Verdict with Ted Cruz - Elon Musk： 1-on-1 Exclusive at the White House-DOGE, AI, Trump, Mars & Killer Robots (Part 1)

00:00:00.000 This is an iHeart Podcast.

00:00:02.420 Guaranteed human.

00:00:04.140 Welcome.

00:00:05.040 It is Verdict with Senator Ted Cruz, Ben Ferguson with you.

00:00:08.580 And today is a very special day as we are doing part one of our two-part conversation

00:00:15.660 at the White House with Elon Musk.

00:00:19.180 Now, Elon is going to break news during today and Wednesday's show on Doge and some credible,

00:00:26.260 shocking information about corruption within our government.

00:00:29.040 I want to make sure you hit that subscribe button, that auto-download button right now

00:00:34.380 so you do not miss part two on Wednesday.

00:00:38.440 Also, please help this go viral as we're exposing government waste by sharing this episode on

00:00:45.440 any social media platform that you are on.

00:00:48.680 But before we get to that, after more than a year of war, terror, and pain in Israel, the

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00:02:00.120 So, without any further ado, here is part one of our sit-down conversation at the White House with Elon Musk.

00:02:09.060 Well, we're in the White House right now, and we're here with my friend Elon Musk,

00:02:13.380 who really has not been doing much of anything, has not made any news, and nobody has noticed the impact.

00:02:21.420 Welcome, Elon.

00:02:22.580 Thank you. 0.94

00:02:23.000 Holy crap. 0.96

00:02:24.380 Yes, wow. 0.99

00:02:25.480 Let me just say...

00:02:27.740 Never a dull moment.

00:02:28.620 Never a dull moment.

00:02:29.820 The first 50 days the president has spent in office, over the top, and the first 50 days you've spent,

00:02:37.180 I don't think there's ever been anyone to have an impact the way you have at the beginning.

00:02:41.620 Let me start with a question you know a lot about.

00:02:44.700 Which was worse, the mess you found at Twitter or the mess you found in the federal government?

00:02:50.460 Well, it's hard to compete with the federal government.

00:02:53.160 What surprised you about the federal government?

00:02:54.980 I assume you came in and assumed it was bad.

00:02:57.440 Is it worse than you expected?

00:02:58.700 It is worse than I expected, but on the plus side, that means there's more opportunity for improvement.

00:03:05.080 So, look, if you look on the bright side, there's actually a lot of opportunity for improvement in federal government expenditures because it's so bad.

00:03:15.300 If it was a well-run ship, it would be very difficult to improve.

00:03:18.780 So, like...

00:03:19.080 But, you know, so now it's like, people say, well, how will you figure out how to save money in the federal government?

00:03:23.960 Well, it's like being in a room where the walls, the roof, and the floor are all targets.

00:03:29.740 You should, in any direction, you can't miss.

00:03:33.100 Wow.

00:03:33.660 Again, I'm sure you would agree.

00:03:35.680 So, a lot of folks have talked about, like...

00:03:38.680 You can't miss.

00:03:39.440 You can't miss.

00:03:41.020 Yeah, this is going in any direction.

00:03:42.300 A lot of the crazy expenditures, things like, like, two million bucks for sex change surgeries in Guatemala...

00:03:49.140 An essential...

00:03:50.200 You know, transgendered mice and Sesame Street in Iraq. 0.90

00:03:56.240 A lot of that has gotten attention.

00:03:57.640 But some of the stuff you've told me about, like, tell us about computer licenses and government agencies.

00:04:03.480 Yeah, so, most of what Doge is finding, you don't need to be Sherlock Holmes.

00:04:07.460 It's very obvious, basic stuff.

00:04:10.160 So, in every government department, I say every because we've not yet found a single exception,

00:04:15.960 there are far too many software licenses and media subscriptions,

00:04:21.480 meaning many more software licenses and media subscriptions than there are humans in the department.

00:04:26.820 Like you were saying, like, an agency with 15,000 people might have 30,000 licenses.

00:04:31.020 Yes.

00:04:31.340 And even of the 15,000 employees, a good chunk of them hadn't used the license,

00:04:36.800 had never logged on or used the application.

00:04:40.360 Yes.

00:04:41.160 We found entire situations of software licenses or media subscriptions where there were zero logins.

00:04:49.040 Wow.

00:04:49.180 So, it had...

00:04:49.740 And yet we were paying for it.

00:04:51.140 Yes.

00:04:51.500 So, the government was paying for thousands of licenses of software or media subscriptions,

00:04:56.340 and no one had ever logged in even once.

00:04:59.060 Or, like, credit cards.

00:04:59.900 You found the same thing with government credit cards.

00:05:01.980 We found that there are twice as many credit cards as there are humans.

00:05:05.960 And I still don't have a good explanation for why this is the case.

00:05:09.700 And these are $10,000 limit cards.

