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Speaker 1: Well, first half, welcome it is Verdict with Ted Cruz,

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Speaker 1: Ben Ferguson with you. Happy New Year's Center to you

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Speaker 1: as well and to everyone listening right now. And we've

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Speaker 1: got a really fun show that we're going to do

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Speaker 1: to day on New Year's and it deals with Waye's

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Speaker 1: fraud and abuse that we talked about that's now becoming

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Speaker 1: a reality in Minnesota months ago with your good friend

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Speaker 1: Elon Musk.

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Speaker 2: Well, Happy New Year to everyone. I hope you had

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Speaker 2: a fantastic New Year's Eve. I hope you stayed safe.

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Speaker 2: I hope you enjoyed time with your family, you celebrate it.

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Speaker 2: I hope you're ready now for an incredible twenty twenty six.

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Speaker 2: I hope that you accomplish something that really makes a difference,

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Speaker 2: That you make a difference in the lives of those

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Speaker 2: around you, you make a difference in the lives of

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Speaker 2: your kids and your community, and you make a real

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Speaker 2: impact fighting for our country. Our country is at a

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Speaker 2: pivotal time, and I hope twenty twenty six is a

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Speaker 2: time where you stand up and say I am going

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Speaker 2: to stand up and defend our nation. Like so many

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Speaker 2: patriots who have preceded me on this New Year's Day,

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Speaker 2: We're going to play one of my favorite podcasts that

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Speaker 2: Bet and I ever did, and this was last year.

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Speaker 2: Last summer, we interviewed Elon Musk. Elon Musk is a

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Speaker 2: good friend of mine. We sat down with him for

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Speaker 2: an hour in the White House, talking to him about

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Speaker 2: Doge and what he was doing with President Trump, but

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Speaker 2: also talking talking to him personally about who he is,

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Speaker 2: about how he built Tesla, how he built SpaceX. We

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Speaker 2: talked to him about AI and killer robots. And it's

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Speaker 2: a fascinating show and we present it to you right

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Speaker 2: now in its entirety.

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Speaker 1: Make sure you download it wherever you get your podcast

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Speaker 1: It's a great episode. It's out right now. Verdict with

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Speaker 1: Ted Cruz wherever you get your podcasts.

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Speaker 2: Well, we're in the White House right now and we're

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Speaker 2: here with my friend Elon Musk, who really has not

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Speaker 2: been doing much of anything, has not made any news

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Speaker 2: is and nobody has noticed the impact.

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Speaker 3: Welcome Elon.

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Speaker 4: Thank you.

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Speaker 3: Holy crap.

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Speaker 4: Oh yes, wow. Let me just say, never a dull moment.

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Speaker 3: Never a dull moment.

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Speaker 2: The first fifty days the president and has spent an

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Speaker 2: office over the top and the first fifty days you've spent.

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Speaker 2: I don't think there's ever been anyone to have an

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Speaker 2: impact the way you have. At the beginning, let me

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Speaker 2: start with a question. You know a lot about which

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Speaker 2: was worse the mess you found at Twitter or the

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Speaker 2: mess you found in the federal government.

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Speaker 4: Well, it's hard to compete with the federal government.

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Speaker 2: What's surprised you about the federal government? I assume you

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Speaker 2: came in and assumed it was bad. Is it worse

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Speaker 2: than you expected?

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Speaker 4: It is worse than I expected. But on the plus side,

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Speaker 4: that means there's more opportunity for improvement. So look, if

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Speaker 4: you look on the bright side, there's actually a lot

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Speaker 4: of opportunity for improvement in federal government expenditures because it's

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Speaker 4: so bad. If it was a well run ship, it

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Speaker 4: would be very difficult to improve. So now it's like

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Speaker 4: people say, well, how will you figure out how to

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Speaker 4: save money in the federal government? Well, it's like being

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Speaker 4: in a room where the walls, the roof, and the

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Speaker 4: floor are old targets. Any direction, yeah, jitness, Wow, Yeah,

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Speaker 4: I'm sure you would agree.

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Speaker 3: So a lot of folks have talked about like like.

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Speaker 4: You can't right, yeah, this is going to any direction?

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Speaker 2: A lot of the crazy expenditures, things like like two

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Speaker 2: million bucks for sex change surgeries in Guatemala. In essential,

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Speaker 2: you know, transgendered mice and sesame street in Iraq.

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Speaker 3: A lot of that has gotten attention.

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Speaker 2: But some of the stuff you've told me about, like

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Speaker 2: tell us about computer licenses and government agencies.

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Speaker 4: Yeah, so most of what do just finding. You don't

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Speaker 4: need to be shock comes. It's very obvious, basic stuff.

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Speaker 4: So in every goblet depopment, I say every because we've

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Speaker 4: not yet found a single exception. There are far too

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Speaker 4: many software licenses and media subscriptions, meaning many more software

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Speaker 4: licenses and media subscriptions than there are humans in the department.

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Speaker 2: Like you were saying, like an agency with fifteen thousand

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Speaker 2: people might have thirty thousand licenses. Yes, and even of

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Speaker 2: the fifteen thousand employees, a good chunk of them hadn't

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Speaker 2: used the license, had never logged on or used the application.

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Speaker 4: Yes, we found entire situations of software licenses or media subscriptions.

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Speaker 4: There were zero logins, so it had and yet we

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Speaker 4: were paying for it. Yes, the government's paying for thousands

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Speaker 4: of licenses of software or media subscriptions and no one

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Speaker 4: had ever logged in even once or credit cards.

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Speaker 3: You found the same thing with government credit cards.

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Speaker 4: We found that there are twice as many credit cards

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Speaker 4: as there are humans could and I still don't have

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Speaker 4: a good explanation for why this is the case. And

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Speaker 4: these are ten thousand dollars limited cards, so it's a

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Speaker 4: lot of money.

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Speaker 1: Is it incompetent that you're finding or is this like

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Speaker 1: the biggest money wandering scheme in the history of the

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Speaker 1: world that you're finding?

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Speaker 4: Okay, I think it's mostly if you say, look, what's

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Speaker 4: the waste to fraud ratio? Yeah, in my opinion, it's

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Speaker 4: it's like eighty percent wasst twenty percent for But you

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Speaker 4: do have these sort of gray areas. For example, example

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Speaker 4: be so, uh, we saw a lot of payments going

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Speaker 4: out of treasury that had no payment code and no

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Speaker 4: explanation for the payment, and then we're we're we're trying

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Speaker 4: to figure out what that payment is and we'd see

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Speaker 4: that Okay, that contract was supposed to be shut off,

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Speaker 4: but but someone forgot to shut off that that contract

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Speaker 4: and so the company kept getting money. Wow. Now is

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Speaker 4: that waste or fraud both? Both?

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Speaker 1: Yeah, you're not.

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Speaker 4: Supposed to get you're not supposed to get it, but

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Speaker 4: you but the government sent it to you and nobody

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Speaker 4: from the government asked for it back. Take for example,

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Speaker 4: the one the one point nine billion dollars given to

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Speaker 4: Stacy Abrams y fake ng O.

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Speaker 5: Utter insanity, explain that story. That's that's just corrupt. I

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Speaker 5: think that's paying off cronies at that point. Yeah, and

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Speaker 5: by the way, she knew, like when you get two

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Speaker 5: billion dollars, you don't miss that.

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Speaker 4: That's not on accident. That's allegedly it was for like, uh,

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Speaker 4: you know, environmentally friendly appliances or something. And they've given

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Speaker 4: like like one hundred appliances so far for two billion dollars.

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Speaker 4: It's very expensive toast roll that's fridge, it's nice. Is

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Speaker 4: It's just obviously one of the biggest scam Ford holes

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Speaker 4: we've uncovered, which is really crazy, is uh? Is that

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Speaker 4: is that the government can give money to a so

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Speaker 4: called nonprofit with with very few controls and then that

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Speaker 4: and there's there's no auditing subsequently of that nonprofit, so

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Speaker 4: there's no So this is where with the you know,

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Speaker 4: one point nine billion of Stacey Arams, who's who's that

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Speaker 4: they didn't give themselves extremely lavished like insane salaries, expense

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Speaker 4: everything yep, to the to the nonprofit you know, buy

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Speaker 4: jets and homes and all sorts of things, live like

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Speaker 4: kings and queens. Yes on the taxpayer, dont correct you.

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Speaker 4: This is happening at scale. It's not just one or two.

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Speaker 4: We're seeing this everywhere.

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Speaker 2: Now, one of the things you told me about is

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Speaker 2: at least what you call say, magic money computers. Well,

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Speaker 2: so tell us about it, because I've never heard of

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Speaker 2: that until you brought that up.

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Speaker 4: Okay, So you may think that these the government computers

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Speaker 4: like all talk to each other, they synchronize, they add

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Speaker 4: up what funds are going somewhere, and it's you know,

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Speaker 4: it's coherent that that that the you know, there's that,

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Speaker 4: and that the numbers, for example, that you're presented as

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Speaker 4: a senator, yeah, are actually the real numbers. And one

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Speaker 4: would think we would think they're not. Yeah, okay, I

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Speaker 4: mean they're not totally wrong, but they're probably off by

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Speaker 4: five percent or ten percent in some cases. So I

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Speaker 4: call it magic money computer. Any computer which can just

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Speaker 4: make money out of thin air best magic money.

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Speaker 3: So how does that work?

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Speaker 4: It just issues payments?

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Speaker 2: And you said something like eleven of these computers of

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Speaker 2: treasury that are that are sending out truellions in payments.

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Speaker 4: They're mostly a treasury, some are with the sum at HHS,

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Speaker 4: some that there's one one of two as states. There's

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Speaker 4: some at DoD. I think we found now fourteen magic

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Speaker 4: money computers Gene. Okay, they just send money out of nothing.

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Speaker 2: You have an ability to see where leverage points are

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Speaker 2: and how things actually happen. So I remember back I

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Speaker 2: think it was September October of this year, before the election.

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Speaker 2: We didn't know who was going to win, and I

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Speaker 2: was at your house in Austin. We were talking about

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Speaker 2: it and you said, you said, look, I don't want

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Speaker 2: a job in Washington, and you said, all I want

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Speaker 2: is the log in for every computer. And I remember

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Speaker 2: thinking at the time that sounded kind of weird, like

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Speaker 2: I just didn't get it. And I have to say,

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Speaker 2: what's interesting on this. If I would have thought like, okay,

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Speaker 2: how do you reform government, like sort of the traditional

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Speaker 2: way to think about it is, okay, give me an

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Speaker 2: ORC chart, let me sit down with the people who

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Speaker 2: are running agencies. And what you saw immediately is to

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Speaker 2: understand what's really going on, get to the payment systems,

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Speaker 2: get to the computers. Yeah, Like, why is getting to

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Speaker 2: the computers so critical to understanding what's actually happening?

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Speaker 4: Well, the government is run by computers, so you've got

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Speaker 4: essentially several hundred computers that effectively run the government. And

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Speaker 4: if you want to know, did you know that then no? Like, yeah,

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Speaker 4: so when somebody, like even when the president issues an

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Speaker 4: executive order, that's going to go through a whole bunch

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Speaker 4: of people until ultimately it is implemented at a computer somewhere.

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Speaker 4: And if you want to know what the situation is

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Speaker 4: with the accounting and you're trying to reconcile accounting and

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Speaker 4: get rid of waist and fraud, you must be able

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Speaker 4: to analyze the computer databases. Otherwise you can't figure it

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Speaker 4: out because all you're doing is asking a human who

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Speaker 4: will then ask another human, ask another human, and finally

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Speaker 4: usually ask some contractor will ask another contractor to your

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Speaker 4: query on the computer. Wow, that's out. Actually, look so

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Speaker 4: it's many layers d. So the only way to reconcile

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Speaker 4: the databases and get rid of waste and fraud is

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Speaker 4: to to actually look at the computers and see what's

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Speaker 4: going on. So that's what I call it. That's like,

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Speaker 4: that's what when I sort of cryptically referred to reprogramming

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Speaker 4: the matrix. You have to understand what's going on the computers.

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Speaker 4: You have to reconcile the computer databases in order to

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Speaker 4: identify the waste and fraud.

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Speaker 2: I don't know that there was anyone in Congress who understood,

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Speaker 2: certainly myself included, who understood the leverage that comes from

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Speaker 2: the computer and the data. In particular, that that Congress

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Speaker 2: would think about give me a report on what your

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Speaker 2: expenditures are rather than actually getting into the pipes. And

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Speaker 2: I think that has been fascinating that it's let you

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Speaker 2: uncover a bunch of craft that just nobody knew.

