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Speaker 1: Media.

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Speaker 2: It is with great excitement that I would like to

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Speaker 2: announce the newest joint venture in the high tech world

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Speaker 2: between Fast Future Podcasts Limited, formerly oil Warehouse formerly NFT

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Speaker 2: Tax Loss Harvesting Service formerly I believe, several kinds of

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Speaker 2: consulting firm and maybe a private investigator, and our good

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Speaker 2: friends at Better Offline, and of.

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Speaker 3: Course I'm representing the SoftBank Zitron merger we did earlier

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Speaker 3: in the year, in which case I am now technically

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Speaker 3: Masayoshi's son's son, and so we are related. He is

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Speaker 3: my father and I am his son. Now I am

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Speaker 3: Masiosi son. We are all Masaoji's son on some level.

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Speaker 3: Welcome to Better Offline and Trash Future at the same time. Yeah,

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Speaker 3: it's tf X Xitron. Oh, it's beautiful.

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Speaker 2: I'm so excited to announce that. Between our our two shows,

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Speaker 2: which are our independent company and iHeart, we're actually going

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Speaker 2: to be building apart. Look, Meta and Blue Owl have

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Speaker 2: said they're going to be building a data center, an

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Speaker 2: AI data center the size of I believe several Manhattans. Well,

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Speaker 2: we are building a podcast generating data center that will

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Speaker 2: cover nineteen Staten islands and cost only one trillion dollars

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Speaker 2: is expected to generate upwards of fifty dollars a year.

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Speaker 4: People are telling me you're on too many podcasts November

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Speaker 4: and I will not start. Not only am I starting

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Speaker 4: more podcasts, but I'm also folding more into the existing

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Speaker 4: podcast So pretty soon everything will be trash future.

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Speaker 5: Yes, zaraon Stke trying to stop us from building the

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Speaker 5: data center, saying that it's not viable. And to that

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Speaker 5: I tell I say to him, well, have you ever

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Speaker 5: started a business it's been successful.

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Speaker 6: No, you haven't, so shut.

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Speaker 3: No, that's one of the two things that can happen

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Speaker 3: in New York City. Yeah.

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Speaker 4: I mean this is a really a really obvious thing.

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Speaker 4: When you look at Zara Mundane, you look at that guy,

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Speaker 4: and you say, that guy doesn't know a thing about

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Speaker 4: being successful. I'm very certainly guy's never succeeded.

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Speaker 3: Yeah, he's truly disliked by New Yorkers. That's the thing

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Speaker 3: that I hear from them. They're not just like welling

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Speaker 3: up with pride over his Fourth of July speech. They

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Speaker 3: don't love the fact to fix the Williamsburg bike lay. No, no, no,

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Speaker 3: it's all just everyone's sitting in their apartments in Connecticut

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Speaker 3: where they live most of the time, other than the

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Speaker 3: one day of the year where they come into New

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Speaker 3: York to complain.

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Speaker 2: Well, okay, I did say nineteen Staten Islands. What if

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Speaker 2: we data centered over Staten Island and just made it

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Speaker 2: nineteen stories.

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Speaker 3: Actually based on everything I know about Staten Island. The people,

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Speaker 3: they might approve, but they'll be like, ah, fuck it,

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Speaker 3: We've done our best.

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Speaker 2: We've motovated Staten Island. No, welcome to TF better upline.

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Speaker 2: And here's the thing TF listeners have been saying to me, like,

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Speaker 2: you know, discord and stuff. Why haven't you covered the

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Speaker 2: Masso She saw the newest piece of I guess outsider

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Speaker 2: art published by soft Bank in the form of their

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Speaker 2: investor presentation.

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Speaker 3: It's so beautiful.

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Speaker 2: There's always a lot in them and Masso she san

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Speaker 2: your father, yes, our I believe uncle.

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Speaker 3: Has these fucking podcast NAPO babies.

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Speaker 2: There's always some visual metaphor. I think that the Masseo

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Speaker 2: son decides this is gonna be how I communicate to everybody.

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Speaker 2: The thing that Chad GBT and I stayed up all

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Speaker 2: night for a month kind of coming up with.

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Speaker 3: Yeah, and it used to be like.

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Speaker 2: Flying unicorns, right, how they would fly over like the

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Speaker 2: trench of despair and into like the future of optimists.

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Speaker 3: Yeah, the trench of coronavirus, right, that was one of

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Speaker 3: his Yeah, the trench of COVID. That was the one,

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Speaker 3: the valley of coronavirus.

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Speaker 2: Now, this SoftBank presentation has I would say a different

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Speaker 2: recurrent visual metaphor that starts around slide up for forty.

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Speaker 3: And we'll link to this in the in the notes

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Speaker 3: so that you can behold the goose. Yeah, So can

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Speaker 3: everybody turn to slide forty four in your packs? Please?

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Speaker 3: I'm there, this is it's beautiful. I am crying.

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Speaker 2: So what I have in front of me in case

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Speaker 2: you can't turn to slide forty four in your packs

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Speaker 2: because you're catching up on our investor presentation or our

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Speaker 2: presentation of SoftBank's investor presentation. Imagine your investor in SoftBank.

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Speaker 2: Maybe you're a pension fund, you're Ontario teachers, you've invested

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Speaker 2: in soft Bank, and the MASSOHI saw on you can

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Speaker 2: see his face light up because he's about to give

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Speaker 2: you his visual metaphor. Slide forty three to forty four transition.

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Speaker 2: It's a picture of a goose in five golden eggs. Yep,

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Speaker 2: that's right.

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Speaker 3: I think. Yeah, the thing is like it actually does

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Speaker 3: make sense when you read it one hundred times because actually,

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Speaker 3: let's go a little bit into it and that I'll

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Speaker 3: give a full explanation, because there is a logic. It's

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Speaker 3: just insane.

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Speaker 6: Generally, I love the graphics.

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Speaker 5: Like I've got a friend who's like he does like

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Speaker 5: his his job is to sort of apparently upgrade decks.

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Speaker 5: He goes like he does consulting for like companies to

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Speaker 5: be like, here's how you can make your PowerPoint presentations

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Speaker 5: look better because real like.

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Speaker 4: Do you pronounce that unionized or unionized? Moment there where

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Speaker 4: I'm like, the decks like the thing you have like

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Speaker 4: outside of a house.

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Speaker 5: Well, well, I mean I asked him in certain in

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Speaker 5: terms of like what you mean like magic the gathering,

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Speaker 5: which apparently which I guess would make more money. But

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Speaker 5: but I saw this, and I sent this to him,

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Speaker 5: and he was and he and he and like his

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Speaker 5: reaction I think was one of the funniest things that

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Speaker 5: I've ever I've sort of ever encountered. Every graphic in

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Speaker 5: this presentation is a mixture of graphic designers my passion,

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Speaker 5: but also like I it's one like I sort of

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Speaker 5: feel like it's actually ironically beautiful. Yes, this is amazing,

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Speaker 5: It's an amazing.

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Speaker 3: It's genuinely beautiful because like I said, so I I

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Speaker 3: must be clear when the goose is soft Bank.

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Speaker 6: Right, Okay, here's like seven times in this as well, right.

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Speaker 3: Okay, So soft Bank is the goose, Masiosi, Masayoshi's son

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Speaker 3: is the gander. Masayoshi son mounts and impregnates soft Bank,

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Speaker 3: by which I mean invests money in companies using soft

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Speaker 3: Bank's funds, which point the goose, which is soft Bank,

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Speaker 3: becomes pregnant, and the portfolio company goes larger, then it

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Speaker 3: lays the egg, the portfolio company goes public. Basically, soft

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Speaker 3: Bank is a company that invests in companies that then

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Speaker 3: go public and makes soft Bank money. In theory, and

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Speaker 3: Masayoshi's son just vigorously you could you could more normally

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Speaker 3: call this like an incubator, but instead he's picturing himself

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Speaker 3: as a virile goose. Yes, exactly, He's just he is

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Speaker 3: just like absolutely going to town on the goose of

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Speaker 3: soft Bank every year.

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Speaker 7: Jesus, Jesus, just a discuss coming up to the coming

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Speaker 7: out to the legs and grasping it with both hands

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Speaker 7: and talking to a lot of people who have real

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Speaker 7: sort of influence and terms of capitalist central planning and going,

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Speaker 7: I've in fucking gooses.

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Speaker 3: Can you imagine like being a major investor in stuff?

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Speaker 3: But like the Japanese government is invested in this company

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Speaker 3: through ETFs, like and you're just like, great, what what

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Speaker 3: Masioshi Son's got for me this year? And you're just

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Speaker 3: like the what what?

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Speaker 8: What?

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Speaker 4: I think the sort of interesting question about this slide

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Speaker 4: decking about Masioshi Son himself is like, yes, there is

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Speaker 4: a logic if you work hard enough. This is also

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Speaker 4: true of the ramblings of someone experiencing a florid mental

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Speaker 4: health episode on public transports who we've you know, decided

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Speaker 4: as a society. Now, I guess it's okay to kill

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Speaker 4: that person, but it's not okay to kill Masioshi's son.

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Speaker 4: And I don't know, really know how to reconcile those

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Speaker 4: two things.

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Speaker 3: Not to not to say that we approve of that

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Speaker 3: for legal reasons, just to be just to be clear

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Speaker 3: and new. Yeah, I mean that's your dad. I wouldn't

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Speaker 3: say that you should leave my father alone anyway.

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Speaker 2: Sorry, rally, so basically and this this is that the

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Speaker 2: mental health point I think is interesting, right because there's

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Speaker 2: this idea that's been going around, that's been going sort

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Speaker 2: of like legitimate business publications that CEOs are getting AI psychosis. Yes,

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Speaker 2: it's just that because they're CEOs, you know, they when

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Speaker 2: they get AI psychosis, they don't like get on the

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Speaker 2: path train and have a heart attackle trying to meet

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Speaker 2: like their fake girlfriend from character AI, which more or

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Speaker 2: less sort of actually happened to somebody, yeah details AI specifically, yeah.

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Speaker 3: Yeah yeah.

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Speaker 2: But in this case, they get up on stage and

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Speaker 2: they say, I have been I am destined. I am

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Speaker 2: destined to bring about the birth of an artificially superintelligent

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Speaker 2: god through this goose that has historically not been valued.

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Speaker 2: Because if you turn to slide forty seven, you'll see

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Speaker 2: the main problem is Goose was not valued.

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Speaker 3: Yes, Goose value zero. And I think I don't know

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Speaker 3: if you remember the Robe Wismann fake Uber YouTube thing

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Speaker 3: that the listeners are going to love this because it's

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Speaker 3: just and it's just him going Uber Driver suck me off,

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Speaker 3: and he's just like sure, I just thinkost zero zero,

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Speaker 3: it's really good.

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Speaker 2: Imagine this in the I imagine this in the dark

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Speaker 2: soul spont goose not value.

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Speaker 4: Well, this is the thing, right, what we've got here

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Speaker 4: is And I think it's interesting that the AIS of

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Speaker 4: cyber psychosis thing because nas something is very open about

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Speaker 4: using AI, spending a lot of time talking to AI,

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Speaker 4: really eternalizing and personalizing the AI for himself. What we've

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Speaker 4: done is we've done a kind of like European medieval

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Speaker 4: royalty thing where we've created a kind of system where

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Speaker 4: if you are you know, at the top of it,

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Speaker 4: you can have the delusions and society has to conform

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Speaker 4: around you.

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Speaker 3: You are the king of France. Everybody has to act

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Speaker 3: like you are made of glass. Oh god, it is.

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Speaker 3: It's just besides its digital versa. It's just that like

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Speaker 3: everyone stinks, everyone's weird. It's like it's either shit or

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Speaker 3: oranges in the air. Now everyone's just like, wow, we

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Speaker 3: all love loops now, right, and everyone goes loops. Yeah, yeah, yeah,

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Speaker 3: I love loops. Loops are the best where we hate

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Speaker 3: we hate the other thing now.

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Speaker 2: And so each of these eggs is a trillion yen yeah,

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Speaker 2: and the markets are only the eggs, which is the

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Speaker 2: value of the companies but the goose not valued.

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Speaker 3: Goose not value zero. Yeah, goose value zero.

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Speaker 2: But in fact, and it says eggs do not lay eggs,

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Speaker 2: and it was the goose that created the value.

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Speaker 6: Many people are saying that I died.

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Speaker 3: This whole time. I had it wrong. The eggs. Fuck.

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Speaker 4: It's very funny to have a sort of like arch

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Speaker 4: capitalist go Wait a second, this business doesn't create any

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Speaker 4: of its own value, and this value has got to

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Speaker 4: come from somewhere, so I assume it's from you know,

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Speaker 4: analogously goose and non analogously me.

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Speaker 3: Yeah. So yeah, I've been doing the hater's go to

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Speaker 3: soft bank and they just went out, so I can

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Speaker 3: very freshen my mind. And the thing that you'll know

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Speaker 3: when you look back at Massiosha Sun is he's a

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Speaker 3: terrible fucking investor, like historically bad, other than like four

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Speaker 3: times when he was amazing. He bought Ala Barbara at

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Speaker 3: twenty million dollars. He invested it, put twenty million in

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Speaker 3: worth about one hundred billion dollars equity value at the top,

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Speaker 3: sold it for about thirty billion because that's Masayoshi sign.

