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Speaker 1: Welcome.

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Speaker 2: It is Verdict with Center, Ted Cruz, Ben Ferguson with you,

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Speaker 2: and this is a special week in Review. We had

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Speaker 2: the awesome opportunity to sit down with Elon Musk at

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Speaker 2: the White House and we did it as a two

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Speaker 2: part series this week. Some of you may have missed it,

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Speaker 2: or you may want to share that with your family

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Speaker 2: and your friends. So if you would do us a favor,

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Speaker 2: because what Elon Musk had to say, we want.

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Speaker 3: Everyone to hear it.

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Speaker 2: It's a lot of info the media refuses to cover.

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Speaker 3: Now.

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Speaker 2: The good news is this interview went viral on x

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Speaker 2: But if you are on other social media platforms, please

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Speaker 2: share this podcast right now so that everyone can hear

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Speaker 2: what mus said about waste, fraud and abuse in our government.

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Speaker 2: He also had some amazing things to talk about when

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Speaker 2: it comes to colonizing Mars and the idea that may

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Speaker 2: actually become a reality.

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Speaker 1: So grab this and share it.

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Speaker 2: This is the entire interview, uninterrupted with Elon Musk at

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Speaker 2: the White House.

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Speaker 4: Well, we're in the White House right right now, and

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Speaker 4: we're here with my friend Elon Musk, who really has

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Speaker 4: not been doing much of anything, has not made any news.

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Speaker 4: Is and nobody has noticed. Yeah, the impact.

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Speaker 1: Welcome elon, thank you, Holy crap ah, yes wow. Let

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Speaker 1: me just say, never a dull moment. Never a dull moment.

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Speaker 4: The first fifty days the president has spent in office

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Speaker 4: over the top, and the first fifty days you've spent.

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Speaker 4: I don't think there's ever been anyone to have an

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Speaker 4: impact the way you have.

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Speaker 3: At the beginning.

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Speaker 1: Let me start with a question.

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Speaker 4: You know a lot about which was worse the mess

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Speaker 4: you found at Twitter or the mess you found in

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Speaker 4: the federal government.

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Speaker 3: Well, it's hard to compete with the federal government.

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Speaker 4: What's surprised you about the federal government? I assume you

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Speaker 4: came in and assumed it was bad. Is it worse

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Speaker 4: than you expected?

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Speaker 3: It is worse than I expected. But on the plus side,

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Speaker 3: that means there's more opportunity for improvement. So look, if

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Speaker 3: you look on the bright side, there's actually a lot

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Speaker 3: of opportunity for improvement in federal goverment expenditures because it's

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Speaker 3: so bad. If it was a well run ship, it

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Speaker 3: would be very difficult to improve. So like, but so

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Speaker 3: now it's like, people say, well, how how do you

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Speaker 3: figure out how to save money in the federal government. Well,

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Speaker 3: it's like being in a room where the walls, the roof,

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Speaker 3: and the floor are old targets any direction. Yeah, and

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Speaker 3: you're your kindness. Wow, yeah, I'm sure you would agree.

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Speaker 1: So a lot of folks have talked about like like.

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Speaker 3: You can't right, this is going to any direction.

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Speaker 1: A lot of the crazy expenditures, things like like two

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Speaker 1: million bucks for sex change surgeries in Guatemala, an essential

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Speaker 1: you know, transgendered mice, and and sesame street in Iraq,

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Speaker 1: A lot of that has gotten the tention. But some

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Speaker 1: of the stuff you've told me about, like tell us

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Speaker 1: about computer licenses and government agencies.

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Speaker 3: Yeah, so most of what do just finding you don't

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Speaker 3: need to shock comes. It's very obvious, basic stuff. So

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Speaker 3: it in every govert department. I say every because we've

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Speaker 3: not yet found a single exception. There are far too

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Speaker 3: many software licenses and media subscriptions, meaning many more software

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Speaker 3: licenses and media subscriptions than there are humans in the department.

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Speaker 4: Like you were saying, like an agency with fifteen thousand

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Speaker 4: people might have thirty thousand licenses. Yes, and even of

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Speaker 4: the fifteen thousand employees, a good chunk of them hadn't

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Speaker 4: used the license had never logged on or used the application.

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Speaker 3: Yes, we found entire situations of software licenses or media

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Speaker 3: subscriptions where there were zero logins.

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Speaker 1: So it had and yet we were paying for it.

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Speaker 3: Yes, the government's paying for thousands of licenses of software

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Speaker 3: or media subscriptions and no one had ever logged in

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Speaker 3: even once.

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Speaker 1: Or credit cards. You found the same thing. With government

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Speaker 1: credit cards.

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Speaker 3: We found that there are twice as many credit cards

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Speaker 3: as there are humans. And I still don't have a

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Speaker 3: good explanation for why this is the case. And these

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Speaker 3: are ten thousand dollar limit cards, so it's a lot

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Speaker 3: of money.

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Speaker 2: Is it incompetent that you're finding or is this like

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Speaker 2: the biggest money wandering scheme in the history of the

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Speaker 2: world that you're finding.

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Speaker 3: Okay, I think it's mostly If you say, look, what's

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Speaker 3: the waste to fraud ratio, Yeah, in my opinion, it's

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Speaker 3: it's like eighty percent wist twenty percent fraud. But you

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Speaker 3: do have these sort of gray areas. For example, example

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Speaker 3: be so uh, we saw a lot of payments going

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Speaker 3: out of treasury that had no payment code and no

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Speaker 3: explanation for the payment. And then we're we're we're we're

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Speaker 3: trying to figure out what that payment is and we'd

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Speaker 3: see that, Okay, that contract was supposed to be shut off,

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Speaker 3: but but someone forgot to shut off that that contract

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Speaker 3: and so the company kept getting money. Wow. Now is

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Speaker 3: that waste or fraud? Both both? Yeah, you're not supposed

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Speaker 3: to get you're not supposed to get it, but you

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Speaker 3: but the the government sent it to you, and nobody

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Speaker 3: from the government asked for it back. Take for example,

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Speaker 3: the one the one point nine billion dollars given to

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Speaker 3: Stacy Abrams.

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Speaker 1: Yeah, fake ng O, utter insanity.

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Speaker 3: Explain the story.

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Speaker 1: That's that's just corrupt. I think that's paying off cronies

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Speaker 1: at that point.

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Speaker 3: Yeah.

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Speaker 1: Yeah.

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Speaker 4: And by the way, she knew, like when you get

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Speaker 4: two billion dollars, you don't miss that.

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Speaker 1: That's not on accident.

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Speaker 3: That's allegedly it was for like, uh, you know, environmentally

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Speaker 3: friendly appliances or something. And they've given like like a

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Speaker 3: hundred appliances so far for two billion dollars. It's very

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Speaker 3: expensive toast that's fridge, it's nice. Is it's just obviously

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Speaker 3: one of the biggest scam fordoles we've uncovered, which is

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Speaker 3: really crazy, is uh? Is that is that the government

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Speaker 3: can give money to a so called nonprofit with with

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Speaker 3: very few controls, and then that and there's there's no

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Speaker 3: auditing subsequently of that nonprofit, so there's no So this

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Speaker 3: is where with the you know, one point nine billion

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Speaker 3: of Stacey Abrams, who's who's that they didn't give themselves

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Speaker 3: extremely lavished like insane salaries, expense everything yep, to the

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Speaker 3: to the nonprofit, you know, buy jets and homes and

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Speaker 3: all sorts of.

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Speaker 1: Things, live like kings and queens. Yes on the taxpayer done.

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Speaker 3: Correct. You mentioned this is happening at scale. It's not

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Speaker 3: just one or two. We're seeing this everywhere.

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Speaker 4: Now, one of the things you told me about is

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Speaker 4: at least what you call say, magic money computers. Well,

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Speaker 4: so tell us about it, because I've never heard of

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Speaker 4: that until you brought that up.

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Speaker 3: Okay, So you may think that these the government computers

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Speaker 3: like all talk to each other, they synchronize, they add

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Speaker 3: up what funds are going somewhere, and it's you know,

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Speaker 3: it's coherent that that that the you know, there's and

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Speaker 3: that and that the numbers, for example, that you're presented

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Speaker 3: as a senator are actually the real numbers. And one

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Speaker 3: would think we would think they're not okay. I mean,

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Speaker 3: they're not totally wrong, but they're probably off by five

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Speaker 3: percent or ten percent in some cases. So I call

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Speaker 3: it magic money computer. Any computer which can just make

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Speaker 3: money out of thin air best magic money.

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Speaker 1: So how does that work?

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Speaker 3: It just issues payments.

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Speaker 4: And you said something like eleven of these computers a

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Speaker 4: treasury that are that are sending out trillions in payments.

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Speaker 3: They're mostly a treasury. Some are with the sum at HHS,

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Speaker 3: some that there's one as one or two it states

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Speaker 3: there's summit at DoD. I think we found now fourteen

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Speaker 3: magic money computers. Gene, Okay, they just send money out

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Speaker 3: of nothing.

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Speaker 4: You have an ability to see where leverage points are

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Speaker 4: and how things actually happen. So I remember back I

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Speaker 4: think it was September October of this year, before the election.

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Speaker 4: We didn't know who was going to win, and I

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Speaker 4: was at your house in Austin. We were talking about it,

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Speaker 4: and you said, you said, look, I don't want a

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Speaker 4: job in Washington, and you said, all I want is

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Speaker 4: the log in for every computer. And I remember thinking

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Speaker 4: at the time that sounded kind of weird, like I

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Speaker 4: just didn't get it. And I have to say what's

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Speaker 4: interesting on this. If I would have thought like, okay,

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Speaker 4: how do you reform government? Like sort of the traditional

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Speaker 4: way to think about it is, okay, give me an

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Speaker 4: orc chart, let me sit down with the people who

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Speaker 4: are running agencies. And what you saw immediately is to

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Speaker 4: understand what's really going on, get to the payment systems,

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Speaker 4: get to the computers. Yeah, Like, why is getting to

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Speaker 4: the computers so critical to understanding what's actually happening?

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Speaker 3: Well, the government is run by computers. So you've got

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Speaker 3: essentially several hundred computers that effectively run the government. And

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Speaker 3: if you want to know, did you know that? Then no? Like, yeah,

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Speaker 3: so when somebody, like even when the president issues an

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Speaker 3: executive order, that's going to go through a whole bunch

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Speaker 3: of people until ultimately it is implemented at a computer somewhere.

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Speaker 3: And if you want to know what the situation is

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Speaker 3: with the accounting and you're trying to reconcile accounting and

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Speaker 3: get rid of waste and fraud, you must be able

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Speaker 3: to analyze the computer databases. Otherwise you can't figure it

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Speaker 3: out because all you're doing is asking a human who

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Speaker 3: will then ask another human, ask another human, and finally

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Speaker 3: usually ask some contractor will ask another contractor to your

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Speaker 3: query under computer. Wow, that's how it actually works. So

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Speaker 3: it's many layers D So the only way to reconcile

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Speaker 3: the databases and get rid of waste and fraud is

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Speaker 3: to to actually look at the computers and see what's

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Speaker 3: going on. So that's what I call it. That's like,

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Speaker 3: that's why when I sort of cryptically referred to reprogramming

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Speaker 3: the matrix. You have to understand what's going on the computers.

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Speaker 3: You have to reconcile the computer databases in order to

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Speaker 3: identify the waste and fraud.

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Speaker 4: I don't know that there was anyone in Congress who understood,

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Speaker 4: certainly myself included, who understood the leverage that.

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Speaker 1: Comes from the computer and the data.

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Speaker 4: In particular, that Congress would think about give me a

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Speaker 4: report on what your expenditures are rather than actually getting

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Speaker 4: into the pipes. And I think that has been fascinating

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Speaker 4: that it's let you uncover a bunch of crap that

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Speaker 4: just nobody knew.

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Speaker 3: Yes, I mean in order for money to go to

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Speaker 3: a van account. It's it's not like we're sending truckloads

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Speaker 3: of cash all over the place where it's a we're

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Speaker 3: wiring money. Right, we're sending money through the ACH system

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Speaker 3: or through the Swift system. So in order for money

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Speaker 3: to flow, it's going to flow electronically. So that's that's

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Speaker 3: what you need to look at. You need to look

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Speaker 3: at the actual electronic money flows.

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Speaker 4: And Tesla and all your companies, you have accounting and

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Speaker 4: you have every expenditure. You have it coded for what

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Speaker 4: it's going for. Federal government doesn't work that way. They

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Speaker 4: don't code what the money is going for.

