A Look Inside Elon Musk’s Vision: Complete Interview (YouTube Video Transcript)

(00:00:00) Your YouTube transcript will appear here (00:00:06) Well, first off, welcome. It is Verdict (00:00:08) with Ted Cruz, Ben Ferguson with you. (00:00:10) Happy New Year, Senator, to you uh as (00:00:12) well and to everyone listening right (00:00:14) now. And we've got a really fun show (00:00:16) that we're going to do today on New (00:00:18) Year's and it deals with waste, fraud, (00:00:20) and abuse that we talked about that's (00:00:22) now becoming a reality in Minnesota (00:00:24) months ago with your good friend Elon (00:00:26) Musk. (00:00:28) >> Well, happy new year to everyone. I hope (00:00:29) you had a fantastic New Year's Eve. I (00:00:31) hope you stayed safe. I hope you enjoyed (00:00:33) time with your family. You celebrated. I (00:00:35) hope you're ready now for an incredible (00:00:37) 2026. Uh I hope that you accomplish (00:00:40) something that really makes a difference (00:00:41) that you you you make a difference in (00:00:43) the lives of those around you. You make (00:00:45) a difference in the lives of your kids (00:00:47) and your community and and and you make (00:00:49) a real impact fighting for our country. (00:00:51) Our country is at a pivotal time and I (00:00:54) hope 2026 is a time where you stand up (00:00:56) and say, "I am going to stand up and (00:00:59) defend our nation like so many patriots (00:01:00) who have preceded me." On this New (00:01:02) Year's Day, we're we're going to play (00:01:04) one of my favorite podcast that Ben and (00:01:06) I ever did. And and and this was last (00:01:09) year, last summer, we interviewed Elon (00:01:11) Musk. Elon Musk is a good friend of (00:01:12) mine. We sat down with him for for an (00:01:14) hour in the White House talking to him (00:01:17) about Doge and what he was doing with (00:01:19) with President Trump, but also talking (00:01:21) to talking to him personally about who (00:01:23) he is, about how he how he built Tesla, (00:01:25) how he built SpaceX. We talked to him (00:01:27) about AI and killer robots and and it's (00:01:30) a fascinating show and we present it to (00:01:33) you right now in its entirety. Today is (00:01:35) a really fun day, Senator, because we (00:01:37) have a special guest and we're in a (00:01:39) special place. I'm going to let you do (00:01:41) the rest of the intro. Well, we're in (00:01:42) the White House right now and we're here (00:01:44) with my friend Elon Musk who really has (00:01:47) not been doing much of anything, has not (00:01:49) made any news, is and uh nobody has (00:01:52) noticed (00:01:53) >> Yeah. (00:01:53) >> the impact. Welcome, Elon. (00:01:55) >> Thank you. (00:01:56) >> Holy crap. (00:01:57) >> Uh yes. Wow. (00:01:59) >> Let me just say (00:02:00) >> never a dull moment. (00:02:01) >> Never a dull moment. The first 50 days (00:02:04) the president has spent in office over (00:02:07) the top. and the first 50 days you've (00:02:09) spent, I I don't think there's ever been (00:02:11) anyone to have an impact the way you (00:02:13) have the beginning. (00:02:14) >> Let me let me start with a question you (00:02:16) know a lot about. (00:02:18) >> Which was worse, the mess you found at (00:02:20) Twitter or the mess you found in the (00:02:22) federal government? (00:02:23) >> Well, it's hard to compete with the (00:02:24) federal government. (00:02:25) >> Uh, what surprised you about the federal (00:02:27) government? I I assume you came in and (00:02:29) assumed it was bad. Is it worse than you (00:02:31) expected? (00:02:33) it it is worse than I expected. But on (00:02:35) the plus side, that means there's more (00:02:37) opportunity for improvement. So, look, (00:02:39) if you look on the bright side, um (00:02:42) there's there's actually a lot of (00:02:43) opportunity for improvement uh in (00:02:45) federal government expenditures uh (00:02:46) because it's so bad. (00:02:48) >> Um if if it was a well-run ship, it (00:02:50) would be very difficult to improve. (00:02:51) >> So, like, but but you so so now it's (00:02:53) like people say, "Well, how how will you (00:02:55) figure out how to save money in the (00:02:56) federal government?" Well, it's like (00:02:57) being in a room where the the walls, the (00:02:59) roof, and the floor are all targets. So, (00:03:02) You shoot in any direction and you're (00:03:04) can miss. (00:03:06) >> Wow. Again, I'm sure you would agree. (00:03:08) >> So, a lot of folks have talked about (00:03:10) like like (00:03:11) >> you can't you can't miss going any (00:03:15) direction. (00:03:16) >> A lot of the crazy expenditures, things (00:03:18) like like 2 million bucks for sex change (00:03:20) surgeries in Guatemala, (00:03:22) >> an essential (00:03:25) >> um you know, transgendered mice and and (00:03:28) Sesame Street in Iraq. A lot of that has (00:03:30) gotten attention, but some of the stuff (00:03:31) you've told me about like like tell us (00:03:33) about computer licenses and government (00:03:36) agencies. (00:03:36) >> Yeah. So most of what Doge is finding, (00:03:38) you don't need to be Sherlock Holmes. (00:03:40) Okay. It's very obvious basic stuff. So (00:03:43) it in in every government department, I (00:03:46) say every because we've not yet found a (00:03:47) single exception. Um, there are far too (00:03:50) many software licenses um and and media (00:03:53) subscriptions, meaning many more uh (00:03:56) software licenses and media (00:03:57) subscriptions than there are humans in (00:03:59) the department. (00:04:00) >> Like you were saying, like an agency (00:04:01) with 15,000 people might have 30,000 (00:04:03) licenses. (00:04:04) >> Yes. (00:04:05) >> And even of the 15,000 employees, a good (00:04:08) chunk of them hadn't used the license, (00:04:09) had never logged on or or used the used (00:04:12) the application. (00:04:13) >> Yes. We we found entire uh situations of (00:04:17) of software licenses or media (00:04:19) subscriptions where there were zero (00:04:21) login. (00:04:22) >> So it had (00:04:23) >> and yet we were paying for it. (00:04:24) >> Yes. The government was paying for (00:04:25) thousands of licenses of software uh or (00:04:28) media subscriptions and no one had ever (00:04:30) logged in even once (00:04:32) >> or like credit cards. You found the same (00:04:33) thing with government credit cards. (00:04:35) >> Uh we found that there are twice as many (00:04:36) credit cards as there are humans. (00:04:39) >> Good. (00:04:40) >> And I still don't have a good (00:04:40) explanation for why this is the case. (00:04:42) And these are $10,000 limit cards. So, (00:04:45) it's a lot of money. (00:04:47) >> Is it incompetent that you're finding or (00:04:49) is this like the biggest moneyaundering (00:04:51) scheme in the history of the world that (00:04:53) you're finding? (00:04:54) >> Look, I think it's mostly (00:04:56) >> if you say, look, what's the waste to (00:04:58) fraud ratio? Yeah. Uh, in my my opinion, (00:05:01) it's (00:05:02) >> it's like 80% waste, 20% fraud. (00:05:04) >> But but but but you do have these sort (00:05:06) of gray areas. (00:05:07) >> Yeah. Example, (00:05:09) >> example be so uh we saw a lot of (00:05:12) payments uh going out of treasury that (00:05:15) had no u payment code and no explanation (00:05:18) for the payment and then we're we're (00:05:20) we're tra we're trying to figure out (00:05:22) what that payment is and we'd see that (00:05:24) okay that contract was supposed to be (00:05:25) shut off uh but but someone forgot to (00:05:28) shut off that that contract and so the (00:05:30) company kept getting money. (00:05:32) >> Wow. (00:05:33) >> Now is that waste or fraud? (00:05:36) >> Yeah. Both. (00:05:36) >> Both. Yeah, but it's you know you're (00:05:39) getting something you're not supposed to (00:05:41) get. (00:05:42) >> You're not supposed to get it, but you (00:05:43) but the the government sent it to you (00:05:45) and nobody from the government asked for (00:05:46) it back. Take for example the one the (00:05:49) $1.9 billion given to Stacy Abram's a (00:05:52) fake NGO. (00:05:53) >> Utter insanity. (00:05:55) >> Explain that for (00:05:58) that's just corrupt. I think that's (00:06:00) paying off cronies at that point. (00:06:01) >> 1,000%. (00:06:02) >> Yeah. (00:06:02) >> Yeah. And by the way, she knew like when (00:06:04) you get $2 billion, you don't miss that. (00:06:07) That's not (00:06:07) >> that's not accident. That's (00:06:09) >> allegedly it was for like uh you know (00:06:12) environmentally friendly appliances or (00:06:13) something and they've given like like a (00:06:16) hundred appliances so far for $2 (00:06:17) billion. It's very expensive toaster (00:06:21) of an appliance. (00:06:22) >> That's Subzero fridge. Boy, it's nice. (00:06:24) >> Right. This just obviously one of the (00:06:26) biggest uh scam port holes we've (00:06:28) uncovered which is really crazy is uh is (00:06:32) that is that the government can give (00:06:34) money to a so-called nonprofit uh with (00:06:38) with very few controls and then that and (00:06:40) there's there's no auditing subsequently (00:06:42) of that nonprofit. So there's no so this (00:06:45) is where with the you know 1.9 billion (00:06:47) Stacy Abrams who's who's they then give (00:06:50) themselves extremely lavish like insane (00:06:52) salaries (00:06:53) >> uh expense everything to the to the (00:06:55) nonprofit um you know buy jets and homes (00:06:59) and all sorts of things (00:07:00) >> live like kings and queens. (00:07:01) >> Yes. (00:07:02) >> On