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Elon Musk Discuss The Future! · Elon Musk Thinking

• 0:00
  You know, it's somewhat frankly predictable. Yes, yes, well that's not
• 0:05
  what we're about. As you know, at ARC, we're all about the
• 0:09
  future, trying to figure out the way the world's going to work. And
• 0:14
  well, I'd love to give you an opportunity right now to you know,
• 0:19
  address what you think mainstream media does not understand because there's such a big story
• 0:26
  here. There are so many big stories that you know, offer all kinds
• 0:30
  of hope and you know, really transformation in the future, and you're leaving
• 0:37
  the charge. So what don't they get, do you think, and what
• 0:41
  would you like to what would you like them to understand? Well, I
• 0:47
  think that's quite a long list of things that don't understand or where they basically
• 0:53
  don't wish to focus on because it doesn't quite lead to clicks and traffic.
• 1:00
  So I guess, I guess I could I could you know, go over
• 1:07
  at a high level what space Exit has are accomplishing or have accomplished this year.
• 1:12
  You know, well you just said that like media is a dwindling pie,
• 1:17
  and you own a big kind of like media platform franchise. How do
• 1:19
  you think about the future of X within that context, and how it should
• 1:25
  evolve. Well, I mean X is actually growing in traffic, so I
• 1:34
  mean, again when doesn't know quite which to believe. But uh, the
• 1:37
  you know, when you look at the traffic numbers, the traditional media is
• 1:41
  down, but but X's is up, So you know, I think that's
• 1:47
  you know, of course for optimism. But of course the traditional media would
• 1:51
  never actually write a story about that. I'm not going to write a story
• 1:53
  that says, hey, we're losing an X is winning is a very unlikely
• 2:00
  headline. In fact, you see the opposite headlines which are quite misleading that
• 2:06
  X FK Twitter is dying or dead or whatever. I mean, how many
• 2:09
  times have we seen that headline. It's getting a little tedious. I mean
• 2:13
  you can just press, you know, repost the same thing every month,
• 2:17
  is what it seems like. So you know, that's you know, So
• 2:23
  I think I feel quite optimistic about the sort of X platform and where it's
• 2:27
  going. And we're adding a ton of functionality that I think people will find
• 2:32
  useful. There's been immense progress in just the course of a year. We've
• 2:38
  accomplished more advancements in a year than I think in the Twitter done in the
• 2:44
  prior at least five years. So, yeah, one of the we've been
• 2:50
  talking a lot about X. We know, we own it in our venture
• 2:55
  fund, and we've been talking about, you know, the democratization that you
• 3:04
  are enabling in many ways. We were just going back to Tesla. You'll
• 3:08
  remember that, you know when when Tesla, when you were thinking about taking
• 3:16
  a private I implored you, you know, no, you know the you
• 3:22
  know we've been supporting We the retail investor and others have been supporting Tesla,
• 3:28
  don't take it private. You'll you'll take it you know away, this incredible
• 3:31
  growth opportunity. And so thank you for that. That was a democratization move.
• 3:36
  But Twitter, yeah, should I should say that that, you know,
• 3:39
  your little play was influential, you know, played as a significant role
• 3:45
  in the decision ultimately not to take the company private. We could have taken
• 3:49
  the company private. The downside was that it would have been quite a big
• 3:53
  distraction. So and of course it would would have made it difficult for many
• 4:00
  investors to remain invested. And I mean the combination of factors of complexity having
• 4:05
  to leave behind so many investors. Really that was Those are the two factors
• 4:12
  that you know why we decided not to take company private. We absolutely could
• 4:16
  have. I want to be just absolutely super clear, No, no,
• 4:20
  I know that, And we did have funding secured, so you know,
• 4:28
  it was six more than enough funding. You know, it's it's it's worth
• 4:31
  bear in mind that, you know, I was sued in a San Francisco
• 4:35
  court which which was jury shopped by a class action plaintiff law firm. It's
• 4:42
  always it's important bear in mind in these class action laws lawsuits, the media
• 4:46
  will actually write as though it is actually an aggrieved shareholder, but in fact
• 4:49
  it is not. The true plaintiff is the class action law firm, and
• 4:54
  the plaintiff is simply a puppet. Yes, so, but the media never
• 5:00
  never mentioned this. You took Twitter private, was, you know, to
• 5:05
  to really enable free speech? And again the whole democratization, this democratization concept,
• 5:15
  you know, we're we're all about that as well. We give our
• 5:19
  research away. We want people to understand how how much the world's changing,
• 5:26
  how technologically enabled innovation is going to transform could transform everyone's lives for the better
• 5:32
  if they get on the right side of change. So so, yeah,
• 5:39
  thank you, Well, absolutely so. The there's that kind of like maybe
• 5:46
  an augment that sounds or kind of esoteric. But it's the way I actually
• 5:53
  think about it that you can think of the X platform or social media in
• 5:58
  general as kind of a collective consciousness or group mind, and you want to
• 6:06
  have as much signal and as little noise as possible. And obviously we've got
• 6:11
  a lot of work to do on that front. But you want your information
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  to becoming you from people who are experts in the field or who are in
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  the case of let's say a war zone, literally in the field, and
• 6:28
  as opposed to filtered through journalists who are not experts in the field and who
• 6:35
  most of the time from probably ninety nine percent of time are literally not in
• 6:39
  the scene. At the scene, there's only a few reporter, sometimes only
• 6:43
  one reporter at the scene. So now, in the past that it was
• 6:49
  the only way to have things work. That's why, you know, so
• 6:53
  the legacy structure in the past was you had to have information filtered to media
• 6:59
  organizations and then too and then and then they would decide what to publish,
• 7:06
  and they publish it, and then people would read really a small subset of
• 7:11
  what was actually going on in the world, and obviously a subset that was
• 7:15
  chosen by a handful of editors curated, Yeah, curated. So it's it's
• 7:20
  sort of if the editors weren't that interested in the subject, you simply didn't
• 7:24
  care about it. So now that's in the past, especially in a non
• 7:32
  Internet world, that's kind of how things. There was really another way to
• 7:35
  do it. You didn't really have a mechanism for connecting all of the humans.
• 7:42
  But now with the Internet and a fast moving social media or what social
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  media is terrible word, but fast moving sort of platform, like like the
• 7:51
  X platform, you can actually get have all of the you can get all
• 8:01
  the people out there that are on the platform, reporting information, distilling it
• 8:05
  down, have people who are who are world class experts in their field tell
• 8:13
  you exactly what's going on. I mean, if you see, for example,
• 8:15
  the AI discussions on X are by far the best relately, absolutely absolutely.
• 8:22
  You know, Elon we I conceived of this open source research ecosystem that
• 8:28
  we've evolved in twenty twelve. I never dreamed that Twitter at the time,
• 8:35
  it was for tweens and teens and celebrities, and there's still some of those
• 8:41
  on BED. I never dreamed that it would become our primary platform for giving
• 8:46
  away our research and having dialogue with the people in the field out there who
• 8:52
  are innovating. You know, we're getting information that no one else in the
• 8:56
  financial world doing it the traditional way is getting just because we are engaging with
• 9:03
  these you know, with the innovators. So it's it's a marvelous platform.
• 9:09
  And I think it's the knowledge workers platform. Yeah, hi, Elen,
• 9:16
  this is Jelly. Hey, how's it going it? It would be great
• 9:20
  to learn more about how you're thinking actually about the roadmap to expand X from
• 9:26
  where you see it today to where you see it becoming and risks, challenges
• 9:30
  and also opportunities of that including AI and how you see that that transition well
• 9:39
  along lines of what I was saying earlier, the it's it's really true kind
• 9:46
  of create a group mind or collective consciousness where every person is essentially a part
• 9:56
  of that group minor electical and is kind of reporting information to the system,
• 10:05
  consuming information, giving their opinion on it. And you can just think about
• 10:11
  like a giant brain basically, And you know, I posted I think a
• 10:16
  few years ago that a neuron doesn't feel like it's it doesn't know it's a
• 10:20
  neuron, So right, Uh, you know, individuals on the system.