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Speaker 3: They do know, but they didn't. They didn't.

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Speaker 4: And like one of the things that that you told me,

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Speaker 4: you said, if any company kept its books the way

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Speaker 4: the federal government does, they'd arrest the officers and put

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Speaker 4: them in jail.

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Speaker 3: Yes, if it was a poly company would be dealisted immediately,

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Speaker 3: it would fail, it's ordered, and the officers of the

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Speaker 3: company would be imprisoned. That's level of enough easiness in

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Speaker 3: the middle. Unfortunately, it's deliberately or do you think this

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Speaker 3: is in competence again, it's eighty percent. It's eighty percent

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Speaker 3: incompetence or in twenty percent malice.

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Speaker 2: If you look at DOGE now and you look at

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Speaker 2: the government and what you're finding, what percentage have you

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Speaker 2: guys even gotten to and how much of it is

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Speaker 2: Mars where you haven't even gotten there yet because there's

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Speaker 2: so much you're finding out here. I mean, how many

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Speaker 2: you seem like a timeline guy when you say all

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Speaker 2: I want to get in there and get all these

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Speaker 2: you know, numbers and things. How far are we from

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Speaker 2: the end game where you've seen it all, been able

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Speaker 2: to process it all and fix it.

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Speaker 3: I mean are we years away? Months away? Not yours?

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Speaker 3: I mean recently confident that we'll be able to get

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Speaker 3: a trillion dollars of waste and forward opt and that

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Speaker 3: meaning that it will have what we'll have a net

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Speaker 3: savings in f I twenty six, which thoughts in October

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Speaker 3: obviously of a trillion dollars provider were allowed to We're

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Speaker 3: allowed to continue and our progress is not impeded. And

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Speaker 3: we're very public about what we do.

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Speaker 1: Yeah, put it on.

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Speaker 3: The website about how we could be more transparent. Literally

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Speaker 3: everything action we do, smaller, large, we put on the

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Speaker 3: dose dot dot gov website and we post on the

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Speaker 3: x handle. And when people complain about it and they say, oh,

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Speaker 3: you're doing something costumes, I'm like, well, which of these costs?

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Speaker 1: Daylight everyone knows exactly what you're doing.

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Speaker 3: Extreme transparent. Yeah, I don't think it's anything's been this

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Speaker 3: transparent ever.

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Speaker 4: So five years ago you were a hero to the left, cool,

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Speaker 4: you had electric cars, you had space, And in five

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Speaker 4: years you've got.

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Speaker 3: To go to a party in Hollywood and not get

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Speaker 3: doddy looks. In fact, yeah, and now you might not

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Speaker 3: even get invited. It's invited, but I don't know if

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Speaker 3: I need to go.

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Speaker 4: And I don't think it's an exaggeration to say today,

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Speaker 4: after Donald Trump, the left hates you more than a

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Speaker 4: person on earth.

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Speaker 3: Yes, I appear to be number two. I mean, if

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Speaker 3: you're judged by the various signs.

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Speaker 1: They estrangements, it's Trump arrangement syndrome and Elon de arrangement syndrome.

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Speaker 1: How is that for you?

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Speaker 4: That's a little bit of whiplash of going from being

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Speaker 4: like mister cool to the devil incarnate in just a

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Speaker 4: couple of years. Is that is that kind of weird

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Speaker 4: to experience that transformation?

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Speaker 3: Yes?

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Speaker 1: Why do they hate you so much?

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Speaker 3: Well, because we're we're clearly over the target. If those

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Speaker 3: was ineffective, if we were not actually getting rid of

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Speaker 3: a bunch of wasting forward and a bunch of that.

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Speaker 3: For I mean, the ford we're seeing is overwhelmingly on

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Speaker 3: the on the left. I mean it's not zero on

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Speaker 3: the right, but these angos are almost all left wing

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Speaker 3: NGOs that are being funded for example. Yep. So they

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Speaker 3: hate me because Dog is being effective and Dog is

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Speaker 3: getting rid of a lot of waste. For that, they

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Speaker 3: were that people and left were taking advantage of that.

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Speaker 3: That's that's that's where it comes out to. And and

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Speaker 3: the single biggest thing that they're that they're worried about

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Speaker 3: is that Dogs is going to turn off fraudulent payments

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Speaker 3: of entitlements. I mean everything from Social Security, medicare, uh

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Speaker 3: you know, unemployment, disability, smallpers administ registration loans, turn them

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Speaker 3: off to illegals. This is that flux of the matter.

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Speaker 3: Ye okay, this is this is the this is the

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Speaker 3: thing that why they really hit my guts and want

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Speaker 3: me to die.

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Speaker 4: And do you think that's billions? Hundreds of billions? What

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Speaker 4: do you think the scale is of that?

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Speaker 3: I think across the country it's it's in the it's well,

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Speaker 3: not of one hundred billion, maybe two hundred million. So uh,

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Speaker 3: by by using entitlements fraud the Democrats have been able

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Speaker 3: to attract and retain vast numbers of illegal immigrants.

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Speaker 1: And buy voters and and buy.

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Speaker 3: Voters exactly the basically bring in ten twenty million people

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Speaker 3: who are beholden to the Democrats for governor handouts and

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Speaker 3: will vote overwhelming the Democrats. Has been demonstrated in California.

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Speaker 3: This is it's an election strategy. Yes, it's powered, Yes,

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Speaker 3: and it doesn't take much to turn the swing states blue.

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Speaker 3: I mean off in a swing state yet be won

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Speaker 3: by ten twenty thousand votes. Sure, so the DAMS can

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Speaker 3: bring in two hundred thousand illegals and over time get

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Speaker 3: them legalized, not counting any cheating that takes place, because

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Speaker 3: there is some cheating, but even without cheating, if you bake,

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Speaker 3: if you if you bring in illegals that are ten

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Speaker 3: x the voted differential in a swing state, it will

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Speaker 3: no longer be a swing state, right, and the DAMS

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Speaker 3: will win all the swing states just a matter of time,

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Speaker 3: and America will be permanent deep blue socialist state. At

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Speaker 3: the House, the Senate, YEP, the Presidency, and the Supreme

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Speaker 3: Court will all go hardcore down. They will then further

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Speaker 3: cement that by bringing even more aliens so you can't

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Speaker 3: vote your way out of it. Their objement is to

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Speaker 3: make it one party socialist state, and it will be

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Speaker 3: much worse than California, because at least California is mitigated

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Speaker 3: by the fact that someone can leave California.

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Speaker 1: You can go to Texas.

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Speaker 3: Yeah, exactly, So you're gonna make everywhere California but worse.

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Speaker 4: By the way, the middle of the pandemic, I spent

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Speaker 4: forty five minutes on the phone with Elon.

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Speaker 1: He was still in California.

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Speaker 4: I was walking my dog's snowflake and trying to convince

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Speaker 4: you come to Texas. The commis in California can't stand you.

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Speaker 4: We love you, we want you here, and you didn't

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Speaker 4: quite go then, but you went not that long afterwards.

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Speaker 3: I mean, the COVID actions almost killed Tesla because they

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Speaker 3: let every other auto plant in the country was allowed

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Speaker 3: to open, but ours, which was in California, was not

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Speaker 3: a lot to open. Wow. Wow, So they almost killed Tesla.

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Speaker 4: So as a personal matter, you do you ever regret it?

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Speaker 4: Like five years ago you go to the OSCARS and

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Speaker 4: mister cool and now you're you've got death threats every day,

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Speaker 4: Like do you well?

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Speaker 3: These days the OSCARS are boring. I wouldn't want to go.

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Speaker 1: God bless the movies they nominate.

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Speaker 4: No one on earth has ever seen like, like, could

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Speaker 4: they actually nominate a movie that human beings go watch?

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Speaker 3: I mean, how many great movies have come out in

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Speaker 3: the last several years.

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Speaker 1: Very few, depressingly few.

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Speaker 3: Yeah, very few. Last Oscars came and went I didn't

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Speaker 3: watch it. There's nothing to see.

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Speaker 4: I was sad that Gene Hackman just passed away because

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Speaker 4: Unforgiven was spectacular, but that was a long time ago.

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Speaker 3: Forgiven came out.

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Speaker 2: You've mentioned today here and before about the possibility of

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Speaker 2: someone wanting.

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Speaker 3: To take you out, dealing with the death threats we see.

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Speaker 3: It's not in my imagination. You could just look on

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Speaker 3: social media. Yeah, but like is it because very clear?

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Speaker 1: Yeah, And look I'm I'm very familiar with it.

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Speaker 3: And they've got science. They are people with science and demonstrations, uh,

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Speaker 3: saying that I need to die.

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Speaker 4: Do you think are these just why jobs? Or do

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Speaker 4: you think there are foreign sane people? Do you think

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Speaker 4: there are foreign entities behind this? Do you think they're

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Speaker 4: domestic entities behind the threats? And also the attacks to

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Speaker 4: Twitter are not Twitter, but Tesla, I mean you know,

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Speaker 4: you're getting Tesla's charging stations lit on fire. Do you

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Speaker 4: think that's organized and paid for?

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Speaker 3: Yes, at least some of it is organized and paid

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Speaker 3: for I think by domestic you know, basically left wing

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Speaker 3: organizations in America funded by left wing billionaires. Essentially, is

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Speaker 3: it like Act Blue or what Act Blue is one

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Speaker 3: of them? You know Arabella, you know the classic it's

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Speaker 3: funded by the you know, the blue basically the left

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Speaker 3: wing and g O cabal.

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Speaker 2: How big of a threats is to like what you

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Speaker 2: build at Tesla? I mean, I remember when Tesla's came out,

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Speaker 2: it was people that they didn't want to have gas cars.

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Speaker 2: A lot of it was environmental reasons. I jokingly said,

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Speaker 2: I was like, I'm a Texas guy, I'm always going

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Speaker 2: to have something that burns gas. My kids now, all

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Speaker 2: three of my boys think that that Tesla's are awesome.

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Speaker 2: The cyber truck is the car they want their dad

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Speaker 2: to buy, which I laugh because I never could have

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Speaker 2: imagined that five years ago.

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Speaker 3: And now I'm looking at We're worth.

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Speaker 4: The White House in the President's Tesla sparks. Yeah, I mean,

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Speaker 4: which is the fullest dand but I mean you've you've

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Speaker 4: changed a generation.

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Speaker 2: When you look at my kids are six and eight

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Speaker 2: and they're going Dad buy a cyber truck, and I'm

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Speaker 2: considering it. That's a that's a full circle in a

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Speaker 2: weird way.

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Speaker 3: Yeah. Well, I do have the story that the most

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Speaker 3: errantating outcome is the most likely. So yeah, it seems

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Speaker 3: often to be true. I like, what, uh, what twistal

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Speaker 3: turn of fate? Uh? Well, I would the highest ratings

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Speaker 3: if this was if we're a TV show, what twistal

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Speaker 3: turn of fate would generate the highest ratings that there's

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Speaker 3: a good chance that happens.

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Speaker 4: Well, I will say if if Act Blue and Arabella

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Speaker 4: Network was a huge scam, next level, do you think

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Speaker 4: it's foreign money? Chinese money? Where do you think the

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Speaker 4: money in Act Blue is coming from? How do you

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Speaker 4: figure that out?

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Speaker 3: Well, it's not coming from from a whole bunch of

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Speaker 3: from a ground swell of public support, because when individual

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Speaker 3: donors looked at an Act Blue, they a bunually turned

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Speaker 3: out to be like diehard Republicans, people have never given

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Speaker 3: money in their life. So you're going to track down

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Speaker 3: a bunch of these where it says, oh I gave

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Speaker 3: sixteen thousand dollars and they're like, I didn't give sixteen

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Speaker 3: thousand dollars. We're talking about. Well, if those whole con

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Speaker 3: friends of mine, if I found themselves on the Act

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Speaker 3: Blue List the like.

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Speaker 4: So that's if it can actually be shown that they

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Speaker 4: are funding firebombing of Tesla charging stations, that's objectively a

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Speaker 4: criminal act. That that is funding terrorist activity, and the

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Speaker 4: statutes make clear that an incendiary device qualifies.

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Speaker 3: So that down is a terrorist activity.

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Speaker 4: Let me ask AI in ten years, how is life

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Speaker 4: going to be different because of AI for just a

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Speaker 4: normal person?

