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Speaker 1: All Zone Media.

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Speaker 2: Hello and welcome to Better Offline. I'm your host ed

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Speaker 2: ze tron. As I've discussed in the last episode, Sam

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Speaker 2: Mortman has spent more than a decade accumulating power and

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Speaker 2: wealth in Silicon Valley without ever having to actually build anything,

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Speaker 2: using a network of tech industry all stars like LinkedIn

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Speaker 2: co founder and investor Reid Hoffman and Airbnb CEO Brian

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Speaker 2: Chesky to insulate himself from responsibility and accountability. Yet things

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Speaker 2: are beginning to fall apart as years of half baked

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Speaker 2: ideas and terrible, terrible product decisions have kind of made

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Speaker 2: society sour on the tech industry, and the last month

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Speaker 2: has been particularly difficult for Sam, starting with the chaos

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Speaker 2: cause by open ai blatantly mimicking Scarlet Johansson's voice for

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Speaker 2: the new version of chat GPT, followed by the resignation

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Speaker 2: of researchers who claimed the open ai prioritized and I

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Speaker 2: quote shiny products over AI safety. After the dissolution of

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Speaker 2: open AI's safety team, I know, it's just it's almost cliche.

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Speaker 2: Shortly thereafter, former open ai board member Helen Toner revealed

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Speaker 2: that Sam Altman was fired from an open Ai because

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Speaker 2: of a regular pattern of deception, one where Aortman would

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Speaker 2: give inaccurate info about the company's safety processes on multiple occasions,

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Speaker 2: and his de seat was so severe the open Aiyes

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Speaker 2: Board only found out about the launch of chat GPT,

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Speaker 2: which by the way, is open a eyes first product

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Speaker 2: that really made money, arguably the biggest product in tech.

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Speaker 2: Do you want to know how they found out about it, Well,

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Speaker 2: they found out when they were browsing Twitter. They found

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Speaker 2: out then, not from the CEO of open Ai, the

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Speaker 2: company which they were the border very weird. Toner also

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Speaker 2: noted that Ortmand was an aggressi political player with the board,

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Speaker 2: correctly by the way, worrying the and I quote again

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Speaker 2: that if Sam Ortman had any inkling that the board

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Speaker 2: might do something that went against him, he'd pull out

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Speaker 2: all the stops, do everything in his power to undermine

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Speaker 2: the board and to prevent them from even getting to

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Speaker 2: the point of being able to fire him. As a reminder,

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Speaker 2: by the way, the board succeeded in firing Sam Mortman

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Speaker 2: in November last year, but not for long, with Ortmand

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Speaker 2: returning a CEO a few days later, kicking Helen Toner

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Speaker 2: off of the board along with Ilia Sudskava, a technical

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Speaker 2: co founder that Altman manipulated long enough to build chat

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Speaker 2: GBT and announced it him the moment that he chose

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Speaker 2: to complain. Sudskav, by the way, has resigned now He's

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Speaker 2: also one of the biggest technical minds though it's so

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Speaker 2: how is OPENAA going to continue anyway? Last week, a

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Speaker 2: group of insiders at various AI companies published an open

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Speaker 2: letter asking for their overlords, for the heads of these companies,

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Speaker 2: for the right to warn about advanced artificial intelligence in

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Speaker 2: a monument genuinely impressive monument to the bullshit machine that

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Speaker 2: Sam Olman has created. While there are genuine safety concerns

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Speaker 2: with AI, there really are, There are many of them

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Speaker 2: to consider. These people are desperately afraid of the computer

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Speaker 2: coming alive and killing them when they should fear. The

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Speaker 2: non technical asshole manipulate are getting rich making egregious promises

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Speaker 2: about what AI can do. AI researchers, you have to

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Speaker 2: live up to sam Ulman's promises. Sam Molton doesn't. This

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Speaker 2: is not your friend. The problem is not the boogeyman

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Speaker 2: computer coming alive. That's not happening, man. What's happening is

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Speaker 2: this guy is leading your industry to ruin, and the

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Speaker 2: bigger concern that they should have should be about what

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Speaker 2: Leo Ashenbrenner, a former safety researcher open ai, had to

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Speaker 2: say on the Duaquesh Ptel podcast, where he claimed that

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Speaker 2: security processes of open ai were and I quote egregiously

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Speaker 2: insufficient and that the priorities that the company were focused

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Speaker 2: on growth over stability of security. These people are afraid

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Speaker 2: of open ai potentially creating a computer that can think

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Speaker 2: for itself, that will come and kill them at a

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Speaker 2: time where they should be far more concerned about this

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Speaker 2: manipulative con artist that's running open ai. Sam Altman is

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Speaker 2: dangerous to artificial intelligence. Not because he's building artificial general intelligence,

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Speaker 2: which is a kind of AI that meets or surpasses

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Speaker 2: human cove capabilities by the way, kind of like data

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Speaker 2: from Star Trek. They're afraid of that happening when they

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Speaker 2: should be afraid of Aortman's focus. What does Sam Moortman

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Speaker 2: care about? Because the only thing I can find reading

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Speaker 2: about what Sam Mortman cares about is Sam Bloody Aortman.

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Speaker 2: And right now the progress attached to Sam Mortman actually

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Speaker 2: isn't looking that great. Open AI's growth is stalling, with

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Speaker 2: Alex Cantrewitz reporting that user growth has effectively come to

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Speaker 2: a halt based on a recent release claiming that chat

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Speaker 2: gpt had one hundred million users a couple of weeks ago,

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Speaker 2: which is, by the way, the exact same number that

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Speaker 2: the company claimed chat GPT had in November twenty twenty three.

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Speaker 2: Chat GPT is also a goddamn expensive product to operate,

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Speaker 2: with the company burning through capital at this insane rate.

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Speaker 2: It's definitely more than seven hundred thousand dollars a day.

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Speaker 2: It's got to be in the millions if not. What

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Speaker 2: it's insane and what open Ai is aggressively monetizing chat gbt,

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Speaker 2: both the customers and to businesses. It's so obviously far

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Speaker 2: from crossing the break even rubicon. They keep leaking and

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Speaker 2: they'll claim, oh, I didn't put that out there. They

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Speaker 2: keep telling people, oh, it's making billions of revenue, but

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Speaker 2: they never say profit. And eventually someone's going to turn

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Speaker 2: to them and say, hey, man, you can't just do

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Speaker 2: this for free or for negative. At some point, Sacha

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Speaker 2: Nadella is going to call Sam Ortman and say, Sammy, Sammy,

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Speaker 2: it's time, Sammy, it's got to be a real business.

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Speaker 2: I assume he calls him that because the supernatural. But

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Speaker 2: as things get desperate, Samuel was going to use the

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Speaker 2: only approach he really has, sheer force of will. He's

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Speaker 2: going to push open AI to grow and sell into

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Speaker 2: as many industries as possible. And he's a specious hype man.

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Speaker 2: He's going to be selling to other specious hype men.

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Speaker 2: The Jim Kramers of the world are going to eat

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Speaker 2: it up. And they're all all of them, the mock Bernioffs,

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Speaker 2: the satch In, the dell As, the sun Dapashais. They're

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Speaker 2: all desperate to connect themselves with the future and with

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Speaker 2: generative AI and those that he's selling to the company's

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Speaker 2: brokering deals, yes, even Apple. They're desperate to connect their

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Speaker 2: companies to another company which is building a bubble, a

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Speaker 2: bubble inflated by Sam Altman. And I'd argue that this

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Speaker 2: is exceedingly dangerous for Silicon Valley and for the tech

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Speaker 2: industry writ large, as executives that have become disconnected from

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Speaker 2: the process of creating software and hardware follow yet another

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Speaker 2: non technical founder hocking unprofitable, unsustainable, and hallucination prone software.

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Speaker 2: It's just very frustrating. If there was a very technical

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Speaker 2: mind at these companies, they might walk away. And I'm

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Speaker 2: not going to give Tim Cook much credit, but looking

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Speaker 2: into it, I can't find any evidence that Apple is

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Speaker 2: buying a bunch of GPUs, the things that you use

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Speaker 2: to power these generative AI models. I found some researcher

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Speaker 2: and analysts suggesting that they would buy a lot. But

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Speaker 2: now open Ai is doing a deal with Apple to

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Speaker 2: power the next iOS, and it's interesting. It is interesting

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Speaker 2: that Apple isn't doing this themselves. Apple a company with

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Speaker 2: hundreds of billions of dollars in the bank. I believe

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Speaker 2: that pretty much prints money. That alone makes me think

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Speaker 2: it's a bubble. Now it might look like an asshole

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Speaker 2: if it comes out they have. But also, why are

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Speaker 2: they subcontracting this to open ai when they could build

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Speaker 2: it themselves, as Apple has always done. Very strange. It's

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Speaker 2: all so peculiar. But I wanted to get a little

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Speaker 2: bit deeper into the Sam Mormon's story, And as I

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Speaker 2: discussed last episode, Ellen Hue of Bloomberg, she's been doing

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Speaker 2: this excellent reporting on the land and joins me today

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Speaker 2: to talk about the subject of a recent podcast. Sam

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Speaker 2: Olman's Rise to Power. So tell me a little bit

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Speaker 2: about the show are you working on?

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Speaker 1: The show is the new season of Foundering, which is

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Speaker 1: a serialized podcast from Bloomberg Technology. So this is season five,

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Speaker 1: and in every season we've told one story of a

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Speaker 1: high stakes drama in Silicon Valley. I was also the

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Speaker 1: host of season one, which came out several years ago,

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Speaker 1: was about we Work, and we've done other companies since then,

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Speaker 1: and season five is about Open AI and Sam Altman,

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Speaker 1: and I think we really tried to cover the arc

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Speaker 1: of the company's creation and where it is now. But

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Speaker 1: in doing so, we really tried to do a character

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Speaker 1: study of Sam Altman, like he's a very important person

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Speaker 1: in the tech industry right now with a lot of power,

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Speaker 1: and we really wanted to ask ourselves a question and

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Speaker 1: to help listeners ask themselves a question. Should we trust him?

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Speaker 1: Should we trust this person who is currently in a

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Speaker 1: position of a lot of influence and about whom there

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Speaker 1: have been very serious, you know, allegations and questions raised

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Speaker 1: about you know, to put it in the words of

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Speaker 1: the opening eyeboard, his not consistently candid behavior. And I

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Speaker 1: think it's, you know, my hope is that we give

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Speaker 1: listeners a chance to hear kind of the whole story,

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Speaker 1: and it's like broader, you know, when there's news that's happening,

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Speaker 1: it can happen so quickly it's hard to get a

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Speaker 1: step back. And I think what the show really does

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Speaker 1: is it collects a lot of information in one place,

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Speaker 1: and we also have lots of new information that you

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Speaker 1: won't hear anywhere else, and interviews with people who you know,

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Speaker 1: have worked with Sam, who knew him when he was younger.

