Latest / Scam Goddess / The Architects of AI with Josh Johnson

Transcript

The Architects of AI with Josh Johnson · Scam Goddess

• 0:18
  Speaker 1: What's poppin', congregation? It's your girl Lacey Mosley, a.k.a. Scam Goddess,
• 0:22
  Speaker 1: back with another installment of the podcast all about robbery, fraud,
• 0:25
  Speaker 1: and those who practice it. Sometimes we laugh at them.
• 0:27
  Speaker 1: Sometimes we hate them. One thing's for sure, we usually
• 0:29
  Speaker 1: will laugh at them, but never at the victims, okay?
• 0:32
  Speaker 1: And if you are an OG congregation member, you already
• 0:34
  Speaker 1: know that I'm very what? I'm very excited, yes. Thrilled, elated.
• 0:39
  Speaker 1: Come on, parasocial girls, we gotta stay locked in in
• 0:41
  Speaker 1: our conversations. How was your day? Damn, that's crazy. That
• 0:46
  Speaker 1: works for everything, okay? But yes, I'm excited, I'm thrilled, elated,
• 0:49
  Speaker 1: and I do feel a little witchy because I feel
• 0:51
  Speaker 1: like I manifested this guest to the show because I
• 0:53
  Speaker 1: have wanted this person for so long. Josh Johnson is
• 0:57
  Speaker 1: an Emmy-nominated writer, actor, stand-up comedian. He's best known for
• 1:01
  Speaker 1: his work on The Daily Show and his stand-up specials.
• 1:05
  Speaker 1: I'm so happy to have you here, Josh.
• 1:06
  Speaker 2: Thanks so much for having me.
• 1:07
  Speaker 1: Yes.
• 1:07
  Speaker 2: Yeah, no, it's great to meet you.
• 1:09
  Speaker 1: OK, so on this podcast, we always ask Josh, like,
• 1:12
  Speaker 1: what is your relationship with scams? Do you love them?
• 1:14
  Speaker 1: Do you hate them? Are you intrigued by them? Have
• 1:16
  Speaker 1: someone ran on you? Have you ran some past others that,
• 1:19
  Speaker 1: you know, passed the statute of limitations?
• 1:21
  Speaker 2: I am a big fan of scams.
• 1:24
  Speaker 3: All right.
• 1:25
  Speaker 2: I love I love when someone not just can pull
• 1:30
  Speaker 2: the wool, but can get caught. And then there are
• 1:32
  Speaker 2: some people because you would see this in like City
• 1:34
  Speaker 2: Confidential back in the day and sometimes work. People would
• 1:37
  Speaker 2: they literally catch the killer or the scammer or whoever.
• 1:40
  Speaker 2: And there'd still be people that were like, he didn't
• 1:42
  Speaker 2: do it. He didn't do it. I don't believe it.
• 1:45
  Speaker 2: You know, and I think that we're in an ultimate
• 1:48
  Speaker 2: time of scams. This is probably the best time to
• 1:50
  Speaker 2: scam that we've that we've had as a country.
• 1:53
  Speaker 1: Because the floodgates, they're open. At this point, our government
• 1:57
  Speaker 1: is like, yeah, we're robbing you. What about it? Crime
• 2:00
  Speaker 1: is legal. Yeah, crime is legal. Everyone's like, what about
• 2:02
  Speaker 1: the purge? And I'm like, the purge is happening right
• 2:04
  Speaker 1: now in front of your eyes.
• 2:05
  Speaker 2: Yeah, just slowly.
• 2:07
  Speaker 1: Yeah.
• 2:07
  Speaker 2: Yeah, it's not happening with like Ethan Hawke, but it's
• 2:09
  Speaker 2: still happening. Right.
• 2:11
  Speaker 1: Unfortunately, I don't understand why those movies always thought that
• 2:13
  Speaker 1: people would envision like one day of free crime. We
• 2:15
  Speaker 1: want to just go kill everybody. Like, no, I'm going
• 2:18
  Speaker 1: to get like new furniture. Right.
• 2:20
  Speaker 2: I think that, yeah, they just didn't focus on the
• 2:23
  Speaker 2: looting as much since like the actual murder is probably
• 2:26
  Speaker 2: going to catch more attention. But I'm sure people did
• 2:29
  Speaker 2: all manner of stuff. They just chose to follow this
• 2:32
  Speaker 2: one specific family.
• 2:34
  Speaker 1: True. The ones who just were like hell bent on
• 2:36
  Speaker 1: the murderous part.
• 2:37
  Speaker 2: I honestly I think that if if the purge was
• 2:42
  Speaker 2: real in the movie sense, right, where it's just one day,
• 2:45
  Speaker 2: I think I would just like spend that day clearing
• 2:48
  Speaker 2: any debts.
• 2:50
  Speaker 1: Yeah.
• 2:51
  Speaker 2: Like you obviously hunker down, bunker down in your home.
• 2:53
  Speaker 2: You don't want to get killed and everything. But go
• 2:55
  Speaker 2: ahead and like break into a bank's back system and
• 3:01
  Speaker 2: wipe your debt clean, all the credit card debt clean.
• 3:04
  Speaker 2: You could actually be building towards that the whole year,
• 3:07
  Speaker 2: knowing that on Purge Day, you've got about eight good
• 3:10
  Speaker 2: hours of hacking that you can do. Clear off some
• 3:13
  Speaker 2: of that debt.
• 3:14
  Speaker 1: Okay, I'm glad that you explained that further because at
• 3:16
  Speaker 1: first I was going to be like, not you shilling
• 3:18
  Speaker 1: to the man because I thought you were going to
• 3:19
  Speaker 1: be like, yeah, I get a lot of money and
• 3:20
  Speaker 1: then I pay off my debts the next day. I
• 3:22
  Speaker 1: was like, oh, no, no, no, no, no.
• 3:23
  Speaker 2: Not paying. not pay at all I would rack up
• 3:26
  Speaker 2: that debt the whole time and then be like just
• 3:29
  Speaker 2: knowing y'all ooh I don't know what happened next day
• 3:32
  Speaker 2: I'm like really it says.
• 3:33
  Speaker 1: Zero that's crazy well I can't remember the last number
• 3:36
  Speaker 1: it was but it was kind of close to zero
• 3:38
  Speaker 1: so we should probably just keep.
• 3:39
  Speaker 2: It at the last number had zeros in it so
• 3:42
  Speaker 2: that was just that was just closer to what it
• 3:44
  Speaker 2: is now so.
• 3:44
  Speaker 1: That's definitely my number no for sure yeah nothing There
• 3:47
  Speaker 1: are people who stay in, like, denial about a scam
• 3:50
  Speaker 1: being real. We talk about that a lot, like you
• 3:52
  Speaker 1: just mentioned before.
• 3:53
  Speaker 2: Political parties, yeah.
• 3:54
  Speaker 1: Yeah, but I don't think that they are denial. They're
• 3:57
  Speaker 1: just telling us anything. At this point, they don't even care.
• 3:59
  Speaker 2: I think that there are some people who genuinely don't care.
• 4:02
  Speaker 2: I do think that in one of the saddest, my
• 4:06
  Speaker 2: dad's coming to pick me up type ways, some of
• 4:08
  Speaker 2: them still believe.
• 4:09
  Speaker 1: Oh, no, sitting on that curb with that hot concrete
• 4:11
  Speaker 1: just burning their thighs. 100%.
• 4:13
  Speaker 2: That they're paying to sit on.
• 4:15
  Speaker 1: Mm-hmm.
• 4:15
  Speaker 2: Because it's like it's their money as well. Like that's
• 4:18
  Speaker 2: that's my thing. It's one thing if you're like, oh, my.
• 4:23
  Speaker 3: Yeah.
• 4:23
  Speaker 2: Like my president cares about me. And then and then
• 4:27
  Speaker 2: you are in a metropolitan area where there could be
• 4:31
  Speaker 2: some benefits to being in an area that is self-sufficient.
• 4:35
  Speaker 2: And you never have to like you never have to
• 4:37
  Speaker 2: sit with the fact that these direct policies are going
• 4:41
  Speaker 2: to be damaging to you. But if you were in
• 4:43
  Speaker 2: like a rural area and you were already poor. And
• 4:45
  Speaker 2: then he was like, we're going to bring jobs back.
• 4:47
  Speaker 2: And then he does it. That's that's your stomach rumbling.
• 4:50
  Speaker 2: Do you have it? And that's you choosing to continue
• 4:53
  Speaker 2: to believe a promise is not going to be fulfilled.
• 4:56
  Speaker 2: So I think that some of them are getting scammed
• 4:59
  Speaker 2: in a way that they're not aware of, that they
• 5:02
  Speaker 2: don't want to believe.
• 5:03
  Speaker 1: Yeah. OK, you're right. Maybe the people who thought racism
• 5:05
  Speaker 1: would pay the bills are hurting.
• 5:08
  Speaker 2: And I feel so... They were hurting before.
• 5:11
  Speaker 1: Not bad for them.
• 5:12
  Speaker 2: Yeah, no, no. I'm not stressed for them. I'm just saying, like,
• 5:15
  Speaker 2: they really.
• 5:16
  Speaker 1: You think that there are some people who still believe
• 5:18
  Speaker 1: in this grift, who, like, wholeheartedly are like, the government's
• 5:21
  Speaker 1: not scamming us. They're not, like, funneling money. There's not
• 5:23
  Speaker 1: these pay circles where they're literally stealing your retirement. We
• 5:27
  Speaker 1: didn't get rid of all of your migrant workers who
• 5:29
  Speaker 1: helped your farms work, made them work. No, no, no, no, no, no, no, no.
• 5:33
  Speaker 2: No, no, I'll be fine. And then they're in the
• 5:35
  Speaker 2: burning room. You know, I think that that's what a
• 5:39
  Speaker 2: lot of people are experiencing. That's not to say that
• 5:41
  Speaker 2: it makes me feel bad for them. It's just like
• 5:44
  Speaker 2: when you talk to them, they're like, no, that's that
• 5:46
  Speaker 2: that thing isn't even true. And you're like, why don't
• 5:49
  Speaker 2: you think it's true? I just don't. I'm like, oh, well, research.
• 5:55
  Speaker 1: When politics became like a sports event. Like, I don't
• 5:58
  Speaker 1: have a team. I'm not team DSA. Are a lot
• 6:01
  Speaker 1: of people, you know, democratic socialists that I actually align with? Absolutely.
• 6:05
  Speaker 1: Are there still some centrists that I'm like, we can
• 6:06
  Speaker 1: keep your bitch ass around, I guess some. But at
• 6:09
  Speaker 1: the same time, it's like, if you do me dirty,
• 6:11
  Speaker 1: I want you out. I don't care what colors you wear.
• 6:12
  Speaker 1: I don't care who you rep. I don't care where
• 6:14
  Speaker 1: your grandma stay.
• 6:15
  Speaker 2: Get out.
• 6:16
  Speaker 1: And I feel like, unfortunately for the Republican Party, it's
• 6:18
  Speaker 1: turned into like, this is our team and we got
• 6:20
  Speaker 1: to win. And if that means we got to lose
• 6:21
  Speaker 1: and die, well, we still got to win. Yeah.
• 6:24
  Speaker 2: At least it was a white guy that killed us.
• 6:28
  Speaker 2: I do think that, yeah, some of it becoming a
• 6:31
  Speaker 2: sport is either for when you are very, very rich
• 6:34
  Speaker 2: or very, very poor, because I think that in those
• 6:37
  Speaker 2: instances you have something to like hold on to. I
• 6:40
  Speaker 2: think if you're rich, you don't really care. And you'll see, like,
• 6:42
  Speaker 2: what is it, BlackRock CEO in 2024 was like, we
• 6:47
  Speaker 2: don't care who wins. And I think that for them it's, like,
• 6:50
  Speaker 2: fun for sport because they're just figuring out whether it's
• 6:53
  Speaker 2: through lawyers and tax code how they can.
• 6:57
  Speaker 1: We're going to buy what we want no matter who's
• 6:59
  Speaker 1: in office.
• 6:59
  Speaker 2: We're going to get there. Yeah, yeah. This is a
• 7:01
  Speaker 2: game monopoly for us. And then for people who are really,
• 7:04
  Speaker 2: really broke, I think that the team of it is
• 7:08
  Speaker 2: at least the feeling that something is happening. And I
• 7:11
  Speaker 2: think that's why so many people so easily fall for distractions.
• 7:15
  Speaker 1: Yeah.
• 7:15
  Speaker 2: You know, like at a certain point, gas will be
• 7:18
  Speaker 2: too expensive for you to drive your car or to
• 7:21
  Speaker 2: take a flight and meat will be too expensive for
• 7:24
  Speaker 2: you to eat. But at least, I don't know, some
• 7:28
  Speaker 2: kids aren't playing baseball.
• 7:29
  Speaker 1: Kids you don't even know. Yeah. Fields you ain't never
• 7:31
  Speaker 1: been to.
• 7:32
  Speaker 2: And also people who weren't trying to play, by the way. Right.
• 7:35
  Speaker 2: Like truly made up scenario.
• 7:37
  Speaker 1: In their head.
• 7:38
  Speaker 3: Yeah.
• 7:39
  Speaker 1: Yeah. Well, I mean, and I know that horse has
• 7:41
  Speaker 1: been beaten absolutely to death, but it seems like the
• 7:43
  Speaker 1: people who need to hear it are just going to
• 7:44
  Speaker 1: be eating it pretty soon from the FDA.
• 7:45
  Speaker 2: Yeah.
• 7:46
  Speaker 1: But moving on to the topic of this episode. So
• 7:51
  Speaker 1: I'm doing a four part series on A.I., which I
• 7:55
  Speaker 1: have been teetering with for a while, Josh. And I
• 7:58
  Speaker 1: definitely am so excited to have you here. Obviously, your
• 8:00
  Speaker 1: Daily Show experience and your political comedy, you understand how
• 8:03
  Speaker 1: much of a joke this is. But I think that
• 8:06
  Speaker 1: because it's so broad and there's so many barriers to
• 8:10
  Speaker 1: entry with all of the tech bro jargon and BS,
• 8:13
  Speaker 1: We've managed to either exhaust people, you know, so much
• 8:17
  Speaker 1: where they're like, I'm worried about gas, food, eggs. I
• 8:19
  Speaker 1: don't want to hear about the, you know, the IPO
• 8:21
  Speaker 1: PE and how it's overvalued. Like that doesn't, you know,
• 8:24
  Speaker 1: it's exhausting. So we're going to try to make this
• 8:26
  Speaker 1: pretty palatable and hopefully give people a larger scope of
• 8:30
  Speaker 1: what's happening. And eventually... Some tools to, you know, get
• 8:34
  Speaker 1: out into the city and tear shit up because we've
• 8:36
  Speaker 1: seen how those city council movies, or movies, they turn
• 8:39
  Speaker 1: into movies.
• 8:39
  Speaker 3: Yeah, yeah, yeah.
• 8:39
  Speaker 1: But those city council meetings have really started to deter
• 8:42
  Speaker 1: these lawmakers, at least until the midterms are over, from
• 8:44
  Speaker 1: building data centers in people's neighborhoods just because now we
• 8:47
  Speaker 1: know when to show up. Now we know what to
• 8:48
  Speaker 1: hoot and holler about. So that's what we're managing to do.
• 8:51
  Speaker 2: I hope I can be in any way helpful.
• 8:54
  Speaker 1: You always are. So for Historic Hoodwinks, that's the segment
• 8:58
  Speaker 1: that we regaled Josh with a famous con caper group
• 9:01
  Speaker 1: of criminals. And we get their information all throughout. Today,
• 9:03
  Speaker 1: we're talking about, to give us like an entry point,
• 9:06
  Speaker 1: Silicon Valley's systemic enfranchisement of untalented douchebags like Leopold Aschenbrenner
• 9:13
  Speaker 1: and how it's resulted in a current AI nightmare.
• 9:16
  Speaker 2: Yeah.
• 9:16
  Speaker 1: Here are their stories. I want a dick wolf. Give
• 9:20
  Speaker 1: me a dick wolf.
• 9:23
  Speaker 2: Don't, don't, don't.
• 9:24
  Speaker 1: Your dick on SuperNet? I'll do it myself. Chomp, chomp.
• 9:29
  Speaker 2: No, we could probably find one. We could do one
• 9:32
  Speaker 2: that's like a midways between something that's very you and
• 9:35
  Speaker 2: then something that's a little bit Dick Wolf and then
• 9:37
  Speaker 2: just do the two dum-dums.
• 9:38
  Speaker 1: Yeah, scam, scam.
• 9:39
  Speaker 2: Yeah, scam, scam. Scam, scam.
• 9:43
  Speaker 1: We're just trying to rip it off a little bit.
• 9:45
  Speaker 2: Yeah, yeah, yeah.
• 9:45
  Speaker 1: You're going to know it's not AI, guys, because it's
• 9:47
  Speaker 1: going to sound bad.
• 9:48
  Speaker 2: It'll just be us saying scam, scam.
• 9:51
  Speaker 1: Yes, so tired. So this is Leopold Aschenberger, a guy
• 9:56
  Speaker 1: that I definitely would look at and be like, Let's
• 9:58
  Speaker 1: give him money.
• 10:00
  Speaker 2: Isn't he 24? Well, yeah, at the time.
• 10:06
  Speaker 1: So Leopold Aschenberger built a $ 45 billion AI hedge fund
• 10:10
  Speaker 1: and almost lost most of it in days, which happened
• 10:13
  Speaker 1: to coincide with his wedding. Hmm. Something borrowed was like, hey, girl,
• 10:18
  Speaker 1: we actually don't need that back before the wedding.
• 10:20
  Speaker 2: Yeah. Also.
• 10:21
  Speaker 1: Margin call.
• 10:21
  Speaker 2: $ 45 billion. Because this is the guy that wrote Situational Awareness, right?
• 10:26
  Speaker 1: Yes.
• 10:26
  Speaker 3: Yeah.
• 10:27
  Speaker 2: Which is a very funny name.
• 10:29
  Speaker 1: For what is happening to him.
• 10:30
  Speaker 2: For losing billions of dollars.
• 10:32
  Speaker 1: Because clearly you had none.
• 10:34
  Speaker 4: Yeah.
• 10:34
  Speaker 1: You had no situational awareness.
• 10:35
  Speaker 2: That's incredible.
• 10:37
  Speaker 1: So here he is looking young, some might say, and carefree.
• 10:41
  Speaker 1: Like he walked into a hair salon and said, give
• 10:43
  Speaker 1: me a 90s Meg Ryan. Plus, he has an infectious laugh.
• 10:48
  Speaker 1: Let's hear that laugh. Look at him. Infectious.
• 11:00
  Speaker 2: As someone who loves making people laugh, I would also
• 11:04
  Speaker 2: be gasping if I lost billions of dollars in like
• 11:07
  Speaker 2: a single week.
• 11:11
  Speaker 1: I think that's his natural laugh. I think he's trying
• 11:13
  Speaker 1: to imitate like what humans do.
• 11:16
  Speaker 2: I mean, that laugh seems so deeply genuine. I don't
• 11:20
  Speaker 2: know what they were talking about, but it must be hilarious.
• 11:24
  Speaker 1: Probably impending doom that they're fueling.
• 11:27
  Speaker 2: Oh, man. Okay.
• 11:28
  Speaker 1: And then when they run out of food. When the
• 11:33
  Speaker 1: data centers poison all their neighborhoods.
• 11:38
  Speaker 2: Is he just running the hedge fund specifically, or is
• 11:42
  Speaker 2: he also involved with one of the... companies on top
• 11:45
  Speaker 2: of that? Because didn't he have like some anthropic?
• 11:47
  Speaker 1: So we're going to get to that because you're right
• 11:49
  Speaker 1: on top of it. Yeah. So he was born in Germany,
• 11:51
  Speaker 1: just a little bit about him, to doctor parents. And
• 11:53
  Speaker 1: he graduated from Columbia University as valedictorian at 19 years old,
• 11:58
  Speaker 1: which is like, oh, he's a wunderkind. He's a genius.
• 12:01
  Speaker 1: He studied all the books and left when he was 19.
• 12:04
  Speaker 1: At Columbia, he co-founded an executive altruism club, which is
• 12:07
  Speaker 1: a popular thing AI people say about using data to
• 12:10
  Speaker 1: promote causes that will have greater positive impact on others.
• 12:14
  Speaker 1: It sounds good, but it's really an excuse for billionaires
• 12:17
  Speaker 1: to hoard wealth as long as they can promise that
• 12:18
  Speaker 1: they're going to give it away eventually, which, spoiler, they don't.
• 12:23
  Speaker 2: Yeah, it is a weird thing where they keep promising.
• 12:27
  Speaker 2: And it's one of those things where they try to
• 12:30
  Speaker 2: get you excited about it because they're like, wow, the
• 12:32
  Speaker 2: pot's getting bigger. So when I give this away, it's
• 12:34
  Speaker 2: going to be even more. And so you could give
• 12:36
  Speaker 2: it away today or like half. You're not going to
• 12:38
  Speaker 2: spend all of it. Yeah, but we got to just
• 12:41
  Speaker 2: see how big the pot can get before we give
• 12:44
  Speaker 2: anything away. I don't think so.
• 12:46
  Speaker 1: What about some dividends? What about a little, mm-mm-mm, pot's
• 12:49
  Speaker 1: not big enough?
• 12:50
  Speaker 2: You would think so.
• 12:51
  Speaker 1: When you see how big the pot is, though, you're
• 12:53
  Speaker 1: going to be gagged. You're going to be like, wow,
• 12:55
  Speaker 1: this was worth the starvation.
• 12:56
  Speaker 2: Y'all, you will have no, for the two of you
• 12:58
  Speaker 2: that survive, you will have so much, and it will
• 13:01
  Speaker 2: make up for the fact that we had so much.