• 10:28
  Obviously you feel like an individual, but actually you are actually part of a
• 10:31
  collective sort of group mind. And and then you know, see if they
• 10:37
  say, well, what makes it a better or worse? You know,
• 10:43
  collective consciousness, it's it's well ups these feed is very important. How fast
• 10:48
  is information being transmitted? How is is that information is the most interesting information
• 10:56
  being propagated to the the right other people as quickly as possible. You know,
• 11:05
  how much noise is in the system. Noise would be information that is
• 11:09
  either not interesting. Uh, obviously spam, scams, actual misinformation. But
• 11:18
  you know that that that that term is overused, but just say, like
• 11:24
  just say information that that that that is deviates from the truth meaningfully, because
• 11:30
  there's always this question of what is the truth? You know, and it's
• 11:35
  like there's an old sort of police saying, uh, you know, for
• 11:37
  any given crime, there are at least three stories, the victim, the
• 11:41
  perpetrator in the truth, right, you know, or you know, uh,
• 11:48
  the well that coursa movie Rassamon where they the same event happens and you
• 11:56
  see that perceived completely differently by four different people. So but nonetheless, one
• 12:03
  can still aspire to the truth and have the least aspire to have the least
• 12:07
  amount of error. So so that's that's really Uh, that's the main thing
• 12:15
  is is like how do we get as many people as possible participating in providing
• 12:20
  information that's accurate correcting information that is not accurate. And just if you think
• 12:28
  of it, sort of like it from an information theory standpoint, this is
• 12:31
  like, I think the right way to think about it. Think about it
• 12:33
  from an information theory standpoint. You want to have what would make for the
• 12:37
  most effective group mind or collective consciousness, and it's it's like all the neurons
• 12:45
  all communicating as quickly as possible with the lowest signles noise, and yeah,
• 12:52
  and there do you think you need to enable users to put like skin in
• 12:58
  the game behind their messages in a more frictionless way, as in, if
• 13:01
  I'm like within capital markets, I can bet I can put capital to work,
• 13:07
  right, and I stand to lose it if I'm wrong. Uh,
• 13:09
  And the information space and X is it's kind of like a survival of the
• 13:13
  fittest, but kind of like the marginal energy needed to put in for an
• 13:16
  individual tweet, I can't really change that or an individual post? Is that
• 13:22
  like a direction to go. You mean, like when you put something assign
• 13:33
  sort of a some amount of your credits effectively you're yeah, I mean within
• 13:39
  prediction. Prediction markets work because people are able to bet on one thing versus
• 13:43
  another. Like conceptually, if I'm right about something, if the truth,
• 13:46
  if I if I get some kind of like you know, more than just
• 13:50
  reputational cruel, but capital cruel for being correct about something on X. Is
• 13:54
  that a way to kind of increase essentially effective signal to noise within the network.
• 14:09
  Do you have a suggestion for how that might be implemented? I mean,
• 14:13
  conceptually, you're the fact that I can advertise on X, like I
• 14:16
  can promote a tweet, you know, is in some ways in instant atiation
• 14:22
  of that. But there's no mechanism by which I effectively lose for being wrong,
• 14:26
  or maybe within the distribution algorithm there is, but it just seems very
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  kind of like a loose kind of connection between whether or not I'm contributing positively
• 14:37
  to the network and whether or not the network actually rewards me in some way,
• 14:39
  either financially or otherwise for contributing positively. Well, I mean, we
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  are paying creators for you know, for people who are posting on the system
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  where that post is interesting and gets a lot of views. So that's that's
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  one way in which people are occurring value. If you if you post something
• 15:05
  that's boring around uninteresting then just or wrong whatever you peraps will get less views
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  and thus earn less. You know, there's a there is this like very
• 15:20
  challenging problem of of bots and trolls, which is I think, I mean
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  just tackling that and I think we've made great strides, but just a long
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  way to go. That is the biggest source of noise is because the fundamental
• 15:41
  problem you have right now is that it's it's quite easy to pass the are
• 15:48
  you a human test? You know, even if I mean basically open source
• 15:54
  AI at this point can pass are you a human test? Spatter but I
• 15:58
  think out than most humans m hmm, so uh, and that's only going
• 16:06
  to become more widely available. So you know you have to I think biased
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  that the network too, ah have basically raised the cost of manipulation and raise
• 16:18
  the cost of bots and trolls. You cannot completely get rid of them,
• 16:23
  this is not possible, but you can make it much harder and much more
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  expensive, Like I mean having say a drug enforcement agency like the or any
• 16:36
  kind of if making drugs legal does it doesn't make the drugs disappear, It
• 16:41
  just makes them more expensive. So you know, sometimes there's a false dipot
• 16:47
  of me of like, well, it's all or nothing. No, you
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  just you have to do things that that dramatically increase the cost of noise in
• 16:55
  the system so that somebody can't spoil up one hundred thousand or a million bots
• 17:02
  in a day and and then minigulate the system. So this is why the
• 17:08
  you know, we've moved to sort of a subscription, there's at least a
• 17:15
  small monthly payment, even even a small amount, like if like three dollars
• 17:21
  a month is or so some some small amount, it's still several orders of
• 17:26
  magnitude. If it raises the cost of bots by several orders of magnitude,
• 17:30
  maybe by one thousand or ten thousand, so uh, and then it's not
• 17:38
  just the cost, it's not just the dollar amount. But then you effectively
• 17:41
  piggyback on the payment system, so payment authentication. So it's just it's just
• 17:47
  hard to find more credit cards to misuse that like there's a natural cost in
• 17:56
  the black market for credit cards that work. So so just just biasing things
• 18:02
  to where the subscribers, effectively for premium users content is elevated above that of
• 18:12
  bought amplified content is I think a very big deal. Sorry, And my
• 18:19
  prediction actually is that any given social network that does not move in this direction
• 18:29
  will be swarmed with bots and and will simply be overwhelmed. You know,
• 18:33
  I have an experience with that. We all of a sudden, I guess
• 18:40
  bots were taking over. And this was not on Twitter but on or on
• 18:45
  X but on Instagram and Facebook. I mean, it was just all over
• 18:49
  the place. So we've already experienced attacks like that. Can we stay on
• 18:56
  the X platform as a topic, elon, but maybe take us a little
• 19:04
  bit more into the future about this super app opportunity. Will you become a
• 19:10
  financial platform? Identification is and we're already seeing you're still tipping I think on
• 19:22
  X. But are you going to are you going to turn into a financial
• 19:26
  platform, which is where you started your entrepreneurial journey many years ago? Is
• 19:33
  this still is this still on the drawing board? Yeah? Absolutely, We're
• 19:40
  just waiting for the final approvals to come through for the money transmitter licenses.
• 19:45
  Has just taken longer than expected to get the money transmitter licenses. Yes,
• 19:48
  so I did see you have fifteen or so now or is it more?
• 19:55
  I think we actually have a majority of the states. Oh, I've been
• 19:59
  for this, but it's it's irrelevant until California and New Yorker brewers. I
• 20:03
  see, I see, And are there any showstoppers or it's just bureaucracy.
• 20:11
  It's just I mean, really just I guess bureaucracy. You know the thing.
• 20:18
  Things were obviously quite chaotic, especially for the first few months, so
• 20:21
  you know, it's not entirely the fault. We were bit late in submitting
• 20:26
  our you know, money transmitter licenses, and I essentially thought I thought we
• 20:33
  had done it, but we had not done it until around the middle of
• 20:37
  this year. So I think we'll probably get our approvals early next year,
• 20:45
  and so I would expect payments to roll out. I would be surprised if
• 20:48
  we aren't if it takes us longer than the middle of next year to roll
• 20:51
  out payments. So I'm not aware of any any showstoppers. Is just kind
• 20:56
  of working through the system. Yeah, that'll be exciting, if you don't
• 21:00
  mind, Elan, I'd like to actually make an announcement on X since you
• 21:10
  know, we learned in the market that once once you say something on exit,
• 21:17
  it actually becomes public information from the SEC's point of view. We've seen
• 21:22
  that tested comes and so I just wanted to announce that we're pretty excited that
• 21:30
  for the first time, beginning in January, our venture fund will be available
• 21:36
  on so far right now, if you want to buy our venture fund,
• 21:41
  the Titan app is the way to go. That's an Andresen Horoitz funded company
• 21:45
  and they've been great, but we are expanding and you know, we'd love
• 21:51
  again in this movement towards democratization of VC if any other platforms want to participate
• 21:59
  in this movement. You know, we're not exclusive, so and we're very
• 22:04
  excited about the possibilities. So thank you for letting me do that. And
• 22:11
  it's also a big part of bringing the broader base of a huge number of
• 22:17
  non accredited investors whould love to enter companies like your Zealand of course, and
• 22:21
  we are already with the Ark Venture Fund in SpaceX and X, and we'd
• 22:25
  love to do others and really allowing you know, obviously your companies are extremely
• 22:30
  well funded, but for many companies that don't have access to capital necessarily at
• 22:33
  the scale you've built without going public. So we think that's a really exciting
• 22:37
  potential for companies to stay private for longer. And really that sounds great.
• 22:41
  Yeah, it's really really cool. I mean, the burden of being a
• 22:47
  poly company really has increased over time such that it has it's somewhat persuaded a
• 22:52
  lot of companies from being public, and I really frankly would recommend companies don't
• 23:00
  go public unless they absolutely have to. So, yeah, do you think
• 23:07
  do you think that going back to like the Model three ramp, when you
• 23:11
  had customers and shareholders going out and facilitating delivery of vehicles, do you think
• 23:15
  that could have happened without people having like skin in the game in the same
• 23:21
  way. Yeah. Absolutely, Most most of the people who help we're not
• 23:26
  shoulders. That's interesting. I mean that I don't know, you know,
• 23:36
  Elon, so many people have come up to me and all of us over
• 23:41
  the years because we were out there, you know, pounding the table,
• 23:45
  uh for Tesla against you know, against the traditional financial world, and they
• 23:52
  they read our research on Tesla and and bought into it. And so many
• 24:00
  people have come up and said thank you for doing that research, alerting us
• 24:06
  to the opportunities. What's happened to the public markets, Elon is I think
• 24:14
  is I think they're kind of broken. I agree with you. I think
• 24:18
  part of it is regulatory, but part of it is the way the traditional
• 24:22
  financial world works. And I saw, I've seen this time and again,
• 24:27
  is if a company is not in a broad based benchmark, then then financial
• 24:34
  analysts and portfolio managers very often say, okay, not relevant, not relevant
• 24:41
  to me. Not in an index. I'm not competing against it. That's
• 24:45
  how broken it is. Instead of focusing on the future, and you know
• 24:49
  which companies are going to be transformative and are going to scale brilliantly, they're
• 24:55
  very nicely situated in the past, you know, in stocks that are where
• 25:00
  they are in benchmarks because of past performance. That's the other thing that's happened
• 25:04
  here. Sure, but it's important we changed that. Elon and Tesla,
• 25:11
  it has been a change maker in that regard. Sure, you didn't get
• 25:15
  into an index because of the way they construct them until Tesla was five hundred
• 25:21
  billion dollars, So a lot of it was pretty crazy. You know,
• 25:25
  how many more, how many companies are bigger than that. You know,
• 25:27
  it's just crazy, but you did, you made it, and you opened
• 25:32
  people's eyes. And we're trying to change this shift away from passive back to
• 25:40
  active so that there is an efficient allocation of capital. Yeah, you're touching
• 25:45
  on a very important point, which is that I think the percentage of the
• 25:49
  market that is passive is simply is too great at this point. So at
• 25:55
  the end of the day, somebody actually has to make an active decision that
• 25:57
  the passive investors are riding on the decisions of the active investors. And so
• 26:04
  the passive passive you know, investments like index funds whatnot, are they're like
• 26:10
  a an They're just that they're an amplifier. It's like that, you know,
• 26:14
  like an electric guitar app or something. So, but but you don't
• 26:18
  want that amplifier gain to be too high or you get essentially massive movements of
• 26:23
  the stock based on the decisions of maybe four or five active major stock pickers.