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Speaker 3: He bought Armed for thirty two billion dollars, took it

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Speaker 3: private and then took public and now it's worth a

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Speaker 3: bunch more money. But Yahoo Japan is the craziest one,

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Speaker 3: like classic loser company Yahoo. But it turns out that

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Speaker 3: he managed to, through one of his weird joint ventures,

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Speaker 3: stop it from being absorbed into the problematic Yahoo. So

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Speaker 3: he acted it. But every time he does something, well,

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Speaker 3: it's by accident. Every time he loves Also, I swear

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Speaker 3: this is true. He has a thing for whimsical white

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Speaker 3: boys like well, who doesn't I mean the Green Silk

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Speaker 3: Cat like Lex green Sill and him used to talk

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Speaker 3: on the phone every day he invested in we work

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Speaker 3: in twenty eight minutes they signed the four point four

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Speaker 3: billion dollar deal in the back of a car on

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Speaker 3: an iPad And it was like twenty seventeen, so the

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Speaker 3: iPad wasn't very good the time. So they're just like

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Speaker 3: like this fucking like clunky, probably cracked like across the

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Speaker 3: front font probably seventy two, just like, no, we must

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Speaker 3: do this, we must do this, now, we have to

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Speaker 3: do this. I must I'm being whimsical in front of

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Speaker 3: the wrong peep exactly. No, I genuinely think the if

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Speaker 3: I got in front of Masioshi's son for maybe ten minutes.

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Speaker 3: I could get seven billion dollars.

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Speaker 2: But here's your father, so you hope that you will

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Speaker 2: he will give you the time.

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Speaker 3: I wish all of this could. I wish I could

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Speaker 3: get in front of him. I wish I could just

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Speaker 3: tell him some of the great ideas I have about

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Speaker 3: like I don't know. Look, I have a newslet with

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Speaker 3: one hundred and eight thousand subscribers Masaosi's son. What if

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Speaker 3: it had a trillion subscribers? Huh right, And He'll be like, whoa,

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Speaker 3: that's and we're we're in on the ground floor of this.

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Speaker 3: We can get in. That's a big number. Ed, I'd

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Speaker 3: love to invest seven billion dollars. I'll be like, I

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Speaker 3: think that should be good enough to get us started.

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Speaker 3: Macaiosi son, another ten billion dollars, and I guarantee you

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Speaker 3: a trullion subscribers will happen by it could be as

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Speaker 3: early as twenty ninety easy pasy. Hmmm.

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Speaker 4: Well, the thing is right, I think this is a

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Speaker 4: good start, right, but we've got to aim high, Okay,

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Speaker 4: So like, yeah, what we do is we get we

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Speaker 4: get you in front of him and we say all

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Speaker 4: of this. But then you know, as he's sort of

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Speaker 4: like he's.

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Speaker 3: Warming to you. You see that he's kind of receptive

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Speaker 3: to this.

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Speaker 4: What you do is you switch it up right, you

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Speaker 4: lean forward, you jump out of the seat and grab

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Speaker 4: him by both lapels and you look him dead in

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Speaker 4: the eye and you say, and I'm going to invent God?

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Speaker 3: Oh yeah, And how do you love that? And here's

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Speaker 3: the thing, how do Christians like get a relationship with God?

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Speaker 3: The Bible a written document? What if the Bible could

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Speaker 3: be emailed to people every week? Every week they email

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Speaker 3: the Bible? That's what? That's what? Where's your head at is?

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Speaker 3: And Masaiosi Sun by this point is just he is

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Speaker 3: taking out a margin loan. He's like calling these back

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Speaker 3: and I need every dollar I've got, say it all

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Speaker 3: I need to back this. We direct all of it

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Speaker 3: from open Ai.

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Speaker 2: I've got a new person who's recently who told me

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Speaker 2: they're going to build God most recently so basically because

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Speaker 2: that's a little like we work was supposed to be

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Speaker 2: heaven on earth.

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Speaker 3: Like that was the pitch?

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Speaker 2: Is that, oh, that you could remake You could remake

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Speaker 2: a kind of prelapse arian, non alienated community. You could

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Speaker 2: have gardens of Eden everywhere. It was the point. Yeah,

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Speaker 2: but just that office sharing that same thing with flow

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Speaker 2: that's supposed to be that too, Like no, no, we've

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Speaker 2: got to much much more abstract. God yeah, any case,

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Speaker 2: yeah yeah, he said to the geese, he said, so

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Speaker 2: back to the gate, can we focus on the geese

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Speaker 2: on this technology? Sorry? Sorry I got I got us

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Speaker 2: off of goose.

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Speaker 3: My bad.

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Speaker 2: So eggs do not lay eggs obviously, obviously, and so

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Speaker 2: the mission to go for how do you go from

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Speaker 2: three eggs to seventy four eggs and increase of seventy.

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Speaker 3: More geese and Massioshi sounds gonna stop fucking them.

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Speaker 2: It was the Google that created it was the goose

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Speaker 2: that created value.

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Speaker 3: Oh so the value came from the goose.

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Speaker 2: I think I read that in capital Yeah, so the

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Speaker 2: goose value, goose value is seventy one, right, So goose

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Speaker 2: value seventy one, and people didn't value the goose at

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Speaker 2: seventy one. No, what matters not the eggs, It is

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Speaker 2: the goose itself, and true value is the power to

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Speaker 2: keep laying eggs. Right, And because of this, he estimates

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Speaker 2: that in the next sixteen years he will be the

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Speaker 2: first yen based quadrillionaire, or at least soft Bank will

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Speaker 2: be a gooseworth of a quadrillion yen.

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Speaker 3: I'm not sure what effects me more the fact that

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Speaker 3: this is written so much like sort of serial killer

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Speaker 3: taunting the police, or the fact that it kind of

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Speaker 3: appears to maybe be working well. The thing is, it

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Speaker 3: works because Masayoshi's son is able to keep getting debt

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Speaker 3: and genuinely, had open Aiye not come along, Masayoshi's son

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Speaker 3: might have been fine. Arm turned out so well like

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Speaker 3: it just as a chip maker, he's been able to

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Speaker 3: do basically unlimited margin loans, and he was okay, he

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Speaker 3: could have been fine, but then the whimsical white boy

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Speaker 3: operated in front of him, and he was like, okay,

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Speaker 3: this is it, Like this is my boy. I will

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Speaker 3: give him. He took out a forty billion dollar margin loan,

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Speaker 3: not margin, sorry, a bridge loan. It's a year long loan. Yeah,

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Speaker 3: jesus if you wanted to.

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Speaker 2: If you want the story on bridging loans, refer back

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Speaker 2: to our episode of Earth Rob Smith about bridging loans

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Speaker 2: and what kinds of things they're for and what kinds

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Speaker 2: of terms they usually have. So the true source of

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Speaker 2: the value. Could he ever turn to place fifty five.

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Speaker 2: This includes everyone listening on your on your packet. So

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Speaker 2: the true source of the value is the golden egg

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Speaker 2: factory inside the goose. Yes, and then it actually gets

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Speaker 2: helpfully broken.

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Speaker 3: Like a woom.

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Speaker 2: I guess well, So the goose here is soft bank

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Speaker 2: bringing out artificial superintelligence, and the internal mechanism is an

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Speaker 2: AI generated factory of eggs that are also labeled artificial superintelligence.

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Speaker 3: Yeah, each egg is a SI. Right, So eggs used

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Speaker 3: to be eggs used to be just a trillion dollars

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Speaker 3: of yen. But that's sorry, a trillion yen. It's like

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Speaker 3: six something billion dollars. What. I don't really know what

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Speaker 3: the eggs mean anymore other than ASI, which is it's

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Speaker 3: kind of like a yeah, it was like Ben Garrison cartoon, Like, well,

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Speaker 3: I mean this is where we want to go.

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Speaker 2: I want to go back to what Doova was saying

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Speaker 2: about mental illness right about. This is someone who because

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Speaker 2: we know what happens with Maso she Song, we know

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00:17:26,880 --> 00:17:29,320
Speaker 2: he talks to chat GPT every day. He's like one

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Speaker 2: of the probably one of the world's biggest users of

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Speaker 2: it's like talk to you function, and he has been

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Speaker 2: convinced by it that he's going to build God. But

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Speaker 2: because he is a because he is one of the

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Speaker 2: central economic planners of the global economy, he gets to

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Speaker 2: allocate capital according to his delusion, as opposed to the

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Speaker 2: porschmuck dying on the path train who just gets like

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Speaker 2: scraped off the wall that Masao she saw gets to

356
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Speaker 2: fucking run through. Yeah, it's a bit like the bit

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Speaker 2: like Peter t I think also went crazy with ais

358
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Speaker 2: more unhinged in public example, recently said that the pulp

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Speaker 2: is a Chinese Communist Party agent, which he's not supposed

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Speaker 2: to know, right, Look that's you're not you.

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Speaker 3: Look, you don't have any.

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Speaker 4: Fans And the odds of him having figured that out

363
00:18:14,560 --> 00:18:17,960
Speaker 4: were crazy low. So like it's no shame on the Vatican.

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Speaker 4: But like Jesus, guys, the other thing.

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Speaker 3: Is as well, is it's like on top of just

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Speaker 3: the ridiculousness of this, And if you had a homeless

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Speaker 3: man on the tube saying jus.

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Speaker 8: Us about he's golden egg VECTORI inside the goose, you

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Speaker 8: see the internal mechanism, right, what you see the eggs

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Speaker 8: that produces them is the factories you would like hopefully

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Speaker 8: get them the help they need it.

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Speaker 3: But because he invested in alib Barba, we have to

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Speaker 3: like take this shit seriously now. Slide fifty six is

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Speaker 3: also good because he invents a new kind of goose

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Speaker 3: math where egg value. You were wasting on this, I've

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00:18:54,560 --> 00:18:57,919
Speaker 3: been using Tarren's mallicks old goose math. You've heard of

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00:18:57,960 --> 00:19:01,119
Speaker 3: girl math. Get ready for goose man. It's like goose

378
00:19:01,240 --> 00:19:06,320
Speaker 3: value alpha. I don't know, I'm not going to come

379
00:19:06,359 --> 00:19:09,040
Speaker 3: up with an actual thing because soft Bank is a

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00:19:09,119 --> 00:19:11,639
Speaker 3: valueless company outside of the things it helps. It is

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Speaker 3: just a large holding company that is kind of a

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Speaker 3: big part. It's like the second or third largest company

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Speaker 3: on the Japanese stock market. And it's like that. The

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Speaker 3: other thing that I keep coming back to that really

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Speaker 3: isn't shown here is that's not actually the net asset

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00:19:27,960 --> 00:19:31,119
Speaker 3: value of soft Bank. Like that's like I'm going to

387
00:19:31,160 --> 00:19:33,760
Speaker 3: just go right, Like the net asset value right now

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00:19:34,000 --> 00:19:38,240
Speaker 3: is yeah, forty trillion, Like this is from soft Bank's

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Speaker 3: own website. So what he is doing here is he's like, yeah,

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Speaker 3: I'm adding the other thirty trillion from open Ai. He's

391
00:19:43,800 --> 00:19:46,280
Speaker 3: just adding He's just making up how much open ai

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Speaker 3: is worth. And as eager listeners will know right now,

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Speaker 3: Masiyoshi Son tried to get a margin loan on this

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Speaker 3: open Ai stock all of it, and yeah, then couldn't.

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Speaker 3: The banks were like, no, thank you.

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Speaker 2: I was going to play this game later, but can

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Speaker 2: we get an applause sound effectfully? Is because we're gonna

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Speaker 2: have an impromptu episode of everybody's favorite gamey uh with

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Speaker 2: with So far it's only contested possibly host et Cron,

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Speaker 2: welcome to Is that good?

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Speaker 3: Yeah? Thank you for coming on the show, sprinting down

402
00:20:35,400 --> 00:20:42,960
Speaker 3: from the audience. Yeah, just chosen again for I really

403
00:20:43,000 --> 00:20:47,800
Speaker 3: hope I get on? Is that good? Atron? My fingers crossed?

404
00:20:48,080 --> 00:20:51,960
Speaker 4: Liked you have like a do you have like a phone?

405
00:20:52,000 --> 00:20:52,320
Speaker 6: A friend?

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Speaker 3: Option on? That? Just a switch, It's just an unlabeled switch.

407
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Speaker 3: So ed, thank you for playing? Is that good? For

408
00:21:00,440 --> 00:21:04,120
Speaker 3: having me? So? All right?

409
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Speaker 2: The situation you just described where Masseo chi san, who's

410
00:21:08,240 --> 00:21:10,960
Speaker 2: already borrowed a lot of money to invest in open Ai,

411
00:21:11,400 --> 00:21:14,919
Speaker 2: essentially like a sports sports gambler paying for his bets

412
00:21:14,920 --> 00:21:18,440
Speaker 2: by borrowing from the mob. The bet on open It

413
00:21:18,520 --> 00:21:20,399
Speaker 2: if you can't roll over the bet to keep on

414
00:21:20,440 --> 00:21:22,880
Speaker 2: doubling down on the bet, is that good?