00:05:12.460 So, it's a lot of money.

00:05:14.160 Is it incompetence that you're finding, or is this, like, the biggest money laundering scheme in the history of the world that you're finding?

00:05:20.640 Look, I think it's mostly...

00:05:23.860 If you say, look, what's the waste-to-fraud ratio?

00:05:26.580 Yeah.

00:05:26.900 In my opinion, it's like 80% waste, 20% fraud.

00:05:31.300 But you do have these sort of gray areas.

00:05:34.760 Yeah.

00:05:35.220 Example.

00:05:35.740 Example would be, so, we saw a lot of payments going out of treasury that had no payment code and no explanation for the payment.

00:05:46.180 And then we're trying to figure out what that payment is, and we'd see that, okay, that contract was supposed to be shut off, but someone forgot to shut off that contract.

00:05:56.420 And so, the company kept getting money.

00:05:59.440 Wow.

00:06:00.140 Now, is that waste or fraud?

00:06:03.120 Yeah, both.

00:06:03.740 Both?

00:06:04.420 Yeah.

00:06:04.840 Yeah, I mean, both.

00:06:05.640 It's sort of a gray area.

00:06:06.780 If you know you're getting something you're not supposed to get.

00:06:08.760 You're not supposed to get it, but the government sent it to you, and nobody from the government asked for it back.

00:06:15.000 Take, for example, the $1.9 billion given to Stacey Abrams, a fake NGO.

00:06:20.480 Utter insanity.

00:06:21.820 Explain that from the story.

00:06:23.760 But that's corrupt.

00:06:24.460 That's just corrupt, I think.

00:06:26.840 That's paying off cronies at that point.

00:06:28.640 1,000%.

00:06:29.220 Yeah, yeah.

00:06:30.160 And by the way, she knew.

00:06:31.560 Like, when you get $2 billion, you don't miss that.

00:06:33.940 That's not an accident.

00:06:36.320 Allegedly, it was for, like, you know, environmentally friendly appliances or something.

00:06:41.160 And they've given, like, 100 appliances so far for $2 billion.

00:06:45.520 It's a very expensive toaster.

00:06:46.880 But they're really nice.

00:06:47.860 One hell of an appliance.

00:06:49.000 That's some zero fridge. 0.83

00:06:50.320 Boy, it's nice.

00:06:51.060 Right.

00:06:51.480 This is obviously one of the biggest scam fraud holes we've uncovered, which is really crazy, is that the government can give money to a so-called non-profit with very few controls.

00:07:06.280 And then that, and there's no auditing subsequently of that non-profit.

00:07:11.080 So there's no, so this is where, with the, you know, $1.9 billion to Stacey Abrams, who's, they then give themselves extremely lavish, like insane salaries, expense everything to the non-profit, you know, buy jets and homes and all sorts of things.

00:07:27.060 Live like kings and queens.

00:07:28.520 Yes.

00:07:28.840 On the taxpayer dime.

00:07:30.020 Correct.

00:07:30.300 And this is happening at scale.

00:07:32.940 It's not just one or two.

00:07:34.160 We're seeing this everywhere.

00:07:35.600 Now, one of the things you told me about is what you called magic money computers.

00:07:40.980 Oh, yeah, yeah.

00:07:42.480 So tell us about it, because I'd never heard of that until you brought that up.

00:07:45.400 Okay, so you may think that these, that the government computers, like, all talk to each other, they synchronize, they add up what funds are going somewhere, and it's, you know, it's coherent.

00:07:59.080 That, you know, there's, and that the numbers, for example, that you're presented as a senator are actually the real numbers.

00:08:06.940 One would think.

00:08:07.920 One would think.

00:08:08.440 They're not.

00:08:09.180 Yeah.

00:08:09.320 I mean, they're not totally wrong, but they're probably off by 5% or 10% in some cases.

00:08:17.340 So I call it magic money computer, any computer which can just make money out of thin air.

00:08:22.400 That's magic money.

00:08:23.420 So how does that work?

00:08:24.640 It just issues payments.

00:08:26.980 And you said there's something like 11 of these computers at Treasury that are sending out trillions in payments?

00:08:32.800 They're mostly at Treasury.

00:08:33.740 Some are, there's some at HHS, some at, there's one at one or two at State, there's some at DOD.

00:08:43.140 I think we found now 14 magic money computers.

00:08:46.900 14, okay.

00:08:47.620 They just send money out of nothing.

00:08:50.760 You have an ability to see where leverage points are and how things actually happen.

00:08:57.860 So I remember back, I think it was September, October of this year, before the election, we didn't know who was going to win.

00:09:02.980 And I was at your house in Austin.

00:09:04.820 We were talking about it.

00:09:05.760 And you said, you said, look, I don't want a job in Washington.

00:09:10.180 And you said, all I want is the login for every computer.

00:09:13.360 And I remember thinking at the time that sounded kind of weird.