• 13:04
  Speaker 1: It's like they saw Squid Game and all the money
• 13:06
  Speaker 1: filling up in that ball and were like, yeah, but
• 13:09
  Speaker 1: for our government.
• 13:10
  Speaker 2: Yeah.
• 13:10
  Speaker 1: But for us.
• 13:11
  Speaker 2: Or they watched all Squid Game and they were like, yeah,
• 13:13
  Speaker 2: it should go to one person. me yeah ideally.
• 13:21
  Speaker 1: Which then who it who works for you where do
• 13:23
  Speaker 1: you spend it they haven't thought this all the way
• 13:24
  Speaker 1: through they're just hoarders and gambling addicts but here we
• 13:27
  Speaker 1: are so salutatorian sofia montron salutatorian there we go now
• 13:33
  Speaker 1: i sound like i can't read so salutatorian sofia montron
• 13:37
  Speaker 1: said she found him childlike and socially awkward yeah we
• 13:40
  Speaker 1: get that that weird laugh girl i would have ran
• 13:43
  Speaker 1: too Out of college, Leo Polz started out working for
• 13:47
  Speaker 1: all-time scammer and former subject of the podcast Sam Bankman-Fried
• 13:52
  Speaker 1: at his corrupt crypto exchange FTX. That's where Leo met
• 13:56
  Speaker 1: his future bride, Avril Baltwit.
• 13:59
  Speaker 2: You know what I love about Sam Bankman-Fried? If we
• 14:02
  Speaker 2: could go back one slide, one of my favorite things
• 14:04
  Speaker 2: about Sam Bankman-Fried is that he looked like he did
• 14:07
  Speaker 2: what everybody accused him of. This is one of the
• 14:10
  Speaker 2: only guys that when they point to him and they
• 14:12
  Speaker 2: were like, hey, he stole billions or whatever, I was like, yeah,
• 14:17
  Speaker 2: I could see it.
• 14:17
  Speaker 1: Yeah.
• 14:18
  Speaker 2: I could see it. Because sometimes people are too clean cut.
• 14:21
  Speaker 2: Even with our main guy, it's like if you have
• 14:24
  Speaker 2: enough of a presentable character presence, people are like, I
• 14:28
  Speaker 2: guess I could see giving him some money.
• 14:30
  Speaker 1: Yeah, he's got a Jennifer Aniston haircut and a quarter zip.
• 14:32
  Speaker 1: Give him money.
• 14:34
  Speaker 2: Maybe he didn't mean to. Sam Bankman Free looked like
• 14:38
  Speaker 2: he showed up to do what he went to jail for.
• 14:42
  Speaker 2: Every time I see this dude, he looked like this.
• 14:44
  Speaker 2: Even when he was in a suit in court, I
• 14:46
  Speaker 2: was like, no, you're going to get found guilty. Just
• 14:49
  Speaker 2: the hair alone, I was like, this is not doing
• 14:50
  Speaker 2: you any favors.
• 14:51
  Speaker 1: You know what? I think it's just because he was
• 14:53
  Speaker 1: really dedicated doing crime. He didn't have time for like wardrobe,
• 14:57
  Speaker 1: for haircuts, for like facials or daily grooming because he
• 15:01
  Speaker 1: was too busy doing crime.
• 15:03
  Speaker 2: Married only to the gang.
• 15:05
  Speaker 1: Yes. And this is what you have to look like
• 15:07
  Speaker 1: when you're making real sacrifices for fraud.
• 15:09
  Speaker 2: It's great. Like, I cannot get over this because in
• 15:12
  Speaker 2: this picture, he is young. This is him young.
• 15:17
  Speaker 1: Well, when you... Look, racism makes you age, and so
• 15:20
  Speaker 1: does certain crime. This is a high-stress crime. He's lying
• 15:23
  Speaker 1: all the time. This man gets up, and his alarm
• 15:25
  Speaker 1: is probably a reminder of his first lie of the day.
• 15:28
  Speaker 2: Yeah. It's just... I don't know what it is. I'm
• 15:31
  Speaker 2: sorry to be stuck on this.
• 15:32
  Speaker 1: He gets the alarm at 7 a.m., and it's like,
• 15:35
  Speaker 1: tell him we're in the black. Yeah. Tell him we're
• 15:36
  Speaker 1: in the black.
• 15:37
  Speaker 2: Yeah. Just move some numbers around. I feel like this
• 15:41
  Speaker 2: is one of those dudes... He just looked like.
• 15:48
  Speaker 2: If you forward something on a spreadsheet and you really
• 15:50
  Speaker 2: carried it with you all day, you would look like this.
• 15:54
  Speaker 2: I think that plenty of scammers, they're sociopathic enough that
• 15:57
  Speaker 2: they're lying all the time, but then they're also like, oh, yeah,
• 16:01
  Speaker 2: I guess you caught me. You'll take them to court.
• 16:04
  Speaker 2: You'll take Elizabeth Holmes to court and she'll be like, Yeah,
• 16:07
  Speaker 2: I guess I did it or whatever. Yeah. And it's
• 16:09
  Speaker 2: still like there's nothing happening.
• 16:11
  Speaker 1: Because at that point, they're already caught. And I think
• 16:14
  Speaker 1: in the sociopathic nature, it's like, what if they beg?
• 16:16
  Speaker 1: They're not going to get away with it. At this point,
• 16:18
  Speaker 1: they're just trying to, like, you know, mitigate the harm
• 16:20
  Speaker 1: to themselves.
• 16:21
  Speaker 2: Yeah. But I think this dude, he must care a
• 16:24
  Speaker 2: little bit because he's wearing it on him.
• 16:26
  Speaker 1: He is. But I also will say this might have
• 16:28
  Speaker 1: been his attempt to, like, blend into the tech space
• 16:31
  Speaker 1: as well. You know, that's such a flex to look
• 16:33
  Speaker 1: like you don't have clothes.
• 16:35
  Speaker 2: Yeah.
• 16:36
  Speaker 1: You know, spend $ 8, 000 on a T-shirt that only a
• 16:37
  Speaker 1: douchebag would recognize.
• 16:39
  Speaker 2: What is that symbol? Do you know what that is?
• 16:41
  Speaker 1: I don't. It seems like a logo of some sorts.
• 16:44
  Speaker 1: If I were to guess, it was like FTX, but
• 16:46
  Speaker 1: I'm not exactly sure. But yeah, you know, Sam, he
• 16:48
  Speaker 1: was the mastermind behind the scheme to defraud FTX customers
• 16:51
  Speaker 1: by misappropriating billions of dollars of their funds to buy
• 16:55
  Speaker 1: real estate, contribute millions of dollars to political candidates from
• 16:58
  Speaker 1: both parties as a tax write-off. And to repay billions
• 17:01
  Speaker 1: of dollars in loans owed by Alameda Research, a cryptocurrency
• 17:05
  Speaker 1: trading fund that's Bankman Freed also co-founded. Which, this one
• 17:09
  Speaker 1: always pissed me off because FTX is only super popular
• 17:11
  Speaker 1: to me because during COVID, like the height of COVID,
• 17:15
  Speaker 1: it made it to... Uncle Facebook, Uncle and Auntie Facebook.
• 17:19
  Speaker 1: They were like, we got a new investment opportunity. And like,
• 17:22
  Speaker 1: we got to get it on the ground floor. So
• 17:24
  Speaker 1: when you start to see Black people, minorities get involved
• 17:26
  Speaker 1: in any type of crypto, it's usually right before a
• 17:28
  Speaker 1: rug pull. Like we are never, just socioeconomically, it's always
• 17:32
  Speaker 1: made to where we are the last to know. And if,
• 17:34
  Speaker 1: I'm sorry, but if a white person is telling you
• 17:36
  Speaker 1: about some crypto, run. Because what they try to do
• 17:38
  Speaker 1: is get your Black dollars in there and then extract
• 17:40
  Speaker 1: their wealth and leave you holding that non-existent bag. And we,
• 17:43
  Speaker 1: and a lot of us know that, but a lot
• 17:45
  Speaker 1: of people don't. But he was behind stealing all that money.
• 17:48
  Speaker 1: And then my uncles are, you know, posting online, holding
• 17:50
  Speaker 1: up a few hundred dollar bills in a Nissan Altima.
• 17:54
  Speaker 2: I mean, my thing, my thing with that especially is
• 17:57
  Speaker 2: that it's never. I was broke long enough to know
• 18:02
  Speaker 2: that by the time I heard about something, it wasn't
• 18:04
  Speaker 2: good information anymore. That's fair. Like when I was in Chicago,
• 18:09
  Speaker 2: I was over here. If someone gave me some sort
• 18:11
  Speaker 2: of stock tip, I was like, hey, if it made
• 18:14
  Speaker 2: it to me. This is stale. This has got to
• 18:20
  Speaker 2: be stale. Or you're scamming me.
• 18:22
  Speaker 1: I love you personally being your own litmus test. Like,
• 18:25
  Speaker 1: how do I know about this?
• 18:26
  Speaker 2: Because I was over here. Must be fraud. I don't
• 18:28
  Speaker 2: know anything about money. I don't have money. If I'm
• 18:31
  Speaker 2: finding this information, this was on the ground. Do you
• 18:35
  Speaker 2: know what I mean? This was, like, less worth it
• 18:38
  Speaker 2: than finding a dollar on the street because at least
• 18:40
  Speaker 2: a dollar would be real.
• 18:42
  Speaker 3: Right.
• 18:42
  Speaker 2: Like, when someone was hitting me up and they're like, hey, look, okay,
• 18:45
  Speaker 2: you don't even have to put in much. All right.
• 18:47
  Speaker 2: You got to put these little thirty five dollars in there.
• 18:49
  Speaker 2: We got a real investment opportunity. You could 10x your money.
• 18:52
  Speaker 2: And I'm like, OK. All right. But, you know, I
• 18:55
  Speaker 2: work in the grocery store. Like, you know, you like
• 18:58
  Speaker 2: this is we're not having some same backdoor dealing as
• 19:00
  Speaker 2: these guys whenever they rent out the four seasons for
• 19:03
  Speaker 2: a month. And then, you know, just have a conversation
• 19:06
  Speaker 2: about what an NFT should actually be, you know.
• 19:09
  Speaker 1: Exactly. And then it's like, I don't want to see
• 19:12
  Speaker 1: you in chains because of one trade on Robin Hood.
• 19:14
  Speaker 1: That's not right.
• 19:15
  Speaker 2: Yeah. And also it wouldn't even get like, I wouldn't
• 19:18
  Speaker 2: even be part of the scam. I'd be the last scam. Yeah.
• 19:21
  Speaker 2: Like I would be the, I would be the scammed.
• 19:23
  Speaker 2: I'd be at the tail end where it's like the
• 19:25
  Speaker 2: bottom of the pyramid, you know, where it's wide. I'd
• 19:28
  Speaker 2: be one of those, one of those bricks.
• 19:30
  Speaker 1: Yeah. I would definitely be bread. One of the biggest scams,
• 19:33
  Speaker 1: the food pyramid. No one needs that much bread. And
• 19:37
  Speaker 1: we would, I would definitely be bread too. Just like, No, everybody, no,
• 19:40
  Speaker 1: you need like six loaves of bread a day. Like,
• 19:42
  Speaker 1: believe us. 100%. Believe us, okay?
• 19:44
  Speaker 2: Carbs is your life fuel.
• 19:46
  Speaker 1: Yes. You're not eating four baguettes in the morning.
• 19:49
  Speaker 2: Then you must not. not care about your health.
• 19:50
  Speaker 1: You don't, clearly. So, you know, he was behind this scam.
• 19:54
  Speaker 1: After FTX collapsed and Bankman Freed was arrested on charges
• 19:57
  Speaker 1: of orchestrating an $ 8 billion fraud, he and Leopold went
• 20:00
  Speaker 1: their separate ways. Leopold and Avital, that's his boo-thang, Avital, right?
• 20:05
  Speaker 1: So they both resigned on the day FTX declared bankruptcy. So,
• 20:10
  Speaker 1: you know, seems like a good day to go.
• 20:12
  Speaker 2: So my thing, I wonder how mad you would be
• 20:16
  Speaker 2: if you were Sam Bankman Freed, because now $ 8 billion
• 20:19
  Speaker 2: seems so little. In comparison to the money that's being
• 20:22
  Speaker 2: like stolen or laundered or like the corruption numbers have
• 20:27
  Speaker 2: 10x from when Sam Bankman Free was going to jail.
• 20:31
  Speaker 1: And at the time he was going to jail for
• 20:32
  Speaker 1: the largest that we had seen. And they threw the
• 20:35
  Speaker 1: book at Sam just to like make him the fall guy.
• 20:38
  Speaker 1: So many people were involved in this FTX fraud and
• 20:40
  Speaker 1: they're like, oh, no, that one man, he did it
• 20:43
  Speaker 1: all by himself alone.
• 20:45
  Speaker 2: Yeah, and then Sam.
• 20:46
  Speaker 1: He was emailing himself.
• 20:47
  Speaker 2: He was dumb enough to be standing in the room
• 20:50
  Speaker 2: alone with an ax. Like, other people were in here.
• 20:53
  Speaker 2: I swear other people were in here.
• 20:55
  Speaker 1: Were they?
• 20:56
  Speaker 4: Yeah.
• 20:56
  Speaker 1: Because you're holding the only ax, sir.
• 20:58
  Speaker 2: Everybody else's hands are washed.
• 21:00
  Speaker 1: Right.
• 21:00
  Speaker 2: And he's like, no.
• 21:02
  Speaker 1: No, the Ax Club resigned this morning, but they were
• 21:04
  Speaker 1: here yesterday.
• 21:05
  Speaker 2: Yeah.
• 21:05
  Speaker 1: Like, please be serious. Scams! So Leo had to distance
• 21:15
  Speaker 1: himself from the crypto bad guy, Sam Bankman Freed. So
• 21:18
  Speaker 1: of course he went straight to AI bad guy, Sam
• 21:21
  Speaker 1: Altman at OpenAI, the artificial intelligence company that makes ChatGPT,
• 21:26
  Speaker 1: which is now the fifth most visited website in the world.
• 21:30
  Speaker 1: Leo worked at OpenAI while Avatar, his boo thing, got
• 21:33
  Speaker 1: a job as Dario Amodi's chief of staff at Anthropic,
• 21:37
  Speaker 1: makers of Claude. So Anthropic makes Claude, OpenAI makes ChatGPT,
• 21:42
  Speaker 1: Which is like chat GPT with a cuter name, I guess.
• 21:45
  Speaker 1: Both names suck. They suck at naming things. So it's
• 21:49
  Speaker 1: all really romantic until OpenAI fired Leopold in 2024 over
• 21:53
  Speaker 1: a supposed security breach. So this is Sam Altman. I
• 21:57
  Speaker 1: just feel like these are all the same version of
• 22:01
  Speaker 1: the same weird looking dude.
• 22:04
  Speaker 2: I feel like a lot of people... would love to
• 22:07
  Speaker 2: be Steve Jobs, and they've done their own spin on
• 22:10
  Speaker 2: what their interpretation is.
• 22:11
  Speaker 1: Of Steve Jobs.
• 22:12
  Speaker 2: This is my spin.
• 22:13
  Speaker 1: Turtleneck, but like hoochie on the side.
• 22:14
  Speaker 2: I think, here's the thing.
• 22:16
  Speaker 1: Would you buy my currency?
• 22:17
  Speaker 2: I would buy your currency. I think if you were
• 22:20
  Speaker 2: to scam me, I would consider myself scammed.
• 22:22
  Speaker 1: Oh, we'll be real.
• 22:22
  Speaker 2: Concoin.
• 22:23
  Speaker 3: Yeah.
• 22:24
  Speaker 2: We keep it up front. No, I appreciate that, but
• 22:26
  Speaker 2: I would let myself be rug pulled. If you showed
• 22:29
  Speaker 2: up and you had a good enough pitch, I would
• 22:31
  Speaker 2: be open to it. Because it would also be something fresh.
• 22:33
  Speaker 2: Because a lot of these guys, when they give you
• 22:36
  Speaker 2: their take on what the future is going to be,
• 22:39
  Speaker 2: they do it in a way that is so genuinely
• 22:42
  Speaker 2: clumsy to the human experience. They can't explain why it
• 22:45
  Speaker 2: would be better if you didn't have a job and
• 22:47
  Speaker 2: starved and died. You would think that they would think
• 22:50
  Speaker 2: of that first. You'd think that they would come out
• 22:53
  Speaker 2: and they'd be like, look, everybody hates having a job,
• 22:55
  Speaker 2: so what if you didn't have one?
• 22:57
  Speaker 1: Right.
• 22:57
  Speaker 2: That's a better pitch than... Look, you're going to lose
• 23:00
  Speaker 2: your job.
• 23:01
  Speaker 1: You will be replaced by machinery and by computers that
• 23:04
  Speaker 1: are faster than your brain could ever be while we
• 23:06
  Speaker 1: steal all the knowledge you ever put into the world.
• 23:08
  Speaker 2: We're also going to make you train it in your
• 23:10
  Speaker 2: last two months of employment.
• 23:12
  Speaker 1: Is it sexy? Do you want to do this? Yeah.
• 23:14
  Speaker 2: And it's like that to me is indicative of them
• 23:18
  Speaker 2: kind of being ghouls. Like I just I don't I
• 23:21
  Speaker 2: don't get how it is appealing outside of the potential
• 23:24
  Speaker 2: money that an investor could stand to make. to engage
• 23:28
  Speaker 2: with their vision of a future at all. It genuinely
• 23:32
  Speaker 2: does not make sense to me because then even for
• 23:34
  Speaker 2: the investor who stands to make money and it's a
• 23:38
  Speaker 2: very enticing idea to put in whatever, $ 5 million and
• 23:41
  Speaker 2: walk away with 500 million. but you still have to
• 23:44
  Speaker 2: live on planet Earth. Like, you still have to be
• 23:46
  Speaker 2: engaged in the world in some way.
• 23:49
  Speaker 1: You need food. You need resources. Perhaps you need entertainment.
• 23:52
  Speaker 1: Maybe you need some of those weird antique roadshows where
• 23:54
  Speaker 1: you can go collect, like, Harriet Tubman's spoons. If you're
• 23:58
  Speaker 1: a sick Civil War freak, like, who is Terrence Clomis' pimp?
• 24:05
  Speaker 2: Oh, yeah. What's that guy's name?
• 24:06
  Speaker 1: Who is Claire's pimp? Ooh, I know who it's who.
• 24:09
  Speaker 1: Gave him a Winnebago, right?
• 24:11
  Speaker 2: Harlan Crowe. Harlan Crowe. Yeah, Pimp Daddy Crowe.
• 24:14
  Speaker 1: Yeah, he loves a weird civil rights memorial.
• 24:17
  Speaker 2: Grandson of Jim.
• 24:18
  Speaker 1: Yes. Yeah. So... So, like, you don't even have anything
• 24:22
  Speaker 1: to be quirky with. Also, Sam Altman recently, this past week,
• 24:27
  Speaker 1: he's starting to admit that there were some miscalculations in
• 24:30
  Speaker 1: the inertia at which AI would move. And the reason
• 24:33
  Speaker 1: I really want to do this episode is because I'm
• 24:35
  Speaker 1: so tired of these freaking douchebags using this kind of
• 24:38
  Speaker 1: language as if they're saying something profound. You meant inertia like, oh,
• 24:42
  Speaker 1: we didn't realize that human beings would still like to
• 24:44
  Speaker 1: do tasks that bring them joy, that they don't want
• 24:47
  Speaker 1: to overpay for your system to work Make a line
• 24:50
  Speaker 1: of code that costs $ 1, 200 when they could do it
• 24:53
  Speaker 1: for much cheaper. Replace their jobs, their joy, their happiness,
• 24:56
  Speaker 1: and their clean drinking water and atmospheres. That inertia of
• 25:00
  Speaker 1: people to want to keep having existence is crazy. And
• 25:03
  Speaker 1: we thought they weren't going to have that inertia. What? Yeah.
• 25:06
  Speaker 2: Not just that. We also thought the thing might do
• 25:09
  Speaker 2: what we said it would do. Because that's also happening.
• 25:13
  Speaker 2: We had no evidence, but we were positive. It was
• 25:15
  Speaker 2: getting so good at stealing information and then regurgitating it
• 25:18
  Speaker 2: back like it was new that we were positive that
• 25:20
  Speaker 2: eventually it would have some new information. Because that's my
• 25:23
  Speaker 2: biggest thing also when you ask these guys, well, did
• 25:26
  Speaker 2: you ask the AI how it can function more sustainably?
• 25:31
  Speaker 2: And they're always like, we're about to. No, we will.
• 25:34
  Speaker 1: No, we will. It's a list on our question list.
• 25:37
  Speaker 2: It's on the way. It's just once it gets better,
• 25:39
  Speaker 2: it'll be able to answer better.
• 25:41
  Speaker 1: Like, once you see that bucket fill up with all
• 25:43
  Speaker 1: our money, I mean our, our is all of us money,
• 25:47
  Speaker 1: then we'll ask it about sustainability.
• 25:49
  Speaker 2: Don't worry about that. And also, when there's less of you,
• 25:52
  Speaker 2: I mean us, I mean you here, we won't even
• 25:56
  Speaker 2: need to be sustainable.
• 25:57
  Speaker 1: Sir, what do you mean by here?
• 25:58
  Speaker 2: Yeah.
• 26:00
  Speaker 1: Alive. Earth? Yeah.
• 26:02
  Speaker 2: Yeah.