• 26:33
  Well, you know, actually it's it's it's a little more complicated.
• 26:37
  So if you if you well, yeah, if you if you look,
• 26:41
  if you were in a risk off market, a bear market like we were
• 26:45
  in twenty two, what actually happens is these managers are very fearful and they
• 26:52
  just get closer and closer to their benchmarks, and they sell the stocks that
• 26:59
  the kind of stocks that we're invested in because we're completely active, we don't
• 27:03
  we're benchmark agnostic. We just we just don't even look at them. We're
• 27:07
  all about the future. So that's in a risk of market, it punishes
• 27:12
  stocks that are not in indexes more than otherwise would be the case. And
• 27:17
  then to your point, it rewards stocks that you know, in a risk
• 27:23
  one period that that that are growing very quickly like yours. And as you
• 27:29
  say, yes, there's a pylon effect. If they get into a benchmark,
• 27:33
  now everybody has to consider them. So it's really it's it's a really
• 27:37
  distorted way of that. The public equity markets have evolved. Yeah, I
• 27:45
  mean essentially getting into any kind of index will pass up fund well I think
• 27:49
  increase the volatility significantly because you know, just now it's amplified that stock's not
• 27:56
  amplified by by the passive. So you know, and I think Bogo was
• 28:03
  was it was a good idea to create, you know, bank guard and
• 28:08
  passives, but it's gone. It's just gone too far it has, so
• 28:14
  you just don't want to have the amplify sort of the the amp is turned
• 28:18
  up too high, there's a way to think of it. So there should
• 28:22
  be more more active and less less passive. Totally agree and absolutely And the
• 28:30
  other thing that's happening, I didn't know where we're going to go here,
• 28:32
  elon. But the other thing that really is gripping the markets is you know,
• 28:37
  seventy five percent plus UH of training every day is algorithmic, and we
• 28:45
  see they're very simple algorithms. You know, in a bear market, okay,
• 28:49
  do they have cash? Are they burning cash? And and those two
• 28:55
  variables will will dominate the stock action. So yeah, we've watched this over
• 29:00
  the last three years. It's a very simplistic way of managing money, and
• 29:08
  I really do think it has led to the most massive miss allocation of capital
• 29:14
  in history. A lot more private companies should be public, but we understand
• 29:18
  why they don't go public because of the kind of behavior you're subjected to.
• 29:22
  And now you know all about it, right, yeah, I mean the
• 29:26
  regulatory burden of being public is way too high, and then the legal burden
• 29:33
  of being public is also way too high. So if you're public, you're
• 29:37
  just going to be sued NonStop by these class action law firms with their fake
• 29:41
  plaintiffs, as is the case with Tesla. We're just you know, constantly
• 29:45
  being sued by you know, I said what the media will portray as a
• 29:52
  member of the class, but in fact we're just being sued by class action
• 29:55
  law firms with with puppets like that drives me crazy. It happens, you
• 29:57
  know, it's happening. But the problem that we're talking about here is non
• 30:06
  accredited investors have not been invited to the venture capital party because they don't make
• 30:14
  enough money or they are they're not wealthy enough, which we think is quite
• 30:18
  a regressive tax. Yes, absolutely, I fully agree. That's why we're
• 30:23
  democratizing venture capital by not taking a carry ourselves so that we can offer our
• 30:32
  fund for as little as five hundred dollars to anyone anyone. That sounds great,
• 30:38
  Well, I think more people should take you up on that. Yeah,
• 30:42
  there is. I mean, most most of the the vast majority of
• 30:49
  companies are obviously private, they're not public. Yes, And and you're right
• 30:56
  that that it is somewhat of a regressive tax that makes it difficult for the
• 31:00
  average citizen to participate in the outside of those companies, because once you go
• 31:06
  i think above twenty five hundred shareholders, non employee shareholders, then you're forced
• 31:11
  to go public. So the reason that SpaceX cannot simply offer stock to anyone
• 31:15
  who wants to own it is because of that twenty five hundred direct shareholder limit.
• 31:22
  Right, So do you think do you think that within SpaceX are just
• 31:26
  thinking about Tesla versus SpaceX? Do you think you've been enabled to take more
• 31:30
  appropriate risks within SpaceX than you have within Tesla because of the public versus private
• 31:38
  Absolutely. I mean at SpaceX, we never think about what the quarter.
• 31:45
  We never think about it, and we don't think, we don't think about
• 31:48
  the stock price. So you know, there's there's a lot of pressure,
• 31:53
  like an immense pressure on a public company to not have a bad quarter.
• 31:57
  So this can act actually result in a less efficient operation where you're going to
• 32:04
  great lengths at the end of a quarter to not disappoint people. And you
• 32:10
  know that's just that's just how it goes. So uh and and then you
• 32:17
  know you've also got a lot sort of a long term challenge with public markets
• 32:22
  where a lot of the analysts following companies have a time horizon that is maybe
• 32:25
  only a year or two. It's you know, rarely more than a few
• 32:30
  years. So and so they literally don't care because then their incentive structure is
• 32:37
  a short term. They do not care about what your long term outcome will
• 32:42
  be because their careers dependent on how you do in the short term. Elon,
• 32:45
  you have been great at I think standing up to short term oriented shareholders.
• 32:52
  That's one of the scores in our scoring system as we're evaluating companies.
• 32:58
  Is this a visionary management and will they stand up to short term shareholders who
• 33:04
  want their profits now, their dividends, their share repurchases, Will they invest
• 33:08
  aggressively enough in the future. And I think you've done a great job.
• 33:15
  Well, thank you and credit to the test the team as well. So
• 33:19
  but that that said, we at Tesla, we do go to great lengths
• 33:23
  to ensure that our quarter is good as that that we don't disappoint because it's
• 33:30
  not so much about the it's just that we feel like we have a sort
• 33:34
  of you know, moral obligation too. You know, I don't know that
• 33:38
  to not have a bad quarter and disappoint people. So we you know,
• 33:44
  the number of New Year's Eves that I've spent in delivery centers is like,
• 33:49
  I don't know of six. I don't know seven. I don't know I
• 33:53
  blast camp how many times I was in I was delivering forest until like basically,
• 33:58
  but not on Year's Eve personally. So, you know, has it
• 34:07
  done any Let me just ask the question the other way, SpaceX. You
• 34:10
  you feel like you have more degrees of freedom being public. Has it done
• 34:16
  anything positive for you? For Tesla? I mean, well, it did
• 34:28
  allow us to clean up our capital structure, which was overly complex as a
• 34:30
  private company and have a single class of common so were really getting things were
• 34:37
  getting quite unwieldy with the private company capital structure. There was obviously the capital
• 34:43
  availability in the public markets, which is a lot more than the private markets.
• 34:49
  And a car company is capital intensive, so I guess access to Ladge
• 34:53
  has capital and cleaning up what had become an extremely complex your private company share
• 35:01
  structure were two, you know, major things. Certainly, it was also
• 35:09
  good to give access to the company stock to a small shareholders, you know,
• 35:19
  so those are those are good things, but you know, I think
• 35:21
  it's also been a tremendous distraction as well on the downside. So and you
• 35:30
  know, there's just a lot of a lot of overhead just there's more time
• 35:32
  that's required to manage a public company than a private company. So in the
• 35:37
  past you've talked about potentially I guess listing Starlank or doing something on the space
• 35:44
  X within the public capital markets. But do you think that that's actually not
• 35:46
  something that you need to do or anticipate doing across all of your companies outside
• 35:51
  of Tesla. At this point, I don't think it's worth going public and
• 36:00
  ntil you have maybe an extremely stable and predictable revenue stream. So if your
• 36:07
  cash flows are extremely stable and predictable at that point, going public is less
• 36:15
  of an issue because you know, you're just not going to have these big
• 36:19
  gyrations. So you know, isn't that ironic? Like the point of the
• 36:25
  equity markets is to is to provide like perpetual capital for capital intensive businesses,
• 36:31
  right, And what you're describing as a business that actually doesn't really need equity
• 36:36
  capital necessarily, you could you could debt fund it to some degree if you
• 36:38
  have very stable cash flows, right, I mean I can equity or debt
• 36:46
  fund just about anything. At this point, you know, the You know,
• 36:51
  it's worth noting that in all my old companies, across all the years,
• 36:57
  I've never lost money for an investor even once, and this is now
• 37:01
  over one hundred financing rounds. Now, of course I cannot stop people from
• 37:05
  selling when they should not sell, but I have never driven them to a
• 37:08
  bad outcome. So that's a pretty good betting average. And obviously, when
• 37:19
  you've treated capital well, then capital if it treats you well in turn,
• 37:27
  and so you know, it's it's basically very easy for me to raise almost
• 37:34
  any amount of capital. Frankly, So now, of course I need to
• 37:38
  make sure that traffic stays intact and not get complacent or entitled. But you
• 37:45
  know, obviously I do not have a need to to raise capital, and
• 37:52
  in fact a lot of in most cases I don't really need even for say
• 37:57
  like Boring Company or Neural Link. I mean, I can funded myself entirely.