415
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Speaker 3: Yesl like you for the questions again, it's amazing. It's

416
00:21:28,760 --> 00:21:32,439
Speaker 3: just really funny as well because literally the we keep

417
00:21:32,480 --> 00:21:34,600
Speaker 3: coming back to the point. Literally the only reason we

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Speaker 3: don't treat this man like he's an insane person is

419
00:21:37,760 --> 00:21:41,320
Speaker 3: because he is. He hasn't blown himself up yet, like

420
00:21:41,440 --> 00:21:43,800
Speaker 3: it really and it is. Yeah, it's like he has

421
00:21:43,840 --> 00:21:46,440
Speaker 3: taken out so much there on open Ai, like way

422
00:21:46,480 --> 00:21:49,760
Speaker 3: more than we work, like historic ammounts, and he's just

423
00:21:49,960 --> 00:21:52,359
Speaker 3: and he's even the more thing. But he's doing Goose

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00:21:52,400 --> 00:21:56,040
Speaker 3: fraud right now, Like he's like fifty seven claims seventy

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Speaker 3: four trillion dollars of egg value or show older value,

426
00:22:00,240 --> 00:22:05,280
Speaker 3: and that's not what's on bank's website. It's thirty trillion dollars. Sorry,

427
00:22:05,280 --> 00:22:07,920
Speaker 3: it's forty eight point two six trillion yen is the

428
00:22:08,080 --> 00:22:11,480
Speaker 3: xit value of holdings. That's lower than seventy four. I'm

429
00:22:11,520 --> 00:22:14,360
Speaker 3: pretty new to Goose math, but I can see that

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Speaker 3: that is still a drives me insane actually because in

431
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Speaker 3: a world of deep equality, Masayoshi Son gets away with

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Speaker 3: it only because he's a whimsical man out in Japan,

433
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Speaker 3: like because he's fun he is, And the thing is,

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Speaker 3: eight people, you're like, oh, we got ai psychosis. It's

435
00:22:33,640 --> 00:22:36,439
Speaker 3: like I think he might have had it already, like

436
00:22:36,560 --> 00:22:39,480
Speaker 3: without he just got it for the first case of

437
00:22:40,040 --> 00:22:44,080
Speaker 3: world's first case of ai psychosis inflicted before twenty twenty two. Well,

438
00:22:44,440 --> 00:22:47,320
Speaker 3: first person to get ai psychosis from GPT two. I

439
00:22:47,359 --> 00:22:51,600
Speaker 3: actually want to read you a quick quote about Massa

440
00:22:51,680 --> 00:22:55,399
Speaker 3: Yoshi son from an article this is I promise you

441
00:22:55,520 --> 00:22:58,320
Speaker 3: this is worthwhile. It's actually very important to understand the

442
00:22:58,359 --> 00:23:03,400
Speaker 3: whole goose thing. So from a Kakashi great pseudonymous analyst guy.

443
00:23:03,440 --> 00:23:06,480
Speaker 3: I followed, So okay, his dad was talking about him

444
00:23:06,480 --> 00:23:08,400
Speaker 3: and sixty year old Matsio. She signed. He was super

445
00:23:08,400 --> 00:23:10,800
Speaker 3: wrestling his older brother and losing badly, but he refused

446
00:23:10,840 --> 00:23:12,800
Speaker 3: to stop. When his father finally he pulled him away.

447
00:23:12,840 --> 00:23:15,919
Speaker 3: The boys eyes were in Mitsunari's words. Is that like

448
00:23:16,040 --> 00:23:18,679
Speaker 3: an animal's a wolf size? I thought to myself, this

449
00:23:18,840 --> 00:23:19,960
Speaker 3: bustard is not human.

450
00:23:22,000 --> 00:23:26,560
Speaker 4: Doing hype edits for your son like playfight thing is

451
00:23:26,640 --> 00:23:27,320
Speaker 4: really funny.

452
00:23:27,480 --> 00:23:30,040
Speaker 3: I just really like that him just getting his ass

453
00:23:30,119 --> 00:23:33,000
Speaker 3: kicked when he's six and he's like he just turns round.

454
00:23:33,040 --> 00:23:37,919
Speaker 2: He just has like demonie a world's first person to

455
00:23:37,960 --> 00:23:41,040
Speaker 2: have laser eyes in real life. Look, here's the thing.

456
00:23:41,040 --> 00:23:42,720
Speaker 2: There's the other thing, right, we're talking about marso she

457
00:23:42,800 --> 00:23:47,520
Speaker 2: sign's life. The presentation concludes with what used to be

458
00:23:47,560 --> 00:23:49,800
Speaker 2: his fifty year life plan, but now is his sixty

459
00:23:49,880 --> 00:23:53,120
Speaker 2: year life It's so good. So his fifty year life

460
00:23:53,119 --> 00:23:56,640
Speaker 2: plan was get acknowledged in your twenties. Finance a war

461
00:23:56,720 --> 00:24:00,639
Speaker 2: chest in your thirties. In your forties, take on a

462
00:24:00,760 --> 00:24:03,199
Speaker 2: challenge in your fifties.

463
00:24:03,160 --> 00:24:05,919
Speaker 3: Complete business. To do that, just like a bucket, like

464
00:24:06,000 --> 00:24:08,080
Speaker 3: ins any of them, any of them like an eighteen

465
00:24:08,160 --> 00:24:13,560
Speaker 3: year old girls Instagram post. To take take on a challenge.

466
00:24:13,600 --> 00:24:16,840
Speaker 2: Sure, remember ice bucket challenge for als and twenty eleven.

467
00:24:17,000 --> 00:24:21,240
Speaker 2: Take on that challenge. Done to finish the decade. Fifties

468
00:24:21,320 --> 00:24:25,399
Speaker 2: complete business okay, so uh, to complete all the business.

469
00:24:25,440 --> 00:24:27,040
Speaker 3: That means yeah, yeah.

470
00:24:27,680 --> 00:24:31,600
Speaker 2: Sixties handover business to next generation. But no fucking cross

471
00:24:31,680 --> 00:24:35,480
Speaker 2: thou no crossed out. This is the sixty year life plan.

472
00:24:35,800 --> 00:24:39,160
Speaker 2: Sixties crossed out, handover business to next generation. Gone, It's

473
00:24:39,200 --> 00:24:42,320
Speaker 2: not replaced. It now just has a seventies value, which

474
00:24:42,359 --> 00:24:47,199
Speaker 2: is realizing ASI or artificial super intelligence a similar a

475
00:24:47,280 --> 00:24:49,240
Speaker 2: term that's used in this is.

476
00:24:49,400 --> 00:24:53,600
Speaker 4: Like not a new Cubris. Right, you could have done

477
00:24:53,600 --> 00:24:56,560
Speaker 4: this at any point in human history. There were guys

478
00:24:56,640 --> 00:25:00,879
Speaker 4: back in the day whose life plan was twenty unite

479
00:25:00,920 --> 00:25:06,000
Speaker 4: Southern Song Dynasty, thirties, conquer Northern Song Dynasty. Forties, establish

480
00:25:06,119 --> 00:25:11,720
Speaker 4: mandate as son of Heaven. Fifties alchemy, sixties alchemy, seventies,

481
00:25:12,040 --> 00:25:14,800
Speaker 4: never die.

482
00:25:15,280 --> 00:25:17,119
Speaker 6: I feel like it's missing, like a little detour.

483
00:25:17,119 --> 00:25:18,320
Speaker 5: I feel like you need like a bit of a

484
00:25:18,320 --> 00:25:20,239
Speaker 5: side quest to sort of really make this fun, Like

485
00:25:20,600 --> 00:25:22,920
Speaker 5: you know, you should, like, you know, fifty five start

486
00:25:22,920 --> 00:25:23,280
Speaker 5: a band.

487
00:25:23,320 --> 00:25:25,000
Speaker 6: I don't know, there's so many.

488
00:25:24,800 --> 00:25:27,919
Speaker 3: Like, yeah, sixty learn to ride a motorcycle. No, it's

489
00:25:28,000 --> 00:25:30,560
Speaker 3: it's in this case, it's really just like the most

490
00:25:30,600 --> 00:25:34,880
Speaker 3: obvious thing of like, twenties conquer entire known world. Thirties

491
00:25:34,920 --> 00:25:38,600
Speaker 3: weep because there's no more worlds to conquer. Forties build

492
00:25:38,800 --> 00:25:44,359
Speaker 3: giant statue. Fifties start reinforcing statue at legs. Yeah. I

493
00:25:44,480 --> 00:25:46,639
Speaker 3: also want to be clear, it's really funny to do

494
00:25:46,720 --> 00:25:50,320
Speaker 3: this insane hour and fifty minute long presentation where you're

495
00:25:50,359 --> 00:25:55,280
Speaker 3: like slide four JP, why one quadrillion and they just

496
00:25:55,320 --> 00:25:58,040
Speaker 3: be like, and I'm not retiring for at least another decade.

497
00:25:58,520 --> 00:26:01,640
Speaker 3: Fuck you, I don't. I don't think that I live

498
00:26:01,680 --> 00:26:04,679
Speaker 3: in a functional enough economy or society to have a

499
00:26:04,760 --> 00:26:08,680
Speaker 3: life plan, Like my life plan is like twenties, fuck

500
00:26:08,720 --> 00:26:11,440
Speaker 3: around this mental health and drop out of UNI, thirties,

501
00:26:11,520 --> 00:26:18,600
Speaker 3: podcast forces, podcast, fifties podcast, sixties climate Wars. Maybe yeah,

502
00:26:18,960 --> 00:26:20,840
Speaker 3: woke Battalion in Climate Wars.

503
00:26:21,240 --> 00:26:23,119
Speaker 4: She thinks the climate Wars I'm gonna start until she's

504
00:26:23,119 --> 00:26:24,560
Speaker 4: in a sixties fucking idiot.

505
00:26:25,680 --> 00:26:28,640
Speaker 2: So this is but this is basically this is This

506
00:26:28,680 --> 00:26:30,639
Speaker 2: is the story of someone who has I think we

507
00:26:30,760 --> 00:26:32,720
Speaker 2: come back round to this because think it's very important

508
00:26:33,040 --> 00:26:37,520
Speaker 2: someone who has been driven to mania about this thing,

509
00:26:37,680 --> 00:26:40,600
Speaker 2: but who happens to be able to force that mania

510
00:26:40,680 --> 00:26:41,640
Speaker 2: upon everybody else.

511
00:26:41,800 --> 00:26:42,320
Speaker 3: Yeah.

512
00:26:42,359 --> 00:26:44,399
Speaker 2: And you know, one of the things I want to

513
00:26:44,400 --> 00:26:46,679
Speaker 2: dig a little deeper into actually is his claim that

514
00:26:46,800 --> 00:26:51,200
Speaker 2: artificial superintelligence is coming. Artificial super intelligence and artificial general intelligence,

515
00:26:51,200 --> 00:26:54,200
Speaker 2: I think are used pretty interchangeably. He uses artificial super

516
00:26:54,800 --> 00:26:58,720
Speaker 2: the same thing. Yeah, and so he basically Maso she

517
00:26:58,800 --> 00:27:01,840
Speaker 2: Son is Sam Altman? Are now so Sam Altman's guys?

518
00:27:01,880 --> 00:27:05,760
Speaker 2: Excuse me? Told Masseoshi Son probably in the we just

519
00:27:05,760 --> 00:27:08,000
Speaker 2: need another can you take out alone to give us

520
00:27:08,000 --> 00:27:11,840
Speaker 2: a loan? Said that an AI model is designing the

521
00:27:11,840 --> 00:27:13,200
Speaker 2: next future AI model.

522
00:27:13,240 --> 00:27:16,640
Speaker 3: It open a up. Ah, so like sorry, son said,

523
00:27:17,040 --> 00:27:19,439
Speaker 3: you can't. You can't see the model or anything to

524
00:27:19,480 --> 00:27:22,200
Speaker 3: do with the model. Read this like philosopher, we got

525
00:27:22,240 --> 00:27:25,440
Speaker 3: in to talk about you know, the cost whatever. It's

526
00:27:25,560 --> 00:27:27,919
Speaker 3: just like it's if they find a new key to

527
00:27:28,000 --> 00:27:31,159
Speaker 3: jingle and it's like, well, why don't we invent I

528
00:27:31,160 --> 00:27:33,040
Speaker 3: don't know, make the model do something new. It's like,

529
00:27:33,080 --> 00:27:35,199
Speaker 3: what if we just made the model do that, or

530
00:27:35,240 --> 00:27:39,240
Speaker 3: if we just fucking you know, like the model could

531
00:27:39,320 --> 00:27:41,520
Speaker 3: do the model stuff and we could just sit here

532
00:27:41,560 --> 00:27:44,359
Speaker 3: and take the cash massire and like it's the laziest

533
00:27:44,400 --> 00:27:47,200
Speaker 3: thing in the world. It's like if any any other situation,

534
00:27:47,320 --> 00:27:49,720
Speaker 3: it's like I'll have someone else do it. You'd probably

535
00:27:49,760 --> 00:27:51,399
Speaker 3: be like they'd be like, well, no, you've got to

536
00:27:51,440 --> 00:27:54,080
Speaker 3: do something I gave you gave you forty billion dollars,

537
00:27:54,400 --> 00:27:56,480
Speaker 3: like you probably want to do something with it. But

538
00:27:56,600 --> 00:28:00,320
Speaker 3: Macioshi sounds like hell yeah. What's funny is mashi Yoshi's son,

539
00:28:00,960 --> 00:28:04,280
Speaker 3: Sam Altman, came to him in twenty seventeen, I think,

540
00:28:04,320 --> 00:28:07,920
Speaker 3: and asked for ten billion dollars. Mashioshi's son said yes,

541
00:28:09,359 --> 00:28:11,879
Speaker 3: But then Sam Altman just kind of walked off and

542
00:28:11,920 --> 00:28:15,480
Speaker 3: took the money from from Microsoft, and that drove Massaiyoshi's

543
00:28:15,480 --> 00:28:18,640
Speaker 3: son insane. He was like, oh my fuck, what ah,

544
00:28:18,840 --> 00:28:21,840
Speaker 3: I missed out the one that got away, and now

545
00:28:21,880 --> 00:28:25,200
Speaker 3: I will shower her with jewels and gems. She will

546
00:28:25,240 --> 00:28:26,760
Speaker 3: be mine.

547
00:28:27,080 --> 00:28:29,760
Speaker 2: Yeah, and like the time to get it if you

548
00:28:29,800 --> 00:28:31,720
Speaker 2: wanted to sort of make money on that, the time

549
00:28:31,720 --> 00:28:33,360
Speaker 2: to get in was then, and the time to get

550
00:28:33,359 --> 00:28:33,960
Speaker 2: out is now.