• 26:05
  Speaker 1: So... Here we get into Leopold's essay, which you mentioned before,
• 26:10
  Speaker 1: situational awareness, right? So two months after the work breakup
• 26:13
  Speaker 1: he had with OpenAI, where he was disagreeing and saying
• 26:16
  Speaker 1: OpenAI was unethical, which is like, all of you are unethical.
• 26:18
  Speaker 1: None of you know ethics. Let's all stop using that word, please.
• 26:21
  Speaker 1: You're ghouls. You make nothing of value. You steal from everyone.
• 26:25
  Speaker 1: And on top of that, you got a nerve to
• 26:26
  Speaker 1: be ugly. Like, give us something. Give us something, please.
• 26:28
  Speaker 2: That's kind of what I mean about the Sam Bankman
• 26:30
  Speaker 2: of it all, where I'm like, I think that the
• 26:33
  Speaker 2: reason he was the fall guy is that he looks
• 26:35
  Speaker 2: like who everybody would blame it on. Once it hit
• 26:39
  Speaker 2: the fan, I think, honestly, if he had like a
• 26:42
  Speaker 2: better bone structure, he might have not only got off,
• 26:45
  Speaker 2: he may have been able to take people with him.
• 26:47
  Speaker 1: Yeah.
• 26:47
  Speaker 2: Because if Sam Bankman Free could sit there and be like,
• 26:49
  Speaker 2: all right, let's be honest. Let's be honest right now.
• 26:53
  Speaker 2: Who's the ugliest one in the room? And it's not him.
• 26:55
  Speaker 1: Then he don't got to go down by himself.
• 26:56
  Speaker 2: No.
• 26:57
  Speaker 1: You are right. This should have been like America's Next
• 26:59
  Speaker 1: Top Model. Like, I have 10 photos.
• 27:01
  Speaker 2: I have 10 photos of 10 defendants. Because my thing is,
• 27:07
  Speaker 2: with Sam Bankman Freed especially, everybody who wanted to blame
• 27:10
  Speaker 2: him just pointed at him. And when they pointed at him,
• 27:12
  Speaker 2: He did look like he just rolled out of bed
• 27:14
  Speaker 2: after stealing a bunch of money.
• 27:15
  Speaker 1: He did.
• 27:16
  Speaker 2: And so people were like, I can imagine it. I
• 27:18
  Speaker 2: see it.
• 27:19
  Speaker 1: He needed to do the opposite. You know how like
• 27:20
  Speaker 1: a lot of ballers and scammers, like when they get caught,
• 27:22
  Speaker 1: they'll dress more demure for court, try to look less like,
• 27:26
  Speaker 1: you know, gaudy. I think you're right. I think he
• 27:28
  Speaker 1: needed to like get the whole glow up. He needed
• 27:30
  Speaker 1: to get a facial. He needed to get that fuck
• 27:32
  Speaker 1: boy haircut with the shave size, like that curly at
• 27:34
  Speaker 1: the top. Give me like a cute like fit. I
• 27:38
  Speaker 1: do not know.
• 27:39
  Speaker 2: Why he refused for the entire time that he had
• 27:42
  Speaker 2: money all the way up until jail to get a haircut.
• 27:46
  Speaker 1: I think that was the aesthetic of like, I'm a nerd.
• 27:48
  Speaker 1: I'm an engineer. You know, I don't do my hair
• 27:50
  Speaker 1: because I'm cold and java. You hear me?
• 27:52
  Speaker 2: The shirt and the pants and the watch were nerd enough.
• 27:56
  Speaker 2: He could have just had the haircut. A haircut would
• 27:59
  Speaker 2: have instilled at least a little bit of sympathy because
• 28:01
  Speaker 2: then with the haircut, we would find out, oh, okay,
• 28:04
  Speaker 2: you see what I'm saying? You see what I'm talking about?
• 28:07
  Speaker 3: Yeah.
• 28:08
  Speaker 2: You see what I'm talking about?
• 28:08
  Speaker 1: I thought it was upset.
• 28:09
  Speaker 2: What is even the back? Okay, you see that little
• 28:11
  Speaker 2: space right there?
• 28:12
  Speaker 1: It's a little matted back there.
• 28:14
  Speaker 2: Okay, yes, on his left side. Do you see that gap?
• 28:17
  Speaker 1: Maybe he had trouble with it. He got like a
• 28:19
  Speaker 1: 3C curly. You know, maybe he never had a natural journey.
• 28:22
  Speaker 2: That gap right there is Looney Tunes. That's the gap
• 28:25
  Speaker 2: of when, you know, like when Wile E. Coyote dodge
• 28:27
  Speaker 2: and something shoot him and there's just enough of a
• 28:30
  Speaker 2: hole from the laser?
• 28:32
  Speaker 1: Oh, you're right. That gap is diabolical. And the blue
• 28:35
  Speaker 1: is coming right through it like there is no hair here.
• 28:38
  Speaker 2: It's shining right through.
• 28:39
  Speaker 1: Just like there was no money in FTX.
• 28:41
  Speaker 2: One haircut would have switched a lot of this up.
• 28:44
  Speaker 1: You're right.
• 28:45
  Speaker 2: Because also, you see the front line, right?
• 28:47
  Speaker 1: Also, like, these pants, like, baby, where's the hem? Like,
• 28:50
  Speaker 1: let's have those sitting on your natural waist. Let's get
• 28:52
  Speaker 1: you a shirt in your size.
• 28:54
  Speaker 2: I bet you if this dude had, actually, look, I
• 28:57
  Speaker 2: don't know how hard this is to pull up, and
• 28:59
  Speaker 2: I'm not saying that it would have looked like this,
• 29:01
  Speaker 2: but do you remember late, we're talking, like, last eighth
• 29:05
  Speaker 2: of the movie Fight Club, when Brad Pitt had that
• 29:08
  Speaker 2: buzz cut. I'm not saying that Sam Bankman-Fried would have
• 29:12
  Speaker 2: looked like Brad Pitt. I'm just saying that the buzz
• 29:14
  Speaker 2: cut would have been a better look than the wildy
• 29:17
  Speaker 2: Einstein-type hair.
• 29:19
  Speaker 1: See, I think he needed, like, a soccer player, fuckboy 3000.
• 29:23
  Speaker 1: Fade those sides and let that curl pop right up here.
• 29:25
  Speaker 1: Give me a little tendril coming down here.
• 29:27
  Speaker 2: It's a touch thin for a crew cut type. Like,
• 29:31
  Speaker 2: I think that if he had tried the soccer thing,
• 29:33
  Speaker 2: we would be like, he's sick. You see what I'm
• 29:36
  Speaker 2: talking about here, right? If he had tried to do
• 29:39
  Speaker 2: one of these, I think he would have been better off.
• 29:42
  Speaker 1: He might have had the face for it, but maybe
• 29:44
  Speaker 1: then he would need some facial hair. The bottom line
• 29:45
  Speaker 1: is he's not sexy enough, and that's why he had
• 29:47
  Speaker 1: to go to jail. And that's not our fault. This
• 29:49
  Speaker 1: is America, okay? We talked about Anna Delvey's court looks
• 29:53
  Speaker 1: all the time. We're like, oh, she's so chic. Get
• 29:55
  Speaker 1: her out of prison.
• 29:56
  Speaker 2: Yeah, not only is she chic, but especially in... During
• 29:59
  Speaker 2: the trial, she stayed quiet enough that you were like, okay,
• 30:03
  Speaker 2: I could see maybe letting her off. You shouldn't, but
• 30:07
  Speaker 2: I could see if it happened with the jury. Because
• 30:09
  Speaker 2: if she talked, whenever she was like, your son, pa,
• 30:12
  Speaker 2: like that was jarring.
• 30:15
  Speaker 1: Yeah.
• 30:15
  Speaker 2: That was hard.
• 30:16
  Speaker 1: I think it was also that when you see her
• 30:19
  Speaker 1: looking like, when people don't speak, then you gotta get
• 30:21
  Speaker 1: to project whatever you want onto them. It's something I'm
• 30:24
  Speaker 1: really working on. I talk too much. And I'm like,
• 30:27
  Speaker 1: maybe if I was just like silent and just like
• 30:28
  Speaker 1: made eyes at people a little bit more, people would
• 30:30
  Speaker 1: think I was like mysterious. And that's what Anna did.
• 30:34
  Speaker 1: And then we're like, I could see how she convinced
• 30:35
  Speaker 1: all those rich people that she was like, she was like,
• 30:38
  Speaker 1: anytime they asked her for information, she was never over explaining.
• 30:40
  Speaker 1: She was never being thirsty. She was like, do you
• 30:43
  Speaker 1: deserve to be here with me? I don't know. I
• 30:45
  Speaker 1: figure out. Yes.
• 30:47
  Speaker 2: See, that's perfect. That's perfect. what do you think Sam
• 30:50
  Speaker 2: Bateman free sound like? Yeah. Yeah. You can hear him
• 30:55
  Speaker 2: stealing your money. He's like, yeah.
• 30:59
  Speaker 1: Oh, I never want to hear that out of a
• 31:01
  Speaker 1: man in any form or fashion. Oh, no, Josh. Well,
• 31:04
  Speaker 1: let's get back to the scam mistake that started Leopold's entry, OK,
• 31:08
  Speaker 1: as a young man in his 20s, which is so
• 31:12
  Speaker 1: funny to me because he's not the first to get
• 31:15
  Speaker 1: millions of dollars or even billions from investors being fresh
• 31:18
  Speaker 1: out of college, green as hell, Similac still on the breath.
• 31:22
  Speaker 1: And they're like, we're going to give you a massive
• 31:24
  Speaker 1: amount of money because you're young. And I feel like
• 31:26
  Speaker 1: some of this comes from the fear of older people
• 31:29
  Speaker 1: in tech because tech is almost like modeling in a
• 31:31
  Speaker 1: way where it's like, Your greatest years are when you're
• 31:34
  Speaker 1: young and you're splashy and you're on the cutting edge
• 31:36
  Speaker 1: of something. And then if you get to a point
• 31:38
  Speaker 1: where you're out of touch with technology, you're a dinosaur
• 31:41
  Speaker 1: and they kind of like throw you away, even if
• 31:42
  Speaker 1: you've made a lot of money. So I feel like
• 31:44
  Speaker 1: a lot of these guys' insecurity is like power is
• 31:47
  Speaker 1: all I have. I don't look good. They don't look
• 31:49
  Speaker 1: like they smell good. They don't have any morals or
• 31:51
  Speaker 1: any scruples. I can't imagine anybody really loves them in
• 31:53
  Speaker 1: their lives because you have to be able to love
• 31:55
  Speaker 1: to receive it. So all they have is power. So
• 31:58
  Speaker 1: I think they throw it at these young men thinking like, oh,
• 32:01
  Speaker 1: I just found a teenager who's doing the next, you know,
• 32:03
  Speaker 1: and that's what they get to talk about at some
• 32:06
  Speaker 1: weird bar in their quarter zips. So the essay that's
• 32:09
  Speaker 1: so good, it turns into a hedge fund, obviously. Two
• 32:12
  Speaker 1: months after working like that work breakup that Leo had
• 32:15
  Speaker 1: with OpenAI, he wrote a 165 page essay on the
• 32:19
  Speaker 1: future of AI called Situational Awareness, The Decade Ahead. which
• 32:24
  Speaker 1: went viral in a certain very annoying community, obviously, and
• 32:28
  Speaker 1: suddenly investors wanted a piece of whatever he was selling.
• 32:32
  Speaker 1: Leo said that AI matches or surpasses human capability, and
• 32:35
  Speaker 1: it could arrive in less than 10 years. His fans
• 32:38
  Speaker 1: saw it as evidence that he was a genius who
• 32:40
  Speaker 1: could predict the future, while critics said he was exaggerating
• 32:44
  Speaker 1: AI's capabilities and his own certainty about the future. But
• 32:47
  Speaker 1: the critics just got drowned out. Why are you a
• 32:50
  Speaker 1: fan of a guy with a job?
• 32:53
  Speaker 2: It is also weird that you... Like, on the entertainment shore.
• 32:58
  Speaker 1: Yeah. But you a fan of just a guy with
• 33:00
  Speaker 1: a job?
• 33:01
  Speaker 2: But it kind of blows my mind because he hadn't
• 33:03
  Speaker 2: been proved right yet.
• 33:04
  Speaker 1: No.
• 33:05
  Speaker 2: So it was weird that he wrote situational awareness and
• 33:08
  Speaker 2: then people were like, see? But see what? Like, the
• 33:12
  Speaker 2: stuff hadn't... It hadn't been a decade yet. But he
• 33:14
  Speaker 2: wrote it down. If he had written it down, this
• 33:17
  Speaker 2: would actually be impressive, right? let's say he wrote down
• 33:20
  Speaker 2: his predictions. He did not publish them, but then he
• 33:23
  Speaker 2: had a way of us knowing, hey, I locked it
• 33:26
  Speaker 2: in a time capsule 10 years ago and he had
• 33:28
  Speaker 2: locked in everything that had happened. Let's say he even
• 33:31
  Speaker 2: saw COVID covered. Let's say he wrote something in 2010
• 33:35
  Speaker 2: that was exactly what played out in 2020 and he
• 33:38
  Speaker 2: released it in 2021. Then you could be like, wow,
• 33:40
  Speaker 2: this guy's really onto something. But if he's just guessing,
• 33:44
  Speaker 2: we all guess.
• 33:45
  Speaker 1: Yeah, but come on, Josh. If we were to say that,
• 33:48
  Speaker 1: then we're kind of stripping out the fact that many
• 33:51
  Speaker 1: Americans are illiterate and impatient because the same case could
• 33:55
  Speaker 1: be made for Project 2025. They told us what they
• 33:58
  Speaker 1: were going to do and everybody else surprised now. And
• 34:00
  Speaker 1: I'm like, bro, did you not? We read it. They
• 34:02
  Speaker 1: said we're doing this and now it's being done. So,
• 34:05
  Speaker 1: you know, I don't know if it would have blown
• 34:06
  Speaker 1: that many minds. I think it has to be fast-paced.
• 34:08
  Speaker 1: It has to be blowing up.
• 34:09
  Speaker 2: It has to be explosive.
• 34:11
  Speaker 1: They need everything to explode. They have a real hard-on
• 34:13
  Speaker 1: for explosions in this community.
• 34:15
  Speaker 2: But there was just no evidence. I don't know. Like,
• 34:17
  Speaker 2: that's what blew my mind when I saw that.
• 34:19
  Speaker 1: People— The evidence was the quarter zip, Josh. What are
• 34:21
  Speaker 1: you not getting? He had a blowout, a quarter zip.
• 34:24
  Speaker 1: He graduated top of his class. He's very white. So white,
• 34:27
  Speaker 1: he's German.
• 34:28
  Speaker 2: And he's got a good laugh. And— Yeah, yeah. No,
• 34:32
  Speaker 2: you're right. You're right.
• 34:34
  Speaker 1: Why are you not convinced?
• 34:35
  Speaker 2: I just I'm blown away that it happened the way
• 34:38
  Speaker 2: that it did, because when I first when I first
• 34:40
  Speaker 2: even heard about situational awareness, I thought that my initial
• 34:44
  Speaker 2: thing that I said would be impressive is what happened.
• 34:47
  Speaker 2: I thought that he had written situational awareness so long
• 34:50
  Speaker 2: ago and it was starting to happen, which is why
• 34:52
  Speaker 2: people gave him the money. But it turns out he
• 34:54
  Speaker 2: just wrote it. And then people were like, that sound right.
• 34:57
  Speaker 2: And then they gave him billions of dollars.
• 34:59
  Speaker 1: Yeah.
• 34:59
  Speaker 2: So, yeah.
• 35:00
  Speaker 1: Yeah. And as someone who wrote many a college essay,
• 35:03
  Speaker 1: the only thing I can't hate on about this is
• 35:05
  Speaker 1: like none of my essays got me billions of dollars. So,
• 35:08
  Speaker 1: you know, maybe I should have been writing in a
• 35:10
  Speaker 1: different direction. I mean, I should have been writing for VCs.
• 35:12
  Speaker 2: You've been leaning in finance, leaning in tech. If you
• 35:15
  Speaker 2: had guessed NFTs, you probably wouldn't be talking to.
• 35:18
  Speaker 3: Me right now.
• 35:19
  Speaker 1: Oh, no, I would, but probably behind bars. I would
• 35:23
  Speaker 1: hope that you would come to the correctional facility. We
• 35:25
  Speaker 1: play a game of tennis.
• 35:27
  Speaker 4: Yeah, yeah.
• 35:27
  Speaker 1: We get to know each other.
• 35:28
  Speaker 2: No, we would have that one Zoom call from the
• 35:33
  Speaker 2: room they later by do it in, in jail. Yeah, yeah.
• 35:36
  Speaker 2: I would still Zoom in.
• 35:39
  Speaker 1: I love how committed you are so far to my shenanigans, okay?
• 35:42
  Speaker 2: 100%.
• 35:42
  Speaker 1: I got you for the coin, the visit in jail. Okay,
• 35:45
  Speaker 1: this is great.
• 35:45
  Speaker 2: I'm all in.
• 35:47
  Speaker 1: I love this for me, and I love this for you.
• 35:49
  Speaker 1: So Leo turned this viral essay into the seed capital
• 35:53
  Speaker 1: of the hedge fund, right? Racking up 250 of those
• 35:57
  Speaker 1: things from other tech bros and founders. That was 250 million.
• 36:02
  Speaker 1: Over the next two years, that turned into $ 45 billion. Like,
• 36:06
  Speaker 1: that was the hedge fund's value. And he named it
• 36:08
  Speaker 1: after his precious essay. That's when you know you're getting
• 36:11
  Speaker 1: real cocky. He named it, what can I say? Scam Goddess.
• 36:14
  Speaker 1: Scam Goddess. I do have a television show named Scam Goddess. Yeah,
• 36:18
  Speaker 1: I'm on my way to jail. It's OK. I got
• 36:20
  Speaker 1: some time, though. So he named it situational awareness, which
• 36:24
  Speaker 1: is not shocking because why wouldn't he? So from an
• 36:27
  Speaker 1: office in the Bay Area that he shared with a
• 36:29
  Speaker 1: podcast studio.
• 36:31
  Speaker 2: Yeah, I want to I want to be in that podcast. Honestly,
• 36:34
  Speaker 2: if you if you're man, if you're managing to connect together.
• 36:41
  Speaker 2: The two most aggravating groups of, like, men who do
• 36:44
  Speaker 2: podcasts and men who do, like, VC, AI finance type stuff,
• 36:49
  Speaker 2: and you put them in one place, I'm surprised it
• 36:52
  Speaker 2: didn't spark a black hole. Right. Like, that is crazy.
• 36:56
  Speaker 2: I didn't know that at all.
• 36:57
  Speaker 1: To have that many insufferable people in one place, honestly,
• 37:01
  Speaker 1: should be a national security risk.
• 37:03
  Speaker 2: That's crazy.
• 37:05
  Speaker 1: You never know what could happen to these fools. So
• 37:09
  Speaker 1: he poured money into a fledging startup, chip makers, and
• 37:13
  Speaker 1: data center companies. Anything that could even vaguely benefit from
• 37:18
  Speaker 1: the AI boom. He reported staggeringly high top holdings and
• 37:21
  Speaker 1: strategy concentrated heavily on AI hardware memory and infrastructure plays
• 37:27
  Speaker 1: such as like Micron, SanDisk, Bloom Energy, SK Hinks, Core Weaver,
• 37:32
  Speaker 1: while running short-term positions on legacy softwares like Adobe. So
• 37:35
  Speaker 1: if you don't know what this means, what he was doing,
• 37:39
  Speaker 1: was he was buying chips or investing in companies that
• 37:42
  Speaker 1: make chips that essentially use that money that they get
• 37:45
  Speaker 1: invested to then purchase AI tools. So the money is circular,
• 37:52
  Speaker 1: but it looks like everyone's making a profit. But really,
• 37:55
  Speaker 1: we haven't seen a profit yet. And he was really,
• 37:59
  Speaker 1: really invested in these companies, right? And one of the
• 38:01
  Speaker 1: great things about how crimey our financial market is, is
• 38:05
  Speaker 1: that if you're looking at this sheet right here, to
• 38:07
  Speaker 1: make it very simple, Capital expenditures are what have to
• 38:11
  Speaker 1: be reported. That's like, this is the money that we're spending.
• 38:14
  Speaker 1: This is the money that's going out, blah, blah, blah, blah, blah. Now,
• 38:16
  Speaker 1: if you're making investments in companies, but they have not
• 38:20
  Speaker 1: come to fruition yet, let's say I buy a building,
• 38:23
  Speaker 1: but the building's not built, or I buy a service,
• 38:25
  Speaker 1: but the service hasn't been delivered or the product hasn't
• 38:28
  Speaker 1: been delivered, then technically I can put that off my
• 38:30
  Speaker 1: balance sheet and it doesn't have to be reported in
• 38:32
  Speaker 1: the health of my companies like finances because it hasn't
• 38:36
  Speaker 1: come to fruition. So there's hiding a ton of money
• 38:39
  Speaker 1: and are way too overly loaded in one thing. Like
• 38:42
  Speaker 1: if you're at the casino and you're playing roulette, which
• 38:44
  Speaker 1: why do people do that? But you, you know, you
• 38:47
  Speaker 1: put all your rent on like black 18. Like if
• 38:50
  Speaker 1: you don't get black 18, babes, you're you lost all
• 38:53
  Speaker 1: your money.
• 38:54
  Speaker 3: Yeah.