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Speaker 4: Yes, I mean, in order for money to go to

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Speaker 4: a van acount, it's it's not like we're standing truckloads

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Speaker 4: of cash all over the place where it's a where

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Speaker 4: hiring money. Right, it was sending money through the ach

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Speaker 4: system or through the Swift system. So in order for

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Speaker 4: money to flow, it's going to flow electronically. So that's

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Speaker 4: that's what you need to look at. You can look

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Speaker 4: at the actual electronic money flows.

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Speaker 2: And Tesla and all your companies you have accounting and

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Speaker 2: you have every expenditure. You have it coded for what

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Speaker 2: it's going for. Federal government doesn't work that way. They

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Speaker 2: don't code what.

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Speaker 3: The money's going for.

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Speaker 4: They do not, but they didn't. They didn't.

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Speaker 2: And like one of the things that that you told me,

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Speaker 2: you said, if any company kept its books the way

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Speaker 2: the federal government does, they'd arrest the officers and put

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Speaker 2: them in jail.

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Speaker 4: Yes, if it was a poly company would be dealisted immediately.

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Speaker 4: It would fail, it's ordered, and the officers of the

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Speaker 4: company would be imprisoned. That's the level of enough business

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Speaker 4: in the Unfortunately it's deliberately or do you think this

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Speaker 4: is in competence again, it's eighty percent. It's eighty percent

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Speaker 4: incompetence or in twenty percent malice.

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Speaker 1: If you look at DOGE now and you look at

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Speaker 1: the government and what you're finding, what percentage have you

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Speaker 1: guys even gotten to and how much of it is

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Speaker 1: mars where you haven't even gotten there yet? Because there's

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Speaker 1: so much you're finding out here, I mean, how many

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Speaker 1: you seem like a timeline guy when you say, all right,

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Speaker 1: I want to get in there and get all these

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Speaker 1: you know, numbers and things. How far are we from

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Speaker 1: the in game where you've seen it all, been able

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Speaker 1: to process it all and fix it. I mean are

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Speaker 1: we years away, months away.

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Speaker 4: Not yours, I mean recently confident that we'll be able

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Speaker 4: to get a trillion dollars of waste and forward out,

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Speaker 4: and that meaning that it will have what we'll have

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Speaker 4: a net savings in f I twenty six, which thoughts

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Speaker 4: in October obviously of a trillion dollars provider were allowed

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Speaker 4: to We're allowed to continue and and our progress is

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Speaker 4: not impeded. And we're very public about what we do.

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Speaker 3: Yeah, you put it out on the website about.

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Speaker 4: How we could be more transparent. Literally everything action we do,

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Speaker 4: smaller lodge we put on the doorst dot gov website,

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Speaker 4: and we post on the x handle. And when people

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Speaker 4: complain about it and they say, oh, you're doing something costumes,

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Speaker 4: I'm like, well, which of these costs?

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Speaker 3: Everyone knows exactly what you're doing.

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Speaker 4: Extreme transparent. Yeah, I don't think it's anything's been this

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Speaker 4: transparent ever.

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Speaker 2: So five years ago you were a hero to the left, cool,

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Speaker 2: you had electric cars, you had space, And in five

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Speaker 2: years you've got.

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Speaker 4: To go to a party in Hollywood and not getduddy looks. Yeah.

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Speaker 2: In fact, yeah, and you might's invited, but I don't

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Speaker 2: know if I need to go. And I don't think

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Speaker 2: it's an exaggeration to say today after Donald Trump, the

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Speaker 2: left hates you more than a person on earth.

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Speaker 4: Yes, I appear to be number two. I mean, if

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Speaker 4: you're judged by the various signs.

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Speaker 2: The estrangements, it's Trump arrangement syndrome and elon de arrangement syndrome.

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Speaker 3: How is that for you?

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Speaker 2: That's a little bit of whiplash of going from being

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Speaker 2: like mister cool to the devil incarnate in just a

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Speaker 2: couple of years. Is that is that kind of weird experience,

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Speaker 2: that transformation?

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Speaker 4: Yes?

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Speaker 3: Why do they hate you so much?

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Speaker 4: Well, because we're we're clearly over the target if those

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Speaker 4: was ineffective, if we were not actually getting rid of

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Speaker 4: a bunch of wasting forward and a bunch of that

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Speaker 4: for I mean, the forward reason we're seeing is overwhelmingly

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Speaker 4: on the on the left. I mean, it's it's there's

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Speaker 4: it's not zero on the right. But these NGOs are

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Speaker 4: almost all left wing NGOs that are being funded for example,

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Speaker 4: So they hate me because Doge is being effective and

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Speaker 4: dog is getting rid of a lot of waste for

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Speaker 4: that they were the people and left were taking advantage

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Speaker 4: of that. That's that's that's what it comes out to you.

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Speaker 4: And and the single biggest thing that they're that they're

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Speaker 4: worried about is that doge is is going to turn

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Speaker 4: off fraudulent payments of entitlements. I mean everything from Social Security, medicare, uh,

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Speaker 4: you know, unemployment does ability, smallpers administ registration loans turn

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Speaker 4: them off to illegals. This is that flux of the matter. Yeah, okay,

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Speaker 4: this is this is the this is the thing that

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Speaker 4: why they really hit my guts, want me to die.

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Speaker 2: And do you think that's billions, hundreds of billions? What

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Speaker 2: do you think the scale is of that?

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Speaker 4: I think across the country it's in the it's well,

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Speaker 4: notth of one hundred billion, maybe two hundred million. So

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Speaker 4: by using entitlements fraud, the Democrats have been able to

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Speaker 4: attract and retain vast numbers of illegal immigrants and buy voters,

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Speaker 4: and buy voters exactly the basically bring in ten twenty

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Speaker 4: million people who are beholden to the Democrats for governor

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Speaker 4: handouts and will vote overwhelming the Democrat as has been

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Speaker 4: demonstrated in California. This is it's an election strategy. Yes,

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Speaker 4: it's powered. Yes, and it doesn't take much to turn

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Speaker 4: the swing states blue. I mean off in a swing

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Speaker 4: state yet be won by ten twenty thousand votes. Sure,

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Speaker 4: so if the DAMS can bring in two hundred thousand

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Speaker 4: illegals and over time get them legal legalized, not counting

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Speaker 4: any cheating that takes place, because there is some cheating,

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Speaker 4: but even without cheating, if you bake, if you if

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Speaker 4: you bring in illegals that are ten x the voted

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Speaker 4: differential in a swing state, it will no longer be

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Speaker 4: a swing state, right, and the DAMS will win all

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Speaker 4: the swing states just a matter of time, and America

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Speaker 4: will be permanent deep blue socialist state. At the House,

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Speaker 4: the Senate, YEP, the Presidency, and the Supreme Court will

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Speaker 4: all go hardcore down. They will then further cement that

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Speaker 4: by bringing even more aliens so you can't vote your

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Speaker 4: way out of it.

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Speaker 3: Their objeman is to make one.

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Speaker 4: Party socialist state, and it will be much worse than California,

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Speaker 4: because at least California is mitigated by the fact that

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Speaker 4: someone can leave California.

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Speaker 3: You can go to Texas.

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Speaker 4: Yeah, exactly, you did go to make everywhere California, but

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Speaker 4: worse by the way.

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Speaker 2: The middle of the pandemic, I spent forty five minutes

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Speaker 2: on the phone with Elon. He was still in California.

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Speaker 2: I was walking my dog's snowflake and trying to convince

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Speaker 2: you come to Texas. The commis in California can't stand you.

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Speaker 2: We love you, we want you here. And you didn't

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Speaker 2: quite go then, but you went not that long afterwards.

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Speaker 4: I mean, the COVID actions almost killed Tesla because every

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Speaker 4: other auto plant in the country was a lot of open,

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Speaker 4: but ours, which was in California, was not a lot

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Speaker 4: of open. Wow wow. So they almost killed Tesla.

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Speaker 2: So as a personal matter, do you ever regret it?

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Speaker 2: Like five years ago you go to the Oscars and

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Speaker 2: mister cool and now you've got death threats every day,

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Speaker 2: Like do you well?

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Speaker 4: These days the Oscars are boring. I wouldn't want to go.

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Speaker 3: God bless the movies they nominate.

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Speaker 2: No one on earth has ever seen, Like could they

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Speaker 2: actually nominate a movie that human beings go watch?

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Speaker 4: I mean, how many great movies have come out and

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Speaker 4: last your very.

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Speaker 3: Few, depressingly few, yeah, very few.

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Speaker 4: Last Oscars came and went. I didn't watch it. There's

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Speaker 4: nothing to see.

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Speaker 2: I was sad that Gene Hackman just passed away because

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Speaker 2: Unforgiven was spectacular, but that was a long time ago.

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Speaker 4: Un Forgiven came out.

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Speaker 1: You've mentioned today here and before about the possibility of

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Speaker 1: someone wanting to take you out, dealing with the death threats,

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Speaker 1: we see.

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Speaker 4: It's not in my imagination. You can just look on

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Speaker 4: social media. Yeah, but like is it because very clear?

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Speaker 2: Yeah, And look I'm I'm very familiar with it.

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Speaker 4: And they've got science. They are people with science and

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Speaker 4: demonstrations saying that I need to die.

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Speaker 2: Do you think are these just whack jobs or do

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Speaker 2: you think there are hopefull foreign people? Do you think

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Speaker 2: there are foreign entities behind this? Do you think they're

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Speaker 2: domestic entities behind the threats? And also the attacks to

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Speaker 2: Twitter are not Twitter but Tesla. I mean, you know

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Speaker 2: you're getting Tesla's charging stations lit on fire. Do you

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Speaker 2: think that's organized and paid for?

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Speaker 4: Yes, at least some of it is organized and hate

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Speaker 4: for I think by domestic you know, basically left wing

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Speaker 4: organizations in America funded by uh, left wing billionaires essentially.

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Speaker 3: Is it like Act Blue or what.

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Speaker 4: Act Blue is one of them? You know, Arabella. You

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Speaker 4: know the classic it's funded by the you know, the

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Speaker 4: blue basically the left wing ANDNGO cabal.

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Speaker 1: How big of a threads is to like what you

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Speaker 1: build at Tesla. I mean, I remember when Tesla's came out,

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Speaker 1: it was people that they didn't want to have gas cars.

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Speaker 1: A lot of it was environmental reasons. I jokingly said,

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Speaker 1: I was like, I'm a Texas guy, I'm always going

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Speaker 1: to have something that burns gas. My kids now, all

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Speaker 1: three of my boys think that that Tesla's are awesome.

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Speaker 1: The cyber truck is the car they want their dad

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Speaker 1: to buy, which I laugh because I never could have

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Speaker 1: imagined that five years ago.

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Speaker 3: And now I'm looking at.

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Speaker 2: We're worth the White House in the President's Tesla sparks.

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Speaker 3: Yeah, meaning which is the fullest damp.

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Speaker 1: But I mean, you've changed a generation when you look

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Speaker 1: at my kids are six and eight and they're going

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Speaker 1: Dad buy a cyber truck and I'm considering it. That's

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Speaker 1: a that's a full circle in a weird way.

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Speaker 4: Yeah. Well, I do have this story that the most

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Speaker 4: errantating outcome is the most likely, So yeah, it seems

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Speaker 4: often to be true. What what twist or turn of fate. Well,

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Speaker 4: I would the highest ratings if this was if we're

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Speaker 4: a TV show, what twistal turn of fate would generate

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Speaker 4: the highest ratings that there's a good chance that happens.

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Speaker 2: Well, I will say if if Act Blue and Arabella.

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Speaker 4: Network Blue is a huge scam X level, do you.

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Speaker 2: Think it's foreign money? Chinese money? Where do you think

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Speaker 2: the money in Act Blue is coming from? How do

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Speaker 2: you figure that out?

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Speaker 4: Well, it's not coming from the from a whole bunch

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Speaker 4: of from a ground swell of public support, because when

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Speaker 4: individual donors looked at and Act Blue, they aventually turned

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Speaker 4: out to be like diehard Republicans, people have never given

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Speaker 4: in their life. So you're going to track down a

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Speaker 4: bunch of thesee where it says, oh, I gave sixteen

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Speaker 4: thousand dollars and they're like, I didn't give sixteen thousand dollars.

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Speaker 4: We're talking about this is Well, if those whole con

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Speaker 4: friends of mine, if I found themselves on the Act

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Speaker 4: Blue list, they.

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Speaker 2: Like So that's if it can actually be shown that

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Speaker 2: they are funding firebombing of Tesla charging stations, that's objectively

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Speaker 2: a criminal act, that that is funding terrorist activity, and

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Speaker 2: the statutes make clear that an incendiary device qualifies.