551
00:28:34,040 --> 00:28:39,080
Speaker 3: Yeah. He really the worst times his only I would

552
00:28:39,160 --> 00:28:42,800
Speaker 3: say maybe if Open Eye goes public, which is now

553
00:28:42,840 --> 00:28:46,680
Speaker 3: an if, he might have done very well based on

554
00:28:46,800 --> 00:28:50,320
Speaker 3: the first forty billion, the next thirty at the highest

555
00:28:50,320 --> 00:28:55,800
Speaker 3: possible valuation, insanely stupid. Just and also, these these hogs

556
00:28:55,800 --> 00:28:58,560
Speaker 3: are going to need more money than this thirty billion dollars.

557
00:28:58,680 --> 00:29:01,160
Speaker 3: We're going to go into that. Oh yeah, we're gonna

558
00:29:01,200 --> 00:29:03,640
Speaker 3: go We're gonna need more money. Uh.

559
00:29:03,680 --> 00:29:05,960
Speaker 2: But so but just before we move on from Sun,

560
00:29:06,080 --> 00:29:08,360
Speaker 2: he said, So that's gonna happen to all the major models.

561
00:29:08,440 --> 00:29:09,600
Speaker 2: So once that happened.

562
00:29:09,280 --> 00:29:14,080
Speaker 4: Before we move on from Sun, like that will be blunt.

563
00:29:14,160 --> 00:29:16,400
Speaker 2: So once that happens, the model generates the next model,

564
00:29:16,440 --> 00:29:18,440
Speaker 2: and it's going to be exponentially smarter than all of us.

565
00:29:18,480 --> 00:29:21,080
Speaker 2: That's a super intelligence. In my mind, I thought it

566
00:29:21,120 --> 00:29:22,920
Speaker 2: was coming in four years instead of the next ten.

567
00:29:23,080 --> 00:29:25,400
Speaker 2: Now I'm saying it's coming in the next two. Then

568
00:29:25,720 --> 00:29:28,080
Speaker 2: the CNBC article goes on to say the soft Bank

569
00:29:28,160 --> 00:29:30,960
Speaker 2: CEO says he currently uses open ayes Chat GPT for

570
00:29:31,080 --> 00:29:33,240
Speaker 2: up to three hours a day as the AI is

571
00:29:33,240 --> 00:29:35,680
Speaker 2: smarter than he is on quote most subjects.

572
00:29:36,000 --> 00:29:39,040
Speaker 3: That's so good. I believe that three hours a day

573
00:29:39,200 --> 00:29:39,480
Speaker 3: is so.

574
00:29:39,920 --> 00:29:42,080
Speaker 2: If you're awake for twelve hours, that's a quarter of

575
00:29:42,120 --> 00:29:45,680
Speaker 2: your time spent just talking to the mirror that drives

576
00:29:45,720 --> 00:29:46,360
Speaker 2: you crazy.

577
00:29:46,640 --> 00:29:47,280
Speaker 3: That's cool.

578
00:29:47,600 --> 00:29:50,280
Speaker 2: It's what if narcissist wasn't just sucked into the pool

579
00:29:50,320 --> 00:29:51,760
Speaker 2: but also driven mad by it.

580
00:29:51,920 --> 00:29:55,760
Speaker 3: It's just it's so good as well, because the grandest

581
00:29:55,800 --> 00:29:58,520
Speaker 3: theme of this, it's pretty much all of these CEOs

582
00:29:58,600 --> 00:30:03,320
Speaker 3: have AI psychosis because usually even with human beings, there

583
00:30:03,360 --> 00:30:05,440
Speaker 3: is a limit to how many ideas someone will say

584
00:30:05,480 --> 00:30:08,160
Speaker 3: are good or at least before you fire them. With

585
00:30:08,280 --> 00:30:10,959
Speaker 3: an AI, you can just brate them into any idea

586
00:30:11,080 --> 00:30:13,760
Speaker 3: you could just be I heard a story of someone

587
00:30:13,920 --> 00:30:16,520
Speaker 3: at a major tech company where they weren't they didn't

588
00:30:16,520 --> 00:30:20,200
Speaker 3: have security access to access something, and they just said, actually, yes,

589
00:30:20,320 --> 00:30:22,479
Speaker 3: I do to the internal LM and it gave it

590
00:30:22,520 --> 00:30:25,880
Speaker 3: to them like it's just like this is just like

591
00:30:26,000 --> 00:30:28,240
Speaker 3: anything it disagrees with. You could just be like, actually

592
00:30:28,320 --> 00:30:31,920
Speaker 3: that's true and it will go yeah, absolutely, yeah, sure,

593
00:30:32,120 --> 00:30:35,120
Speaker 3: Like just so can you imagine the shit he's saying this, Like,

594
00:30:35,360 --> 00:30:38,600
Speaker 3: you know, you're exactly right, the goose will lay lay

595
00:30:38,680 --> 00:30:42,600
Speaker 3: golden eggs forever. You're absolutely right. I would love to

596
00:30:42,640 --> 00:30:44,959
Speaker 3: read his logs. I'd love to read the insane back

597
00:30:45,040 --> 00:30:46,960
Speaker 3: and forth he's having with them.

598
00:30:47,120 --> 00:30:51,880
Speaker 2: Masseyoshi San, your understanding of goose biology isn't isn't just detailed,

599
00:30:51,920 --> 00:30:52,560
Speaker 2: it's prescient.

600
00:30:55,160 --> 00:30:59,320
Speaker 3: So if shat GBT role playing as a goose, no,

601
00:30:59,600 --> 00:31:01,800
Speaker 3: I think you you need GROX adult mode for that.

602
00:31:01,880 --> 00:31:02,240
Speaker 3: I showed.

603
00:31:06,040 --> 00:31:08,320
Speaker 2: So here's what you've said. Actually, edam at Masso she

604
00:31:08,360 --> 00:31:11,160
Speaker 2: saw in an open AI. If Open AI doesn't go public,

605
00:31:11,160 --> 00:31:13,680
Speaker 2: there's a very real possibility that soft bank collapses or

606
00:31:13,680 --> 00:31:15,440
Speaker 2: at the very least is forced to finally put an

607
00:31:15,520 --> 00:31:18,360
Speaker 2: end to the era of unrivaled financial risk. It's easy

608
00:31:18,360 --> 00:31:20,040
Speaker 2: to like Masso, she saw, on to laugh at his

609
00:31:20,040 --> 00:31:22,760
Speaker 2: goofy Geese related presentations. And I'll say, as a side dope,

610
00:31:22,920 --> 00:31:26,120
Speaker 2: it is and his ridiculous statements about the future. But

611
00:31:26,240 --> 00:31:28,560
Speaker 2: in reality, he's a deranged, delusional man with too much

612
00:31:28,600 --> 00:31:30,800
Speaker 2: money and a few lucky breaks that have saved him annihilation.

613
00:31:31,200 --> 00:31:33,560
Speaker 2: His future lies in Sam Altman's hands, and if this

614
00:31:33,600 --> 00:31:35,840
Speaker 2: is what finally ends his wasteful, reckless reign, it's a

615
00:31:35,880 --> 00:31:38,640
Speaker 2: well deserved punishment for believing every damp, porked up white

616
00:31:38,640 --> 00:31:41,320
Speaker 2: boy to beg him for a billion dollars. He's an enabler,

617
00:31:41,400 --> 00:31:44,480
Speaker 2: enabled by other enablers that's created a culture of unbelievable

618
00:31:44,560 --> 00:31:45,360
Speaker 2: risk and destruction.

619
00:31:46,280 --> 00:31:49,480
Speaker 3: Yeah, tell me you really think that guy. That guy's smart, like,

620
00:31:51,360 --> 00:31:53,640
Speaker 3: but he's really funny as well. Because we live in

621
00:31:54,320 --> 00:31:56,440
Speaker 3: My girlfriend brought this up. There's a Twilight Zone episode

622
00:31:56,440 --> 00:31:58,880
Speaker 3: where there's a kid who if he doesn't if he

623
00:31:58,920 --> 00:32:01,600
Speaker 3: doesn't believe you're happy, turns you into an ear of corn.

624
00:32:01,960 --> 00:32:04,840
Speaker 3: We basically live in that society now where it's like

625
00:32:05,280 --> 00:32:07,680
Speaker 3: all of these CEOs get caught. The AI bubble is

626
00:32:07,720 --> 00:32:10,920
Speaker 3: just the large coddling. It's just like, yeah, the rich

627
00:32:10,960 --> 00:32:14,680
Speaker 3: people always have good ideas. We must orient ourselves around them.

628
00:32:14,800 --> 00:32:17,840
Speaker 3: Despite the fact that most of the industry's revenue is

629
00:32:17,840 --> 00:32:20,520
Speaker 3: either anthropic and open ai or anthropic and open ai

630
00:32:20,680 --> 00:32:23,360
Speaker 3: paying for the compute to lose money. Like it's not

631
00:32:23,760 --> 00:32:27,560
Speaker 3: even sophisticated. It's just that it's people nibbling around the

632
00:32:27,680 --> 00:32:31,360
Speaker 3: edges and massiosi son. Literally, I must be clear, had

633
00:32:31,360 --> 00:32:34,520
Speaker 3: he just not invested in open ai, SoftBank would be

634
00:32:34,560 --> 00:32:38,520
Speaker 3: doing great, it would be it would perhaps not have

635
00:32:38,680 --> 00:32:42,080
Speaker 3: had the massive on paper gain of open ai stop

636
00:32:42,160 --> 00:32:44,680
Speaker 3: going up, but like it probably also wouldn't have needed

637
00:32:44,760 --> 00:32:50,160
Speaker 3: forty fucking billion dollars forty billion dollars. It's just and

638
00:32:50,560 --> 00:32:53,200
Speaker 3: I I wasn't able to add up all the there

639
00:32:53,400 --> 00:32:55,960
Speaker 3: and do a deep analysis of that part yet, but

640
00:32:56,480 --> 00:32:58,800
Speaker 3: it really does seem that at some point he's just

641
00:32:58,840 --> 00:33:00,760
Speaker 3: not going to be able to refs a loan and

642
00:33:00,840 --> 00:33:04,160
Speaker 3: run out of money. It's it's it's just like a

643
00:33:04,200 --> 00:33:07,120
Speaker 3: teenager with a credit card, except it's one hundred and

644
00:33:07,160 --> 00:33:10,240
Speaker 3: fifty billion dollars of debt and there's gooseymbol.

645
00:33:10,800 --> 00:33:13,440
Speaker 2: And what what open a what SoftBank is doing via

646
00:33:13,520 --> 00:33:16,320
Speaker 2: open ai right now? This is a very refreshingly candid

647
00:33:16,360 --> 00:33:19,840
Speaker 2: telecoms dot com article, is that it's going it's addition,

648
00:33:19,960 --> 00:33:22,400
Speaker 2: going to take on additional debt in order to build

649
00:33:22,520 --> 00:33:25,360
Speaker 2: data centers, more data centers in the US, tens of

650
00:33:25,360 --> 00:33:27,440
Speaker 2: billions of dollars in AI data centers in the US,

651
00:33:28,400 --> 00:33:30,520
Speaker 2: and giving more money like of that to open AI

652
00:33:30,680 --> 00:33:32,760
Speaker 2: so that the data center project is called I believe

653
00:33:32,880 --> 00:33:38,400
Speaker 2: sb NEO yep, and they are they are going to

654
00:33:38,520 --> 00:33:42,120
Speaker 2: again say okay, we're going to build ten ten gigawatts

655
00:33:42,160 --> 00:33:43,840
Speaker 2: of of of data center.

656
00:33:43,960 --> 00:33:46,800
Speaker 3: Right. But quick question. We talk about data.

657
00:33:46,600 --> 00:33:48,280
Speaker 2: Centers a lot, you and I. We're talk aboutdata centers

658
00:33:48,280 --> 00:33:49,800
Speaker 2: a lot on this show. You and I talk about

659
00:33:49,880 --> 00:33:54,040
Speaker 2: data centers a lot. Do you have any of the

660
00:33:54,360 --> 00:33:57,960
Speaker 2: enormous supply chain bottlenecks that have largely prevented data centers

661
00:33:57,960 --> 00:34:01,120
Speaker 2: from being built? But yet, let alone the sort of

662
00:34:01,160 --> 00:34:03,840
Speaker 2: let's say, lack of demand from outside the industry for

663
00:34:03,880 --> 00:34:07,480
Speaker 2: their services, are any of those bottlenecks alleviated?

664
00:34:07,560 --> 00:34:10,080
Speaker 3: Can you get a gas turbine right now? Oh? And

665
00:34:10,120 --> 00:34:12,239
Speaker 3: the thing is as well, is just data centers have

666
00:34:12,320 --> 00:34:14,640
Speaker 3: taken like eighteen to thirty six months to build. So

667
00:34:15,080 --> 00:34:17,600
Speaker 3: him saying we're gonna build five or ten. He did

668
00:34:17,600 --> 00:34:19,800
Speaker 3: a thing with France as well. It doesn't bear repeating.

669
00:34:20,040 --> 00:34:23,920
Speaker 3: Something with Emmanuel Macaran and he's like, if they're building

670
00:34:23,920 --> 00:34:26,440
Speaker 3: five gig what's their ten? What's here? You may as

671
00:34:26,440 --> 00:34:29,520
Speaker 3: well be talking about the year twenty nineties, like, because

672
00:34:31,000 --> 00:34:34,080
Speaker 3: just the speed of construction. Put aside any thoughts I

673
00:34:34,160 --> 00:34:36,520
Speaker 3: have about the AI bubble. The speed of building these

674
00:34:36,520 --> 00:34:40,480
Speaker 3: things is very slow, and that's before the power comes in.