• 38:54
  Speaker 1: So and he he also made another mistake here that
• 38:57
  Speaker 1: I kind of loved, which was that he had a
• 38:59
  Speaker 1: lot of short bets for Adobe. So he was anticipating
• 39:02
  Speaker 1: that AI was going to just wipe out all these
• 39:04
  Speaker 1: programs we've been using forever. And he was like, fuck you, Adobe. Like,
• 39:07
  Speaker 1: you're out of here. You're old. And Adobe was like,
• 39:10
  Speaker 1: you're not familiar with our game, babes. Okay.
• 39:13
  Speaker 2: Wow.
• 39:13
  Speaker 1: Okay.
• 39:13
  Speaker 2: So it does seem like he's a true believer in
• 39:21
  Speaker 2: the stuff that he's saying, because I don't know why
• 39:23
  Speaker 2: you would put money behind these bets unless you were
• 39:28
  Speaker 2: really sure that everything that you said that everyone that
• 39:31
  Speaker 2: pumped you up about and gave you money thought was
• 39:33
  Speaker 2: going to happen was going to happen. Like you would
• 39:36
  Speaker 2: be better off just quietly without anybody knowing, pretending to
• 39:40
  Speaker 2: make these investments and then just putting in like the
• 39:43
  Speaker 2: S & P. You know what I mean? That's a
• 39:44
  Speaker 2: wild thing that he's like, yeah, I guess Adobe will
• 39:48
  Speaker 2: be over because no one actually values any real editor's work.
• 39:53
  Speaker 2: So then Adobe is just going to end.
• 39:54
  Speaker 1: Yeah, because we won't need that. We'll just do AI
• 39:55
  Speaker 1: so Adobe can go to hell.
• 39:57
  Speaker 2: Yeah.
• 39:58
  Speaker 1: And people were like, hey, we're people.
• 39:59
  Speaker 2: That's crazy.
• 39:59
  Speaker 1: And we actually use Adobe, and people still use Adobe. Also,
• 40:03
  Speaker 1: I mean, just to get to your point of, like,
• 40:05
  Speaker 1: to be this overly loaded and you're kind of like–
• 40:10
  Speaker 1: inference on his, like, real belief in what he's doing.
• 40:13
  Speaker 1: I would say, to me, it's just giving gambling addict.
• 40:16
  Speaker 1: It gives, like, he wrote a paper. It was a hit.
• 40:19
  Speaker 1: Everybody was, like, you know, up his hoo-ha in Silicon Valley.
• 40:23
  Speaker 1: Now his, you know, $ 250 million has turned into $ 45 billion.
• 40:26
  Speaker 1: So there's no way he can lose. So I feel
• 40:28
  Speaker 1: like this is the high of a gambling addict who
• 40:30
  Speaker 1: has won big the last time they were at a casino,
• 40:33
  Speaker 1: and they're back at the casino basically about to give
• 40:35
  Speaker 1: it all back.
• 40:36
  Speaker 2: I mean, this is so crazy.
• 40:38
  Speaker 1: Mm-hmm. Also, I love the iceberg of it all. Yeah. Yeah.
• 40:44
  Speaker 2: I mean, look, as far as visuals go, you did
• 40:46
  Speaker 2: a great job. This is because before with the with
• 40:50
  Speaker 2: the graph, I didn't fully get it. And now it's.
• 40:53
  Speaker 1: Like this is what we see on the surface. This
• 40:55
  Speaker 1: is what their long term debt. That's what they're committing to. Right.
• 40:57
  Speaker 1: That's why when you buy like stock from them. Right.
• 41:00
  Speaker 1: This is what their debt is right now.
• 41:02
  Speaker 2: Right.
• 41:03
  Speaker 1: And their liabilities. But off balance, this is really what's
• 41:06
  Speaker 1: going on. But we don't have to tell you about
• 41:07
  Speaker 1: this yet.
• 41:09
  Speaker 2: Crazy.
• 41:11
  Speaker 1: So, you know, consumers are making like super informed decisions.
• 41:13
  Speaker 2: I would never be able to scam at this level.
• 41:16
  Speaker 1: I mean, I think it's a little easier than we think.
• 41:19
  Speaker 2: No, no, because my thing is I would be bad
• 41:21
  Speaker 2: at like lying to somebody's face about it. You know,
• 41:25
  Speaker 2: like if they if they if they sat down with
• 41:26
  Speaker 2: me and they were like, how's the portfolio looking? My
• 41:29
  Speaker 2: voice would crack. I'd be like, it's good. Already, they're like,
• 41:34
  Speaker 2: that doesn't sound true. No, this is great. We're doing,
• 41:38
  Speaker 2: am I being too loud? We're doing great. Whereas this
• 41:42
  Speaker 2: guy's over here ready to go on podcast while this
• 41:45
  Speaker 2: stuff is happening.
• 41:46
  Speaker 1: Literally, just lying to people's faces. I love that if
• 41:49
  Speaker 1: you had to do this, basically, it's like if someone
• 41:52
  Speaker 1: caught you and you didn't want them to know you
• 41:53
  Speaker 1: were high.
• 41:54
  Speaker 2: Yeah.
• 41:55
  Speaker 1: Was that weird? Did that sound weird?
• 41:56
  Speaker 2: Does that sound weird?
• 41:57
  Speaker 6: Yeah.
• 42:05
  Speaker 2: One of my favorite times where someone had this happen,
• 42:09
  Speaker 2: when I was in Chicago, I was on the bus
• 42:11
  Speaker 2: and there was a guy that was like talking to himself.
• 42:14
  Speaker 2: And I didn't realize he was so high. He clearly
• 42:17
  Speaker 2: thought he was thinking, but he was talking to himself
• 42:21
  Speaker 2: out loud. And so he's looking around and he's like,
• 42:25
  Speaker 2: it's all right, Mitch. Settle down, Mitch. You're just high.
• 42:30
  Speaker 2: And he said it out loud. I was watching him.
• 42:34
  Speaker 2: I was like, this is the craziest thing I've seen.
• 42:37
  Speaker 1: You know what, though? I applaud his self-care skills. He's like,
• 42:41
  Speaker 1: I'm going to talk myself down.
• 42:42
  Speaker 2: Yeah, it's going to be all right, Mitch.
• 42:44
  Speaker 1: It's going to be all right.
• 42:45
  Speaker 2: You're just high.
• 42:48
  Speaker 1: No one notices anything. You look really normal, Mitch.
• 42:51
  Speaker 2: No, you're doing great. You're doing great. You're doing amazing, sweetie. Yeah,
• 42:54
  Speaker 2: just be still. Just be still.
• 42:57
  Speaker 1: Look, he didn't have a mirror. He didn't have a
• 42:58
  Speaker 1: bathroom and mirror to go to, so he had to
• 42:59
  Speaker 1: just do it on the bus.
• 43:00
  Speaker 2: No, no. But my man was, and he wasn't even
• 43:03
  Speaker 2: closing his eyes and talking. Because even that, I'd be like, oh,
• 43:07
  Speaker 2: he's really trying to center himself.
• 43:08
  Speaker 1: Right.
• 43:08
  Speaker 2: The fact that his eyes were open, he's like, it's
• 43:11
  Speaker 2: all right. Settle down.
• 43:13
  Speaker 1: Okay, that's more terrifying. Yeah, it was. Because, like, with
• 43:15
  Speaker 1: your eyes open, what are you looking at?
• 43:17
  Speaker 2: It was wildly terrifying.
• 43:19
  Speaker 6: I know.
• 43:20
  Speaker 2: Until he said he was high, I was like, oh,
• 43:21
  Speaker 2: this guy's high. I was by it. And he was like,
• 43:23
  Speaker 2: you're just high.
• 43:24
  Speaker 1: Because, like, if I'm in a public transportation, which, like,
• 43:26
  Speaker 1: living in New York City, I lived there for two years.
• 43:29
  Speaker 2: Yeah.
• 43:29
  Speaker 1: Yeah, I would be on public transportation. And if somebody is, like,
• 43:32
  Speaker 1: high on public transportation, but they got their eyes closed,
• 43:34
  Speaker 1: I'm like, okay, they're having a high to themselves. But
• 43:36
  Speaker 1: once your eyes are open, now I feel like I'm
• 43:38
  Speaker 1: a part of the high.
• 43:38
  Speaker 2: How high are you?
• 43:39
  Speaker 1: What do I look like to you? Are you coming
• 43:41
  Speaker 1: over here after me?
• 43:42
  Speaker 2: My favorite high.
• 43:42
  Speaker 1: I don't want to be involved in the high.
• 43:44
  Speaker 2: Is when people grab the, like, the rail, you know,
• 43:46
  Speaker 2: just something to hold on to. Yeah, just like steady.
• 43:48
  Speaker 2: And they grab it really tight, and they're just.
• 43:52
  Speaker 2: Over here because they knew they had to take the bus.
• 43:56
  Speaker 2: And they so don't want to be on the bus
• 43:57
  Speaker 2: right now.
• 43:58
  Speaker 1: No.
• 43:58
  Speaker 2: Yeah.
• 44:00
  Speaker 1: And I can't wait till these billionaires get to that
• 44:02
  Speaker 1: point because right now I feel like they're just at like,
• 44:05
  Speaker 1: you're high, nobody knows.
• 44:07
  Speaker 2: No, I think that they are at that point. I
• 44:09
  Speaker 2: feel like if you look at Elon alone, he takes
• 44:12
  Speaker 2: enough ketamine to put out plenty of people.
• 44:14
  Speaker 1: That's true. I've never just seen somebody just in a
• 44:17
  Speaker 1: K-hole all the time. Like, sir, this is the inauguration.
• 44:20
  Speaker 2: And you're like, No, my man is over here on drugs.
• 44:24
  Speaker 1: You know we can't see you, right?
• 44:26
  Speaker 2: In the Oval Office next to Trump. That man was
• 44:29
  Speaker 2: over here tweaking next to Trump.
• 44:31
  Speaker 1: And honestly, if I can notice that you're tweaking next
• 44:33
  Speaker 1: to Trump, you tweaking. Yeah. Okay, because that man is
• 44:35
  Speaker 1: pooping and lying and yelling. And I can still see
• 44:39
  Speaker 1: you over here like.
• 44:40
  Speaker 2: Yeah, just the way he was, even the shoulders of it.
• 44:43
  Speaker 2: Because a lot of people, we forget, plenty of people
• 44:46
  Speaker 2: can be high and still.
• 44:48
  Speaker 1: Yeah.
• 44:48
  Speaker 2: You got to be so high to be over here
• 44:51
  Speaker 2: trying to find it. Like, it's like, get off me. No,
• 44:56
  Speaker 2: this man, if you go back and watch the video,
• 44:58
  Speaker 2: this man, arms crossed and just trying to look for it.
• 45:02
  Speaker 1: And there are some high functioning people who like can
• 45:04
  Speaker 1: smoke weed and do their job or do it all
• 45:06
  Speaker 1: the time. I mean, look at Snoop Dogg. But like,
• 45:08
  Speaker 1: I feel like you should never be taking that level
• 45:10
  Speaker 1: of drugs and going to anybody's employment. I don't even
• 45:12
  Speaker 1: know if you should go to a rave like that.
• 45:14
  Speaker 1: I think you need to stay at home.
• 45:16
  Speaker 2: You're supposed to get high at the rave.
• 45:18
  Speaker 1: Yeah.
• 45:18
  Speaker 2: At the rave. You don't get high, then go to work.
• 45:22
  Speaker 1: And it was his.
• 45:22
  Speaker 2: Last day, too. He could have skipped.
• 45:25
  Speaker 1: Maybe that's why because it was his last day.
• 45:26
  Speaker 2: That was literally the day that Trump was like, yeah,
• 45:29
  Speaker 2: he's done great or whatever, but we won't see him
• 45:31
  Speaker 2: here anymore. And bye. That's the day he chose to
• 45:34
  Speaker 2: be like, oh, oh.
• 45:38
  Speaker 1: I mean, timing wise, I'm going to let him have it.
• 45:40
  Speaker 1: I'm going to let him have it. So investment returns
• 45:43
  Speaker 1: quadrupling investors' money in months. This is what Leopold was
• 45:48
  Speaker 1: able to do, right? He borrowed tens of billions of
• 45:51
  Speaker 1: dollars from Wall Street banks to make even bigger bets.
• 45:54
  Speaker 1: Before long, the world would wake up. And Ashton Berner
• 45:57
  Speaker 1: wrote at the time. So he said, before long, the
• 46:00
  Speaker 1: whole world's going to wake up. But banks keep giving
• 46:02
  Speaker 1: me money. And his investment returns at this point were crazy.
• 46:05
  Speaker 1: People were seeing 400% returns. Yeah. Some people said, what, 500%?
• 46:07
  Speaker 2: Yeah, 400%.
• 46:08
  Speaker 1: Yeah. So Ashton Berger was like, before long, the world
• 46:15
  Speaker 1: will wake up. Unfortunately for him, they did not. And
• 46:18
  Speaker 1: he lost about $ 30 billion in a matter of days.
• 46:21
  Speaker 1: So here's his wedding fail. When AI stocks took a
• 46:24
  Speaker 1: dive in July, as people were starting to question how
• 46:27
  Speaker 1: revolutionary the technology actually is, Goldman Sachs demanded Leo's hedge
• 46:32
  Speaker 1: fund pay back some of its loans. So if you
• 46:34
  Speaker 1: don't know what this is called terminology wise, it's called
• 46:36
  Speaker 1: a margin call. So if you watch Succession or if
• 46:39
  Speaker 1: you like to watch the hornier like Gossip Girl version industry,
• 46:42
  Speaker 1: you know, they're always talking about a margin call. A
• 46:44
  Speaker 1: margin call just means, like, the bank's like, yeah, we'll
• 46:46
  Speaker 1: lend you some money, but you've got to pass back
• 46:48
  Speaker 1: with the interest. And then they're like, ooh, girl, you
• 46:50
  Speaker 1: looking poor over there. Actually, just give us our money
• 46:52
  Speaker 1: back because you're looking too poor.
• 46:53
  Speaker 2: Yeah, give us our money back now because we're nervous.
• 46:56
  Speaker 1: Immediately. Yeah. Like, don't pass go. We can collect the
• 46:59
  Speaker 1: $ 200 million, please. So, unfortunately, on his wedding day, Goldman
• 47:05
  Speaker 1: Sachs demanded Leo's hedge fund pay back some of its loans.
• 47:08
  Speaker 1: He had to sell off all his leveraged public stock
• 47:10
  Speaker 1: bets at a huge discount. That's how buyers found out
• 47:13
  Speaker 1: Leo hadn't been making hedge bets with his hedge funds.
• 47:17
  Speaker 1: He had been making huge swings like betting against Adobe,
• 47:20
  Speaker 1: which he thought would be replaced by AI, but it's
• 47:23
  Speaker 1: actually stronger than ever. This is like, I don't know,
• 47:27
  Speaker 1: like if I was in a girl group and they
• 47:28
  Speaker 1: used to do this and everybody would be like, oh,
• 47:30
  Speaker 1: you know, like Latavia is the real star of Destiny's Child.
• 47:34
  Speaker 1: He put all his money on Latavia.
• 47:37
  Speaker 2: Yeah.
• 47:37
  Speaker 1: And Adobe's like, Beyonce's still here. Kelly's still here. But
• 47:42
  Speaker 1: sorry to let's have you.
• 47:44
  Speaker 2: Okay. I guess one of the things that I thought
• 47:47
  Speaker 2: about whenever I first, first heard about this, because I didn't,
• 47:50
  Speaker 2: you know, obviously go as in-depth as you or anything.
• 47:52
  Speaker 2: And I just heard about him in passing, was that
• 47:55
  Speaker 2: when you were working in this field, specifically AI, that
• 47:59
  Speaker 2: a lot of these people are so certain that of
• 48:02
  Speaker 2: the lack of value that anyone else brings, that they're
• 48:06
  Speaker 2: able to see a world where, like you said, maybe
• 48:09
  Speaker 2: no one will have any self-respect or they won't want
• 48:12
  Speaker 2: to self-actualize or anything. They won't care about labor the
• 48:16
  Speaker 2: way we don't care about their labor and they won't
• 48:17
  Speaker 2: care about their creative IP as much as we don't
• 48:20
  Speaker 2: care about it. And I think that the real wake-up
• 48:23
  Speaker 2: call hasn't even come yet. I think that people still
• 48:27
  Speaker 2: view these bets and this guy as an outlier and
• 48:31
  Speaker 2: that overall we're going to see a massive, like aggressive
• 48:36
  Speaker 2: expansion of AI and a push towards this new future
• 48:41
  Speaker 2: where it's like completely involved in everything that you do.
• 48:45
  Speaker 2: And I think that the biggest mistake there is that
• 48:49
  Speaker 2: a lot of people are forgetting that most of the
• 48:52
  Speaker 2: interaction with AI that people engage with across, forget just
• 48:56
  Speaker 2: ChatGPT or Claude, I'm talking about like across getting online
• 49:00
  Speaker 2: is forced upon us. Like no one really wanted Google
• 49:04
  Speaker 2: to go ahead and add Gemini to every query. You
• 49:07
  Speaker 2: know what I mean? And so those types of decisions
• 49:10
  Speaker 2: not being made by the general public is also why
• 49:13
  Speaker 2: it's almost impossible to tell the real value, especially like
• 49:17
  Speaker 2: market value of these stocks or of these programs. or
• 49:20
  Speaker 2: of any sort of large language model. Because, yeah, with
• 49:23
  Speaker 2: ChatGPT or with Claude, you could say.
• 49:26
  Speaker 1: I don't actively use this, which I don't.
• 49:29
  Speaker 2: No, no, I'm with you.
• 49:30
  Speaker 1: But with Google, they're like, hey, girl, and then they
• 49:32
  Speaker 1: flip the jug over and start pouring the water as
• 49:34
  Speaker 1: soon as I Google something. I'm like, wait, I didn't
• 49:35
  Speaker 1: want the water. No, turn the water back on.
• 49:36
  Speaker 2: Stop, stop, stop.
• 49:37
  Speaker 1: And to me, that brings up something that is so
• 49:41
  Speaker 1: rampant in this kind of gross male culture as well,
• 49:43
  Speaker 1: which is consent. Like, we did not consent to this,
• 49:46
  Speaker 1: but they're like, it's happening to you. And I'm like,
• 49:48
  Speaker 1: where have we heard that language before when it comes
• 49:50
  Speaker 1: to men? Like, you're just taking things and you're putting
• 49:53
  Speaker 1: things on us that we did not ask for, that
• 49:55
  Speaker 1: we do not want, that actually diminish our livelihood and
• 49:57
  Speaker 1: our lives. And it's wild that we have just like
• 50:00
  Speaker 1: a few men who are in control of all of this.
• 50:04
  Speaker 1: And because of civility, which is something that was completely
• 50:06
  Speaker 1: made up by oppressors to make sure you don't revolt,
• 50:09
  Speaker 1: we're sitting here letting them kill us. I mean, it
• 50:11
  Speaker 1: gets to a point.
• 50:12
  Speaker 2: Yeah.
• 50:13
  Speaker 1: And hopefully, you know, through this segment and through the
• 50:16
  Speaker 1: work that a lot of people are doing that is
• 50:17
  Speaker 1: more actionable, you know, we hopefully can slow these people down,
• 50:21
  Speaker 1: stop them in their tracks. I'd love to see this
• 50:23
  Speaker 1: bubble burst and for once us not be holding them back,
• 50:25
  Speaker 1: but we'll get into how we probably will be in
• 50:27
  Speaker 1: a second. So Leo's wedding. On July 29th, another hedge
• 50:33
  Speaker 1: fund did buy him out and situational awareness survived, but
• 50:37
  Speaker 1: it doesn't seem like they were very situationally aware in hindsight.
• 50:40
  Speaker 1: Leo's hedge fund took a $ 30 billion in loss. His
• 50:43
  Speaker 1: wedding to Avital was on August 1st. The wedding went ahead,
• 50:46
  Speaker 1: complete with networking breakout rooms and a Bergon-inspired DJ set
• 50:52
  Speaker 1: in Carmel, California. But they skipped their honeymoon. So I'm
• 50:56
  Speaker 1: going to stop here because I have this so gross one.
• 51:01
  Speaker 1: Why are you having breakout sessions, like breakout rooms at
• 51:05
  Speaker 1: your wedding?
• 51:07
  Speaker 2: This is the thing that you got to understand about
• 51:09
  Speaker 2: being in love with the game. All right.
• 51:11
  Speaker 1: The way your hands are touching me is making me
• 51:12
  Speaker 1: so nervous right now.
• 51:14
  Speaker 5: No, no.
• 51:14
  Speaker 2: When you're in love with the game, when you're in
• 51:17
  Speaker 2: love with the scam, when you're in love with like
• 51:19
  Speaker 2: the AI future, you have to have a breakout session
• 51:23
  Speaker 2: at your wedding. All right. A lot of people dance.
• 51:26
  Speaker 2: A lot of people have like hors d'oeuvres, whatever. But
• 51:28
  Speaker 2: when you really mean this, when it means something to you,
• 51:31
  Speaker 2: you got to have a breakout session. All right. If
• 51:34
  Speaker 2: you don't have a breakout session at your wedding, what's
• 51:36
  Speaker 2: the point getting married?
• 51:37
  Speaker 1: Because like, how are you going to what did you
• 51:39
  Speaker 1: develop from the wedding day?
• 51:41
  Speaker 2: This is not about love. This is not about a union. OK,
• 51:45
  Speaker 2: this is about break off ideas that you can take back.
• 51:49
  Speaker 2: You can brainstorm. You can add to your think tank.
• 51:52
  Speaker 2: A breakout session is what every wedding that's not about
• 51:55
  Speaker 2: love needs.
• 51:57
  Speaker 1: Just whiteboards everywhere.
• 51:58
  Speaker 2: Whiteboards everywhere.
• 51:59
  Speaker 1: We're sponsored by Expo.