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Speaker 3: So thats down is a terrorist activity.

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Speaker 4: Yeah.

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Speaker 2: Let me ask AI in ten years, how is life

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Speaker 2: going to be different because of AI for just a

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Speaker 2: normal person.

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Speaker 4: Well, ten years is a long time. In ten years,

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Speaker 4: probably AI could do anything better than a human can cognitively,

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Speaker 4: probably almost. I think in ten years, based on the

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Speaker 4: cart rate of improvement, AI will be smarter than the

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Speaker 4: smartest human. Yeah. Yeah. There will also be a massive

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Speaker 4: number of robots, So humanoid robots.

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Speaker 2: By the way, I got to ask, how come your

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Speaker 2: robots look so much like the creepy robots for my robot?

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Speaker 3: Was that intentional or just.

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Speaker 1: I was hoping he's gonna say, yeah, just to mess

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Speaker 1: with you.

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Speaker 4: It's not meant to look like any prior robot. And

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Speaker 4: we'll iterate the design and you'll be able to have

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Speaker 4: a lot of the robot parts are cosmetic. You'll be

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Speaker 4: able to switch out the kind of snap on cosmetic

438
00:22:27,880 --> 00:22:29,760
Speaker 4: parts of the robot make it look like something else.

439
00:22:29,760 --> 00:22:35,320
Speaker 4: I you lying. So there'll be ultimately billions of humanoid

440
00:22:35,440 --> 00:22:39,399
Speaker 4: robots all costs will be self driving in ten years.

441
00:22:39,880 --> 00:22:43,320
Speaker 4: In ten years, probably ninety percent of miles driven will

442
00:22:43,359 --> 00:22:48,600
Speaker 4: be autonomous. Huh wow that fast. Yeah, in five years,

443
00:22:48,640 --> 00:22:52,119
Speaker 4: probably fifty percent of all miles driven will be autonomous.

444
00:22:52,119 --> 00:22:55,000
Speaker 2: Now, if AI will be smarter than any persons, how

445
00:22:55,040 --> 00:22:59,280
Speaker 2: many jobs go away because of that? And what do

446
00:22:59,400 --> 00:23:01,520
Speaker 2: people do if you've got billions of people that are

447
00:23:01,520 --> 00:23:03,760
Speaker 2: losing their jobs like that, a lot of people are

448
00:23:04,000 --> 00:23:05,480
Speaker 2: understandably freaked out about that.

449
00:23:05,840 --> 00:23:11,280
Speaker 4: Well, goods, goods and services will become close to free.

450
00:23:11,760 --> 00:23:14,119
Speaker 4: So it's not as though people will be wanting in

451
00:23:14,240 --> 00:23:17,800
Speaker 4: terms of goods and services. So why is that? What?

452
00:23:17,800 --> 00:23:20,320
Speaker 2: Why are goods and services free in an AI world

453
00:23:20,840 --> 00:23:21,679
Speaker 2: or close to free?

454
00:23:22,040 --> 00:23:24,960
Speaker 4: Well, you have I don't know, call it tens of

455
00:23:24,960 --> 00:23:29,080
Speaker 4: billions of robots that they will They will make you

456
00:23:29,119 --> 00:23:33,520
Speaker 4: anything or provide any service you want for basically next

457
00:23:33,560 --> 00:23:38,560
Speaker 4: to nothing. It's it's not that people will be will

458
00:23:38,560 --> 00:23:40,239
Speaker 4: have a lower stand of living. They'll have actually much

459
00:23:40,320 --> 00:23:45,439
Speaker 4: higher standard of living. But the challenge will be fulfillment.

460
00:23:45,480 --> 00:23:48,120
Speaker 4: How do you drive fulfillment and meeting in life?

461
00:23:48,680 --> 00:23:54,080
Speaker 2: Is skynet real like you get the apocalyptic visions of AI?

462
00:23:55,040 --> 00:23:59,800
Speaker 2: How real is the prospect of killer robots annihilating humanity?

463
00:24:00,320 --> 00:24:05,080
Speaker 4: Twenty percent likely? Maybe ten percent on what timeframe fifty

464
00:24:05,160 --> 00:24:07,119
Speaker 4: ten years so soon.

465
00:24:07,240 --> 00:24:09,920
Speaker 3: Like you you see a world where that's possible.

466
00:24:10,760 --> 00:24:12,240
Speaker 4: Yeah, but I mean you can look at it like

467
00:24:12,280 --> 00:24:16,879
Speaker 4: the glasses eighty ninety percent full, meaning like eighty percent

468
00:24:17,160 --> 00:24:20,560
Speaker 4: likely will have extreme prosperity for all.

469
00:24:21,080 --> 00:24:23,520
Speaker 2: Now, I guess my view, we're in a race to

470
00:24:23,920 --> 00:24:26,840
Speaker 2: win AI. We're in a race with China, and my

471
00:24:27,000 --> 00:24:28,800
Speaker 2: view is, if they're going to be killer robots, I'd

472
00:24:28,840 --> 00:24:33,040
Speaker 2: rather they be American killer robots than Chinese. How likely

473
00:24:33,720 --> 00:24:36,040
Speaker 2: are we winning right now? Is America winning right now?

474
00:24:36,080 --> 00:24:38,359
Speaker 2: And how likely is America to win the race for

475
00:24:38,440 --> 00:24:39,520
Speaker 2: AI visa v.

476
00:24:39,680 --> 00:24:40,560
Speaker 3: China or anyone else?

477
00:24:41,000 --> 00:24:43,240
Speaker 4: Well, the next few years, I think America is likely

478
00:24:43,280 --> 00:24:46,160
Speaker 4: to win. Then it will be a function of who

479
00:24:46,160 --> 00:24:51,359
Speaker 4: controls the AI chip fabrication, the factories that make the

480
00:24:51,359 --> 00:24:54,800
Speaker 4: AI chiefs, who controls them if they are controlled, If

481
00:24:54,800 --> 00:24:57,000
Speaker 4: more of them will controlled by China, than China will win.

482
00:24:57,440 --> 00:24:59,920
Speaker 2: More of the factories that are making the AI chip.

483
00:25:00,040 --> 00:25:01,520
Speaker 2: So you think that will determine it?

484
00:25:01,920 --> 00:25:02,280
Speaker 4: Yes?

485
00:25:02,640 --> 00:25:04,960
Speaker 3: And how are we doing versus China on that front?

486
00:25:05,560 --> 00:25:11,280
Speaker 4: Well, right now almost all the advanced AI chip factories

487
00:25:11,280 --> 00:25:14,720
Speaker 4: they call them fabs are in Taiwan.

488
00:25:14,920 --> 00:25:17,440
Speaker 3: And what if China invades one miles away from Yeah,

489
00:25:17,720 --> 00:25:18,760
Speaker 3: what happens if China?

490
00:25:19,080 --> 00:25:22,439
Speaker 2: If China invades Taiwan, what happens to the world.

491
00:25:22,760 --> 00:25:26,440
Speaker 4: Well, if they were to invade in the niatom, the

492
00:25:26,480 --> 00:25:30,359
Speaker 4: world would be cuttle from advanced AI chips. And currently

493
00:25:30,359 --> 00:25:33,240
Speaker 4: one of advanced AI chips are made in Taiwan.

494
00:25:33,600 --> 00:25:35,520
Speaker 1: How fast can we put that online in America? How

495
00:25:35,520 --> 00:25:37,040
Speaker 1: important is that for national security?

496
00:25:37,520 --> 00:25:40,600
Speaker 4: I think it's essential for national security, and we're not

497
00:25:40,600 --> 00:25:41,160
Speaker 4: doing enough.

498
00:25:41,440 --> 00:25:44,119
Speaker 2: You're fifty three years old. I'm one hundred and eighteen

499
00:25:44,200 --> 00:25:46,080
Speaker 2: days older than you. By what the hell have I

500
00:25:46,119 --> 00:25:46,840
Speaker 2: done in my life?

501
00:25:46,880 --> 00:25:47,080
Speaker 3: I know?

502
00:25:47,200 --> 00:25:47,480
Speaker 4: Right?

503
00:25:47,920 --> 00:25:49,080
Speaker 3: Fifty three years old?

504
00:25:49,320 --> 00:25:49,879
Speaker 4: Pretty well?

505
00:25:51,560 --> 00:25:54,840
Speaker 2: Well, so seventy one was a great year, and I

506
00:25:54,880 --> 00:25:57,720
Speaker 2: was December seventy because I was just just right before

507
00:25:58,160 --> 00:25:59,480
Speaker 2: you were the summer of seventy one.

508
00:26:00,920 --> 00:26:02,879
Speaker 4: I was born sixty nine days after four twenty.

509
00:26:03,280 --> 00:26:05,640
Speaker 3: Wow, I did ask Ben.

510
00:26:06,280 --> 00:26:07,080
Speaker 4: This is look.

511
00:26:09,800 --> 00:26:10,680
Speaker 3: I did ask Ben.

512
00:26:10,720 --> 00:26:12,600
Speaker 2: Should I show up and pull up a joint and say,

513
00:26:13,040 --> 00:26:15,600
Speaker 2: can we beat Rogan's views? But I was pretty sure

514
00:26:16,720 --> 00:26:19,240
Speaker 2: it might cause a scandal if we speak a podcast.

515
00:26:20,040 --> 00:26:21,679
Speaker 4: It just turned out to be like a chocolate cigard.

516
00:26:22,200 --> 00:26:26,840
Speaker 2: Yeah, let me ask you if if today was your

517
00:26:26,880 --> 00:26:27,680
Speaker 2: last day on Earth?

518
00:26:27,960 --> 00:26:29,159
Speaker 4: Yeah, what what?

519
00:26:29,359 --> 00:26:30,800
Speaker 3: I'm not suggesting it's going to be.

520
00:26:30,800 --> 00:26:32,159
Speaker 2: But if it were, what do you think your biggest

521
00:26:32,200 --> 00:26:35,240
Speaker 2: legacy would be if everything you've done one hundred years

522
00:26:35,280 --> 00:26:37,480
Speaker 2: from now? What do you think people would remember if

523
00:26:37,600 --> 00:26:40,600
Speaker 2: if if it were zero to today.

524
00:26:40,440 --> 00:26:43,000
Speaker 1: And were you ever going to space in the.

525
00:26:43,800 --> 00:26:46,320
Speaker 4: In the distant future one hundred or one thousand years ago,

526
00:26:46,880 --> 00:26:50,160
Speaker 4: if SpaceX got humans to Mars, that's what they would

527
00:26:50,240 --> 00:26:53,120
Speaker 4: remember me for. All right, final set of questions.

528
00:26:53,320 --> 00:26:55,840
Speaker 2: Who's the smartest guy you've ever met? You hang out

529
00:26:55,880 --> 00:26:58,080
Speaker 2: with some brilliant people, Like like when you look at

530
00:26:58,160 --> 00:27:00,840
Speaker 2: what's the CEO you look at than yourself?

531
00:27:01,119 --> 00:27:02,440
Speaker 4: What CEO? Do you say?

532
00:27:03,440 --> 00:27:04,640
Speaker 3: Damn, that guy's good.

533
00:27:05,080 --> 00:27:09,959
Speaker 4: Larry Elson's very smart. So I say, Larry Elison's one

534
00:27:09,960 --> 00:27:14,480
Speaker 4: of the smartest people. You know, Larry Page. I mean,

535
00:27:14,520 --> 00:27:15,640
Speaker 4: there are a lot of people that are very smart.

536
00:27:15,640 --> 00:27:18,120
Speaker 4: It's hard to say, Like, you know, I think something

537
00:27:18,119 --> 00:27:21,679
Speaker 4: Toree smart is as smart as so you know what

538
00:27:21,480 --> 00:27:28,200
Speaker 4: if what have they done that is difficult and significant?

539
00:27:28,400 --> 00:27:31,280
Speaker 4: You know, Jeff Bezos has not a lot of difficult

540
00:27:31,320 --> 00:27:34,720
Speaker 4: and significant things. I mean, there are a lot of

541
00:27:34,720 --> 00:27:37,480
Speaker 4: smart humans. I call them smart for smart for a

542
00:27:37,560 --> 00:27:39,320
Speaker 4: human A lot of people who are in the smart

543
00:27:39,359 --> 00:27:40,280
Speaker 4: for a human category.

544
00:27:40,840 --> 00:27:44,120
Speaker 2: All right, final lightning round, Star Wars or Star Trek.