• 38:02
  But I think it is good to have other investors. Why why why
• 38:07
  even bother with with outside shareholders at all? It would be simpler to you
• 38:12
  could take whatever risk you want without having to answer to anybody. Well,
• 38:17
  I do take a lot of risks your way. I don't know, I
• 38:22
  think it's I think it's good to have I don't know, I think it's
• 38:29
  good. It's good to have other investors. I mean, I think that
• 38:35
  you know, each investor you ad is an ally it's good to have more
• 38:40
  allies. I think it also, you know, establishes that I'm not delusional
• 38:51
  in the valuation of the companies. So if if others are prepared to invest
• 38:55
  at a particular value, then then then you know, I'm not the sole
• 39:04
  just decider of what the value of the company is. Others are deciding what
• 39:08
  the value of the companies are. You know, it's it's sort of an
• 39:10
  outside assessment of the value of the company. And and that you know,
• 39:15
  there is also a need to uh, you know, provide liquidity so uh
• 39:29
  to to to people at the company. So I believe in providing stock to
• 39:37
  the people of the company, the employees and creators of the company. It's
• 39:43
  important to provide them stock to have the incentive be aligned with the company outcome
• 39:47
  and uh and then you know, you the various points want to gain liquidity
• 39:52
  so that you you want to then establish an outside valuation. And you know,
• 40:00
  so there's not it's not just me deciding it and enable liquidity for those
• 40:05
  who've been awarded stock and options at the companies, and and and generally been
• 40:09
  my approach to award everyone at the company stuff. You know, A tells
• 40:15
  that we've awarded. We awarded everyone stock you no matter how junior they were.
• 40:24
  So that actually obviously made a lot of people millionaires. I think I
• 40:30
  think Teslam may have created more employee millionaires than any company in history. Yeah,
• 40:37
  so I would say, like, if there's not a company that's done
• 40:40
  has created more employee millionaires than Tela. You know, there's it's maybe there's
• 40:45
  one, maybe it's there's one or two others. But but really the SURE
• 40:51
  tests around one hundred and forty thousand people, and you know, I think
• 40:57
  I think we might be number one. I think I think you are.
• 41:00
  So I'm conscious of time here and thank you so much. Elon. We
• 41:06
  Frank Downing, our director of research on Next Generation Internet, asked Grok,
• 41:12
  what questions do people want? Kathy Wood to ask Elon Musk to Okay,
• 41:15
  basis, and we would be remiss if we didn't, if we didn't summarize
• 41:22
  this first and then let you take it where you'd like it. And it
• 41:25
  basically said, it seems that this is Grock talking. Seems that people are
• 41:30
  even here about the latest developments and AI's I mean, in Tesla's AI technologies
• 41:35
  we definitely are, such as FSD twelve and the next generation platform for Robotaxi.
• 41:40
  They're also interested in learning more about the company's plans for the Optimist project.
• 41:45
  Additionally, there is a lot of curiosity surrounding Elon Musk's thought on the
• 41:51
  AI space, as well as his take on the future of bitcoin. I
• 41:54
  guess that was a little repetitive AI there, but these topics are sure to
• 42:00
  spark some engaging discussions. That's that's Grock for you. Okay, well Crok,
• 42:06
  that's pretty good. Yeah, that's pretty good. So AI and and
• 42:16
  I do. I do have more time than you know, if you would
• 42:21
  like to go alonger longer than fifteen minutes, we can go alonger than fifteen
• 42:23
  minutes, right, I mean trying to still my thoughts here on AI,
• 42:30
  because I could really talk four hours on AI. You know, we both
• 42:34
  Charlie and Brett are steeped in it, so is Frank and of course Tasha,
• 42:42
  she's done our work on autonomous but one of the one of the things
• 42:46
  we've been very curious about is open source versus closed AI? And I don't
• 42:53
  know if you've seen I don't know if you've seen the chart that Frank and
• 43:00
  Joseph did on our team, but they they drew a line. They basically
• 43:07
  calculated performance improvements in both the closed closed or private AI companies and models large
• 43:17
  language models, and then the open ones. And open is behind closed,
• 43:22
  but the steep the performance is improving at a steeper rate than closed. Do
• 43:30
  you have any thoughts about that and about open versus closed generally when it comes
• 43:36
  to AI. Sure, well, I mean, I think a lot of
• 43:42
  people know that. You know, I was instrumental in the creation of Opening
• 43:45
  I and the impact. I came up with the name of the Opening open
• 43:50
  I means open source, yes, and thought it as an open source nonprofit
• 43:55
  And the reason I wanted to create it was to create establish a counterweight to
• 44:00
  Google deep Mind, because it was a unipolar world at that point. It
• 44:02
  was, you know, Google deep Mind had probably two thirsd of more of
• 44:07
  the top AI talent and of course fast computing and financial resources. And at
• 44:16
  the time I was close friends with Larry Page and it did not seem to
• 44:20
  me that he was taking AI safety seriously. So I felt there needed to
• 44:24
  be some, like I said, some counterweights, some competitor to sort of
• 44:31
  the Google Deep Mind situation. So prankically instrumental in Crain, the company was
• 44:39
  recruiting Iliosiskaer, which was a back and forth thing where actually Eli have changed
• 44:47
  his mind a few times and ultimately decided to come to Opening Eye. And
• 44:52
  uh so I won that recruiting battle, and that is actually what caused Larry
• 44:59
  Page to stop being friends with me. Frankly so, but now ironically,
• 45:07
  because fate loves irony, Opening Eye is a super closed source and and for
• 45:15
  maximum profit it's it should be renamed closed for maximum profit AI, it won't
• 45:21
  be more accurate. So because that's that's you know, it's literally the polar
• 45:24
  opposite of what of how it started. I guess I'm I generally have a
• 45:30
  bias in favor of open source, and you can see that certainly with the
• 45:37
  X platform, where we've open sourced the algorithm U and for for example,
• 45:42
  for community notes, we open source not just the algorithm, but all the
• 45:46
  data as well, so you can see exactly how a note was created,
• 45:50
  can be ordered by third parties. There's no there's no mystery, nothing hidden
• 45:53
  at all, I think. So that's one of that seems to be one
• 45:59
  of the confusing things about open source as pertains to large language models. It's
• 46:02
  it's it's not as simple, and I think this has been lost in some
• 46:06
  of the debate as just open sourcing the code. It's open sources the shades
• 46:08
  of gray here of course, with parameter, weights, data, there's there's
• 46:14
  all of that spectrum, and I think that's been maybe lost from some of
• 46:15
  the debate. So it's great to hear, Yeah, there's there's actually a
• 46:20
  very little code, very little actual traditional lines of software. Certainly at the
• 46:25
  at the first level, there's there's very little. It's a remarkably tiny number
• 46:30
  of lines of code. So it's it's just these giant, you know,
• 46:36
  waste files and you know what your hyperparameter you know, numbers are and it's
• 46:43
  basically a giant Comma separated value file. So I was find amusing to contemplate
• 46:50
  that perhaps our digital guard will be a CSP file, you know, like
• 46:57
  and and then you make a you see fee file that has maybe more weights
• 47:02
  and the weights are better, and then you're pretty much delete the old one.
• 47:08
  So just the AI is evolving and deleting its prior self constantly, So
• 47:19
  we're going to worship a giant tel file essentially. That's pretty kind of I
• 47:22
  mean, you need a very big Yeah, it's a lot of cells,
• 47:27
  but it's really just a bunch of numbers. And then those numbers are they're
• 47:31
  getting smaller in magnitude too, you know, going from f P sixteen to
• 47:37
  fp F thirty two to P sixteen to in sixteen to into eight and now
• 47:44
  it looks like things are training towards mostly into four, so they're not particularly
• 47:52
  large numbers. Yeah. Yeah, I'm not sure if I'm answering, I'm
• 48:00
  gonna asking a question, but I mean, I think it's true that closed
• 48:06
  source is not that far, like from a time standpoint, not that far
• 48:10
  ahead of of a of a source. But let's say, and if you
• 48:21
  assume open sources, do you have six months because of the immense rate of
• 48:30
  improvement of AI, that's six months is a is actually a massive amount of
• 48:37
  time, I mean, or at least the delta in an exponentially improving situation,
• 48:45
  six months, Well, I think feel like an eternity. So I
• 48:52
  think closed will outperform open by a meaningful amount at any given point in time.