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Speaker 3: Well, ten years is a long time. In ten years,

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Speaker 3: probably AI could do anything better than a human can cognitively,

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Speaker 3: probably almost. I think in ten years, based on the

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Speaker 3: cart rate of improvement, AI will be smarter than the

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Speaker 3: smartest human.

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Speaker 1: Yeah.

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Speaker 3: Yeah. There will also be a massive number of robots,

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Speaker 3: so humanoid robots.

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Speaker 4: By the way, I got to ask, how come your

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Speaker 4: robots look so much like the creepy robots for my robot?

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Speaker 1: Was that intentional or.

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Speaker 3: Just I was hoping he's gonna say, yeah, just to

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Speaker 3: mess with you, it's not meant to look like any

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Speaker 3: prior robot, and we'll iterate the design and you'll be

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Speaker 3: able to have a lot of the robot parts are cosmetic.

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Speaker 3: You'll be able to switch out the kind of snap

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Speaker 3: on cosmetic parts of the robot make it look like

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Speaker 3: something else if you lying so. There'll be ultimately billions

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Speaker 3: of humanoid robots all costs will be self driving in

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Speaker 3: ten years. In ten years, probably ninety percent of miles

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Speaker 3: driven will be autonomous. Huh wow that fast. Yeah. In

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Speaker 3: five years, probably fifty percent of miles will driven will

441
00:22:12,160 --> 00:22:12,720
Speaker 3: be autonomous.

442
00:22:12,760 --> 00:22:15,640
Speaker 4: Now, if AI will be smarter than any persons, how

443
00:22:15,680 --> 00:22:19,920
Speaker 4: many jobs go away because of that? And what do

444
00:22:20,040 --> 00:22:22,159
Speaker 4: people do if you've got billions of people that are

445
00:22:22,160 --> 00:22:24,400
Speaker 4: losing their jobs like that, A lot of people are

446
00:22:24,640 --> 00:22:26,080
Speaker 4: understandably freaked out about that.

447
00:22:26,480 --> 00:22:32,520
Speaker 3: Well, goods and services will become close to free. So

448
00:22:33,200 --> 00:22:35,040
Speaker 3: it's not as though people will be wanting in terms

449
00:22:35,080 --> 00:22:35,960
Speaker 3: of goods and services.

450
00:22:37,200 --> 00:22:37,919
Speaker 1: So why is that?

451
00:22:37,960 --> 00:22:38,400
Speaker 3: What?

452
00:22:38,440 --> 00:22:40,960
Speaker 4: Why are goods and services free in an AI world

453
00:22:41,480 --> 00:22:42,360
Speaker 4: or close to free?

454
00:22:42,680 --> 00:22:45,600
Speaker 3: Well, you have I don't know, call it tens of

455
00:22:45,600 --> 00:22:50,119
Speaker 3: billions of robots. They will they will make you anything

456
00:22:50,280 --> 00:22:54,600
Speaker 3: or provide any service you want for basically next to nothing.

457
00:22:56,600 --> 00:22:59,359
Speaker 3: It's it's not that people will be will have a

458
00:22:59,359 --> 00:23:01,480
Speaker 3: lower standable I mean, they'll have actually much higher standard

459
00:23:01,520 --> 00:23:06,359
Speaker 3: of living. But the challenge will be fulfillment. How do

460
00:23:06,400 --> 00:23:08,760
Speaker 3: you drive fulfillment and meeting in life?

461
00:23:09,320 --> 00:23:14,720
Speaker 4: Is Skynet real? Like you get the apocalyptic visions of AI?

462
00:23:15,680 --> 00:23:21,280
Speaker 4: How real is the prospect of killer robots annihilating humanity?

463
00:23:21,800 --> 00:23:23,439
Speaker 3: Likely? Maybe ten percent?

464
00:23:23,960 --> 00:23:24,879
Speaker 1: On what timeframe?

465
00:23:25,359 --> 00:23:27,480
Speaker 3: Fat ten years so soon?

466
00:23:27,880 --> 00:23:30,560
Speaker 1: Like you you see a world where that's possible.

467
00:23:31,400 --> 00:23:32,879
Speaker 3: Yeah, But I mean you can look at it like

468
00:23:32,920 --> 00:23:37,520
Speaker 3: the glasses eighty ninety percent full, meaning like eighty percent

469
00:23:37,800 --> 00:23:41,200
Speaker 3: likely will have extreme prosperity for all.

470
00:23:41,720 --> 00:23:44,119
Speaker 4: Now, I guess my view, we're in a race to

471
00:23:44,560 --> 00:23:47,480
Speaker 4: win AI. We're in a race with China, and my

472
00:23:47,600 --> 00:23:49,440
Speaker 4: view is if they're going to be killer robots, I'd

473
00:23:49,480 --> 00:23:53,679
Speaker 4: rather they be American killer robots than Chinese. How likely

474
00:23:54,359 --> 00:23:56,680
Speaker 4: are we winning right now? Is America winning right now?

475
00:23:56,720 --> 00:23:59,000
Speaker 4: And how likely is America to win the race for

476
00:23:59,080 --> 00:24:01,200
Speaker 4: AI v to be China or anyone else?

477
00:24:01,640 --> 00:24:03,880
Speaker 3: Well the next few years, I think America is likely

478
00:24:03,920 --> 00:24:06,800
Speaker 3: to win. Then it will be a function of who

479
00:24:06,800 --> 00:24:11,919
Speaker 3: controls the AI chip fabrication, if the factories that make

480
00:24:11,920 --> 00:24:14,720
Speaker 3: the AI chifs who controls them, If they are controlled,

481
00:24:15,280 --> 00:24:17,120
Speaker 3: if more of them will controlled by China than China

482
00:24:17,119 --> 00:24:17,639
Speaker 3: will win.

483
00:24:18,080 --> 00:24:20,720
Speaker 4: More of the factories that are making the AI chips.

484
00:24:20,960 --> 00:24:23,719
Speaker 4: You think that will determine it? Yes, And how are

485
00:24:23,760 --> 00:24:25,600
Speaker 4: we doing versus China on that front?

486
00:24:26,200 --> 00:24:31,920
Speaker 3: Well, right now, almost all the advanced AI chip factories

487
00:24:31,920 --> 00:24:35,360
Speaker 3: they call them babs are in Taiwan.

488
00:24:35,560 --> 00:24:38,600
Speaker 1: And what if China invaded one miles away from what

489
00:24:38,680 --> 00:24:39,640
Speaker 1: happens if China.

490
00:24:39,920 --> 00:24:43,080
Speaker 4: China invades Taiwan, what happens to the world.

491
00:24:43,400 --> 00:24:45,879
Speaker 3: Well, if they were to invade in the nea term,

492
00:24:47,040 --> 00:24:49,800
Speaker 3: the world would be cut off from advanced AI chips.

493
00:24:50,160 --> 00:24:53,360
Speaker 3: And currently one percent of advanced AI chips are made

494
00:24:53,400 --> 00:24:53,880
Speaker 3: in Taiwan.

495
00:24:54,240 --> 00:24:56,160
Speaker 2: How fast can we put that online in America? How

496
00:24:56,160 --> 00:24:57,680
Speaker 2: important is that for national security?

497
00:24:58,160 --> 00:25:01,199
Speaker 3: I think it's essential for national security, and we're not

498
00:25:01,240 --> 00:25:01,800
Speaker 3: doing enough.

499
00:25:02,080 --> 00:25:04,760
Speaker 4: You're fifty three years old. I'm one hundred and eighteen

500
00:25:04,840 --> 00:25:06,720
Speaker 4: days older than you. By what the hell have I

501
00:25:06,760 --> 00:25:07,480
Speaker 4: done in my life?

502
00:25:07,520 --> 00:25:07,720
Speaker 1: I know?

503
00:25:07,840 --> 00:25:08,119
Speaker 3: Right?

504
00:25:08,560 --> 00:25:09,640
Speaker 1: Fifty three years old?

505
00:25:10,240 --> 00:25:14,720
Speaker 3: Well, well, so seventy one was a great year.

506
00:25:15,240 --> 00:25:17,720
Speaker 4: And I was December seventy because I was just just

507
00:25:17,840 --> 00:25:20,120
Speaker 4: right before you were the summer of seventy one.

508
00:25:21,560 --> 00:25:23,520
Speaker 3: I was born sixty nine days after four twenty.

509
00:25:23,920 --> 00:25:27,440
Speaker 1: Wow, I did ask Ben, this is true.

510
00:25:27,520 --> 00:25:32,119
Speaker 4: Look, I did ask Ben, should I show up and

511
00:25:32,160 --> 00:25:35,000
Speaker 4: pull up a joint and say can we beat Rogan's views?

512
00:25:35,040 --> 00:25:38,439
Speaker 4: But I was pretty sure it might cause a scandal

513
00:25:38,480 --> 00:25:39,880
Speaker 4: if we spent a podcast.

514
00:25:40,680 --> 00:25:45,480
Speaker 3: It just turned out to be like a chocolate cigarden. Yeah.

515
00:25:45,560 --> 00:25:47,920
Speaker 4: Let me ask you if today was your last day

516
00:25:47,920 --> 00:25:51,439
Speaker 4: on Earth. Yeah, well, I'm not suggesting it's going to be.

517
00:25:51,440 --> 00:25:52,800
Speaker 4: But if it were, what do you think your biggest

518
00:25:52,840 --> 00:25:55,880
Speaker 4: legacy would be if everything you've done one hundred years

519
00:25:55,920 --> 00:25:58,159
Speaker 4: from now? What do you think people would remember if

520
00:25:58,600 --> 00:26:00,919
Speaker 4: if it were zero to today?

521
00:26:01,040 --> 00:26:04,520
Speaker 3: And will you ever go to space in the in

522
00:26:04,560 --> 00:26:06,960
Speaker 3: the distant future, one hundred or one thousand years ago?

523
00:26:07,520 --> 00:26:10,840
Speaker 3: If SpaceX got humans to Mars, that's what they would

524
00:26:10,880 --> 00:26:11,440
Speaker 3: remember me for.

525
00:26:12,119 --> 00:26:13,760
Speaker 1: All Right, final set of questions.

526
00:26:13,960 --> 00:26:16,480
Speaker 4: Who's the smartest guy you've ever met? You hang out

527
00:26:16,520 --> 00:26:18,720
Speaker 4: with some brilliant people, Like like, when you look at

528
00:26:18,800 --> 00:26:22,399
Speaker 4: what's a CEO? You look at other than yourself, what CEO?

529
00:26:22,480 --> 00:26:23,080
Speaker 3: Do you say?

530
00:26:24,080 --> 00:26:25,280
Speaker 1: Damn, that guy's good.

531
00:26:25,720 --> 00:26:30,600
Speaker 3: Larry Elson's very smart. So I say, Larry Elson's one

532
00:26:30,600 --> 00:26:35,119
Speaker 3: of the smartest people you know, Larry Page. I mean,

533
00:26:35,160 --> 00:26:36,280
Speaker 3: there are a lot of people that are very smart

534
00:26:36,280 --> 00:26:38,760
Speaker 3: it's hard to say. Like, you know, I think something

535
00:26:38,760 --> 00:26:41,920
Speaker 3: to be smart is as smart as so you know,

536
00:26:42,000 --> 00:26:48,840
Speaker 3: what if what have they done that is difficult and significant?

537
00:26:49,040 --> 00:26:51,920
Speaker 3: You know, Jeff Bezos has not a lot of difficult

538
00:26:51,960 --> 00:26:55,359
Speaker 3: and significant things. I mean, there are a lot of

539
00:26:55,400 --> 00:26:58,480
Speaker 3: smart humans. I call them smart for smart for a human,

540
00:26:58,680 --> 00:27:00,080
Speaker 3: A lot of people who are in the smart for

541
00:27:00,119 --> 00:27:00,920
Speaker 3: a human category.

542
00:27:01,440 --> 00:27:04,760
Speaker 1: All right, final lightning round, Star Wars or Star Trek.

543
00:27:05,320 --> 00:27:07,440
Speaker 3: The first movie I saw in the theater was Star Wars,

544
00:27:07,440 --> 00:27:09,159
Speaker 3: so I think it had a profound effect on me.

545
00:27:09,640 --> 00:27:13,040
Speaker 3: I'm six years old. I think, imagine, best first movie

546
00:27:13,040 --> 00:27:16,200
Speaker 3: you ever see in a theater is Star Wars. It's

547
00:27:16,200 --> 00:27:16,920
Speaker 3: gonna blaw her mind.

548
00:27:17,000 --> 00:27:18,040
Speaker 1: Best Star Wars.