545
00:27:44,640 --> 00:27:46,800
Speaker 4: The first movie I said in a theater was Star Wars,

546
00:27:46,800 --> 00:27:48,520
Speaker 4: so I think it had a profound effect on me.

547
00:27:49,000 --> 00:27:52,159
Speaker 4: I was six years old. I think, imagine, best first

548
00:27:52,160 --> 00:27:55,360
Speaker 4: movie you ever see in a theater is Star Wars.

549
00:27:55,400 --> 00:27:56,280
Speaker 4: It's gonna blaw your mind.

550
00:27:56,359 --> 00:27:57,399
Speaker 3: Best Star Wars.

551
00:27:57,119 --> 00:27:59,800
Speaker 4: Movie Empires tracks Back.

552
00:28:00,080 --> 00:28:01,879
Speaker 3: The only objectively right answer.

553
00:28:01,920 --> 00:28:03,840
Speaker 2: I stood in line in three hours with my dad

554
00:28:03,840 --> 00:28:04,960
Speaker 2: to see it on opening day.

555
00:28:05,800 --> 00:28:08,800
Speaker 4: Kirk or Picard, I like them both.

556
00:28:08,800 --> 00:28:13,560
Speaker 2: For Kirk again, objectively right answer. By the way, James T.

557
00:28:13,720 --> 00:28:16,720
Speaker 2: Kirk is a Republican and Picard is a Democrat, and

558
00:28:16,920 --> 00:28:20,440
Speaker 2: the left gets very mad when I say that best

559
00:28:20,480 --> 00:28:21,200
Speaker 2: Star Trek.

560
00:28:21,000 --> 00:28:23,720
Speaker 4: Movie, I mean the original, the first Star Trek movie.

561
00:28:24,680 --> 00:28:31,840
Speaker 4: That's okayons. Both of both Ratha coons were pretty good.

562
00:28:32,000 --> 00:28:33,600
Speaker 4: But yeah, the original Wratha Khon.

563
00:28:34,080 --> 00:28:38,800
Speaker 3: Ricardo Montalbaan Revenge is a dish best served cold. It

564
00:28:38,920 --> 00:28:43,800
Speaker 3: is very cold in space, although I will say Wrathacon

565
00:28:43,920 --> 00:28:46,360
Speaker 3: is objectively the right answer. But but four as a

566
00:28:46,360 --> 00:28:49,440
Speaker 3: sleeper when they go back to San Francisco and and

567
00:28:49,440 --> 00:28:52,000
Speaker 3: and go find the whales and and you know, Scotty

568
00:28:52,080 --> 00:28:54,760
Speaker 3: picks up spicks, picks up the mouth and talks to

569
00:28:54,800 --> 00:28:58,680
Speaker 3: it and goes a keyboard. How quaint that's a sleeper?

570
00:28:58,720 --> 00:28:59,040
Speaker 4: All right?

571
00:28:59,120 --> 00:29:01,520
Speaker 3: Last question? Did Han shoot first?

572
00:29:03,400 --> 00:29:06,000
Speaker 4: It seemed like he shot second. This is verdict.

573
00:29:06,080 --> 00:29:08,560
Speaker 2: And by the way, I apologized Ben so Ben was

574
00:29:08,600 --> 00:29:10,960
Speaker 2: a jock and played tennis at ole miss and so

575
00:29:10,960 --> 00:29:13,560
Speaker 2: so occasionally when when we geek out a little, I.

576
00:29:13,520 --> 00:29:14,880
Speaker 3: Love watching y'all geek out over.

577
00:29:14,880 --> 00:29:18,560
Speaker 4: There is still on the question, I love you missed

578
00:29:18,560 --> 00:29:21,080
Speaker 4: his The alien miss is flaster shot, So why do

579
00:29:21,080 --> 00:29:22,840
Speaker 4: you miss his flaster shot? Must have been because he

580
00:29:22,880 --> 00:29:26,080
Speaker 4: got shot first. He's missing a point blank bastel shot.

581
00:29:26,200 --> 00:29:28,040
Speaker 4: If they less, they got knocked off kids.

582
00:29:28,040 --> 00:29:31,600
Speaker 2: But it's a question of real shot, which is is

583
00:29:31,680 --> 00:29:34,720
Speaker 2: Han Solo simply a hero or an anti hero? And

584
00:29:34,720 --> 00:29:37,520
Speaker 2: and so I'm in the Han shot first category. I

585
00:29:37,560 --> 00:29:39,320
Speaker 2: think I don't like sanitized stories.

586
00:29:39,320 --> 00:29:41,040
Speaker 4: You would have had to shot first because other way,

587
00:29:41,040 --> 00:29:43,800
Speaker 4: why why would the alien miss a point blank range?

588
00:29:44,240 --> 00:29:46,000
Speaker 3: Are you ever going to go to outer space?

589
00:29:46,080 --> 00:29:47,240
Speaker 1: Is that thing in your life goals?

590
00:29:47,600 --> 00:29:49,040
Speaker 4: Yeah, I'd like to go to Mars at some point,

591
00:29:49,120 --> 00:29:52,080
Speaker 4: And people have said do I want to dine maz

592
00:29:52,880 --> 00:29:54,520
Speaker 4: and I say, yes, just not an impact.

593
00:29:54,760 --> 00:29:57,800
Speaker 2: Now that's a very good answer. The astronauts on the

594
00:29:57,800 --> 00:30:02,520
Speaker 2: space station are they political prisoners? Some of them are

595
00:30:03,600 --> 00:30:05,800
Speaker 2: because because you could have given them a ride back,

596
00:30:05,880 --> 00:30:09,920
Speaker 2: and Joe Biden said no, purely for politics.

597
00:30:10,280 --> 00:30:13,720
Speaker 4: Yeah, I mean, you know, there's been some debate about

598
00:30:13,720 --> 00:30:16,040
Speaker 4: this online. But the thing is that it was very

599
00:30:16,080 --> 00:30:19,080
Speaker 4: a very high level of decision, so it wasn't really

600
00:30:19,120 --> 00:30:23,080
Speaker 4: even an acid decision. It was just that the Biden

601
00:30:23,120 --> 00:30:25,760
Speaker 4: White House did not want to have someone who is

602
00:30:26,120 --> 00:30:31,200
Speaker 4: pro Trump rescuing askorate's rifle before the election, so they

603
00:30:31,240 --> 00:30:31,600
Speaker 4: pushed it.

604
00:30:31,680 --> 00:30:33,240
Speaker 2: Well, if you're one of those astronauts, you got to

605
00:30:33,240 --> 00:30:34,520
Speaker 2: be pretty pissed off about that.

606
00:30:34,920 --> 00:30:40,920
Speaker 4: Well if they're a Democrat, yes, a Democrat, like everything's fine,

607
00:30:40,960 --> 00:30:43,280
Speaker 4: fair enough. So I think one of them is a

608
00:30:43,320 --> 00:30:45,560
Speaker 4: republicable is a Democrat, So it depends on which one

609
00:30:45,600 --> 00:30:45,960
Speaker 4: you ask.

610
00:30:46,240 --> 00:30:48,560
Speaker 2: Well, thank you, Elon, this was this was awesome. And

611
00:30:48,840 --> 00:30:51,960
Speaker 2: let me say, and by the way, I put out

612
00:30:52,000 --> 00:30:54,560
Speaker 2: on X the day before yesterday, if you were having

613
00:30:54,560 --> 00:30:56,400
Speaker 2: a beer with Elon and could ask him anything, what

614
00:30:56,440 --> 00:30:59,600
Speaker 2: would you ask? And got lots of responses. The most

615
00:30:59,640 --> 00:31:04,120
Speaker 2: common response people said is say thank you. Look, Texans

616
00:31:04,120 --> 00:31:06,880
Speaker 2: and the American people appreciate what you're doing. You don't

617
00:31:06,960 --> 00:31:09,120
Speaker 2: have to put up with this BS, and you're doing it.

618
00:31:09,200 --> 00:31:11,800
Speaker 2: I'm grateful you're making a hell of a difference for

619
00:31:11,840 --> 00:31:15,000
Speaker 2: this country. I appreciate you, and the Americans appreciate you.

620
00:31:15,280 --> 00:31:17,520
Speaker 4: Yeah, it's essential for the future of civilization. Otherwise I

621
00:31:17,560 --> 00:31:19,280
Speaker 4: wouldn't be doing it. Yes, it's not like I want

622
00:31:19,320 --> 00:31:20,000
Speaker 4: to get death threats.

623
00:31:20,080 --> 00:31:24,480
Speaker 2: You know, Now, what year does man first set foot

624
00:31:24,520 --> 00:31:24,960
Speaker 2: on Mars?

625
00:31:25,280 --> 00:31:29,720
Speaker 4: I think the soonest would be twenty nine, twenty nine, yes,

626
00:31:30,040 --> 00:31:32,600
Speaker 4: and I don't think it's more than two to four

627
00:31:32,680 --> 00:31:33,400
Speaker 4: years beyond that.

628
00:31:33,680 --> 00:31:36,920
Speaker 2: And that's not an unman, that's a human being putting

629
00:31:37,000 --> 00:31:38,040
Speaker 2: his foot on the surface.

630
00:31:38,280 --> 00:31:39,920
Speaker 4: Yes, best case would be twenty nine.

631
00:31:40,040 --> 00:31:44,040
Speaker 2: And what do you put the odds of finding either

632
00:31:44,080 --> 00:31:46,480
Speaker 2: alien life or evidence of alien life.

633
00:31:46,560 --> 00:31:48,960
Speaker 4: I don't think we're going to find aliens, okay, but.

634
00:31:48,960 --> 00:31:50,760
Speaker 2: Do we find ruins, do we find remnants?

635
00:31:51,040 --> 00:31:52,760
Speaker 4: We may we may find the ruins of a long

636
00:31:52,840 --> 00:31:57,400
Speaker 4: dead alien civilization. That's possible, and we may find subterranean

637
00:31:57,840 --> 00:31:59,480
Speaker 4: microbial life. That's possible.

638
00:31:59,600 --> 00:32:02,240
Speaker 2: All right, if man lands on Mars and twenty nine

639
00:32:02,640 --> 00:32:05,000
Speaker 2: how soon after that do you land on.

640
00:32:04,960 --> 00:32:07,440
Speaker 4: Mars remains to be seen. I'm not sure. The important

641
00:32:07,440 --> 00:32:11,360
Speaker 4: thing is that we build a self sustaining city on

642
00:32:11,400 --> 00:32:16,680
Speaker 4: Mars as quickly as possible. The key threshold is when

643
00:32:16,720 --> 00:32:20,560
Speaker 4: that city can continue to grow, continue to prosper even

644
00:32:20,640 --> 00:32:24,600
Speaker 4: when the supply ships from Earth stopped coming. At that point,

645
00:32:24,800 --> 00:32:27,920
Speaker 4: even if something would happen on Earth, it might It

646
00:32:28,000 --> 00:32:28,920
Speaker 4: might not be World War.

647
00:32:28,880 --> 00:32:32,680
Speaker 3: Three, but it might be that a bad virus.

648
00:32:33,280 --> 00:32:35,440
Speaker 4: Yeah, it might not be anything for those things. It's like,

649
00:32:35,520 --> 00:32:37,560
Speaker 4: lets say, civilization, you could die with a bang or whimper.

650
00:32:37,600 --> 00:32:40,280
Speaker 4: It may be that civilization dies with a whimper rather

651
00:32:40,360 --> 00:32:43,560
Speaker 4: than a bang or and simply loses the ability to

652
00:32:43,880 --> 00:32:47,240
Speaker 4: send ships to Mars. But so you often need Mars

653
00:32:47,240 --> 00:32:49,800
Speaker 4: to become self sustaining and be able to grow by

654
00:32:49,800 --> 00:32:53,880
Speaker 4: itself before the resupply ships from Earth stopped coming. That

655
00:32:54,240 --> 00:32:59,320
Speaker 4: is the critical a civilizational threshold, beyond which the probable

656
00:32:59,360 --> 00:33:01,440
Speaker 4: life span of civilization is much greater.

657
00:33:01,760 --> 00:33:04,520
Speaker 2: And how close are we technologically to be able to

658
00:33:04,560 --> 00:33:08,360
Speaker 2: do that, To have a self sustaining settlement on the

659
00:33:08,360 --> 00:33:09,080
Speaker 2: surface of Mars.

660
00:33:09,320 --> 00:33:11,120
Speaker 4: I think it can be done in twenty years, but.

661
00:33:11,120 --> 00:33:13,480
Speaker 2: It would take twenty years, So we're not in twenty nine,

662
00:33:13,520 --> 00:33:15,360
Speaker 2: We're not there. What are we missing? What are the

663
00:33:15,360 --> 00:33:16,400
Speaker 2: big technologies?