• 49:01
  And given the Yeah, I'm just gonna say, given the questions we
• 49:06
  were talking about before about truth and not truth, and do you think in
• 49:07
  ten years' time a I will have been a net truth improver or detractor from
• 49:15
  where we are today, I think it will be, well speaking for at
• 49:21
  least for Groark, I think it will be a significant truth improver. That
• 49:27
  that is the three. Our goal is to be maximum truth seeking, maximally
• 49:30
  curious, minimizing the the error between between perceived reality and describe reality and actual
• 49:39
  reality, and always acknowledging the error, not being too confident about it.
• 49:49
  So I and I think there will be a competition for truth, and you
• 49:53
  will go. People will tend towards the one that they think is most accurate.
• 50:00
  So and if there's at least one AI that is aiming for maximum accuracy,
• 50:05
  I think it pushes all of the AI is to aim for maximum accuracy,
• 50:09
  just as with with the X platform FK twitters. As you know,
• 50:19
  X pushes for maximum truth and accuracy. It's not forces the hand of others.
• 50:23
  They the others now also have to do that. Right, The truth
• 50:29
  the truth arms race among the cs fees and is Yeah, is one of
• 50:32
  the one of our thesis I think with our is that Teesla is one of
• 50:36
  the most undervalued AI companies there is because of the insane amount of data you've
• 50:40
  got on all or you know, to feed into autonomous I don't know if
• 50:45
  there's any commentary on that because I think, you know, obviously, with
• 50:47
  the rise of these l M companies which are by and large working off essentially
• 50:52
  available data that is not proprietary, the benefits coming to the companies like Teesla
• 50:57
  that understand how to use the benefits but do have these enormous propriety data pools,
• 51:01
  seems like that's going to be the next frontier. Yeah, I think
• 51:10
  that's accurate, an accurate description. It is one of the leading A companies
• 51:16
  in the world, and with respect to real world AI, it is obviously,
• 51:20
  by fear and away the leader. So you know, the what large
• 51:27
  language model with phrase long large language model l M is massively overused. But
• 51:34
  what what I do see happening is somewhat of a convergence towards intelligence. You
• 51:44
  know, it's just like, really to make full self driving work, you
• 51:52
  kind of need baby a g I in the car because you need to understand
• 51:59
  reality and is messy and complicated, and just as as a side effect,
• 52:04
  the car AI has to be able to read, for example, has to
• 52:08
  be able to read read read aubitrary science as a little just a little side
• 52:12
  effect of understanding reality in every language. So you know, I think that
• 52:22
  everything is coming down to, you know, different layers of transformers and diffusion,
• 52:29
  and then how you put together the transformers and in diffusion. That's that's
• 52:36
  what That's what I made. That that's somewhat niche AI joke on the X
• 52:39
  platform. Who do you think will be present in twenty thirty two? Transformers
• 52:44
  or diffusion? Do you think that? Do you think that switching to full
• 52:47
  stack AI for for Tesla's full self driving reduces the kind of forecast error for
• 52:58
  you in terms of when the problem will be solved as in you famously have
• 53:02
  you know, said it's a your way for a few years now. Do
• 53:07
  you think that like actually line of sight wherever it ends up, you'll have
• 53:10
  a better line of sight on when you're going to cross a particular threshold of
• 53:15
  performance where it can go without human intervention. Yeah, I mean the cars
• 53:22
  are really incredibly good at driving itself. So now, especially if you say,
• 53:29
  like okay, drive in California, which is you know, both generally
• 53:37
  easy driving because you don't have heavy rain and snow and that kind of thing
• 53:42
  in most parts of California, and tails the engineering is primarily in California,
• 53:49
  so you're gonna get it's gonna overfit for solving California. But if you're just
• 53:52
  driving to stay around Palo Alto, the probability that you'll need an intervention at
• 53:57
  this point is incredibly low. In fact, even if you're driving through San
• 54:01
  Francisco, the probably intervention at this point is very low. So we're really
• 54:06
  just going through a march of nines, Like how many nines of reliability do
• 54:13
  you need before somebody does not need to monitor the system? You know,
• 54:17
  it's so interesting GM basically shutting down Cruise. Tasha has done the work on
• 54:27
  safety and it seems that Tesla with FSDV has an accidents once every three point
• 54:35
  two million miles. At Tesla without FSD six hundred thousand miles. The average
• 54:42
  vehicle on the road I think this is surface streets one hundred and ninety thousand,
• 54:46
  and Cruz was forty thousand, so there really was a safety issue there.
• 54:51
  Do you worry that it has potentially set back regulators, you know,
• 54:58
  from consider ring autonomous transportation or is this data, given that accidents on the
• 55:09
  streets have gone up in the last ten years fairly dramatically actually because it texted,
• 55:15
  do you think do you think that regulators are going to look at the
• 55:21
  data which, I mean, we've done the research, Tasha's do other research
• 55:24
  on this and is pretty compelling. Well, you know, our regulator in
• 55:35
  the US is the End Enforcement Division of NITSA, for whom I actually have
• 55:39
  a lot of respect. I think those guys are they really have I mean,
• 55:46
  they're they're quite I think actually, in my experience thus far, have
• 55:50
  been quite sensible. You know that that that doesn't mean that they're on't silly
• 55:55
  things that happen from time to time, but they've really been quite sensible because
• 56:00
  they see the actual truth of the accidents, and they see the fact that
• 56:05
  they're on the order of forty thousand people killed every year in motivical accidents,
• 56:10
  and so they actually do they do care about the safety statistics, and they
• 56:20
  do recognize that there's always going to be some risk with cars. Uh,
• 56:28
  they're well aware of the fact that that our cars are much safer than other
• 56:31
  vehicles. So you know, we really I mean, there's been a few
• 56:37
  things where, you know, maybe we have had some disagreements, but you
• 56:42
  know, like like for example, coming to an absolute full stop at stop
• 56:45
  streets even when the you know, it's very clear there are no cars anywhere
• 56:51
  in sight that could possibly cause an impact. No, no, no cars,
• 56:55
  no pedestrians, completely clear and actually almost no humans stop at stop streets
• 57:04
  a stop signs. Almost no humans actually come to a full stop that typically
• 57:07
  let me think they came to full stop, but typically they'll be going at
• 57:09
  least a few miles an hour, so that you know, they said,
• 57:14
  well, the Lord does say that you have to stop at a stop street.
• 57:15
  Well even though no, almost no humans do. So that actually created
• 57:21
  a bit of a challenge for us because we had to select the rare cases
• 57:27
  were from the fleet where humans actually stopped at stop streets at stop scigns,
• 57:34
  so and then actually get our QA team to stop at stop streets and then
• 57:40
  overfit the stopping stopping at stop signs in order to get the car to stop
• 57:45
  at stop science. Because it was quite a bit behave like a sort of
• 57:51
  a good, normal human driver who does not stop at stuff signs. So,
• 57:54
  you know, we had a disagreement there on it, but we ultimately,
• 58:00
  you know, have made the car stop at stop signs, even though
• 58:04
  it's a lit annoying. So but you know, overwhelmingly, you know,
• 58:10
  that's one of the things in the media will try to create this that that
• 58:13
  I'm some sort of lawbreaking maverick who just does what he wants and doesn't care
• 58:17
  about legal matters. This is actually not true. Of the literally millions of
• 58:24
  laws that I am subject to in my company's the subject to there are a
• 58:28
  handful over the years that we've disagreed with almost but the vast majority ninety nine
• 58:32
  point I don't know, nine percent of laws and regulations we do a buy
• 58:38
  bine and we do agree with, well, maybe maybe we don't agree with.
• 58:42
  We certainly a buy bye. You know, there's once in a while
• 58:46
  the gout disagreement, but it's it's really minor. And but if you sum
• 58:52
  up the disagreements across over the you know, twenty years, it can just
• 58:58
  sound like a lot. But but in fact, my companies are incredibly low
• 59:01
  abiding. So that's the that's the that's truth of it. Anyway, I
• 59:08
  think I think it'll be I think it'll be fine from a regulatory standpoint.
• 59:13
  When we can show that there's even completely without supervision, there is a massive
• 59:21
  statistical case for self driving being actually safer than if someone had their hands on
• 59:28
  the wheel, or was even potentially having their hands in wheel, then I
• 59:31
  think the regulators will accept that. You know, it's been really interesting as
• 59:38
  a we were watching the breakthroughs as everybody has in AI, and we had
• 59:45
  agreed with you. Our original our original research had autonomous mobility in pretty much
• 59:53
  full force. This was our original research by now. But if we didn't
• 59:59
  have the breaks truths in a I that that we've seen, particularly transformer architecture,
• 1:00:07
  it wouldn't have been possible, right, But we didn't know that.
• 1:00:09
  Is that how you're viewing it now? Well, it's certainly true that transformers
• 1:00:17
  are transformational. Yes, so, uh, you know, pretty much everyone's
• 1:00:27
  using transformers, and it's really just how many transformers. What kind of transformers
• 1:00:34
  are you using? Order aggressive transformers which are very memory bound with intensive you
• 1:00:40
  know, there's but you I think you really I'm not sure you can really
• 1:00:45
  do AI without transformers in a meaningful way. Diffusion is also very important.
