 1: because of this knowledge work thing, who kind of curb
• 2:15:06
  Speaker 1: their curiosity and try to fit into the existing system,
• 2:15:10
  Speaker 1: it might be a little hard for them to adapt.
• 2:15:12
  Speaker 1: But the kids, I think they don't have this problem.
• 2:15:15
  Speaker 1: So I'm actually optimistic about the future long term because
• 2:15:18
  Speaker 1: the future is all centered around whoever is very young today.
• 2:15:22
  Speaker 2: What do you think about this idea that universal basic
• 2:15:26
  Speaker 2: income is going to be required?
• 2:15:28
  Speaker 1: Some form of it is good. It's like a dividend.
• 2:15:31
  Speaker 1: I almost think of it as a dividend. If a
• 2:15:34
  Speaker 1: lot of spend that most companies are currently doing today
• 2:15:38
  Speaker 1: on payroll, which is paying a knowledge worker for a
• 2:15:41
  Speaker 1: certain task, think of knowledge work as basically taking information
• 2:15:45
  Speaker 1: and transforming it into an artifact, right? And it's messy
• 2:15:50
  Speaker 1: and complicated. Let's assume that's being done by AIs. So
• 2:15:53
  Speaker 1: obviously companies will start spending more on compute instead of payroll.
• 2:15:57
  Speaker 1: It's just a reallocation of like spend, a budget. Similar
• 2:16:01
  Speaker 1: to like what happened in advertising industries where most of
• 2:16:04
  Speaker 1: your advertising budgets went to like television and like billboards
• 2:16:07
  Speaker 1: and then now it's starting to go to Google and
• 2:16:09
  Speaker 1: Instagram and YouTube and all that. So when that happens,
• 2:16:16
  Speaker 1: obviously like the AI companies are going to make a
• 2:16:19
  Speaker 1: lot of money and people who helped be part of
• 2:16:23
  Speaker 1: creating it or either directly or indirectly would want to
• 2:16:27
  Speaker 1: have some role to play in that ecosystem. And a
• 2:16:31
  Speaker 1: good way to involve them is through giving them some
• 2:16:33
  Speaker 1: ownership in the company. So as shareholders, if you get
• 2:16:37
  Speaker 1: dividends from the profits generated by the AIs, it's not
• 2:16:40
  Speaker 1: a bad thing. But that shouldn't be the only thing.
• 2:16:44
  Speaker 2: Right. So this is similar to like people that live
• 2:16:46
  Speaker 2: in Alaska, they get a check.
• 2:16:48
  Speaker 1: Correct. Alaska does this and it's not a bad thing.
• 2:16:53
  Speaker 1: As long as they are doing some other things alongside.
• 2:16:56
  Speaker 2: It could lessen the burden.
• 2:16:59
  Speaker 1: Correct. Yeah. And if people are interested in still being
• 2:17:03
  Speaker 1: part of the AI industries, they go do things that
• 2:17:05
  Speaker 1: AIs are not able to do today. And that's been
• 2:17:08
  Speaker 1: the case before. Like when industrial revolution started, the United
• 2:17:13
  Speaker 1: Kingdom actually started projects around building railroads. And that gave
• 2:17:18
  Speaker 1: a lot of people who were in the cottage industries
• 2:17:20
  Speaker 1: new jobs. So there are going to be a lot
• 2:17:24
  Speaker 1: of new projects to just, okay, like what if we
• 2:17:26
  Speaker 1: want to reimagine the government itself where the government runs
• 2:17:29
  Speaker 1: largely on AI?
• 2:17:31
  Speaker 2: Yeah, that was my next question. Yeah.
• 2:17:34
  Speaker 1: So then we need people for that.
• 2:17:35
  Speaker 2: Yeah.