664
00:33:16,600 --> 00:33:19,160
Speaker 4: We don't have a few people running around the surface

665
00:33:19,600 --> 00:33:21,160
Speaker 4: in a hostile environment is not going to make it

666
00:33:21,160 --> 00:33:23,200
Speaker 4: self sustaining. So you're going to need on the order

667
00:33:23,240 --> 00:33:25,800
Speaker 4: of a million people, maybe a million tons of cargo.

668
00:33:26,040 --> 00:33:27,680
Speaker 2: So but you think we could have a million people

669
00:33:27,680 --> 00:33:31,960
Speaker 2: on Mars in twenty years, Yes, And what's the technology

670
00:33:32,000 --> 00:33:34,200
Speaker 2: we're missing right now? When you think about a million

671
00:33:34,200 --> 00:33:36,760
Speaker 2: people on Mars, do we have the ability to get water,

672
00:33:36,840 --> 00:33:39,600
Speaker 2: to get food, to keep them safe? I mean, what

673
00:33:39,880 --> 00:33:41,240
Speaker 2: do we need to make that happen?

674
00:33:41,280 --> 00:33:43,600
Speaker 4: Well, you need to recreate the entire base of industry both.

675
00:33:43,880 --> 00:33:46,960
Speaker 4: So you know, we're here at the top of a

676
00:33:47,000 --> 00:33:51,200
Speaker 4: massive permit of industry that starts with mining a vas

677
00:33:51,320 --> 00:33:55,440
Speaker 4: array of materials, those materials going through hundreds of steps

678
00:33:55,440 --> 00:34:00,560
Speaker 4: of refinement. We grow food, obviously, we grow trees, We

679
00:34:00,640 --> 00:34:03,360
Speaker 4: make things out of the trees. There's you know, you've

680
00:34:03,400 --> 00:34:04,920
Speaker 4: got to You've got to build all that on Mars,

681
00:34:05,040 --> 00:34:07,720
Speaker 4: and Mars is a hostile environment. It's you know, it

682
00:34:07,800 --> 00:34:10,920
Speaker 4: sometimes gets above zero on a warm summer day near

683
00:34:11,000 --> 00:34:13,920
Speaker 4: the equator on Mars, mean it's quite cold. How do

684
00:34:13,960 --> 00:34:16,680
Speaker 4: you prep for that? Well, in the beginning, on Mars,

685
00:34:16,719 --> 00:34:21,160
Speaker 4: you have to have a life support habitation module right

686
00:34:21,360 --> 00:34:23,319
Speaker 4: like you need you can't just live outdoors. You can't

687
00:34:23,360 --> 00:34:26,000
Speaker 4: breathe the air like a dome you think is likely? Yeah,

688
00:34:26,200 --> 00:34:27,279
Speaker 4: glass domes type of thing.

689
00:34:27,440 --> 00:34:31,560
Speaker 2: Have you identified a location on Mars that is likely

690
00:34:31,640 --> 00:34:33,400
Speaker 2: to be ideal for a habitat?

691
00:34:33,880 --> 00:34:38,200
Speaker 4: What might be Arcadia planetare is one of the one

692
00:34:38,239 --> 00:34:41,279
Speaker 4: of the good options. That's one of my daughters is

693
00:34:41,360 --> 00:34:45,200
Speaker 4: named Arcadia after that, and what makes that attractive? My

694
00:34:45,239 --> 00:34:48,440
Speaker 4: eldest son's middle name is Ari's Mars.

695
00:34:48,800 --> 00:34:50,239
Speaker 1: You've been thinking about this for a long time. If

696
00:34:50,239 --> 00:34:51,560
Speaker 1: you're name and your kids around it.

697
00:34:51,719 --> 00:34:54,960
Speaker 4: My eldest kid is middle name is essentially Mars.

698
00:34:55,280 --> 00:34:56,239
Speaker 1: When did you get the dream?

699
00:34:56,360 --> 00:34:58,960
Speaker 4: Like, I mean, there's twenty twenty one soon.

700
00:34:59,320 --> 00:35:00,520
Speaker 1: This is a decad it's old.

701
00:35:00,840 --> 00:35:02,960
Speaker 2: Yeah, dream So like when you were ten, did you

702
00:35:02,960 --> 00:35:04,320
Speaker 2: look up and say I'm going to Mars?

703
00:35:04,680 --> 00:35:08,320
Speaker 4: No? No. I read a lot of science fiction books

704
00:35:08,400 --> 00:35:12,160
Speaker 4: and program computers. But the first finally off, the first

705
00:35:12,239 --> 00:35:15,919
Speaker 4: video game that I sold was a space video game

706
00:35:15,960 --> 00:35:17,920
Speaker 4: called Blastar. Maybe I was born this way?

707
00:35:18,400 --> 00:35:23,080
Speaker 2: How do you do how do you become elon musk? Look,

708
00:35:23,120 --> 00:35:25,479
Speaker 2: you're obviously smart as hell, but but there are lots

709
00:35:25,800 --> 00:35:27,239
Speaker 2: there are a lot of smart people that don't do

710
00:35:27,360 --> 00:35:31,719
Speaker 2: squat and you've managed everything you've touched has been an

711
00:35:31,719 --> 00:35:37,160
Speaker 2: extraordinary success. Yeah, yeah, Look, I mean that's just objectively right.

712
00:35:37,239 --> 00:35:38,520
Speaker 3: So what has led to that?

713
00:35:38,600 --> 00:35:40,640
Speaker 2: Because there are other smart people that that's not true

714
00:35:40,960 --> 00:35:43,120
Speaker 2: and they gaze at their nabel and they don't do anything.

715
00:35:43,239 --> 00:35:45,680
Speaker 2: So what what do you do differently that makes you

716
00:35:45,680 --> 00:35:46,280
Speaker 2: so effective?

717
00:35:46,360 --> 00:35:48,759
Speaker 4: Well, I suppose to have a philosophy of curiosity. I

718
00:35:48,800 --> 00:35:51,280
Speaker 4: want to find out the nature of the universe, understand

719
00:35:51,280 --> 00:35:54,120
Speaker 4: the universe. And in order to do that, we have

720
00:35:54,160 --> 00:35:57,040
Speaker 4: to travel to other planets, see other staw systems, maybe

721
00:35:57,040 --> 00:36:01,239
Speaker 4: other galaxies, find perhaps other aian civilizations or at least

722
00:36:01,239 --> 00:36:04,920
Speaker 4: the remnants of alien civilizations, gain a better understanding of

723
00:36:04,960 --> 00:36:07,440
Speaker 4: worse it's universe going, wherey to come from? And what

724
00:36:07,560 --> 00:36:10,239
Speaker 4: questions do we not yet know to ask about the

725
00:36:10,239 --> 00:36:11,440
Speaker 4: answer that is the universe.

726
00:36:11,760 --> 00:36:15,799
Speaker 2: So let's go back twenty five years, late nineties. You're

727
00:36:15,840 --> 00:36:18,680
Speaker 2: at PayPal. How do you turn PayPal into the success

728
00:36:18,719 --> 00:36:21,319
Speaker 2: it was which then helped launch you to the next one?

729
00:36:21,320 --> 00:36:23,279
Speaker 4: And the next one. Yeah. So I studied physics and

730
00:36:23,360 --> 00:36:26,640
Speaker 4: economics and college, which is a good foundation for understanding

731
00:36:26,640 --> 00:36:30,680
Speaker 4: how the economy works and how reality works. And then

732
00:36:31,600 --> 00:36:36,000
Speaker 4: was going to do a PhD at Stanford in advanced

733
00:36:36,440 --> 00:36:41,840
Speaker 4: ultra capacitors actually as a potential means of energy storage

734
00:36:41,880 --> 00:36:46,120
Speaker 4: for electric transport. Put that on hold to start an

735
00:36:46,120 --> 00:36:49,840
Speaker 4: Internet company. Essentially came to the conclusion that the Internet

736
00:36:50,040 --> 00:36:52,439
Speaker 4: was one of those rare things and I could either

737
00:36:52,480 --> 00:36:55,200
Speaker 4: watch it happen while a grad student or anticipate. And

738
00:36:55,239 --> 00:36:56,920
Speaker 4: I figured, I've always go to back to grad school.

739
00:36:57,160 --> 00:36:58,680
Speaker 4: Grad school is going to be kind of the same.

740
00:36:58,960 --> 00:37:01,719
Speaker 4: But I couldn't bear the thought of just watching the

741
00:37:01,760 --> 00:37:03,600
Speaker 4: Internet happen. So I wanted to be a part of

742
00:37:03,600 --> 00:37:07,120
Speaker 4: building it. So I created an Internet Internet company. We

743
00:37:07,160 --> 00:37:10,799
Speaker 4: did the first maps, directions, yealow pages, white pages on

744
00:37:10,840 --> 00:37:13,160
Speaker 4: the Internet. I actually wrote the first motion of suffware

745
00:37:13,280 --> 00:37:17,040
Speaker 4: just by myself in ninety five, and we ended up

746
00:37:17,080 --> 00:37:20,960
Speaker 4: selling that to Compac Texas Company. I can yeah, for

747
00:37:21,000 --> 00:37:23,359
Speaker 4: about three hundred million dollars in cash about four years

748
00:37:23,360 --> 00:37:27,200
Speaker 4: after I graduated. Wow. So I should say just to

749
00:37:27,239 --> 00:37:29,799
Speaker 4: preface that I graduated with about one hundred thousand dollars

750
00:37:29,840 --> 00:37:32,080
Speaker 4: a student debt. So it wasn't yeah you and me

751
00:37:32,120 --> 00:37:37,360
Speaker 4: a both, yeah, yeah, right, I know. And when I

752
00:37:37,360 --> 00:37:39,680
Speaker 4: first arrived in North America, I arrived with twenty five

753
00:37:39,719 --> 00:37:42,720
Speaker 4: hundred dollars, a bag of books and a bag of clothes.

754
00:37:42,840 --> 00:37:45,080
Speaker 2: All right, so you sell the company for three hundred million,

755
00:37:45,200 --> 00:37:46,720
Speaker 2: How much does that change your life?

756
00:37:46,760 --> 00:37:52,560
Speaker 4: Well? I got twenty one million dollars that jack, But

757
00:37:52,600 --> 00:37:55,440
Speaker 4: I wanted to do more on the internet, so started

758
00:37:55,440 --> 00:37:58,320
Speaker 4: a company called x dot com, which merch with a

759
00:37:58,360 --> 00:38:02,439
Speaker 4: company called Confinity, which is Peter Teel and Max leftun yep.

760
00:38:02,600 --> 00:38:05,680
Speaker 4: And the combined company was actually at first sttle called

761
00:38:05,840 --> 00:38:08,040
Speaker 4: x dot com, but we later later changed the name

762
00:38:08,080 --> 00:38:11,239
Speaker 4: of the company to PayPal. Because of all the name changes,

763
00:38:11,239 --> 00:38:13,560
Speaker 4: it's kind of confusing. But the company that people know

764
00:38:13,680 --> 00:38:17,520
Speaker 4: is know as PayPal today was actually I filed those

765
00:38:17,520 --> 00:38:19,720
Speaker 4: in corporation documents for that company. Interesting.

766
00:38:20,000 --> 00:38:23,000
Speaker 2: Yeah, well, And as you know, Peter Tiel and I

767
00:38:23,080 --> 00:38:25,680
Speaker 2: were buddies back in the mid nineties before he went

768
00:38:25,719 --> 00:38:27,560
Speaker 2: and did any of this. But you know, I became

769
00:38:27,600 --> 00:38:29,680
Speaker 2: friends with him when he was a corporate lawyer in

770
00:38:29,680 --> 00:38:32,160
Speaker 2: New York and just sort of a young libertarian with

771
00:38:32,320 --> 00:38:33,080
Speaker 2: a lot of dreams.

772
00:38:33,360 --> 00:38:36,000
Speaker 4: So it's been a heck of a journey. Yeah yeah,

773
00:38:36,040 --> 00:38:39,440
Speaker 4: And nously, Peter was involved in a coup. You know,

774
00:38:39,560 --> 00:38:42,000
Speaker 4: we had a little sort of knifing in the Senate

775
00:38:42,080 --> 00:38:50,480
Speaker 4: situation where you know that they did cooon met at PayPal.

776
00:38:51,840 --> 00:38:53,920
Speaker 3: I kind of now, did you all make peace after that?