549
00:27:17,760 --> 00:27:20,480
Speaker 3: Movie Empires Trucks Back.

550
00:27:20,920 --> 00:27:22,520
Speaker 1: The only objectively right answer.

551
00:27:22,560 --> 00:27:24,480
Speaker 4: I stood in line in three hours with my dad

552
00:27:24,480 --> 00:27:25,600
Speaker 4: to see it on opening day.

553
00:27:26,440 --> 00:27:29,440
Speaker 3: Kirk or Picard, I like them both.

554
00:27:29,440 --> 00:27:34,199
Speaker 4: For Kirk again, objectively right answer. By the way, James T.

555
00:27:34,359 --> 00:27:37,359
Speaker 4: Kirk is a Republican and Picard is a Democrat, and

556
00:27:37,560 --> 00:27:41,080
Speaker 4: the left gets very mad when I say that best

557
00:27:41,119 --> 00:27:41,840
Speaker 4: Star Trek.

558
00:27:41,640 --> 00:27:44,359
Speaker 3: Movie, I mean the original, the first Star Trek movie.

559
00:27:45,160 --> 00:27:51,880
Speaker 3: That's okay, most of both of both. Wrath of cons

560
00:27:51,880 --> 00:27:54,280
Speaker 3: were pretty good. But yeah, the original wrath of kN.

561
00:27:54,720 --> 00:27:59,439
Speaker 1: Ricardo Montaban revenge is a dish best served cold. It

562
00:27:59,560 --> 00:28:00,240
Speaker 1: is very a.

563
00:28:00,400 --> 00:28:05,160
Speaker 4: Cold in space, although I will say Rathacon is objectively

564
00:28:05,200 --> 00:28:07,560
Speaker 4: the right answer. But but four is a sleeper. When

565
00:28:07,600 --> 00:28:10,480
Speaker 4: they go back to San Francisco and and and go

566
00:28:10,520 --> 00:28:13,720
Speaker 4: find the whales and and you know, Scotty picks up

567
00:28:14,119 --> 00:28:15,920
Speaker 4: picks up the mouth and talks to it and goes

568
00:28:16,000 --> 00:28:16,640
Speaker 4: a keyboard.

569
00:28:16,880 --> 00:28:19,320
Speaker 1: How quaint that's a sleeper?

570
00:28:19,359 --> 00:28:19,680
Speaker 3: All right?

571
00:28:19,760 --> 00:28:22,160
Speaker 1: Last question? Did Han shoot first?

572
00:28:24,040 --> 00:28:25,359
Speaker 3: It seemed like he shot second.

573
00:28:25,920 --> 00:28:26,639
Speaker 1: This is verdict.

574
00:28:26,720 --> 00:28:29,200
Speaker 4: And by the way, I apologize Ben so Ben was

575
00:28:29,240 --> 00:28:31,600
Speaker 4: a jock and played tennis at ole miss and so

576
00:28:31,600 --> 00:28:34,680
Speaker 4: so occasionally when when we geek out a little and

577
00:28:34,720 --> 00:28:35,360
Speaker 4: y'all geek.

578
00:28:35,200 --> 00:28:38,600
Speaker 3: Out over, there is still on the question I love

579
00:28:38,840 --> 00:28:41,600
Speaker 3: you miss his The alien misses fast shot. So why

580
00:28:41,640 --> 00:28:43,400
Speaker 3: do you miss his vast shot? Must have been because

581
00:28:43,400 --> 00:28:46,040
Speaker 3: he got shot first and he's missing a point blank

582
00:28:46,120 --> 00:28:48,680
Speaker 3: bassil shot. If they less, they got knocked off kids.

583
00:28:48,720 --> 00:28:52,560
Speaker 4: But it's a question of real which is is Han

584
00:28:52,680 --> 00:28:55,520
Speaker 4: Solo simply a hero or an anti hero? And and

585
00:28:55,600 --> 00:28:58,840
Speaker 4: so I'm in the Han shot first category. I don't

586
00:28:58,880 --> 00:29:00,360
Speaker 4: like sanitized stories would have.

587
00:29:00,320 --> 00:29:02,400
Speaker 3: Had to have shot first, because otherwise, why why would

588
00:29:02,400 --> 00:29:05,680
Speaker 3: the alien miss appoint blank range? Are you ever going

589
00:29:05,760 --> 00:29:07,360
Speaker 3: to go to outer space? Is that saying in your

590
00:29:07,400 --> 00:29:09,320
Speaker 3: life goals? Yeah, I'd like to go to Mars at

591
00:29:09,360 --> 00:29:12,160
Speaker 3: some point. And people have said do I want to

592
00:29:12,200 --> 00:29:15,160
Speaker 3: die in maz and I say yes, just not an impact.

593
00:29:15,400 --> 00:29:16,760
Speaker 1: Now, that's a very good answer.

594
00:29:17,280 --> 00:29:21,480
Speaker 4: The astronauts on the space station, are they political prisoners?

595
00:29:22,480 --> 00:29:25,640
Speaker 4: Some of them are because because you could have given

596
00:29:25,640 --> 00:29:26,600
Speaker 4: them a ride back, and.

597
00:29:28,360 --> 00:29:30,560
Speaker 1: Joe Biden said no, purely for politics.

598
00:29:30,920 --> 00:29:34,360
Speaker 3: Yeah, I mean, you know, there's been some debate about

599
00:29:34,360 --> 00:29:36,680
Speaker 3: this online. But the thing is that it was very

600
00:29:36,720 --> 00:29:39,920
Speaker 3: a very high level decision, so it wasn't really even

601
00:29:39,960 --> 00:29:43,960
Speaker 3: an acid decision. It was just that the Biden White

602
00:29:43,960 --> 00:29:46,920
Speaker 3: House did not want to have someone who is pro

603
00:29:47,080 --> 00:29:52,240
Speaker 3: Trump rescuing Askrowt's rife before the election, so they pushed it.

604
00:29:52,320 --> 00:29:53,880
Speaker 4: Well, if you're one of those astronauts, you got to

605
00:29:53,880 --> 00:29:55,160
Speaker 4: be pretty pissed off about that.

606
00:29:55,560 --> 00:30:01,560
Speaker 3: Well, if they're a Democrat, yes, a prat like everything's fine,

607
00:30:01,600 --> 00:30:03,960
Speaker 3: fair enough. So I think one of them is a

608
00:30:03,960 --> 00:30:06,600
Speaker 3: repulicable incident. It depends on which one you ask.

609
00:30:06,920 --> 00:30:09,120
Speaker 1: Well, thank you Elan, this was this was awesome.

610
00:30:09,320 --> 00:30:12,400
Speaker 4: And let me say, and by the way, I put

611
00:30:12,440 --> 00:30:15,000
Speaker 4: out on X the day before yesterday, if you were

612
00:30:15,000 --> 00:30:16,880
Speaker 4: having a beer with Elon and could ask him anything,

613
00:30:16,960 --> 00:30:19,960
Speaker 4: what would you ask? And got lots of responses. The

614
00:30:20,000 --> 00:30:24,080
Speaker 4: most common response people said is is say thank you. Look,

615
00:30:24,280 --> 00:30:27,320
Speaker 4: Texans and the American people appreciate what you're doing. You

616
00:30:27,320 --> 00:30:29,320
Speaker 4: don't have to put up with this bs, and you're

617
00:30:29,360 --> 00:30:31,960
Speaker 4: doing it. I'm grateful. You're making a hell of a

618
00:30:32,000 --> 00:30:35,000
Speaker 4: difference for this country. I appreciate you, and the Americans

619
00:30:35,040 --> 00:30:35,640
Speaker 4: appreciate you.

620
00:30:35,920 --> 00:30:38,160
Speaker 3: Yeah, it's essential for the future of civilization. Otherwise I

621
00:30:38,200 --> 00:30:39,920
Speaker 3: wouldn't be doing it. Yes, it's not like I want

622
00:30:39,960 --> 00:30:43,040
Speaker 3: to get death threats. You know, Now, what.

623
00:30:42,920 --> 00:30:45,600
Speaker 4: Year does man first set foot on Mars?

624
00:30:45,920 --> 00:30:50,360
Speaker 3: I think the soonest would be twenty nine, twenty nine, yes,

625
00:30:50,680 --> 00:30:53,240
Speaker 3: and I don't think it's more than two to four

626
00:30:53,320 --> 00:30:54,000
Speaker 3: years beyond that.

627
00:30:54,320 --> 00:30:56,959
Speaker 4: And that's not an unman, that's that's a human being

628
00:30:57,280 --> 00:30:58,640
Speaker 4: putting his foot on the surface.

629
00:30:58,920 --> 00:31:00,560
Speaker 3: Yes, best case twenty nine.

630
00:31:00,680 --> 00:31:04,680
Speaker 4: And what do you put the odds of finding either

631
00:31:04,720 --> 00:31:07,120
Speaker 4: alien life or evidence of alien life.

632
00:31:07,160 --> 00:31:08,520
Speaker 3: I don't think we're going to find aliens.

633
00:31:08,600 --> 00:31:11,480
Speaker 1: Okay, but do we find ruins, do we find remnants?

634
00:31:11,680 --> 00:31:13,400
Speaker 3: We may we may find the ruins of a long

635
00:31:13,440 --> 00:31:18,040
Speaker 3: dead alien civilization. That's possible, And we may find subterranean

636
00:31:18,480 --> 00:31:20,120
Speaker 3: microbial life. That's possible.

637
00:31:20,280 --> 00:31:20,600
Speaker 1: All right.

638
00:31:20,640 --> 00:31:23,800
Speaker 4: If man lands on Mars and twenty nine, how soon

639
00:31:23,880 --> 00:31:25,640
Speaker 4: after that do you land on.

640
00:31:25,600 --> 00:31:28,040
Speaker 3: Mars remains to be seen. I'm not sure. The important

641
00:31:28,080 --> 00:31:32,000
Speaker 3: thing is that we build a self sustaining city on

642
00:31:32,040 --> 00:31:37,320
Speaker 3: Mars as quickly as possible. The key threshold is when

643
00:31:37,360 --> 00:31:41,240
Speaker 3: that city can't continue to grow, continue to prosper even

644
00:31:41,280 --> 00:31:45,240
Speaker 3: when the supply ships from Earth stopped coming. At that point,

645
00:31:45,440 --> 00:31:48,920
Speaker 3: even if something would happen on Earth, it might not

646
00:31:48,960 --> 00:31:49,560
Speaker 3: be World War.

647
00:31:49,520 --> 00:31:53,320
Speaker 1: Three, but it might be that a bad virus.

648
00:31:53,920 --> 00:31:56,480
Speaker 3: Yeah, it might not be anything. It's like, let's say

649
00:31:56,480 --> 00:31:58,360
Speaker 3: civilization you could die with a bang or whooper. It

650
00:31:58,360 --> 00:32:00,960
Speaker 3: may be that civilization is dies with a whimper rather

651
00:32:01,000 --> 00:32:04,720
Speaker 3: than a bang and simply loses the ability to send

652
00:32:04,760 --> 00:32:08,600
Speaker 3: ships to Mars. So you often need Mars to become

653
00:32:08,680 --> 00:32:12,120
Speaker 3: self sustaining and be able to grow by itself before

654
00:32:12,520 --> 00:32:15,080
Speaker 3: the recupply ships from Earth stopped coming. That is the

655
00:32:15,360 --> 00:32:20,440
Speaker 3: critical a civilizational threshold, beyond which the probable last span

656
00:32:20,520 --> 00:32:22,080
Speaker 3: of civilization is much greater.

657
00:32:22,400 --> 00:32:25,160
Speaker 4: And how close are we technologically to be able to

658
00:32:25,200 --> 00:32:29,000
Speaker 4: do that, to have a self sustaining settlement on the

659
00:32:29,000 --> 00:32:29,720
Speaker 4: surface of Mars.

660
00:32:29,960 --> 00:32:31,840
Speaker 3: I think it can be done in twenty years, but it.

661
00:32:31,800 --> 00:32:34,120
Speaker 4: Would take twenty years, so we're not in twenty nine.

662
00:32:34,160 --> 00:32:35,600
Speaker 4: We're not there. What are we missing?

663
00:32:35,680 --> 00:32:37,040
Speaker 1: What are the big technologies?