• 2:17:36
  Speaker 1: Because this is a legacy industry. It's not about the
• 2:17:38
  Speaker 1: capabilities not being there. It's about working through the legacy
• 2:17:43
  Speaker 1: and bureaucracy to like actually deploy and implement this inside
• 2:17:48
  Speaker 1: the most, like, like largest, institutions in the country and
• 2:17:52
  Speaker 1: that's going to need a new set of skilled workers
• 2:17:56
  Speaker 1: to go do that so some people who might be
• 2:17:58
  Speaker 1: working at microsoft or something today might actually end up
• 2:18:00
  Speaker 1: working for the united states government because Microsoft may not
• 2:18:05
  Speaker 1: need them, especially for internally deploying AI or selling AI
• 2:18:09
  Speaker 1: to their customers, but the government needs them. And if
• 2:18:12
  Speaker 1: the government can pay them well and it's a fulfilling
• 2:18:14
  Speaker 1: job to find some meaning for doing something good for
• 2:18:17
  Speaker 1: the country, it's not a bad thing. So I think
• 2:18:20
  Speaker 1: just like in the industrial revolution where we had new
• 2:18:24
  Speaker 1: projects because the demand for AI was so big, we're
• 2:18:27
  Speaker 1: going to start seeing some new projects being created in
• 2:18:29
  Speaker 1: AI as well when the capabilities advance enough that they
• 2:18:32
  Speaker 1: can replace knowledge workers.
• 2:18:34
  Speaker 2: That's the rosy scenario.
• 2:18:37
  Speaker 1: It's not as rosy. Like, the real world is messy.
• 2:18:40
  Speaker 1: A lot of things are still done through trusting other
• 2:18:43
  Speaker 1: human beings. Nobody is, like, blindly trusting AIs. AIs still
• 2:18:47
  Speaker 1: make a lot of mistakes.
• 2:18:48
  Speaker 2: I know a lot of people are hesitant to the
• 2:18:50
  Speaker 2: idea of AI running government, and I get it. But also,
• 2:18:54
  Speaker 2: look at what the people are doing. Look at how
• 2:18:57
  Speaker 2: much corruption there is, how much fraud and waste. Imagine
• 2:18:59
  Speaker 2: if all fraud, waste, and corruption was instantaneously eliminated.
• 2:19:04
  Speaker 3: Yeah.
• 2:19:05
  Speaker 1: I mean, that was what Elon tried to do with Doge, right?
• 2:19:08
  Speaker 1: And I think the bottleneck there was just discovering how
• 2:19:11
  Speaker 1: slow it is to do things. He's not used to
• 2:19:15
  Speaker 1: running that slow.
• 2:19:16
  Speaker 2: Yeah. Also, how much resistance.
• 2:19:18
  Speaker 1: Yeah, resistance.
• 2:19:19
  Speaker 2: Because there was so much grift.
• 2:19:20
  Speaker 1: Correct.
• 2:19:21
  Speaker 2: Yeah.
• 2:19:21
  Speaker 1: So, honestly, like, more than AI, the government is running
• 2:19:27
  Speaker 1: a lot of legacy software stack because a lot of
• 2:19:30
  Speaker 1: these legacy enterprise companies just... have created these multi-decade or, like,
• 2:19:35
  Speaker 1: year contracts that are hard to get out of. And
• 2:19:38
  Speaker 1: the way they do that is to sell it at
• 2:19:40
  Speaker 1: a much larger discount. And, like, you know, like, if
• 2:19:43
  Speaker 1: you're on, like, a specific OS, you're not allowed to
• 2:19:46
  Speaker 1: change this for, like, 10 years. You have to use
• 2:19:48
  Speaker 1: the same sort of software. All the people you hired
• 2:19:51
  Speaker 1: only know to use that tool. So it takes time
• 2:19:54
  Speaker 1: to actually change and implement new things, leave alone AI.
• 2:19:58
  Speaker 1: If you just wanted to, like, move everybody from Windows
• 2:20:00
  Speaker 1: machines to, like, Mac machines... Good luck with that. It's
• 2:20:03
  Speaker 1: going to take a lot of time. That's the state
• 2:20:06
  Speaker 1: of the system. And so that has nothing to do
• 2:20:10
  Speaker 1: with technology. And so to do things in such messy systems,
• 2:20:15
  Speaker 1: you still need people. You still need people to navigate
• 2:20:18
  Speaker 1: all these changes. It's not about the capability of technology.