777
00:38:54,000 --> 00:38:56,960
Speaker 4: Yeah? Yeah, yeah. I mean I was doing a lot

778
00:38:56,960 --> 00:38:59,040
Speaker 4: of sort of risky moves that I think ultimately would

779
00:38:59,080 --> 00:39:02,439
Speaker 4: have been successful. But I then went on a two

780
00:39:02,480 --> 00:39:07,840
Speaker 4: week trip which was a dual money raising trip and honeymoon,

781
00:39:07,920 --> 00:39:10,600
Speaker 4: and said not done my honeymoon earlier in the year,

782
00:39:10,760 --> 00:39:13,040
Speaker 4: So it's raising money while doing doing holly honeymoon. But

783
00:39:13,040 --> 00:39:14,920
Speaker 4: I was kind of awake. Did that go over by

784
00:39:14,960 --> 00:39:17,839
Speaker 4: the way it worked? It worked, there you go, kind

785
00:39:17,880 --> 00:39:20,120
Speaker 4: of worked. I raised money, yeah, yeah, and we had

786
00:39:20,160 --> 00:39:23,799
Speaker 4: honeymoon there you go. So yeah, but you don't want

787
00:39:23,800 --> 00:39:26,640
Speaker 4: to be away from the battle when things are scary,

788
00:39:27,880 --> 00:39:29,680
Speaker 4: so I was not there to assuage the concerns of

789
00:39:29,760 --> 00:39:36,239
Speaker 4: the troops. And anyway, we passed things up. And I

790
00:39:36,239 --> 00:39:40,880
Speaker 4: have been friends nonetheless, and you know these days all

791
00:39:40,920 --> 00:39:42,239
Speaker 4: like stay at his house and stuff. So I was

792
00:39:42,239 --> 00:39:45,520
Speaker 4: super friends. And he's also invested in most of my companies.

793
00:39:46,360 --> 00:39:49,040
Speaker 2: All right, So two thousand and two, you start SpaceX,

794
00:39:49,400 --> 00:39:51,479
Speaker 2: Like how do you start a rocket company? Like what's

795
00:39:51,520 --> 00:39:54,040
Speaker 2: the first day where you're like, I want to make

796
00:39:54,120 --> 00:39:55,560
Speaker 2: rockets and I want to go to Mars?

797
00:39:55,600 --> 00:39:56,799
Speaker 3: Like what do you do on day one?

798
00:39:57,000 --> 00:39:58,960
Speaker 4: So I think you have to start with a some

799
00:39:59,000 --> 00:40:02,319
Speaker 4: sort of philosophical premise in order to have in order

800
00:40:02,400 --> 00:40:04,319
Speaker 4: for the in order to be in order to be

801
00:40:04,360 --> 00:40:09,080
Speaker 4: highly motivated, you have to have some philosophical foundation. In

802
00:40:09,080 --> 00:40:12,560
Speaker 4: my case, it was that that we want to expand

803
00:40:12,600 --> 00:40:16,160
Speaker 4: the scale, the scope and scale of consciousness to better

804
00:40:16,239 --> 00:40:19,680
Speaker 4: understand the nature of the universe. And in order to

805
00:40:20,080 --> 00:40:24,280
Speaker 4: expand scale, expand consciousness, we need to go beyond one planet.

806
00:40:24,320 --> 00:40:27,320
Speaker 4: If from one planet there's there's too much risk. You know,

807
00:40:27,360 --> 00:40:30,560
Speaker 4: hopefully Earth civilization prosperos very far into the future, but

808
00:40:30,640 --> 00:40:32,520
Speaker 4: it may not. There's always some risk that we are

809
00:40:32,920 --> 00:40:35,960
Speaker 4: we self annihilate through nuclear war, or that there's a

810
00:40:36,000 --> 00:40:38,279
Speaker 4: big meter that takes us out like the dinosaurs. Yep,

811
00:40:38,480 --> 00:40:40,160
Speaker 4: there's always some risk if all your eggs are in

812
00:40:40,200 --> 00:40:43,080
Speaker 4: one basket. So it's going to be better if we're

813
00:40:43,080 --> 00:40:46,000
Speaker 4: a multiplanet species. And then once we're a multiplanet species

814
00:40:46,000 --> 00:40:47,720
Speaker 4: that the next step would be to be a multi

815
00:40:47,719 --> 00:40:52,440
Speaker 4: stellar and have civilization among on many different star systems.

816
00:40:52,600 --> 00:40:54,640
Speaker 4: So in two thousand and one, I didn't think that

817
00:40:54,680 --> 00:40:56,640
Speaker 4: I could. I didn't think I could sell a rocket companies.

818
00:40:56,680 --> 00:41:00,160
Speaker 4: So I thought I'd take some of the money from paypall.

819
00:41:00,440 --> 00:41:02,719
Speaker 4: In that case, I think it was about one hundred

820
00:41:02,719 --> 00:41:05,759
Speaker 4: and eighty eight million dollars after tax, something like that,

821
00:41:05,920 --> 00:41:08,160
Speaker 4: and I thought, you know, I don't need one hundred

822
00:41:08,160 --> 00:41:10,759
Speaker 4: and eighty million dollars, so I'll spend a bunch of

823
00:41:10,800 --> 00:41:15,520
Speaker 4: it on a philanthropic Mars mission to get the public

824
00:41:15,560 --> 00:41:18,600
Speaker 4: excited about going back to Mars. We're going to Mars,

825
00:41:18,600 --> 00:41:21,319
Speaker 4: I should say, Yeah, Mars was always going to be

826
00:41:21,360 --> 00:41:24,200
Speaker 4: the destination after the Moon. Right. In fact, if you

827
00:41:24,239 --> 00:41:26,840
Speaker 4: told people in nineteen sixty nine that it would be

828
00:41:26,840 --> 00:41:29,040
Speaker 4: twenty twenty five and we've not even gone back to.

829
00:41:29,000 --> 00:41:31,120
Speaker 3: The Moon, let alone, it's hard to believe.

830
00:41:31,040 --> 00:41:33,880
Speaker 4: Let alone Mars, they'd be like what happened in the

831
00:41:33,920 --> 00:41:38,279
Speaker 4: civilization collapse? Top Yeah, Like they would be incomprehensible that

832
00:41:38,320 --> 00:41:40,160
Speaker 4: we've not been to Mars. By now, if you told

833
00:41:40,200 --> 00:41:42,480
Speaker 4: people this after landing on the Moon in sixty.

834
00:41:42,280 --> 00:41:44,480
Speaker 3: Nine, why do you think in fifty years America never

835
00:41:44,520 --> 00:41:45,320
Speaker 3: went back to the moon.

836
00:41:45,400 --> 00:41:48,600
Speaker 4: Well, we destroyed the Saturn five rocket that could take

837
00:41:48,600 --> 00:41:50,520
Speaker 4: people to the moon, and had the Space Shuttle, which

838
00:41:50,520 --> 00:41:53,279
Speaker 4: could only go to lowth orbit, and then there really

839
00:41:53,280 --> 00:41:57,239
Speaker 4: hasn't been anything to replace any No vehicle has been

840
00:41:57,239 --> 00:41:59,960
Speaker 4: made since then that can go to the Moon or

841
00:42:00,080 --> 00:42:04,239
Speaker 4: to Mars until the SpaceX Starship rocket. Yeah, so you

842
00:42:04,320 --> 00:42:05,799
Speaker 4: can't go to Mars if you don't have the ride.

843
00:42:06,080 --> 00:42:09,720
Speaker 2: So I remember you and I first met in twenty

844
00:42:09,760 --> 00:42:12,920
Speaker 2: thirteen when when I was a brand new baby senator. Yeah,

845
00:42:13,040 --> 00:42:15,279
Speaker 2: and I was still down in the basement office. They

846
00:42:15,320 --> 00:42:18,320
Speaker 2: stick freshman senators in the basement office kind of like hazey.

847
00:42:18,400 --> 00:42:19,200
Speaker 4: Yeah, yeah, that's what say.

848
00:42:19,200 --> 00:42:22,000
Speaker 3: It sounds like there are one hundred seared offices. But

849
00:42:22,040 --> 00:42:23,280
Speaker 3: for six months you stay in the basement.

850
00:42:24,120 --> 00:42:27,560
Speaker 1: It's like worry, mean, you know where you're supposed to

851
00:42:27,560 --> 00:42:28,399
Speaker 1: you know, I got to stay.

852
00:42:28,400 --> 00:42:30,120
Speaker 2: Now, thirteen years into it, I think there's a lot

853
00:42:30,120 --> 00:42:33,480
Speaker 2: of wisdom to doing that. But you were down in

854
00:42:33,480 --> 00:42:35,319
Speaker 2: the basement office, and I remember you were coming and

855
00:42:35,320 --> 00:42:38,120
Speaker 2: sitting down with SpaceX and at the time the Air

856
00:42:38,160 --> 00:42:40,759
Speaker 2: Force was not letting y'all bid to launch satellites, and

857
00:42:40,800 --> 00:42:42,840
Speaker 2: so you were coming and saying, look, we got a company.

858
00:42:42,880 --> 00:42:44,279
Speaker 2: I think we can do a really good job of this,

859
00:42:44,360 --> 00:42:46,640
Speaker 2: and yet we're locked out of this. It's a little

860
00:42:46,680 --> 00:42:50,080
Speaker 2: amazing to think the journey SpaceX is gone from then

861
00:42:50,280 --> 00:42:50,760
Speaker 2: to now.

862
00:42:51,239 --> 00:42:53,160
Speaker 4: Yes, it's hard to believe that this is all real

863
00:42:54,400 --> 00:42:57,960
Speaker 4: because originally, consistently with I believe that we need to

864
00:42:58,000 --> 00:43:00,400
Speaker 4: become a multiplant species, I thought the only way to

865
00:43:00,400 --> 00:43:03,200
Speaker 4: do that would be through NASA sou and I think

866
00:43:03,280 --> 00:43:05,760
Speaker 4: I thought, well, if I just get the public excited

867
00:43:05,800 --> 00:43:08,640
Speaker 4: about Mars, then they'll do a mission to Mars. And

868
00:43:09,239 --> 00:43:11,239
Speaker 4: so initially my thought was to have to send a

869
00:43:11,239 --> 00:43:15,799
Speaker 4: small greenhouse with seeds and dehydrated nutrient gel. Then land

870
00:43:16,040 --> 00:43:19,279
Speaker 4: the greenhouse, hydrate the seeds, and you see these the

871
00:43:19,320 --> 00:43:21,520
Speaker 4: sort of money shot proof. The money shot would be

872
00:43:21,640 --> 00:43:25,239
Speaker 4: green plants on a red background. I also recently knowned

873
00:43:25,280 --> 00:43:29,080
Speaker 4: that money shot has a different meaning in some other arenas.

874
00:43:29,080 --> 00:43:35,719
Speaker 4: But yeah, story, But what I'm trying to say is

875
00:43:36,160 --> 00:43:40,080
Speaker 4: the captivating shot would be the green plants on a

876
00:43:40,120 --> 00:43:43,120
Speaker 4: red background. And then hopefully that would if you did

877
00:43:43,120 --> 00:43:45,200
Speaker 4: something like that, that would get the public excited about Mars,

878
00:43:45,200 --> 00:43:47,520
Speaker 4: that would increase NASA's budget and then we could send

879
00:43:47,520 --> 00:43:50,760
Speaker 4: people to Mars. Dream was nasty to do this? Yes,

880
00:43:51,000 --> 00:43:55,200
Speaker 4: not you No, The original original plan was literally to

881
00:43:55,560 --> 00:43:58,239
Speaker 4: take a bunch of the money from PayPal and I

882
00:43:58,280 --> 00:44:02,440
Speaker 4: guess by some people's definition way with no profit on

883
00:44:02,480 --> 00:44:05,239
Speaker 4: a non profit thing to I wanted to spend a

884
00:44:05,239 --> 00:44:07,160
Speaker 4: whole bunch of my money for free to get nasta's

885
00:44:07,160 --> 00:44:10,120
Speaker 4: budget to be bigger so we could go to friggin Mars. Right, wow,

886
00:44:10,760 --> 00:44:13,040
Speaker 4: that's what I wanted. So that was the holy Grail,

887
00:44:13,280 --> 00:44:14,920
Speaker 4: That's what I wanted. I was like, so when did

888
00:44:14,960 --> 00:44:18,239
Speaker 4: I Mars? That's what I wanted to know? Well, when

889
00:44:18,360 --> 00:44:18,880
Speaker 4: when did.

890
00:44:18,719 --> 00:44:20,879
Speaker 3: It strike you? Okay, you're going to have to do this.