00:09:15.960 Like I just didn't get it.

00:09:17.140 And I have to say, what's interesting on this, if I would have thought, like, okay, how do you reform government?

00:09:25.360 Like sort of the traditional way to think about it is, okay, give me an org chart.

00:09:28.660 Let me sit down with the people who are running agencies.

00:09:30.700 And what you saw immediately is to understand what's really going on, get to the payment systems, get to the computers.

00:09:38.880 Yeah.

00:09:39.280 Like why is getting to the computers so critical to understanding what's actually happening?

00:09:48.440 Well, the government is run by computers.

00:09:50.660 So you've got essentially several hundred computers that effectively run the government.

00:09:57.100 And if you want to know.

00:09:58.040 Did you know that, Ben?

00:09:59.040 No.

00:09:59.260 Yeah.

00:09:59.320 Like, yeah.

00:10:00.560 So when somebody, like even when the president issues an executive order, that's going to go through a whole bunch of people until ultimately it is implemented at a computer somewhere.

00:10:08.940 And if you want to know what the situation is with the accounting and you're trying to reconcile accounting and get rid of waste and fraud, you must be able to analyze the computer databases.

00:10:17.620 Otherwise, you can't figure it out.

00:10:19.700 Because all you're doing is asking a human who will then ask another human, ask another human.

00:10:24.500 And finally, usually ask some contractor, we'll ask another contractor to do a query on the computer.

00:10:30.540 Wow.

00:10:31.520 That's how it actually works.

00:10:32.900 So it's many layers deep.

00:10:34.160 So the only way to reconcile the databases and get rid of waste and fraud is to actually look at the computers and see what's going on.

00:10:42.760 So you...

00:10:43.560 That's what I call...

00:10:44.620 That's what I, when I sort of cryptically referred to reprogramming the matrix, you have to understand what's going on at the computers.

00:10:53.180 You have to reconcile the computer databases in order to identify the waste and fraud.

00:10:56.880 I don't know that there was anyone in Congress who understood, certainly myself included, who understood the leverage that comes from the computer and the data in particular.

00:11:10.840 That Congress would think about, give me a report on what your expenditures are, rather than actually getting into the pipes.

00:11:17.520 And I think that has been fascinating that it's let you uncover a bunch of crap that just nobody knew. 0.95

00:11:24.340 Yes.

00:11:24.660 I mean, in order for money to go to a bank account, it's not like we're sending truckloads of cash all over the place.

00:11:31.580 It's a...

00:11:32.660 We're wiring money.

00:11:33.800 Right.

00:11:34.100 We're sending money through the ACH system or through the SWIFT system.

00:11:36.900 So in order for money to flow, it's going to flow electronically.

00:11:40.000 So that's what you need to look at.

00:11:41.460 You need to look at the actual electronic money flows.

00:11:44.140 And Tesla and all your companies, you have accounting and you have every expenditure.

00:11:47.920 You have it coded for what it's going for.

00:11:50.560 Federal government doesn't work that way.

00:11:51.980 They don't code what the money's going for.

00:11:53.140 They do now.

00:11:53.520 But they didn't.

00:11:54.980 They didn't.

00:11:56.220 And like one of the things that you told me, you said if any company kept its books the way the federal government does, they'd arrest the officers and put them in jail.

00:12:04.760 Yes.

00:12:05.260 If it was a public company, it would be delisted immediately.

00:12:07.660 It would fail its audit.

00:12:08.880 And the officers of the company would be imprisoned.

00:12:12.020 That's the level of malfeasance in the federal government, unfortunately.

00:12:16.000 It's stunning.

00:12:16.460 Deliberately, or do you think this is incompetence again?

00:12:19.800 It's 80%.

00:12:20.800 It's 80% incompetence and 20% malice.

00:12:25.700 So if you look at Doge now and you look at the government and what you're finding, what percentage have you guys even gotten to?

00:12:35.980 And how much of it is Mars where you haven't even gotten there yet because there's so much you're finding out here?

00:12:41.500 I mean, how many, you seem like a timeline guy when you say, all right, I want to get in there and get all these, you know, numbers and things.

00:12:47.100 How far are we from the end game where you've seen it all, been able to process it all and fix it?

00:12:54.200 I mean, are we years away, months away?

00:12:57.080 Not years.

00:12:58.600 I mean, I'm reasonably confident that we'll be able to get a trillion dollars of waste and fraud out.

00:13:05.040 And that meaning that it will have, we'll have a net savings in FY26, which starts in October, obviously, of a trillion dollars.

00:13:15.440 Wow.

00:13:15.680 Provided we're allowed to continue and our progress is not impeded.

00:13:20.000 And we're very public about what we do.

00:13:21.980 Yeah.

00:13:22.220 You put it on the website.

00:13:23.360 It's on the website.

00:13:24.300 I don't know how we could be more transparent.