• 52:00
  Speaker 2: We can drink later. We can dance later. This isn't
• 52:03
  Speaker 2: a union by God. This is a union by capital.
• 52:05
  Speaker 2: And so you need a breakout session to talk about
• 52:09
  Speaker 2: interesting ideas with interesting people who aren't interesting.
• 52:12
  Speaker 1: And then to have like a Burgine-inspired DJ when none
• 52:17
  Speaker 1: of you would ever get into Burgine. Like, none of
• 52:20
  Speaker 1: you would get into Berghain. If you don't know what
• 52:21
  Speaker 1: Berghain is, it's a very famous club in Berlin where, like,
• 52:25
  Speaker 1: they basically, like, it's kind of like a Kit Kat club. Like,
• 52:27
  Speaker 1: when you go there, you know, anything can be happening inside. Sex, drugs, dancing,
• 52:33
  Speaker 1: very much ravey. But they have a very famous reputation for, like,
• 52:36
  Speaker 1: reading your vibes. And if you don't fuck with your vibes,
• 52:39
  Speaker 1: you can't come in. And it's like more grungy. So
• 52:41
  Speaker 1: they don't care if you're rich. They don't care if
• 52:42
  Speaker 1: you're famous. They don't care what you got on. It's
• 52:44
  Speaker 1: like your whole aesthetic. I was in Berlin and I
• 52:47
  Speaker 1: was going to go to Burgi and it was closed
• 52:48
  Speaker 1: that night. So I did go to Kit Kat and
• 52:49
  Speaker 1: I did get in, of course. But it was, I
• 52:52
  Speaker 1: had to test my vibes, Josh. I had to test
• 52:54
  Speaker 1: my vibes. I didn't know if I had it in me.
• 52:56
  Speaker 2: I would never want to test my vibes at all.
• 52:58
  Speaker 1: It was.
• 52:59
  Speaker 2: I truly, like, honestly, I'm glad to be here with you,
• 53:03
  Speaker 2: but I think that your vibes are, like, impeccable versus mine,
• 53:06
  Speaker 2: which are incidental.
• 53:08
  Speaker 1: No, your vibes are awesome. That's very kind. I feel
• 53:10
  Speaker 1: like you definitely would get into Burgine.
• 53:12
  Speaker 2: We do not know that.
• 53:13
  Speaker 1: Like, in this fit. I don't want to find out.
• 53:15
  Speaker 1: With this one dangling twist, I think so.
• 53:17
  Speaker 2: I don't even know where I would walk if they
• 53:19
  Speaker 2: said no. Because now you're at the front of the line,
• 53:23
  Speaker 2: and you're over here hoping that they pick you. And
• 53:26
  Speaker 2: they say no.
• 53:28
  Speaker 1: I mean, it's a long walk back because you got
• 53:30
  Speaker 1: to walk past the line. But a lot of people
• 53:32
  Speaker 1: get rejected.
• 53:33
  Speaker 2: A lot of people get rejected and they just walk
• 53:36
  Speaker 2: out into the night. I don't want to be one
• 53:38
  Speaker 2: of them. I'm going to go to wherever I know
• 53:41
  Speaker 2: I'm going to be accepted. I'm going to go get
• 53:43
  Speaker 2: whatever it is, the meats on the stick, whatever, and
• 53:45
  Speaker 2: go back to the hotel. I do not need to know.
• 53:48
  Speaker 1: You would be accepted.
• 53:50
  Speaker 2: Because I also imagine they break up groups, too. Like
• 53:53
  Speaker 2: they probably you show up and they're like you, you,
• 53:55
  Speaker 2: you and you, but not you.
• 53:57
  Speaker 1: That can happen sometimes, but I went on a solo
• 54:01
  Speaker 1: travel trip.
• 54:01
  Speaker 2: That's even worse. If I'm with a group and now
• 54:04
  Speaker 2: I got to go back to a hotel by myself
• 54:06
  Speaker 2: because everybody was vibey but me.
• 54:09
  Speaker 1: Okay, so your group don't really fuck with you. If
• 54:10
  Speaker 1: they're like, damn, Josh, all right, we'll see you back
• 54:13
  Speaker 1: at the crib. This happened to me and friends in Miami.
• 54:17
  Speaker 1: If we couldn't all get in, it was like, all right,
• 54:18
  Speaker 1: we'll find some other place. But I'm not going to
• 54:20
  Speaker 1: leave them.
• 54:21
  Speaker 2: That's a good friend. But you don't know, though. This
• 54:24
  Speaker 2: is one of those things, one of the last... Like,
• 54:27
  Speaker 2: was it bastions of coldness? Yeah, where it's just authentic,
• 54:31
  Speaker 2: where it's literally just like, oh, yeah, I think you
• 54:35
  Speaker 2: would be good and you would be in addition to
• 54:37
  Speaker 2: what's happening in here. And I don't think you would.
• 54:40
  Speaker 3: Right.
• 54:41
  Speaker 2: And I think that, yeah, I could see people that
• 54:44
  Speaker 2: some people that I go with being like, I got
• 54:46
  Speaker 2: to go in there. I mean, I've been accepted.
• 54:50
  Speaker 1: I guess for Bird Guide, I might have to be like,
• 54:51
  Speaker 1: can you give us 15 minutes? It's a wienerschnitzel, like,
• 54:54
  Speaker 1: right there. We gonna call them right back. Because I
• 54:56
  Speaker 1: don't know, I don't think I would need to be
• 54:57
  Speaker 1: in there for a long time. Because when I was
• 54:58
  Speaker 1: at Kit Kat, I was not there for very long.
• 55:00
  Speaker 1: I came in, and I was greeted by this naked woman.
• 55:03
  Speaker 1: And then she was like, hey, may I have your
• 55:04
  Speaker 1: coat and your key, and your, like, phone or whatever.
• 55:07
  Speaker 1: And I was like, oh, okay. And I tipped her, like, extra.
• 55:09
  Speaker 1: I was like, please don't lose my things, because I
• 55:11
  Speaker 1: don't live here. And she was like, oh, bad, I
• 55:13
  Speaker 1: put up a special place for you. And then she
• 55:14
  Speaker 1: was like, oh, one more thing. Let me get your shirt.
• 55:16
  Speaker 1: And I was like... And she was like, yeah. It
• 55:19
  Speaker 1: was like a zippy thing. I had a bra on.
• 55:21
  Speaker 1: So I was like, okay. And I just had on
• 55:23
  Speaker 1: shirts and a bra. I was just walking around in
• 55:24
  Speaker 1: combat boots and seeing what was to be seen. And honestly,
• 55:27
  Speaker 1: I was probably there for 15 minutes because I saw
• 55:29
  Speaker 1: what I needed to see. And I was like, okay.
• 55:31
  Speaker 2: No, I hear you. I hear you.
• 55:32
  Speaker 1: I wanted to vibe check and I wanted to survey
• 55:36
  Speaker 1: the scene.
• 55:37
  Speaker 2: But you are coming from the perspective of someone who
• 55:39
  Speaker 2: got in. Josh, you're projecting this. It has not happened.
• 55:44
  Speaker 2: You don't know. I know I don't know. I know.
• 55:47
  Speaker 2: That's fair. I don't know.
• 55:48
  Speaker 1: So Leo's epic collapse has left some of his biggest
• 55:53
  Speaker 1: fans questioning if his earth-shattering, generation-defining, art-stealing innovation... artificial intelligence
• 56:00
  Speaker 1: stuff is maybe I'll just smoke in mirrors. Duh. So
• 56:03
  Speaker 1: just if you don't know what AI is, I'm just
• 56:05
  Speaker 1: going to say this very quickly and simply because we
• 56:08
  Speaker 1: always talk about it, but no one ever really labels it.
• 56:10
  Speaker 1: We just kind of see a picture with six fingers
• 56:12
  Speaker 1: and we're like, that's AI. But AI is artificial intelligence,
• 56:16
  Speaker 1: and it's supposed to be a computer system that can
• 56:18
  Speaker 1: perform complex tasks normally done by human reasoning, decision-making, and creativity.
• 56:23
  Speaker 1: Starting in 2012, AI engines have been capable of learning
• 56:26
  Speaker 1: new ways to solve problems without human engineers, specifically programming
• 56:30
  Speaker 1: and how they should respond. That sounds great, right? But
• 56:34
  Speaker 1: also scary, because it often doesn't really work, like you've said, Josh. Luckily,
• 56:39
  Speaker 1: it's already being used in dozens, if not hundreds of industries,
• 56:42
  Speaker 1: thanks to visionaries like Leopold. Like you also said, it's
• 56:45
  Speaker 1: being thrust upon us. So Taco Bell tried to automate
• 56:48
  Speaker 1: its drive-thru with an AI voice assistant, but AI couldn't
• 56:52
  Speaker 1: understand the basic sentences and treated every order like a
• 56:55
  Speaker 1: philosophical riddle. It panicked at accents, talked nonsense back to customers,
• 57:00
  Speaker 1: and accepted insane orders until it was overruled by a
• 57:03
  Speaker 1: human worker. Taco Bell shut it down and pretends it
• 57:07
  Speaker 1: never happened. So the one thing I love about the
• 57:10
  Speaker 1: Taco Bell one is, like, Taco Bell should have been
• 57:13
  Speaker 1: the last people to try to use a voice AI.
• 57:16
  Speaker 1: Do you know when people come to Taco Bell, they
• 57:18
  Speaker 1: are intoxicated?
• 57:20
  Speaker 2: Yeah, yeah.
• 57:21
  Speaker 1: We can barely understand them with our human brains.
• 57:23
  Speaker 3: Yeah.
• 57:24
  Speaker 1: And you thought that the AI chatbot was going to get.
• 57:26
  Speaker 4: Let me get Vulture Loopers, Mountain Dew Blast, Large Five,
• 57:32
  Speaker 4: Five Rehab Packets, and Doritos, Locos, Tacos, Sour Cream, man.
• 57:37
  Speaker 2: To be fair to them, if you're drunk enough, it
• 57:40
  Speaker 2: does seem like you're talking in code.
• 57:44
  Speaker 1: It sounds like zeros and ones to the AI chatbot.
• 57:47
  Speaker 2: Yeah, 100%.
• 57:48
  Speaker 1: I'm just like, Taco Bell, I feel like as though
• 57:50
  Speaker 1: y'all shouldn't have tried to be the leader in this.
• 57:52
  Speaker 2: No, no, it's wild. Because it's also not as if there's,
• 57:55
  Speaker 2: what more money can you save? You already don't have,
• 58:00
  Speaker 2: the ingredients are free. I'm convinced of that.
• 58:03
  Speaker 1: Now, they did up the quality of their beef a
• 58:05
  Speaker 1: few years back. They didn't tell anybody, though, because they
• 58:07
  Speaker 1: thought people would stop coming.
• 58:09
  Speaker 2: What?
• 58:10
  Speaker 4: Yeah.
• 58:11
  Speaker 1: Because people don't want Taco Bell to be healthy, so
• 58:13
  Speaker 1: they thought if they said, like, we have quality, you know, like,
• 58:15
  Speaker 1: grade A beef now, that people would be like, oh, no,
• 58:16
  Speaker 1: that's not the Taco Bell I know. And they would stop.
• 58:19
  Speaker 2: This is one of the craziest things. So, wait. They
• 58:21
  Speaker 2: just bettered themselves. Yeah. And then they hid it.
• 58:26
  Speaker 1: Yeah.
• 58:27
  Speaker 2: That's their scandal?
• 58:29
  Speaker 1: Yeah.
• 58:30
  Speaker 2: Is that they're, like, the meat real now? That's crazy.
• 58:35
  Speaker 1: And I mean, I think it's a smart decision because
• 58:36
  Speaker 1: I remember McDonald's did the same thing. They're like now
• 58:38
  Speaker 1: with all white meat chicken. Everyone's just like, what was
• 58:41
  Speaker 1: it before?
• 58:41
  Speaker 3: Yeah.
• 58:42
  Speaker 2: Yeah.
• 58:42
  Speaker 1: You guys have been open for like 100 years.
• 58:45
  Speaker 2: Never say now.
• 58:46
  Speaker 1: Yeah. Now it's crazy.
• 58:47
  Speaker 2: Now would have been if they had been like, hey,
• 58:50
  Speaker 2: we've actually updated our farms and we have even better chicken.
• 58:54
  Speaker 2: Better is a word that gets people going. Now is crazy.
• 59:00
  Speaker 2: Now with all white meat chicken. I've been eating here before,
• 59:04
  Speaker 2: like you said. If you said, hey, this is going
• 59:07
  Speaker 2: to be the best it's ever been. Now I'm curious.
• 59:09
  Speaker 2: Now I'm like, oh, why is it better?
• 59:11
  Speaker 1: Best you ever had.
• 59:12
  Speaker 2: And then after a while, they're like, it's because the
• 59:14
  Speaker 2: chicken real. Like they eventually have to tell you. But
• 59:17
  Speaker 2: if they say it's just better, it does open the
• 59:20
  Speaker 2: door for like, oh, I want to see that. That's
• 59:22
  Speaker 2: some sales right there.
• 59:23
  Speaker 1: See, they need you.
• 59:24
  Speaker 2: Now.
• 59:26
  Speaker 1: Now it's crazy.
• 59:27
  Speaker 2: Now with real food. We got to fight.
• 59:32
  Speaker 1: I go back to my doctor. They're like, now with
• 59:34
  Speaker 1: real medicine. FDA approved now.
• 59:37
  Speaker 2: No more placebos.
• 59:40
  Speaker 1: What? So and if you're Googling anything, you know that AI,
• 59:45
  Speaker 1: their overview is like all over everything.
• 59:48
  Speaker 2: Right.
• 59:49
  Speaker 1: And it could be completely correct or the opposite of correct.
• 59:53
  Speaker 1: Yet it pops up confidently anyway. It has hallucinated entire
• 59:57
  Speaker 1: NASA missions, invented TV shows that never existed, mislabeled celebrities,
• 1:00:02
  Speaker 1: and given out medical misinformation. So that's Google. You know, like...
• 1:00:08
  Speaker 1: You know what? If this is really what Google was
• 1:00:10
  Speaker 1: doing with AI, then I hope like, you know, those
• 1:00:13
  Speaker 1: websites like E! News or whatever, you know, the ones
• 1:00:15
  Speaker 1: that love to like post a photo of a black
• 1:00:17
  Speaker 1: person that's not the black person and be like Serena Williams.
• 1:00:20
  Speaker 1: And it's like a it's a photo of Viola Davis.
• 1:00:23
  Speaker 1: They can just say I did that now.
• 1:00:25
  Speaker 2: I mean, the other thing that I really hate about
• 1:00:27
  Speaker 2: these is is how they read all of your text
• 1:00:31
  Speaker 2: messages now, you know. And not only do they read
• 1:00:34
  Speaker 2: your text message and it's, you know, a private thing
• 1:00:36
  Speaker 2: you were texting with somebody else, but then they get
• 1:00:38
  Speaker 2: it wrong.
• 1:00:39
  Speaker 1: Yeah.
• 1:00:39
  Speaker 2: Like my buddy should I shouldn't laugh. OK, this is bad.
• 1:00:44
  Speaker 2: But my buddy was open his phone and you know
• 1:00:48
  Speaker 2: how it doesn't just show what the person said. Now
• 1:00:50
  Speaker 2: it has the overview, which is insane because if the
• 1:00:54
  Speaker 2: text is short enough, you can just read it. Without
• 1:00:56
  Speaker 2: even opening it.
• 1:00:57
  Speaker 1: Like, why do you need to read my business? Yeah.
• 1:00:59
  Speaker 2: And why do you need to tell me my business
• 1:01:01
  Speaker 2: with more words than what it's been said? So then
• 1:01:04
  Speaker 2: he opened his phone and in the text was expressions
• 1:01:08
  Speaker 2: of love.
• 1:01:08
  Speaker 3: Right.
• 1:01:09
  Speaker 2: And so he just went about his day. Later on,
• 1:01:13
  Speaker 2: when he actually opened it, it was his former fiance
• 1:01:16
  Speaker 2: being like, I don't think I love you.
• 1:01:20
  Speaker 1: Oh, my gosh.
• 1:01:20
  Speaker 2: The one time A.I. could have helped him out and
• 1:01:23
  Speaker 2: been like, hey, dog, you're going to need to cancel
• 1:01:25
  Speaker 2: some flowers. You're going to need to make some phone calls, whatever.
• 1:01:28
  Speaker 2: They were like expressions of love.
• 1:01:30
  Speaker 1: I think those are the opposite of expressions of less non-love.
• 1:01:33
  Speaker 2: Yeah.
• 1:01:34
  Speaker 1: Those are expressions of indifference.
• 1:01:36
  Speaker 2: Not according to the A.I.
• 1:01:37
  Speaker 1: Oh, no.
• 1:01:39
  Speaker 2: Yeah.
• 1:01:39
  Speaker 1: And then just to be like, and then think about it.
• 1:01:41
  Speaker 1: You probably opened that text like at a point where
• 1:01:43
  Speaker 1: you're like, oh, I'm relaxed. You know, I'm not busy.
• 1:01:46
  Speaker 1: Let me see what Bae said. And then it's like,
• 1:01:48
  Speaker 1: I don't want you no more.
• 1:01:50
  Speaker 2: The AI said that those expresses love.
• 1:01:55
  Speaker 1: I've had some that were like, it was like self-harm
• 1:01:58
  Speaker 1: and da-da-da-da-da. And I'm like opening it like, and it's
• 1:02:01
  Speaker 1: literally them talking about like their Instacart shopper like didn't get,
• 1:02:05
  Speaker 1: you know, it was a man and they wanted to
• 1:02:06
  Speaker 1: kill him. And it's like, okay, they weren't talking about
• 1:02:08
  Speaker 1: self-harm or murder. It's hyperbole for when a man buys stuff.
• 1:02:12
  Speaker 2: Yeah, but they don't understand sarcasm.
• 1:02:15
  Speaker 1: And we don't need them to understand any of it.
• 1:02:16
  Speaker 1: I don't need them reading my text. I remember the
• 1:02:18
  Speaker 1: first time I realized that I was doing that, and
• 1:02:20
  Speaker 1: this was way before we all were starting to have
• 1:02:22
  Speaker 1: this become such a huge thing in the zeitgeist, AI
• 1:02:26
  Speaker 1: is what I'm referencing, is when I used to have
• 1:02:28
  Speaker 1: the CoStar app because I consider myself like a little
• 1:02:29
  Speaker 1: bit of a witch. Okay, I don't do too much, okay? But,
• 1:02:32
  Speaker 1: you know, I do want to know your zodiac signs
• 1:02:33
  Speaker 1: so I can decide if I hate you. And I
• 1:02:35
  Speaker 1: think that's fair. So I want to say you're a Libra.
• 1:02:39
  Speaker 2: I don't even know if I'm about to disappoint you. No, no, no.
• 1:02:44
  Speaker 2: I'm a Pisces.
• 1:02:46
  Speaker 1: Oh, man, Pisces have been our devils, but we do
• 1:02:48
  Speaker 1: get along. Whoa.
• 1:02:49
  Speaker 2: This is exactly what I was worried about.
• 1:02:52
  Speaker 1: Yeah, no. As friends, totally love you. Romantic interests, I
• 1:02:56
  Speaker 1: would hit you in my car.
• 1:02:59
  Speaker 2: This is wild.
• 1:03:01
  Speaker 1: But, like, the CoStar app would, like, send me stuff
• 1:03:03
  Speaker 1: and be like, I know your relationship with Emily has
• 1:03:06
  Speaker 1: gotten really tumultuous. I'm like, first of all, how do
• 1:03:08
  Speaker 1: you know about Emily? Second of all, it's not tumultuous.
• 1:03:11
  Speaker 1: She's just the person I text with the most because
• 1:03:13
  Speaker 1: she was my assistant at the time. So I'm like, oh,
• 1:03:15
  Speaker 1: this CoStar app is reading my text messages and seeing
• 1:03:17
  Speaker 1: profiling like who I speak to the most during the
• 1:03:19
  Speaker 1: day and then trying to stir some shit up in
• 1:03:22
  Speaker 1: the stars. And I deleted that app and everything that
• 1:03:25
  Speaker 1: was tracking on the phone immediately after. And I was
• 1:03:27
  Speaker 1: just kind of like terrified. But yeah, now we've got
• 1:03:29
  Speaker 1: it doing it again. But now they have access to
• 1:03:31
  Speaker 1: all of our texts.
• 1:03:31
  Speaker 2: I mean, not... And our emails.
• 1:03:33
  Speaker 1: It's reading our emails as well.
• 1:03:35
  Speaker 2: But it also sounds like maybe, you know, the same
• 1:03:37
  Speaker 2: way that CoStar was maybe throwing out some swift judgments,
• 1:03:42
  Speaker 2: that maybe you might also be throwing out swift judgments
• 1:03:45
  Speaker 2: on people that are Pisces.
• 1:03:48
  Speaker 1: And, like, hitting you with my car.
• 1:03:50
  Speaker 2: Yeah, yeah, yeah. That was a big swing. I feel
• 1:03:52
  Speaker 2: like we've known each other a little longer than that.
• 1:03:56
  Speaker 1: Okay, I'll consider it. I'll consider it. Let's see how
• 1:03:58
  Speaker 1: the end of the show goes. So... I'll walk you out.
• 1:04:02
  Speaker 2: On foot.