the taxpayer done (00:07:03) >> correct you mentioned (00:07:04) >> this is happening at scale. It's not (00:07:06) just one or two. We're seeing this (00:07:08) everywhere. Now, one of the things you (00:07:09) told me about is what you call (00:07:12) >> magic money computers at the very (00:07:15) >> well. (00:07:16) >> So, tell us about because I never heard (00:07:17) of that until you you brought that up. (00:07:19) >> Okay. So, you may think that these that (00:07:21) that the government computers uh like (00:07:23) all talk to each other. They (00:07:25) synchronize. They they add up what funds (00:07:27) are going somewhere and it's, you know, (00:07:30) um it's coherent that that that the you (00:07:33) know there's um and that and that the (00:07:35) numbers, for example, that you're (00:07:36) presented as a senator Yeah. are (00:07:38) actually the real numbers (00:07:39) >> in one would think (00:07:41) >> one would think they're they're not. (00:07:42) Yeah. Okay. (00:07:44) >> Um I mean they're not totally wrong, but (00:07:46) they're probably off by 5% or 10% in (00:07:48) some cases. (00:07:49) >> Um so uh I call a magic money computer (00:07:52) any computer which can just make money (00:07:53) out of thin air. (00:07:55) >> That's magic money. (00:07:56) >> So how does that work? (00:07:57) >> It just issues payments. (00:08:00) >> And you said there's something like 11 (00:08:01) of these computers at Treasury that are (00:08:03) that are sending out trillions in in (00:08:05) payments. (00:08:06) >> They're mostly at Treasury. Uh some are (00:08:08) but there's some at HHS, some at there's (00:08:12) one or two at state. Uh there's some at (00:08:15) DoD. I think we found now 14 magic money (00:08:18) computers. (00:08:20) >> 14. Okay. (00:08:20) >> They just send money out of nothing. (00:08:24) >> You have an ability to see where (00:08:26) leverage points are and and how things (00:08:30) actually happen. So, I remember back, I (00:08:32) think it was September, October of this (00:08:33) year before the election, we didn't know (00:08:35) who was going to win. And I I was at (00:08:36) your h house in Austin. We were talking (00:08:38) about it and and and you said you you (00:08:40) you said, "Look, I I I don't want a job (00:08:42) in in Washington." And you said, "All I (00:08:44) want is the login for every computer." (00:08:46) >> And and I remember thinking at the time (00:08:48) that sounded kind of weird. Like, I just (00:08:49) didn't get it. And I have to say, what (00:08:51) what's interesting on this, (00:08:54) if I would have thought like, okay, how (00:08:57) do you reform government? like sort of (00:08:58) the traditional way to think about it is (00:09:00) okay give me an ORC chart let me sit (00:09:02) down with the people who are running (00:09:03) agencies and and what you saw (00:09:06) immediately is to understand what's (00:09:08) really going on get to the payment (00:09:10) systems get to the computers (00:09:12) >> like like (00:09:15) why are are why is getting to the (00:09:17) computers so critical to understanding (00:09:19) what's actually happening (00:09:21) >> well the government is run by computers (00:09:23) so you've got um essentially several (00:09:27) hundred computers that affect (00:09:28) effectively run the government. Um, and (00:09:30) if you want to know, (00:09:31) >> did you know that, Ben? (00:09:32) >> No. (00:09:32) >> Like, (00:09:33) >> yeah. So, when somebody like even when (00:09:35) the president issues an executive order, (00:09:37) that's got to go through a whole bunch (00:09:38) of people until ultimately it is (00:09:39) implemented at a computer somewhere. (00:09:42) And if you want to know what what the (00:09:43) situation is with the accounting and (00:09:45) you're trying to reconcile accounting (00:09:46) and get rid of waste and fraud, you must (00:09:48) be able to analyze the computer (00:09:49) databases. Otherwise, you can't figure (00:09:51) it out. Um because all you're doing is (00:09:53) asking a human who will then ask another (00:09:56) human, ask another human and finally (00:09:58) usually ask some contractor who will ask (00:10:00) another contractor to do a query on the (00:10:02) computer. (00:10:03) >> Wow. (00:10:04) >> That's how it actually works. So it's (00:10:06) many layers deep. Um so the only way to (00:10:09) reconcile the databases and get rid of (00:10:10) waste and fraud is to um to actually (00:10:13) look at the computers and see what's (00:10:15) going on. So, so you (00:10:16) >> that's what I call that's like (00:10:20) that's what I when I sort of cryptically (00:10:22) refer to reprogramming the matrix. You (00:10:24) have to understand what's going at the (00:10:25) computers. You have to reconcile the (00:10:27) computer databases uh in order to (00:10:29) identify the waste and fraud. I don't (00:10:31) know that there was anyone in Congress (00:10:35) who understood, certainly myself (00:10:37) included, who understood the leverage (00:10:39) that comes from the computer and the (00:10:42) data in particular that that Congress (00:10:44) would think about give me a report on (00:10:46) what your expenditures are rather than (00:10:49) actually getting into the pipes. And I (00:10:50) think that has been fascinating that (00:10:53) it's let you uncover a bunch of crap (00:10:55) that just nobody knew. (00:10:57) >> Yes. I mean, in order for money to go to (00:11:00) a bank account, it it's it's not like (00:11:02) we're sending truckloads of cash all (00:11:03) over the place. We're it it's a we're (00:11:06) wiring money, right? We're sending money (00:11:07) through the AC system or through the (00:11:09) Swift system. So, in order for money to (00:11:11) flow, it's going to flow electronically. (00:11:13) >> So, that's that's what you need to look (00:11:14) at. You need to look at the the the (00:11:15) actual electronic money flows. (00:11:17) >> And Tesla and all your companies, you (00:11:19) have accounting and you have every (00:11:20) expenditure. You have it coded for what (00:11:22) it's going for. (00:11:23) >> Federal government doesn't work that (00:11:24) way. They don't code what the money is (00:11:26) going for. (00:11:26) >> They do not. But they didn't. (00:11:28) >> They didn't. (00:11:29) >> And and like one of the things that that (00:11:30) that you told me, you said if any (00:11:32) company kept its books the way the (00:11:34) federal government does, they'd arrest (00:11:36) the officers and put them in jail. (00:11:38) >> Yes. If it was a poly company, it would (00:11:39) be delisted immediately. It would fail (00:11:41) its order. Uh and the the officers of (00:11:43) the company would be imprisoned. That's (00:11:45) the level of healthiness in the federal (00:11:47) government. Unfortunately, (00:11:49) >> it's deliberately or do you think this (00:11:51) is incompetence? Again, (00:11:53) >> it's 80%. It's 80% (00:11:56) incompetence or and 20% malice. (00:11:58) >> So if if you look at (00:12:00) >> if you look at Doge now and you look at (00:12:03) the government and what you're finding, (00:12:06) what percentage have you guys even (00:12:08) gotten to and how much of it is Mars (00:12:11) where you haven't even gotten there yet (00:12:12) because there's so much you're finding (00:12:14) out here. I mean, how many You seem like (00:12:16) a timeline guy when you say, "All right, (00:12:17) I want to get in there and get all (00:12:18) these, you know, numbers and things." (00:12:20) How far are we from the endgame where (00:12:22) you've seen it all, been able to process (00:12:24) it all and fix it? I mean, are we years (00:12:28) away, months away? (00:12:30) >> Uh, not years. (00:12:32) Um, (00:12:34) I I I mean, I'm reasonably confident (00:12:36) that we'll be able to get a trillion (00:12:39) dollars of waste and fraud out. uh and (00:12:44) that that meaning that it will have (00:12:46) we'll have a net savings in FI26 which (00:12:49) starts in October obviously um of of a (00:12:51) trillion dollars (00:12:52) >> provided we allowed to we're allowed to (00:12:54) continue and and and our progress is not (00:12:56) impeded and and and we're very public (00:12:58) about what we do (00:12:59) >> yeah put it on the website I don't know (00:13:01) how we could be more transparent uh (00:13:03) literally every action we do small or (00:13:05) large we put on the doge.gov website. (00:13:08) Uh, and we post on on the X handle. Um, (00:13:11) and when people complain about it, I I I (00:13:13) and they say, "Oh, you're doing (00:13:14) something on costume." I'm like, "Well, (00:13:15) which of these cost?" (00:13:16) >> You're doing it in the daylight. I mean, (00:13:18) everyone knows exactly what you're (00:13:19) doing. (00:13:20) >> Extreme transparency. (00:13:22) >> Um, I don't think it's anything's been (00:13:24) this transparent ever. (00:13:25) >> So, five years ago, you were a hero to (00:13:28) the left. You were cool. You had (00:13:30) electric cars. You had space. And in (00:13:33) five years, you (00:13:34) >> go to I could go to a party in Hollywood (00:13:36) and not get dirty looks. (00:13:37) >> Yeah. Yeah. (00:13:38) >> In fact, uh Yeah. (00:13:39) >> And (00:13:39) >> no, you might not even get invited. (00:13:41) >> Get invited. But I don't know if I (00:13:42) should go. (00:13:45) >> And I don't think it's an exaggeration (00:13:46) to say today after Donald Trump, (00:13:51) the left hates you more than any person (00:13:52) on earth. (00:13:53) >> Uh yes, I appear to be number two. I (00:13:56) mean, if you judge by the various signs, (00:13:58) >> they (00:13:59) >> It's derangements. It's Trump (00:14:00) derangement syndrome and Elon (00:14:02) derangement syndrome. How is it that for (00:14:04) you? That's a little bit of whiplash of (00:14:06) going from being like Mr. Cool to the (00:14:09) devil incarnate in just a couple of (00:14:11) years. Is that is that kind of weird to (00:14:13) experience that transformation? (00:14:14) >> Yes. (00:14:15) >> Why do they hate you so much? (00:14:18) >> Well, because we're we're clearly over (00:14:20) the target. If Doge was ineffective, if (00:14:23) we were not actually getting rid of a (00:14:25) bunch of waste and fraud and a bunch of (00:14:27) that fraud, uh I mean the fraud re we're (00:14:30) seeing is over overwhelmingly on the on (00:14:33) the left. (00:14:34) >> Mhm. (00:14:34) >> I mean there's it's not zero on the (00:14:36) right, but uh these NOS's are almost all (00:14:39) leftwing NGOs's that are being funded (00:14:41) for example. (00:14:41) >> Yeah. (00:14:42) >> Um so they they hate me because Doge is (00:14:46) being effective. Um, and Doge is getting (00:14:49) rid of a lot of uh waste and for that (00:14:51) they were that people on the left were (00:14:53) taking advantage of that. That's that's (00:14:55) that's that's what it comes down to. And (00:14:56) and the the the single biggest thing (00:14:58) that they're that they're worried about (00:15:00) is that um Doge is is going to turn off (00:15:05) fraudulent payments of entitlements. Uh (00:15:07) I mean everything from social security, (00:15:09) Medicare, uh you know, unemployment, (00:15:12) disability, uh small business (00:15:14) administration loans, turn them off to (00:15:18) uh illegals. This is the crux of the (00:15:21) matter. (00:15:21) >> Y (00:15:21) >> Okay. This is this is the this is the (00:15:24) thing that why why they really hit my (00:15:26) guts and want me to die. (00:15:27) >> Um (00:15:28) >> and do you think that's billions, (00:15:29) hundreds of billions? What do you think (00:15:30) the scale is of that? I think across the (00:15:33) country it's it's in the it's well north (00:15:35) of 100 billion maybe 200 billion. (00:15:37) >> Um so uh by by using entitlements fraud (00:15:43) the Democrats have been able to attract (00:15:45) and retain vast numbers of illegal (00:15:49) immigrants (00:15:50) >> and and by voters (00:15:51) >> and and by voters. Exactly. the and (00:15:55) basically bring in I don't know 10 20 (00:15:58) million uh people who are beholden to (00:16:00) the Democrats for government handouts (00:16:03) >> and will vote overwhelmingly Democrat as (00:16:06) has been demonstrated in California. (00:16:08) This is overwhelm (00:16:09) >> it's an election strategy. (00:16:11) >> Yes. It's power. (00:16:12) >> Yes. And and it doesn't take much to (00:16:14) turn the swing states blue. I mean often (00:16:16) a swing state might be won by 10 20,000 (00:16:18) votes. (00:16:18) >> Sure. So, if the Dems can bring in (00:16:20) 200,000 illegals and over time get them (00:16:24) legalized, not not counting any cheating (00:16:26) that takes place because there is some (00:16:27) cheating. Uh, but even without cheating, (00:16:30) if you if you if you make if you have if (00:16:32) you bring in illegals that are 10x the (00:16:34) voted differential in in a swing state, (00:16:36) it will no longer be a swing state, (00:16:37) >> right? (00:16:38) >> Um, and the the dams will win all the (00:16:40) swing states. Just a matter of time. Um, (00:16:43) and America will be permanent deep blue (00:16:46) socialist state. where uh the the House, (00:16:49) the Senate, (00:16:50) >> Yep. (00:16:51) >> uh the presidency and the Supreme Court (00:16:53) will all go hardcore them. (00:16:55) >> They will then further cement that by by (00:16:57) ex bringing in even more aliens. So you (00:16:59) you can't vote your way out of it. (00:17:02) >> Their objective is one party socialist (00:17:05) state and it'll be much worse than (00:17:06) California because at least California (00:17:07) is mitigated by the fact that someone (00:17:09) can leave California. (00:17:10) >> You can go to Texas. (00:17:11) >> Yeah, exactly. (00:17:13) >> They're going to make everywhere (00:17:14) California but worse. By the way, the (00:17:15) middle of the pandemic, I spent 45 (00:17:18) minutes on the phone with Elon. He was (00:17:19) still in California. I was walking my (00:17:22) dog, Snowflake, and trying to convince (00:17:24) you, come to Texas. The commies in (00:17:26) California can't stand you. We love you. (00:17:29) We want you here. And you didn't quite (00:17:30) go then, but you went not that long (00:17:32) afterwards. I mean the the the co (00:17:34) actions u almost killed Tesla uh because (00:17:38) they they let every other auto plant in (00:17:40) the country was allowed to open but ours (00:17:42) which was in California was not allowed (00:17:44) to open. (00:17:45) >> Wow. (00:17:45) >> Wow. (00:17:46) >> So they almost killed Tesla. (00:17:48) >> So as a as a personal matter did do you (00:17:52) ever regret it? Like five years ago you (00:17:54) go to the Oscars and we're Mr. Cool and (00:17:56) now you're you've got death threats (00:17:58) every day. Like do do you (00:17:59) >> Well, these days the Oscars are boring. (00:18:02) I wouldn't want to go. (00:18:03) >> God bless the movies they nominate no (00:18:04) one on earth has ever seen. Like like (00:18:06) could they actually nominate a movie (00:18:07) that human beings go watch? (00:18:09) >> I mean the how many great movies have (00:18:11) come out in the last several years? Very (00:18:13) few. (00:18:14) >> Depressingly few. (00:18:15) >> Yeah. Very few. The last Oscars came and (00:18:17) went. I didn't even watch it. There's (00:18:18) nothing to see. (00:18:19) >> I I was sad that Gene Hackman just (00:18:22) passed away because Unforgiven was (00:18:23) spectacular, but that was a long time (00:18:24) ago when Unforgiven came out. you you've (00:18:26) mentioned today here and before about (00:18:30) the possibility of someone wanting to (00:18:32) take you out, dealing with the death (00:18:34) threats. We see (00:18:36) >> it's not in my imagination. You could (00:18:37) just look on social media. (00:18:38) >> Yeah. (00:18:39) >> But like is is it because (00:18:41) >> that very clear? (00:18:42) >> Yeah. And look, I'm I'm very familiar (00:18:43) with that. (00:18:44) >> And they've got signs there people with (00:18:45) signs and demonstrations uh saying that (00:18:48) I need to die. Do do you think are these (00:18:51) just whack jobs or do you think there (00:18:53) are jobs (00:18:55) >> foreign sane people? (00:18:56) >> Do do you think there are foreign (00:18:58) entities behind this? Do you think (00:18:59) they're domestic entities behind the the (00:19:01) threats and also the attacks to Twitter (00:19:03) like not Twitter Tesla? I mean, you (00:19:06) know, you're getting Tesla's charging (00:19:09) stations lit on fire. Do do you think (00:19:10) that's organized and paid for? Uh (00:19:13) >> yes, at least some of it is organized (00:19:15) and paid for. um I think by domestic uh (00:19:20) you know what basically leftwing (00:19:23) organizations in America um funded by uh (00:19:28) leftwing billionaires essentially (00:19:30) >> is it like act blue or what (00:19:32) >> act blue is one of them um you know (00:19:36) Arabella you know the classic it's (00:19:37) funded by the you know the the the (00:19:42) blue basically the the left-wing NGO (00:19:46) Cabal, (00:19:47) >> how big of a thread is this to like what (00:19:48) you built at Tesla? I mean, I remember (00:19:50) when Teslas came out, it was people that (00:19:52) they didn't want to have gas cars. A lot (00:19:54) of it was environmental reasons. I (00:19:56) jokingly said, I was like, I'm a Texas (00:19:58) guy. I'm always going to have something (00:19:59) that burns gas. My kids now, all three (00:20:02) of my boys (00:20:04) think that the that Teslas are awesome. (00:20:07) The Cyber Truck is the car they want (00:20:09) their dad to buy, which I laugh because (00:20:11) I never could have imagined that 5 years (00:20:13) ago. And now I'm looking at, (00:20:15) >> well, we're at the White House and the (00:20:16) president's Tesla's parked right outside (00:20:18) the West Wing, which is the coolest damn (00:20:19) thing. (00:20:20) >> But I mean, you've changed a generation. (00:20:21) When you look at my kids are six and (00:20:23) eight and they're going, "Dad, buy a (00:20:24) Cyber Truck and I'm considering it." (00:20:27) That's a that's a full circle in a weird (00:20:30) way. (00:20:30) >> Yeah. Well, I do have this theory that (00:20:32) the most entertaining outcome is the (00:20:33) most likely. So, um yeah, it seems often (00:20:39) to be true. You say like what uh what (00:20:41) twist or turn of fate (00:20:43) >> uh would generate the highest ratings if (00:20:46) this was if we were a TV show what twist (00:20:48) or turn of fate would generate the (00:20:49) highest ratings that there's a good (00:20:51) chance that happens. (00:20:52) >> Well, I will say if if Act Blue and (00:20:55) Arabella Network (00:20:56) >> Act Blue is a huge scam next level. (00:20:58) >> Do you think it's foreign money, Chinese (00:21:00) money? Where do where do you think the (00:21:01) money in Act Blue is coming from? How do (00:21:03) you figure that out? Well, it's not (00:21:05) coming from the from a whole bunch of (00:21:07) from a a ground swell