675
00:34:40,520 --> 00:34:44,440
Speaker 3: It's just the power doesn't exist either. Again, if you

676
00:34:44,560 --> 00:34:48,160
Speaker 3: took away the money, this person would sound fucking in set.

677
00:34:48,160 --> 00:34:50,000
Speaker 3: Well they do right now, but like you would laugh

678
00:34:50,040 --> 00:34:51,680
Speaker 3: them out of the building. If just a random guy

679
00:34:51,760 --> 00:34:55,160
Speaker 3: was like, I'm gonna raise ten gig what's so a

680
00:34:55,280 --> 00:34:58,240
Speaker 3: trillion dollars? Because a giga what is now one hundred

681
00:34:58,239 --> 00:35:01,280
Speaker 3: billion dollars trillion dollars, I'm gonna raise a trillion dollars

682
00:35:01,280 --> 00:35:04,600
Speaker 3: for data center and then one company's gonna rent all

683
00:35:04,640 --> 00:35:07,360
Speaker 3: of it, and yeah, that company loses money, but like

684
00:35:08,200 --> 00:35:11,440
Speaker 3: they won't and anyone else you'd be like, you sound

685
00:35:11,480 --> 00:35:14,279
Speaker 3: like a moron, man. But because it's Mashioshi's son, because

686
00:35:14,280 --> 00:35:20,320
Speaker 3: it's o Benai, Sam Moorman, because it's Dario Amade, You're like, ah, yeah, yeah, absolutely, yeah, absolutely,

687
00:35:20,360 --> 00:35:21,840
Speaker 3: that makes these are the guys.

688
00:35:22,239 --> 00:35:25,440
Speaker 2: They're the guy they're the pharaohs all things have And

689
00:35:25,640 --> 00:35:29,720
Speaker 2: it went with inequality accelerating with the bets, the actual

690
00:35:29,800 --> 00:35:32,240
Speaker 2: bets on the future getting better, getting smaller and smaller

691
00:35:32,280 --> 00:35:35,320
Speaker 2: and smaller and concentrated on a smaller and smaller number

692
00:35:35,360 --> 00:35:38,839
Speaker 2: of big hands. If you like, you get a kind

693
00:35:38,880 --> 00:35:41,480
Speaker 2: of you sort of rebuild like a pharonic system of

694
00:35:41,560 --> 00:35:45,000
Speaker 2: kingship from first principles, where you know what you can

695
00:35:45,160 --> 00:35:47,960
Speaker 2: just be like, you know what, we're work. We're monotheistic.

696
00:35:48,000 --> 00:35:50,880
Speaker 2: Now Egyptian polytheism is done. We're gonna try monotheism for

697
00:35:51,080 --> 00:35:56,160
Speaker 2: three generations. But like the problem is also being in

698
00:35:56,200 --> 00:35:58,239
Speaker 2: a pharonic system like that, with sort of this much

699
00:35:58,239 --> 00:36:02,560
Speaker 2: concentration of give just this much allocation of productive capacity

700
00:36:02,600 --> 00:36:07,040
Speaker 2: to madness is quite I'm gonna surprise you, quite damaging

701
00:36:07,880 --> 00:36:10,360
Speaker 2: because the question of can you get a gas turbine

702
00:36:10,840 --> 00:36:13,759
Speaker 2: that's super important for lots of stuff other than AI

703
00:36:13,840 --> 00:36:18,200
Speaker 2: data centers. It's just these data centers are in some cases,

704
00:36:18,200 --> 00:36:20,360
Speaker 2: because of political pressure, like in the UK, able to

705
00:36:20,360 --> 00:36:22,560
Speaker 2: skip the queue for certain kinds of planning or grid

706
00:36:22,560 --> 00:36:27,319
Speaker 2: hook up capacity, or you know, they're they're just they're

707
00:36:27,400 --> 00:36:30,040
Speaker 2: clogging up the order book for these things that we'll

708
00:36:30,080 --> 00:36:32,480
Speaker 2: just get deployed to these data centers that we're going

709
00:36:32,520 --> 00:36:35,080
Speaker 2: to explore if people are let's say, using enough and

710
00:36:35,440 --> 00:36:39,840
Speaker 2: profitably enough to make them viable, and all those spiking

711
00:36:39,880 --> 00:36:43,960
Speaker 2: infrastructure demand has now is now going out to other

712
00:36:44,239 --> 00:36:49,120
Speaker 2: It's like spreading through other pieces of like infrastructure, like

713
00:36:49,239 --> 00:36:50,720
Speaker 2: hard to build infrastructure equipment.

714
00:36:50,840 --> 00:36:55,239
Speaker 4: Right, quick question, has then the thing else happened recently

715
00:36:55,760 --> 00:36:59,040
Speaker 4: to maybe fuck up like global infrastructure.

716
00:36:59,239 --> 00:36:59,840
Speaker 3: That's all.

717
00:37:01,719 --> 00:37:04,600
Speaker 2: Something in the World Cup maybe yeah, the English world

718
00:37:04,640 --> 00:37:05,840
Speaker 2: people watching World.

719
00:37:05,640 --> 00:37:10,719
Speaker 4: Cup because I kind of feel like the strace of

720
00:37:10,719 --> 00:37:14,080
Speaker 4: Homer is fucking up the supply chain for this and

721
00:37:14,160 --> 00:37:16,400
Speaker 4: everything else. It's sort of like one point on the

722
00:37:16,680 --> 00:37:21,480
Speaker 4: sort of trifecta, the palace logo of we are really

723
00:37:21,520 --> 00:37:26,560
Speaker 4: fucking bad at long latency stuff as people. So like

724
00:37:26,920 --> 00:37:31,200
Speaker 4: it's I'm sure all of the consequences of this will

725
00:37:31,280 --> 00:37:36,040
Speaker 4: just be fine for an extremely like fragile, sort of

726
00:37:36,120 --> 00:37:39,960
Speaker 4: delicately balanced to goose fucking portfolio. But that actually leads

727
00:37:40,000 --> 00:37:42,319
Speaker 4: me to an important point, which is, let's take the

728
00:37:42,320 --> 00:37:44,120
Speaker 4: AI people at face value.

729
00:37:44,160 --> 00:37:45,520
Speaker 3: Don't know why we're doing that, but let's do it.

730
00:37:46,320 --> 00:37:50,640
Speaker 3: They are saying because based on Nvidia CEO Jensen Hwang says,

731
00:37:50,680 --> 00:37:53,920
Speaker 3: trillion dollars of GPU's visibility sales through the end of

732
00:37:53,960 --> 00:37:57,160
Speaker 3: twenty twenty seven, it's about four hundred and five hundred

733
00:37:57,200 --> 00:38:00,120
Speaker 3: billion dollars a year worth of AI compute revenue. You

734
00:38:00,200 --> 00:38:02,400
Speaker 3: just needed to pay for that. Put aside my thoughts,

735
00:38:02,440 --> 00:38:05,480
Speaker 3: just like you need that. This is not a hyperbole.

736
00:38:05,560 --> 00:38:08,160
Speaker 3: This is like, you need that money there the demand

737
00:38:08,160 --> 00:38:11,440
Speaker 3: doesn't exist. But on top of that, they are just saying, yeah,

738
00:38:11,719 --> 00:38:14,560
Speaker 3: the AI bubble is going. The boom even in their mind,

739
00:38:14,840 --> 00:38:16,400
Speaker 3: is going to just keep going. We're just going to

740
00:38:16,480 --> 00:38:19,880
Speaker 3: spend three trillion dollars on this every year, like just

741
00:38:20,200 --> 00:38:22,640
Speaker 3: and when you ask them how that works, they're just like,

742
00:38:22,719 --> 00:38:25,160
Speaker 3: the money'll be there, the money. How are we going

743
00:38:25,239 --> 00:38:27,279
Speaker 3: to substantiate the money. You'll be there, the money, you'll

744
00:38:27,320 --> 00:38:30,040
Speaker 3: be there. It will happen, the demand's there. And you're like, well,

745
00:38:30,040 --> 00:38:32,439
Speaker 3: there's compelling proof it isn't there, and they're like, well

746
00:38:32,480 --> 00:38:32,880
Speaker 3: it will.

747
00:38:33,480 --> 00:38:35,480
Speaker 2: It's a great way of it's a great way of

748
00:38:35,520 --> 00:38:39,319
Speaker 2: magicing away these long latency problems you bring up nova

749
00:38:39,400 --> 00:38:40,359
Speaker 2: like climate change.

750
00:38:40,360 --> 00:38:41,920
Speaker 3: For example, we were talking earlier.

751
00:38:41,960 --> 00:38:45,120
Speaker 2: It was like, well, the warming that's happening now was

752
00:38:45,160 --> 00:38:47,440
Speaker 2: from emissions from I don't know, forty years ago whatever, right,

753
00:38:47,480 --> 00:38:48,399
Speaker 2: Like this is all big day.

754
00:38:48,960 --> 00:38:52,480
Speaker 4: If you stopped like any CO two emissions like today,

755
00:38:52,600 --> 00:38:54,640
Speaker 4: we would still be logged in on like decades of warming,

756
00:38:54,640 --> 00:38:56,680
Speaker 4: which is really going to fuck up my life plan.

757
00:38:56,760 --> 00:38:59,640
Speaker 3: I think, yeah, that's good climate wars in the sixties.

758
00:38:59,640 --> 00:39:02,640
Speaker 6: Come on, yeah, you're gonna have to add another decade.

759
00:39:02,920 --> 00:39:05,520
Speaker 3: So but that their answer to this.

760
00:39:05,640 --> 00:39:09,280
Speaker 2: The way that the AI comes in forestalls like actual

761
00:39:09,320 --> 00:39:11,400
Speaker 2: good long term latency planning is it's like, well, the

762
00:39:11,400 --> 00:39:12,960
Speaker 2: AI is going to be smarter than us because it's

763
00:39:13,000 --> 00:39:15,360
Speaker 2: going to be super intelligent, so we won't have to

764
00:39:15,440 --> 00:39:17,080
Speaker 2: solve long latency problems.

765
00:39:17,320 --> 00:39:19,719
Speaker 3: We don't have to worry about the fact I love that.

766
00:39:20,120 --> 00:39:21,960
Speaker 4: Well that's a relief, yeah, to be honest, because I

767
00:39:22,560 --> 00:39:25,360
Speaker 4: hate solving problems, and to be honest, in my sixties,

768
00:39:25,400 --> 00:39:27,080
Speaker 4: I'm hoping to get into like alchemy.

769
00:39:27,360 --> 00:39:30,279
Speaker 2: So so here's another stat I picked up right, which

770
00:39:30,320 --> 00:39:33,200
Speaker 2: is it's no longer it's not just gas turbines anymore.

771
00:39:33,280 --> 00:39:36,440
Speaker 2: High voltage transformer lead times have gone from twelve months

772
00:39:36,480 --> 00:39:40,160
Speaker 2: to forty eight in some cases, So good luck build. So,

773
00:39:40,200 --> 00:39:41,640
Speaker 2: for example, at a time where we need to do

774
00:39:41,719 --> 00:39:45,759
Speaker 2: let's say an energy transition or time when say even

775
00:39:45,800 --> 00:39:49,960
Speaker 2: just in the UK, right national level grid upgrades are

776
00:39:50,800 --> 00:39:53,759
Speaker 2: more or less needing to happen in the next ten years,

777
00:39:53,880 --> 00:39:57,000
Speaker 2: or they're going to be like rolling blackouts. All the

778
00:39:57,040 --> 00:39:59,840
Speaker 2: high voltage transformers you can order are going to the

779
00:40:00,000 --> 00:40:02,600
Speaker 2: odd machine, which will then solve the grid problem some

780
00:40:02,640 --> 00:40:03,120
Speaker 2: other way.

781
00:40:03,280 --> 00:40:06,000
Speaker 3: I just like it. This is why will work it out?

782
00:40:06,120 --> 00:40:12,040
Speaker 3: When we work it out using the work and out machine, stay,

783
00:40:12,320 --> 00:40:16,000
Speaker 3: keep giving it money and then a fucking duh at

784
00:40:16,000 --> 00:40:18,719
Speaker 3: some point you know you work it out. Why are

785
00:40:18,760 --> 00:40:21,560
Speaker 3: you being a quap by wait, come on, man, just

786
00:40:21,560 --> 00:40:25,400
Speaker 3: give me ten billion. You're you're being laying. You're being laying, man,

787
00:40:25,560 --> 00:40:26,040
Speaker 3: come on.

788
00:40:27,040 --> 00:40:29,839
Speaker 2: So and also it's like another all thing is really

789
00:40:29,840 --> 00:40:32,239
Speaker 2: funny that this sphere is always AI is going to

790
00:40:32,280 --> 00:40:35,000
Speaker 2: be a paper clip maximizer, right, the entire be it,

791
00:40:35,040 --> 00:40:37,080
Speaker 2: the whole world in universe and all matter we made

792
00:40:37,080 --> 00:40:39,480
Speaker 2: into paper clips by an AI. But if you look

793
00:40:39,480 --> 00:40:41,680
Speaker 2: at what we're doing with data centers, and we're going

794
00:40:41,760 --> 00:40:43,360
Speaker 2: to go on again to the profitability of them in

795
00:40:43,400 --> 00:40:47,440
Speaker 2: a second, because some stuff has happened there is you

796
00:40:47,480 --> 00:40:49,719
Speaker 2: don't need the AI to be a paper clip maximizer

797
00:40:49,920 --> 00:40:53,480
Speaker 2: because capitalism as a system is already maximizing the paper

798
00:40:53,480 --> 00:40:56,520
Speaker 2: clips in the form of the data centers. We're cannibalizing

799
00:40:56,719 --> 00:41:00,279
Speaker 2: useful things to build this that you can't read the

800
00:41:00,280 --> 00:41:03,359
Speaker 2: grid anymore because all of the transformers are being turned

801
00:41:03,360 --> 00:41:05,200
Speaker 2: into effectively paper clips.