664
00:32:37,240 --> 00:32:39,800
Speaker 3: We don't have a few people running around the surface

665
00:32:40,240 --> 00:32:41,800
Speaker 3: in a hostile environment is not going to make it

666
00:32:41,800 --> 00:32:43,840
Speaker 3: self sustaining. So you're going to need on the order

667
00:32:43,880 --> 00:32:46,440
Speaker 3: of a million people, maybe a million tons of cargo.

668
00:32:46,680 --> 00:32:48,320
Speaker 4: So but you think we could have a million people

669
00:32:48,320 --> 00:32:52,600
Speaker 4: on Mars in twenty years, yes, And what's the technology

670
00:32:52,640 --> 00:32:54,840
Speaker 4: we're missing right now? When you think about a million

671
00:32:54,840 --> 00:32:57,400
Speaker 4: people on Mars? Do we have the ability to get water,

672
00:32:57,480 --> 00:32:59,880
Speaker 4: to get food, to keep them safe?

673
00:33:00,000 --> 00:33:01,880
Speaker 1: I mean, what what do we need to make that happen?

674
00:33:01,920 --> 00:33:04,320
Speaker 3: Well, you need to recreate the entire base of industry Earth.

675
00:33:04,520 --> 00:33:07,600
Speaker 3: So you know, we're here at the top of a

676
00:33:07,640 --> 00:33:12,240
Speaker 3: massive permitive industry that starts with mining a vast array

677
00:33:12,280 --> 00:33:16,720
Speaker 3: of materials. Those materials going through hundreds of steps of refinement.

678
00:33:17,800 --> 00:33:21,680
Speaker 3: We grow food, obviously, we grow trees, we make things

679
00:33:21,720 --> 00:33:24,240
Speaker 3: out of the trees. There's you know, you've got to

680
00:33:24,280 --> 00:33:26,120
Speaker 3: you've got to build all that on Mars, and Mars

681
00:33:26,160 --> 00:33:29,160
Speaker 3: is a hostile environment. It's you know, it sometimes gets

682
00:33:29,160 --> 00:33:32,160
Speaker 3: above zero on a warm summer day near the equator

683
00:33:32,160 --> 00:33:35,000
Speaker 3: on Mars. Meanly, it's quite cold. How do you prep

684
00:33:35,040 --> 00:33:37,600
Speaker 3: for that? Well, in the beginning, on Mars, you have

685
00:33:37,640 --> 00:33:42,160
Speaker 3: to have a life support habitation module, right, like you

686
00:33:42,400 --> 00:33:44,320
Speaker 3: need You can't just live outdoors. You can't breathe the.

687
00:33:44,280 --> 00:33:46,320
Speaker 1: Air like a dome you think is likely?

688
00:33:46,440 --> 00:33:47,920
Speaker 3: Yeah, glass domes type of thing.

689
00:33:48,080 --> 00:33:52,200
Speaker 4: Have you identified a location on Mars that is likely

690
00:33:52,280 --> 00:33:54,040
Speaker 4: to be ideal for a habitat?

691
00:33:54,520 --> 00:33:58,320
Speaker 3: What might be Arcadia planet? Here is one of the

692
00:33:58,720 --> 00:34:01,840
Speaker 3: one of the good options. That's one of my daughters

693
00:34:01,880 --> 00:34:03,120
Speaker 3: is named Arcadia after that.

694
00:34:04,160 --> 00:34:05,520
Speaker 1: And what makes that attractive.

695
00:34:05,760 --> 00:34:09,680
Speaker 3: My eldest son's middle name is Ari's Mars. You've been

696
00:34:09,719 --> 00:34:11,239
Speaker 3: thinking about this for a long time. If you're name

697
00:34:11,239 --> 00:34:13,920
Speaker 3: and your kids around it. My eldest kid is middle

698
00:34:14,000 --> 00:34:17,080
Speaker 3: name is essentially Mars. When did you get the dream? Like,

699
00:34:17,200 --> 00:34:22,200
Speaker 3: I mean it's twenty twenty one soon, this is decades old? Yeah, dream?

700
00:34:22,320 --> 00:34:23,920
Speaker 4: So like when you were ten, did you look up

701
00:34:23,960 --> 00:34:24,960
Speaker 4: and say I'm going to Mars.

702
00:34:25,320 --> 00:34:29,000
Speaker 3: No No. I read a lot of science fiction books

703
00:34:29,040 --> 00:34:32,799
Speaker 3: and program computers. But the first finally off. The first

704
00:34:32,880 --> 00:34:36,560
Speaker 3: video game that I sold was a space video game

705
00:34:36,600 --> 00:34:38,520
Speaker 3: called Blastar. Maybe I was born this way?

706
00:34:39,040 --> 00:34:39,520
Speaker 1: How do you do?

707
00:34:40,960 --> 00:34:44,680
Speaker 4: How do you become Elon Musk? Look, you're obviously smart

708
00:34:44,680 --> 00:34:46,719
Speaker 4: as hell, but but there are lots there are a

709
00:34:46,719 --> 00:34:49,200
Speaker 4: lot of smart people that don't do squat And you've

710
00:34:49,280 --> 00:34:56,160
Speaker 4: managed everything you've touched has been an extraordinary success. Yeah, yeah, Look,

711
00:34:56,200 --> 00:34:57,799
Speaker 4: I mean that's just objectively right.

712
00:34:57,880 --> 00:34:59,160
Speaker 1: So what has led to that?

713
00:34:59,200 --> 00:35:01,280
Speaker 4: Because there are others are people that that's not true,

714
00:35:01,600 --> 00:35:03,760
Speaker 4: and they gaze at their nable and they don't do anything.

715
00:35:03,880 --> 00:35:06,920
Speaker 4: So what do you do differently that makes you so effective?

716
00:35:07,000 --> 00:35:09,400
Speaker 3: Well, I suppose I have a philosophy of curiosity. I

717
00:35:09,440 --> 00:35:11,920
Speaker 3: want to find out the nature of the universe, understand

718
00:35:11,920 --> 00:35:14,759
Speaker 3: the universe, And in order to do that, we have

719
00:35:14,800 --> 00:35:17,680
Speaker 3: to travel to other planets, see other star systems, maybe

720
00:35:17,680 --> 00:35:21,879
Speaker 3: other galaxies, find perhaps other alien civilizations, or at least

721
00:35:21,880 --> 00:35:25,560
Speaker 3: the remnants of alien civilizations, gain a better understanding of

722
00:35:25,560 --> 00:35:28,719
Speaker 3: words universe going ready to come from? And what questions

723
00:35:28,920 --> 00:35:31,160
Speaker 3: do we not yet know to ask about the answer

724
00:35:31,239 --> 00:35:32,080
Speaker 3: that is the universe.

725
00:35:32,400 --> 00:35:36,040
Speaker 4: So let's go back twenty five years, late nineties.

726
00:35:36,280 --> 00:35:38,880
Speaker 1: You're at PayPal. How do you turn PayPal into the

727
00:35:38,920 --> 00:35:41,480
Speaker 1: success it was, which which then helped launch you to

728
00:35:41,480 --> 00:35:41,960
Speaker 1: the next one?

729
00:35:41,960 --> 00:35:43,920
Speaker 3: In the next one. Yeah, So I studied physics and

730
00:35:44,000 --> 00:35:47,280
Speaker 3: economics and college, which is a good foundation for understanding

731
00:35:47,280 --> 00:35:51,920
Speaker 3: how the economy works and how reality works, and then

732
00:35:52,239 --> 00:35:56,640
Speaker 3: was going to do a PhD at Stanford in advanced

733
00:35:57,120 --> 00:36:02,480
Speaker 3: ultra capacitors actually as a potential means of energy storage

734
00:36:02,520 --> 00:36:06,759
Speaker 3: for electric transport. Put that on hold to start an

735
00:36:06,760 --> 00:36:10,480
Speaker 3: Internet company. Essentially came to the conclusion that the Internet

736
00:36:10,680 --> 00:36:13,080
Speaker 3: was one of those rare things and I could either

737
00:36:13,120 --> 00:36:15,800
Speaker 3: watch it happen while a grad student or participated. And

738
00:36:15,880 --> 00:36:18,000
Speaker 3: I figured, I've always go back to grad school. Grad

739
00:36:18,000 --> 00:36:19,680
Speaker 3: school is going to be kind of the same. But

740
00:36:20,920 --> 00:36:23,080
Speaker 3: I couldn't betther thought of just watching the Internet happen.

741
00:36:23,320 --> 00:36:24,759
Speaker 3: So I wanted to be a part of building it.

742
00:36:24,880 --> 00:36:28,080
Speaker 3: So I created an Internet Internet company. We did the

743
00:36:28,080 --> 00:36:31,880
Speaker 3: first maps, directions, yellow pages, white pages on the Internet.

744
00:36:31,880 --> 00:36:34,200
Speaker 3: I actually wrote the first version of Suffered just by

745
00:36:34,200 --> 00:36:38,200
Speaker 3: myself in ninety five, and we ended up selling that

746
00:36:38,239 --> 00:36:42,319
Speaker 3: to Compact Texas company. I guess for about three hundred

747
00:36:42,320 --> 00:36:45,320
Speaker 3: million dollars in cash about four years after I graduated. Wow.

748
00:36:45,880 --> 00:36:49,240
Speaker 3: So I should say just to preface that I graduated

749
00:36:49,280 --> 00:36:51,440
Speaker 3: with about one hundred thousand dollars a student debt. So

750
00:36:51,440 --> 00:36:56,480
Speaker 3: it wasn't yeah you and me about yeah, yeah, I know.

751
00:36:57,680 --> 00:36:59,520
Speaker 3: And when I first arrived in North America, I arrived

752
00:36:59,520 --> 00:37:02,080
Speaker 3: with twenty five hundred dollars, a bag of books and

753
00:37:02,520 --> 00:37:03,360
Speaker 3: a bag of clothes.

754
00:37:03,480 --> 00:37:05,720
Speaker 4: All right, So you sell the company for three hundred million,

755
00:37:05,880 --> 00:37:07,360
Speaker 4: How much does that change your life?

756
00:37:07,400 --> 00:37:13,200
Speaker 3: Well, I got twenty one million dollars that jack, But

757
00:37:13,239 --> 00:37:16,080
Speaker 3: I wanted to do more on the internet, so started

758
00:37:16,080 --> 00:37:18,960
Speaker 3: a company called x dot com, which merch with a

759
00:37:19,000 --> 00:37:23,080
Speaker 3: company called Confinity, which is Peter Teel and Max Levchun yep.

760
00:37:23,239 --> 00:37:26,319
Speaker 3: And the combined company was actually at first still called

761
00:37:26,480 --> 00:37:28,680
Speaker 3: x dot com, but we later later changed the name

762
00:37:28,719 --> 00:37:31,879
Speaker 3: of the company to PayPal. Because of all the name changes,

763
00:37:31,880 --> 00:37:34,200
Speaker 3: it's kind of confusing. But the company that people know

764
00:37:34,320 --> 00:37:38,160
Speaker 3: is know as PayPal today was actually I filed those

765
00:37:38,160 --> 00:37:40,360
Speaker 3: in corporation documents for that company. Interesting.

766
00:37:40,640 --> 00:37:43,640
Speaker 4: Yeah, well, And as you know, Peter Tiel and I

767
00:37:43,719 --> 00:37:46,319
Speaker 4: were buddies back in the mid nineties before he went

768
00:37:46,360 --> 00:37:48,200
Speaker 4: and did any of this. But you know, I became

769
00:37:48,239 --> 00:37:50,319
Speaker 4: friends with him when he was a corporate lawyer in

770
00:37:50,320 --> 00:37:52,560
Speaker 4: New York and just sort of a young libertarian with

771
00:37:52,960 --> 00:37:53,760
Speaker 4: a lot of dreams.

772
00:37:53,960 --> 00:37:55,520
Speaker 1: So it's been a heck of a journey.

773
00:37:56,200 --> 00:37:59,000
Speaker 3: Yeah. Yeah, Now, Sly Peter was involved in a coup.

774
00:38:00,360 --> 00:38:03,160
Speaker 3: We had a little sort of knifing in the Senate situation,

775
00:38:03,840 --> 00:38:09,880
Speaker 3: uh where you know that they did Coon met at

776
00:38:10,440 --> 00:38:11,120
Speaker 3: at PayPal.

777
00:38:12,480 --> 00:38:14,560
Speaker 1: I kind of did you all make peace after that?