891
00:44:20,880 --> 00:44:22,839
Speaker 4: If you want, I'll tell you. It gets crazier, all right,

892
00:44:22,840 --> 00:44:25,319
Speaker 4: it gets crazier so so that I couldn't afford any

893
00:44:25,320 --> 00:44:26,759
Speaker 4: of the US rockets because as you know, the US

894
00:44:26,840 --> 00:44:29,839
Speaker 4: rockets are way too expensive, boying rock Lucky rockets are

895
00:44:29,840 --> 00:44:31,880
Speaker 4: crazy money. I didn't have. I didn't even even with

896
00:44:31,880 --> 00:44:33,520
Speaker 4: one hundred eighty millions, So way I could have afforded

897
00:44:33,920 --> 00:44:39,720
Speaker 4: they back then, well, the with with the additional stage

898
00:44:39,719 --> 00:44:41,040
Speaker 4: to get to Mars, it would have been about like

899
00:44:41,040 --> 00:44:43,800
Speaker 4: eighty million, So technically I could have afforded one of them,

900
00:44:43,840 --> 00:44:45,840
Speaker 4: but I wanted to do too in case one of

901
00:44:45,840 --> 00:44:49,000
Speaker 4: them didn't work. Yeah. So and then I didn't have

902
00:44:49,080 --> 00:44:50,680
Speaker 4: enough money for that. Yeah, and I was sort of

903
00:44:50,680 --> 00:44:54,200
Speaker 4: prepared to, you know, I don't know, waste half the money.

904
00:44:55,239 --> 00:44:57,000
Speaker 4: And I think if I had ninety million left, that'd

905
00:44:57,000 --> 00:44:59,719
Speaker 4: be fine, you know, but ideally on all of it.

906
00:45:00,320 --> 00:45:03,840
Speaker 4: So I went to Russia twice to try to buy ICBMs.

907
00:45:04,960 --> 00:45:05,560
Speaker 3: How did that go?

908
00:45:05,960 --> 00:45:08,720
Speaker 4: And who do you call? The Russian rocket forces?

909
00:45:09,280 --> 00:45:11,080
Speaker 3: Do they sell ICBMs? Does that work?

910
00:45:11,280 --> 00:45:11,560
Speaker 4: Yeah?

911
00:45:13,120 --> 00:45:14,719
Speaker 1: You got to tell us a story that I want

912
00:45:14,719 --> 00:45:17,640
Speaker 1: to know who you can buy anything in Russia?

913
00:45:17,719 --> 00:45:21,040
Speaker 3: Yeah, I like, please walk me down that.

914
00:45:21,200 --> 00:45:23,040
Speaker 1: I want to know how you made that phone call

915
00:45:23,120 --> 00:45:24,960
Speaker 1: and when you get there, how did that work?

916
00:45:24,960 --> 00:45:27,440
Speaker 4: And what do you tell your friends? Yeah, listen, I'm

917
00:45:27,480 --> 00:45:30,160
Speaker 4: going to Russian device in ICBMs. I might not return,

918
00:45:30,480 --> 00:45:36,680
Speaker 4: you know, in this situation. Literally, Yeah, So I guess

919
00:45:36,719 --> 00:45:41,360
Speaker 4: slightly less insane when you when you understand that the

920
00:45:41,440 --> 00:45:45,400
Speaker 4: Russians had to demolish a bunch of their ICBMs because

921
00:45:45,440 --> 00:45:48,800
Speaker 4: of uh, you know, soul talks like the people because

922
00:45:49,040 --> 00:45:53,040
Speaker 4: basically an agreementtween the United States and Russia to reduce

923
00:45:53,080 --> 00:45:56,200
Speaker 4: the total number of ICBMs. Russia was actually obligated to

924
00:45:56,719 --> 00:45:58,920
Speaker 4: scrap a bunch of their ICBMs. So you took it

925
00:45:59,000 --> 00:46:02,320
Speaker 4: the very biggest CBMs. You could converte those into a rocket,

926
00:46:02,480 --> 00:46:05,240
Speaker 4: added additional stage and send something to Mars.

927
00:46:05,440 --> 00:46:07,960
Speaker 3: So those are big enough with one more stage to

928
00:46:08,000 --> 00:46:08,880
Speaker 3: get to Mars.

929
00:46:09,120 --> 00:46:11,279
Speaker 4: To send a small payload to Mars. Yeah, so the

930
00:46:11,400 --> 00:46:12,040
Speaker 4: s S eighteen.

931
00:46:12,440 --> 00:46:14,799
Speaker 2: So you try to buy CBMs, do you succeed or no?

932
00:46:15,040 --> 00:46:16,920
Speaker 2: Or do you figure out you got to build your

933
00:46:16,960 --> 00:46:17,520
Speaker 2: own instead?

934
00:46:17,800 --> 00:46:21,279
Speaker 4: They kept raising the price on me, so because I

935
00:46:21,280 --> 00:46:22,800
Speaker 4: figured like, look, they're going to throw these things to

936
00:46:22,840 --> 00:46:25,880
Speaker 4: scrappy on anyway, you should get a really good deal, right.

937
00:46:26,760 --> 00:46:30,480
Speaker 4: So the price thoughted out at four million, Then the

938
00:46:30,480 --> 00:46:32,919
Speaker 4: next conversation they were at eight million. Then the next

939
00:46:32,920 --> 00:46:35,640
Speaker 4: conversation they were at like nineteen million, and I'm like,

940
00:46:35,800 --> 00:46:37,000
Speaker 4: this is before we signed a contract.

941
00:46:37,040 --> 00:46:39,680
Speaker 2: By the way, was there another Was there another bidd

942
00:46:39,760 --> 00:46:41,160
Speaker 2: or were you the only one trying to buy them?

943
00:46:41,520 --> 00:46:43,399
Speaker 4: I think I don't know if there were other bits,

944
00:46:43,400 --> 00:46:45,960
Speaker 4: but they didn't mention any other bits. But I was like, man,

945
00:46:45,960 --> 00:46:48,719
Speaker 4: if the price is increasing this much before the contract signed.

946
00:46:49,200 --> 00:46:51,319
Speaker 4: I'm really going to get fleeced after the contracts. Yeah,

947
00:46:51,640 --> 00:46:56,280
Speaker 4: so I got pretty frustrated there. Actually, in some cases

948
00:46:56,280 --> 00:47:01,120
Speaker 4: we got into like shouting matches in Moscow, some guys

949
00:47:01,160 --> 00:47:03,120
Speaker 4: shouting at me in Russian and I'm shouting back at

950
00:47:03,160 --> 00:47:08,440
Speaker 4: him really badly, you know, I'm like.

951
00:47:08,680 --> 00:47:10,719
Speaker 1: So you are all I mean, you're all.

952
00:47:14,400 --> 00:47:18,960
Speaker 4: In Moscow? Yeah, so uh man, I should have recorded

953
00:47:18,960 --> 00:47:20,239
Speaker 4: that. That would have been one for them.

954
00:47:20,280 --> 00:47:22,479
Speaker 1: How many days were you there negotiating that first time?

955
00:47:22,640 --> 00:47:24,600
Speaker 1: I mean was just like ongoing, Yeah.

956
00:47:24,520 --> 00:47:27,680
Speaker 4: Yeah, is this this took place. These conversations took place

957
00:47:27,680 --> 00:47:32,200
Speaker 4: over probably six months or so. Wow. So and then

958
00:47:32,239 --> 00:47:35,960
Speaker 4: the final trip trip there was with the with was

959
00:47:35,960 --> 00:47:41,000
Speaker 4: with Mike Revenue later became as administrator. I actually realized

960
00:47:41,080 --> 00:47:44,200
Speaker 4: in the course of this that my original premise was wrong,

961
00:47:44,440 --> 00:47:47,239
Speaker 4: that that America actually has plenty of will to go

962
00:47:47,280 --> 00:47:50,040
Speaker 4: to Mars, but needs that it just needs a way

963
00:47:50,600 --> 00:47:54,920
Speaker 4: to Mars that is affordable and that doesn't break the budget.

964
00:47:54,960 --> 00:47:56,359
Speaker 3: You know, just as you know, we couldn't even get

965
00:47:56,360 --> 00:47:58,239
Speaker 3: to the space station. We needed the Russians to to

966
00:47:58,440 --> 00:47:59,720
Speaker 3: get us to our own space station.

967
00:47:59,800 --> 00:48:00,480
Speaker 4: That was Parsonal.

968
00:48:00,600 --> 00:48:01,760
Speaker 3: It really was pitiful.

969
00:48:01,920 --> 00:48:04,319
Speaker 4: I'm not sure most Americans know just how much we're

970
00:48:04,360 --> 00:48:05,840
Speaker 4: being fleeced. Like I think they got up to like

971
00:48:05,920 --> 00:48:09,440
Speaker 4: ninety million dollars a seat, Yeah wow, Yeah, for a

972
00:48:09,440 --> 00:48:09,879
Speaker 4: seat that.

973
00:48:09,800 --> 00:48:14,080
Speaker 3: Cost them like tenre obviously, but it was the only Yeah.

974
00:48:13,880 --> 00:48:17,640
Speaker 4: It was before SpaceX's ninety million dollars a seat for

975
00:48:17,719 --> 00:48:20,919
Speaker 4: a seat that cost him ten million. Is high. Yeah,

976
00:48:21,360 --> 00:48:23,279
Speaker 4: that's a lot of money. Yeah.

977
00:48:23,360 --> 00:48:25,720
Speaker 2: So a few months ago you and I were down

978
00:48:26,000 --> 00:48:29,320
Speaker 2: in Bocachica with a president for a starship launch, and

979
00:48:29,800 --> 00:48:32,319
Speaker 2: it is incredible what you built in Boca Chica. You know,

980
00:48:32,680 --> 00:48:34,879
Speaker 2: five years ago it was an empty beach.

981
00:48:35,000 --> 00:48:36,680
Speaker 4: At the southern tip of this soundbar.

982
00:48:36,760 --> 00:48:40,200
Speaker 2: Yeah, and it's now a city and a factory where

983
00:48:40,239 --> 00:48:43,520
Speaker 2: you're building a rocket ship a month with incredible precision.

984
00:48:44,160 --> 00:48:45,879
Speaker 2: But one of the things you said to me when

985
00:48:45,880 --> 00:48:47,600
Speaker 2: we were down there that really stood out to me

986
00:48:47,840 --> 00:48:51,879
Speaker 2: is is you said your philosophy on intellectual property talked

987
00:48:51,880 --> 00:48:54,320
Speaker 2: to lots of CEOs or like we fight to guard

988
00:48:54,320 --> 00:48:57,200
Speaker 2: our IP, and you had a very different approach. What's

989
00:48:57,280 --> 00:48:58,319
Speaker 2: what's your view of IP?

990
00:48:58,760 --> 00:49:03,280
Speaker 4: Patterns of the week patents for those who innovate slowly.

991
00:49:03,600 --> 00:49:06,719
Speaker 2: I literally do not know anyone else in business who

992
00:49:06,719 --> 00:49:08,560
Speaker 2: would say something like that, like like it was a

993
00:49:08,920 --> 00:49:11,920
Speaker 2: startling and and and what Elon said down there is

994
00:49:11,960 --> 00:49:14,880
Speaker 2: he said, look this stuff, I assume everyone will steal everything,

995
00:49:14,920 --> 00:49:16,439
Speaker 2: but by the time they steal it will be five

996
00:49:16,480 --> 00:49:17,960
Speaker 2: generations beyond and it won't matter.

997
00:49:18,080 --> 00:49:21,680
Speaker 4: Yes, at Tesla, we actually open sourced law of patents.

998
00:49:21,680 --> 00:49:24,000
Speaker 4: So we said our patents are anyone can use it

999
00:49:24,080 --> 00:49:27,279
Speaker 4: for free. Really yeah, uh, the only we only do

1000
00:49:27,360 --> 00:49:32,160
Speaker 4: patents at Tesla to avoid patent trolls causing causing trouble.