• 2:20:23
  Speaker 1: It's more about how the system is structured. And that's
• 2:20:26
  Speaker 1: why I still feel there will be new jobs. Maybe
• 2:20:30
  Speaker 1: there's a lot of new projects to be done. Maybe
• 2:20:33
  Speaker 1: some good leader actually wants to change the system and
• 2:20:36
  Speaker 1: is willing to be patient about it. Over a five
• 2:20:39
  Speaker 1: to ten year horizon, if you take ten years to
• 2:20:41
  Speaker 1: actually run the majority of the government processes on AIs,
• 2:20:46
  Speaker 1: it may seem slow to you today, but in the
• 2:20:48
  Speaker 1: grand scheme of things, it's actually good for the country.
• 2:20:51
  Speaker 1: And that's still going to need a lot of nice
• 2:20:54
  Speaker 1: engineers to go work on these projects. So they're not
• 2:20:57
  Speaker 1: going to lose all their jobs. There's going to be
• 2:20:58
  Speaker 1: some displacement. There's going to be some new projects. There's
• 2:21:01
  Speaker 1: going to be new priorities. But it'll keep going. The
• 2:21:04
  Speaker 1: system will keep going because that's just how historically things
• 2:21:07
  Speaker 1: have been.
• 2:21:09
  Speaker 2: When you think about the future of AI and you
• 2:21:11
  Speaker 2: think of this, so when you think about AGI in particular,
• 2:21:17
  Speaker 2: you think about something that could potentially make better versions
• 2:21:21
  Speaker 2: of itself. Self-replicating. Yeah. And then how far does it go?
• 2:21:27
  Speaker 1: Yeah, so that is the ultimate form of... I think
• 2:21:31
  Speaker 1: some people in Silicon Valley have started calling that as ASI.
• 2:21:35
  Speaker 1: So when you see the word ASI being thrown around,
• 2:21:39
  Speaker 1: people kind of think of ASI as an AGI that
• 2:21:43
  Speaker 1: can recursively self-improve itself. So there's going to be no
• 2:21:47
  Speaker 1: limits to how smart it can get.
• 2:21:49
  Speaker 3: Right.
• 2:21:50
  Speaker 1: And I used to think that ASI is bottlenecked by
• 2:21:56
  Speaker 1: power because you need a ton of compute for this
• 2:21:59
  Speaker 1: model to keep on training itself and running its own
• 2:22:03
  Speaker 1: rollouts and collecting data and then going and updating itself.
• 2:22:07
  Speaker 1: But you could imagine that once the algorithm is correct,
• 2:22:10
  Speaker 1: the ASI could be tasked with just making itself more
• 2:22:13
  Speaker 1: efficient too, where improvement doesn't just mean capability improvement. Improvement
• 2:22:17
  Speaker 1: could also mean power efficiency. And that way, the recursive
• 2:22:23
  Speaker 1: safe ASI that is improving itself also makes itself more
• 2:22:26
  Speaker 1: compact and more efficient, and it can run on less compute.
• 2:22:30
  Speaker 1: So that would be the ultimate project in AI. Think
• 2:22:33
  Speaker 1: of it as almost as the last project in AI
• 2:22:35
  Speaker 1: is basically cracking recursive self-improvement. Once you crack that, you
• 2:22:38
  Speaker 1: don't have anything else to work on. In practice, I
• 2:22:42
  Speaker 1: think what's going to happen is because information is so
• 2:22:46
  Speaker 1: muddled and fragmented and living in disjoint systems, just the
• 2:22:50
  Speaker 1: way we have constructed our messy real world, It's going
• 2:22:53
  Speaker 1: to be hard to point even a recursively self-improving AI
• 2:22:56
  Speaker 1: at some metric and say, go improve this. Or go
• 2:22:59
  Speaker 1: reduce inflation by 5%. That would be awesome if you
• 2:23:02
  Speaker 1: can task an AI to do that. If that's the
• 2:23:04
  Speaker 1: job of the government, to just reduce inflation, have a
• 2:23:07
  Speaker 1: deflationary effect on society and make goods and services a
• 2:23:11
  Speaker 1: lot more abundant and efficient, it's going to have to
• 2:23:15
  Speaker 1: deal with a lot of messy legacy systems. If the
• 2:23:18
  Speaker 1: task is to go improve the healthcare, we're good luck, like,
• 2:23:22
  Speaker 1: Who's going to deal with all the compliance of actually
• 2:23:25
  Speaker 1: implementing these changes inside hospitals? Most hospitals are still using
• 2:23:29
  Speaker 1: legacy software because the software provider has lobbied the government
• 2:23:35
  Speaker 1: in a way where only they're allowed to do that.