778
00:38:14,640 --> 00:38:17,600
Speaker 3: Yeah? Yeah, yeah, I mean I was doing a lot

779
00:38:17,600 --> 00:38:19,680
Speaker 3: of sort of risky moves that I think ultimately would

780
00:38:19,719 --> 00:38:23,080
Speaker 3: have been successful. But I then went on a two

781
00:38:23,120 --> 00:38:28,480
Speaker 3: week trip which was a dual money raising trip and honeymoon,

782
00:38:28,560 --> 00:38:31,239
Speaker 3: and said not done my honeymoon earlier in the year,

783
00:38:31,400 --> 00:38:33,640
Speaker 3: So it's raising money while doing doing holly honeymoon. But

784
00:38:33,680 --> 00:38:35,560
Speaker 3: I was kind of awake. Did that go over by

785
00:38:35,600 --> 00:38:38,480
Speaker 3: the way it worked? It worked? There you go, kind

786
00:38:38,520 --> 00:38:41,320
Speaker 3: of worked. I raised money, yeah, and we had honeymoon

787
00:38:41,400 --> 00:38:44,520
Speaker 3: there you go. So yeah, but you don't want to

788
00:38:44,520 --> 00:38:48,640
Speaker 3: be away from the battle when things are scary, so

789
00:38:48,680 --> 00:38:50,840
Speaker 3: I was not there to assuage the concerns of the troops.

790
00:38:51,719 --> 00:38:56,960
Speaker 3: And anyway, Uh, we passed things up, and I have

791
00:38:57,120 --> 00:39:01,600
Speaker 3: been friends nonetheless, and you know these days all like

792
00:39:01,680 --> 00:39:03,799
Speaker 3: stay at his house and stuff, So super friends. And

793
00:39:03,840 --> 00:39:06,160
Speaker 3: he's also invested in most of my companies.

794
00:39:07,000 --> 00:39:09,680
Speaker 4: All right, So two thousand and two you start SpaceX,

795
00:39:10,040 --> 00:39:12,120
Speaker 4: Like how do you start a rocket company? Like what's

796
00:39:12,160 --> 00:39:14,680
Speaker 4: the first day where you're like, I want to make

797
00:39:14,760 --> 00:39:16,200
Speaker 4: rockets and I want to go to Mars?

798
00:39:16,239 --> 00:39:17,440
Speaker 1: Like what do you do on day one?

799
00:39:17,640 --> 00:39:19,600
Speaker 3: So I think you have to start with a some

800
00:39:19,640 --> 00:39:23,000
Speaker 3: sort of philosophical premise in order to have in order

801
00:39:23,040 --> 00:39:24,960
Speaker 3: for the in order to be in order to be

802
00:39:25,000 --> 00:39:29,719
Speaker 3: highly motivated, you have to have some philosophical foundation. In

803
00:39:29,719 --> 00:39:33,160
Speaker 3: my case, it was that that we want to expand

804
00:39:33,239 --> 00:39:37,440
Speaker 3: the scope and scale of consciousness to better understand the

805
00:39:37,520 --> 00:39:41,359
Speaker 3: nature of the universe. And in order to expand scate,

806
00:39:42,080 --> 00:39:45,560
Speaker 3: expand consciousness, we need to go beyond one planet. From

807
00:39:45,640 --> 00:39:48,400
Speaker 3: one planet, there's there's too much risk. You know, hopefully

808
00:39:48,400 --> 00:39:51,360
Speaker 3: Earth civilization prosperos very far into the future, but it

809
00:39:51,360 --> 00:39:53,640
Speaker 3: may not. There's always some risk that we are we

810
00:39:53,680 --> 00:39:56,839
Speaker 3: self annihilate through nuclear war, or that there's a big

811
00:39:56,920 --> 00:39:59,319
Speaker 3: meter that takes us out like the dinosaurs. Yep, there's

812
00:39:59,320 --> 00:40:01,360
Speaker 3: always some risk full. Your eggs are in one basket.

813
00:40:01,400 --> 00:40:04,880
Speaker 3: So it's going to be better if we're a multiplanet species.

814
00:40:04,960 --> 00:40:07,000
Speaker 3: And then once we're a multiplanet species, that the next

815
00:40:07,000 --> 00:40:09,440
Speaker 3: step would be to be a multi stellar and have

816
00:40:09,800 --> 00:40:14,000
Speaker 3: a civilization among on many different star systems. So in

817
00:40:14,000 --> 00:40:15,720
Speaker 3: two thousand and one, I didn't think that I could.

818
00:40:15,840 --> 00:40:17,400
Speaker 3: I didn't think I could sell a rocket company. So

819
00:40:17,440 --> 00:40:20,800
Speaker 3: I thought I'd take some of the money from PayPal

820
00:40:21,040 --> 00:40:23,400
Speaker 3: in that case, I think was about one hundred and

821
00:40:23,440 --> 00:40:26,719
Speaker 3: eighty eight million dollars after tax, something like that, and

822
00:40:27,200 --> 00:40:28,840
Speaker 3: I thought, you know, I don't need one hundred and

823
00:40:28,840 --> 00:40:31,560
Speaker 3: eighty million dollars, so I'll spend a bunch of it

824
00:40:31,640 --> 00:40:36,680
Speaker 3: on a philanthropic Mars mission to get the public excited

825
00:40:36,880 --> 00:40:39,279
Speaker 3: about going back to Mars. We're going to Mars, I

826
00:40:39,320 --> 00:40:42,040
Speaker 3: should say, yeah, Mars was always going to be the

827
00:40:42,080 --> 00:40:45,000
Speaker 3: destination after the Moon. Right. In fact, if you told

828
00:40:45,040 --> 00:40:47,760
Speaker 3: people in nineteen sixty nine that it would be twenty

829
00:40:47,800 --> 00:40:49,680
Speaker 3: twenty five and we've not even gone back to.

830
00:40:49,640 --> 00:40:51,440
Speaker 1: The Moon let alone, it's hard to believe.

831
00:40:51,680 --> 00:40:54,520
Speaker 3: Let alone Mars, they'd be like what happened in the

832
00:40:54,560 --> 00:40:59,239
Speaker 3: civilization collapse, like they would be incomprehensible that we've not

833
00:40:59,360 --> 00:41:01,879
Speaker 3: been to Mars by if you told people this after

834
00:41:01,960 --> 00:41:03,120
Speaker 3: landing on the Moon in sixty nine.

835
00:41:03,160 --> 00:41:05,120
Speaker 1: But what do you think in fifty years America never

836
00:41:05,160 --> 00:41:05,919
Speaker 1: went back to the moon.

837
00:41:06,040 --> 00:41:08,640
Speaker 3: Well, we destroyed the Saturn five rocket that was that

838
00:41:08,920 --> 00:41:10,960
Speaker 3: could take you to the Moon, and had the Space Shuttle,

839
00:41:10,960 --> 00:41:13,680
Speaker 3: which could only go to lowth orbit, and then there

840
00:41:13,680 --> 00:41:17,719
Speaker 3: really hasn't been anything to replace any No vehicle has

841
00:41:17,719 --> 00:41:20,480
Speaker 3: been made since then that can go to the Moon

842
00:41:20,600 --> 00:41:24,520
Speaker 3: or to Mars until the SpaceX Starship rocket. Yeah, so

843
00:41:24,840 --> 00:41:26,479
Speaker 3: you can't go to Mars if you don't have the ride.

844
00:41:26,719 --> 00:41:30,360
Speaker 4: So I remember you and I first met in twenty

845
00:41:30,400 --> 00:41:33,560
Speaker 4: thirteen when when I was a brand new baby senator. Yeah,

846
00:41:33,680 --> 00:41:35,920
Speaker 4: and I was still down in the basement office. They

847
00:41:35,960 --> 00:41:38,279
Speaker 4: stick freshman senators in the basement.

848
00:41:37,960 --> 00:41:38,960
Speaker 1: Office, kind of like hazeny.

849
00:41:39,040 --> 00:41:39,839
Speaker 3: Yeah, yeah, that's what say.

850
00:41:39,840 --> 00:41:42,759
Speaker 1: It sounds like there aree hundred sected offices. But for

851
00:41:42,800 --> 00:41:43,920
Speaker 1: six months you stay in the basement.

852
00:41:44,760 --> 00:41:48,360
Speaker 3: It's like worry, mean, you know where you're supposed to know.

853
00:41:48,400 --> 00:41:49,040
Speaker 1: I got to stay.

854
00:41:49,040 --> 00:41:50,759
Speaker 4: Now, thirteen years into it, I think there's a lot

855
00:41:50,760 --> 00:41:54,120
Speaker 4: of wisdom to doing that. But you were down in

856
00:41:54,120 --> 00:41:55,960
Speaker 4: the basement office and I remember you were coming and

857
00:41:55,960 --> 00:41:58,759
Speaker 4: sitting down with SpaceX and at the time the Air

858
00:41:58,800 --> 00:42:01,280
Speaker 4: Force was not letting you all be to launch satellites,

859
00:42:01,320 --> 00:42:03,080
Speaker 4: and so you were coming and saying, look, we got

860
00:42:03,080 --> 00:42:04,440
Speaker 4: a company. I think we can do a really good

861
00:42:04,520 --> 00:42:06,200
Speaker 4: job of this, and yet we're locked out of this.

862
00:42:06,719 --> 00:42:09,719
Speaker 4: It's a little amazing to think the journey SpaceX is

863
00:42:09,760 --> 00:42:11,359
Speaker 4: gone from then to now.

864
00:42:11,880 --> 00:42:13,839
Speaker 3: Yes, it's hard to believe that this is all real

865
00:42:15,040 --> 00:42:18,600
Speaker 3: because originally, consistently with my belief that we need to

866
00:42:18,640 --> 00:42:21,040
Speaker 3: become a multiplant species, I thought the only way to

867
00:42:21,040 --> 00:42:23,839
Speaker 3: do that would be through Nassau So and I think

868
00:42:23,920 --> 00:42:26,040
Speaker 3: I thought, well, if I can just get the public

869
00:42:26,040 --> 00:42:28,720
Speaker 3: excited about Mars, then they'll do a mission to Mars.

870
00:42:29,040 --> 00:42:31,759
Speaker 3: And so initially my thought was to have to send

871
00:42:31,800 --> 00:42:36,000
Speaker 3: a small greenhouse with seeds and dehydrated nutrient gel. Then

872
00:42:36,200 --> 00:42:39,439
Speaker 3: land the greenhouse, hydrate the seeds, and you see these

873
00:42:39,840 --> 00:42:42,040
Speaker 3: the sort of money shot proof. The money shot would

874
00:42:42,080 --> 00:42:45,680
Speaker 3: be green plants on a red background. I also recently

875
00:42:45,760 --> 00:42:48,319
Speaker 3: known that money shot has a different meaning in some

876
00:42:48,560 --> 00:42:55,960
Speaker 3: other arenas. But yeah, story, But what I'm trying to

877
00:42:56,000 --> 00:43:00,560
Speaker 3: say is the captivating shot would be the green plants

878
00:43:00,600 --> 00:43:03,520
Speaker 3: on a red background, and then hopefully that would if

879
00:43:03,520 --> 00:43:05,320
Speaker 3: you did something like that, that would get the public excited

880
00:43:05,320 --> 00:43:07,759
Speaker 3: about Mars, that would increase nasta's budget and then we

881
00:43:07,800 --> 00:43:11,400
Speaker 3: could send people to Mars. Dream was nasty to do this, yes,

882
00:43:11,640 --> 00:43:16,359
Speaker 3: not you. The original original plan was literally to take

883
00:43:16,360 --> 00:43:19,160
Speaker 3: a bunch of the money from PayPal and I guess

884
00:43:19,160 --> 00:43:23,200
Speaker 3: by some people's definition wasteed with no profit on a

885
00:43:23,239 --> 00:43:26,239
Speaker 3: non profit thing. I wanted to spend a whole bunch

886
00:43:26,280 --> 00:43:28,239
Speaker 3: of my money for free to get Nasta's budget to

887
00:43:28,239 --> 00:43:30,760
Speaker 3: be bigger so we could go to friggin Mars. Right, Wow,

888
00:43:31,400 --> 00:43:33,680
Speaker 3: that's what I wanted. So that was the holy grail,

889
00:43:33,920 --> 00:43:35,560
Speaker 3: That's what I wanted. I was like, so, when did

890
00:43:35,600 --> 00:43:38,359
Speaker 3: you Mars? That's what I wanted to know.

891
00:43:38,480 --> 00:43:41,040
Speaker 1: Well, when when did it strike you? Okay, you're going to.

892
00:43:41,040 --> 00:43:42,200
Speaker 3: Have to do this if you want, I'll tell you.