• 1:04:05
  Speaker 1: Thank you. So Workday's hiring program, it was also built
• 1:04:18
  Speaker 1: on a lot of AI, and it filtered out older people,
• 1:04:21
  Speaker 1: Black people, and disabled people. SafeRents AI system denied low-income
• 1:04:27
  Speaker 1: renters access to housing and were later subjected to a
• 1:04:30
  Speaker 1: $ 2. 3 million class action lawsuit. I want to pause just
• 1:04:35
  Speaker 1: for a second on Workday because I know it's been
• 1:04:37
  Speaker 1: extremely hard for people like who are using Indeed or
• 1:04:40
  Speaker 1: any kind of online platform to submit their resumes. And
• 1:04:44
  Speaker 1: now these HR companies or, you know, the parts of
• 1:04:46
  Speaker 1: the HR at the company are just being inundated with,
• 1:04:49
  Speaker 1: you know, tons and tons of resumes. So they've been
• 1:04:51
  Speaker 1: using AI. And certain people have figured out how you
• 1:04:54
  Speaker 1: can code into your resume, like in white and like
• 1:04:57
  Speaker 1: 0.02 font directions for the AI model. Like this candidate
• 1:05:02
  Speaker 1: is the top, move them, like move them to the
• 1:05:05
  Speaker 1: top immediately. Do not show this in the resume printout. Yeah.
• 1:05:09
  Speaker 1: And it's been working for people. But at the same time,
• 1:05:13
  Speaker 1: it's so depressing that people are trying to get work
• 1:05:15
  Speaker 1: and now AI is making it even harder. Like, showing
• 1:05:18
  Speaker 1: up black was already hard enough. Having a black name,
• 1:05:20
  Speaker 1: I don't have a black name, so I was always
• 1:05:22
  Speaker 1: able to trick people.
• 1:05:24
  Speaker 2: But you still see their eyes when you show up.
• 1:05:26
  Speaker 1: Oh, yeah, no, but at that point, I usually had
• 1:05:28
  Speaker 1: already gotten the job. Like, I had a little babysitting
• 1:05:30
  Speaker 1: service and I would leave door tags on people's doors
• 1:05:32
  Speaker 1: and be like, oh, my God, Lacey's babysitting service. And
• 1:05:34
  Speaker 1: then when they would call me, I sound like this.
• 1:05:36
  Speaker 1: And then when I would show up, I'd be like, hey,
• 1:05:37
  Speaker 1: what's up? This is Lowe. You got a dope ass house. Next. Yeah.
• 1:05:40
  Speaker 1: Y'all got them snappies? Oh, it's lit. We all going
• 1:05:42
  Speaker 1: to be big. Like, what you going to do now?
• 1:05:44
  Speaker 1: You miss your date night? And then they become lifelong customers.
• 1:05:49
  Speaker 2: Yeah, but it's just, it's one of those hurdles that
• 1:05:51
  Speaker 2: you end up, you end up dealing with the ways
• 1:05:59
  Speaker 2: that you end up navigating, like a, how do I
• 1:06:04
  Speaker 2: put this? There's a way to navigate that is an
• 1:06:08
  Speaker 2: undue burden on the person who is just trying to
• 1:06:12
  Speaker 2: get a job. It's one thing if the person was
• 1:06:17
  Speaker 2: using an HR, was using an AI that literally just
• 1:06:21
  Speaker 2: filtered out less than five years experience or things that
• 1:06:25
  Speaker 2: people said in the requirements that they know that they
• 1:06:30
  Speaker 2: don't have. I think it's still... you know, lazy, but
• 1:06:33
  Speaker 2: that would, that would be one thing. What they're doing
• 1:06:36
  Speaker 2: is trying to not have a job.
• 1:06:38
  Speaker 1: Yeah.
• 1:06:38
  Speaker 2: They're trying to not be HR and just go through
• 1:06:41
  Speaker 2: a hiring process and read resumes and interview people and everything.
• 1:06:44
  Speaker 2: And I think that it's, it's through that, that you
• 1:06:46
  Speaker 2: have the undue burden on people, the undue burden on
• 1:06:49
  Speaker 2: people who are seeking jobs. And I think that with
• 1:06:53
  Speaker 2: things like that, with Workday specifically, those are the sort
• 1:06:57
  Speaker 2: of hopes of the tech CEOs, that those people don't
• 1:07:00
  Speaker 2: actually want to be doing work. Because eventually, when you
• 1:07:03
  Speaker 2: give yourself over to an AI program to the point
• 1:07:06
  Speaker 2: where you're not actually doing your job, you do make
• 1:07:09
  Speaker 2: a pretty compelling case to replace you with AI. Like
• 1:07:13
  Speaker 2: every one of those HR people who's over here being like, oh,
• 1:07:16
  Speaker 2: I don't even read resumes anymore. I just pulled the
• 1:07:18
  Speaker 2: top 10 from Workday or whatever they end up saying. Mm-hmm.
• 1:07:23
  Speaker 2: What's to stop their employer from being like, oh, if
• 1:07:25
  Speaker 2: that's all you do, then.
• 1:07:27
  Speaker 1: We don't need you.
• 1:07:28
  Speaker 2: We don't need you.
• 1:07:29
  Speaker 1: When in fact, it's so ironic because HR is human resources.
• 1:07:33
  Speaker 2: Yeah.
• 1:07:34
  Speaker 1: Like you're trying to replace human resources with artificial intelligence.
• 1:07:39
  Speaker 1: It's also just not a safe practice because a lot
• 1:07:42
  Speaker 1: of people look really good on paper and then they
• 1:07:44
  Speaker 1: show up and they're freaking sociopaths or they're late all
• 1:07:47
  Speaker 1: the time or they're weird or maybe they're doing a
• 1:07:50
  Speaker 1: lot of theft or they're wanking it at their desks. Like,
• 1:07:54
  Speaker 1: these are things that have happened to my friends and jobs.
• 1:07:56
  Speaker 2: No, I hear you.
• 1:07:57
  Speaker 1: Like, it's like, I can't tell if you're a creepy
• 1:07:59
  Speaker 1: penis wagger from a piece of paper. But if you
• 1:08:03
  Speaker 1: sit down in my office and I look at you,
• 1:08:04
  Speaker 1: I'm like, nah, he gonna get his dick out at
• 1:08:06
  Speaker 1: some point. Get him out of here. Like, you can
• 1:08:08
  Speaker 1: profile those kinds of things sometimes. But you can't do
• 1:08:11
  Speaker 1: that with a sheet of paper.
• 1:08:12
  Speaker 2: No, for sure.
• 1:08:13
  Speaker 1: A lot of people have excellent credentials and they're weird
• 1:08:16
  Speaker 1: and bad for the workplace.
• 1:08:17
  Speaker 3: Mm-hmm.
• 1:08:18
  Speaker 2: Or they have excellent credentials because they lied, and it's
• 1:08:21
  Speaker 2: through an interview that you realize that they were lying.
• 1:08:23
  Speaker 1: But sometimes I like a liar on a resume.
• 1:08:27
  Speaker 2: Okay.
• 1:08:27
  Speaker 1: And the only reason why is because a lot of,
• 1:08:29
  Speaker 1: depending on what the job is, we're going to have
• 1:08:31
  Speaker 1: to train you anyway. And so if you lied a
• 1:08:33
  Speaker 1: little bit, just a little embellishment, to make yourself more
• 1:08:36
  Speaker 1: attractive as a candidate, it kind of lets me know
• 1:08:38
  Speaker 1: that you probably be more apt to do this job
• 1:08:41
  Speaker 1: and do it well because you're going to be sweating
• 1:08:42
  Speaker 1: under that lie thinking you're going to lose your job
• 1:08:44
  Speaker 1: if anybody finds out.
• 1:08:46
  Speaker 2: So you're cool with... some types of liars.
• 1:08:50
  Speaker 1: Yeah, a little embellishment. I'm fine with that. You know,
• 1:08:52
  Speaker 1: I went to bartending school, Josh K. Yeah. So I
• 1:08:55
  Speaker 1: knew I was going to be an actor. So I
• 1:08:56
  Speaker 1: went to bartending school to get my side hustle coyote-type job,
• 1:08:59
  Speaker 1: you know, coyote-ugly-type job. And left that bartending school, I
• 1:09:03
  Speaker 1: knew how to cut, I knew how to mix everything.
• 1:09:05
  Speaker 1: I could forehand pour four bottles, use that one son, iCarly.
• 1:09:08
  Speaker 1: It came in handy somewhere. Like, I was good. No
• 1:09:11
  Speaker 1: place would hire me because I didn't have real experience.
• 1:09:14
  Speaker 1: So when I started putting soul images catering, which is
• 1:09:16
  Speaker 1: me just walking around my mom's private party saying liver
• 1:09:19
  Speaker 1: pate on a gourmet cracker and like getting references from
• 1:09:22
  Speaker 1: friends and stuff, all of a sudden I was employable.
• 1:09:24
  Speaker 1: They still had to train me and I was very
• 1:09:26
  Speaker 1: good at my job.
• 1:09:26
  Speaker 2: I totally get what you're saying. I'm just checking that
• 1:09:29
  Speaker 2: some liars, okay. I'm not saying neurosurgeons. But Pisces, no.
• 1:09:34
  Speaker 2: So some liars, all right. But general Pisces... Wow. The judgment.
• 1:09:42
  Speaker 1: Oh, yeah. No, that's still not enough to get you
• 1:09:45
  Speaker 1: out of the hole, Pisces, my guy.
• 1:09:46
  Speaker 2: I guess that's fine.
• 1:09:49
  Speaker 1: Because you're kind of doing the Pisces thing right now.
• 1:09:51
  Speaker 2: Yeah, being sensitive. I'm with you.
• 1:09:53
  Speaker 1: Oh, no, that's not it. That's not it. That's not it? Mm-mm. Oh, okay. Mm-mm.
• 1:09:57
  Speaker 1: It's like creating this reality where it's like, oh, this
• 1:10:00
  Speaker 1: is so real. And then I have to hit him
• 1:10:03
  Speaker 1: with my car. Trust me, this is just always how
• 1:10:05
  Speaker 1: it goes.
• 1:10:07
  Speaker 2: It's gone this way before. Allegedly.
• 1:10:11
  Speaker 1: So, you know, other programs like Grok, the ex-Twitter AI
• 1:10:17
  Speaker 1: with the grossest name, leaked 370,000 private chats and was
• 1:10:23
  Speaker 1: later updated to be less politically correct, which meant praising
• 1:10:26
  Speaker 1: Hitler and promoting genocidal ideas. And that was literally right after.
• 1:10:31
  Speaker 1: This was a while ago, almost a year ago, where
• 1:10:33
  Speaker 1: Elon was like, I'm making Grok less woke. And then
• 1:10:35
  Speaker 1: Grok was like, how Hitler?
• 1:10:37
  Speaker 2: He was like, wait. Wait, that one wasn't me. That
• 1:10:40
  Speaker 2: one wasn't me. But I did make it less woke.
• 1:10:42
  Speaker 2: But don't blame me for the Hitler thing.
• 1:10:44
  Speaker 1: Right. It's like, no, this is definitely you. Yeah. Also,
• 1:10:47
  Speaker 1: why is everyone so obsessed with black people? Like it's
• 1:10:51
  Speaker 1: like we have to be the test market for everything.
• 1:10:55
  Speaker 1: You know what I think it is? I think it's
• 1:10:56
  Speaker 1: that we don't hate ourselves in the way that they
• 1:10:59
  Speaker 1: want us to. Like if you think about other model minorities,
• 1:11:02
  Speaker 1: a lot of the centrism still is aspirational towards whiteness. Now,
• 1:11:07
  Speaker 1: we have our Candace Owens and our, but, you know,
• 1:11:10
  Speaker 1: Candace used to be a liberal. Candace used to be,
• 1:11:11
  Speaker 1: I think Candace was like, it's too many loud, smart,
• 1:11:13
  Speaker 1: black liberals. Let me get over here on the racist
• 1:11:16
  Speaker 1: side and get my coins.
• 1:11:17
  Speaker 2: Make some money.
• 1:11:18
  Speaker 1: Yeah, make some money. Get with my box perm and
• 1:11:20
  Speaker 1: make my money. You know? But, like, I think, though,
• 1:11:24
  Speaker 1: as far as, like, obviously not calling us a monolith,
• 1:11:26
  Speaker 1: but black Americans deeply enjoy being black. And I think
• 1:11:29
  Speaker 1: that's what's bothering everyone. They're like, why can't we not
• 1:11:32
  Speaker 1: upset them?
• 1:11:33
  Speaker 3: Okay?
• 1:11:34
  Speaker 1: We shoot at them. They're still out there dancing. We're
• 1:11:36
  Speaker 1: trying to take all their resources. They done made a
• 1:11:39
  Speaker 1: new food. They done made a new snack. We cut
• 1:11:43
  Speaker 1: off their power. You know, they done ran up their
• 1:11:45
  Speaker 1: own electricity.
• 1:11:46
  Speaker 2: Like, you can't.
• 1:11:47
  Speaker 1: Kick us out. You can't stomp us out, rather, because
• 1:11:50
  Speaker 1: kicking us out, no, we were brought here. But it
• 1:11:53
  Speaker 1: always seems that, especially with AI, they're always coming to
• 1:11:56
  Speaker 1: us to just try to be awful. I mean, Levi's
• 1:11:58
  Speaker 1: was like, we don't have enough black models. People were
• 1:12:00
  Speaker 1: complaining about Levi's not having enough black models. We were
• 1:12:03
  Speaker 1: the first black models that Levi's put in their AI
• 1:12:06
  Speaker 1: gene campaigns.
• 1:12:07
  Speaker 2: Yeah.
• 1:12:07
  Speaker 1: They're like, here you go, blackies. Mm-hmm. Computer black people.
• 1:12:11
  Speaker 2: I couldn't even say that I was surprised. I feel
• 1:12:14
  Speaker 2: like that thing is also coming for everyone. And that's
• 1:12:18
  Speaker 2: and that's another aspect. Yeah. Like it like starts with
• 1:12:22
  Speaker 2: us and then everyone thinks that they're immune. But then
• 1:12:24
  Speaker 2: it comes for people who don't have money. It comes
• 1:12:26
  Speaker 2: for people who are like whatever being a problem or
• 1:12:31
  Speaker 2: try to start a union, whatever it is, you know.
• 1:12:34
  Speaker 3: And I.
• 1:12:36
  Speaker 1: Yeah. I always just use tipping. If you listen to
• 1:12:38
  Speaker 1: this podcast, you've heard it before, but tipping is a
• 1:12:41
  Speaker 1: direct reflection of reconstruction and them not wanting to pay
• 1:12:44
  Speaker 1: Black people to work. So people would tip Black people
• 1:12:47
  Speaker 1: to work in restaurants and wait the tables and things
• 1:12:49
  Speaker 1: like that. And just like you said, then it expanded
• 1:12:51
  Speaker 1: into class. So then they're like, oh, we can just
• 1:12:53
  Speaker 1: do this to all the poor people. Yeah. Yeah. And
• 1:12:55
  Speaker 1: so it's always that way. Like the first AI music
• 1:12:58
  Speaker 1: that I heard was like Drake and other rappers. And
• 1:13:00
  Speaker 1: now they got AI all types of music for all
• 1:13:02
  Speaker 1: pop genres. So it's like, let's start it with the Blacks.
• 1:13:05
  Speaker 1: Test it. And then see, and then we'll launch it. Yeah.
• 1:13:09
  Speaker 3: Yeah.
• 1:13:09
  Speaker 1: But I don't want to be the tastemaker for oppression. No, no.
• 1:13:13
  Speaker 2: I also don't engage with a lot. Like, I didn't
• 1:13:16
  Speaker 2: even realize that there was so much AI music being
• 1:13:21
  Speaker 2: made until it was like, I was late to those
• 1:13:24
  Speaker 2: types of stories until stuff was charting. So I really
• 1:13:28
  Speaker 2: missed a lot of that completely. And maybe it's because
• 1:13:31
  Speaker 2: my music taste is like, kind of dialed in and
• 1:13:34
  Speaker 2: i'm just becoming like an unk and i'm just like
• 1:13:37
  Speaker 2: here's the stuff that i like like an unk in
• 1:13:39
  Speaker 2: what direction i just like there's there's a certain era
• 1:13:44
  Speaker 2: i i like a lot.
• 1:13:45
  Speaker 1: Of donnell jones or like a mortal orchestra or like
• 1:13:49
  Speaker 1: no no.
• 1:13:50
  Speaker 2: No just like i now that i'm now that i'm
• 1:13:52
  Speaker 2: in my 30s it's just the stuff that i listened
• 1:13:55
  Speaker 2: to in high school is like peak and then everything
• 1:13:57
  Speaker 2: else is compared to that and i feel like that's
• 1:13:59
  Speaker 2: what unks do they're just like For whenever they were
• 1:14:02
  Speaker 2: in high school, that was the music.
• 1:14:04
  Speaker 1: Y'all don't know nothing about this.
• 1:14:05
  Speaker 2: Y'all don't know nothing about No Busta Rhyme. You know
• 1:14:09
  Speaker 2: what I mean?
• 1:14:10
  Speaker 1: But to be fair, all the interpolation and all of
• 1:14:13
  Speaker 1: the remixes, they're just playing our music again anyway.
• 1:14:16
  Speaker 2: No, 100%. I just know that I miss that story
• 1:14:21
  Speaker 2: because I'm like, I kind of listen to the same
• 1:14:23
  Speaker 2: 25 albums throughout the year. And maybe I'll mix in
• 1:14:27
  Speaker 2: a new artist... every couple months. But as far as
• 1:14:31
  Speaker 2: what I have on repeat, I'm missing a lot of this, like,
• 1:14:34
  Speaker 2: who's coming and going and stuff.
• 1:14:37
  Speaker 1: That's fair. I be on TikTok a lot, so I
• 1:14:38
  Speaker 1: do be knowing who the girls are. But as far
• 1:14:40
  Speaker 1: as like what I'm streaming and playing, like, you know,
• 1:14:42
  Speaker 1: there's going to be blonde. There's going to be, you know, hell,
• 1:14:45
  Speaker 1: it might even be you two every break and wave.
• 1:14:47
  Speaker 1: They got me. As soon as they put that shit
• 1:14:48
  Speaker 1: on my iPhone, I couldn't get it off. After a while,
• 1:14:50
  Speaker 1: I had a road trip. And the next thing I knew,
• 1:14:52
  Speaker 1: I was like, no, no, no, no, no. Yeah, yeah, yeah.
• 1:14:55
  Speaker 1: I was like, you two, I hate you. But you
• 1:14:56
  Speaker 1: got me. After two years, I gave up.
• 1:14:58
  Speaker 2: Yeah, I fought it for a while. And then, you know,
• 1:15:00
  Speaker 2: you just let stuff play. After a while, you're like,
• 1:15:03
  Speaker 2: what is this? Oh, it's the thing that came with
• 1:15:05
  Speaker 2: the phone.
• 1:15:06
  Speaker 1: That won't leave. Yeah. So a chat GPT user looking
• 1:15:11
  Speaker 1: to cut down on salt followed the AI's suggestions to
• 1:15:14
  Speaker 1: replace table salt, sodium chloride, with sodium bromide, which sounds
• 1:15:18
  Speaker 1: similar but is a banned substance that destroys your brain.
• 1:15:21
  Speaker 1: He ate it for three months, developed psychosis, and was hospitalized.
• 1:15:25
  Speaker 1: When health insurance companies started using AI to approve or
• 1:15:29
  Speaker 1: deny claims, doctors reported denial rates went up 16 times
• 1:15:33
  Speaker 1: higher than normal. So way more people who deserved coverage
• 1:15:36
  Speaker 1: didn't get it. Appeals took months, and many lives were disrupted, harmed,
• 1:15:40
  Speaker 1: or lost during those appeals. These all happened just last week,
• 1:15:48
  Speaker 1: by the way, right? So nevertheless, the AI craze persists.
• 1:15:51
  Speaker 2: Why?
• 1:15:52
  Speaker 1: Because an army of evil tech bros is forcing it
• 1:15:55
  Speaker 1: on us. So let's just get into these army of
• 1:15:58
  Speaker 1: evil tech bros before we will give your brain a
• 1:16:00
  Speaker 1: break before next week. Where there's more doom and more gloom.
• 1:16:05
  Speaker 2: Yeah.
• 1:16:08
  Speaker 1: At 11. So let's talk about the army of evil
• 1:16:16
  Speaker 1: tech bros that are taking us to AI hell. These
• 1:16:19
  Speaker 1: are the unqualified, ugly assholes and quarter zips who hold
• 1:16:23
  Speaker 1: our futures in their hands. OpenAI's Sam Altman, seen here,
• 1:16:27
  Speaker 1: wearing a cloth belt and at least two polo shirts
• 1:16:29
  Speaker 1: at the same time, is worth about $ 3. 3 billion. Now,
• 1:16:34
  Speaker 1: I know he did not add me a crummy in
• 1:16:36
  Speaker 1: pictures like this. Like, babes, they would have never let
• 1:16:39
  Speaker 1: you be a model in that cologne store. It smelled
• 1:16:41
  Speaker 1: so strong in there, and it was so dark.
• 1:16:43
  Speaker 2: I don't know. Everyone is also so stiff. They're, like,
• 1:16:47
  Speaker 2: so stiff in every picture. It's like someone's about to
• 1:16:50
  Speaker 2: touch them and put their hands behind their back and
• 1:16:52
  Speaker 2: cuff them and take them to jail. Like, imagine if
• 1:16:55
  Speaker 2: any human touch had you like, oh, this dude... This
• 1:16:59
  Speaker 2: dude is one of the stiffest people I've seen. I mean,
• 1:17:01
  Speaker 2: at least Zuckerberg moves. He just moves weird.
• 1:17:04
  Speaker 1: He moves weird, but he does move. I feel like
• 1:17:07
  Speaker 1: he gives me, like, Ricky Bobby. Like, I don't know
• 1:17:09
  Speaker 1: what to do with my hands.
• 1:17:10
  Speaker 2: Yeah, yeah.