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Speaker 1: We have an interview with Sam's sister Annie, from whom

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Speaker 1: he is estranged, and there's a lot of material in there.

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Speaker 1: I think that tries to get closer to this answer

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Speaker 1: of like, what should we make of this person? How

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Speaker 1: should we think about checks and balances of power when

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Speaker 1: we have these companies that are, by all appearances, gathering

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Speaker 1: a lot of power and there for the people who

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Speaker 1: are running them have a lot of power as well.

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Speaker 1: So we have it's a five episode arc, five episode season,

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Speaker 1: and the first three episodes are out now to the

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Speaker 1: general public, and the last two will come out on

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Speaker 1: subsequent Thursdays, And if you would like to binge the

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Speaker 1: whole season right away, The episodes are available early to

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Speaker 1: Bloomberg dot Com subscribers.

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Speaker 2: So you've just started this series about Sam Altman and

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Speaker 2: his upbringing indoors, so the growth of open ai and

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Speaker 2: looped and everything. Who are the people that have helped

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Speaker 2: him get where he is today?

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Speaker 1: Though, So the making of Sam Altman is really interesting

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Speaker 1: part of the overall story of Sam Altman. You know,

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Speaker 1: many people know him as the CEO of open Ai

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Speaker 1: because that's the role he's been in when he has

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Speaker 1: risen to prominence, you know, beyond Silicon Valley. Like I

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Speaker 1: think for many years he was well known in Silicon Valley,

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Speaker 1: but this is like now he's kind of a household name,

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Speaker 1: and so it's important to understand where Sam came from.

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Speaker 1: You know, he's been in the valley for you know,

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Speaker 1: since two thousand and five, I think is when he

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Speaker 1: started college two thousand and four, two thousand and five

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Speaker 1: at Stanford. Then he dropped out, and then he joined

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Speaker 1: y Combinator, the now famous startup accelerator. But he was

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Speaker 1: actually part of the first cohort of founders ever in

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Speaker 1: n YC. Along with which as well right yes, including

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Speaker 1: the the co founders of Twitch and of Reddit and

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Speaker 1: so Emmett Sheer, you know, for those who know Emmit

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Speaker 1: Sheer has a like very short, seventy two hour cameo

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Speaker 1: in the open AI very Sam been firing Saga. But yes,

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Speaker 1: Emmett and Sam were both in the same y C batch.

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Speaker 1: So when we think about Sam's early career in Silicon Valley,

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Speaker 1: I think what's important to know is that he rose

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Speaker 1: very quickly, in part because he was very successful in

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Speaker 1: making these strategic, advantageous friendships and connections with already established

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Speaker 1: people in the valley. The most important one is Paul Graham,

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Speaker 1: who is the you know, one of the founders of

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Speaker 1: y Combinator and you know basically like immediately took Sam

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Speaker 1: under his wing when Sam joined this first batch of YC.

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Speaker 1: And yeah, Paul's a really important mentor to Sam. He's

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Speaker 1: kind of the first person who really sees in Sam

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Speaker 1: this you know, ambition, this hunger for power, this like

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Speaker 1: drive to really build bigger and bigger companies. Even when

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Speaker 1: you know they met when Sam Altman was nineteen, so

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Speaker 1: Paul like sees him as a teenager and sees this

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Speaker 1: future potential. And so yes, you know, not only did

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Speaker 1: Paul become a mentor to him and sort of helped

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Speaker 1: build Sam's profile over those early years because he would

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Speaker 1: you know, Paul Graham is very famous for writing these

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Speaker 1: essays about how to build startups and how to build

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Speaker 1: the best startups, and if you're at all interested in

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Speaker 1: building startups, you've read many of them. They're kind of

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Speaker 1: like almost like a startup bible. And in many of

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Speaker 1: them he extols the virtues of Sam Altman. He talks

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Speaker 1: about Sam's ambition, he talks about Sam's cunning, his ability

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Speaker 1: to like you know, make deals and like think big

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Speaker 1: and never.

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Speaker 2: Actually think Sam Motman is done, is what I've found.

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Speaker 1: Yeah, there are some interesting you know, I've read many

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Speaker 1: of the things Paul has written about Sam. Some of

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Speaker 1: my favorite ones include Paul writing that within three minutes

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Speaker 1: of meeting Sam, this was when Sam was nineteen, Paul

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Speaker 1: thought to himself, Ah, so this is what a young

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Speaker 1: Bill Gates is like, or you know, this is what

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Speaker 1: Bill Gates was like at nineteen, I think is the

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Speaker 1: exact quote. So, you know, he really build him up

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Speaker 1: in the way. And I do think Paul had like

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Speaker 1: unique insight into Sam, like they were close. They in

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Speaker 1: many ways I'm sure still are, but it is this

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Speaker 1: interesting role where you know, Paul met Sam when he

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Speaker 1: really didn't have much to his name, and he really

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Speaker 1: elevated him early on through his writings as this like

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Speaker 1: startup founder to emulate right that other founders should be

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Speaker 1: emulating Sam. And then of course, as Sam progresses in

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Speaker 1: the valley, he also starts to write these like startup

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Speaker 1: wisdom essays in a similar style to Paul. And then,

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Speaker 1: of course, the most important thing that happens is that

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Speaker 1: in twenty fourteen, when Paul decides he no longer wants

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Speaker 1: to run by Combinator, which at this point is a

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Speaker 1: much bigger vehicle than it was when Sam first started.

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Speaker 1: It has no longer just a few stops totally. It

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Speaker 1: has produced Stripe, Dropbox, Airbnb. This is a big job, right,

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Speaker 1: like running y Combinator. And when Paul wants to hand

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Speaker 1: it off to someone, you know, he has said that

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Speaker 1: the only person he considered giving this to was Sam.

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Speaker 1: So in twenty fourteen, when Sam is I believe twenty

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Speaker 1: eight years old, he becomes the president of Y Combinator,

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Speaker 1: and this is you know, he had started a startup,

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Speaker 1: it didn't really work, he sold it and was starting

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Speaker 1: to tabble in angel investing, and at that point Paul

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Speaker 1: really elevated Sam to this new position of power. And

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Speaker 1: then he ran YC for a while and then started

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Speaker 1: open Ai. And in starting open Ai, he also leveraged

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Speaker 1: these like very useful connections with particularly powerful people who

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Speaker 1: could help him, such as Elon Musk, who was able

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Speaker 1: to give the vast majority of the pledged funding to

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Speaker 1: start open Ai. Later, when Elon Musk splits from open Ai,

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Speaker 1: Sam makes his very powerful partnership with Satya Nadella to

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Speaker 1: help fund open Ai. Another important partnership that Sam has made,

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Speaker 1: you know, much earlier on was his friendship with Peter

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Speaker 1: Teel And one of the things Peter Teal does is

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Speaker 1: also you know, gives him millions of dollars to start investing.

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Speaker 1: This is like before Sam takes over at y Yeah.

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Speaker 1: And you know another thing that Paul did that really

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Speaker 1: Paul Graham did that really helped Sam was also he

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Speaker 1: gave Paul had the opportunity to be one of the

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Speaker 1: first investors in Stripe. He was offered the chance to

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Speaker 1: invest thirty thousand dollars for four percent of Stripe, which,

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Speaker 1: of course, now that Stripe is enormous we all know

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Speaker 1: how valuable that was, and Paul split it with Sam.

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Speaker 1: He was like, oh, I might as well share this

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Speaker 1: with Sam. So Sam has said that that fifteen thousand

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Speaker 1: dollars for a two percent of Stripe has been, you know,

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Speaker 1: one of his best performing angel investments ever.

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Speaker 2: That was something he question is always where he got

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Speaker 2: fifteen grand from. He was still working on Looped at

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Speaker 2: the time. It's funny how perfletrip anyway.

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Speaker 1: Yeah, my guess is fifteen grand was I don't actually

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Speaker 1: know this, but my guess is fifteen perllen was not

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Speaker 1: hard for him to pull up. And it's one of

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Speaker 1: those things where it's really is, you know, access to

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Speaker 1: access and relationships are the sorts of things that can

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Speaker 1: build a career and can lead to great wealth, right

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Speaker 1: like Sam is now you know, by our own internal

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Speaker 1: accounts and by other lists billionaire. And this money comes

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Speaker 1: from you know, not from open AI, but from these

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Speaker 1: angel investments that he's made early on that have been

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Speaker 1: enormously successful.

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Speaker 2: So you called him in one of the titles, the

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Speaker 2: Most Silicon Valley Man Alive. Is this what you're getting at,

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Speaker 2: this kind of power player mentality?

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Speaker 1: Yeah, I think it's it reflects a few things. One

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Speaker 1: that even though he's you know, he's in his late thirties,

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Speaker 1: he's been a player in Silicon Valley for such a

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Speaker 1: long time, you know, close to two decades. And also

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Speaker 1: that he's just someone who is extremely well connected. So

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Speaker 1: even before he took over Y Combinator, which I think

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Speaker 1: you could argue is like kind of king of the

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Speaker 1: startup world in some sense, like Y Combinators, like you know,

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Speaker 1: the topics totally, even before he took over I Y Comminator,

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Speaker 1: I think he was extremely well connected. He's very social,

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Speaker 1: he's very helpful, he's very efficient, Like many people have

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Speaker 1: told me stories in which he, you know, calling Sam

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Speaker 1: and talking for five minutes has saw their problem because

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Speaker 1: he knows exactly the right person to call to fix it,

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Speaker 1: or you know, he's really good at making deals. I

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Speaker 1: think it's just clear he's extremely well integrated into this

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Speaker 1: world and has very successfully moved up the Silicon Valley

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Speaker 1: status ladder to the point where he is now, which

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Speaker 1: is kind of you know, one of the you know,

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Speaker 1: he's the CEO of the one of the arguably hottest

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Speaker 1: companies in the valley right now, and I think that

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Speaker 1: that's not luck right, Like he didn't just come up

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Speaker 1: with He's not like a nobody who came up with

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Speaker 1: an idea. It's like he has the connections and has

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Speaker 1: parlayed his connections into power to bring him to the

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Speaker 1: point he is now.

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Speaker 2: So in your experience talking to people about Sam Altman,

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Speaker 2: how technical is he? Do you think? What if you heard?