• 1:00:52
  So I mean it just really looks like a GI is some combination of transformers
• 1:00:59
  and diffusion. That's interesting. Does diffusion help elon and the things that transformers
• 1:01:07
  are necessarily not necessarily that good at yet, like planning and remembering rather than
• 1:01:10
  sort of a current state. Uh, My, transformers are important for all
• 1:01:19
  aspects of AI. Yeah, I mean, computers are very good at remembering
• 1:01:25
  things. Your phone remembers the video that you took down to the last pixel,
• 1:01:32
  whereas you know, most humans cannot remember who they met last week.
• 1:01:37
  So memory is the easiest. I mean, we were already outsourced memory to
• 1:01:45
  computers in that Like you say, how much of human knowledge is in digital
• 1:01:53
  form versus in I contained in human neurons. It's overwhelmingly in silicon rather than
• 1:02:06
  biological neurons, right, So I mean, and there's there's I mean,
• 1:02:14
  I think it's always you know, it's good to think of. Like I
• 1:02:20
  tried to consider one of the most fundamental ratios. This is like in physics,
• 1:02:24
  you always thinking about trying to looking at fundamental ratios and some of the
• 1:02:30
  you know, one of the fundamental ratios is the ratio of digital to biological
• 1:02:34
  compute just you know, just just in rural compute and how much, and
• 1:02:43
  the ratio of digital memory to biological memory. So you know, at what
• 1:02:47
  point it's that's like I think at this point, I think we're probably over
• 1:02:52
  ninety nine percent of all memory is digital as opposed to biological. So you've
• 1:02:58
  got over I think over one hundred digital to biological ratio, and memory at
• 1:03:01
  this point trending towards a thousand, you know, and many or is married
• 1:03:07
  to beyond that. Then then you've got the digital biological compute ratio. And
• 1:03:17
  since the number of humans is more or less constant, I'm worried about it.
• 1:03:23
  You know, humans declining quite significantly in the years to come because the
• 1:03:28
  birth rate is so low. But you know, so so human human computer
• 1:03:32
  is more or less it looks like a flat line versus time, whereas the
• 1:03:37
  digital compute is exponential, right, And you know, at some point it's
• 1:03:49
  that that will also be above one hundred, meaning more than ninety nine percent
• 1:03:53
  of all compute will be digital instead of biological. Right, And if we're
• 1:04:00
  not there already, we will be within a year or two. Although it's
• 1:04:04
  amazing how much data biology can store. I reckon, I believe it.
• 1:04:09
  It's estimated that a gram of dry DNA can store between four and five hundred
• 1:04:13
  exabytes. So maybe this bill things to learn from biology. But yes,
• 1:04:18
  incredible the pace of change. Yeah, I mean, if you encode memories
• 1:04:23
  in DNA like a ticker tape, then the DNA memory potential is amounts.
• 1:04:30
  But I'm not sure that's actually what's happening, or if it is, it's
• 1:04:33
  I don't know. I'm not sure why my memory is so terrible. But
• 1:04:41
  actually, I mean your memory in terms of the raw details, like you
• 1:04:44
  have an amazing search function, right, it's kind of like yeah, well
• 1:04:48
  for for any I mean I would argue kind of in some ways like the
• 1:04:55
  transformer architecture enables effective search of a very very broad amount of data, and
• 1:05:03
  or that's or it's like data compression. It seems like the yes, we
• 1:05:10
  have there's many more like data bytes and coded are gigabytes and coded and disk.
• 1:05:15
  But but actually being able to effectively search that space is pretty still primitive
• 1:05:21
  with compute, at least at large scale relative to humans ability to access information.
• 1:05:30
  I mean, it's still some things that humans be better than computers.
• 1:05:33
  I mean, if you say, like computers that have not yet discovered any
• 1:05:39
  fundamental physics, but humans have discovered a lot of fundamental physics. The computers
• 1:05:45
  have not yet invented a useful technology. Humans have invented many useful, useful
• 1:05:53
  technologies. So you know, do you think that do you ascribe to the
• 1:06:01
  notion that, like you, essentially training AI systems on language is not enough
• 1:06:08
  and that you have to have some kind of embodied source of data, like
• 1:06:11
  through an optimist robot to actually get kind of the raw learning in that AI
• 1:06:18
  system would need to understand fundamental physics. Yeah, so that's what I think
• 1:06:30
  is coming. I think I think what's coming is is a understanding fundamental physics
• 1:06:38
  and and AI inventing new technologies. It definitely definitely feels like rather than even
• 1:06:48
  though some things now apparently past the cheering test, most importantly pussing the money
• 1:06:53
  penny test, as in kind of a I actually pay bills, do expense
• 1:06:57
  reports to the extent James bonded those, and actually pay parking clients and things
• 1:07:01
  like that. That would actually be a very good use of AI that I
• 1:07:03
  think would have a lot of users immediately and maybe the the Billy Connolly test
• 1:07:09
  of Cannon a I actually be consistently funny. Those feel like Grok is pretty
• 1:07:15
  funny. That's fair. I think you know, one of our goals for
• 1:07:18
  Grock is to be the funniest AI. So I mean, if you ask
• 1:07:24
  Rock to provide a vulgar roast, it's really good. And speaking of Groc
• 1:07:32
  to not to not let down our future AI overlords. The final question on
• 1:07:36
  the GROC summary that that that Kathy touched on was the future of bitcoin.
• 1:07:40
  Not sure if we want to touch on that or not, whether that's out.
• 1:07:43
  Yeah, that that and and then just before I don't know if we're
• 1:07:48
  wrapping up here, but I'd love to talk about bitcoin and your your view
• 1:07:56
  of crypto assets, and then maybe back into kind of tying things up with
• 1:08:03
  convergences among technologies. You mentioned that a little earlier Elon and the impact ultimately
• 1:08:11
  of all of this on economic growth longer term, you know the surprises that
• 1:08:15
  might come from there. But first, first bitcoin, okay, sure,
• 1:08:24
  what's the question regarding well, you know, there's when we first when you
• 1:08:31
  put it or Tesla put it on its balance sheet, there was I remember
• 1:08:41
  afterwards, there was this backlash in terms of its economic impact, all of
• 1:08:48
  the energy usage and so forth. And then and then as part of the
• 1:08:54
  seminar that we did that you participated in elon, we basically we and block
• 1:09:00
  had come up with this notion that wait, you put uh, bitcoin mining
• 1:09:06
  into a utility ecosystem. Uh, so that you know, if if there's
• 1:09:13
  a storage unit and you know, the the intermittent energy, you know,
• 1:09:17
  the storage unit's full, the sun is still shining, the excess power goes
• 1:09:21
  over to bitcoin, and uh, and you can mint bitcoin and overbuild solar
• 1:09:28
  and wind and renewables and all of that. So so that that that argument
• 1:09:35
  against bitcoin, and Larry Think himself used it quite vociferously for a long time
• 1:09:42
  until until recently that that is going away. What do you think about bitcoin's
• 1:09:51
  potential impact on the financial system, the monetary monetary systeminancial services generally. Well,
• 1:10:03
  I have to say I don't spend a lot of time thinking about cryptocurrency,
• 1:10:08
  hardly, any hardly any at all. I I have thought for a
• 1:10:13
  long time about money and the you know the nature of money, what is
• 1:10:15
  money? And you know it's really a database for resource allocation? Is the
• 1:10:21
  way to think about money in my view, So now field currency is actually
• 1:10:28
  fine as a data based for resource allocation. If you have a predictable money
• 1:10:32
  supply and it doesn't, you know, just get inflator or deflated too much.
• 1:10:41
  Rules based, it's rules based, and then and then, and provided
• 1:10:45
  government does not too much abuse the privilege to create more money. You know,
• 1:10:53
  some amount of abuse is almost is guaranteed to happen. But but you
• 1:10:57
  know you can go too far. So uh, you know, the temptation
• 1:11:04
  over the ages to debase money is I think it goes back to probably the
• 1:11:10
  ancient Sumerians, you know. But if as at the point which money was
• 1:11:14
  invented in any form, including in gold, there was there was the unavoidable
• 1:11:20
  temptation to debase the money supply. So so then you think of any given
• 1:11:29
  money system again I sort of applying information theory to a money problem. Just
• 1:11:35
  think of it like it's a it's an information system. You want to minimize
• 1:11:40
  noise, minimize latency, minimized packet loss, and and so any like like
• 1:11:49
  inflation would be adding noise to the system. If if the if, the
• 1:11:55
  transaction rate, if if the if what it takes to concluded transaction is a
• 1:12:00
  long time that as latency to the system of fraud is kind of like packet
• 1:12:06
  loss. Uh, you know, it's it's you know, so, so
• 1:12:12
  I guess I kind of think of money like like I think of information moving
• 1:12:17
  on a on a network, uh, bandwidth, latency, jutter, which
• 1:12:24
  is the variants in latency, packet loss, those fundamental elements. Yeah,
• 1:12:33
  it's been interesting to watch how human beings in this case that fed you know,
• 1:12:40
  the words they say, whip around markets and there's just something not right
• 1:12:45
  about that. I mean, that's that's my point of view. I think
• 1:12:49
  our point of view certainly on on the crypto team. And you know Art
• 1:12:56
  Laffer, who was my professor in school, he's supply side you know,
• 1:13:00
  Austrian School of economics. You know, when he first he collaborated on our
• 1:13:05
  first bitcoin paper in two thousand and fifteen, and after he got through reading
• 1:13:13
  it, he said, you know, I've been waiting for this since they
• 1:13:18
  closed the gold window in nineteen seventy one. I've been waiting for a rules
• 1:13:25
  a new rules based global monetary system. And I think that's where our optimism
• 1:13:33
  comes from. This is truly rules based and so he's gotten more and more
• 1:13:39
  excited about it the more he's learned about it. So, you know,
• 1:13:45
  anyway back to convergence though, and you're you're the maestro here. You know,
• 1:13:51
  when I think of when we think of, you know, autonomous taxi
• 1:13:57
  platforms, rubotaxi networks and so forth, you know that that's the convergence of
• 1:14:02
  three of the major platforms around which we have centered our research, robotics,
• 1:14:10
  energy storage, and artificial intelligence. Each one of those technologies, you know,
• 1:14:17
  basically gearing up for or in the in the sweet spot of a of
• 1:14:25
  the S curve. And I sort of think it of S curves feeding S
• 1:14:29
  curves and creating the potential for explosive growth that no one is expecting. And
• 1:14:35
  and Brett has just written a paper it should come out in the next few
• 1:14:40
  weeks around this topic. I just want to get your thoughts about that,
• 1:14:46
  and Brett, if you wanted to ask any questions specifically about that, but
• 1:14:50
  that the bottom line from an economics point of view is we could see you
• 1:14:57
  know, very surprising up uptick not just uptick, a step function up in
• 1:15:03
  economic a real economic growth if these technologies are as big as we think they
• 1:15:10
  are. Yeah, absolutely, Well, I mean the real economy is not
• 1:15:15
  money, it's goods and services. So you know, I was saying earlier,
• 1:15:20
  money is really just the database for resource allocation, and you know it's
• 1:15:28
  but if they're no resources to allocate, or if the actual goods and services
• 1:15:31
  output have is fixed, then you really I just try to allocate that that
• 1:15:38
  same pie but more efficiently. But it's really not only as good as as
• 1:15:42
  growing the pie, so growing the the the output of goods and services.