802
00:41:05,640 --> 00:41:06,520
Speaker 3: Yeah, and.

803
00:41:08,000 --> 00:41:10,640
Speaker 2: I know that's not even touching data bricks, which is

804
00:41:10,640 --> 00:41:12,959
Speaker 2: another n scale type snaff food that got uncovered by.

805
00:41:12,840 --> 00:41:17,000
Speaker 3: A similar So you can be saying that, Riley, Sorry, sorry,

806
00:41:17,440 --> 00:41:18,720
Speaker 3: check out no gods, no Mayers.

807
00:41:19,600 --> 00:41:35,239
Speaker 2: But we'll go into that on Thursday. Heyway, I wanted

808
00:41:35,239 --> 00:41:37,920
Speaker 2: to talk about some profitability stuff right as we mentioned

809
00:41:37,920 --> 00:41:40,880
Speaker 2: that open AI's going public is now an if in

810
00:41:40,960 --> 00:41:43,280
Speaker 2: that earlier episode of Is That Good that we played,

811
00:41:44,160 --> 00:41:46,360
Speaker 2: so I actually want you a quote from friend of

812
00:41:46,360 --> 00:41:48,560
Speaker 2: the show, Mike Isaac. The Wall Street Journal reported that

813
00:41:48,600 --> 00:41:50,120
Speaker 2: the company planned to go public by the end of

814
00:41:50,120 --> 00:41:52,960
Speaker 2: twenty twenty six. Open Ai said this month, a month

815
00:41:53,000 --> 00:41:56,040
Speaker 2: it had filed confidential paperwork with securities regulars to kick

816
00:41:56,040 --> 00:41:59,160
Speaker 2: off the process. A trillion dollar valuation of the public market,

817
00:41:59,200 --> 00:42:01,560
Speaker 2: which would exceed the more capitalization of Walmart, would be

818
00:42:01,600 --> 00:42:05,000
Speaker 2: staggering for open Ai, a startup that is not believed

819
00:42:05,000 --> 00:42:06,840
Speaker 2: to have turned a profit and is aggressively spending on

820
00:42:06,920 --> 00:42:10,279
Speaker 2: new data centers, open AIS advisors presenting company executives with

821
00:42:10,320 --> 00:42:12,880
Speaker 2: the option of waiting till twenty twenty seven or lower

822
00:42:12,880 --> 00:42:17,640
Speaker 2: the target valuation for a quicker IPO. Mister Altman responded

823
00:42:17,640 --> 00:42:20,440
Speaker 2: that any change to a trillion dollar valuation was a

824
00:42:20,480 --> 00:42:23,359
Speaker 2: non starter. I assume this is me editorializing because he's

825
00:42:23,360 --> 00:42:25,000
Speaker 2: in a pissing contest with Elon Musk.

826
00:42:25,640 --> 00:42:28,920
Speaker 3: I mean, I think it's also the so their last

827
00:42:29,160 --> 00:42:32,320
Speaker 3: pre money, so before the cash they actually raised, valuation

828
00:42:32,440 --> 00:42:35,360
Speaker 3: was LO two sorry, seven hundred and thirty something, So

829
00:42:36,120 --> 00:42:39,560
Speaker 3: a trillion dollars would be a thirty percent premium. Ish,

830
00:42:39,920 --> 00:42:42,920
Speaker 3: that's not a lot. And the fact that the bankers

831
00:42:42,920 --> 00:42:46,000
Speaker 3: are saying that they couldn't get that, because that's I'm

832
00:42:46,040 --> 00:42:48,240
Speaker 3: reading between the lines, but I mean, that's what's happening.

833
00:42:48,239 --> 00:42:51,600
Speaker 3: They clearly talked to some advisors who are like, you know, no,

834
00:42:52,000 --> 00:42:55,840
Speaker 3: that's a negative. That's worse than people are giving this

835
00:42:55,920 --> 00:42:58,680
Speaker 3: credit for. If you can't get a thirty percent premium,

836
00:42:58,719 --> 00:43:01,160
Speaker 3: it basically means all of your private investors at the

837
00:43:01,200 --> 00:43:05,360
Speaker 3: last round fucked up. Because you're not even get like

838
00:43:05,400 --> 00:43:08,279
Speaker 3: a good venture capital return would be like three x.

839
00:43:09,120 --> 00:43:12,319
Speaker 3: You're not even getting just to it, like it's you're

840
00:43:12,400 --> 00:43:15,920
Speaker 3: genuinely making nothing here. And also they're saying they couldn't

841
00:43:16,000 --> 00:43:19,399
Speaker 3: list it one trillion, so they probably wouldn't be able

842
00:43:19,400 --> 00:43:23,160
Speaker 3: to list it much above eight hundred, which is fatal.

843
00:43:23,400 --> 00:43:25,759
Speaker 3: I mean just and this is fatal for soft Bank

844
00:43:25,800 --> 00:43:28,440
Speaker 3: as well, because bank needs open a high to go public.

845
00:43:28,800 --> 00:43:33,000
Speaker 3: But it's just like these things. The reason we keep

846
00:43:33,040 --> 00:43:37,080
Speaker 3: having bubbles is because when stuff like this happens, the

847
00:43:37,200 --> 00:43:42,400
Speaker 3: media and a great many different people immediately move not

848
00:43:42,520 --> 00:43:46,000
Speaker 3: to go, hey, that's a problem, we should fix that,

849
00:43:46,160 --> 00:43:48,480
Speaker 3: or like, hey, we should be worried about the company

850
00:43:48,480 --> 00:43:51,560
Speaker 3: that's become the single focus of everyone isn't going to

851
00:43:51,640 --> 00:43:54,040
Speaker 3: make it. Instead it's like no, no, no, let's rationalize

852
00:43:54,040 --> 00:43:58,040
Speaker 3: this bad boy real quick. Let's enable the enabler, like

853
00:43:58,280 --> 00:44:00,399
Speaker 3: we need to make sure we keep this and it's

854
00:44:00,440 --> 00:44:04,160
Speaker 3: just completely nonsensical. And to be clear, when this explodes,

855
00:44:04,200 --> 00:44:07,040
Speaker 3: I'm going to be ripping holes in anyone who tries

856
00:44:07,080 --> 00:44:08,960
Speaker 3: to be like, how did we not see this coming?

857
00:44:09,840 --> 00:44:12,000
Speaker 3: You didn't look? Is the big thing?

858
00:44:12,080 --> 00:44:16,080
Speaker 2: Well, because the main the thing that as at the

859
00:44:16,080 --> 00:44:18,680
Speaker 2: bottom of this is always the unit economics. And what

860
00:44:18,760 --> 00:44:21,920
Speaker 2: I think is very telling is that open air executives

861
00:44:21,920 --> 00:44:24,080
Speaker 2: and talking about the IPO, said well, the company is

862
00:44:24,120 --> 00:44:26,080
Speaker 2: moving in the right direction because more than five million

863
00:44:26,120 --> 00:44:28,600
Speaker 2: people use codex in a monthly but on a weekly basis,

864
00:44:28,640 --> 00:44:31,640
Speaker 2: the company said, now more than five million people using

865
00:44:31,640 --> 00:44:34,320
Speaker 2: Codex on a weekly basis pretty good, which means I

866
00:44:34,320 --> 00:44:36,600
Speaker 2: assume they've solved their unit economics problem and that's not

867
00:44:36,680 --> 00:44:38,280
Speaker 2: costing them a huge amount of money.

868
00:44:38,600 --> 00:44:42,200
Speaker 1: Yeah, they've definitely avoided They've gotten out of the sort

869
00:44:42,239 --> 00:44:44,960
Speaker 1: of thing that they were doing of just going hey,

870
00:44:45,000 --> 00:44:47,440
Speaker 1: AI is free until everyone uses it and then they

871
00:44:47,440 --> 00:44:50,040
Speaker 1: can start charging what it actually costs, right right.

872
00:44:50,880 --> 00:44:54,120
Speaker 3: Yeah. And what's great about that is they did that

873
00:44:54,200 --> 00:44:55,839
Speaker 3: and they were like okay, and now the jack up

874
00:44:55,840 --> 00:44:59,960
Speaker 3: the price, and within one month they're like, ah, everyone's like,

875
00:45:00,160 --> 00:45:03,120
Speaker 3: well we've got to limit the cost of this just immediately.

876
00:45:03,440 --> 00:45:05,200
Speaker 3: And by the way, on a two hundred buck a

877
00:45:05,280 --> 00:45:09,000
Speaker 3: month subscription to check GPT, you can burn fourteen thousand

878
00:45:09,040 --> 00:45:13,279
Speaker 3: dollars worth of credits of tokens. Geez, it's so good,

879
00:45:13,440 --> 00:45:18,160
Speaker 3: it's I mean, so this is the thing we've had

880
00:45:18,200 --> 00:45:22,399
Speaker 3: everybody panic, right and go, oh god, it's expensive. Now

881
00:45:22,480 --> 00:45:24,799
Speaker 3: we gotta like maybe think why it's about using it.

882
00:45:25,239 --> 00:45:29,239
Speaker 3: They're still charging a fraction of what it cost, just

883
00:45:29,280 --> 00:45:33,520
Speaker 3: a slightly smaller fraction, a slightly larger fraction exactly. And

884
00:45:33,840 --> 00:45:37,839
Speaker 3: amazing also instead of instead of it costs like I

885
00:45:37,880 --> 00:45:41,399
Speaker 3: have fourteen thousand dollars for a dollar, you can set

886
00:45:41,400 --> 00:45:43,879
Speaker 3: that on fire in front of me. What they've gone

887
00:45:44,000 --> 00:45:46,239
Speaker 3: is it now costs two dollars to do that, and

888
00:45:46,280 --> 00:45:49,279
Speaker 3: everyone has part what's happened. What's happening is it's a

889
00:45:49,320 --> 00:45:52,560
Speaker 3: little different from that where it's the enterprises are having

890
00:45:52,600 --> 00:45:55,399
Speaker 3: to pay the actual per million token rates, so they

891
00:45:55,600 --> 00:45:57,600
Speaker 3: and they this is it's really it was actually a

892
00:45:57,680 --> 00:46:01,000
Speaker 3: very funny punchline setup because they bait all of the

893
00:46:01,120 --> 00:46:03,520
Speaker 3: bus the city it's been using AI who have got

894
00:46:03,520 --> 00:46:06,040
Speaker 3: a isochosis, told all their people because they were all

895
00:46:06,080 --> 00:46:07,920
Speaker 3: able to burn as many token as they like, use

896
00:46:07,960 --> 00:46:10,799
Speaker 3: this constantly, use it for everything. If you don't use this,

897
00:46:10,880 --> 00:46:13,759
Speaker 3: I'll kill you. I'll shoot you with a gun. And

898
00:46:13,800 --> 00:46:16,879
Speaker 3: then the moment that they because in I think it's

899
00:46:16,920 --> 00:46:19,479
Speaker 3: March or April the anthropic and open aie. We're like, okay,

900
00:46:19,480 --> 00:46:21,040
Speaker 3: you're gonna have to pay on a per million token

901
00:46:21,080 --> 00:46:25,640
Speaker 3: basis within one month. We're just like like John Major Stalakar,

902
00:46:25,640 --> 00:46:28,520
Speaker 3: I've got a austerity measures. We've got to be very

903
00:46:28,520 --> 00:46:31,040
Speaker 3: careful with the cost of hay out. We couldn't couldn't possibly.

904
00:46:31,200 --> 00:46:33,840
Speaker 3: And it's just so funny because it's like, even if

905
00:46:34,040 --> 00:46:37,480
Speaker 3: they cut the price in half, it's not clear if

906
00:46:37,520 --> 00:46:40,040
Speaker 3: that would actually fix the problem because you can't measure

907
00:46:40,040 --> 00:46:42,200
Speaker 3: the ROI of any of this. So with just a

908
00:46:42,200 --> 00:46:46,560
Speaker 3: certain degree of like great, now it's half of half

909
00:46:46,560 --> 00:46:48,279
Speaker 3: of a thing that we still can't measure, so we

910
00:46:48,320 --> 00:46:51,839
Speaker 3: probably have to cut that too. It's just it's truly ludicrous.

911
00:46:52,040 --> 00:46:55,759
Speaker 3: It's genuinely I mean, it's genuinely hilarious as well. I

912
00:46:55,800 --> 00:46:58,000
Speaker 3: mean the I have you have you heard of the

913
00:46:58,000 --> 00:47:02,120
Speaker 3: new plugin for Claude called k man Oh yeah, where

914
00:47:02,160 --> 00:47:07,279
Speaker 3: it's just like it just gives you very simple single sentences. Yeah,

915
00:47:07,280 --> 00:47:08,799
Speaker 3: this is that a plug in? That was you?

916
00:47:09,000 --> 00:47:12,800
Speaker 2: That is that is useful to let's say be austere

917
00:47:12,920 --> 00:47:15,359
Speaker 2: with tokens by saying, Okay, well maybe we can save

918
00:47:15,400 --> 00:47:17,160
Speaker 2: a little bit of money on our token budget if

919
00:47:17,160 --> 00:47:20,640
Speaker 2: we make Claude be kind of rude and abrupt. It's like,

920
00:47:20,680 --> 00:47:23,080
Speaker 2: I don't I don't think that says anything good. If

921
00:47:23,080 --> 00:47:24,120
Speaker 2: that's if that's so.