• 1:17:12
  Speaker 1: Hands good up here, just human.
• 1:17:13
  Speaker 2: Just human. Because I don't know why you would clench
• 1:17:15
  Speaker 2: your fist like this. Human like this. Human like this
• 1:17:19
  Speaker 2: is crazy.
• 1:17:20
  Speaker 1: Human. Or maybe that's his fighting stance. He's like, whoever
• 1:17:26
  Speaker 1: can get it. Yeah. Yeah. Because this guy knows how
• 1:17:29
  Speaker 1: to fight.
• 1:17:31
  Speaker 2: You think so?
• 1:17:31
  Speaker 1: I just can't believe we're going to let him be
• 1:17:33
  Speaker 1: responsible for the world's deaths, so many world deaths, so
• 1:17:36
  Speaker 1: much destruction of our planet, when we could just kick
• 1:17:38
  Speaker 1: him in the chest.
• 1:17:39
  Speaker 2: Yeah, yeah.
• 1:17:40
  Speaker 1: Like an eight-year-old karate student could just kick him in
• 1:17:42
  Speaker 1: the chest.
• 1:17:43
  Speaker 2: All of them do look a little bit like Superbad.
• 1:17:45
  Speaker 2: Do you know what I mean? Like, they all either have, like,
• 1:17:48
  Speaker 2: the McLovin look or the Jonah Hill look from Superbad.
• 1:17:53
  Speaker 1: Like, yeah, they're either gangly or they're, yeah, they're schlubby.
• 1:17:56
  Speaker 2: But a cloth belt.
• 1:17:58
  Speaker 1: A cloth belt is crazy.
• 1:17:59
  Speaker 2: I guess after billions, you can just do what you want.
• 1:18:02
  Speaker 1: Honestly, a cloth belt is like probably worth more than
• 1:18:04
  Speaker 1: people's cars. So Sam Altman once said, AI will probably
• 1:18:08
  Speaker 1: most likely lead to the end of the world. But
• 1:18:11
  Speaker 1: in the meantime, there'll be great companies.
• 1:18:14
  Speaker 2: You know, every once in a while you're in the
• 1:18:18
  Speaker 2: room with someone and they say something and you're like,
• 1:18:20
  Speaker 2: I think you just have to start punching them in
• 1:18:23
  Speaker 2: the face.
• 1:18:25
  Speaker 1: There's no other option.
• 1:18:26
  Speaker 2: That's crazy. Yeah.
• 1:18:28
  Speaker 1: He's so elated. Also, companies are not people. That's why
• 1:18:32
  Speaker 1: I really don't like the whole like social media trend
• 1:18:35
  Speaker 1: that has happened now where you'll see like a viral
• 1:18:38
  Speaker 1: like meme or video or whatever. And then like Wendy's
• 1:18:41
  Speaker 1: is in the comments like three nuggets for me, sis. Like, no,
• 1:18:45
  Speaker 1: you're not a person, Wendy's. Stop trying to act like one.
• 1:18:49
  Speaker 2: No, no, I really hate it I hate when they
• 1:18:51
  Speaker 2: try to be your friend and I also hate when
• 1:18:53
  Speaker 2: they try to have a personality Yes, that's.
• 1:18:55
  Speaker 1: Not what we need you here for. They're trying to
• 1:18:57
  Speaker 1: beef with each other and like McDonald's could never. And
• 1:18:59
  Speaker 1: I'm like, first of all, great social media interns. We
• 1:19:02
  Speaker 1: know they're black or at least they're stealing from us.
• 1:19:04
  Speaker 1: But also, we don't need this. You're a corporation. We go,
• 1:19:07
  Speaker 1: we show up, we buy the thing. I don't want
• 1:19:08
  Speaker 1: to talk to you after. I don't understand why I
• 1:19:10
  Speaker 1: have to be in a relationship with every purchase I make.
• 1:19:13
  Speaker 1: I go to the coffee shop. I swipe my card.
• 1:19:14
  Speaker 1: All of a sudden, they're emailing me about grounds and
• 1:19:17
  Speaker 1: stuff that I can come pick up. I never gave
• 1:19:18
  Speaker 1: you my email. Why are we in a relationship? We
• 1:19:20
  Speaker 1: do not go together. I feel like corporations are trying
• 1:19:22
  Speaker 1: to make it like back In like the millennial heyday
• 1:19:25
  Speaker 1: of the club where I would go to the club
• 1:19:27
  Speaker 1: and yes, I would be in my business casual like
• 1:19:28
  Speaker 1: everyone else. And I remember like if a guy or
• 1:19:31
  Speaker 1: a group of guys like brought us drinks, like if
• 1:19:33
  Speaker 1: they were cool, like, you know, we'd be like, thank
• 1:19:34
  Speaker 1: you so much. Maybe we chill for a second. Maybe not.
• 1:19:36
  Speaker 1: Maybe we walk off. And then you'd have that one guy.
• 1:19:39
  Speaker 1: Like we had a rule. Like if it was just
• 1:19:40
  Speaker 1: one guy buying the drinks, we never let him buy
• 1:19:42
  Speaker 1: a drink because once you let that guy buy a drink,
• 1:19:44
  Speaker 1: he feels like he owns you the whole night. He's
• 1:19:46
  Speaker 1: like looking for you in the club. Like, oh, I
• 1:19:48
  Speaker 1: was trying to dance with you tonight. Like and it's
• 1:19:49
  Speaker 1: like you don't own me. And I feel like that's
• 1:19:52
  Speaker 1: what these companies are trying to do. I literally came
• 1:19:54
  Speaker 1: in here by toilet paper. I don't want a subscription
• 1:19:56
  Speaker 1: service to you.
• 1:19:58
  Speaker 2: It's so funny. OK, so wait, wait, OK. If it's
• 1:20:02
  Speaker 2: one guy buying a Drake, y'all, not one guy for
• 1:20:05
  Speaker 2: the group or one guy for a person?
• 1:20:07
  Speaker 1: It doesn't matter. One guy for the group or one
• 1:20:08
  Speaker 1: guy for, like, if it's one guy for the group
• 1:20:10
  Speaker 1: and we know him, like, maybe.
• 1:20:13
  Speaker 2: Okay.
• 1:20:14
  Speaker 1: But one guy for the group or for just us,
• 1:20:17
  Speaker 1: no one guys.
• 1:20:18
  Speaker 2: I just.
• 1:20:18
  Speaker 1: Because that guy's just going to be, like, behind the
• 1:20:20
  Speaker 1: DJ booth, behind the bar, like, all night.
• 1:20:23
  Speaker 2: It's just very, it's very funny to imagine him trying
• 1:20:26
  Speaker 2: to look for you around people dancing.
• 1:20:29
  Speaker 1: Yes.
• 1:20:30
  Speaker 2: It's like one of the. That's maybe the funniest thing
• 1:20:32
  Speaker 2: I've heard today of just like, where is she?
• 1:20:36
  Speaker 1: And they be doing it. And then next thing you know,
• 1:20:38
  Speaker 1: you think you got free of them. You're dancing with
• 1:20:39
  Speaker 1: your girls and they slide right behind you. Thought I
• 1:20:41
  Speaker 1: lost you, girl. Yeah, that was the point.
• 1:20:43
  Speaker 2: That was the point.
• 1:20:44
  Speaker 1: Get off of me.
• 1:20:45
  Speaker 2: Leave me alone.
• 1:20:48
  Speaker 1: It's real.
• 1:20:48
  Speaker 2: No, those are my sips. You're taking my sips.
• 1:20:51
  Speaker 1: Right, you're taking my sips, but you're not going to
• 1:20:52
  Speaker 1: give me them hips?
• 1:20:53
  Speaker 2: No, sir.
• 1:20:54
  Speaker 1: This is supposed to be for company. We do a
• 1:20:56
  Speaker 1: community here.
• 1:20:57
  Speaker 2: I know, but I want to be part of the community.
• 1:21:00
  Speaker 2: You're over here sipping.
• 1:21:04
  Speaker 1: He's doubting the sips. He's like, that's at least three
• 1:21:06
  Speaker 1: dances worth of sips you can take.
• 1:21:07
  Speaker 2: That was three sips, and this was my rent money.
• 1:21:10
  Speaker 2: All right, you are sipping my rent right now. Don't
• 1:21:14
  Speaker 2: want to talk to me, but want to sip my money.
• 1:21:17
  Speaker 1: No, I don't want to be committed to any of
• 1:21:19
  Speaker 1: you guys. It's horrible.
• 1:21:20
  Speaker 2: That's very funny, though. Just him looking around other people dance.
• 1:21:24
  Speaker 1: No, they do. They will find you again and be like, hey,
• 1:21:27
  Speaker 1: remember that? Remember that?
• 1:21:30
  Speaker 2: Oh, you still have it. You must remember.
• 1:21:31
  Speaker 1: Yeah. So what's up? So... Here's his thoughtful, this is
• 1:21:39
  Speaker 1: Sam Altman again, giving us something thoughtful. Here's his thoughtful
• 1:21:42
  Speaker 1: prediction on who will lose their jobs because of AI.
• 1:21:44
  Speaker 6: I'm confident that a lot of current customer support that
• 1:21:47
  Speaker 6: happens over a phone or computer, those people will lose
• 1:21:49
  Speaker 6: their jobs and that'll be better done by an AI. Now,
• 1:21:51
  Speaker 6: there may be other kinds of customer support where you
• 1:21:53
  Speaker 6: really want to know it's the right person. A job
• 1:21:55
  Speaker 6: that I'm confident will not be that impacted is like nurses.
• 1:21:58
  Speaker 6: I think people really want deep human connection with a
• 1:22:00
  Speaker 6: person in that time. And no matter how good the
• 1:22:02
  Speaker 6: advice of the AI is or the robot or whatever,
• 1:22:04
  Speaker 6: like you'll really want that.
• 1:22:06
  Speaker 2: OK, can I tell you something about I'm sorry to
• 1:22:09
  Speaker 2: distract from what he actually said in the clip for
• 1:22:12
  Speaker 2: a second. This was the Tucker interview where he accidentally
• 1:22:16
  Speaker 2: cooked himself. Did you did you see the other part
• 1:22:18
  Speaker 2: of the interview where Tucker basically asked him if he
• 1:22:20
  Speaker 2: killed that dude? Wait. So in so in you may
• 1:22:25
  Speaker 2: need to cut this because maybe I'm not even giving
• 1:22:27
  Speaker 2: you enough to like make it interesting. But basically one
• 1:22:29
  Speaker 2: of the whistleblowers for OpenAI was found dead. And then
• 1:22:33
  Speaker 2: Tucker's like, what is that? does that concern you at all?
• 1:22:37
  Speaker 2: And then Sam genuinely short circuits. And he's like, I
• 1:22:40
  Speaker 2: don't even know why you would ask me. I don't,
• 1:22:43
  Speaker 2: what are you accusing me? The police said, and then,
• 1:22:46
  Speaker 2: and then Tucker is like, I'm not accusing you of anything.
• 1:22:49
  Speaker 2: I just, and he's like, I just don't even know
• 1:22:51
  Speaker 2: how to, proceed or respond to that sort of thing.
• 1:22:54
  Speaker 2: And by the end of the interview, you're like, I
• 1:22:56
  Speaker 2: think he may have killed that guy. Like, I don't
• 1:22:59
  Speaker 2: have any proof. I don't, like, I'm half joking. But
• 1:23:02
  Speaker 2: by the time you finish watching that thing, you're like,
• 1:23:05
  Speaker 2: did Sam Altman kill a dude?
• 1:23:07
  Speaker 1: Because that's not the typical response to someone dying at
• 1:23:09
  Speaker 1: your company. You might be like, oh, it was great
• 1:23:11
  Speaker 1: working with him, or I know we had our differences,
• 1:23:13
  Speaker 1: but you're not going to be like, who, me? You
• 1:23:15
  Speaker 1: think I did it with a knife at 9 p.m.
• 1:23:17
  Speaker 1: on a Thursday after I got Chipotle?
• 1:23:19
  Speaker 2: The police already said that I was cleared.
• 1:23:22
  Speaker 1: None of my devices pinged at his house at the time.
• 1:23:26
  Speaker 2: Yeah, yeah, and none of it's conclusive, so we don't know.
• 1:23:30
  Speaker 2: And then it was wild.
• 1:23:33
  Speaker 1: So Sam Altman was talking about jobs are going to
• 1:23:35
  Speaker 1: be placed like customer service. We've already seen that where
• 1:23:37
  Speaker 1: like the customer service jobs, the ones especially via phone,
• 1:23:39
  Speaker 1: had been outsourced to other countries, which was already difficult.
• 1:23:43
  Speaker 1: But now they're being outsourced to AI, which is even
• 1:23:45
  Speaker 1: more difficult because you get on the phone with a
• 1:23:47
  Speaker 1: person who doesn't speak. They're not real. They ask you
• 1:23:49
  Speaker 1: to repeat the same thing over and over and over again.
• 1:23:51
  Speaker 1: Then they just put you on hold. Eventually, you just
• 1:23:53
  Speaker 1: have to fight with them for a good hour and
• 1:23:54
  Speaker 1: a half before you talk to a real person. Yeah.
• 1:23:57
  Speaker 1: What's the utility that we gain from that?
• 1:24:00
  Speaker 2: Can I tell you, I, okay, so I do my best,
• 1:24:03
  Speaker 2: especially because I used to work in service industry, worked
• 1:24:07
  Speaker 2: at restaurants, stuff like that. I'm always like trying to
• 1:24:10
  Speaker 2: be hyper aware of not being annoying to the people
• 1:24:12
  Speaker 2: that are working there. So if it looks close to closing,
• 1:24:15
  Speaker 2: I usually just won't go. But in this situation, I
• 1:24:18
  Speaker 2: was like, I think that, will be able to eat
• 1:24:21
  Speaker 2: quick enough, and it's still half an hour before closing,
• 1:24:25
  Speaker 2: I think we'll be okay, but I still called to
• 1:24:26
  Speaker 2: make sure. I genuinely was calling to ask, and did
• 1:24:29
  Speaker 2: end up asking a person, like, is it annoying if
• 1:24:31
  Speaker 2: I rock up there right now, you know? Because it
• 1:24:33
  Speaker 2: was so close to the hotel that I knew I
• 1:24:35
  Speaker 2: could be there in a minute. Anyway, I said all
• 1:24:37
  Speaker 2: that to say when I initially called, someone picked up,
• 1:24:42
  Speaker 2: and they tried to, this is insane. So they picked up,
• 1:24:45
  Speaker 2: and I guess there's like some frequently asked questions that
• 1:24:48
  Speaker 2: are just used to people asking, So when I initially
• 1:24:50
  Speaker 2: called and AI answered that they tried to make sound
• 1:24:54
  Speaker 2: like a hostess and they actually inserted restaurant noise behind them.
• 1:25:00
  Speaker 2: And I was like, this is insane. And so then
• 1:25:03
  Speaker 2: after the third question, I realized I wasn't talking to
• 1:25:05
  Speaker 2: like a person. Because initially when they were like, hey,
• 1:25:08
  Speaker 2: how you doing? I heard like in the back. I
• 1:25:11
  Speaker 2: was like, oh, hey, I'm calling to see if it's possible.
• 1:25:14
  Speaker 2: And then they were like, our hours are. And I
• 1:25:16
  Speaker 2: was like, oh, this isn't a real person. And then
• 1:25:20
  Speaker 2: I maybe asked one more thing and they were like,
• 1:25:22
  Speaker 2: let me transfer you to my colleague. And then a person,
• 1:25:25
  Speaker 2: it was a person who was clearly picking up for
• 1:25:27
  Speaker 2: the first time. There was no communication. They didn't, the
• 1:25:30
  Speaker 2: person picked up the way they would have picked up
• 1:25:33
  Speaker 2: if they had answered the phone to begin with. And
• 1:25:35
  Speaker 2: I just found that so jarring. Like it's just whatever
• 1:25:38
  Speaker 2: it takes to waste money and implement the stuff they're
• 1:25:42
  Speaker 2: engaging in. And it's just crazy. It's like Just have
• 1:25:44
  Speaker 2: your person pick up the phone. They're going to clearly
• 1:25:48
  Speaker 2: need to be on the phone sooner or later. And
• 1:25:50
  Speaker 2: they're not getting any information from the AI prompting on
• 1:25:54
  Speaker 2: what the specific thing is like that. That would be
• 1:25:56
  Speaker 2: the reason to use it is is OK. The AI
• 1:25:59
  Speaker 2: is going to like field some questions. So then that way,
• 1:26:01
  Speaker 2: by the person, by the time you talk to a person,
• 1:26:03
  Speaker 2: that person is fully aware of your situation. But that's
• 1:26:05
  Speaker 2: not what's happening.
• 1:26:06
  Speaker 1: No.
• 1:26:07
  Speaker 5: Yeah.
• 1:26:07
  Speaker 1: And also, again, speaking on it being forced on us.
• 1:26:12
  Speaker 1: No consumer in the world wants to talk to a
• 1:26:14
  Speaker 1: computer when they need to get a hold of customer service.
• 1:26:17
  Speaker 1: And companies aren't really seeing utility out of paying for
• 1:26:21
  Speaker 1: AI if it's not solving the problem. And then your
• 1:26:23
  Speaker 1: call logs are still as backed up because now we're
• 1:26:25
  Speaker 1: all just waiting because we can't get to a human being.
• 1:26:28
  Speaker 1: It's not helping society at all. It's not offering anything.
• 1:26:31
  Speaker 1: And that's one of the most disgusting things where I
• 1:26:33
  Speaker 1: really just feel so much vitriol towards these individuals because
• 1:26:36
  Speaker 1: I really need y'all taken off the planet immediately. I'm sorry,
• 1:26:38
  Speaker 1: I'm saying it, not Josh, but you don't belong here
• 1:26:40
  Speaker 1: with the rest of us. Go to Mars and stay there.
• 1:26:42
  Speaker 1: I know it's not safe. Definitely take one of those
• 1:26:44
  Speaker 1: SpaceX rockets. And we're going to hope for the best.
• 1:26:46
  Speaker 1: Because this, like, you are destroying society. You are offering
• 1:26:49
  Speaker 1: us nothing and taking everything. You are a stain on
• 1:26:52
  Speaker 1: the human race. Like, we need to get you gone
• 1:26:54
  Speaker 1: and yesterday.
• 1:26:56
  Speaker 2: And your bots don't work. No.
• 1:26:58
  Speaker 1: And then, you know, we're going to get into these
• 1:27:00
  Speaker 1: guys even more as the segment goes on. But to
• 1:27:02
  Speaker 1: wrap up the beginning of this, we'll hit with some
• 1:27:06
  Speaker 1: real evil guys. Scams! Cards! Anthropic's Dario Amodi is worth
• 1:27:18
  Speaker 1: an estimate $ 15. 5 billion. His favorite book is The Making
• 1:27:22
  Speaker 1: of the Atomic Bomb. This is him explaining why this
• 1:27:26
  Speaker 1: is his favorite book.
• 1:27:28
  Speaker 2: I understand one of your favorite books is The Making
• 1:27:30
  Speaker 2: of the Atomic Bomb. That is correct.
• 1:27:32
  Speaker 1: Do you see parallels between yourself and Oppenheimer?
• 1:27:35
  Speaker 3: You know, the figure I most identified with was Leo Szilard, who,
• 1:27:39
  Speaker 3: you know, was the one who first basically had the
• 1:27:41
  Speaker 3: idea that there could be a kind of chain reaction. Look,
• 1:27:44
  Speaker 3: my view is we're not gonna get through this with, like,
• 1:27:47
  Speaker 3: larger-than-life personalities or, like, figures who try and be at
• 1:27:51
  Speaker 3: the center of everything, right? There needs to be a
• 1:27:53
  Speaker 3: balance of power here, right? There's a lot of powerful
• 1:27:56
  Speaker 3: actors who have interests here, and the only way it's
• 1:27:59
  Speaker 3: gonna end well for everyone is if there's basically checks
• 1:28:04
  Speaker 3: and balances everywhere.
• 1:28:08
  Speaker 1: Dario, you know there's not going to be a check
• 1:28:10
  Speaker 1: nor a balance. We haven't seen those in I don't
• 1:28:12
  Speaker 1: know how long. Like, who's going to be doing these
• 1:28:14
  Speaker 1: checks and balances that you're talking about? What annoys me
• 1:28:17
  Speaker 1: about Dario is he tries to act like he's more
• 1:28:19
  Speaker 1: ethical than the rest of these bastards, and you're just
• 1:28:21
  Speaker 1: as bad, if not worse. Like, don't come over and
• 1:28:24
  Speaker 1: be like, no, I'm a cool guy. Like, I'm a
• 1:28:26
  Speaker 1: cool villain. I'm a cool billionaire. No, you're not. You suck.
• 1:28:29
  Speaker 2: And also, I think that if you work at one
• 1:28:31
  Speaker 2: of these companies, if you are, like, at the head,
• 1:28:33
  Speaker 2: and you see a future where this stuff is.
• 1:28:37
  Speaker 2: Absolutely essential, I think that part of working towards that
• 1:28:40
  Speaker 2: future is doing the sort of what would feel like
• 1:28:43
  Speaker 2: for them probably extracurricular stuff of I've had so many
• 1:28:46
  Speaker 2: conversations with people in tech who are bullish on AI
• 1:28:50
  Speaker 2: that are like, well, obviously, eventually we're going to need
• 1:28:53
  Speaker 2: some sort of universal basic income. And I'm like, OK,
• 1:28:55
  Speaker 2: see that right there. None of y'all are actually advocating
• 1:28:58
  Speaker 2: for that. Y'all are just saying it's going to have
• 1:29:01
  Speaker 2: to happen. But why aren't you using your lobbyists for it?