1001
00:49:32,920 --> 00:49:35,600
Speaker 4: So we'll try to look ahead and say, okay, patent

1002
00:49:35,600 --> 00:49:38,560
Speaker 4: trolls are going to trial patent file patterns to blocks

1003
00:49:38,640 --> 00:49:40,520
Speaker 4: and things, will file patents and then open source to

1004
00:49:40,800 --> 00:49:42,840
Speaker 4: make it free. I mean, I'm gonna say patents for

1005
00:49:42,880 --> 00:49:46,120
Speaker 4: the week. Now. There are a few cases, in say

1006
00:49:46,320 --> 00:49:48,680
Speaker 4: with pharmaceuticals, where it might cost you a billion dollars

1007
00:49:48,680 --> 00:49:52,480
Speaker 4: to do a phase three human file, but then subsequently

1008
00:49:52,600 --> 00:49:56,399
Speaker 4: the drug is very cheap to manufacture. So cases there

1009
00:49:56,400 --> 00:49:59,239
Speaker 4: are some, in my opinion, which would massively reduce what

1010
00:49:59,320 --> 00:50:03,479
Speaker 4: can be patented. And and say, because the whole point

1011
00:50:03,480 --> 00:50:07,600
Speaker 4: of patenting is to maximize innovation, not inhibit it. And

1012
00:50:08,160 --> 00:50:12,480
Speaker 4: in my opinion, maybe a controversial opinion. Most patents inhibit innovation,

1013
00:50:12,560 --> 00:50:15,680
Speaker 4: they do not help it. But there are case I

1014
00:50:15,680 --> 00:50:17,960
Speaker 4: want to do one a single cases like we're such

1015
00:50:17,960 --> 00:50:19,920
Speaker 4: as a phase three clinical trial that might cost a

1016
00:50:19,920 --> 00:50:22,839
Speaker 4: billion dollars, but then the drugs thereafter cost a few

1017
00:50:22,840 --> 00:50:27,000
Speaker 4: dollars to manufacture, and if you can then immediately copy

1018
00:50:27,040 --> 00:50:28,879
Speaker 4: those drugs for a few dollars, no one will pay

1019
00:50:28,880 --> 00:50:32,040
Speaker 4: for the billion dollars. Write problem. Free writer problem, yeah, exactly,

1020
00:50:32,080 --> 00:50:33,960
Speaker 4: So you have to address the free writer problem. But

1021
00:50:34,120 --> 00:50:36,360
Speaker 4: other than that, there should be no patents. The ideas

1022
00:50:36,360 --> 00:50:37,160
Speaker 4: are easy.

1023
00:50:37,400 --> 00:50:40,759
Speaker 1: You want ideas to flow maximum to people, to get

1024
00:50:40,880 --> 00:50:42,760
Speaker 1: there faster and do things bigger.

1025
00:50:43,160 --> 00:50:46,320
Speaker 4: The idea is the easy part. The herd execution is

1026
00:50:46,320 --> 00:50:48,719
Speaker 4: the hard part. As the old saying goes, it's one

1027
00:50:48,719 --> 00:50:51,920
Speaker 4: percent inspiration, if not less than one percent, and nineteen

1028
00:50:51,960 --> 00:50:52,960
Speaker 4: nine percent perspiration.

1029
00:50:53,280 --> 00:50:56,200
Speaker 2: But I'll say the perspiration part you're really damn good at.

1030
00:50:56,200 --> 00:50:59,400
Speaker 2: Also because you're making. You know, the companies you're building

1031
00:51:00,080 --> 00:51:04,000
Speaker 2: are actually building stuff. They're building cars, they're building spaceships,

1032
00:51:04,040 --> 00:51:05,799
Speaker 2: they're building things that if they don't work, it's a

1033
00:51:05,840 --> 00:51:10,640
Speaker 2: real problem. And the precision you manufacture things with, how

1034
00:51:10,640 --> 00:51:12,440
Speaker 2: do you get that level of precision? How do you

1035
00:51:12,480 --> 00:51:15,600
Speaker 2: get how do you build a culture? You're not You're

1036
00:51:15,640 --> 00:51:19,080
Speaker 2: amazing at thinking outside the box. But what's interesting is

1037
00:51:19,120 --> 00:51:22,040
Speaker 2: your you may even be better at execution, which is

1038
00:51:22,719 --> 00:51:24,480
Speaker 2: how do you execute so effectively?

1039
00:51:24,640 --> 00:51:28,040
Speaker 4: Well? I take as express principles approach to everything. It's

1040
00:51:28,080 --> 00:51:31,680
Speaker 4: not as though I wanted to in source manufacturing. It's

1041
00:51:31,680 --> 00:51:35,640
Speaker 4: just that I was unable to outsource it effectively. So uh.

1042
00:51:36,000 --> 00:51:37,600
Speaker 4: You know, the idea of the beginning of Tesla was

1043
00:51:37,640 --> 00:51:41,879
Speaker 4: that we would outsource almost all the manufacturing. But then

1044
00:51:42,040 --> 00:51:44,560
Speaker 4: it turned out there was no there were no good

1045
00:51:45,040 --> 00:51:49,560
Speaker 4: companies to outsourced manufacturing too, which there wasn't a really really,

1046
00:51:49,560 --> 00:51:53,680
Speaker 4: it wasn't peaceable outsourced manufacturing actually is the exception of

1047
00:51:53,719 --> 00:51:56,839
Speaker 4: the rule. And uh. And just over time, we had

1048
00:51:56,880 --> 00:51:59,680
Speaker 4: to in source almost everything for Tesla, and same for SpaceX.

1049
00:52:00,040 --> 00:52:02,520
Speaker 4: It became very good at manufacturing because I had to

1050
00:52:03,000 --> 00:52:05,000
Speaker 4: was no choice. At this point. I might know more

1051
00:52:05,000 --> 00:52:08,359
Speaker 4: about manufacturing than any any human ever has, because I've

1052
00:52:08,440 --> 00:52:10,840
Speaker 4: done so many I've manufactured so many different things and

1053
00:52:10,920 --> 00:52:13,920
Speaker 4: so many different arenas. I think probably more than anyone

1054
00:52:14,239 --> 00:52:14,719
Speaker 4: ever has.

1055
00:52:15,080 --> 00:52:18,480
Speaker 2: Look, that's that sounds like an astonishing statement, but it's

1056
00:52:18,480 --> 00:52:22,520
Speaker 2: not a crazy statement, and you're somehow running Tesla and

1057
00:52:22,640 --> 00:52:26,280
Speaker 2: running SpaceX and running X and running the boring company

1058
00:52:26,320 --> 00:52:29,759
Speaker 2: and running Dourlink and doing doge. How much do you

1059
00:52:29,800 --> 00:52:30,680
Speaker 2: sleep in a given night?

1060
00:52:31,080 --> 00:52:32,640
Speaker 4: About six hours and average.

1061
00:52:32,320 --> 00:52:34,840
Speaker 2: So about six So that's it wouldn't have shocked me

1062
00:52:34,880 --> 00:52:35,759
Speaker 2: if you said three or four.

1063
00:52:35,960 --> 00:52:37,680
Speaker 3: So the Crenet question is how many hours do you

1064
00:52:37,760 --> 00:52:38,359
Speaker 3: work a day?

1065
00:52:38,680 --> 00:52:40,759
Speaker 4: I work almost every working.

1066
00:52:40,480 --> 00:52:43,239
Speaker 3: Hour, and Ben, he's not kidding at that.

1067
00:52:43,320 --> 00:52:44,880
Speaker 2: Like when Elan and I were first getting to know

1068
00:52:44,920 --> 00:52:48,800
Speaker 2: each other, I suggested, I said, hey, let's grab dinner sometime.

1069
00:52:48,840 --> 00:52:50,000
Speaker 3: And I don't know if you remember what you said.

1070
00:52:50,040 --> 00:52:51,800
Speaker 3: You said, I don't eat dinner.

1071
00:52:52,200 --> 00:52:54,200
Speaker 4: I don't have social dinners really.

1072
00:52:54,080 --> 00:52:56,680
Speaker 3: Right, I mean that, yeah, I mean you obviously eat food,

1073
00:52:56,719 --> 00:52:59,680
Speaker 3: but yeah, idea going to a restaurant for two hours.

1074
00:52:59,440 --> 00:53:02,560
Speaker 2: But the idea like, I don't, But it was it

1075
00:53:02,600 --> 00:53:04,600
Speaker 2: was just kind of matter of fact. Why would I

1076
00:53:04,880 --> 00:53:07,839
Speaker 2: go to dinner like you'd jump you work?

1077
00:53:08,440 --> 00:53:10,719
Speaker 4: Yeah, I literally just thought I'll have lunch, and then

1078
00:53:10,719 --> 00:53:13,000
Speaker 4: it brought during meetings and continue being.

1079
00:53:12,960 --> 00:53:16,239
Speaker 1: How many nights have you slept at your offices?

1080
00:53:16,280 --> 00:53:18,239
Speaker 4: You think your career percentage.

1081
00:53:17,680 --> 00:53:20,120
Speaker 1: Wise where you say, I just got to take this

1082
00:53:20,200 --> 00:53:22,440
Speaker 1: nap basically because my body forces me to, and I

1083
00:53:22,480 --> 00:53:24,960
Speaker 1: got to get back to work fast and efficiently without

1084
00:53:25,000 --> 00:53:25,879
Speaker 1: going somewhere else.

1085
00:53:26,239 --> 00:53:29,560
Speaker 4: Well, I guess it started out. Even with the first

1086
00:53:29,560 --> 00:53:33,239
Speaker 4: company H two, which is a terrible name, but the

1087
00:53:33,280 --> 00:53:37,400
Speaker 4: first internet company. We were able to rent an office,

1088
00:53:37,800 --> 00:53:40,480
Speaker 4: which was like in a leaky attack essentially for five

1089
00:53:40,560 --> 00:53:44,799
Speaker 4: hundred dollars a month, and the cheapest apartment we could

1090
00:53:44,800 --> 00:53:47,719
Speaker 4: find was eight hundred dollars a month. So like and

1091
00:53:47,760 --> 00:53:50,319
Speaker 4: we only had about five thousand dollars between our brother

1092
00:53:50,320 --> 00:53:53,600
Speaker 4: and I. Oh, so like we're not We'll just stay

1093
00:53:53,600 --> 00:53:56,920
Speaker 4: in the office. Yeah, So we got some couches that

1094
00:53:56,960 --> 00:54:01,000
Speaker 4: converted into beds and we'd can't sleep at night, and

1095
00:54:01,000 --> 00:54:04,040
Speaker 4: then we just have like turn the beds back into

1096
00:54:04,040 --> 00:54:07,600
Speaker 4: couches before anyone came, and then we would shout the

1097
00:54:07,800 --> 00:54:09,960
Speaker 4: YMCA down the road and so that went that. That

1098
00:54:10,920 --> 00:54:13,880
Speaker 4: literally was for several months. What we did, it was

1099
00:54:13,920 --> 00:54:17,400
Speaker 4: in great shape, you know, work out the way. I

1100
00:54:17,400 --> 00:54:21,880
Speaker 4: still remember that that ymcau Page Miller al Camino in

1101
00:54:22,040 --> 00:54:24,440
Speaker 4: Palo Alto. So that was a long time. Again, so

1102
00:54:24,480 --> 00:54:26,799
Speaker 4: it's been I don't know, I've never thought to count it,

1103
00:54:26,840 --> 00:54:29,600
Speaker 4: but several hundred days maybe I don't know.

1104
00:54:30,080 --> 00:54:32,239
Speaker 2: So you're now the richest man on earth. Do you

1105
00:54:32,280 --> 00:54:33,600
Speaker 2: still sleep in the office?

1106
00:54:33,880 --> 00:54:34,560
Speaker 3: Well, that's true.

1107
00:54:35,440 --> 00:54:38,680
Speaker 2: Maybe Mars, we'll find someone else, but I think if.

1108
00:54:38,920 --> 00:54:40,840
Speaker 4: Someone is a sovereign head of a country, there to

1109
00:54:40,840 --> 00:54:42,160
Speaker 4: facto richer by a lot.

1110
00:54:42,400 --> 00:54:43,919
Speaker 3: Do you still sleep at the office now?

1111
00:54:44,120 --> 00:54:45,319
Speaker 4: I have sometimes left at the office.

1112
00:54:45,400 --> 00:54:46,040
Speaker 3: Yeah.

1113
00:54:46,200 --> 00:54:49,520
Speaker 1: As always, thank you for listening to Verdict with center

1114
00:54:49,560 --> 00:54:52,080
Speaker 1: Ted Cruz Ben Ferguson with you don't forget to down

1115
00:54:52,080 --> 00:54:54,280
Speaker 1: with my podcast and you can listen to my podcast

1116
00:54:54,360 --> 00:54:56,319
Speaker 1: every other day you're not listening to Verdict or each

1117
00:54:56,400 --> 00:54:58,840
Speaker 1: day when you listen to Verdict. Afterwards, I'd love to

1118
00:54:58,840 --> 00:55:01,960
Speaker 1: have you as a listener to again the Ben Ferguson podcasts,

1119
00:55:01,960 --> 00:55:04,240
Speaker 1: and we will see you back here tomorrow morning.