00:13:26.260 Literally every action we do, small or large, we put on the doge.gov website and we post on the X handle.

00:13:33.420 And when people complain about it, and they say, oh, you're doing something on costume?

00:13:38.020 So I'm like, well, which of these costumes?

00:13:39.620 You're doing it in the daylight.

00:13:41.100 Everyone knows exactly what you're doing.

00:13:42.940 Extreme transparency.

00:13:45.560 I don't think anything's been this transparent ever.

00:13:48.100 So five years ago, you were a hero to the left.

00:13:52.180 You were cool.

00:13:53.280 You had electric cars.

00:13:54.520 You had space.

00:13:56.280 And in five years, you've gone.

00:13:57.900 I could go to a party in Hollywood and not get dirty looks.

00:14:00.180 Yeah.

00:14:00.540 In fact, yeah.

00:14:01.580 Now you might not even get invited.

00:14:04.060 Still get invited, but I don't know if I should go.

00:14:07.760 And I don't think it's an exaggeration to say today, after Donald Trump, the left hates you more than any person on earth.

00:14:16.340 Yes.

00:14:17.000 I appear to be number two.

00:14:18.680 I mean, if you're judged by the various signs, they—

00:14:22.060 It's derangements.

00:14:22.960 It's Trump derangement syndrome and Elon derangement syndrome.

00:14:25.860 Yes.

00:14:25.980 How is that for you?

00:14:27.100 That's a little bit of whiplash of going from being like Mr. Cool to the devil incarnate in just a couple of years.

00:14:34.620 Is that kind of weird to experience that transformation?

00:14:37.420 Yes.

00:14:38.580 Why do they hate you so much?

00:14:39.960 Well, because we're clearly over the target.

00:14:44.820 If Doge was ineffective, if we were not actually getting rid of a bunch of waste and fraud, and a bunch of that fraud—I mean, the fraud we're seeing is overwhelmingly on the left.

00:14:56.680 I mean, it's not zero on the right, but these NGOs are almost all left-wing NGOs that are being funded, for example.

00:15:04.740 Yep.

00:15:05.900 So they hate me because Doge is being effective, and Doge is getting rid of a lot of waste and fraud that people on the left were taking advantage of.

00:15:17.260 That's what it comes out of.

00:15:19.420 And the single biggest thing that they're worried about is that Doge is going to turn off fraudulent payments of entitlements.

00:15:30.300 I mean, everything from Social Security, Medicare, unemployment, disability, small business administration loans.

00:15:39.260 Turn them off to illegals. 1.00

00:15:42.460 This is the crux of the matter.

00:15:44.380 Yep. 0.98

00:15:44.520 Okay, this is the thing that—why they really hit my guts and want me to die.

00:15:50.660 And do you think that's billions, hundreds of billions?

00:15:53.380 What do you think the scale is of that?

00:15:55.160 I think across the country, it's well worth of $100 billion, maybe $200 billion.

00:16:01.100 So by using entitlements fraud, the Democrats have been able to attract and retain vast numbers of illegal immigrants. 0.85

00:16:12.800 And by voters.

00:16:14.520 And by voters, exactly.

00:16:16.640 Exactly.

00:16:17.700 Basically, bring in, I don't know, 10, 20 million people who are beholden to the Democrats for government handouts.

00:16:26.800 And will vote overwhelmingly Democrat, as has been demonstrated in California.

00:16:30.940 This is—

00:16:31.520 It's an election strategy.

00:16:33.420 Yes.

00:16:34.100 It's power.

00:16:34.660 Yes.

00:16:35.100 Yes.

00:16:35.540 And it doesn't take much to turn the swing states blue.

00:16:38.580 I mean, often a swing state might be won by 10,000, 20,000 votes.

00:16:41.720 Sure.

00:16:41.860 So if the Dems can bring in 200,000 illegals and over time get them legalized, not counting any cheating that takes place, because there is some cheating, but even without cheating, if you bring in illegals that are 10x the voter differential in a swing state, it will no longer be a swing state.

00:17:00.500 Right.

00:17:00.700 And the Dems will win all the swing states, just a matter of time.

00:17:04.780 And America will be a permanent, deep blue socialist state.

00:17:11.180 The House, the Senate, the presidency, and the Supreme Court will all go hardcore down.

00:17:17.780 They will then further cement that by bringing in even more aliens, so you can't vote your way out of it. 0.80

00:17:25.080 Their objective is to make it permanent.

00:17:26.760 And it will be a permanent, one-party socialist state.

00:17:28.380 And it will be much worse than California, because at least California is mitigated by the fact that someone can leave California.

00:17:32.800 Right.

00:17:33.020 You can go to Texas.

00:17:33.620 Yeah.

00:17:34.240 Exactly.

00:17:35.620 That's what you did.

00:17:35.960 But they're going to make everywhere California a bit worse.