893
00:43:42,239 --> 00:43:44,799
Speaker 3: It gets crazier, all right, It gets crazier. So so

894
00:43:44,840 --> 00:43:46,839
Speaker 3: that I couldn't afford any of the US rockets because

895
00:43:46,880 --> 00:43:48,560
Speaker 3: as you know, the US rockets are way too expensive,

896
00:43:48,800 --> 00:43:51,360
Speaker 3: boying lucky rock Lucky rockets are crazy money. I didn't have.

897
00:43:51,840 --> 00:43:53,400
Speaker 3: I didn't even even with one hundred eight millions, so

898
00:43:53,400 --> 00:43:55,760
Speaker 3: way I could have afforded sure they back then well

899
00:43:56,080 --> 00:44:00,960
Speaker 3: the with with the additional stage to get tomorrows, it

900
00:44:00,960 --> 00:44:03,040
Speaker 3: would have been about like eighty million. So technically I

901
00:44:03,040 --> 00:44:05,319
Speaker 3: could have afforded one of them, but I wanted to

902
00:44:05,320 --> 00:44:08,040
Speaker 3: do too in case one of them didn't work. Yeah. So,

903
00:44:09,000 --> 00:44:10,520
Speaker 3: and then I didn't have enough money for that. Yeah,

904
00:44:10,520 --> 00:44:12,920
Speaker 3: and I was sort of prepared to, you know, I

905
00:44:12,920 --> 00:44:16,600
Speaker 3: don't know, waste half the money. And I figured if

906
00:44:16,600 --> 00:44:18,400
Speaker 3: I had ninety million left, that'd be fine, you know,

907
00:44:19,040 --> 00:44:21,600
Speaker 3: but ideally on all of it. So I went to

908
00:44:21,680 --> 00:44:26,200
Speaker 3: Russia twice to try to buy ICBMs. How'd that go?

909
00:44:26,600 --> 00:44:29,360
Speaker 3: And who do you call? The Russian rocket forces?

910
00:44:29,920 --> 00:44:31,719
Speaker 1: Do they sell ICBMs? Does that work?

911
00:44:31,920 --> 00:44:32,200
Speaker 3: Yeah?

912
00:44:33,760 --> 00:44:35,359
Speaker 2: You got to tell us a story that I want

913
00:44:35,360 --> 00:44:38,280
Speaker 2: to know who you can buy anything in Russia?

914
00:44:38,360 --> 00:44:41,680
Speaker 3: Yeah, I like, please walk me down that.

915
00:44:41,800 --> 00:44:43,680
Speaker 2: I want to know how you made that phone call

916
00:44:43,760 --> 00:44:45,600
Speaker 2: and when you get there, how did that work?

917
00:44:45,600 --> 00:44:48,080
Speaker 3: And what do you tell your friends? Yeah, listen, I'm

918
00:44:48,120 --> 00:44:50,840
Speaker 3: going to Russian device in ICBMs. I might not return,

919
00:44:51,120 --> 00:44:57,319
Speaker 3: you know, in this situation. Literally, Yeah, so I guess

920
00:44:57,360 --> 00:45:02,480
Speaker 3: slightly less insane when when you understand that the Russians

921
00:45:02,520 --> 00:45:06,160
Speaker 3: had to demolish a bunch of their ICBMs because of

922
00:45:07,280 --> 00:45:10,480
Speaker 3: you know, Soult talks like the piece because basically an

923
00:45:10,480 --> 00:45:13,799
Speaker 3: agreement between the United States and Russia to reduce the

924
00:45:13,800 --> 00:45:17,760
Speaker 3: total number of ICBMs, Russia was actually obligated to scrap

925
00:45:17,840 --> 00:45:19,680
Speaker 3: a bunch of their ICBMs. So you took it the

926
00:45:19,800 --> 00:45:22,960
Speaker 3: very biggest ICBMs. You could converte those into a rocket,

927
00:45:23,120 --> 00:45:25,880
Speaker 3: added additional stage and send something to Mars.

928
00:45:26,080 --> 00:45:28,600
Speaker 4: So those are big enough with one more stage to

929
00:45:28,640 --> 00:45:29,520
Speaker 4: get to Mars.

930
00:45:29,760 --> 00:45:31,920
Speaker 3: To send a small payload to Mars. Yeah, so the

931
00:45:32,040 --> 00:45:32,680
Speaker 3: s S eighteen.

932
00:45:33,080 --> 00:45:35,440
Speaker 4: So you try to buy CBMs, do you succeed or no?

933
00:45:35,680 --> 00:45:37,560
Speaker 4: Or do you figure out you got to build your

934
00:45:37,600 --> 00:45:38,160
Speaker 4: own instead?

935
00:45:38,440 --> 00:45:41,920
Speaker 3: They kept raising the price on me, so because I

936
00:45:41,920 --> 00:45:43,440
Speaker 3: figured like, look, they're going to throw these things in

937
00:45:43,480 --> 00:45:46,480
Speaker 3: scrappy on anyway, you should get a really good deal, right,

938
00:45:47,400 --> 00:45:51,120
Speaker 3: So the price thought out at four million. Then the

939
00:45:51,120 --> 00:45:53,560
Speaker 3: next conversation they were at eight million. Then the next

940
00:45:53,560 --> 00:45:56,279
Speaker 3: conversation they were at like nineteen million. And I'm like,

941
00:45:56,440 --> 00:45:57,640
Speaker 3: this is before we signed a contract.

942
00:45:57,680 --> 00:46:00,200
Speaker 4: By the way, was there another was there an they're

943
00:46:00,200 --> 00:46:01,799
Speaker 4: bit or were you the only one trying to buy them?

944
00:46:02,120 --> 00:46:04,040
Speaker 3: I think I don't know if there were other bits,

945
00:46:04,040 --> 00:46:06,600
Speaker 3: but they didn't mention any other bits. But I was like, man,

946
00:46:06,600 --> 00:46:08,680
Speaker 3: if if the price is increasing this much before the

947
00:46:08,680 --> 00:46:11,720
Speaker 3: contract signed, I'm really going to get fleeced after the contracts.

948
00:46:12,280 --> 00:46:16,560
Speaker 3: So so I got pretty frustrated there. Actually, in some

949
00:46:16,600 --> 00:46:21,560
Speaker 3: cases we got into like shouting matches in Moscow, some

950
00:46:21,600 --> 00:46:23,640
Speaker 3: guys shouting at me in Russia, and I'm shouting back

951
00:46:23,640 --> 00:46:29,600
Speaker 3: at him really badly, you know, I'm like, so you

952
00:46:29,640 --> 00:46:31,359
Speaker 3: are all I mean, you're all.

953
00:46:35,040 --> 00:46:35,640
Speaker 1: In Moscow?

954
00:46:35,920 --> 00:46:39,960
Speaker 3: Yeah, so, uh man, I should have recorded that. That would

955
00:46:40,000 --> 00:46:40,920
Speaker 3: have been one for them.

956
00:46:40,920 --> 00:46:43,120
Speaker 2: How many days were you there negotiating that first time?

957
00:46:43,280 --> 00:46:44,799
Speaker 2: I mean, was this like ongoing?

958
00:46:44,920 --> 00:46:48,319
Speaker 3: Yeah, yeah, this this took place. These conversations took place

959
00:46:48,320 --> 00:46:52,839
Speaker 3: over probably six months or so. Wow. So and then

960
00:46:52,880 --> 00:46:56,600
Speaker 3: the final trip trip there was with the with was

961
00:46:56,600 --> 00:47:01,640
Speaker 3: with Mike Revenue later became assid administrator. I actually realized

962
00:47:01,719 --> 00:47:04,840
Speaker 3: in the course of this that my original premise was wrong,

963
00:47:05,080 --> 00:47:07,880
Speaker 3: that that America actually has plenty of will to go

964
00:47:07,920 --> 00:47:11,319
Speaker 3: to Mars, but needs it just needs a way to

965
00:47:11,560 --> 00:47:15,560
Speaker 3: Mars that is affordable and that doesn't break the budget.

966
00:47:15,600 --> 00:47:17,000
Speaker 1: You know, just as you know, we couldn't even get

967
00:47:17,000 --> 00:47:19,239
Speaker 1: to the space station. We needed the Russians to get

968
00:47:19,320 --> 00:47:20,360
Speaker 1: us to our own space station.

969
00:47:20,440 --> 00:47:21,080
Speaker 3: That was embarrassing.

970
00:47:21,239 --> 00:47:22,400
Speaker 1: It really was pitiful.

971
00:47:22,520 --> 00:47:24,880
Speaker 3: I'm not sure most Americans know just how much we

972
00:47:24,880 --> 00:47:26,400
Speaker 3: were being fleeced. Like I think they got up to

973
00:47:26,440 --> 00:47:29,960
Speaker 3: like ninety million dollars a seat. Yeah, wow, Yeah, for

974
00:47:30,000 --> 00:47:33,200
Speaker 3: a seat that cost them like ten prege obviously, but

975
00:47:33,239 --> 00:47:37,160
Speaker 3: it was the only Yeah it was before SpaceX. Ninety

976
00:47:37,160 --> 00:47:39,160
Speaker 3: million dollars a seat for a seat that cost them

977
00:47:39,160 --> 00:47:43,840
Speaker 3: ten million is high. Yeah, that's a lot of money. Yeah.

978
00:47:44,000 --> 00:47:46,360
Speaker 4: So a few months ago you and I were down

979
00:47:46,640 --> 00:47:49,240
Speaker 4: in Boca Chica with a president for a starship launch,

980
00:47:49,560 --> 00:47:52,480
Speaker 4: and it is incredible what you built in Boca Chica.

981
00:47:52,719 --> 00:47:55,440
Speaker 4: You know, five years ago it was an empty beach.

982
00:47:55,640 --> 00:47:58,640
Speaker 3: At the southern tip of the Sundbar. Yeah, and it's.

983
00:47:58,520 --> 00:48:01,760
Speaker 4: Now a city and factory where you're building a rocket

984
00:48:01,760 --> 00:48:05,120
Speaker 4: ship a month with with incredible precision. But one of

985
00:48:05,160 --> 00:48:06,920
Speaker 4: the things you said to me when we were down

986
00:48:06,960 --> 00:48:09,400
Speaker 4: there that really stood out to me is is you

987
00:48:09,440 --> 00:48:12,960
Speaker 4: said your philosophy on intellectual property talked to lots of

988
00:48:13,000 --> 00:48:16,239
Speaker 4: CEOs or we fight to guard our IP and you

989
00:48:16,239 --> 00:48:19,160
Speaker 4: had a very different approach. What's what's your view of IP.

990
00:48:19,400 --> 00:48:23,920
Speaker 3: Patents of the week, patents of for those that innovate slowly.

991
00:48:24,239 --> 00:48:27,359
Speaker 4: I literally do not know anyone else in business who

992
00:48:27,360 --> 00:48:29,200
Speaker 4: would say something like that, like like it was a

993
00:48:29,560 --> 00:48:32,440
Speaker 4: startling and and and and what Elon said down there

994
00:48:32,520 --> 00:48:34,879
Speaker 4: is he said, look this stuff, I assume everyone will

995
00:48:34,880 --> 00:48:36,799
Speaker 4: steal everything, but by the time they steal it will

996
00:48:36,800 --> 00:48:38,600
Speaker 4: be five generations beyond and it won't matter.

997
00:48:38,719 --> 00:48:42,400
Speaker 3: Yes, at Tesla, we actually open sourcial lat patents. So

998
00:48:42,400 --> 00:48:45,120
Speaker 3: we said our patents are anyone can use it for free.

999
00:48:45,280 --> 00:48:48,880
Speaker 3: Really yeah, uh, the only really your patents of Tesla

1000
00:48:49,160 --> 00:48:54,680
Speaker 3: to to avoid patent trolls causing causing trouble. So we'll

1001
00:48:54,719 --> 00:48:56,880
Speaker 3: try to look ahead and say, okay, patent trolls are

1002
00:48:56,960 --> 00:48:59,520
Speaker 3: going to trial pat file patents to blocks and things,

1003
00:48:59,560 --> 00:49:02,040
Speaker 3: will FIP patents and then open sources make it free.

1004
00:49:02,320 --> 00:49:04,160
Speaker 3: I mean, I want to say patents for the week. Now.