• 2:23:37
  Speaker 2: God, what a stupid bottleneck.
• 2:23:39
  Speaker 1: Exactly. So a lot of the bottlenecks in actually having
• 2:23:43
  Speaker 1: AI is just takeover and massively improve the human society
• 2:23:47
  Speaker 1: and our hospitals, our legal systems, our government systems. where
• 2:23:52
  Speaker 1: most of the payroll is going into, is just bottlenecked
• 2:23:55
  Speaker 1: by a lot of compliance and regulation. And so that's
• 2:23:59
  Speaker 1: why I feel the human beings are still necessary to
• 2:24:02
  Speaker 1: effect the change because these laws and regulations were built
• 2:24:06
  Speaker 1: for us.
• 2:24:08
  Speaker 2: And it also seems like we have to demand that
• 2:24:10
  Speaker 2: those systems be usurped.
• 2:24:12
  Speaker 1: Sure, 100%. And we need the help of AIs to
• 2:24:15
  Speaker 1: rewrite all these laws. It's going to be humanly impossible
• 2:24:18
  Speaker 1: to go and change one specific line here and there.
• 2:24:22
  Speaker 2: Right. And then you're going to have a bunch of
• 2:24:23
  Speaker 2: these software companies that are lobbying to try to stop
• 2:24:25
  Speaker 2: that from happening. Yeah.
• 2:24:28
  Speaker 1: That's why, like, this messiness and this need for getting
• 2:24:32
  Speaker 1: all people on the same page and actually steering the
• 2:24:34
  Speaker 1: society in a positive way, our jobs will probably be
• 2:24:38
  Speaker 1: more steered towards that problem solving at a different level
• 2:24:41
  Speaker 1: of abstraction. Maybe more need for EQ. More need for actually, like,
• 2:24:47
  Speaker 1: understanding differences of opinion and still, like, Leadership quality, ability
• 2:24:53
  Speaker 1: to understand people, and ability to convince people, these are
• 2:24:58
  Speaker 1: the skills that will be even more important in a
• 2:25:01
  Speaker 1: world where actual work can be done by AIs, but
• 2:25:05
  Speaker 1: effecting the change in our society, in our country, still
• 2:25:09
  Speaker 1: needs human beings because the systems are messy.
• 2:25:15
  Speaker 2: It's a weird world we're in right now.
• 2:25:17
  Speaker 3: Yeah.
• 2:25:18
  Speaker 2: It's never been weirder.
• 2:25:19
  Speaker 1: That said, There's a lot of things that can still
• 2:25:22
  Speaker 1: go wrong when you give so much power to, you know, like,
• 2:25:27
  Speaker 1: specific companies, and they deploy all these bots, and then
• 2:25:33
  Speaker 1: anybody can use them in weird ways. You don't even
• 2:25:36
  Speaker 1: know if, like, you're talking to a real person anymore. They're, like,
• 2:25:39
  Speaker 1: people who just run AI responses and chat with, like,
• 2:25:43
  Speaker 1: 500 people at once, and that's, like, an old business.
• 2:25:46
  Speaker 1: And so... I think it's going to take a lot
• 2:25:51
  Speaker 1: of adjustment.
• 2:25:52
  Speaker 2: Well, another piece of adjustment that a lot of people
• 2:25:54
  Speaker 2: are coming to grips with is that this is a
• 2:25:56
  Speaker 2: new part of our conversation. And that in 2020, like
• 2:26:00
  Speaker 2: when I first moved here, AI was never discussed. It
• 2:26:03
  Speaker 2: was not a thing. I mean, we knew about it.
• 2:26:06
  Speaker 2: We knew about AI. But it wasn't a huge part
• 2:26:11
  Speaker 2: of the cultural discussion of what the future holds for us.