922
00:47:24,840 --> 00:47:27,759
Speaker 4: That's it's kind of funny how much of the cost

923
00:47:27,840 --> 00:47:30,759
Speaker 4: of this was making it glaze of the user at least.

924
00:47:32,000 --> 00:47:36,160
Speaker 2: And like, so in late June there has been this

925
00:47:36,280 --> 00:47:39,240
Speaker 2: huge it's not because this is not just price is rising.

926
00:47:39,520 --> 00:47:41,880
Speaker 2: There's been a huge sell off in names across the

927
00:47:41,920 --> 00:47:45,640
Speaker 2: stock market related to AI and Vidia. SpaceX by SpaceX

928
00:47:45,680 --> 00:47:49,120
Speaker 2: already is down like hundreds of billions of dollars from

929
00:47:49,120 --> 00:47:51,279
Speaker 2: its post IPO pop. So if you thought you were

930
00:47:51,280 --> 00:47:54,799
Speaker 2: gonna get out on the Elon scam, you got hosed this.

931
00:47:55,000 --> 00:47:57,800
Speaker 2: But this is also related to Microsoft, Alphabet, Amazon, and

932
00:47:57,840 --> 00:48:01,520
Speaker 2: Meta all suddenly becoming like high happex heavy industry companies

933
00:48:01,520 --> 00:48:04,640
Speaker 2: more or less overnight. So the customers of these companies, right,

934
00:48:04,719 --> 00:48:06,600
Speaker 2: they're the ones who are supposed to provide the money

935
00:48:06,600 --> 00:48:08,759
Speaker 2: to help them lose money more efficiently, still aren't able

936
00:48:08,800 --> 00:48:12,120
Speaker 2: to capitalize on them. Like like consulting firms aren't using

937
00:48:12,160 --> 00:48:14,440
Speaker 2: it to get better, Banking companies aren't using it to

938
00:48:14,440 --> 00:48:14,879
Speaker 2: get better.

939
00:48:14,920 --> 00:48:15,320
Speaker 3: You can't.

940
00:48:15,400 --> 00:48:17,360
Speaker 2: You're using it to really generate a lot of return

941
00:48:17,400 --> 00:48:20,280
Speaker 2: on investment. And so more and more people are reasing

942
00:48:20,640 --> 00:48:23,959
Speaker 2: realizing this subsidized pricing is coming up against reality and

943
00:48:24,160 --> 00:48:28,520
Speaker 2: like that exuberant that exuberant investment pop is that that's

944
00:48:28,560 --> 00:48:30,680
Speaker 2: been happening for the lest little while. Those names are

945
00:48:30,719 --> 00:48:32,560
Speaker 2: beginning to go down. In fact, this is from Katie

946
00:48:32,600 --> 00:48:35,680
Speaker 2: Martin and the ft. The once vaunted magnificent seven stocks

947
00:48:35,719 --> 00:48:38,480
Speaker 2: and imperfect but nonetheless go to gage of Hyperscaler performance

948
00:48:38,719 --> 00:48:42,320
Speaker 2: performs slightly worse than the UK government debt.

949
00:48:42,640 --> 00:48:48,279
Speaker 3: M Oh, how are you a worse investment than Kistoma. Yeah,

950
00:48:48,520 --> 00:48:50,640
Speaker 3: that's like that's like at the World Up.

951
00:48:53,920 --> 00:48:56,680
Speaker 2: It's like getting rolled by katar at the World Cup, Like,

952
00:48:56,840 --> 00:49:06,000
Speaker 2: come on, you shouldn't be beating us. Yes, and I

953
00:49:06,000 --> 00:49:08,919
Speaker 2: mean this is this is a this is The Bank

954
00:49:08,960 --> 00:49:11,919
Speaker 2: of International Settlements is also getting another as well, which

955
00:49:11,920 --> 00:49:15,480
Speaker 2: is yeah now suggesting that with the five largest hyperscalers

956
00:49:15,719 --> 00:49:18,560
Speaker 2: setting to spend over a trillion dollars on AI related

957
00:49:18,560 --> 00:49:20,960
Speaker 2: capex from twenty twenty five through twenty six, that the

958
00:49:21,000 --> 00:49:24,480
Speaker 2: campaign commit commitments are outpacing earnings and free cash flow,

959
00:49:24,880 --> 00:49:27,799
Speaker 2: leading some to issue debt to raise additional financing, and

960
00:49:27,840 --> 00:49:30,879
Speaker 2: that again the Bank of International Settlements is now saying

961
00:49:31,000 --> 00:49:33,759
Speaker 2: this is a this is now let's say, a significant

962
00:49:34,360 --> 00:49:35,080
Speaker 2: global risk.

963
00:49:35,480 --> 00:49:38,440
Speaker 3: Yeah, one of those guys woudy, someone had fucking said something.

964
00:49:38,800 --> 00:49:43,000
Speaker 3: It's so funny as one would like. The BIS put

965
00:49:43,000 --> 00:49:46,240
Speaker 3: that out so like the Servile Bank and central banks,

966
00:49:46,680 --> 00:49:49,560
Speaker 3: and immediately I saw an analyst, this guy called Daniel

967
00:49:49,560 --> 00:49:53,359
Speaker 3: Newman on Twitter. Is a massive word, I won't say.

968
00:49:54,440 --> 00:49:56,360
Speaker 3: It was just immediate, like, oh oh, what was this

969
00:49:56,440 --> 00:49:58,320
Speaker 3: a press release? A press release from the hate is

970
00:49:58,320 --> 00:50:01,040
Speaker 3: It's like, no, it's a statement from the Central Bank

971
00:50:01,080 --> 00:50:04,480
Speaker 3: of Central Banks. You're a financial analyst, but this is

972
00:50:04,840 --> 00:50:07,759
Speaker 3: the media behind this. The media is just like immediately

973
00:50:07,800 --> 00:50:11,719
Speaker 3: ready to just attack any bad sign, and it's very strange.

974
00:50:11,880 --> 00:50:16,200
Speaker 3: It's I know it's always been like this, but to

975
00:50:16,280 --> 00:50:19,879
Speaker 3: see it reach its kind of pornographic heights. I think

976
00:50:19,920 --> 00:50:22,520
Speaker 3: it's just the the data centers are too easy to

977
00:50:22,560 --> 00:50:24,960
Speaker 3: invest in. The AI companies are too easy to invest in.

978
00:50:25,000 --> 00:50:27,200
Speaker 3: There's so many places to put your money, and they're

979
00:50:27,280 --> 00:50:30,600
Speaker 3: so brain damaged from years of ignoring the consequences of

980
00:50:30,600 --> 00:50:33,880
Speaker 3: their actions that they don't think anything can go wrong. Massio.

981
00:50:33,960 --> 00:50:35,640
Speaker 3: She's on all of them, I mean all of the

982
00:50:35,680 --> 00:50:38,399
Speaker 3: data center operators. Same deal, Hyperscale as the same deal.

983
00:50:38,520 --> 00:50:41,320
Speaker 3: They're not. They all think that they they have found

984
00:50:41,360 --> 00:50:42,360
Speaker 3: the mandate.

985
00:50:42,000 --> 00:50:46,799
Speaker 2: Of Heaven printer, Yeah, and like the thing that was

986
00:50:46,840 --> 00:50:49,040
Speaker 2: that the test is it was this the mandate of Heaven?

987
00:50:49,239 --> 00:50:53,200
Speaker 2: Is is this going to Is this going to do

988
00:50:53,320 --> 00:50:57,080
Speaker 2: to like knowledge work, for example, what containerization did to

989
00:50:57,120 --> 00:51:01,520
Speaker 2: Steve Adores? Is this going to do? Is this going

990
00:51:01,560 --> 00:51:05,000
Speaker 2: to be like the great enclosure of the digital commons

991
00:51:05,000 --> 00:51:06,719
Speaker 2: once and for all? Is this going to be the

992
00:51:06,760 --> 00:51:09,800
Speaker 2: thing that creates the new I don't know, six person

993
00:51:09,880 --> 00:51:13,960
Speaker 2: ruling class of the entire world by fundamentally transforming the

994
00:51:14,000 --> 00:51:17,600
Speaker 2: economy with this like huge technological displacement of labor? Like

995
00:51:17,640 --> 00:51:20,239
Speaker 2: that was the actual question, are you going to do that?

996
00:51:20,800 --> 00:51:22,960
Speaker 2: And on day of recording, to.

997
00:51:22,960 --> 00:51:25,720
Speaker 3: Which the answer is yeah, I reckon, Yeah, sure probably

998
00:51:25,960 --> 00:51:26,440
Speaker 3: sounds good.

999
00:51:26,640 --> 00:51:30,440
Speaker 2: Well here here's the great thing. And look, this is inferential,

1000
00:51:30,480 --> 00:51:33,560
Speaker 2: This is not deductive, This is not provable. But the

1001
00:51:33,800 --> 00:51:37,280
Speaker 2: Wall Street Journal has posted that Big Tech has suddenly

1002
00:51:37,320 --> 00:51:41,239
Speaker 2: flipped on the AI gibe jobs wipeout scenario, where they

1003
00:51:41,280 --> 00:51:45,839
Speaker 2: they've they've now they've collected some let's say, uh, barometers

1004
00:51:45,880 --> 00:51:47,839
Speaker 2: of opinion from the from the big guys, the sam

1005
00:51:47,920 --> 00:51:52,520
Speaker 2: Altmans and and Daryamadis and stuff surveys, and they've said, hey,

1006
00:51:52,520 --> 00:51:55,319
Speaker 2: wait a minute, looks like all that all those jobs

1007
00:51:55,360 --> 00:51:57,320
Speaker 2: aren't going away. A lot of people are still fired

1008
00:51:57,360 --> 00:51:59,520
Speaker 2: with AI as an excuse. A lot of them got

1009
00:51:59,560 --> 00:52:03,560
Speaker 2: rehighed in some cases. But this is excerpt one that

1010
00:52:03,640 --> 00:52:06,280
Speaker 2: the Wall Street Journal quoted a year ago. The message

1011
00:52:06,280 --> 00:52:08,400
Speaker 2: of many business leaders was that AI was going to

1012
00:52:08,400 --> 00:52:10,839
Speaker 2: wipe out jobs. The past month or so, tech CEO

1013
00:52:10,880 --> 00:52:13,640
Speaker 2: has been striking more optimistic tone. In late May, Sam

1014
00:52:13,680 --> 00:52:17,600
Speaker 2: Altman said, we've been roughly right in the technological predictions

1015
00:52:17,600 --> 00:52:20,359
Speaker 2: and pretty wrong in the social and economic implication, saying

1016
00:52:20,400 --> 00:52:23,520
Speaker 2: to see NBC, our industry underestimated how much we're going

1017
00:52:23,600 --> 00:52:25,520
Speaker 2: to be able to keep people at the center of everything.

1018
00:52:25,880 --> 00:52:32,000
Speaker 2: But what your thing was the replace all human labor machine. Yes,

1019
00:52:32,280 --> 00:52:35,000
Speaker 2: and your replace all human labor machine. What you're saying

1020
00:52:35,080 --> 00:52:37,319
Speaker 2: is it's failed to replace all human labor at least

1021
00:52:37,360 --> 00:52:39,520
Speaker 2: in the timescale that you need it to in order

1022
00:52:39,560 --> 00:52:41,440
Speaker 2: to go public at write down a value and you

1023
00:52:41,480 --> 00:52:42,560
Speaker 2: can decide how rich you are.

1024
00:52:43,360 --> 00:52:43,760
Speaker 3: Yeah.

1025
00:52:43,840 --> 00:52:47,399
Speaker 5: I do kind of wonder whether, like the reason why

1026
00:52:47,400 --> 00:52:50,279
Speaker 5: they don't think of the ideal consequences is because the

1027
00:52:50,360 --> 00:52:53,160
Speaker 5: AI is not telling you that this might be the

1028
00:52:53,200 --> 00:52:56,160
Speaker 5: thing that happens, Like I know, there's that sort of

1029
00:52:56,160 --> 00:52:58,719
Speaker 5: thing where like chat O Sam Altman sort of sounds

1030
00:52:58,800 --> 00:53:01,560
Speaker 5: like he is kind of just he sort of his

1031
00:53:01,600 --> 00:53:04,000
Speaker 5: brain is entirely like chat GPT and that sort of

1032
00:53:04,040 --> 00:53:06,200
Speaker 5: you know, the guy who sort of drinks too much

1033
00:53:06,200 --> 00:53:09,520
Speaker 5: of the chol aid and becomes a cool aid guy.

1034
00:53:09,760 --> 00:53:11,480
Speaker 2: How you make new kool aid guys that.

1035
00:53:13,520 --> 00:53:14,240
Speaker 3: Value zero?