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Speaker 2: Because you say, there he wasn't lucky, But he also

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Speaker 2: does not appear to have successfully run a business because

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Speaker 2: Luke shut down two people, well, two executives tried to

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Speaker 2: get him fired from there. He got fired from y Combinator,

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Speaker 2: which did very well. But at the same time, why

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Speaker 2: he was basically a convey about for money at one point,

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Speaker 2: not so much recently. Yeah, it just it feels weird

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Speaker 2: that this completely non technical, semi non technical guy has

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Speaker 2: ascended so far.

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Speaker 1: My sense is that's not maybe the most fair description.

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Speaker 1: Like I think Sam is incredibly smart, and people say

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Speaker 1: this a lot, and you know, I believe them. I

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Speaker 1: think his special skill, you know, he obviously knows how

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Speaker 1: to like he's an engineer, he has training. I'm sure

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Speaker 1: he can build a lot of stuff. It seems like

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Speaker 1: his comparative advantage, his special skill is relationships, deal making,

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Speaker 1: figuring out who exactly is the right person to help

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Speaker 1: him in whatever he's really trying to get done, and

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Speaker 1: figuring out the best way to get something to happen.

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Speaker 1: You know, one of the people I spoke to is

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Speaker 1: someone who knows Sam from when he was younger and

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Speaker 1: knows him personally, and said that his superpower is figuring

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Speaker 1: out who's in charge or figuring out who is in

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Speaker 1: the best position to help him, and then charming them

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Speaker 1: so that they help him with whatever goal he's trying

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Speaker 1: to get done. And I think that, like, yeah, one

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Speaker 1: could argue that that's actually a really good skill set

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Speaker 1: if you want to build a very big company, which

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Speaker 1: you know, I think at this current moment he has

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Speaker 1: right like opening eyes. Really, you know, you can there's

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Speaker 1: a lot that you can say about whether they're upholding

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Speaker 1: their original mission or that. You know, that's up for debate,

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Speaker 1: But I think that they've obviously been commercially successful so far, so.

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Speaker 2: It feels like Silicon Valley on some level. And I

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Speaker 2: just to give some thoughts here within the two episodes

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Speaker 2: I'm doing here, the pattern I've seen with Sam Oltman

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Speaker 2: is that everyone seems to want him to win, and

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Speaker 2: there's almost a degree of they will make it. So

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Speaker 2: have you seen anyone who's really a detractor or anyone

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Speaker 2: who's not pro Sam Oltman, because it's interesting how few

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Speaker 2: people are in tech.

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Speaker 1: Well there is. I won't get too into it because

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Speaker 1: this is in some of the future episodes which will

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Speaker 1: drop in future weeks, but you know, I would say

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Speaker 1: in in in some of the conversations that I've had

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Speaker 1: off the record about people about in some of the

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Speaker 1: conversations I've had off the record with people about Sam,

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Speaker 1: I think, you know, my general impressions are people often

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Speaker 1: do find him impressive in terms of what he has

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Speaker 1: gotten done, you know, the size and scale of his

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Speaker 1: ambitions and the way that he has generally been able

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Speaker 1: to make that happen. I think there's also a lot

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Speaker 1: of people who you know, are willing to privately share

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Speaker 1: some gripes that they might have about him. Also, you know,

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Speaker 1: in recent weeks we've seen people be a lot more

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Speaker 1: public about some of those gripes. We have Helen Toner,

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Speaker 1: a former former board member at open AI who voted

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Speaker 1: to remove Sam last November, saying publicly in the last

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Speaker 1: few weeks that Sam lied to her and the other

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Speaker 1: former board members that his you know, misdirection made them

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Speaker 1: feel like they couldn't do their jobs. And she has

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Speaker 1: also said that people were intimidated to the point where

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Speaker 1: they did not feel comfortable speaking more publicly about negative

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Speaker 1: experiences they'd had about Sam, that they are afraid to

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Speaker 1: speak more publicly about you know, times that he has

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Speaker 1: not been honest with them or you know, has in

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Speaker 1: which they've had challenging experiences. And that has also been

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Speaker 1: reflected in some of the private conversations I've had in

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Speaker 1: which people you know, they might have complaints or they

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Speaker 1: might have had like challenging situations with him, and I

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Speaker 1: think they just feel like the risk calculus is not

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Speaker 1: worth it to come out and say something like that.

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Speaker 1: But you know, there have been bits and pieces where

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Speaker 1: people have come out and said things that you know,

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Speaker 1: Sam has. You know. Another thing that the board members

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Speaker 1: have said was that Sam had been deceptive and manipulative,

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Speaker 1: and that's also followed up by or not followed up.

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Speaker 1: There was also I think back in November, a former

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Speaker 1: open ai employee who had tweeted something publicly about that

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Speaker 1: you know, saying that Sam had lied to him on occasion,

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Speaker 1: even though he had also always been nice to him,

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Speaker 1: which I think is a very interesting combination of.

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Speaker 2: That Silicon Valley though, I'm afraid of dealing with them,

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Speaker 2: but they were so nice to me.

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Speaker 1: And yeah, of course that you know that person has

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Speaker 1: not elaborated more publicly about what they meant. But I

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Speaker 1: think I think, you know, I think this is why

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Speaker 1: people are asking themselves these questions, which is like, you know,

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Speaker 1: the more that we hear about what the board uh

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Speaker 1: was thinking before they decided to fire Sam, I think

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Speaker 1: the more people are wondering about what are the patterns

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Speaker 1: of behavior that he shows that you know that led

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Speaker 1: to the board trying to make this drastic move.

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Speaker 2: Yeah, that's actually an interesting point. So when Samulton was

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Speaker 2: fired from open AI, there was this very strange reaction

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Speaker 2: from Silicon Valley, including some in the media, where it

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Speaker 2: was almost like a tounga Games everyone doing the symbol

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Speaker 2: thing where everyone's like, oh, we got to put sam

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Speaker 2: otment back in, isn't it kind of strange? We still

432
00:24:13,640 --> 00:24:16,320
Speaker 2: don't know why he was actually fired, though, I mean,

433
00:24:16,320 --> 00:24:19,800
Speaker 2: Helen Tona has elaborated like I've never seen a have

434
00:24:19,840 --> 00:24:21,439
Speaker 2: you seen anything like this? In your career.

435
00:24:22,080 --> 00:24:26,000
Speaker 1: I think that it has been surprising that there has

436
00:24:26,080 --> 00:24:31,760
Speaker 1: not been more of a clear answer. I think, you know,

437
00:24:31,800 --> 00:24:35,080
Speaker 1: as as time has gone on, like we have heard

438
00:24:35,119 --> 00:24:38,160
Speaker 1: a little bit more like I think Helen Toner has,

439
00:24:39,000 --> 00:24:42,120
Speaker 1: you know, to her credit, tried to give more information

440
00:24:42,359 --> 00:24:46,479
Speaker 1: in recent weeks about what happened. I think, you know,

441
00:24:46,800 --> 00:24:49,639
Speaker 1: people were obviously asking this question six months ago, and

442
00:24:49,680 --> 00:24:51,119
Speaker 1: so I think like there's been a little bit of

443
00:24:51,160 --> 00:24:55,320
Speaker 1: a delay and trying to get this this answer, and

444
00:24:55,359 --> 00:24:57,880
Speaker 1: I wonder if maybe there just isn't like a very

445
00:24:59,560 --> 00:25:02,200
Speaker 1: neat answer to it, and so and then in that

446
00:25:02,800 --> 00:25:07,080
Speaker 1: absence we get this kind of more of a like murky, multifaceted,

447
00:25:07,160 --> 00:25:09,879
Speaker 1: multi voiced answer. But I yes, I agree that it

448
00:25:10,160 --> 00:25:12,440
Speaker 1: is sort of surprising that there that there hasn't been

449
00:25:13,280 --> 00:25:17,959
Speaker 1: more clarification on what exactly happened or a little bit

450
00:25:18,040 --> 00:25:22,080
Speaker 1: more granular detail about what led up to it.

451
00:25:23,359 --> 00:25:26,560
Speaker 2: So on today, I aihype in general said that a

452
00:25:26,560 --> 00:25:29,800
Speaker 2: bit weird. I'll keep going, why do you think there's

453
00:25:29,840 --> 00:25:32,760
Speaker 2: such a dolf between what Sam Altman says and what

454
00:25:32,880 --> 00:25:34,520
Speaker 2: chat GPT can actually do?

455
00:25:35,760 --> 00:25:38,480
Speaker 1: What Sam Altman says, what are you talking about specifically.

456
00:25:38,040 --> 00:25:40,400
Speaker 2: As in he says it will be a super smart company. Yeah,

457
00:25:40,440 --> 00:25:42,200
Speaker 2: yeh yeah, that he'll be all of these things.

458
00:25:42,960 --> 00:25:45,280
Speaker 1: Well, this is something that we get into in episode three,

459
00:25:45,280 --> 00:25:47,600
Speaker 1: which is a personal interest of mine, which is kind

460
00:25:47,640 --> 00:25:51,399
Speaker 1: of the psychology of the AI industry right now. And

461
00:25:52,280 --> 00:25:55,399
Speaker 1: you know, I what I find so interesting about this

462
00:25:55,440 --> 00:25:58,120
Speaker 1: and what we try to delve into in episode three

463
00:25:58,160 --> 00:26:01,639
Speaker 1: and kind of throughout the series is these kind of

464
00:26:01,680 --> 00:26:05,200
Speaker 1: like extreme projections about AI and in the industry, you

465
00:26:05,240 --> 00:26:07,840
Speaker 1: see both positive ones and negative ones, and I think,

466
00:26:08,080 --> 00:26:11,440
Speaker 1: you know, the negative ones, that's what looks like AI dooomerism,

467
00:26:11,560 --> 00:26:15,159
Speaker 1: AI existential risks, sometimes called AI safety depending on your

468
00:26:15,160 --> 00:26:17,240
Speaker 1: point of view. But you know, it's these projections that

469
00:26:18,200 --> 00:26:23,800
Speaker 1: you know, superintelligence might very quickly and very soon learn

470
00:26:23,920 --> 00:26:27,639
Speaker 1: to self improve in a way that allows it to

471
00:26:27,800 --> 00:26:31,200
Speaker 1: rapidly outstrip our control and our capabilities and could lead

472
00:26:31,240 --> 00:26:34,959
Speaker 1: to the extinction of humanity. There are so many interesting

473
00:26:34,960 --> 00:26:38,160
Speaker 1: things to say about the psychology of believing that our

474
00:26:38,240 --> 00:26:41,760
Speaker 1: human race might either be wiped out or incredibly changed

475
00:26:42,680 --> 00:26:46,320
Speaker 1: within our lifetimes, and we get into that in episode three.