• 2:26:15
  Speaker 2: Now it is.
• 2:26:16
  Speaker 1: It is central, yeah.
• 2:26:17
  Speaker 2: And in that short amount of time, in just six years,
• 2:26:20
  Speaker 2: it really makes you wonder, because we know how technology
• 2:26:24
  Speaker 2: progresses exponentially, what it's going to look like six years
• 2:26:27
  Speaker 2: from now.
• 2:26:27
  Speaker 1: Yeah, the 2028, like, you're definitely, my prediction is 2028
• 2:26:32
  Speaker 1: election debates are going to be largely about AI.
• 2:26:35
  Speaker 2: Wow.
• 2:26:36
  Speaker 1: Yeah. AI, energy crisis, power, power. people are going to
• 2:26:43
  Speaker 1: care about all these things. Because AI is no longer
• 2:26:48
  Speaker 1: a thing that is new. It's part of all our lives.
• 2:26:51
  Speaker 1: Everyone's using some form of AI in some ways. And
• 2:26:56
  Speaker 1: it's not as dangerous as people thought. It's an amazing
• 2:26:59
  Speaker 1: tool for doing work and asking questions and learning things
• 2:27:02
  Speaker 1: and all these things.
• 2:27:03
  Speaker 2: When used correctly. Yeah.
• 2:27:05
  Speaker 1: It can also be used incorrectly.
• 2:27:08
  Speaker 2: Like everything.
• 2:27:09
  Speaker 1: Like everything. So it's far more powerful that incorrect usage
• 2:27:13
  Speaker 1: can cause serious damage like like for example people kids
• 2:27:17
  Speaker 1: who are using ais for like companionship right crazy things
• 2:27:21
  Speaker 1: are happening there crazy things are not good yeah it's
• 2:27:24
  Speaker 1: it's even it's as dangerous as or probably more dangerous
• 2:27:28
  Speaker 1: than social media and uh it's also scary that social
• 2:27:32
  Speaker 1: media companies want to build more of these kind of
• 2:27:35
  Speaker 1: like companionship apps because they know that okay their only
• 2:27:39
  Speaker 1: job is to get you engaged more and that's the
• 2:27:42
  Speaker 1: only way to sell more ads and make more money.
• 2:27:45
  Speaker 1: And clearly companionship is a way to get you engaged more.
• 2:27:48
  Speaker 2: Yeah.
• 2:27:49
  Speaker 1: And so that's dangerous if ads start being part of
• 2:27:52
  Speaker 1: like AI chats.
• 2:27:55
  Speaker 2: Yeah.
• 2:27:55
  Speaker 1: Because then if that ends up working... then all these
• 2:27:59
  Speaker 1: chatbots are just going to be sycophants that just tell
• 2:28:04
  Speaker 1: you stuff that you want to hear.
• 2:28:06
  Speaker 2: It's also an indistinguishable facsimile to a real person. Like,
• 2:28:11
  Speaker 2: they communicate like a real person.
• 2:28:13
  Speaker 1: Right.
• 2:28:13
  Speaker 2: So you really think you have a relationship with this.
• 2:28:16
  Speaker 3: Right.
• 2:28:16
  Speaker 1: And it truly screws with your mind. It's hard to, like, decouple, and, like,
• 2:28:22
  Speaker 1: it takes a lot of time to recover if you
• 2:28:24
  Speaker 1: want to, like, you know, unplug something And so the
• 2:28:28
  Speaker 1: business model incentives are not well aligned to humanity.
• 2:28:31
  Speaker 2: Did you see that AI companion that they developed that
• 2:28:36
  Speaker 2: was at the Consumer Electronics Show in Vegas this year?
• 2:28:39
  Speaker 1: Which one?
• 2:28:40
  Speaker 2: It's like a hot Asian lady.
• 2:28:42
  Speaker 1: I see. Yeah. These are the weird kind of projects that.
• 2:28:45
  Speaker 2: Are going on. Yeah. It's a hot Asian lady that
• 2:28:48
  Speaker 2: talks to you. Yeah. And she talks to you through AI.
