Latest / Elon Musk Thinking / Elon Musk Latest Interview by Ron Baron!!!

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Elon Musk Latest Interview by Ron Baron!!! · Elon Musk Thinking

• 0:00
  Speaker 1: Where's the room for them on the sidewalks? Or are
• 0:03
  Speaker 1: you going to build something? Is that the idea that
• 0:05
  Speaker 1: we have behind a boring company to go underground for
• 0:10
  Speaker 1: the robots to walk around or fly above?
• 0:12
  Speaker 2: Where's the room for them?
• 0:13
  Speaker 3: Well? Actually, actually you can. You can fit all humanity
• 0:18
  Speaker 3: on the poor in the city. That's how small humans
• 0:22
  Speaker 3: are and octopus doesn't mind being pastically how much room.
• 0:26
  Speaker 4: Do people take?
• 0:27
  Speaker 3: And and this is why I think just having it
• 0:29
  Speaker 3: in the back of your mind that all eight billion
• 0:31
  Speaker 3: people on Earth can fit on one floor in the
• 0:37
  Speaker 3: city of New York.
• 0:38
  Speaker 4: So play. Another way I think meet is if you're find.
• 0:41
  Speaker 3: A cross the country and you'll go is to drop
• 0:44
  Speaker 3: a water blapoon on someone you you will fail.
• 0:49
  Speaker 4: Because it's empty.
• 0:50
  Speaker 1: We used to do that when we were in eighth grade.
• 0:53
  Speaker 1: We got them though. Yeah, So so Kaitlin, don't worry.
• 0:59
  Speaker 1: There's enough for so One of the things I think
• 1:01
  Speaker 1: about when you talk about Optimus is that there are
• 1:04
  Speaker 1: so many functions that it can perform. What's going to
• 1:07
  Speaker 1: be left for humans? Is there a job that humans
• 1:10
  Speaker 1: going to have other than just living? And you know
• 1:12
  Speaker 1: this great abundance that you're going to create what's going
• 1:16
  Speaker 1: to happen?
• 1:17
  Speaker 3: Well, I think there is this question of coming, Oh
• 1:20
  Speaker 3: how you write me? If the robots can do everything?
• 1:24
  Speaker 3: But we see lots of example where even though machines
• 1:29
  Speaker 3: can do much better humans sool like athletic experts, or
• 1:35
  Speaker 3: let's take up a mental school like chess, computers are
• 1:38
  Speaker 3: so good at your phone not even connected to the internet,
• 1:41
  Speaker 3: can beat magnus calls easily, but yet chess is that full.
• 1:46
  Speaker 4: Time huts and popularity.
• 1:48
  Speaker 3: So really, machines being better than something doesn't mean we
• 1:53
  Speaker 3: drives that doing.
• 1:55
  Speaker 1: The functions that you see these robots doing is what
• 2:00
  Speaker 1: what are they going to do?
• 2:01
  Speaker 2: And why is that? How are we going to have
• 2:02
  Speaker 2: a billion of them? And we have eight billion people.
• 2:05
  Speaker 3: Look like it's gonna take us a minute to make
• 2:07
  Speaker 3: a billion robots. So you know, I don't love you, brace,
• 2:10
  Speaker 3: but but I think we will.
• 2:11
  Speaker 5: There will ultimately be billions, billions of human robots on
• 2:16
  Speaker 5: a way to think that is, who want to not
• 2:19
  Speaker 5: one their own postal R two D two T three
• 2:23
  Speaker 5: p oo like pretty much goos you know three po.
• 2:28
  Speaker 4: Even better like your personal help for buddy robot.
• 2:32
  Speaker 3: It would be great, Uh, you could teach you teach
• 2:35
  Speaker 3: your kids taking balk from a walk, get the groceries,
• 2:38
  Speaker 3: you know, chat cushats, you know, protect you where need
• 2:42
  Speaker 3: is great? And then how many robots would it be
• 2:46
  Speaker 3: an industry providing products? So it's probably three or four
• 2:50
  Speaker 3: to one relative to humans, which which suggests that total
• 2:54
  Speaker 3: number of robots will be somewhere around maybe his highest
• 2:57
  Speaker 3: forty billion.
• 2:58
  Speaker 4: Don't forty forty billion? Maybe give you thirty billion robots.
• 3:01
  Speaker 4: It's a lot.