1036
00:53:15,160 --> 00:53:19,120
Speaker 5: That's right, presably, presumably that's how it works. But yeah,

1037
00:53:19,160 --> 00:53:20,840
Speaker 5: like even when I sort of think about the boosters

1038
00:53:20,840 --> 00:53:22,560
Speaker 5: of stuff like ed you were just sort of saying

1039
00:53:22,560 --> 00:53:25,799
Speaker 5: now about like sort of boosters and tech types who

1040
00:53:25,840 --> 00:53:28,279
Speaker 5: are like genuinely surprised when people are like, hey, maybe

1041
00:53:28,360 --> 00:53:32,000
Speaker 5: this thing kind of sucks or is overhyped. Like to me,

1042
00:53:32,080 --> 00:53:34,759
Speaker 5: it does sort of strike is like not not just

1043
00:53:34,800 --> 00:53:37,160
Speaker 5: that they believe that this has to happen and this

1044
00:53:37,280 --> 00:53:40,239
Speaker 5: is like the inevitable next frontier, because if not, then

1045
00:53:40,320 --> 00:53:42,400
Speaker 5: like what else You've wasted all this time, You've wasted

1046
00:53:42,400 --> 00:53:45,239
Speaker 5: all this money, You've wasted all this energy basically kind

1047
00:53:45,239 --> 00:53:47,920
Speaker 5: of doing nothing except creating a vanity project. But like,

1048
00:53:48,160 --> 00:53:50,440
Speaker 5: one of the things that feels so evident about this

1049
00:53:50,680 --> 00:53:54,200
Speaker 5: entire cohort is that like they just don't think about

1050
00:53:54,239 --> 00:53:57,520
Speaker 5: consequences because I guess they don't believe it exists. Because

1051
00:53:57,560 --> 00:54:00,319
Speaker 5: to believe that consequence exists, you have to be that

1052
00:54:00,600 --> 00:54:03,399
Speaker 5: other people live among you and that their lives are

1053
00:54:03,520 --> 00:54:06,440
Speaker 5: important and worthy of some kind of dignity.

1054
00:54:06,480 --> 00:54:12,560
Speaker 3: And once you do that, wallet, when do you think

1055
00:54:12,920 --> 00:54:15,360
Speaker 3: do you think he carries money? Do you think he

1056
00:54:15,880 --> 00:54:18,200
Speaker 3: do you think any of these people do? Because this

1057
00:54:18,360 --> 00:54:22,240
Speaker 3: is are they just so separated that the only people

1058
00:54:22,280 --> 00:54:24,920
Speaker 3: they talk to are just worm tongue like figures and

1059
00:54:25,040 --> 00:54:27,280
Speaker 3: chat GPT and one another.

1060
00:54:27,440 --> 00:54:29,359
Speaker 5: Well, I mean yeah, I mean it's sort of it's

1061
00:54:29,360 --> 00:54:31,640
Speaker 5: sort of just strike me as like the guy who

1062
00:54:31,680 --> 00:54:33,839
Speaker 5: sort of has never really had to experience any type

1063
00:54:33,880 --> 00:54:36,799
Speaker 5: of friction in his life and so doesn't have to

1064
00:54:36,920 --> 00:54:39,759
Speaker 5: like understand that. No, there are like parts of the

1065
00:54:39,760 --> 00:54:41,720
Speaker 5: world where you just can't do. I mean, it's also

1066
00:54:41,760 --> 00:54:44,080
Speaker 5: like why they always get confused whenever, Like the European

1067
00:54:44,160 --> 00:54:46,520
Speaker 5: Union is like, yeah, we're going to maybe regulate you,

1068
00:54:47,000 --> 00:54:49,239
Speaker 5: and they're not like, oh, the regulation is bad and

1069
00:54:49,280 --> 00:54:51,560
Speaker 5: we can So it's like, but why why would.

1070
00:54:51,320 --> 00:54:52,279
Speaker 6: You want to regulate us?

1071
00:54:52,400 --> 00:54:54,319
Speaker 3: What regulation do? Like?

1072
00:54:54,360 --> 00:54:57,000
Speaker 5: Why would you why? Yeah, exactly why would you want

1073
00:54:57,000 --> 00:54:59,560
Speaker 5: to restrain us? Like the idea of sort of being

1074
00:54:59,600 --> 00:55:03,080
Speaker 5: held back is like completely foreign to them, and so

1075
00:55:03,200 --> 00:55:05,040
Speaker 5: imagine like sort of events sort of trying to explain

1076
00:55:05,080 --> 00:55:06,880
Speaker 5: to him. But hey, look like there are a lot

1077
00:55:06,920 --> 00:55:10,720
Speaker 5: of societies in the world that like, you know, don't

1078
00:55:10,800 --> 00:55:13,920
Speaker 5: operate using kind of you know, the computer is not

1079
00:55:14,000 --> 00:55:16,719
Speaker 5: the be all and end all of like communication. You know,

1080
00:55:18,080 --> 00:55:20,680
Speaker 5: people actually like talk to each other. There exist like

1081
00:55:21,080 --> 00:55:23,759
Speaker 5: communities and bar systems and all those types of things.

1082
00:55:23,760 --> 00:55:26,759
Speaker 5: Like imagine just trying to explain to them in general, like, hey,

1083
00:55:26,760 --> 00:55:28,160
Speaker 5: like people just don't live like.

1084
00:55:28,160 --> 00:55:32,640
Speaker 3: You they do. What what do you mean they run

1085
00:55:32,680 --> 00:55:36,000
Speaker 3: out of runy? What does that mean? You know?

1086
00:55:36,400 --> 00:55:37,560
Speaker 5: You know, it reminds me of like there was a

1087
00:55:37,600 --> 00:55:40,359
Speaker 5: clip but just circulating today. It's a very old clip,

1088
00:55:40,360 --> 00:55:42,160
Speaker 5: but it's like an Anthony Bourdaine clip where like he's

1089
00:55:42,160 --> 00:55:45,319
Speaker 5: explaining to a bunch of like very rich Singaporeans I

1090
00:55:45,320 --> 00:55:47,040
Speaker 5: think that he does his own laundry, and one of

1091
00:55:47,080 --> 00:55:48,799
Speaker 5: them is just like, well, what do you mean you

1092
00:55:48,840 --> 00:55:50,279
Speaker 5: do your own laundry, And he's just like, yeah, I

1093
00:55:50,320 --> 00:55:52,040
Speaker 5: go to a laundromat and I put the coins in

1094
00:55:52,480 --> 00:55:55,120
Speaker 5: and the machine kind of does it, and I fold it,

1095
00:55:55,160 --> 00:55:57,359
Speaker 5: and I feel quite good. About doing it afterwards, and

1096
00:55:57,440 --> 00:56:00,200
Speaker 5: like the reaction of this guy has is like usping

1097
00:56:00,239 --> 00:56:02,160
Speaker 5: to him in a foreign language that he has never

1098
00:56:02,239 --> 00:56:05,440
Speaker 5: understood the concept of, like touching his own clothes before him.

1099
00:56:05,480 --> 00:56:07,799
Speaker 5: This is like, this reminds me so much of just

1100
00:56:07,880 --> 00:56:10,399
Speaker 5: like what how all these guys view the way?

1101
00:56:10,440 --> 00:56:13,000
Speaker 3: It got too rich? So we got time for one

1102
00:56:13,000 --> 00:56:14,280
Speaker 3: more bit before we have the close.

1103
00:56:14,440 --> 00:56:17,120
Speaker 2: And this one is really interesting, right because this is

1104
00:56:17,120 --> 00:56:19,919
Speaker 2: one of my favorite kinds of statistics, which is how

1105
00:56:20,000 --> 00:56:23,040
Speaker 2: is AI actually being used in companies? What are they

1106
00:56:23,120 --> 00:56:26,280
Speaker 2: using it to do? Is it profitable? Are the pilot successful?

1107
00:56:26,280 --> 00:56:26,640
Speaker 3: And so on?

1108
00:56:27,000 --> 00:56:29,080
Speaker 2: The sentiment change isn't limited to tech leaders. This is

1109
00:56:29,080 --> 00:56:32,439
Speaker 2: from the excerpt again. A survey by ey Parthenon found

1110
00:56:32,440 --> 00:56:34,879
Speaker 2: that the percentage of CEOs who believe AI investments will

1111
00:56:34,880 --> 00:56:38,279
Speaker 2: result in significant reductions at headcount fell from forty six

1112
00:56:38,320 --> 00:56:41,320
Speaker 2: percent in January twenty twenty five to just twenty percent.

1113
00:56:41,400 --> 00:56:47,760
Speaker 3: This may and even the most credulous worm eventually turns yeah,

1114
00:56:47,920 --> 00:56:51,799
Speaker 3: and like so it just goes back to, well, if

1115
00:56:51,800 --> 00:56:55,279
Speaker 3: the firms aren't more productive and they're not able to

1116
00:56:55,280 --> 00:56:58,960
Speaker 3: be the same level of product productive with the with

1117
00:56:58,960 --> 00:57:01,640
Speaker 3: with with fewer people, like if these things aren't happening,

1118
00:57:02,120 --> 00:57:04,280
Speaker 3: and the thing is starting to cost what it costs,

1119
00:57:04,280 --> 00:57:05,319
Speaker 3: and what it costs.

1120
00:57:05,040 --> 00:57:09,839
Speaker 2: Is enormous, and it's still being subsidized and in order

1121
00:57:10,000 --> 00:57:12,759
Speaker 2: to continue building up the demand that they think that

1122
00:57:12,800 --> 00:57:15,520
Speaker 2: they'll need even if the thing suddenly goes to one

1123
00:57:15,600 --> 00:57:18,280
Speaker 2: hundred as everyone needs it for everything, even if all

1124
00:57:18,280 --> 00:57:21,000
Speaker 2: that happens, they still can't build the data centers. Then

1125
00:57:21,120 --> 00:57:24,960
Speaker 2: it's just like in the grand story that you know, you,

1126
00:57:25,200 --> 00:57:27,120
Speaker 2: that you've been telling ed and that we've been sort

1127
00:57:27,120 --> 00:57:29,400
Speaker 2: of checking in on you with every once and again.

1128
00:57:30,160 --> 00:57:32,880
Speaker 2: Is that like if the coyotes run off the cliff,

1129
00:57:33,280 --> 00:57:36,280
Speaker 2: he's held up the sign and is looked down and

1130
00:57:36,320 --> 00:57:39,920
Speaker 2: has held up the sign that says oh no yeah,

1131
00:57:40,080 --> 00:57:43,520
Speaker 2: or he's opened he's opened up the little parasol and

1132
00:57:43,560 --> 00:57:45,760
Speaker 2: the boulders falling on top of him. This is the

1133
00:57:45,800 --> 00:57:49,120
Speaker 2: moment where he has looked down. Yeah, because that was

1134
00:57:49,160 --> 00:57:51,440
Speaker 2: that like the moment where he looks down. That was

1135
00:57:51,480 --> 00:57:53,600
Speaker 2: going to be when the thing has to start costing

1136
00:57:53,640 --> 00:57:56,240
Speaker 2: what it costs, right, not even making a profit, just

1137
00:57:56,240 --> 00:57:57,120
Speaker 2: costing what it costs.

1138
00:57:58,040 --> 00:58:00,800
Speaker 3: And that's now happened. Yeah, And now all the companies

1139
00:58:00,840 --> 00:58:02,640
Speaker 3: are freaking out that it costs a lot of money,

1140
00:58:02,960 --> 00:58:05,680
Speaker 3: and I think it's just that. So you'll notice we

1141
00:58:05,720 --> 00:58:08,280
Speaker 3: haven't had a revenue update from in a while, and

1142
00:58:08,320 --> 00:58:10,439
Speaker 3: I have to wonder if that story might change too.

1143
00:58:10,440 --> 00:58:13,080
Speaker 3: But honestly, the biggest warning sign, and the biggest sign

1144
00:58:13,160 --> 00:58:15,680
Speaker 3: the coyote looked down is when Sam, when when asked

1145
00:58:15,680 --> 00:58:18,800
Speaker 3: about these costs set on stage. Yeah, it's become a

1146
00:58:18,880 --> 00:58:21,040
Speaker 3: huge issue.

1147
00:58:21,320 --> 00:58:24,760
Speaker 2: Yes, someone should look into that.

1148
00:58:24,800 --> 00:58:29,440
Speaker 3: It's like a just like, oh, all right, well he

1149
00:58:29,560 --> 00:58:31,800
Speaker 3: basically got the exact quote, but he was like, yes,

1150
00:58:31,840 --> 00:58:34,120
Speaker 3: someone's gonna have industry is gonna have to sort that out.

1151
00:58:34,720 --> 00:58:37,400
Speaker 3: It's just like you are, bully the big problem.

1152
00:58:37,440 --> 00:58:41,120
Speaker 2: So hopefully the big Black Problem solving box will do that.

1153
00:58:41,320 --> 00:58:43,880
Speaker 3: I shouldn't check what's in it, sell the compute to

1154
00:58:44,000 --> 00:58:46,080
Speaker 3: who Sam fucking Aquaman.

1155
00:58:48,640 --> 00:58:50,920
Speaker 2: Look, I know we're we got a bit of a

1156
00:58:50,960 --> 00:58:53,640
Speaker 2: hard stop today, so I'm gonna I'm gonna call it there.

1157
00:58:54,640 --> 00:59:01,200
Speaker 3: ED joint Venture stat seventeen billion dollars raised and eighteen

1158
00:59:02,440 --> 00:59:04,640
Speaker 3: and we have lost the money already, so we're gonna

1159
00:59:04,640 --> 00:59:06,640
Speaker 3: have to keep doing this. Thanks a lot everyone for

1160
00:59:06,720 --> 00:59:07,320
Speaker 3: joining us.

1161
00:59:08,760 --> 00:59:12,960
Speaker 2: We've been TF and Ed's been better offline, and we

1162
00:59:13,040 --> 00:59:15,640
Speaker 2: will see you on our various If you're listening to this,

1163
00:59:15,720 --> 00:59:17,320
Speaker 2: you know the deal. If it's TF, will see you

1164
00:59:17,360 --> 00:59:21,080
Speaker 2: on the bonus episode. If it's Better Offline, you'll see

1165
00:59:21,200 --> 00:59:22,280
Speaker 2: ed on Better Offline.

1166
00:59:22,600 --> 00:59:24,640
Speaker 3: I should so you see you on the bonus episode

1167
00:59:24,760 --> 00:59:28,760
Speaker 3: either way, Yeah, exactly, Thanks everybody, cheers, Bye bye,