476
00:26:46,359 --> 00:26:48,560
Speaker 1: I think I really wanted to get into the psychology

477
00:26:48,560 --> 00:26:51,359
Speaker 1: of someone who believes that AI doom is just around

478
00:26:51,400 --> 00:26:53,840
Speaker 1: the corner. And so we talked to someone who sort

479
00:26:53,840 --> 00:26:56,920
Speaker 1: of became convinced of this belief soon after the twenty

480
00:26:56,920 --> 00:27:02,160
Speaker 1: sixteen alphag Matches in which the go playing AI beat

481
00:27:02,200 --> 00:27:05,320
Speaker 1: the you know, the world's champion in Go and he

482
00:27:05,359 --> 00:27:07,720
Speaker 1: talks about yeah, no longer, you know, deciding not to

483
00:27:07,840 --> 00:27:09,960
Speaker 1: make a retirement account because he was like, what is

484
00:27:10,000 --> 00:27:13,880
Speaker 1: the point by the time I reach retirement age, either

485
00:27:14,000 --> 00:27:16,960
Speaker 1: the world will be dramatically different and money won't matter,

486
00:27:17,040 --> 00:27:19,880
Speaker 1: or will all be dead? And and I think that

487
00:27:20,280 --> 00:27:22,119
Speaker 1: even though some people might scoff at that, that's like

488
00:27:22,119 --> 00:27:25,679
Speaker 1: a real belief that people believe that this, you know,

489
00:27:25,760 --> 00:27:29,800
Speaker 1: these extreme possible scenarios are in our near future. And

490
00:27:29,880 --> 00:27:32,520
Speaker 1: on the other hand, we also see extreme projections in

491
00:27:33,000 --> 00:27:36,159
Speaker 1: a positive direction. You know, this idea that AI is

492
00:27:36,200 --> 00:27:41,920
Speaker 1: going to unlock a whole new era of human flourishing,

493
00:27:42,000 --> 00:27:44,880
Speaker 1: that we might expand beyond our planet, that we might

494
00:27:44,920 --> 00:27:49,400
Speaker 1: be able to give say what abundant abundance right exactly?

495
00:27:49,440 --> 00:27:52,880
Speaker 1: You know. One of the things we do I believe

496
00:27:52,920 --> 00:27:54,879
Speaker 1: in episode three is is do a little bit of

497
00:27:54,920 --> 00:27:57,320
Speaker 1: a supercut of Sam all been talking about abundance. It's

498
00:27:57,359 --> 00:27:59,840
Speaker 1: it's pretty clear that This is a way that he

499
00:27:59,880 --> 00:28:02,320
Speaker 1: likes to frame our AI future is going to be

500
00:28:02,320 --> 00:28:05,280
Speaker 1: this future in which everyone has plenty, right, everyone has

501
00:28:06,480 --> 00:28:10,000
Speaker 1: you know, access to intelligence, abundant energy, abundant access to

502
00:28:10,920 --> 00:28:13,240
Speaker 1: superintelligence that can help us live kind of our best

503
00:28:13,280 --> 00:28:18,800
Speaker 1: lives and beyond our wildest dreams. Right. And I you know,

504
00:28:18,960 --> 00:28:22,639
Speaker 1: obviously Silicon Valley is a place where people like to

505
00:28:22,840 --> 00:28:26,480
Speaker 1: make grandiose statements. But this is beyond that, right, This

506
00:28:26,600 --> 00:28:30,119
Speaker 1: is not just this is not just like you know,

507
00:28:30,160 --> 00:28:32,840
Speaker 1: we joked about we work, We works. Mission statement was

508
00:28:32,880 --> 00:28:37,160
Speaker 1: to elevate the world's consciousness. Like well, galaxies of human

509
00:28:37,200 --> 00:28:41,080
Speaker 1: flourishing for eons beyond us. Like that is on another scale, right,

510
00:28:41,160 --> 00:28:45,280
Speaker 1: Like we're talking about something that is sort of at

511
00:28:45,320 --> 00:28:49,040
Speaker 1: an unprecedented level of extreme rhetoric. And I think that's

512
00:28:49,040 --> 00:28:52,160
Speaker 1: really interesting. I think it is a very powerful motivator,

513
00:28:52,200 --> 00:28:54,520
Speaker 1: both in a you know, in the doumer sense and

514
00:28:54,560 --> 00:28:57,240
Speaker 1: also in the abundance sense. People believing that what they're

515
00:28:57,240 --> 00:29:01,200
Speaker 1: working on is the most important technological leap forward for humanity.

516
00:29:02,080 --> 00:29:07,760
Speaker 1: Talk about a motivating reason to work on this technology, right,

517
00:29:07,800 --> 00:29:10,800
Speaker 1: talk about a way to feel powerful, feel like you're

518
00:29:10,840 --> 00:29:13,040
Speaker 1: making a huge difference. I think that's a really key

519
00:29:13,080 --> 00:29:16,240
Speaker 1: part of what's driving a lot of work in AI

520
00:29:16,360 --> 00:29:16,720
Speaker 1: right now.

521
00:29:17,480 --> 00:29:20,640
Speaker 2: Striving a lot of work, sure, but with Aortman himself,

522
00:29:21,240 --> 00:29:25,560
Speaker 2: there is this golf. It is a million mile golf

523
00:29:25,600 --> 00:29:28,400
Speaker 2: between the things he says and what chat GBT is

524
00:29:28,440 --> 00:29:31,760
Speaker 2: even even on the most basic level capable of doing

525
00:29:31,840 --> 00:29:34,800
Speaker 2: and will be capable. And it just feels like it

526
00:29:34,840 --> 00:29:39,280
Speaker 2: almost feels like he's become the propagandist for the tech industry.

527
00:29:40,600 --> 00:29:44,160
Speaker 2: And it's very strange to me how far that distance is.

528
00:29:44,200 --> 00:29:48,520
Speaker 2: Because you've got the AI doomers and the AI optimist

529
00:29:48,520 --> 00:29:52,680
Speaker 2: I guess you'd call them. But Aortmand doesn't even feel

530
00:29:52,720 --> 00:29:55,240
Speaker 2: like he's in with He's just kind of He'll say

531
00:29:55,320 --> 00:29:57,560
Speaker 2: one day that he doesn't think it's a creature, the

532
00:29:57,640 --> 00:29:59,400
Speaker 2: next one will say it's going to kill us, or

533
00:30:00,080 --> 00:30:04,200
Speaker 2: all just feels like a pr campaign but for nothing.

534
00:30:05,600 --> 00:30:09,400
Speaker 1: Yeah, it has been interesting to try to answer the question,

535
00:30:09,440 --> 00:30:10,840
Speaker 1: you know, one of the questions we tried to answer

536
00:30:10,840 --> 00:30:14,600
Speaker 1: in the podcast is does Sam actually believe you know,

537
00:30:14,680 --> 00:30:17,560
Speaker 1: because as you mentioned, there are some early clips of him,

538
00:30:17,720 --> 00:30:19,360
Speaker 1: you know, And when I say early, I mean around

539
00:30:19,400 --> 00:30:21,800
Speaker 1: the time of founding Open AI twenty fifteen. Or so,

540
00:30:22,400 --> 00:30:26,600
Speaker 1: there's some clips of him talking about, you know, saying

541
00:30:26,720 --> 00:30:29,080
Speaker 1: somewhat jokingly that AI might kill us all. But there's

542
00:30:29,120 --> 00:30:31,240
Speaker 1: also this uh, you know, very famous blog post that

543
00:30:31,280 --> 00:30:33,440
Speaker 1: he wrote in twenty fifteen in which he says that,

544
00:30:34,080 --> 00:30:36,920
Speaker 1: you know, basically super intelligence is one of the most

545
00:30:36,920 --> 00:30:40,760
Speaker 1: serious risks to humanity, you know, full stop. And so

546
00:30:41,080 --> 00:30:43,640
Speaker 1: it's clear that at some point in his life he

547
00:30:43,800 --> 00:30:46,960
Speaker 1: believed kind of what we might now call a more

548
00:30:47,000 --> 00:30:50,520
Speaker 1: doom ory outlook. But as time has gone on, he

549
00:30:50,640 --> 00:30:53,560
Speaker 1: has you know, offered views that are a little bit

550
00:30:53,560 --> 00:30:56,920
Speaker 1: more measured and more positive. You know, he tends to

551
00:30:57,200 --> 00:30:59,080
Speaker 1: you know, in his big media tour of twenty twenty three,

552
00:30:59,800 --> 00:31:03,360
Speaker 1: he tended to talk about how AI was going to

553
00:31:04,320 --> 00:31:07,720
Speaker 1: you know, his projection was that AI would radically transform society,

554
00:31:07,720 --> 00:31:09,640
Speaker 1: but that it would be net good, right, that like,

555
00:31:09,800 --> 00:31:13,160
Speaker 1: overall we would be glad that this happened, and that

556
00:31:13,240 --> 00:31:16,959
Speaker 1: it would improve lives, even if in the short term

557
00:31:17,680 --> 00:31:20,680
Speaker 1: or for some people it might prove to be bringing

558
00:31:20,720 --> 00:31:24,360
Speaker 1: a lot of challenges as well. And so it is

559
00:31:24,440 --> 00:31:26,040
Speaker 1: you know, I think one of the interesting things about

560
00:31:26,160 --> 00:31:28,240
Speaker 1: is about him is it is a little hard to

561
00:31:28,280 --> 00:31:30,640
Speaker 1: pin down exactly what he thinks. I think you're right

562
00:31:30,680 --> 00:31:35,440
Speaker 1: that I wouldn't consider him like a gung ho effective accelerationist.