of public support. (00:21:09) Yeah. Uh because when individual donors (00:21:12) are looked at in act blue, they a bunch (00:21:14) of them turn out to be like die hard (00:21:16) Republicans, people that have never (00:21:17) given money in their life. So you go and (00:21:19) track down a bunch of these people where (00:21:21) it says, "Oh, I gave $16,000." And (00:21:23) they're like, "I didn't give $16,000. (00:21:24) What are you talking about?" (00:21:26) >> There's this (00:21:28) Republican friends of mine found (00:21:29) themselves on the act blue list. They're (00:21:30) like, "It doesn't want to me." So that's (00:21:33) >> if it can act actually be shown that (00:21:35) they are funding firebombing of Tesla (00:21:37) charging stations (00:21:40) that's objectively a criminal act that (00:21:42) that is funding terrorist activity and (00:21:43) and the statutes make clear that an (00:21:45) incendiary device (00:21:47) >> qualifies. So that's is a terrorist (00:21:49) activity. Yeah. (00:21:50) >> Yeah. Let me ask AI. (00:21:55) In 10 years, how is life going to be (00:21:58) different because of AI for for just a (00:22:00) normal person? (00:22:02) >> Well, 10 years is a long time. (00:22:05) In 10 years, probably AI could do (00:22:10) anything better than a human can (00:22:11) cognitively. Probably almost I think 10 (00:22:14) in 10 years based on the current rate of (00:22:16) improvement, AI will be smarter than the (00:22:19) smartest human. (00:22:21) Yeah. Yeah. Uh there there will also be (00:22:24) a massive number of robots. So, humanoid (00:22:27) robots. (00:22:28) >> By the way, I got to ask, how come your (00:22:29) robots look so much like the creepy (00:22:31) robots for my robot? Was Was that (00:22:33) intentional or just uh (00:22:36) >> I was hoping he was going to say, "Yeah, (00:22:37) just to mess with you. (00:22:40) >> It's not meant to look like any any (00:22:42) prior robot." Uh and we'll iterate the (00:22:45) design. Um, you and you you'll be able (00:22:47) to have a lot of the robot parts are (00:22:50) cosmetic. You'll be able to switch out (00:22:52) the kind of snap-on cosmetic parts of (00:22:55) the robot, make it looks like something (00:22:56) else if you'd like. (00:22:58) >> Um, so there will be ultimately billions (00:23:03) of humanoid robots. Uh, all cars will be (00:23:05) self-driving (00:23:08) >> in 10 years. (00:23:10) Uh in 10 years probably (00:23:13) 90% of miles driven will be uh (00:23:15) autonomous. (00:23:16) >> Huh. Wow. That fast. (00:23:19) >> Yeah. In 5 years probably 50% of all (00:23:23) miles well driven will be autonomous. (00:23:25) >> Now if AI will be smarter than any (00:23:27) person, how many jobs go away because of (00:23:30) that? And what do people do if you've (00:23:33) got millions of people that are losing (00:23:34) their jobs like that? A lot of people (00:23:36) are understandably freaked out about (00:23:38) that. (00:23:39) Well, (00:23:41) I goods goods and services will become (00:23:45) close to free. So, it's not as though (00:23:48) people will be wanting in terms of goods (00:23:50) and services. Um, (00:23:52) >> so why is that? What why are goods and (00:23:54) services free in an AI world or close to (00:23:58) free? Well, you'll have I don't know, (00:24:01) pull it tens of billions of robots (00:24:04) uh that that they will they will make (00:24:06) you anything or provide any service you (00:24:08) want (00:24:09) um for basically next to nothing. Um the (00:24:14) it's it's not that people will be uh (00:24:17) will have a lower standard of living. (00:24:18) They'll have actually a much higher (00:24:19) standard of living. The the challenge (00:24:21) will be (00:24:23) uh (00:24:25) fulfillment. How do you derive (00:24:27) fulfillment and meaning in life? (00:24:29) >> Is Skynet (00:24:31) real? Like like like you get the (00:24:33) apocalyptic visions of AI. (00:24:36) How real is the prospect of of killer (00:24:39) robots annihilating humanity? (00:24:42) >> 20% likely maybe 10%. (00:24:44) >> On what time frame? (00:24:48) >> 5 to 10 years. (00:24:50) So soon like you you you see a world (00:24:53) where that's possible. (00:24:55) >> Yeah. But I mean you could look at it (00:24:56) like the the glass is 80 90% full (00:25:00) meaning like 80% likely we'll have (00:25:04) extreme prosperity for all. (00:25:07) >> Now I guess my view we're in a race to (00:25:09) to win AI. We're in a race with China. (00:25:13) And my view is if they're going to be (00:25:14) killer robots, I'd rather they be (00:25:15) American killer robots than Chinese. (00:25:19) How likely are we winning right now? Is (00:25:22) America winning right now? And how (00:25:23) likely is America to win the race for AI (00:25:26) visa v China or anyone else? (00:25:29) For the next few years, I think America (00:25:30) is likely to win uh then it will be a (00:25:34) function of who controls the AI chip uh (00:25:37) fabrication. (00:25:40) The factories that make the AI chips, (00:25:41) who controls them? (00:25:44) If they are controlled, if more of them (00:25:46) are controlled by China, then China will (00:25:47) win. (00:25:49) >> More of the factories that are making (00:25:51) the AI chips, you you think that will (00:25:53) determine it? (00:25:54) >> Yes. (00:25:56) >> And how are we doing versus China on (00:25:58) that front? (00:25:59) >> Well, right now uh almost all the (00:26:02) advanced AI chip uh factories, they call (00:26:05) them fabs, (00:26:07) um are in Taiwan. (00:26:09) >> And what if China invades (00:26:10) >> 59 miles away from (00:26:12) >> Yeah. If what what happens if China if (00:26:14) China invades Taiwan? What happens to (00:26:16) the world? (00:26:19) >> Well, if they were to invade in the near (00:26:21) term, uh the world would be cut off from (00:26:24) uh advanced AI chips. (00:26:28) >> Currently 100% of advanced AI chips are (00:26:31) made in Taiwan. (00:26:32) >> How fast could we put that online in (00:26:33) America? And how important is that for (00:26:34) national security? (00:26:36) >> I think it's essential for national (00:26:38) security. Uh and we're not doing enough. (00:26:41) You're 53 years old. I'm 118 days older (00:26:44) than you. By what the hell have I done (00:26:46) in my life? (00:26:46) >> I know, right? (00:26:48) >> 53 years old. (00:26:49) >> Doing pretty well. (00:26:52) >> Well, (00:26:53) >> so 71 was a great year. (00:26:55) >> And I was December 70. So I was just (00:26:57) just right before you were the summer of (00:26:59) 71 (00:27:00) >> Um (00:27:01) >> I was born 69 days after 420. (00:27:04) >> Wow. I I I I did ask Ben. (00:27:06) >> Listen, no, this is true. Look, this is (00:27:08) true. All right. You just you just open (00:27:09) up a can of words. (00:27:10) >> I I did ask Ben, should I show up and (00:27:12) pull up a joint and say, "Can we beat (00:27:14) Rogan's views?" But but I was pretty (00:27:16) sure (00:27:17) >> uh it might cause a scandal if if we (00:27:19) spend a pot in the White House. (00:27:20) >> It just turned out to be like a (00:27:22) chocolate cigar. (00:27:23) >> Yeah. (00:27:25) >> Let me ask you, if if today was your (00:27:27) last day on earth, (00:27:28) >> Yeah. what (00:27:29) >> what I'm not suggesting it's going to (00:27:31) be, but if it were, what do you think (00:27:32) your biggest legacy would be? everything (00:27:34) you've done a 100 years from now, what (00:27:36) do you think people would remember if if (00:27:38) if if it were zero to today? (00:27:41) >> And will you ever go to space? (00:27:44) >> Uh in the in the distant future, 100 or (00:27:47) thousand years ago, if SpaceX got humans (00:27:50) to Mars, that's what they would remember (00:27:52) me for. (00:27:54) >> All right, final set of questions. Who's (00:27:56) the smartest guy you've ever met? (00:27:59) You hang out with some brilliant people (00:28:00) like like when you look what's a CEO you (00:28:03) look at other than yourself what CEO do (00:28:05) you say damn that guy's good? (00:28:10) Larry Ellison's very smart. (00:28:13) Um so I say Larry Ellison's one of the (00:28:16) smartest people. Um (00:28:19) you know Larry Page I mean there are a (00:28:21) lot of people that are very smart. It's (00:28:22) hard to say like (00:28:24) you know I think to some degree smart is (00:28:26) as smart does. (00:28:29) So (00:28:31) you know what have what have they done (00:28:33) that is (00:28:35) difficult (00:28:37) uh and significant? (00:28:39) Um you know Jeff Bezos is done a lot of (00:28:43) difficult and significant things. Um (00:28:47) I mean there are a lot of smart humans. (00:28:51) I call them smart for smart for a human. (00:28:53) A lot of people who are in the smart for (00:28:54) a human category. (00:28:56) >> All right, final lightning round. Star (00:28:58) Wars or Star Trek? (00:29:02) >> The first movie I saw in the theater was (00:29:03) Star Wars. So, I think it had a profound (00:29:05) effect on me. I was 6 years old, I (00:29:08) think. Imagine if (00:29:10) >> first movie you ever see (00:29:12) >> in a theater is Star Wars. That's going (00:29:14) to blow your mind. (00:29:15) >> Best Star Wars movie? (00:29:18) Um, Empire Strikes Back. (00:29:21) >> The The only objectively right answer. I (00:29:23) stood in line for three hours with my (00:29:24) dad to see it on opening day. (00:29:26) >> Kirk or Peard? (00:29:28) >> Uh, I like them both, but Kirk, (00:29:31) >> again, objectively right answer. By the (00:29:33) way, James T. Kirk is a Republican and (00:29:36) Peard is