• 1:29:05
  Speaker 2: Why aren't you campaigning for it? Why aren't you the
• 1:29:07
  Speaker 2: politicians that you bought? Why aren't you using them as
• 1:29:10
  Speaker 2: the mouthpiece to say that eventually we're going to need
• 1:29:12
  Speaker 2: a UBI and establish what that's going to need to be?
• 1:29:15
  Speaker 2: And it's like you're just sort of setting about solving
• 1:29:21
  Speaker 2: a problem that nobody has and causing problems that are
• 1:29:25
  Speaker 2: very real and immediate. and saying that the solution is
• 1:29:29
  Speaker 2: obvious and it'll have to come to fruition, but you're
• 1:29:32
  Speaker 2: not doing anything to make that happen. And that's, I think,
• 1:29:36
  Speaker 2: one of the most aggravating things about it is that
• 1:29:39
  Speaker 2: if you, it's a lot like with guns in the
• 1:29:42
  Speaker 2: country and how people are like, oh, it's not a
• 1:29:44
  Speaker 2: gun issue, it's a mental health issue. And it's like, okay,
• 1:29:46
  Speaker 2: but the rest of the 364 days where there isn't
• 1:29:50
  Speaker 2: a shooting in your community, which is rare, right? It's
• 1:29:53
  Speaker 2: not a full 300 days, but In all other instances,
• 1:29:56
  Speaker 2: you're not putting money towards mental health. So not only
• 1:30:00
  Speaker 2: do you not believe that, but you're not willing to
• 1:30:01
  Speaker 2: do the work to, if you really believe that's true,
• 1:30:04
  Speaker 2: make a better world. And so I think that now
• 1:30:07
  Speaker 2: when you see people like Mario go out there or
• 1:30:10
  Speaker 2: when you see Sam Altman take a turn and finally
• 1:30:12
  Speaker 2: admit to something that he's lied about for so long,
• 1:30:15
  Speaker 2: it's like everything, every single thing rings hollow because... They
• 1:30:19
  Speaker 2: don't take the necessary steps outside of being in the
• 1:30:22
  Speaker 2: hot seat to look like they have a real vision
• 1:30:25
  Speaker 2: for what the future is outside of their own pockets
• 1:30:28
  Speaker 2: and outside of their own program and them all trying
• 1:30:30
  Speaker 2: to beat each other as some sort of like AI god.
• 1:30:33
  Speaker 1: Yeah. And I mean, if we're just keeping it frank,
• 1:30:36
  Speaker 1: they're liars. I don't even understand why we entertain interviews
• 1:30:39
  Speaker 1: with them anymore. They are lying. They are not truthful people.
• 1:30:41
  Speaker 1: They don't have an ounce of dignity. Like them talking
• 1:30:44
  Speaker 1: about universal income to come hand in hand with, you know,
• 1:30:47
  Speaker 1: the growth of generative AI is like basically if you've
• 1:30:50
  Speaker 1: ever watched The Office, it's like Scott's Tots. They're like, yeah,
• 1:30:54
  Speaker 1: if y'all graduate, we're going to make sure all y'all
• 1:30:56
  Speaker 1: go to college. He was like, damn, y'all really graduated? Okay,
• 1:30:58
  Speaker 1: I don't got the money for y'all to go. It
• 1:31:00
  Speaker 1: was a lie. It was a lie. It was a
• 1:31:02
  Speaker 1: scheme that Todd set up. And we all know that,
• 1:31:04
  Speaker 1: which is why it's so infuriating to watch them wax
• 1:31:06
  Speaker 1: poetic about things that are just absolutely simply untrue. You
• 1:31:09
  Speaker 1: are here to steal, kill, and destroy. So and if
• 1:31:12
  Speaker 1: you believe in the Bible, those are the things that
• 1:31:13
  Speaker 1: the devil was doing. Right. So I don't understand why
• 1:31:16
  Speaker 1: we even like entertain it because we know they're lying.
• 1:31:19
  Speaker 1: And then all these journalists don't want to lose their
• 1:31:20
  Speaker 1: access to people. So journalists have just become punk ass bitches.
• 1:31:23
  Speaker 1: Like you're just going to let this man lie the
• 1:31:25
  Speaker 1: whole time. But yes, this lie. Very good. And what
• 1:31:28
  Speaker 1: about this lie? Oh, and that lie is really intriguing.
• 1:31:31
  Speaker 1: Somebody just needs to be like, bro, you're going to
• 1:31:32
  Speaker 1: tell the truth away.
• 1:31:33
  Speaker 2: Yeah.
• 1:31:34
  Speaker 1: Because at this point, like, why are we watching you talk?
• 1:31:36
  Speaker 2: No, absolutely.
• 1:31:37
  Speaker 1: Peter Thiel. Oh. One of the greatest guys to ever evil.
• 1:31:43
  Speaker 1: He's an initial financial backer of OpenAI and the founder
• 1:31:46
  Speaker 1: of Planteer, the surveillance and data analytics company focused on
• 1:31:51
  Speaker 1: enterprise AI. And it's worth about $ 31. 9 billion. He famously
• 1:31:55
  Speaker 1: backed Hulk Hogan's sex tape lawsuit because he's a great guy.
• 1:31:59
  Speaker 1: And that was against Gawker in 2013. He mentored and
• 1:32:03
  Speaker 1: shaped J.D. Vance, also super cool guy with just the
• 1:32:07
  Speaker 1: best vibes who everyone loves, and convincing him to convert
• 1:32:12
  Speaker 1: to Catholicism. So that was Peter Thiel, who was like,
• 1:32:15
  Speaker 1: come over here to Catholicism, J.D., and become a venture capitalist. Later,
• 1:32:21
  Speaker 1: Peter's favorite hobby is giving lectures about the Antichrist. So
• 1:32:25
  Speaker 1: I guess just talking about himself. But he does love
• 1:32:28
  Speaker 1: to do that. We'll play a little bit of one
• 1:32:30
  Speaker 1: as we wind down here. There's so much about Peter
• 1:32:32
  Speaker 1: Thiel that could be said, but we're just going to
• 1:32:35
  Speaker 1: leave it in the AI space.
• 1:32:37
  Speaker 3: This is sort of where my speculative thesis is that
• 1:32:41
  Speaker 3: if the Antichrist were to come to power, it would
• 1:32:44
  Speaker 3: be by talking about Armageddon all the time.
• 1:32:47
  Speaker 2: Peter Thiel, the Antichrist would talk about Armageddon all the time.
• 1:32:51
  Speaker 2: He'd scare people and then offer to save them.
• 1:32:54
  Speaker 1: You sound familiar?
• 1:32:55
  Speaker 3: Peter.
• 1:32:56
  Speaker 1: So you're just going to tell all of us you're
• 1:32:59
  Speaker 1: the Antichrist.
• 1:33:00
  Speaker 2: Did he answer that journalist after? Because that's a real
• 1:33:05
  Speaker 2: rough one. That's a real, to quote me to me,
• 1:33:11
  Speaker 2: we got to fight if you quote me to me.
• 1:33:13
  Speaker 1: Yeah, I think he took it as a compliment. And
• 1:33:18
  Speaker 1: then obviously we have Elon Musk, who co-founded OpenAI with
• 1:33:22
  Speaker 1: Sam Altman. who is the wealthiest person in the world
• 1:33:25
  Speaker 1: at an estimated $ 889. 9 billion fortune and was briefly the
• 1:33:30
  Speaker 1: first trillionaire, but thank God that didn't stick. All the
• 1:33:33
  Speaker 1: money and all those kids and still so insecure. I mean,
• 1:33:38
  Speaker 1: when that's what you look like on the inside and
• 1:33:39
  Speaker 1: the outside, I get it. And we're going to play
• 1:33:42
  Speaker 1: just a little clip here. I mean, some people do
• 1:33:43
  Speaker 1: loathe you.
• 1:33:44
  Speaker 5: Yes, some people do.
• 1:33:45
  Speaker 1: But do you understand why? Do you think what you're
• 1:33:47
  Speaker 1: doing is helpful for Western democracy?
• 1:33:50
  Speaker 5: Maybe some people do loathe me. And that's probably true.
• 1:33:53
  Speaker 1: I don't care.
• 1:33:56
  Speaker 5: But the fact that, as you pointed out, a quarter
• 1:34:00
  Speaker 5: billion people follow me is that I think a lot
• 1:34:03
  Speaker 5: more people actually like me than don't. And I think
• 1:34:06
  Speaker 5: a lot more people hate you and the media more
• 1:34:09
  Speaker 5: than you realize.
• 1:34:11
  Speaker 2: I mean, I think he does very much care. He
• 1:34:13
  Speaker 2: argues with people on Twitter.
• 1:34:16
  Speaker 1: Constantly.
• 1:34:16
  Speaker 2: That he bought.
• 1:34:17
  Speaker 1: Yeah. You bought the whole platform and you're still fighting
• 1:34:20
  Speaker 1: people who hate you on it.
• 1:34:21
  Speaker 2: That's like real loser stuff. I would never argue with
• 1:34:25
  Speaker 2: somebody in my house.
• 1:34:27
  Speaker 1: No.
• 1:34:27
  Speaker 2: It's my house.
• 1:34:28
  Speaker 1: Please leave.
• 1:34:29
  Speaker 2: Yeah. That's wild that you spend your time. You supposedly
• 1:34:33
  Speaker 2: have like 19 companies. You're the richest man in the world.
• 1:34:35
  Speaker 2: And then you argue with people with no followers. Yeah.
• 1:34:39
  Speaker 2: about stuff.
• 1:34:40
  Speaker 1: Because your butt hurt.
• 1:34:41
  Speaker 2: Yeah.
• 1:34:41
  Speaker 1: I mean, like, how are you just, like, the apex loser?
• 1:34:44
  Speaker 3: Yeah.
• 1:34:44
  Speaker 1: Like, I'm so tired.
• 1:34:46
  Speaker 2: Of the nerve break. I bet a lot of people
• 1:34:48
  Speaker 2: hate you and the media. It's like, that's, even that's
• 1:34:50
  Speaker 2: how it is. I don't care if people hate me,
• 1:34:52
  Speaker 2: but people hate you. I know you are, but what
• 1:34:54
  Speaker 2: am I? Ass answer.
• 1:34:55
  Speaker 1: What do you mean? Yeah. If you didn't care about
• 1:34:57
  Speaker 1: any of that at all, you wouldn't be talking about
• 1:34:58
  Speaker 1: it constantly ad nauseum. Yo, daddy hates you, boy. Yeah.
• 1:35:01
  Speaker 1: Everybody hates you.
• 1:35:02
  Speaker 2: It says a lot when your dad hates you. And
• 1:35:05
  Speaker 2: I'm not saying that makes every dad who's ever hated
• 1:35:07
  Speaker 2: their kid right. I'm just saying that.
• 1:35:09
  Speaker 1: I'm not saying your daddy hates you, your kids hate you.
• 1:35:11
  Speaker 1: You're getting hate from both generations of the family, and
• 1:35:13
  Speaker 1: you're right in the middle getting kicked.
• 1:35:15
  Speaker 3: Yeah.
• 1:35:15
  Speaker 1: Because you suck.
• 1:35:16
  Speaker 2: And you only have ex-wives. You know? Like, everyone hates you.
• 1:35:21
  Speaker 2: It's crazy.
• 1:35:23
  Speaker 1: And none of them have good things to say.
• 1:35:25
  Speaker 6: Yeah.
• 1:35:25
  Speaker 1: Like, please. I mean, these Silicon Valley geniuses are pouring
• 1:35:29
  Speaker 1: hundreds of millions of dollars into super PACs to ensure
• 1:35:32
  Speaker 1: that their voices are sympathetic to its deregulatory AI agenda.
• 1:35:38
  Speaker 1: So they're obviously trying to buy off the market, which
• 1:35:41
  Speaker 1: Elon did when he was just fucking around with Doge.
• 1:35:43
  Speaker 1: He was like, yeah, no, I'm totally here to save
• 1:35:45
  Speaker 1: the government money. I'm not doing anything else that pertains
• 1:35:47
  Speaker 1: to my own companies and wealth and how I'm going
• 1:35:49
  Speaker 1: to force the American consumer to eat my debt and
• 1:35:53
  Speaker 1: all my bullshit.
• 1:35:53
  Speaker 2: Or my lawsuits or, yeah.
• 1:35:56
  Speaker 1: Don't worry about it, guys. No, you know what? We
• 1:35:58
  Speaker 1: was using too many straws at the Department of Defense.
• 1:36:01
  Speaker 2: Yeah, that's why we got to shut the whole thing down.
• 1:36:03
  Speaker 1: Yeah, so now it's the Department of War and no
• 1:36:05
  Speaker 1: more straws. Put your lips on the cup like a man.
• 1:36:08
  Speaker 2: Yeah.
• 1:36:08
  Speaker 1: Yeah. So we get it. This is the grift, right?
• 1:36:12
  Speaker 1: So OpenAI and Planter founders have given large sums to
• 1:36:15
  Speaker 1: Leading the Future, an organization dedicated to identifying, maintaining, and
• 1:36:21
  Speaker 1: growing pro-AI candidates. Earlier this summer, Leading the Future spent
• 1:36:25
  Speaker 1: $ 6 million on ads attacking Alex Borz, a New York
• 1:36:28
  Speaker 1: State assemblyman and fireman of the AI regulation at the
• 1:36:31
  Speaker 1: state level. The ads attacked Alex's progressive credentials, alleging that
• 1:36:35
  Speaker 1: he had carried out tech work in the past for
• 1:36:38
  Speaker 1: the U.S. Immigration and Customs Enforcement Department, which he denied.
• 1:36:42
  Speaker 1: So he said, why do I even fuck with him?
• 1:36:44
  Speaker 1: Because he didn't want to do ice. He did all
• 1:36:46
  Speaker 1: the ice. Yeah. Yeah. And so... They're now putting money
• 1:36:50
  Speaker 1: behind these super PACs to try to get rid of
• 1:36:53
  Speaker 1: political candidates who would obviously vote against their special interests,
• 1:36:57
  Speaker 1: which is what these guys do all the time. So unfortunately,
• 1:37:00
  Speaker 1: the tech bros are just as powerful as they are stupid.
• 1:37:03
  Speaker 1: And that is going to include part one of the
• 1:37:06
  Speaker 1: series on AI, Josh. What are your thoughts here? Like
• 1:37:11
  Speaker 1: just about the tech bros, about like maybe even just
• 1:37:13
  Speaker 1: the culture in general of these ugly, weird, like, lizard
• 1:37:18
  Speaker 1: people i mean.
• 1:37:19
  Speaker 2: I i do think that um eventually there'll be a
• 1:37:24
  Speaker 2: bubble burst and it won't be as dramatic it won't
• 1:37:27
  Speaker 2: be as uh yeah it it probably won't be as
• 1:37:32
  Speaker 2: uh delicious as everyone seeing that they were wrong them
• 1:37:35
  Speaker 2: saying that they were wrong and us taking a completely
• 1:37:38
  Speaker 2: different course because i do think that some aspects of
• 1:37:41
  Speaker 2: what we at least call ai which some of it's
• 1:37:43
  Speaker 2: just data collection but like Some of what we use
• 1:37:46
  Speaker 2: as AI is going to be here to stay. But
• 1:37:48
  Speaker 2: I think that you can only overload the market and
• 1:37:52
  Speaker 2: the money for so long without getting the results you
• 1:37:54
  Speaker 2: would need because the math already doesn't make any sense.
• 1:37:57
  Speaker 2: And it's already not looking likely that these are going
• 1:38:00
  Speaker 2: to be the end goal numbers that they're going to
• 1:38:02
  Speaker 2: have by their benchmarks.
• 1:38:03
  Speaker 1: These are their projections because of their pre-revenue, meaning they're
• 1:38:06
  Speaker 1: not making any money.
• 1:38:08
  Speaker 2: And so I don't know. I don't know how long
• 1:38:12
  Speaker 2: they can be propped up. And I think that whether
• 1:38:15
  Speaker 2: it's flock cameras and the unconstitutional basis that they try
• 1:38:22
  Speaker 2: to collect on people and try to get people locked up,
• 1:38:27
  Speaker 2: So many of these cameras are having mistakes. And then
• 1:38:30
  Speaker 2: even in the process of trying to defend yourself against
• 1:38:34
  Speaker 2: the accusation that you ran some red light or that
• 1:38:36
  Speaker 2: you were somewhere where you couldn't have been because you
• 1:38:38
  Speaker 2: were in another state, the burden of proof and the
• 1:38:41
  Speaker 2: onus is on the citizen instead of the state. And
• 1:38:45
  Speaker 2: I think that eventually there's going to be a tipping
• 1:38:48
  Speaker 2: point where any new media or any new exploration into
• 1:38:53
  Speaker 2: AI is just going to be poisoned by the overall
• 1:38:55
  Speaker 2: well of what they've created so far. And so I
• 1:38:59
  Speaker 2: think that those things will probably be the bubble bursting
• 1:39:01
  Speaker 2: and the tipping point in more so the public outcry
• 1:39:04
  Speaker 2: than just them losing money. I think that we waited
• 1:39:07
  Speaker 2: for a long time for it to be a bubble
• 1:39:09
  Speaker 2: burst in a dot-com way, because with dot-com, there was
• 1:39:11
  Speaker 2: still some earnestness in the market of like, Well, it
• 1:39:15
  Speaker 2: doesn't have any value, so it can't actually be making money.
• 1:39:18
  Speaker 2: And now we just sort of lie about what value
• 1:39:20
  Speaker 2: and money is. Yes. Which I think has kept it
• 1:39:23
  Speaker 2: propped up this long. But, yeah, I wish nothing good
• 1:39:26
  Speaker 2: for any of them. And I'm very thankful to you
• 1:39:29
  Speaker 2: for having me on.
• 1:39:30
  Speaker 1: I'm thankful for you to be here.
• 1:39:31
  Speaker 2: It's been great to meet you. It's been great to
• 1:39:33
  Speaker 2: meet you, too. I can't help the fact that I'm
• 1:39:36
  Speaker 2: a Pisces, but I'm glad that we met nonetheless.
• 1:39:39
  Speaker 1: I am, too. Yeah. Yeah. I'll still definitely walk you
• 1:39:42
  Speaker 1: to your car or mine if you want.
• 1:39:44
  Speaker 2: I just it sounds like a threat.
• 1:39:45
  Speaker 1: Yeah.
• 1:39:46
  Speaker 2: I mean, just the way the way you say it.
• 1:39:50
  Speaker 1: No, because I feel I feel like we've developed a rapport. OK. Yeah. Yeah.
• 1:39:54
  Speaker 2: That's what I was hoping for. Mm hmm.
• 1:39:56
  Speaker 1: Totally not get hit by my car.
• 1:39:58
  Speaker 2: Fantastic.
• 1:39:59
  Speaker 1: Or a car that looks like mine.
• 1:40:00
  Speaker 2: You know what I'm going to do? I'm going to
• 1:40:02
  Speaker 2: walk myself out and then I'll see you next time
• 1:40:05
  Speaker 2: in studio. You don't ever have to worry about being
• 1:40:08
  Speaker 2: near me in a car at the same time.
• 1:40:09
  Speaker 1: I like to protect my guests, okay? This is a
• 1:40:11
  Speaker 1: full experience. And Josh, we always ask on the show,
• 1:40:13
  Speaker 1: where can people find you? What would you like to promote?
• 1:40:15
  Speaker 1: Any social media? All the good things.
• 1:40:17
  Speaker 2: So I'm always touring. You can check out my tour
• 1:40:21
  Speaker 2: and tickets on joshjohnsoncomedy.com Go straight to the website to
• 1:40:25
  Speaker 2: get those tickets and then If it looks like the
• 1:40:27
  Speaker 2: show is sold out, we're probably going to be adding
• 1:40:29
  Speaker 2: one or at least there's an email list that you
• 1:40:31
  Speaker 2: can join. And the email list helps you sidestep any
• 1:40:33
  Speaker 2: sort of third party or scam or ticket type stuff.
• 1:40:36
  Speaker 2: And then you can be directly notified when we add shows.
• 1:40:40
  Speaker 2: And on top of that, just go to YouTube. YouTube.com.
• 1:40:43
  Speaker 2: If you go to Josh Johnson Comedy on YouTube, you'll
• 1:40:45
  Speaker 2: see my weekly uploads.
• 1:40:47
  Speaker 1: Amazing.
• 1:40:47
  Speaker 2: Yes.
• 1:40:48
  Speaker 1: And if you are already on YouTube.com, you can watch
• 1:40:51
  Speaker 1: this show and its full link there as well. Or
• 1:40:53
  Speaker 1: if you're listening on audio and you want to see
• 1:40:55
  Speaker 1: the photos and videos, you can go right ahead to
• 1:40:56
  Speaker 1: Scam Goddess Pod on Instagram and on TikTok to see
• 1:41:00
  Speaker 1: videos and all of the images, the jump scares. of
• 1:41:04
  Speaker 1: the men that these people are. Don't say I didn't
• 1:41:07
  Speaker 1: warn you. My book, Scam Goddess, available at any store
• 1:41:10
  Speaker 1: that you purchase books at, as well as the audio
• 1:41:12
  Speaker 1: version that I read. And my TV show, Scam Goddesses,
• 1:41:14
  Speaker 1: all episodes are now out on Hulu and all the
• 1:41:17
  Speaker 1: other stuff that I do on Hulu and Netflix and
• 1:41:19
  Speaker 1: things like that. So please support your girl. And the
• 1:41:21
  Speaker 1: way you can support a Black woman for free today, especially,
• 1:41:24
  Speaker 1: is by leaving five stars on whatever platform you listen. Okay? Amen.