563
00:31:35,480 --> 00:31:37,240
Speaker 1: I would not consider him a dumer. He is like

564
00:31:38,360 --> 00:31:41,320
Speaker 1: somewhere in this large gulf in between there. But I

565
00:31:41,360 --> 00:31:46,640
Speaker 1: think he's also smart enough to know that making grandiose

566
00:31:46,680 --> 00:31:52,840
Speaker 1: projections about what AI could bring is a compelling story, right, Like,

567
00:31:53,040 --> 00:31:57,120
Speaker 1: is a story that he can help sell by being

568
00:31:57,160 --> 00:31:59,000
Speaker 1: like a spokesman for it. And often that is the

569
00:31:59,080 --> 00:32:01,520
Speaker 1: role of a CEO, is to be a really good storyteller,

570
00:32:01,920 --> 00:32:05,040
Speaker 1: to bring the pitch of the company to the public,

571
00:32:05,120 --> 00:32:09,800
Speaker 1: to investors, to potential employees, to customers, to try to

572
00:32:09,800 --> 00:32:11,280
Speaker 1: sell them on this vision of the future. And I

573
00:32:11,280 --> 00:32:13,520
Speaker 1: do think Sam is good at that. There is an

574
00:32:13,520 --> 00:32:19,200
Speaker 1: interesting tidbit in episode three in which we interview a

575
00:32:19,280 --> 00:32:22,080
Speaker 1: fiction writer who was actually hired on contract by open

576
00:32:22,120 --> 00:32:28,200
Speaker 1: Ai to write like a novella about AI futures and

577
00:32:28,240 --> 00:32:31,680
Speaker 1: things like that. And yeah, he just talks a little

578
00:32:31,680 --> 00:32:34,160
Speaker 1: bit about you know, the novella is not I think

579
00:32:34,480 --> 00:32:37,120
Speaker 1: in active use within open Ai, but they did at

580
00:32:37,120 --> 00:32:40,480
Speaker 1: some point, see they did, at some point see value

581
00:32:40,600 --> 00:32:43,760
Speaker 1: in commissioning it. And I think you know something that

582
00:32:43,800 --> 00:32:47,000
Speaker 1: the author, Patrick House explains to us, is you know

583
00:32:47,320 --> 00:32:51,360
Speaker 1: that open Ai, just like many other startups, is really

584
00:32:51,440 --> 00:32:54,280
Speaker 1: motivated by story, right, and that Sam Altman is inspired

585
00:32:54,680 --> 00:32:56,880
Speaker 1: by fiction. You know, it's inspired by certain kinds of

586
00:32:56,880 --> 00:32:59,160
Speaker 1: sci fi. I think this is not unique to Sam.

587
00:32:59,240 --> 00:33:02,360
Speaker 1: Many founders in Silicon Valley, you know, Elon Musk has

588
00:33:02,360 --> 00:33:05,640
Speaker 1: talked about this as well, are driven to create things

589
00:33:05,680 --> 00:33:09,160
Speaker 1: in part because of what they read about when they

590
00:33:09,160 --> 00:33:11,600
Speaker 1: were younger, that you know, these dreams of the future.

591
00:33:12,400 --> 00:33:14,720
Speaker 1: And so it's just interesting to get his perspective on

592
00:33:15,320 --> 00:33:18,680
Speaker 1: how motivating a story can be, and how motivating this

593
00:33:19,040 --> 00:33:21,320
Speaker 1: compelling story of like, oh, we're building something that's going

594
00:33:21,400 --> 00:33:23,880
Speaker 1: to change the course of human history. Like you just

595
00:33:23,920 --> 00:33:26,640
Speaker 1: couldn't ask for a more powerful motivating force.

596
00:33:28,000 --> 00:33:33,840
Speaker 2: So as Alman accumulates power and as he kind of

597
00:33:34,000 --> 00:33:37,320
Speaker 2: sends the top of open Ai, do you think he's

598
00:33:37,400 --> 00:33:39,920
Speaker 2: done there? Do you think there's going to be another

599
00:33:40,000 --> 00:33:42,760
Speaker 2: thing he starts? Because it feels like you've discussed like

600
00:33:42,920 --> 00:33:44,720
Speaker 2: UBI and all these other things. Do you think he

601
00:33:44,760 --> 00:33:47,880
Speaker 2: has grander ideas that he wants to pursue.

602
00:33:49,000 --> 00:33:53,760
Speaker 1: Well, obviously I can't speak to what's inside Sam's I

603
00:33:53,840 --> 00:33:58,000
Speaker 1: don't know the man's mind, but I mean past indicators

604
00:33:58,000 --> 00:34:01,160
Speaker 1: would suggest yes, Like I think he has proven pretty

605
00:34:01,160 --> 00:34:05,600
Speaker 1: consistently that he's someone who you know, is you know,

606
00:34:05,600 --> 00:34:08,239
Speaker 1: as much as he might focus on one project with

607
00:34:08,280 --> 00:34:10,759
Speaker 1: a lot of effort, like he is cooking things on

608
00:34:10,840 --> 00:34:13,000
Speaker 1: the side, Like this is a man. This is gonna

609
00:34:13,000 --> 00:34:15,160
Speaker 1: be an extended metaphor, but this is a man working

610
00:34:15,200 --> 00:34:17,239
Speaker 1: at a stove that has like six burners, not one.

611
00:34:17,320 --> 00:34:19,719
Speaker 1: And you know he we already know that.

612
00:34:20,680 --> 00:34:22,839
Speaker 2: What you say, sorry, he's got a big house.

613
00:34:23,840 --> 00:34:28,400
Speaker 1: He's got multiple houses. The uh, the you know, we

614
00:34:28,480 --> 00:34:32,319
Speaker 1: already know that. You know. In addition to running open AI,

615
00:34:33,080 --> 00:34:38,279
Speaker 1: he has funded and or helped prompt the founding of,

616
00:34:38,719 --> 00:34:41,560
Speaker 1: or has you know, been very involved in investing in

617
00:34:41,640 --> 00:34:45,239
Speaker 1: or supporting other startups that you know, are part of

618
00:34:45,280 --> 00:34:50,560
Speaker 1: this kind of ecosystem of businesses that are connected to

619
00:34:51,080 --> 00:34:53,760
Speaker 1: an AI future or might benefit in an AI future.

620
00:34:53,800 --> 00:34:57,080
Speaker 1: So for example, he Leon, which is a nuclear fusion

621
00:34:57,360 --> 00:34:59,680
Speaker 1: company which he has invested a ton of money into.

622
00:35:00,239 --> 00:35:02,160
Speaker 1: I think he has said publicly that you know, his

623
00:35:02,800 --> 00:35:05,960
Speaker 1: vision is that this is a potential way to provide

624
00:35:06,280 --> 00:35:11,400
Speaker 1: abundant energy that could then power the technology that we

625
00:35:11,440 --> 00:35:16,040
Speaker 1: need to you know, improve AI to the level that

626
00:35:16,080 --> 00:35:17,520
Speaker 1: we're hoping that it can get to, or that he's

627
00:35:17,520 --> 00:35:19,880
Speaker 1: hoping that it can get to At the same time.

628
00:35:20,520 --> 00:35:22,880
Speaker 1: You know, we've talked a little bit about universal basic income.

629
00:35:22,960 --> 00:35:26,080
Speaker 1: This has been something that Sam has been a proponent

630
00:35:26,160 --> 00:35:29,640
Speaker 1: of and an advocate of since at least twenty sixteen,

631
00:35:29,719 --> 00:35:32,560
Speaker 1: when he was running y Combinator, and they started a

632
00:35:32,840 --> 00:35:37,120
Speaker 1: side research project to study universal basic income by giving

633
00:35:39,280 --> 00:35:42,279
Speaker 1: cash payments to families in Oakland of I believe a

634
00:35:42,320 --> 00:35:46,320
Speaker 1: thousand dollars a month. That research project is still ongoing.

635
00:35:46,360 --> 00:35:50,319
Speaker 1: It's now moved away from y Combinator and is associated

636
00:35:50,880 --> 00:35:54,200
Speaker 1: with open Research, which is I believe funded by open Ai,

637
00:35:54,320 --> 00:35:56,360
Speaker 1: and so it has kind of moved with Sam to

638
00:35:56,440 --> 00:36:00,480
Speaker 1: his new role. And of course he also so co

639
00:36:00,640 --> 00:36:06,240
Speaker 1: founded this company called world Coin, which used these silver

640
00:36:06,880 --> 00:36:12,120
Speaker 1: orbs machines to scan to take pictures of your iris

641
00:36:12,160 --> 00:36:17,160
Speaker 1: and give everyone register every individual human as like a

642
00:36:17,239 --> 00:36:21,360
Speaker 1: unique human individual, and to create this eyeball registry in

643
00:36:21,480 --> 00:36:24,759
Speaker 1: which by which one could in the future distribute a

644
00:36:24,880 --> 00:36:28,720
Speaker 1: universal basic income. So he's funding these energy companies, He's

645
00:36:29,000 --> 00:36:32,480
Speaker 1: involved in these sort of the sort of crypto eyeball

646
00:36:32,520 --> 00:36:35,720
Speaker 1: registry project that will help distribute ebi in this future

647
00:36:35,719 --> 00:36:37,879
Speaker 1: that he's imagining, Like, I think it's safe to say

648
00:36:37,880 --> 00:36:41,560
Speaker 1: he's definitely thinking about things beyond just open AI for

649
00:36:41,719 --> 00:36:44,920
Speaker 1: the future and imagining like, Okay, well, if we have

650
00:36:45,000 --> 00:36:46,680
Speaker 1: this piece that's growing, what else would we need to

651
00:36:46,680 --> 00:36:49,359
Speaker 1: support it? And I'm sure there are other things he's

652
00:36:49,400 --> 00:36:51,600
Speaker 1: working on that we don't even know about, right, Like

653
00:36:51,600 --> 00:36:55,960
Speaker 1: I know he has also funded some like longevity bioscience

654
00:36:56,040 --> 00:36:59,439
Speaker 1: projects and things like that. He's I guarantee he's thinking

655
00:36:59,480 --> 00:37:01,200
Speaker 1: about stuff beyond what we know about.

656
00:37:03,160 --> 00:37:07,480
Speaker 2: Final question, why do you think the entire tech industry

657
00:37:07,480 --> 00:37:10,040
Speaker 2: has become so fascinated with AI? Do you think it's

658
00:37:10,239 --> 00:37:12,279
Speaker 2: just oldman or is it something more?

659
00:37:13,680 --> 00:37:18,080
Speaker 1: I do think chat Gipt started heating up this interest

660
00:37:18,120 --> 00:37:20,360
Speaker 1: that was already percolating a little bit in the tech industry.