a Democrat. And And the left (00:29:38) gets very mad when I say that. (00:29:40) >> Yeah. (00:29:40) >> Uh, best Star Trek movie. (00:29:43) >> I mean, the original the first Star Trek (00:29:45) movie. Now that's incon (00:29:49) Wrath of Khan. (00:29:51) >> Actually, most both Wrath of Cons were (00:29:53) pretty good. But yeah, the original (00:29:55) Wrath of Khan, (00:29:56) >> Ricardo Monttoban, (00:29:58) Revenge is a dish best served cold. It (00:30:01) is very cold in space. (00:30:04) >> Although I will say Wrathan is (00:30:06) objectively the right answer, but but (00:30:08) four is a sleeper. when they go back to (00:30:10) San Francisco and and and go find the (00:30:13) whales and and you know Scotty picks up (00:30:15) picks picks up the mouth and talks to it (00:30:17) then goes a keyboard. How quaint. (00:30:20) >> That's a sleeper. All right, last (00:30:22) question. (00:30:24) Did Han shoot first? (00:30:28) >> It seemed like he shot second. (00:30:32) >> I like it. (00:30:32) >> This is verdict. And by the way, I (00:30:34) apologize Ben. So Ben was a jock and (00:30:36) played tennis at Old Miss and so so (00:30:38) occasionally when when we geek out a (00:30:40) little. (00:30:40) >> I love watching y'all geek out over (00:30:42) there first though because the guy (00:30:44) >> still on the question he missed his the (00:30:46) alien missed his blaster shot. So why' (00:30:48) he miss his blaster shot? Must have been (00:30:49) because he got shot first. (00:30:51) >> Now he's missing a point blank bassel (00:30:53) shot if unless they got knocked off (00:30:55) killed. (00:30:55) >> But it's a question of real question (00:30:58) >> which is is Han Solo simply a hero or an (00:31:01) anti-hero? And and so I'm in the Hanot (00:31:03) first category. I think I don't like (00:31:05) sanitized stories. (00:31:06) >> You would have had to have shot first (00:31:07) because otherwise why why would the (00:31:09) alien miss a point blank range? (00:31:11) >> Are you ever going to go to outer space? (00:31:13) Is that saying in your life goals? (00:31:14) >> Yeah, I'd like to go to Mars at some (00:31:16) point. And and people have said uh uh do (00:31:19) I want to die on Mars? And I say yes, (00:31:21) just not on impact. (00:31:23) >> Now that's a very good answer. The (00:31:25) astronauts on the space station, are (00:31:28) they political prisoners? (00:31:30) Some of them are (00:31:31) >> be because because you could have given (00:31:33) him a ride back and and and (00:31:36) >> Joe Biden said no purely for politics. (00:31:38) >> Yeah. I mean, you know, there's been (00:31:40) some uh debate about this online, but (00:31:42) the thing is that it it was very a very (00:31:44) high level decision. So, uh it wasn't (00:31:47) really even a NASA decision. It was just (00:31:49) that um the Biden White House did not (00:31:52) want to have someone who was proTrump uh (00:31:56) rescuing astronauts right before the (00:31:58) election. Um, so they pushed it. (00:32:00) >> Well, if you're one of those astronauts, (00:32:01) you got to be pretty pissed off about (00:32:02) that. (00:32:04) >> Well, if they're a Democrat, yes. (00:32:07) Republican, yes. But if a Democrat, like (00:32:09) everything's fine. (00:32:10) >> Fair enough. (00:32:10) >> Um, so I think one of them is a (00:32:12) Republican Democrat. So it depends on (00:32:14) which one you ask. (00:32:15) >> What year does man first set set foot on (00:32:18) Mars? (00:32:20) >> I think the soonest would be 29. (00:32:24) >> 29. (00:32:25) >> Yes. And I don't think it's more than (00:32:29) two to four years beyond that. (00:32:31) >> And that's not an unmanned. That's (00:32:32) that's a human being (00:32:35) putting his foot on the surface. (00:32:37) >> Yes. Best case would be 29. (00:32:40) >> And what do you what do you put the odds (00:32:42) of finding either alien life or evidence (00:32:45) of alien life? (00:32:47) >> I don't think we're going to find (00:32:48) aliens. (00:32:48) >> Okay. (00:32:49) >> Um (00:32:50) >> but do we find ruins? Do we find (00:32:52) remnants? We may we may find the ruins (00:32:54) of a long deadad alien civilization. (00:32:56) That's possible. And we may find uh (00:32:59) subterranean microbial life. That's (00:33:02) possible. (00:33:03) >> All right. If man lands on Mars in 29, (00:33:06) how soon after that do you land on Mars? (00:33:10) >> Remains to be seen. I'm not sure. The (00:33:12) important thing is that uh we uh build a (00:33:16) self-sustaining city on Mars as quickly (00:33:18) as possible. Uh the the key threshold is (00:33:24) when that city (00:33:26) can continue to grow, continue to (00:33:28) prosper. Even when the supply ships from (00:33:31) Earth stop coming at that point, even if (00:33:35) something would happen on Earth, it (00:33:38) might it might it might not be World War (00:33:39) II, but it might be that (00:33:42) >> uh a bad virus. (00:33:44) >> Yeah. Yeah. It might not be anything. (00:33:45) What I'm saying is like like say (00:33:47) civilization could die with a bang or (00:33:48) whooper. It may be that civilization (00:33:50) dies with a whimper rather than a bang. (00:33:52) Um or and simply loses the ability to (00:33:55) send ships to Mars. Um but so you (00:33:58) obviously need Mars to be become (00:34:00) self-sustaining and be able to grow by (00:34:01) itself. Um before the resupply ships (00:34:05) from Earth has stopped coming. That that (00:34:06) is the critical (00:34:09) civilizational threshold beyond which uh (00:34:12) the probable lifespan of civilization is (00:34:14) much greater. And how close are we (00:34:17) technologically to be able to do that? (00:34:19) To have a self- sustaining (00:34:21) settlement uh on the surface of Mars? (00:34:24) >> I think it can be done in 20 years, (00:34:27) >> but it would take 20 years. So, we're (00:34:29) not in 29. We're not there. What are we (00:34:31) missing? What are the big technologies (00:34:33) we we don't have? (00:34:34) >> A few people running around the surface (00:34:36) in a hostile environment is not going to (00:34:37) make it self-sustaining. (00:34:39) >> So, you're going to need on the order of (00:34:40) a million people uh maybe a million tons (00:34:43) of cargo. So, but you think we could (00:34:44) have a million people on Mars in 20 (00:34:46) years? (00:34:47) >> Yes. (00:34:48) >> And and what what's the technology we're (00:34:50) missing right now when you think about a (00:34:52) million people on Mars? Do we have the (00:34:54) ability to get water, to get food, to to (00:34:57) keep them safe? What I mean, what what (00:34:58) do we need to make that happen? (00:35:00) >> Well, you need to recreate the entire (00:35:02) base of industry of Earth. So, um, you (00:35:06) know, we're here at the top of of a (00:35:07) massive pyramid of industry that starts (00:35:10) with mining, uh, a vast array of (00:35:14) materials. Those materials going through (00:35:18) hundreds of steps of refinement. Uh, we (00:35:21) grow food obviously. Uh, we grow trees, (00:35:25) we make things out of the trees. Uh, (00:35:27) there's, you know, you've got to, you've (00:35:29) got to build all that on Mars. And Mars (00:35:30) is a hostile environment. It's um you (00:35:34) know it sometimes gets above zero on a (00:35:36) warm summer day near the equator on (00:35:38) Mars. (00:35:40) >> Meaning it's quite cold. (00:35:42) >> And how do you prep for that? (00:35:43) >> Well, in the beginning on Mars you have (00:35:45) to have a uh a life support habitation (00:35:50) module like you you need you can't just (00:35:52) live outdoors. You can't breathe the (00:35:53) air. (00:35:54) >> Like a dome you think is likely? (00:35:56) >> Yeah. Glass domes type of thing. Have (00:35:58) you identified a location on Mars that (00:36:02) is likely to be ideal for habitat? (00:36:05) >> Uh well, it might be Arcadia Planeta um (00:36:08) is one of the one of the good options. (00:36:11) That's uh one of my daughters is named (00:36:14) Arcadia after that. Um (00:36:17) >> and what makes that attractive? (00:36:19) >> My eldest son's middle name is uh Aris (00:36:23) Mars. (00:36:24) >> You've been thinking about this for a (00:36:25) long time. If you're naming your kids (00:36:26) around it. (00:36:27) >> My eldest kid is middle name is (00:36:30) essentially Mars. (00:36:32) >> When did you get the dream? Like I mean (00:36:33) >> he's 20 now. Turning 21 soon. (00:36:36) >> This is a decades old (00:36:38) >> Yeah. (00:36:39) >> dream. (00:36:39) >> So like when you were 10, did you look (00:36:41) up and say I'm going to Mars? (00:36:42) >> No. (00:36:45) >> No. I read a lot of science fiction (00:36:46) books and program computers. Uh, but the (00:36:49) first, funny enough, the first video (00:36:52) game that I sold was a space video game (00:36:56) called Blastar (00:37:08) and you've managed (00:37:11) everything you've touched has been an (00:37:13) extraordinary success. (00:37:15) >> Uh, yeah. (00:37:16) >> Well, yeah. Look, I mean, that's just (00:37:18) objectively right. So, what what has led (00:37:20) to that? Because there are other smart (00:37:21) people that that's not true and they (00:37:23) gaze at their neighbor and they don't do (00:37:24) anything. So, what what do you do (00:37:27) differently that makes you so effective? (00:37:30) Well, I suppose I have a philosophy of (00:37:31) curiosity. I want to find out (00:37:35) the nature of the universe, understand (00:37:36) the universe. Um, (00:37:41) and in order to do that, we have