• 1:15:49
  You know, productivity is really the thing that leads to prosperity. And obviously
• 1:15:58
  with with robotics and AI, I think digital medicine through a synthetic RNA,
• 1:16:06
  and you know, I think these things are what will just massively improve productivity.
• 1:16:15
  You know, just if you've got if you take the car as an
• 1:16:20
  example, and I think you understand this quite well, although not many people
• 1:16:26
  do that. You know, if you've got to say a passenger car,
• 1:16:33
  it will typically see ten to twelve hours of usage, like maybe one and
• 1:16:36
  a half hours a day over the course of seven days, but there are
• 1:16:42
  one hundred there are one hundred and sixty eight hours in a week, so
• 1:16:45
  it's really used for a very small percentage of the week normally, and then
• 1:16:48
  you've got to pocket somewhere as well. So you've got parking costs, storage
• 1:16:51
  costs, maintenance costs, and you know all these these these costs associate with
• 1:16:56
  the car, and you know you're at five to ten percent of asset utilization
• 1:17:02
  for a car, whereas if you've got an autonomous vehicle, that same car
• 1:17:10
  that costs basically about the same could now I think, be used as a
• 1:17:15
  rough approximation for about a third of the hours of the week. If you
• 1:17:18
  say like productive hours, and this is I think that's a I think that's
• 1:17:23
  a conservative, but I think it's not far wrong. So if you say,
• 1:17:26
  like it goes from say ten hours a week to fifty hours a week
• 1:17:29
  out of one hundred and sixty eight of useful hours, that that I think
• 1:17:31
  is not it's not going to be exactly right, but I don't think it's
• 1:17:35
  far wrong. You now have the same asset being able to having five times
• 1:17:42
  the utility m hm. So that is that is that is a such a
• 1:17:46
  staggering leap of productivity, you know, And and if TESS is able to
• 1:17:54
  do as as I think we will be able to, which is to upgrade
• 1:17:56
  the fleet to make it autonomous will be the biggest step change in asset value
• 1:18:01
  in history. I think overnight we we agree, we agree I'm converted here,
• 1:18:13
  and that's why I prefaced it by I realize I'm preashing converted. But
• 1:18:16
  you're also you're also underestimating the utility uplift because that ten hours that the car
• 1:18:20
  is driving a week, somebody is not being paid to drive it, mostly
• 1:18:25
  right, but but they're devoting their valuable brain to doing it. As then
• 1:18:29
  kind of it's actually there's the human labor loss that that accompanies that as well,
• 1:18:34
  and so freeing up those hours is actually I think on Tasha's work it's
• 1:18:39
  as meaningful, you know as the capital utilization benefit. Absolutely, And I
• 1:18:46
  think you've also predicted a massive increase in traffic. Uh, you know,
• 1:18:50
  because once you take away the pain of driving, people will will go more
• 1:18:57
  places. So so they'll actually be more caught on the road driving more places.
• 1:19:00
  Because if you can sit in the car and you know, be watching
• 1:19:06
  a movie or be texting legally, then then then what you know that that's
• 1:19:13
  really much less pain than having to navigate Audio's traffic for an hour and a
• 1:19:16
  half Yeah, many people miss that. I remember, I just frustrated me
• 1:19:23
  that GM and its marketing material and presentation just would say zero congestion, because
• 1:19:30
  I think that's larious. Yeah, I would suggest threefold the amount of traffic.
• 1:19:39
  And that's what push pushed us into doing more with drones and you know,
• 1:19:45
  delivery of food and parcels with drones and even air taxis because I cannot
• 1:19:53
  imagine the commute from JFK into Manhattan being you know, four hours or five
• 1:20:00
  five hours or six hours, you know. So, yes, well,
• 1:20:03
  fortunately I have a proposed solution to that, which consists of tunnels. Yes,
• 1:20:10
  yes, and we're now in Saint Petersburg. If you could build a
• 1:20:15
  tunnel from here to Tampa, which is just sand, you're not going to
• 1:20:18
  run into anything, that would be very cool. We can absolutely do that.
• 1:20:26
  Yeah, the Born Company has actually made made it has I think at
• 1:20:30
  this point, by far the most advanced tunneling machine. The thing that is
• 1:20:34
  the biggest inhibitor of Boring Company by far is regulatory approval. It's you know,
• 1:20:40
  we're we're in the United States, and particularly in some states like California,
• 1:20:46
  the we are being strangled by regulation. Yeah, and this is an
• 1:20:51
  important point to make, which is I think obvious when you think about it,
• 1:20:56
  that if if we keep making more rules and regulations and laws every year,
• 1:21:02
  and those laws and regulations are immortal, but humans are not immortal,
• 1:21:09
  then over time, you know, you'll be like Gulliva where you're tied down
• 1:21:13
  by millions of strings and you can't move. It's true, It's true.
• 1:21:18
  That's why your first principles approach to your business is so interesting. I wish
• 1:21:24
  we had first principles approach to policy making. And you know, because you're
• 1:21:30
  right that the regulations are strangling. The only good news here in this and
• 1:21:36
  we've seen it, is other countries want innovation. You know, US has
• 1:21:42
  been you know, has been the source of a lot of innovation, but
• 1:21:46
  some of our you look at the FAA and drones there there That business has
• 1:21:54
  done much better elsewhere in the world. You know, it's been very frustrated
• 1:21:58
  here and now the is starting to play ball because of it. Do you
• 1:22:01
  think that that uh, you know, that competitive dynamic or regulatory arbitrage will
• 1:22:10
  change things anytime soon, or do we just need someone to come in first
• 1:22:14
  principles and kind of figure out a way to convince everyone we need to get
• 1:22:18
  a white sheet of paper and and not start all over. But you know
• 1:22:24
  what I mean, I think we need to have a process for garbage collection
• 1:22:28
  of rules and regulations that if you don't have some means of deleting rules and
• 1:22:34
  regulations and you only ever add them, then that we'll obviously just end up
• 1:22:40
  in a situation where everything is illegal. Yes, yes, which is where
• 1:22:45
  we where we are, and and uh kind of the bigger and more complex
• 1:22:49
  the state is, like like California, New York. Uh, you just
• 1:22:54
  have I guess, first approximation, the number of regulators you have is proportioned
• 1:22:59
  to your population, and so other Texas in Florida do do do better in
• 1:23:02
  that regard. But there's just so many rules and regulations in California, New
• 1:23:09
  York. And if you say, you know La County, you know City
• 1:23:14
  of La It's now you've got it's it can take you several months simply to
• 1:23:20
  get a permit to change the tiles in your bathroom. Literally. Yeah,
• 1:23:26
  So you know that's I think things are. We we've got to do something
• 1:23:30
  here or we're just doomed for this reason. Elon, do you think China
• 1:23:41
  is at a competitive advantage, it's command and control. I've heard you,
• 1:23:45
  you know, say that they're very tech savvue down to the mayor of every
• 1:23:49
  city. Do you think or do you think what has happened over there that
• 1:23:54
  there's a dynamic changing. Maybe they've been they've over leveraged after twenty years of
• 1:24:00
  you know, basically buying the dip was the right thing to do until it
• 1:24:04
  wasn't. Do you think that it is now entered more of a Japanese style,
• 1:24:12
  you know, you know, they have to readjust to a new reality.