661
00:37:20,760 --> 00:37:23,319
Speaker 1: But it does seem like something about chatchipt capture the

662
00:37:23,320 --> 00:37:27,360
Speaker 1: public imagination made people imagine very seriously for the first time,

663
00:37:28,200 --> 00:37:32,759
Speaker 1: how AI could affect their lives, their lives individually. It

664
00:37:32,880 --> 00:37:34,279
Speaker 1: used to be kind of this abstract thing that was

665
00:37:34,320 --> 00:37:36,920
Speaker 1: a little farther away, or maybe you understood that like

666
00:37:37,320 --> 00:37:40,880
Speaker 1: you were interacting with AI sometimes, like when you would

667
00:37:40,920 --> 00:37:46,080
Speaker 1: look at like flight price predictors or yeah, exactly. But

668
00:37:46,920 --> 00:37:48,759
Speaker 1: you know, I think as we you know, we talk

669
00:37:48,800 --> 00:37:51,400
Speaker 1: about this in episode three, but you know, chat chipet

670
00:37:51,600 --> 00:37:55,920
Speaker 1: wasn't even new technology. It was actually just a different

671
00:37:56,120 --> 00:38:00,000
Speaker 1: user interface on a model that already existed GPT three

672
00:38:00,040 --> 00:38:00,560
Speaker 1: point five.

673
00:38:01,160 --> 00:38:01,480
Speaker 3: And so.

674
00:38:03,040 --> 00:38:05,200
Speaker 1: To me, that actually speaks, I guess to the power

675
00:38:05,280 --> 00:38:09,440
Speaker 1: of like making a technology accessible to everyone and in

676
00:38:09,480 --> 00:38:11,480
Speaker 1: a way that was like easy to use and you know,

677
00:38:11,520 --> 00:38:13,879
Speaker 1: for better or worse. That kind of got a lot

678
00:38:13,920 --> 00:38:17,160
Speaker 1: of people in this like public momentum of people thinking

679
00:38:17,160 --> 00:38:21,640
Speaker 1: about AI feeling you know, just feeling like it had

680
00:38:22,400 --> 00:38:25,879
Speaker 1: rapidly increased its capabilities in a short period of time.

681
00:38:26,719 --> 00:38:33,120
Speaker 1: And yeah, something about that really captured not just you know,

682
00:38:33,239 --> 00:38:36,120
Speaker 1: the minds, but also the hearts of people and like

683
00:38:36,120 --> 00:38:39,040
Speaker 1: like getting them really thinking about like what could a

684
00:38:39,040 --> 00:38:41,480
Speaker 1: future like this look like. And I think while some

685
00:38:41,480 --> 00:38:44,120
Speaker 1: people were excited, a lot of people also reacted with fear,

686
00:38:44,200 --> 00:38:45,719
Speaker 1: right and like I think in the valley, like you

687
00:38:45,800 --> 00:38:49,960
Speaker 1: will hear a lot of people more openly discussing their

688
00:38:50,040 --> 00:38:55,480
Speaker 1: fears of uh, sort of like job loss or or

689
00:38:56,640 --> 00:38:58,880
Speaker 1: just like dramatic social change that might come about in

690
00:38:58,880 --> 00:39:02,200
Speaker 1: the next ten or twenty years. The feeling I get

691
00:39:02,239 --> 00:39:04,400
Speaker 1: in conversations that I have in and around San Francisco

692
00:39:04,480 --> 00:39:06,680
Speaker 1: is you know, even people who are pretty deep in

693
00:39:06,719 --> 00:39:11,759
Speaker 1: this technology are uncertain about whether it's going to be

694
00:39:11,800 --> 00:39:14,839
Speaker 1: overall good or bad. Like they're just uncertain of how

695
00:39:14,840 --> 00:39:17,480
Speaker 1: to look back on this time, like whether it will

696
00:39:17,520 --> 00:39:22,040
Speaker 1: have ended up being elite forward for humanity or something different.

697
00:39:34,520 --> 00:39:36,600
Speaker 2: Aortman has taken advantage of the fact that the tech

698
00:39:36,640 --> 00:39:40,560
Speaker 2: industry might not have any hypergrowth markets left, knowing that

699
00:39:40,640 --> 00:39:44,319
Speaker 2: chat GPT is much like Sam Altman, incredibly adept at

700
00:39:44,360 --> 00:39:48,279
Speaker 2: mimicking depth and experience by parroting the experiences of those

701
00:39:48,320 --> 00:39:52,560
Speaker 2: that have actually done things. Like Sam Altman, chat GPT

702
00:39:52,680 --> 00:39:55,960
Speaker 2: consumes information and feeds it back to the people using

703
00:39:56,000 --> 00:40:00,440
Speaker 2: it in a way that feels superficially satisfying, and it's

704
00:40:00,520 --> 00:40:03,480
Speaker 2: quite impressive to those who don't really care about creativity

705
00:40:03,560 --> 00:40:06,239
Speaker 2: or depth. And like I've said, it takes advantage of

706
00:40:06,280 --> 00:40:09,080
Speaker 2: the fact that the teche CoSystem has been dominated and

707
00:40:09,120 --> 00:40:13,960
Speaker 2: funded by people who don't really build tech. As I've

708
00:40:14,000 --> 00:40:18,720
Speaker 2: said before, generative AI things like chat GPT, anthropics Claude,

709
00:40:19,040 --> 00:40:22,000
Speaker 2: Microsoft's co Pilot, which is also powered by chat GBT.

710
00:40:22,560 --> 00:40:25,759
Speaker 2: It's not going to become the incredible supercomputer that Sam

711
00:40:25,800 --> 00:40:29,080
Speaker 2: Moortman is promising. It will not be a virtual brain

712
00:40:29,400 --> 00:40:32,480
Speaker 2: or imminently human like or a super smart person that

713
00:40:32,600 --> 00:40:36,600
Speaker 2: knows everything about you, because it is, at its deepest complexity,

714
00:40:36,960 --> 00:40:41,040
Speaker 2: a fundamentally different technology based on mathematics and the probabilistic

715
00:40:41,120 --> 00:40:44,160
Speaker 2: answer to what you have asked it, rather than anything

716
00:40:44,239 --> 00:40:48,520
Speaker 2: resembling how human beings think, or act or even know things.

717
00:40:48,719 --> 00:40:52,759
Speaker 2: Generative AI does not know anything. How can a thing

718
00:40:52,880 --> 00:40:56,480
Speaker 2: think when it doesn't know a anyone? I want to

719
00:40:56,520 --> 00:41:01,239
Speaker 2: ask bradlight cap Miramarati Sam Ortmann of these questions just

720
00:41:01,360 --> 00:41:06,120
Speaker 2: once hear what they fart out. No, a well CHATGBT

721
00:41:06,360 --> 00:41:10,560
Speaker 2: isn't inherently useless. Allman realizes that it's impossible to generate

722
00:41:10,600 --> 00:41:13,200
Speaker 2: the kind of funding and hype he needs based on

723
00:41:13,239 --> 00:41:16,719
Speaker 2: its actual achievements, and that to continue to accumulate power

724
00:41:16,719 --> 00:41:19,200
Speaker 2: and money, which is his only goal, he has the

725
00:41:19,239 --> 00:41:21,640
Speaker 2: speciously hype it, and he has to hype it to

726
00:41:21,719 --> 00:41:25,239
Speaker 2: wealthy and powerful people who also do not participate in

727
00:41:25,280 --> 00:41:30,319
Speaker 2: the creation of anything. And that's who he is. I've

728
00:41:30,360 --> 00:41:32,840
Speaker 2: been pretty mean about this guy, I really have, but

729
00:41:32,880 --> 00:41:36,640
Speaker 2: he does have a skill. He knows a mark, he

730
00:41:36,719 --> 00:41:39,520
Speaker 2: knows he knows how to say the right things and

731
00:41:39,560 --> 00:41:41,840
Speaker 2: get in the right rooms with the people who aren't

732
00:41:41,880 --> 00:41:45,480
Speaker 2: really touching the software or the hardware. He knows what

733
00:41:45,520 --> 00:41:47,719
Speaker 2: they need to hear. He knows what the vcs need

734
00:41:47,800 --> 00:41:53,000
Speaker 2: to hear. He knows quite aptly what this needs to

735
00:41:53,120 --> 00:41:56,080
Speaker 2: sound like. But if he had to say what chat

736
00:41:56,120 --> 00:41:59,279
Speaker 2: GBT does today, what would he say? Yeah, Yeah, it's

737
00:41:59,320 --> 00:42:01,319
Speaker 2: really good at a generating a bunch of TEGs that's

738
00:42:01,400 --> 00:42:04,319
Speaker 2: kind of shitty. Yeah, Sometimes it does math right and

739
00:42:04,360 --> 00:42:06,560
Speaker 2: sometimes it does it really wrong. Sometimes you ask it

740
00:42:06,600 --> 00:42:08,680
Speaker 2: to do. It can draw a picture, Hey, what do

741
00:42:08,719 --> 00:42:11,959
Speaker 2: you think of that? These are all things, by the way,

742
00:42:12,080 --> 00:42:13,799
Speaker 2: that if like a six year old told you'd be like, wow,

743
00:42:13,840 --> 00:42:15,960
Speaker 2: that's really impressive, or like a ten year old perhaps,

744
00:42:16,520 --> 00:42:20,759
Speaker 2: because that's a living being. Chat GPT does these things,

745
00:42:20,760 --> 00:42:22,799
Speaker 2: and it does it. I know it's cheesy to say,

746
00:42:22,840 --> 00:42:24,920
Speaker 2: but in a soulless way, but it really does that.

747
00:42:25,040 --> 00:42:27,239
Speaker 2: Because and the reason all of this, the writing and

748
00:42:27,280 --> 00:42:30,520
Speaker 2: the horrible video and the images, the reason it feels

749
00:42:30,560 --> 00:42:35,880
Speaker 2: so empty is because even the most manure adjacent press

750
00:42:35,920 --> 00:42:42,160
Speaker 2: release still has gone through someone's manure adjacent brain. Even

751
00:42:42,200 --> 00:42:46,000
Speaker 2: the most pallid empty copy you've read has gone through someone.

752
00:42:46,320 --> 00:42:49,200
Speaker 2: A person has put thought and intention in, even if

753
00:42:49,200 --> 00:42:53,280
Speaker 2: they're not great with the English language. What chat GPT

754
00:42:53,520 --> 00:42:56,880
Speaker 2: does is use math to generate the next thing, and

755
00:42:56,920 --> 00:43:00,359
Speaker 2: sometimes it gets it pretty right. But pretty right is

756
00:43:00,400 --> 00:43:04,760
Speaker 2: not enough to mimic human creation. But look at Sam Altman.

757
00:43:05,239 --> 00:43:08,200
Speaker 2: Look who he is. What has he created other than

758
00:43:08,200 --> 00:43:12,720
Speaker 2: wealth for him and other people? What about Sam Moltman

759
00:43:12,840 --> 00:43:17,840
Speaker 2: is particularly exciting? Well, he's been rich before and his

760
00:43:18,040 --> 00:43:21,680
Speaker 2: money made him even richer. That's pretty good. He was

761
00:43:21,760 --> 00:43:24,960
Speaker 2: at y Combinator. Don't ask too much about what happened there.