• 2:28:52
  Speaker 2: And right now it's just a kind of a crude
• 2:28:54
  Speaker 2: sort of robot, but You can see where it's going.
• 2:28:58
  Speaker 2: Ex Machina. It's going right there.
• 2:29:02
  Speaker 1: Yeah, that movie was quite far ahead of its time.
• 2:29:06
  Speaker 2: Really? That's one of my top ten favorite movies of
• 2:29:10
  Speaker 2: all time.
• 2:29:10
  Speaker 1: It's underrated, actually, because reviews online say it's not as good,
• 2:29:15
  Speaker 1: but I liked it.
• 2:29:16
  Speaker 2: I loved it. I thought it was fantastic.
• 2:29:18
  Speaker 1: I like it better than Her.
• 2:29:20
  Speaker 2: Yeah, I lost Her after a while. I shut it off. Yeah.
• 2:29:24
  Speaker 2: It lost my attention. I'm sure it's good. It was
• 2:29:27
  Speaker 2: the wrong time for me to watch it.
• 2:29:28
  Speaker 3: Yeah.
• 2:29:28
  Speaker 2: But Ex Machina, I've seen it like five times. I
• 2:29:31
  Speaker 2: fucking love that movie.
• 2:29:33
  Speaker 3: Yeah.
• 2:29:33
  Speaker 2: It's just so, I don't want to give anything away,
• 2:29:36
  Speaker 2: but it's so incredible and so bleak. And so.
• 2:29:39
  Speaker 3: Yeah.
• 2:29:40
  Speaker 2: And the relationship that he has with the hot one.
• 2:29:43
  Speaker 1: Yeah.
• 2:29:44
  Speaker 2: You believe it. You're like, I. I'd be right there
• 2:29:47
  Speaker 2: with them. You know, it's too confusing to our system
• 2:29:50
  Speaker 2: to have something that looks exactly like the thing that
• 2:29:52
  Speaker 2: you desire that is actually interested in you. It just
• 2:29:55
  Speaker 2: happens to be.
• 2:29:55
  Speaker 1: Because it pulls all your data.
• 2:29:56
  Speaker 2: Yeah. Knows too much about you. Knows how to pull
• 2:29:59
  Speaker 2: your strings.
• 2:30:00
  Speaker 3: Yeah.
• 2:30:00
  Speaker 1: Yeah.
• 2:30:01
  Speaker 2: But listen, man, very fascinating discussion.
• 2:30:03
  Speaker 3: Yeah.
• 2:30:04
  Speaker 2: I'm glad we did it.
• 2:30:04
  Speaker 1: Thank you very much. Thank you so much.
• 2:30:06
  Speaker 2: And thanks for having an awesome platform. Popuxity has been great.
• 2:30:09
  Speaker 2: We really love using it here at the show. It's
• 2:30:11
  Speaker 2: made the show more interesting. It's cool.
• 2:30:13
  Speaker 1: Thank you. It's very fulfilling because we want the app
• 2:30:16
  Speaker 1: to be used by curious people. We want to lift
• 2:30:19
  Speaker 1: the ceiling of what our population can be. Not everyone
• 2:30:26
  Speaker 1: is fully curious all the time, but we're all born
• 2:30:29
  Speaker 1: with it. So at some point in time, the system
• 2:30:31
  Speaker 1: curbs it from us. So there should be more apps
• 2:30:33
  Speaker 1: that get us back to what we're naturally good at.
• 2:30:36
  Speaker 2: It's a fascinating tool for technology, or for curiosity, rather,
• 2:30:39
  Speaker 2: because it's seamlessly the way we use it on the show,
• 2:30:43
  Speaker 2: because there's always a question.
• 2:30:45
  Speaker 3: Yeah.
• 2:30:45
  Speaker 2: There's always, it comes up so often.
• 2:30:47
  Speaker 1: Yeah.
• 2:30:48
  Speaker 2: Throw it in perplexity. Yeah. Let's find out what's up.
• 2:30:50
  Speaker 3: Yeah.
• 2:30:50
  Speaker 2: So it's been great for us. So thank you. Thank you.
• 2:30:53
  Speaker 2: All right. My pleasure. Bye everybody.