to (00:37:42) travel to other planets, see other star (00:37:45) systems, maybe other galaxies. (00:37:47) um (00:37:49) find perhaps other alien civilizations (00:37:51) or at least the remnants of alien (00:37:52) civilizations. (00:37:54) Um (00:37:56) gain a better understanding of where is (00:37:57) this universe going? Where did it come (00:37:59) from and what questions (00:38:02) do we not yet know to ask about the (00:38:04) answer that is the universe? (00:38:06) >> So let's go back 25 years late 90s. (00:38:10) You're at PayPal. How do you turn PayPal (00:38:13) into the success it was which which then (00:38:15) helped launch you to the next one and (00:38:17) the next? (00:38:18) >> Yeah, so I studied physics and economics (00:38:20) in college which is a good foundation (00:38:22) for understanding how the economy works (00:38:23) and how the how reality works. Um and (00:38:28) then um was going to do a PhD at (00:38:31) Stanford in um (00:38:35) advanced (00:38:36) uh ultra capacitors actually as a (00:38:40) uh potential means of uh energy storage (00:38:43) for electric transport. (00:38:46) Um put that on hold to start an internet (00:38:50) company. Um, I essentially came to the (00:38:53) conclusion that the internet was one of (00:38:54) those rare things and I could either (00:38:56) watch it happen while a grad student or (00:38:59) participate. (00:39:00) >> And I figured I could always go back to (00:39:01) grad school. You know, grad school is (00:39:02) going to be kind of the same. (00:39:04) >> But, uh, I I I couldn't bear the thought (00:39:07) of just watching the internet happen. (00:39:08) So, I wanted to be a part of building (00:39:09) it. So, I created a an internet company. (00:39:14) We did the first maps, directions, (00:39:15) yellow pages, white pages um, on the (00:39:18) internet. I actually wrote the first (00:39:19) version of software software just by (00:39:21) myself in 95 and um (00:39:26) we ended up selling that to compact (00:39:30) Texas company I guess. (00:39:30) >> Yeah. (00:39:31) >> Um for about $300 million in cash about (00:39:35) four years after I graduated. (00:39:36) >> Wow. (00:39:36) >> Wow. (00:39:37) >> So I should say just to preface that I I (00:39:40) graduated with about $100,000 in student (00:39:42) debt. So it wasn't uh (00:39:44) >> Yeah. You and me both. (00:39:45) >> Yeah. (00:39:46) >> Yeah. (00:39:46) >> Where's my money? (00:39:47) >> I'm right. Yeah, I know. Um, and when I (00:39:50) first arrived in North America, I (00:39:51) arrived with $2,500, (00:39:53) a bag of books, and a and a bag of (00:39:55) clothes. (00:39:57) >> All right. So, you sell the company for (00:39:58) 300 million. How How much does that (00:40:00) change your life? (00:40:01) >> Well, I got $21 million. Blackjack. (00:40:05) Um, and (00:40:08) but I wanted to do more on the internet. (00:40:11) So started a company called X.com (00:40:15) which merged with a company called (00:40:16) Confinity (00:40:18) uh which is Peter Teal and Max Leon. (00:40:20) >> Yeah. (00:40:20) >> And um the combined company was actually (00:40:23) at first still called X.com but we later (00:40:25) later changed the name of the company to (00:40:27) PayPal. (00:40:28) uh because of all the name changes, it's (00:40:30) kind of confusing, but the company that (00:40:32) people know as know as as as PayPal (00:40:34) today was actually I filed those (00:40:36) incorporation documents with that (00:40:38) company. (00:40:38) >> Interesting. (00:40:39) >> Yeah. (00:40:40) >> Well, and and as you know, Peter Teal (00:40:42) and I were buddies back in the mid '9s (00:40:45) before he went and did any of this. But, (00:40:46) you know, I became friends with him when (00:40:48) he was a corporate lawyer in New York (00:40:50) and just sort of a young libertarian (00:40:52) with with a lot of dreams. So, it's it's (00:40:54) been a heck of a journey. (00:40:55) >> Uh yeah. Yeah. And now obviously Peter (00:40:57) was involved in a coup uh you know we (00:41:00) had a little sort of knifing in the (00:41:02) Senate situation uh (00:41:06) where um (00:41:08) uh you know that they did kum me at at (00:41:10) at PayPal. Um I kind of (00:41:14) >> now did you all make peace after that? (00:41:15) >> Yeah. Yeah. Yeah. I mean, I was doing a (00:41:18) lot of sort of risky moves that I think (00:41:20) ultimately would have been successful, (00:41:21) but um I then went on a two-eek trip (00:41:25) which was a both a dual money raising (00:41:29) trip and honeymoon since I' not done my (00:41:32) honeymoon earlier in the year. So, I was (00:41:35) raising money while doing doing a (00:41:36) honeymoon, but I was kind of a waste. (00:41:38) >> How'd that go over by the way? (00:41:40) >> It worked. It worked. There you go. (00:41:42) >> Kind of it worked. I raised money. Yeah. (00:41:44) >> Yeah. (00:41:44) >> And we had a honeymoon. (00:41:45) >> There you go. So yeah, uh but you don't (00:41:49) want to be away from the battle when (00:41:50) things are scary. Um so I was not there (00:41:55) to assuage the concerns of the troops. (00:41:57) Um and um anyway, (00:42:01) uh we we passed things up and have been (00:42:05) friends uh nonetheless. And um (00:42:10) you know, these days I'll like stay at (00:42:11) his house and stuff. So I have several (00:42:12) friends and he he's also invested in in (00:42:14) most of my companies. (00:42:15) >> All right. So 2002 you you start SpaceX. (00:42:18) Like how do you start a rocket company? (00:42:20) Like what's the first day where you're (00:42:22) like I want to make rockets and I want (00:42:24) to go to Mars like what what do you do (00:42:25) on day one? So I think you have to start (00:42:28) with a some sort of philosophical (00:42:30) premise in order to have in order for (00:42:33) the in order to be in order to be highly (00:42:37) motivated you have to have some um (00:42:41) philosophical foundation. (00:42:44) In my case, it was um (00:42:48) that that we want to expand the sc the (00:42:50) the scope and scale of consciousness (00:42:53) to better understand the nature of the (00:42:55) universe. (00:42:57) >> Um and in order to to expand scan expand (00:43:01) consciousness, we need to go beyond one (00:43:03) planet. If we're on one planet, there's (00:43:06) there's too much risk. You know, (00:43:07) hopefully Earth civilization prospers (00:43:09) very far into the future, but it may (00:43:11) not. There's always some risk that we (00:43:12) are uh we self annihilate through (00:43:14) nuclear war or that there's a big meter (00:43:18) that takes us out like the dinosaurs. (00:43:19) >> Y (00:43:20) >> there's always some risk if all your (00:43:21) eggs are in one basket. So it's going to (00:43:23) be better if uh we're multilanet species (00:43:27) and then once we're multilanet species (00:43:28) that the next step would be to be (00:43:30) multi-stellar and have uh civilization (00:43:33) among on on many different star systems. (00:43:37) So, in 2001, I didn't think that I could (00:43:40) I didn't think I could sell Rock (00:43:41) Company. So, I I thought I'd take some (00:43:43) of the money from (00:43:45) um PayPal. In that that case, I think it (00:43:48) was about $180 million after tax, (00:43:52) >> something like that. And I thought, you (00:43:55) know, I don't need need $180 million, so (00:43:58) I'll spend a bunch of it on uh a (00:44:01) philanthropic Mars mission to (00:44:04) get the public excited about going back (00:44:06) to Mars or going to Mars, I should say. (00:44:10) >> Yeah. (00:44:11) >> Mars was always going to be the (00:44:12) destination after the moon, (00:44:13) >> right? Um, in fact, if you told people (00:44:15) in 19 in 1969 that it would be 2025 and (00:44:19) we've not even gone back to the moon, (00:44:20) let alone (00:44:21) >> it's hard to believe. (00:44:22) >> Let alone Mars, they'd be like, "What (00:44:24) happened? Did civil did civilization (00:44:26) collapse? (00:44:26) >> Stop." Yeah. (00:44:27) >> Like, like they would be (00:44:29) incomprehensible that we've not been to (00:44:31) Mars by now. If you told people this (00:44:33) after landing on the moon in ' 69, (00:44:35) >> why do you think in 50 years America (00:44:37) never went back to the moon? (00:44:39) Well, we destroyed the Saturn 5 rocket (00:44:41) that was that that could take people to (00:44:43) the moon and had the space shuttle which (00:44:44) could only go to low Earth orbit. Um, (00:44:47) and then there really hasn't been (00:44:50) anything to replace any no vehicle has (00:44:53) been made since then that can go to the (00:44:55) moon or to Mars until the SpaceX (00:44:58) Starship rocket. (00:44:59) >> Yeah. (00:45:00) >> So, can't go to Mars if you don't have (00:45:02) the ride. So, I remember you and I first (00:45:05) met in 2013 when when I was a brand new (00:45:09) baby senator (00:45:11) >> and I was still down in the basement (00:45:12) office. They stick freshman senators in (00:45:15) a basement office. Kind of like hazing. (00:45:16) >> Yeah. Yeah. I was supposed to say it (00:45:17) sounds like there are 100 Senate (00:45:19) offices, but for 6 months you stay in (00:45:20) the basement, (00:45:21) >> put you in your place. Basically, (00:45:22) >> it's like wearing beam. They just uh (00:45:23) >> they want you to know where you're (00:45:25) supposed to be. (00:45:25) >> You know, I got to say now 13 years into (00:45:27) it, I think there's a lot of wisdom to (00:45:28) doing that. (00:45:29) >> Sure. But you were down in the basement (00:45:32) office