762
00:43:26,480 --> 00:43:30,280
Speaker 2: Just feels like sometimes Silicon Valley can't wipe its own ass.

763
00:43:30,800 --> 00:43:34,200
Speaker 2: It can't see when there's a wolf amongst the sheep.

764
00:43:34,440 --> 00:43:37,560
Speaker 2: It can't see when someone isn't really part of the

765
00:43:37,600 --> 00:43:41,040
Speaker 2: system other than finding new ways to manipulate and extract

766
00:43:41,120 --> 00:43:44,360
Speaker 2: value from him. And Sam Altman is a monster created

767
00:43:44,680 --> 00:43:47,880
Speaker 2: by Silicon Valley's sin, and their sin, by the way,

768
00:43:48,080 --> 00:43:52,040
Speaker 2: is empowering and elevating those who don't build software, which

769
00:43:52,120 --> 00:43:55,200
Speaker 2: in turn has led to the greater sin of allowing

770
00:43:55,239 --> 00:43:58,280
Speaker 2: the tech industry to drift away from fixing the problems

771
00:43:58,280 --> 00:44:02,960
Speaker 2: of actual human beings. Sam Altman's manipulative little power plays

772
00:44:02,960 --> 00:44:05,760
Speaker 2: have been so effective because so many of the power

773
00:44:05,760 --> 00:44:08,960
Speaker 2: players in venture capital and the public markets and even

774
00:44:09,040 --> 00:44:12,640
Speaker 2: tech companies are disconnected from the process of building things,

775
00:44:12,840 --> 00:44:16,200
Speaker 2: of building software and hardware, and that makes them incapable

776
00:44:16,320 --> 00:44:20,080
Speaker 2: or perhaps unwilling to understand that Sam Altman is leading

777
00:44:20,120 --> 00:44:23,759
Speaker 2: them to a deeply desolate place. And on some level,

778
00:44:23,760 --> 00:44:27,080
Speaker 2: it's kind of impressive how he succeeded in bending these

779
00:44:27,120 --> 00:44:29,920
Speaker 2: fools to his whims, to the point that executives like

780
00:44:29,960 --> 00:44:32,320
Speaker 2: sund up A Shai of Google are willing to break

781
00:44:32,600 --> 00:44:35,720
Speaker 2: Google Search in pursuit of this next big hype cycle

782
00:44:35,960 --> 00:44:40,400
Speaker 2: created by Sam Altman. He might not create anything, but

783
00:44:40,440 --> 00:44:44,799
Speaker 2: he's excellent at spotting market opportunities, even if these opportunities

784
00:44:44,800 --> 00:44:49,600
Speaker 2: involve him transparently lying about the technology he creates, all

785
00:44:49,640 --> 00:44:53,719
Speaker 2: while having his nasty little boosters further propagate these bullshit,

786
00:44:54,320 --> 00:44:57,680
Speaker 2: mostly because they don't know, or perhaps they don't care,

787
00:44:58,000 --> 00:45:01,560
Speaker 2: if Sam Morton's full of shit. It doesn't matter to them.

788
00:45:01,840 --> 00:45:04,520
Speaker 2: It doesn't matter that Google Search is still plagued with

789
00:45:04,600 --> 00:45:09,160
Speaker 2: nonsensical AI answers that sometimes steal other people's work, or

790
00:45:09,160 --> 00:45:13,919
Speaker 2: that AI in legal research has been proven to regularly hallucinate, which,

791
00:45:13,960 --> 00:45:16,280
Speaker 2: by the way, is a problem that's impossible to fix.

792
00:45:17,280 --> 00:45:20,560
Speaker 2: It's all happening because AI is the new thing that

793
00:45:20,600 --> 00:45:23,040
Speaker 2: can be sold to the markets. And it's all happening

794
00:45:23,120 --> 00:45:27,120
Speaker 2: because Sam Altman, intentionally or otherwise has created a totally

795
00:45:27,160 --> 00:45:30,840
Speaker 2: hollow hype cycle. And all of this is thanks to

796
00:45:30,880 --> 00:45:33,800
Speaker 2: Sam Altman and a tech industry that's lost its ability

797
00:45:33,840 --> 00:45:37,319
Speaker 2: to create things worthy of an actual hype cycle to

798
00:45:37,400 --> 00:45:40,879
Speaker 2: the point that this spacious, non technical manipulator can lead

799
00:45:40,920 --> 00:45:46,239
Speaker 2: it down this nasty, ugly offensive anti tech path. The

800
00:45:46,280 --> 00:45:49,640
Speaker 2: tech industry has spent years pissing off customers, with platforms

801
00:45:49,680 --> 00:45:53,319
Speaker 2: like Facebook and Google actively making their products worse in

802
00:45:53,360 --> 00:45:56,680
Speaker 2: the pursuit of perpetual growth and ashamedly turning their backs

803
00:45:56,800 --> 00:45:58,880
Speaker 2: on the people that made them rich and acting with

804
00:45:58,920 --> 00:46:02,840
Speaker 2: this horrifying contempt for their users. And I believe the

805
00:46:02,880 --> 00:46:05,439
Speaker 2: result will be that tech is going to face a

806
00:46:05,520 --> 00:46:09,640
Speaker 2: harsh reprimand from society. As I mentioned in the rock

807
00:46:09,680 --> 00:46:13,120
Speaker 2: com bubble, things that are already falling apart WHEB traffic

808
00:46:13,160 --> 00:46:17,320
Speaker 2: is already dropping. And what sucks is the people around

809
00:46:17,360 --> 00:46:20,920
Speaker 2: Sam Moltman should have been able to see this, even

810
00:46:21,000 --> 00:46:25,360
Speaker 2: putting aside his resume. I've listened to an alarming amount

811
00:46:25,360 --> 00:46:28,799
Speaker 2: of Sam Moreman talk. And I'm a public relations person,

812
00:46:28,840 --> 00:46:30,920
Speaker 2: Who the hell am I? I'm someone who's been around

813
00:46:30,960 --> 00:46:33,160
Speaker 2: a lot of people who make shit up. I've been

814
00:46:33,200 --> 00:46:35,560
Speaker 2: around a lot of people whose job it is to

815
00:46:35,680 --> 00:46:41,440
Speaker 2: kind of obfuscate things, and quite frankly, almost really obvious.

816
00:46:41,960 --> 00:46:43,920
Speaker 2: I'm not going to do any weird light to me

817
00:46:44,120 --> 00:46:47,640
Speaker 2: esque ways of proving he's lying. He just doesn't ever

818
00:46:47,680 --> 00:46:51,719
Speaker 2: get pushed into any depth. No one ever asks him

819
00:46:52,120 --> 00:46:56,000
Speaker 2: really technical questions or even just a question like, Hey, Sam,

820
00:46:56,160 --> 00:46:58,120
Speaker 2: did you work on any of the code at open

821
00:46:58,160 --> 00:47:01,279
Speaker 2: AIY what did you work on? Yeah? I know you

822
00:47:01,320 --> 00:47:04,560
Speaker 2: can't talk about the future, Sam, but how close are

823
00:47:04,560 --> 00:47:06,560
Speaker 2: we actually to AGI? And if he says, ah, a

824
00:47:06,560 --> 00:47:10,480
Speaker 2: few years, that's not specific enough, Sam, how about give

825
00:47:10,520 --> 00:47:15,640
Speaker 2: me a ballpark? And then when he lies again, you say, okay, Sam,

826
00:47:15,719 --> 00:47:20,040
Speaker 2: how do we get from generative AI to AGI? And

827
00:47:20,120 --> 00:47:22,760
Speaker 2: when he starts waffling, say no, no, no, be specific, Sam.

828
00:47:24,280 --> 00:47:26,839
Speaker 2: This is how you actually ask questions. And when you

829
00:47:26,920 --> 00:47:30,040
Speaker 2: say things like this, by the way, to technical founders,

830
00:47:30,400 --> 00:47:34,080
Speaker 2: they don't get worried. They don't offer skate. They may

831
00:47:34,080 --> 00:47:35,839
Speaker 2: say I can't talk about this duty of legal things,

832
00:47:35,840 --> 00:47:39,640
Speaker 2: which is fine, but they'll generally try and talk to you.

833
00:47:40,920 --> 00:47:44,640
Speaker 2: Listen to any interview with any other technical AI person,

834
00:47:46,200 --> 00:47:49,120
Speaker 2: Listen to them, and then listen to Sam Ortman. He's

835
00:47:49,200 --> 00:47:53,240
Speaker 2: full of it. It's so obvious. And one deeply unfair

836
00:47:53,320 --> 00:47:55,799
Speaker 2: thing with the value is there are people that get

837
00:47:55,840 --> 00:47:59,319
Speaker 2: held to these standards. Early stage startups generally do the

838
00:47:59,360 --> 00:48:02,120
Speaker 2: ones that aren't handed to people like Altman or Alexis

839
00:48:02,160 --> 00:48:05,080
Speaker 2: Ohanian have read it, or Paul Graham or read Hoffman.

840
00:48:06,000 --> 00:48:08,360
Speaker 2: They don't get those chances because they're not saying the

841
00:48:08,400 --> 00:48:12,200
Speaker 2: things that need to be said to the venture capitalists.

842
00:48:12,360 --> 00:48:16,080
Speaker 2: They're not in the circles. They're not doing the right

843
00:48:16,120 --> 00:48:19,239
Speaker 2: things because the right things are no longer the right

844
00:48:19,360 --> 00:48:23,319
Speaker 2: thing for the tech industry. And when all of this

845
00:48:23,440 --> 00:48:27,640
Speaker 2: falls apart, Sam Almond's going to be fine. When this

846
00:48:27,840 --> 00:48:31,480
Speaker 2: all collapses, he'll find something to blame it on market forces,

847
00:48:31,560 --> 00:48:36,000
Speaker 2: a lack of energy, breakthroughs, unfortunate economic things. All are

848
00:48:36,080 --> 00:48:39,040
Speaker 2: that nonsense, and he'll remain a billionaire, capable of doing

849
00:48:39,040 --> 00:48:42,280
Speaker 2: anything he wants. The people that are going to suffer

850
00:48:42,400 --> 00:48:45,480
Speaker 2: are the people working in Silicon Valley who aren't Sam Almon.