00:17:38.080 By the way, the middle of the pandemic, I spent 45 minutes on the phone with Elon.

00:17:42.380 He was still in California.

00:17:43.920 I was walking my dog, Snowflake, and trying to convince you, come to Texas.

00:17:48.680 The commies in California can't stand you. 1.00

00:17:51.160 We love you.

00:17:51.920 We want you here.

00:17:52.760 And you didn't quite go then, but you went not that long afterwards.

00:17:55.920 I mean, the COVID actions almost killed Tesla, because every other auto plant in the country was allowed to open

00:18:04.240 but ours, which was in California, was not allowed to open.

00:18:07.780 Wow.

00:18:07.980 Wow.

00:18:09.440 So they almost killed Tesla.

00:18:11.260 So as a personal matter, do you ever regret it?

00:18:15.960 Like five years ago, you go to the Oscars and we're Mr. Cool, and now you've got death threats every day.

00:18:21.360 Well, these days the Oscars are boring.

00:18:25.120 I wouldn't want to go.

00:18:26.140 And God bless the movies they nominate no one on earth has ever seen.

00:18:29.000 Like, could they actually nominate a movie that human beings go watch?

00:18:32.420 I mean, how many great movies have come out in the last several years?

00:18:36.500 Very few.

00:18:36.980 Depressingly few.

00:18:38.120 Yeah, very few.

00:18:39.260 The last Oscars came and went.

00:18:40.560 I didn't even watch it.

00:18:41.340 There's nothing to see.

00:18:42.540 I was sad that Gene Hackman just passed away, because Unforgiven was spectacular.

00:18:47.180 But that was a long time ago that Unforgiven came out.

00:18:49.280 You've mentioned today here and before about the possibility of someone wanting to take you out,

00:18:56.720 dealing with the death threats.

00:18:58.640 Yes, it's not in my imagination.

00:19:00.360 You can just look on social media.

00:19:01.380 Yeah.

00:19:02.120 But like, is it because?

00:19:04.240 To make that very clear.

00:19:05.180 Yeah.

00:19:05.400 And look, I'm very familiar with it.

00:19:07.000 And they've got signs. 0.58

00:19:07.860 There are people with signs and demonstrations saying that I need to die.

00:19:12.080 Do you think, are these just whack jobs?

00:19:15.840 Or do you think there are foreign?

00:19:18.540 They're not sane people.

00:19:19.440 Do you think there are foreign entities behind this?

00:19:22.080 Do you think there are domestic entities behind the threats?

00:19:24.520 And also the attacks to Twitter.

00:19:26.160 Not Twitter, Tesla.

00:19:28.360 I mean, you know, you're getting Tesla's charging stations lit on fire.

00:19:33.000 Do you think that's organized and paid for?

00:19:36.180 Yes.

00:19:36.840 At least some of it is organized and paid for.

00:19:39.420 I think by domestic, you know, basically left-wing organizations in America, funded by left-wing billionaires, essentially.

00:19:52.500 Is it like ActBlue or what?

00:19:54.260 ActBlue is one of them.

00:19:55.180 You know, Arabella, you know, the classic. 1.00

00:19:59.760 It's funded by the, you know, the blue, basically the left-wing NGO cabal.

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00:20:38.380 How big of a thread is this to, like, what you build at Tesla?

00:20:43.340 I mean, I remember when Teslas came out, it was people that they didn't want to have gas cars.

00:20:48.020 A lot of it was environmental reasons.

00:20:49.960 I jokingly said, I was like, I'm a Texas guy.

00:20:52.400 I'm always going to have something that burns gas.

00:20:53.820 My kids now, all three of my boys, think that Teslas are awesome.

00:21:00.280 The Cybertruck is the car they want their dad to buy, which I laugh because I never could have imagined that five years ago. 0.91

00:21:07.580 And now I'm looking at, well, we're at the White House and the President's Teslas parked right outside the West Wing, which is the coolest damn thing. 0.56

00:21:12.920 But I mean, you've changed a generation.

00:21:14.620 When you look at my kids are six and eight, and they're going, Dad, buy a Cybertruck, and I'm considering it, that's a full circle in a weird way.

00:21:23.900 Yeah.

00:21:24.620 Well, I do have this theory that the most entertaining outcome is the most likely.

00:21:28.320 So, yeah, that seems often to be true.

00:21:32.860 You see, like, what twist or turn of fate would generate the highest ratings?

00:21:38.560 If we were a TV show, what twist or turn of fate would generate the highest ratings?

00:21:43.020 I think there's a good chance that happens.

00:21:45.120 Well, I will say if ActBlue and Arabella Networks—

00:21:49.620 ActBlue's a huge scam, X-Level.

00:21:51.740 Do you think it's foreign money, Chinese money?

00:21:53.700 Where do you think the money in ActBlue is coming from?

00:21:55.800 How do you figure that out?