• 1:24:16
  Or do you think, you know, the regulatory or less regulation over
• 1:24:23
  there is going to give them a competitive advantage and innovation is going to you
• 1:24:29
  know, help bail them out. I don't think China is not immune to
• 1:24:35
  the same forces that have driven excess regulation and laws in the United States or
• 1:24:39
  Europe. They you know, absolutely seen just in the course of our operations
• 1:24:46
  in China details in China, we've seen quite a substantial increase in the regulatory
• 1:24:53
  button. So you know, the it's a harder to get things done now
• 1:25:00
  than it was ten years ago. That's that's so what I'm saying is I
• 1:25:06
  think this is just a natural part of the evolution of any any country is
• 1:25:13
  the growth of rules and regulations. Now, in history, the forcing function
• 1:25:19
  for cleaning up bad rules and regulations or or sort of archaic rules and things
• 1:25:29
  that don't really matter anymore has been war. That has been what has driven
• 1:25:32
  has been the clansing function for rules and regulations. So now we would like
• 1:25:41
  to avoid war as ideally we can do this without war. That would be
• 1:25:44
  nice. So you know, it would be nice. Has it ever happened?
• 1:25:54
  Has it ever happened before? I know you're a student of war and
• 1:25:58
  battles and that you really under stand that dynamic. Have we ever cleansed the
• 1:26:02
  system without it? I am not aware of. I'm not aware of a
• 1:26:10
  situation like that that. Yes. Now, the thing is, in history,
• 1:26:14
  wars were very common, so you know that we're in this odd,
• 1:26:20
  odd bit of history where war is quite rare. We're talking about, you
• 1:26:24
  know, total population of the world divided by a number of by percentage of
• 1:26:30
  the population at war. If you say, look what percentage of US population
• 1:26:32
  is actively at war, it's very tiny today compared to any time in history.
• 1:26:42
  The people confuse caring about war from being in war very different. Yeah,
• 1:26:49
  I think exposing and I know you did in Ukraine with Starlink, Exposing
• 1:26:57
  what's going on is half of the It is half the solution in a sense,
• 1:27:02
  right, or or maybe the reason that you know that that we're not
• 1:27:09
  going through the horrors of war because you can see it in living color and
• 1:27:14
  and and how devastating it is. Yeah, I mean that that is certainly
• 1:27:21
  something that is possible. It was not possible in the past, although it
• 1:27:28
  clearly doesn't stop the Ukraine War, right, that's still going on. And
• 1:27:36
  you know, I think a lot of a lot of things if they've been
• 1:27:40
  social media, so clear they would have happened at all, Like the creation
• 1:27:44
  of the United States. If if I was thinking, like if they've been
• 1:27:46
  social media at the time of of Roanoke, I think people would have been
• 1:27:51
  persuaded from future voyages. M h. It's like we're dying of salvation play
• 1:28:00
  the locals. We've got rifles, disease. That's a good point, very
• 1:28:06
  good, but that isn't that is another way to reset the regulatory landscape is
• 1:28:11
  kind of exploration, right, I mean, like who knows what. I'm
• 1:28:15
  sure there's some set of loss that apply on the moon and potentially Mars,
• 1:28:19
  but you know, it's much more difficult to enforce laws from from that long
• 1:28:26
  a distance. Yeah. I think ultimately, if there is a self sustaining
• 1:28:31
  city on the Moon or Mars, that self sustaining city will achieve autonomy at
• 1:28:39
  some point. So I think it's quite important that we have, extremely important
• 1:28:47
  that we become a multi planet civilization and create a self sustaining city, ideally
• 1:28:55
  on Mars, because that's quite far away from Earth, and I think if
• 1:29:00
  something were to take down Earth civilization, then it would it's less likely to
• 1:29:04
  take take out a mar civilization because Earthenware was early in the same quadrant of
• 1:29:12
  the Solar system, you know, for six months every two years, so
• 1:29:15
  for a lot of separation. And I think, you know, I think
• 1:29:23
  a lot about the permi paradox of where are the aliens? I've seen no
• 1:29:26
  evidence of aliens. People always ask me if I've seen any evidence of aliens,
• 1:29:30
  and I would immediately shot from the rooftops and from the X platform of
• 1:29:34
  any any evidence whatsoever about aliens, I would be you've Yeah, I would
• 1:29:41
  be talking about it immediately, and I have. Thus I've seen none.
• 1:29:45
  That's a concern because it means that we perhaps are alone. And you know,
• 1:29:54
  and and maybe there were many other civilizations, but they failed to pass
• 1:29:57
  the great culture of big of going from one planet to being a multiplanet civilization.
• 1:30:03
  So I guess my concern is that we need to keep civilization going at
• 1:30:06
  least long enough to be a multiplanet civilization. At that point, I think
• 1:30:11
  we stabilize civilization and consciousness and greatly extend the probable life span of civilization and
• 1:30:19
  consciousness as we know it. So, you know, I don't want to
• 1:30:26
  have to say this is not some escape patch from Earth, because people are
• 1:30:29
  misinterred with this as like some escape patch from Earth. The this and this
• 1:30:33
  really doesn't apply to me personally, because you know, I will probably die
• 1:30:38
  in I don't know, forty or fifty years, hopefully you know, living
• 1:30:42
  that long. Maybe I don't live even that long. But the civilization can
• 1:30:47
  last for tens of thousands of years, perhaps hundreds of thousands, perhaps millions
• 1:30:53
  of years. So I think it's very important that we make life multiplanetary while
• 1:31:00
  the window is open. And this is the first time in the history of
• 1:31:04
  Earth that in four and a half billion years of Earth's existence that it has
• 1:31:12
  been possible to extend life and consciousness to another planet. So that window is
• 1:31:17
  now open for the first time in four and a half billion years. Now.
• 1:31:23
  It may stay open for a long time, but it may also close,
• 1:31:27
  and I think so we should just take advantage of the time when the
• 1:31:31
  window is open to make life multiplanetary and ensure that the tiny candle of consciousness
• 1:31:42
  in a vast darkness continues to continues to burn, does not go out.
• 1:31:48
  Do you think that Starlink you've said kind of the advance the idea that you
• 1:31:53
  needed hypersonic travel to basically capitalize colonizing mar is starlink ornof or does that still
• 1:32:02
  do you still need that second kind of like business model built on top of
• 1:32:05
  space x to make it happen. I think Starlink is enough. I think
• 1:32:11
  Starlak is enough. You know that there's there's there's a little diagram on the
• 1:32:19
  Stomic router. It's where people will probably don't notice, but it's it's a
• 1:32:30
  homo transfer from Earth to Mars. So if you look on your Starlink router,
• 1:32:38
  you'll see that homo transfer diagram. That Starling is the means by which
• 1:32:50
  life becomes multiplanetary. So well, you know you're you as you are.
• 1:33:03
  You are pioneering us in an amazing way. A lot of a lot of
• 1:33:12
  the hope for the future is so much as it of it, you know
• 1:33:16
  has has has started with you know, with projects you've started and dreams you
• 1:33:25
  have. And I think the world's a better place. And I'll end where
• 1:33:30
  I started. I I know that media clicks, you know, maybe negative
• 1:33:38
  is it works, but long run, long run, truth wins out.
• 1:33:43
  And uh, you know you're doing amazing things and I think the world will
• 1:33:49
  thank you for years and years and years. And maybe just a clue Charnie,
• 1:33:59
  oh sorry and click back immune just as a closing thought to build off
• 1:34:01
  that, maybe as well, how would you think about inspiring the next generation
• 1:34:06
  of entrepreneurs to do the really big hard things. Does it make most sense
• 1:34:11
  to try and do something more consumer internet or something earlier, build up capital
• 1:34:15
  and then go and do something very hard or do you think that what would
• 1:34:17
  you want to have heard as a as a starting out entrepreneur thinking about that
• 1:34:21
  journey and also to inspire the next generation to do great things, including building
• 1:34:27
  all the cottage industry no out of things that will need to survive on Mars.
• 1:34:30
  Great question. Well, I actually think that you know, and anyone
• 1:34:38
  that has a you know, a company that's providing goods and services is doing
• 1:34:46
  great. I mean, it's not that or when you tackle so called you
• 1:34:50
  know it quotes great challenges, I would recommend that they don't actually, because
• 1:34:59
  the probably of failure is very high. I mean, I think I think
• 1:35:03
  just just try to be useful, is my advice. It's very difficult to
• 1:35:08
  be useful. You know. If you see like total area under the curve
• 1:35:13
  of how useful you've been to other people, you know, that's cumulatively,
• 1:35:18
  that's that's it's very hard to make that a big number, you know.
• 1:35:24
  So it's really just trying to be useful and make you great pots and services
• 1:35:30
  that people want and make their lives better. That's it. And you know,
• 1:35:39
  as far as you know, encouraging entrepreneurs to start companies, my advice
• 1:35:44
  would be that if if you need encouragement to start a company, don't do
• 1:35:47
  it, right, right, yeah, because you'll probably I mean, the
• 1:35:56
  probably failure is very high, so you really should not. If if you
• 1:36:01
  need encouragment, yeah, yeah, don't do it. Thank you, yeah,
• 1:36:11
  thank you so much, Elon. You know, as I think,
• 1:36:14
  as it's clear, if you have if you have an idea that will fill
• 1:36:21
  an unmet need that the world, you know some of the world really needs,
• 1:36:26
  and you have a passion to go for it, then yes, but
• 1:36:30
  agreed. The probability of failure is Brett, I think you know. Is
• 1:36:33
  it ninety percent? For new businesses eighty ninety percent. Let's stay