and I remember you were coming (00:45:33) and sitting down with SpaceX and at the (00:45:35) time (00:45:36) >> the Air Force was not letting you all (00:45:37) bid to to launch satellites. And so you (00:45:39) were coming and saying, "Look, we got a (00:45:41) company. I think we can do a really good (00:45:42) job of this and yet we're locked out of (00:45:44) this." (00:45:45) >> It's a little amazing to think the (00:45:47) journey SpaceX has gone from then to (00:45:49) now. (00:45:51) >> Uh yes, I it's hard to believe that this (00:45:53) is all real. Um because originally (00:45:56) consistent with my belief that we need (00:45:59) to become a multilanet species, I (00:46:01) thought the only way to do that would be (00:46:02) through NASA. So uh and I think I (00:46:05) thought well if if I can just get the (00:46:07) public excited about Mars, then they'll (00:46:09) do a mission to Mars. And (00:46:12) uh so initially my thought was to have (00:46:14) to send a small greenhouse uh with seeds (00:46:16) and dehydrated nutrient gel then land (00:46:19) the the greenhouse hydrate the seeds and (00:46:21) you'd see these this the sort of money (00:46:23) shot (00:46:24) >> the money shot would be green plants on (00:46:25) a red background. (00:46:26) >> Yeah. Um, I also recently learned that (00:46:29) money shot uh has a different meaning in (00:46:31) some other arenas, but (00:46:34) >> yeah, I'm glad you did that. It's a very (00:46:37) very different story. But but um (00:46:39) >> what I'm trying to say is the the the (00:46:41) captivating shot um would be the green (00:46:44) plants on a red background. Um and then (00:46:46) hopefully that would if we did something (00:46:48) like that that would get the public (00:46:49) excited about Mars. That would increase (00:46:50) NASA's budget and then we could send (00:46:52) people to Mars. Like (00:46:53) >> So your original dream was NASA to do (00:46:54) this? (00:46:55) >> Yes. Not you. No. The original original (00:46:57) original plan was uh (00:47:01) literally to to take a bunch of the (00:47:02) money from PayPal u and I guess by some (00:47:06) people's definition waste it with no no (00:47:08) profit (00:47:09) >> uh on a nonprofit thing to I wanted to (00:47:12) spend a whole bunch of my money for free (00:47:13) to get NASA's budget to be bigger so we (00:47:15) could go to friaking Mars. (00:47:16) >> Right. (00:47:16) >> Wow. (00:47:18) >> That's what I wanted. (00:47:19) >> So (00:47:19) >> that was the holy grail. (00:47:21) >> That's what I wanted. I was like (00:47:22) >> so when did you change go to Mars? (00:47:24) That's what I wanted to know. (00:47:25) >> Well, when when did it strike you? Okay, (00:47:27) you're going to have to do this if you (00:47:28) want. (00:47:29) >> Well, I'll tell you it gets crazier. All (00:47:30) right, it gets crazier. So So then I (00:47:32) couldn't afford any of the US rockets (00:47:34) because, as you know, the US rockets are (00:47:35) way too expensive. The boy lucky lucky (00:47:37) rockets are crazy money. I didn't have I (00:47:39) didn't even with 180 million way I could (00:47:41) have afforded. (00:47:41) >> How much were they back then? (00:47:43) >> Well, the (00:47:45) the with the additional stage to get to (00:47:49) Mars, it would have been about like 80 (00:47:50) million. So technically I could have (00:47:52) afforded one of them (00:47:53) >> but I wanted to do two in case one of (00:47:55) them didn't work. (00:47:56) >> Yeah. (00:47:56) >> So uh (00:47:58) >> and then I didn't have enough money for (00:47:59) that. And I I was sort of prepared to (00:48:02) you know I don't know waste half the (00:48:04) money. Uh and I figured if I had 90 (00:48:06) million left that'd be fine you know uh (00:48:08) but ideally all of it. (00:48:10) >> Mhm. (00:48:11) >> So I went to Russia twice to try to buy (00:48:13) ICBMs. (00:48:15) >> Oh interesting. (00:48:16) >> How'd that go? And who do you call? Uh, (00:48:19) the Russian rocket forces. (00:48:22) >> Do they sell ICBMs? Does that work? (00:48:24) >> Yeah. (00:48:26) >> You got to tell us a story then. I want (00:48:27) to know who. (00:48:28) >> Turns out you can buy anything in (00:48:30) Russia. (00:48:30) >> Yeah. (00:48:31) >> I like Please walk me down that. I want (00:48:34) to know how you made that phone call and (00:48:36) when you get there, how did that work? (00:48:38) >> And what do you tell your friends? Yeah. (00:48:40) Listen, I'm I'm going to rush advice in (00:48:41) ICBMs. I I might not return it, you (00:48:44) know, depends on the situation. (00:48:46) >> Literally. (00:48:48) >> Yeah. (00:48:49) Um, so I guess slightly less insane when (00:48:52) you uh when uh you understand that uh (00:48:55) the Russians had to demolish a bunch of (00:48:58) their ICBMs because of uh you know salt (00:49:01) talks like the peace because of (00:49:03) basically an agreement between the (00:49:05) United States and and Russia to reduce (00:49:07) the total number of ICBMs. Russia was (00:49:09) actually obligated to scrap a bunch of (00:49:11) their ICBMs. So you took the very (00:49:13) biggest ICBMs, you could convert those (00:49:15) into a rocket, add an additional stage (00:49:18) and and send something to Mars. (00:49:19) >> So So those are big enough with one more (00:49:21) stage to get to Mars. (00:49:23) >> To send a small payload to Mars. Yeah. (00:49:25) >> So the SS18. (00:49:27) >> So you try to buy CBMs. Do you succeed (00:49:29) or no? Or do you figure out you got to (00:49:31) build your own instead? (00:49:32) >> They kept raising the price on me. So um (00:49:38) cuz I figured like look, they're going (00:49:39) to throw these things in scrapyard (00:49:40) anyway. you should get a really good (00:49:42) deal, (00:49:43) >> right? (00:49:43) >> Um, (00:49:45) >> so the price started out at at 4 (00:49:47) million. Then the next conversation they (00:49:49) were at 8 million. Then the next (00:49:51) conversation they were at like 19 (00:49:53) million. And I'm like, this is before we (00:49:55) signed a contract. (00:49:56) >> By the way, was there another bidder? (00:49:58) Was there another bidder or were you the (00:49:59) only one trying to buy them? I (00:50:00) >> I think I don't know if there were other (00:50:02) bits, but they didn't mention any other (00:50:03) bits. (00:50:04) >> Yeah. (00:50:04) >> But I was like, man, if if the price is (00:50:06) increasing this much before the contract (00:50:08) signed, (00:50:08) >> Yeah. I'm really going to get fleeced (00:50:10) after the contract sign. (00:50:12) >> So, (00:50:14) so I got pretty frustrated there. Um, (00:50:18) actually, you know, in some cases, we (00:50:19) got into like shouting matches in (00:50:20) Moscow. (00:50:22) >> So, some guys shouting at me in Russian (00:50:25) and I'm shouting back at him with my (00:50:27) interp that really badly, (00:50:31) >> you know. I'm like, (00:50:32) >> "So, you are all I mean, you're all in. (00:50:34) >> Stop rubbing me off." (00:50:37) >> In Moscow. (00:50:38) >> Yeah. (00:50:40) >> So, uh, man, I should have recorded (00:50:43) that. That would have been wonderful for (00:50:44) the (00:50:44) >> How many days were you there negotiating (00:50:46) that first time? I mean, was this like (00:50:47) ongoing? (00:50:48) >> Yeah. Yeah. This this took place these (00:50:51) conversations took place over probably (00:50:53) six months or so. (00:50:54) >> Wow. Um so um and then the final trip (00:50:59) trip trip trip there was with the uh (00:51:01) with with was with Mike Griffin who (00:51:03) later became NASA administrator. Um (00:51:07) I I actually realized in the in the (00:51:08) course of this that my original premise (00:51:11) was wrong that that America actually has (00:51:13) plenty of will to go to Mars (00:51:16) >> but needs that it just needs a way to (00:51:19) Mars (00:51:20) >> um that is affordable um and that (00:51:22) doesn't break the budget, you know. As (00:51:23) you know, we couldn't even get to the (00:51:24) space station. We needed the Russians to (00:51:26) to get us to our own space station. (00:51:28) >> That was embarrassing. (00:51:28) >> It really was pitiful. (00:51:30) >> I'm not sure most Americans know just (00:51:31) how much we were being fleeced. Like I (00:51:33) think they got up to like $90 million a (00:51:35) seat. (00:51:35) >> Yeah. (00:51:36) >> Wow. (00:51:36) >> Yeah. For a seat that cost them like 10 (00:51:38) million. (00:51:38) >> It was pre- doge obviously. (00:51:40) >> But it was the only It was before (00:51:43) SpaceX. But but $90 million a seat for a (00:51:46) seat that cost him 10 million is high. (00:51:49) >> Yeah. It's a lot of money. (00:51:51) >> Yeah. Um, (00:51:52) >> so a few months ago you and I were down (00:51:55) in Bokeh Chica with the president for a (00:51:57) Starship launch and it is incredible (00:52:00) what you built in Bokh Chica. You know, (00:52:02) five years ago it was an empty beach at (00:52:04) the southern tip of (00:52:05) >> Texas. Yeah. (00:52:06) >> And it's now a city and and a factory (00:52:09) where you're building a rocket ship a (00:52:11) month with with incredible precision. (00:52:13) >> Yeah. (00:52:13) >> But one of the things you you said to me (00:52:15) when we were down there that really (00:52:16) stood out to me is is is you said your (00:52:18) philosophy on intellectual property. (00:52:21) talked to lots of CEOs they're like we (00:52:23) fight to guard our IP and and you had a (00:52:25) very different approach what's what's (00:52:27) your view of IP (00:52:28) >> patent for the weak (00:52:32) >> patent for those who innovate slowly (00:52:34) >> I I literally do not know anyone else in (00:52:36) business who would say something like (00:52:37) that like like it was a startling and (00:52:40) and and and what Elon said down there is (00:52:42) he said look this stuff I assume (00:52:44) everyone will steal everything but by (00:52:46) the time they steal it we'll be five (00:52:47) generations beyond and it won't matter. (00:52:49) >> Yes. Um at at at Tesla we actually open (00:52:52) sourced a lot of patents. So we said our (00:52:53) patents are anyone can use them for free (00:52:55) >> really. (00:52:56) >> Um yeah uh the only we only do patents (00:52:58) at Tesla to to avoid patent trolls (00:53:02) causing causing trouble. (00:53:04) >> So we'll try to look ahead say okay (00:53:06) patent trolls are going to going to (00:53:07) trial pat file patents to block certain (00:53:09) things we'll file patents and then open (00:53:11) source the patent make it free. I mean (00:53:13) it when I say patents for the week. Now (00:53:14) there there are a few uh cases in in say (00:53:17) with pharmaceuticals where it might cost (00:53:19) you a billion dollars to do a phase (00:53:20) three uh human trial (00:53:22) >> um but then subsequently the the drug is (00:53:25) very cheap to manufacture. (00:53:26) >> So cases there are some in my opinion we (00:53:29) should massively reduce what can be (00:53:31) patented (00:53:32) >> um and and and say because the whole (00:53:35) point of patenting is is to maximize (00:53:36) innovation not inhibit it. Um and in my (00:53:40) opinion, it's maybe a controversial (00:53:41) opinion, most patents inhibit (00:53:43) innovation. They do not help it. (00:53:45) >> Um (00:53:46) >> but there are case I want do want to (00:53:48) single out cases like where such as a (00:53:50) phase three clinical trial that might (00:53:52) cost a billion dollars, but the then the (00:53:53) drugs thereafter cost a few dollars to (00:53:56) manufacture and and if you can then (00:53:58) immediately copy those drugs for a few (00:54:00) dollars, no one will pay for the billion (00:54:01) dollar. (00:54:02) >> Free writer problem. (00:54:02) >> Free writer problem. Yeah. Exactly. So (00:54:04) you have to address the free rider (00:54:05) problem, but other than that, there (00:54:07) should be no patents. The ideas are (00:54:09) easy. (00:54:09) >> You want ideas to flow maximum to people (00:54:12) to get there faster and do things (00:54:14) bigger. (00:54:15) >> The idea is the easy part. Uh the hard (00:54:18) execution is the hard part. As the old (00:54:20) saying goes, it's 1% inspiration, if not (00:54:23) less than 1% and 99% perspiration. (00:54:26) >> But I'll say the perspiration part (00:54:28) you're really damn good at also because (00:54:30) you're making, you know, the companies (00:54:31) you're building (00:54:33) are actually building stuff. They're (00:54:36) building cars. They're building (00:54:37) spaceships. They're building things that (00:54:38) if they don't work, it's a real problem. (00:54:40) And and the precision you manufacture (00:54:43) things with. How do you get that level (00:54:45) of precision? How do you get how do you (00:54:47) build a culture? (00:54:49) >> You're not you're amazing at thinking (00:54:51) outside the box, but but what's (00:54:52) interesting is you're you may even be (00:54:54) better at execution, which is how do you (00:54:57) execute so effectively? (00:54:59) >> Well, I take a p physics first (00:55:01) principles approach to everything. It's (00:55:03) not as though I I I wanted to insource (00:55:06) manufacturing. It's just that I was (00:55:08) unable to outsource it effectively. (00:55:11) So, uh you know the idea in the (00:55:14) beginning of Tesla was that we would (00:55:16) outsource almost all the manufacturing. (00:55:20) Uh but then it turned out there was no (00:55:22) there were no good companies to (00:55:24) outsource manufacturing to which there (00:55:26) wasn't uh really really wasn't feasible. (00:55:29) outsource manufacturing actually is uh (00:55:32) the exception of the rule. Um and uh and (00:55:36) just over time we had to insource almost (00:55:38) everything for Tesla and same for (00:55:39) SpaceX. I became very good at (00:55:42) manufacturing because I had to. There (00:55:44) was no choice. (00:55:45) >> At this point I might know more about (00:55:47) manufacturing than any any human ever (00:55:49) has because I've done so many I've (00:55:51) manufactured so many different things in (00:55:53) so many different arenas. Um I think (00:55:56) probably more than anyone ever has. (00:55:58) Look, that's that sounds like an (00:56:00) astonishing statement, but it's not a (00:56:02) crazy statement. And and you're somehow (00:56:05) running Tesla and running SpaceX and (00:56:08) running X and running the Boring Company (00:56:10) and running Norlink and doing Doge. (00:56:14) How much do you sleep in a given night? (00:56:16) >> About six hours on average. (00:56:17) >> So about six. So So that's It wouldn't (00:56:20) have shocked me if you said three or (00:56:21) four. (00:56:21) >> So the next question is, how many hours (00:56:23) do you work a day? (00:56:24) >> I work almost every waking hour. And and (00:56:27) Ben, he he's not kidding at that. Like (00:56:30) when Elon and I were first getting to (00:56:31) know each other, (00:56:32) >> um I suggested I said, "Hey, let's grab (00:56:35) dinner sometime." And I don't know if (00:56:36) you remember what you said. You said, "I (00:56:37) I don't eat dinner. (00:56:39) >> I don't have social dinners really." (00:56:41) >> Right. I mean that Yeah. I mean, you (00:56:42) obviously eat food, but the idea (00:56:45) >> you're not going to restaurant for two (00:56:46) hours. (00:56:46) >> But the idea of like I I don't But it (00:56:49) was it was just kind of matter of fact. (00:56:51) Why would I go to dinner? Like I you (00:56:54) just you work. (00:56:56) >> Uh yeah, I I literally just I'll have (00:56:58) lunch and dinner during meetings and (00:57:00) continue the meeting. (00:57:02) >> How many nights have you slept at your (00:57:04) offices you think your career (00:57:06) percentage-wise (00:57:08) where you say I just got to take this (00:57:09) nap basically because my body forces me (00:57:11) to and I got to get back to work fast (00:57:13) and efficiently without going somewhere (00:57:15) else. Well, I guess it started out even (00:57:19) with with the first company, (00:57:21) uh, Zub 2, which is a terrible name, but (00:57:24) the first internet company, um, the we (00:57:28) were able to rent an office, uh, which (00:57:30) was like in a leaky attic essentially (00:57:32) for $500 a month, and the the cheapest, (00:57:36) um, apartment we could find was $800 a (00:57:38) month. (00:57:39) >> So like, and we only had about $5,000 (00:57:42) between my brother and I. So like we're (00:57:44) not we we'll just stay in the office. (00:57:47) >> Yeah. (00:57:47) >> Uh so we got some um (00:57:50) couches that converted into beds um and (00:57:53) we'd uh kind of sleep at night and then (00:57:56) we just have to like uh turn the the (00:57:59) beds back into couches (00:58:01) uh before anyone came. And then we we'd (00:58:03) shower at the YMCA down the road. (00:58:06) >> And so that went that that that that (00:58:08) literally was the (00:58:10) >> for several months what we did. I was in (00:58:12) great shape, you know, uh work out the (00:58:14) why. Um I still remember that that YMCA (00:58:18) uh at Paige Miller Al Camino uh in Palo (00:58:22) Alto. (00:58:23) >> So that was a long time ago. (00:58:24) >> So it's been I don't know I've never (00:58:26) thought to count it, but uh several (00:58:29) hundred days maybe. I don't know. (00:58:31) >> So you're now the richest man on Earth. (00:58:33) Do you still sleep at the office? (00:58:35) >> Well, that's true. I maybe Mars will (00:58:37) we'll we'll find someone else. But I (00:58:39) think if if someone is a sovereign head (00:58:41) of a country, they're de facto richer by (00:58:43) a lot. (00:58:44) >> Do you still sleep at the office now? (00:58:46) >> I sometimes slept at the office. Yeah. (00:58:48) >> Well, thank you, Elon. This this was (00:58:49) this was awesome. And and let me say, (00:58:51) and by the way, (00:58:53) >> I I put out on X the day before (00:58:55) yesterday, if you were having a beer (00:58:56) with Elon and could ask him anything, (00:58:58) what would you ask? And got lots of (00:59:00) responses. (00:59:01) >> The most common response people said is (00:59:03) is is say thank you. that look, Texans (00:59:06) and the American people appreciate what (00:59:08) you're doing. You don't have to put up (00:59:09) with this BS and you're doing it. I'm (00:59:11) grateful. You're making a hell of a (00:59:13) difference for this country. I (00:59:15) appreciate you and the Americans (00:59:16) appreciate you. Thank you. (00:59:17) >> Yeah. It's essential for the future of (00:59:18) civilization. Otherwise, I wouldn't be (00:59:20) doing it. (00:59:20) >> Yes. (00:59:20) >> So, like I want to get death threats, (00:59:22) you know. (00:59:22) >> No, don't forget we do this show Monday, (00:59:24) Wednesday, and Friday. Hit that (00:59:26) subscribe or auto download button from (00:59:27) the White House. It's been a pleasure. (00:59:29) Thanks for being with us on Verdict. (00:59:30) We'll see you guys back here in a couple (00:59:32) days. (00:59:50) Jefferson.