00:21:57.340 Well, it's not coming from a whole bunch of—from a groundswell of public support.

00:22:03.080 Because when individual donors are looked at in ActBlue, they eventually turn out to be, like, diehard Republicans.

00:22:09.760 People have never given money in their life.

00:22:11.340 So you're going to track down a bunch of these people where it says, oh, I gave $16,000.

00:22:15.660 And they're like, I didn't give $16,000.

00:22:17.480 What are you talking about?

00:22:19.600 Well, if those—

00:22:20.940 Republican friends of mine have found themselves on the ActBlue list.

00:22:23.440 They're like, it definitely wasn't me.

00:22:25.140 So that's—

00:22:26.060 If it can actually be shown that they are funding firebombing of Tesla charging stations, that's objectively a criminal act.

00:22:34.520 That is funding terrorist activity.

00:22:36.540 And the statutes make clear that an incendiary device qualifies.

00:22:40.780 So that's a big deal.

00:22:41.680 If putting things down is a terrorist activity.

00:22:42.840 Let me ask AI.

00:22:46.100 In 10 years, how is life going to be different because of AI for just a normal person?

00:22:53.000 Well, 10 years is a long time.

00:22:55.740 In 10 years, probably AI could do anything better than a human can, cognitively.

00:23:01.420 Probably almost—I think in 10 years, based on the current rate of improvement, AI will be smarter than the smartest human.

00:23:09.120 Yeah, yeah.

00:23:10.440 There will also be a massive number of robots.

00:23:14.260 So humanoid robots.

00:23:15.980 By the way, I've got to ask, how come your robots look so much like the creepy robots from iRobot?

00:23:20.920 Was that intentional or just—

00:23:24.100 I was hoping he was going to say, yeah, just to mess with you.

00:23:28.080 It's not meant to look like any prior robot.

00:23:31.980 And we'll iterate the design.

00:23:33.240 And you'll be able to have—a lot of the robot parts are cosmetic.

00:23:38.540 You'll be able to switch out the kind of snap-on cosmetic parts of the robot, make it look like something else if you'd like.

00:23:47.300 So there will be ultimately billions of humanoid robots.

00:23:52.780 All cars will be self-driving.

00:23:55.340 In 10 years?

00:23:55.920 In 10 years, probably 90% of miles driven will be autonomous.

00:24:02.260 Huh.

00:24:02.720 Wow.

00:24:03.220 That fast?

00:24:04.760 Yeah.

00:24:05.760 In 5 years, probably 50% of miles driven will be autonomous.

00:24:10.740 Now, if AI will be smarter than any person, how many jobs go away because of that?

00:24:17.360 And what do people do if you've got millions of people that are losing their jobs?

00:24:20.880 Like that, a lot of people are understandably freaked out about that.

00:24:25.100 Well, goods and services will become—it's close to free.

00:24:31.900 So it's not as though people will be wanting in terms of goods and services.

00:24:37.720 So why is that?

00:24:39.020 Why are goods and services free in an AI world or close to free?

00:24:43.340 Well, you have, I don't know, tens of billions of robots.

00:24:50.180 They will make you anything or provide any service you want for basically next to nothing.

00:25:00.180 It's not that people will have a lower standard of living.

00:25:03.800 They will have actually a much higher standard of living.

00:25:05.460 But the challenge will be fulfillment.

00:25:11.000 How do you derive fulfillment and meaning in life?

00:25:14.720 Is Skynet real?

00:25:17.060 Like you get the apocalyptic visions of AI.

00:25:21.180 How real is the prospect of killer robots annihilating humanity?

00:25:27.160 20% likely.

00:25:28.880 Maybe 10%.

00:25:29.760 Wow.

00:25:30.140 On what time frame?

00:25:31.940 Five to 10 years.

00:25:32.740 So soon.

00:25:34.720 Like you see a world where that's possible.

00:25:38.760 Yeah.

00:25:39.280 But you can look at it like the glass is 80-90% full.

00:25:43.500 Meaning like 80% likely will have extreme prosperity for all.

00:25:50.380 Now I guess my view, we're in a race to win AI.

00:25:54.000 We're in a race with China. 0.99

00:25:55.920 And my view is if they're going to be killer robots, 0.95

00:25:58.220 I'd rather they be American killer robots than Chinese. 1.00

00:26:00.400 How likely are we winning right now?

00:26:05.120 Is America winning right now?

00:26:06.280 And how likely is America to win the race for AI vis-a-vis China or anyone else?

00:26:11.560 Well, the next few years, I think America is likely to win.

00:26:14.600 Then it will be a function of who controls the AI chip fabrication.

00:26:20.820 The factories that make the AI chips, who controls them?

00:26:23.700 If more of them are controlled by China, then China will win. 1.00

00:26:27.260 More of the factories that are making the AI chips.

00:26:31.100 You think that will determine it?