1005
00:49:04,320 --> 00:49:08,080
Speaker 3: There are a few cases, in say with pharmaceuticals, where

1006
00:49:08,120 --> 00:49:10,000
Speaker 3: it might cost you billion dollars to do a phase

1007
00:49:10,000 --> 00:49:14,600
Speaker 3: three human file, but then subsequently the drug is very

1008
00:49:14,680 --> 00:49:18,120
Speaker 3: cheap to manufacture. So cases there are some in my opinion,

1009
00:49:18,120 --> 00:49:22,399
Speaker 3: which would massively reduce what can be patented and and

1010
00:49:22,560 --> 00:49:26,160
Speaker 3: say because the whole point of patenting is to maximize innovation,

1011
00:49:26,440 --> 00:49:31,080
Speaker 3: not inhibit it. And in my opinion, maybe a controversial opinion,

1012
00:49:31,600 --> 00:49:35,239
Speaker 3: most patents inhibit innovation, they do not help it. But

1013
00:49:35,280 --> 00:49:37,120
Speaker 3: there are case I want to do one a single

1014
00:49:37,320 --> 00:49:40,000
Speaker 3: cases like where such as a phase three clinical trial

1015
00:49:40,040 --> 00:49:42,120
Speaker 3: that might cost a billion dollars, but then the drugs

1016
00:49:42,120 --> 00:49:46,600
Speaker 3: thereafter cost a few dollars to manufacture, and if you

1017
00:49:46,640 --> 00:49:48,960
Speaker 3: can then immediately copy those drugs for a few dollars,

1018
00:49:48,960 --> 00:49:52,680
Speaker 3: no one will pay for the billion dollars free writer problem. Yeah, exactly,

1019
00:49:52,719 --> 00:49:54,600
Speaker 3: So you have to address the free writer problem. But

1020
00:49:54,760 --> 00:49:57,000
Speaker 3: other than that, there should be no patents. The ideas

1021
00:49:57,000 --> 00:49:57,760
Speaker 3: are easy.

1022
00:49:58,000 --> 00:50:01,399
Speaker 2: You want ideas to flow maximum to people to get

1023
00:50:01,520 --> 00:50:03,400
Speaker 2: there faster and do things bigger.

1024
00:50:03,800 --> 00:50:06,960
Speaker 3: The idea is the easy part. The herd execution is

1025
00:50:06,960 --> 00:50:09,359
Speaker 3: the hard part. As the old saying goes, it's one

1026
00:50:09,360 --> 00:50:12,560
Speaker 3: percent inspiration, if not less than one percent and nineteen

1027
00:50:12,600 --> 00:50:13,560
Speaker 3: nine percent perspiration.

1028
00:50:13,920 --> 00:50:16,839
Speaker 4: But I'll say the perspiration part you're really damn good at.

1029
00:50:16,840 --> 00:50:20,080
Speaker 4: Also because you're making you know, the companies you're building

1030
00:50:20,600 --> 00:50:24,640
Speaker 4: are actually building stuff. They're building cars, they're building spaceships,

1031
00:50:24,680 --> 00:50:26,440
Speaker 4: they're building things that if they don't work, it's a

1032
00:50:26,480 --> 00:50:31,279
Speaker 4: real problem. And the precision you manufacture things with, how

1033
00:50:31,280 --> 00:50:33,080
Speaker 4: do you get that level of precision? How do you

1034
00:50:33,120 --> 00:50:36,239
Speaker 4: get how do you build a culture? You're not You're

1035
00:50:36,280 --> 00:50:39,719
Speaker 4: amazing at thinking outside the box. But what's interesting is

1036
00:50:39,760 --> 00:50:43,560
Speaker 4: you may even be better at execution, which is how

1037
00:50:43,560 --> 00:50:45,440
Speaker 4: do you execute so effectively well.

1038
00:50:45,440 --> 00:50:48,799
Speaker 3: I take as expost principles approach to everything. It's not

1039
00:50:48,840 --> 00:50:52,440
Speaker 3: as though I wanted to in source manufacturering, It's just

1040
00:50:52,440 --> 00:50:56,799
Speaker 3: that I was unable to outsource it effectively. So, you know,

1041
00:50:56,880 --> 00:50:58,719
Speaker 3: the idea of the beginning of Tesla was that we

1042
00:50:58,800 --> 00:51:03,040
Speaker 3: would outsource almost all the manufacturing. But then it turned

1043
00:51:03,080 --> 00:51:06,319
Speaker 3: out there was no there were no good companies to

1044
00:51:06,440 --> 00:51:10,319
Speaker 3: outsourced manufacturing too, which there wasn't a really really, it

1045
00:51:10,320 --> 00:51:14,719
Speaker 3: wasn't peaceable. Outsourced manufacturing actually is the exception of the rule.

1046
00:51:15,719 --> 00:51:18,000
Speaker 3: And uh and just over time, we had to insource

1047
00:51:18,040 --> 00:51:21,000
Speaker 3: almost everything for Tesla and same for SpaceX. I became

1048
00:51:21,120 --> 00:51:24,280
Speaker 3: very good at manufacturing because I had to lose no choice.

1049
00:51:24,440 --> 00:51:27,080
Speaker 3: At this point, I might know more about manufacturing than

1050
00:51:27,080 --> 00:51:29,800
Speaker 3: any any human ever has, because I've done so many

1051
00:51:29,880 --> 00:51:32,560
Speaker 3: I've manufactured so many different things, and so many different arenas.

1052
00:51:33,440 --> 00:51:35,359
Speaker 3: I think probably more than anyone ever has.

1053
00:51:35,719 --> 00:51:39,120
Speaker 4: Look, that's that sounds like an astonishing statement, but it's

1054
00:51:39,120 --> 00:51:43,160
Speaker 4: not a crazy statement. And you're somehow running Tesla and

1055
00:51:43,280 --> 00:51:46,920
Speaker 4: running SpaceX and running X and running the boring company

1056
00:51:46,960 --> 00:51:49,240
Speaker 4: and running Nourlink and doing doge.

1057
00:51:49,840 --> 00:51:51,319
Speaker 1: How much do you sleep in a given night?

1058
00:51:51,719 --> 00:51:53,560
Speaker 3: About six hours and average so about.

1059
00:51:53,360 --> 00:51:55,719
Speaker 4: Six So that's it wouldn't have shocked me if you

1060
00:51:55,719 --> 00:51:56,439
Speaker 4: said three or four.

1061
00:51:56,600 --> 00:51:58,319
Speaker 3: So the Crenet struction is how many hours do you

1062
00:51:58,400 --> 00:52:01,400
Speaker 3: work a day? I work almost every working.

1063
00:52:01,120 --> 00:52:04,439
Speaker 4: Hour, and Ben, he's not kidding that. Like when Elan

1064
00:52:04,480 --> 00:52:07,480
Speaker 4: and I were first getting to know each other, I suggested,

1065
00:52:07,560 --> 00:52:09,440
Speaker 4: I said, hey, let let's grab dinner sometime.

1066
00:52:09,480 --> 00:52:10,640
Speaker 1: And I don't know if you remember what you said.

1067
00:52:10,680 --> 00:52:12,440
Speaker 1: You said, I don't eat dinner.

1068
00:52:12,840 --> 00:52:14,760
Speaker 3: I don't have social dinners really.

1069
00:52:14,719 --> 00:52:17,440
Speaker 1: Right, I mean that, Yeah, I mean you obviously eat food, but.

1070
00:52:17,480 --> 00:52:20,200
Speaker 3: Yeah, idea going to a restaurant for two hours, But.

1071
00:52:20,280 --> 00:52:23,200
Speaker 4: The idea of like, I don't, But it was it

1072
00:52:23,239 --> 00:52:25,239
Speaker 4: was just kind of matter of fact, why would I

1073
00:52:25,520 --> 00:52:28,000
Speaker 4: go to dinner like you up?

1074
00:52:28,080 --> 00:52:28,479
Speaker 1: You work?

1075
00:52:28,880 --> 00:52:31,200
Speaker 3: Uh yeah, I literally just thought I'll have lunch and

1076
00:52:31,200 --> 00:52:33,640
Speaker 3: then it brought during meetings and continue being.

1077
00:52:33,600 --> 00:52:36,880
Speaker 2: How many nights have you slept at your offices?

1078
00:52:36,920 --> 00:52:38,880
Speaker 3: You think your career percentage.

1079
00:52:38,320 --> 00:52:40,759
Speaker 2: Wise where you say, I just got to take this

1080
00:52:40,840 --> 00:52:43,080
Speaker 2: nap basically because my body forces me to, and I

1081
00:52:43,120 --> 00:52:45,600
Speaker 2: got to get back to work fast and efficiently without

1082
00:52:45,640 --> 00:52:46,520
Speaker 2: going somewhere else.

1083
00:52:46,880 --> 00:52:50,600
Speaker 3: Well, I guess it started out even with the first company,

1084
00:52:51,160 --> 00:52:53,880
Speaker 3: uh SO two, which is a terrible name, but the

1085
00:52:53,920 --> 00:52:58,040
Speaker 3: first internet company. The we're able to rent an office

1086
00:52:58,440 --> 00:53:01,120
Speaker 3: which was like in a leaky attack, essentially four five

1087
00:53:01,200 --> 00:53:05,439
Speaker 3: hundred dollars a month, and the cheapest apartment we could

1088
00:53:05,440 --> 00:53:08,360
Speaker 3: find just eight hundred dollars a month. So like, and

1089
00:53:08,400 --> 00:53:10,960
Speaker 3: we only had about five thousand dollars between our brother

1090
00:53:10,960 --> 00:53:14,319
Speaker 3: and I, so like, we're not we'll just stay in

1091
00:53:14,320 --> 00:53:17,960
Speaker 3: the office. Yep. So we got some couches that converted

1092
00:53:18,000 --> 00:53:21,759
Speaker 3: into beds and we'd can't sleep at night, and then

1093
00:53:21,760 --> 00:53:25,200
Speaker 3: we just have like turn the beds back into couches

1094
00:53:25,840 --> 00:53:28,880
Speaker 3: before anyone came, and then we would shout the YMCA

1095
00:53:28,960 --> 00:53:31,160
Speaker 3: down the road and so that went that that that

1096
00:53:31,160 --> 00:53:34,440
Speaker 3: that literally was for several months. What we did, it

1097
00:53:34,480 --> 00:53:37,000
Speaker 3: was in great shape, you know, work out the way.

1098
00:53:37,960 --> 00:53:41,360
Speaker 3: I still remember that that YMCA at page Miller al

1099
00:53:41,400 --> 00:53:43,240
Speaker 3: Camino in Palo Alto.

1100
00:53:43,600 --> 00:53:44,560
Speaker 1: So that was a long time.

1101
00:53:44,560 --> 00:53:46,960
Speaker 3: Again, so it's been I don't know. I've never thought

1102
00:53:47,000 --> 00:53:50,279
Speaker 3: to count it, but several hundred days maybe, I don't know.

1103
00:53:50,719 --> 00:53:52,520
Speaker 1: So you're now the richest man on earth.

1104
00:53:52,680 --> 00:53:55,680
Speaker 4: Do you still sleep in the office, Well, that's true,

1105
00:53:56,080 --> 00:53:56,680
Speaker 4: maybe Mars.

1106
00:53:56,680 --> 00:53:58,319
Speaker 1: We'll find someone else, but.

1107
00:53:58,680 --> 00:54:01,160
Speaker 3: I think if someone is a sovereign head of a country,

1108
00:54:01,200 --> 00:54:03,040
Speaker 3: there to facto Richard by Allot.

1109
00:54:03,040 --> 00:54:04,520
Speaker 1: Do you still sleep at the office now?

1110
00:54:04,760 --> 00:54:06,680
Speaker 3: I have sometimes slept at the office. Yeah.

1111
00:54:06,840 --> 00:54:10,160
Speaker 2: As always, thank you for listening to Verdict with Sentner,

1112
00:54:10,200 --> 00:54:12,640
Speaker 2: Ted Cruz, Ben Ferguson with you don't forget to deal

1113
00:54:12,719 --> 00:54:14,920
Speaker 2: with my podcast and you can listen to my podcast

1114
00:54:15,000 --> 00:54:16,960
Speaker 2: every other day you're not listening to Verdict or each

1115
00:54:17,040 --> 00:54:19,480
Speaker 2: day when you listen to Verdict. Afterwards, I'd love to

1116
00:54:19,520 --> 00:54:22,600
Speaker 2: have you as a listener to again the Ben Ferguson podcasts,

1117
00:54:22,600 --> 00:54:25,120
Speaker 2: and we will see you back here on Monday morning.