851
00:48:45,840 --> 00:48:48,480
Speaker 2: The people that did not get born with a silver

852
00:48:48,520 --> 00:48:51,680
Speaker 2: spoon in each hand and then handed further silver spoons

853
00:48:51,680 --> 00:48:55,360
Speaker 2: as they walk the streets of San Francisco. People that

854
00:48:55,440 --> 00:48:58,440
Speaker 2: don't live in nine and a half thousand square foot mansions.

855
00:48:59,480 --> 00:49:02,120
Speaker 2: The people trying to raise money who can't right now

856
00:49:02,160 --> 00:49:06,440
Speaker 2: because all the vcs are obsessed with AI. The people

857
00:49:06,520 --> 00:49:09,880
Speaker 2: that will get fired from public tech companies when a

858
00:49:10,000 --> 00:49:13,319
Speaker 2: depression hits, because the markets realize that the generative AI

859
00:49:13,440 --> 00:49:17,280
Speaker 2: boom was a bubble, when they realized that the most

860
00:49:17,320 --> 00:49:20,640
Speaker 2: famous people in tech have been making these promises for

861
00:49:20,800 --> 00:49:25,080
Speaker 2: nobody other than the markets. Well, the markets need you

862
00:49:25,120 --> 00:49:27,520
Speaker 2: to do something eventually, and I just don't think it's

863
00:49:27,560 --> 00:49:31,040
Speaker 2: going to happen. And I think that we need to

864
00:49:31,120 --> 00:49:34,040
Speaker 2: really think why was Sam Altman allowed to get to

865
00:49:34,080 --> 00:49:37,840
Speaker 2: this point? Why did so many people like Paul Graham,

866
00:49:38,120 --> 00:49:42,239
Speaker 2: like Reid Hoffman, like Brian Chesky, like Sachi Nadella. Back up,

867
00:49:42,440 --> 00:49:45,840
Speaker 2: it's obvious con artists who has acted like this forever.

868
00:49:47,360 --> 00:49:49,560
Speaker 2: And what sucks is I don't know if the value

869
00:49:49,600 --> 00:49:51,520
Speaker 2: is going to learn anything unless it's really bad, and

870
00:49:51,560 --> 00:49:53,200
Speaker 2: I don't want it to be. By the way, I

871
00:49:53,239 --> 00:49:55,399
Speaker 2: would love to be wrong. I would love for all

872
00:49:55,440 --> 00:49:57,920
Speaker 2: of this to just be like Sam Ortman's actually a genius.

873
00:49:58,400 --> 00:50:01,080
Speaker 2: Turns out the whole thing is no, it's not going

874
00:50:01,160 --> 00:50:05,440
Speaker 2: to happen. And I worry that there is no smooth

875
00:50:05,440 --> 00:50:07,239
Speaker 2: way out of this, that there is no way to

876
00:50:07,360 --> 00:50:12,960
Speaker 2: just casually integrate open Ai with Microsoft, because now there's

877
00:50:12,960 --> 00:50:16,680
Speaker 2: an antitrust thing going in with Microsoft and acquiring Inflection Ai,

878
00:50:16,800 --> 00:50:20,799
Speaker 2: another AI company, and that's the thing. It feels like

879
00:50:20,880 --> 00:50:25,560
Speaker 2: we are approaching a press apiece here, and the only

880
00:50:25,600 --> 00:50:28,680
Speaker 2: way to avoid it is for people to come clean,

881
00:50:28,719 --> 00:50:31,719
Speaker 2: which is never going to happen, or of course, for

882
00:50:31,800 --> 00:50:35,040
Speaker 2: Sam Wortman not to be lying, for AGI to actually

883
00:50:35,040 --> 00:50:36,839
Speaker 2: come out of open Ai. And by the way, it's

884
00:50:36,840 --> 00:50:39,080
Speaker 2: going to need to be in the next year. I

885
00:50:39,080 --> 00:50:42,560
Speaker 2: don't think they've got even three quarters left. I think

886
00:50:42,600 --> 00:50:47,359
Speaker 2: that once this falls apart, once the markets realize, oh shit,

887
00:50:47,520 --> 00:50:50,840
Speaker 2: this is not profitable, this is not sustainable, they're going

888
00:50:50,920 --> 00:50:54,040
Speaker 2: to walk away from it. When companies realize that Generative

889
00:50:54,080 --> 00:50:59,279
Speaker 2: AI it's given him a couple percent profit, maybe they're

890
00:50:59,320 --> 00:51:02,600
Speaker 2: going to be pissed because this is not a stock

891
00:51:02,719 --> 00:51:08,680
Speaker 2: rally worthy boondoggle. This is not going to be pretty

892
00:51:09,520 --> 00:51:12,279
Speaker 2: when things fall. Apart from for Nvidia, you're still over

893
00:51:12,280 --> 00:51:15,440
Speaker 2: one thousand dollars when those orders stop coming in quite

894
00:51:15,440 --> 00:51:18,080
Speaker 2: as fast. What do you think is going to happen

895
00:51:18,120 --> 00:51:22,880
Speaker 2: to tech stocks? Startups are already having trouble raising money,

896
00:51:23,239 --> 00:51:26,440
Speaker 2: and they're having trouble raising money because the people giving

897
00:51:26,440 --> 00:51:29,400
Speaker 2: out the money are too disconnected from the creation of

898
00:51:29,440 --> 00:51:33,080
Speaker 2: software and hardware. The only way to fix Silicon Valley

899
00:51:34,080 --> 00:51:37,640
Speaker 2: perhaps is an apocalypse. Perhaps is people like Sam Ortman

900
00:51:37,760 --> 00:51:40,040
Speaker 2: getting washed out. I don't want it to happen. I

901
00:51:40,120 --> 00:51:45,240
Speaker 2: really must be bloody clear. But maybe it won't be apocalyptic.

902
00:51:46,400 --> 00:51:49,160
Speaker 2: Maybe it would just be a brutal realignment. And maybe

903
00:51:49,200 --> 00:51:54,160
Speaker 2: Silicon Valley needs that realignment because this industry desperately needs

904
00:51:55,080 --> 00:51:57,920
Speaker 2: a big bathful of ice. I need to dunk the

905
00:51:58,040 --> 00:52:02,320
Speaker 2: head in it aggressively and wake the hell up. Venture

906
00:52:02,360 --> 00:52:05,840
Speaker 2: capital needs to put money back into real things. The

907
00:52:05,960 --> 00:52:09,360
Speaker 2: largest tech companies need to realign and build for sustainability,

908
00:52:09,520 --> 00:52:13,480
Speaker 2: so are not binging and purging staff with every boom,

909
00:52:13,719 --> 00:52:15,600
Speaker 2: And if we really are at the end of the

910
00:52:15,680 --> 00:52:19,960
Speaker 2: hypergrowth era, every tech company needs to be thinking profit

911
00:52:20,000 --> 00:52:23,240
Speaker 2: and sustainability again. And that's a better silicon valley, because

912
00:52:23,239 --> 00:52:26,200
Speaker 2: a better silicon valley builds things for people. It solves

913
00:52:26,239 --> 00:52:29,279
Speaker 2: real problems. It doesn't have to lie about what the

914
00:52:29,320 --> 00:52:31,399
Speaker 2: thing could do in the future so that it can

915
00:52:31,440 --> 00:52:34,680
Speaker 2: sell a thing today. And I realize that sounds like

916
00:52:34,719 --> 00:52:38,200
Speaker 2: the foundation of most venture capital. That's fine at the

917
00:52:38,239 --> 00:52:42,399
Speaker 2: seed stage, that's fine at this moonshot stage where your

918
00:52:42,440 --> 00:52:46,040
Speaker 2: early early days. It is not befitting the most famous

919
00:52:46,320 --> 00:52:50,200
Speaker 2: company in tech. It is not befitting a multi billionaire.

920
00:52:51,280 --> 00:52:54,279
Speaker 2: It is not befitting anyone, and it is insulting to

921
00:52:54,320 --> 00:52:57,520
Speaker 2: the people actually building things, both in and outside of technology.

922
00:52:58,000 --> 00:53:01,400
Speaker 2: The people I hear from after every episode, they are angry,

923
00:53:01,760 --> 00:53:04,480
Speaker 2: They are frustrated because there are good people in tech.

924
00:53:04,520 --> 00:53:06,440
Speaker 2: There are people building real things. There are people that

925
00:53:06,560 --> 00:53:10,319
Speaker 2: remember a time when the tech industry was exciting, when

926
00:53:10,440 --> 00:53:13,279
Speaker 2: people were talking about cool shit in the future, and

927
00:53:13,320 --> 00:53:17,080
Speaker 2: then they'd actually do it. Returning to that is better

928
00:53:17,120 --> 00:53:20,440
Speaker 2: for society and the tech industry. Just don't know when

929
00:53:20,480 --> 00:53:30,920
Speaker 2: it's gonna happen. Thank you for listening to Better Offline.

930
00:53:31,040 --> 00:53:33,480
Speaker 2: The editor and composer of the Better Offline theme song

931
00:53:33,520 --> 00:53:36,200
Speaker 2: is Mattasowski. You can check out more of his music

932
00:53:36,200 --> 00:53:39,839
Speaker 2: and audio projects at Mattasowski dot com m A T.

933
00:53:39,840 --> 00:53:40,440
Speaker 3: T O.

934
00:53:40,680 --> 00:53:44,920
Speaker 2: S O w Ski dot com. You can email me

935
00:53:44,960 --> 00:53:47,560
Speaker 2: at easy at better offline dot com or visit better

936
00:53:47,600 --> 00:53:50,040
Speaker 2: offline dot com to find more podcast links and of course,

937
00:53:50,080 --> 00:53:53,200
Speaker 2: my newsletter. I also really recommend you go to chat

938
00:53:53,200 --> 00:53:55,879
Speaker 2: dot Where's Youreed dot at to visit the discord, and

939
00:53:55,920 --> 00:53:58,640
Speaker 2: go to our slash Better Offline to check out our reddit.

940
00:53:59,400 --> 00:54:00,760
Speaker 2: Thank you so much much for listening.

941
00:54:01,560 --> 00:54:04,279
Speaker 3: Better Offline is a production of cool Zone Media. For

942
00:54:04,400 --> 00:54:08,440
Speaker 3: more from cool Zone Media, visit our website Coolzonemedia dot com,

943
00:54:08,520 --> 00:54:11,400
Speaker 3: or check us out on the iHeartRadio app, Apple Podcasts,

944
00:54:11,480 --> 00:54:12,960
Speaker 3: or wherever you get your podcasts.