00:26:32.900 Yes.

00:26:33.720 And how are we doing versus China on that front?

00:26:37.320 Well, right now, almost all the advanced AI chip factories, they call them fabs, are in Taiwan.

00:26:47.600 And what if China invades Taiwan?

00:26:48.820 Which is 69 miles away from...

00:26:49.920 What happens if China invades Taiwan, what happens to the world? 0.97

00:26:56.260 Well, if they were to invade in the near term, the world would be cut off from advanced AI chips.

00:27:03.700 Currently, 100% of advanced AI chips are made in Taiwan.

00:27:07.480 How fast can we put that online in America, and how important is that for national security?

00:27:10.820 I think it's essential for national security, and we're not doing enough.

00:27:16.480 You're 53 years old.

00:27:18.460 I'm 118 days older than you.

00:27:20.520 By the way, what the hell have I done in my life?

00:27:22.440 I know, right?

00:27:23.720 53 years old.

00:27:25.080 You did pretty well.

00:27:27.220 Well...

00:27:28.460 So 71 was a great year.

00:27:30.220 And I was December 70, so I was just right before.

00:27:33.820 You were the summer of 71.

00:27:36.520 I was born 69 days after 420.

00:27:39.620 Wow.

00:27:40.660 I did ask Ben...

00:27:42.160 This is true.

00:27:43.260 Look, this is true.

00:27:44.200 All right, you just opened up the can of words.

00:27:46.000 I did ask Ben, should I show up and pull up a joint and say, can we beat Rogan's views?

00:27:50.620 But I was pretty sure it might cause a scandal if we smoke pot in the White House. 1.00

00:27:56.320 It just turned out to be like a chocolate cigar.

00:27:58.300 Yeah.

00:28:01.040 Let me ask you, if today was your last day on Earth...

00:28:04.260 Yeah.

00:28:04.840 What?

00:28:05.520 I'm not suggesting it's going to be, but if it were,

00:28:07.720 what do you think your biggest legacy would be?

00:28:09.040 If everything you've done 100 years from now,

00:28:11.980 what do you think people would remember if it were zero to today?

00:28:16.760 And will you ever go to space?

00:28:19.700 In the distant future, 100 or 1,000 years ago,

00:28:24.420 if SpaceX got humans to Mars, that's what they would remember me for.

00:28:29.520 All right.

00:28:30.200 Final set of questions.

00:28:31.560 Who's the smartest guy you've ever met?

00:28:33.120 You hang out with some brilliant people.

00:28:36.220 Like, when you look...

00:28:37.380 What's a CEO you look at, other than yourself? 0.99

00:28:40.260 What CEO do you say, damn, that guy's good? 0.98

00:28:45.540 Larry Ellison's very smart. 0.98

00:28:49.420 So I'll say Larry Ellison's one of the smartest people.

00:28:54.720 You know, Larry Page.

00:28:56.560 I mean, there are a lot of people that are very smart.

00:28:57.720 It's hard to say, like, you know, I think to some degree smart is as smart does.

00:29:02.760 So, you know, what have they done that is difficult and significant?

00:29:12.280 You know, Jeff Bezos has done a lot of difficult and significant things.

00:29:16.300 I mean, there are a lot of smart humans.

00:29:21.160 I call them smart for a human.

00:29:23.660 A lot of people who are in the smart for a human category.

00:29:26.460 All right.

00:29:26.800 Final lightning round.

00:29:28.800 Star Wars or Star Trek?

00:29:31.080 The first movie I saw in the theater was Star Wars.

00:29:33.360 So I think it had a profound effect on me.

00:29:36.200 I was six years old, I think.

00:29:38.480 Imagine if the first movie you ever see in a theater is Star Wars.

00:29:43.240 It's going to blow your mind.

00:29:44.140 Best Star Wars movie?

00:29:45.040 Empire Strikes Back.

00:29:48.740 The only objectively right answer.

00:29:50.600 I stood in line for three hours with my dad to see it on opening day.

00:29:54.480 Kirk or Picard?

00:29:56.520 I like them both, but Kirk.

00:29:58.660 Again, objectively right answer.

00:30:00.720 By the way, James T. Kirk is a Republican and Picard is a Democrat.

00:30:05.080 And the left gets very mad when I say that.

00:30:08.620 Best Star Trek movie?

00:30:11.000 I mean, the first Star Trek movie, maybe?

00:30:13.740 Now, that's interesting.

00:30:14.480 The Rath of Khan. 0.57

00:30:15.020 Rath of Khan.

00:30:15.440 Okay.

00:30:16.220 Rath of Khan.

00:30:16.660 Rath of Khan.

00:30:18.600 Actually, both Rath of Khans were pretty good.

00:30:21.860 But, yeah, the original Rath of Khan. 0.87

00:30:24.040 Ricardo Montalban.

00:30:26.340 Revenge is a dish best served cold.

00:30:29.120 It is very cold in space.

00:30:31.400 Although I will say, Rath of Khan is objectively the right answer. 1.00

00:30:35.520 But four is a sleeper.

00:30:37.120 When they go back to San Francisco and go find the whales and, you know, Scotty picks up the mouth and talks to it and goes, a keyboard.

00:30:46.460 How quaint.

00:30:48.240 That's a sleeper.

00:30:49.120 All right.

00:30:49.440 Last question.

00:30:50.820 Did Han shoot first?

00:30:53.600 It seemed like he shot second.

00:30:55.980 I like it.

00:30:56.280 This is verdict.

00:30:57.060 And by the way, I apologize, Ben.

00:30:58.820 And so Ben was a jock and played tennis at Ole Miss.

00:31:01.420 And so occasionally when we geek out a little bit.

00:31:04.260 I love watching y'all geek out over there.

00:31:05.980 I think he might have shot first, though, because the guy missed.

00:31:07.680 He's still on the question.

00:31:08.680 I love it.

00:31:09.120 He missed his.

00:31:09.840 The alien missed his basal shot.

00:31:11.700 So why did he miss his basal shot?

00:31:12.940 It must have been because he got shot first. 0.57

00:31:15.280 Now he's missing a point-blank basal shot unless they got knocked or killed.

00:31:18.900 But it's a question of real consequences. 0.86

00:31:20.280 But he was going to shoot.

00:31:21.100 Yeah.

00:31:21.660 Which is, is Han Solo simply a hero or an anti-hero?

00:31:25.500 And so I'm in the Han shot first category. 0.70

00:31:28.360 I don't like sanitized stories.

00:31:30.140 He would have had to have shot first because otherwise, why would the alien miss a point-blank range?

00:31:35.180 Are you ever going to go to outer space?

00:31:36.960 Is that something in your life goals?

00:31:38.640 Yeah, I'd like to go to Mars at some point.

00:31:40.220 And people have said, do I want to die on Mars?

00:31:44.180 And I say, yes, just not on impact.

00:31:46.780 Now that's a very good answer.

00:31:48.080 Here, the astronauts on the space station, are they political prisoners?

00:31:53.720 Some of them are.

00:31:55.520 Because you could have given them a ride back and Joe Biden said no purely for politics.

00:32:02.360 Yeah.

00:32:02.660 I mean, you know, there's been some debate about this online.

00:32:06.300 But the thing is that it was a very high-level decision.

00:32:09.440 So it wasn't really even a NASA decision.

00:32:12.120 It was just that the Biden White House did not want to have someone who was pro-Trump rescuing astronauts right before the election.

00:32:22.760 So they pushed it.

00:32:23.780 Well, if you're one of those astronauts, you've got to be pretty pissed off about that.

00:32:27.580 Well, if they're a Democrat, yes.

00:32:30.260 If they're a Republican, yes.

00:32:31.520 But if they're a Democrat, like, everything's fine.

00:32:33.640 Fair enough.

00:32:34.040 So I think one of them is a Republican, as a Democrat.

00:32:37.380 So it depends on which one you ask.

00:32:38.940 Well, thank you, Elon.

00:32:39.720 Thank you, man.

00:32:40.100 This was awesome.

00:32:41.300 And let me say, and by the way, I put out on X the day before yesterday, if you were having a beer with Elon and could ask him anything, what would you ask?

00:32:49.700 And got lots of responses.

00:32:51.540 The most common response people said is say thank you.

00:32:55.780 Look, Texans and the American people appreciate what you're doing.

00:32:59.000 You don't have to put up with this BS and you're doing it.

00:33:01.820 I'm grateful you're making a hell of a difference for this country.

00:33:05.200 I appreciate you and the Americans appreciate you.

00:33:07.900 Thank you.

00:33:08.160 It's essential for the future of civilization.

00:33:09.920 Otherwise, I wouldn't be doing it.

00:33:11.000 Yes.

00:33:11.260 It's not like I want to get death threats, you know?

00:33:13.140 No.

00:33:13.800 All right.

00:33:14.120 Now, part two of this interview with Elon Musk and some bigger breaking news that we're going to have for you about corruption.

00:33:20.940 The government will hit on Wednesday morning.

00:33:24.220 So make sure you hit that subscribe or auto download button right now.

00:33:28.220 And again, please help this show go viral so that we can continue to expose government waste.

00:33:33.360 Wherever you're on social media, hit that little forward button and post this episode on social media.

00:33:40.500 And the center and I will see you back here with Elon Musk.

00:33:43.220 Part two, Wednesday morning.

00:33:44.740 This is an iHeart podcast.

00:33:47.200 Guaranteed human.

Verdict with Ted Cruz - March 17, 2025

Elon Musk： 1-on-1 Exclusive at the White House-DOGE, AI, Trump, Mars & Killer Robots (Part 1)

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