• 3:02
  Speaker 1: So the Japanese company is Kokop. Those robots that are
• 3:07
  Speaker 1: used in manufacturing are fifty one hundred thousand, one hundred
• 3:11
  Speaker 1: and fifty thousand. And you're describing a robot as twenty
• 3:14
  Speaker 1: thousand dollars. We have to have a million a year
• 3:16
  Speaker 1: to do that, with ten million a year to get
• 3:19
  Speaker 1: to twenty thousand dollars. And is that something that's going
• 3:22
  Speaker 1: to be affordable for people? Are they going to be rented,
• 3:24
  Speaker 1: They're going to be purchased corporations. Are we going to
• 3:26
  Speaker 1: get some kind of carried interest once they buy them
• 3:28
  Speaker 1: from us?
• 3:29
  Speaker 2: How is that going to work? Or don't we have
• 3:30
  Speaker 2: the model yet?
• 3:31
  Speaker 3: My rough guess is that the costs to get sold
• 3:34
  Speaker 3: their labor materials for optimus after we reach a million
• 3:39
  Speaker 3: units of study state production, So call it a year
• 3:41
  Speaker 3: after reaching a million units a year because it takes
• 3:44
  Speaker 3: a lot of effort to.
• 3:45
  Speaker 4: Improve the cost.
• 3:48
  Speaker 3: But at that point, I would expect the bullet the
• 3:51
  Speaker 3: labor materials to be twenty to thirty thousand dollars in
• 3:54
  Speaker 3: count year dollars, and that's a pretty I think that's
• 3:56
  Speaker 3: a pretty safe estimate.
• 3:57
  Speaker 1: When you're improving costs with cars, your idea is that
• 4:01
  Speaker 1: everything we buy from other people to use in our cars,
• 4:05
  Speaker 1: we know exactly how much it costs, and therefore we
• 4:08
  Speaker 1: can tell someone how much we're going to pay for
• 4:10
  Speaker 1: what we're buying from them, and if it doesn't, if
• 4:12
  Speaker 1: they're making too much, then we make that stuff ourselves.
• 4:15
  Speaker 1: Is that the same kind of idea we have in
• 4:17
  Speaker 1: this robots where we're going to it should be much
• 4:19
  Speaker 1: simpler to make in.
• 4:20
  Speaker 2: A car or my rom because in a hand.
• 4:22
  Speaker 3: That the hand is, the hand is extremely complex. There
• 4:25
  Speaker 3: are fifty actuators in the hand in the hand and
• 4:29
  Speaker 3: for actuators the motor, yeah, actuator is the motor Gearbucks
• 4:32
  Speaker 3: and par electronics, So that's one hundred per robot. Really
• 4:37
  Speaker 3: a lot of loot actuators and sensors. Approximately, there's a
• 4:41
  Speaker 3: lot of complexity.
• 4:42
  Speaker 1: Why is that important? Why is it important that we
• 4:44
  Speaker 1: have such a complex hand.
• 4:45
  Speaker 3: In order to do dexterous tasks, you have to have
• 4:48
  Speaker 3: hand with the sensitivity, precision, and degrees of freedom of
• 4:53
  Speaker 3: a human hand, you know. The So something that is
• 4:56
  Speaker 3: we find easy to do, like kick up a screwdriver
• 4:59
  Speaker 3: or ranch or even say thread a needle or play
• 5:04
  Speaker 3: the guitar, actually require a lot of dexterity. But one
• 5:08
  Speaker 3: of the reasons we think we can achieve sustainable abundance,
• 5:11
  Speaker 3: which is sort of the news of the revised version
• 5:14
  Speaker 3: of the company's goal, because it was accelerate sustainable energy, which,
• 5:17
  Speaker 3: as you mentioned, we've we've done that.
• 5:19
  Speaker 4: Our new all this sustainable abundance. So that's abundance for.
• 5:23
  Speaker 3: All, and but in a way that is sustainable that
• 5:26
  Speaker 3: does not destroy any of the national worlds.
• 5:29
  Speaker 2: How do we decide who gets what?
• 5:31
  Speaker 1: Somebody wants to buy my house, they can just come
• 5:33
  Speaker 1: in and start living there.
• 5:34
  Speaker 4: Well I'm not sure why. I mean, I do have
• 5:38
  Speaker 4: a nice house, so.
• 5:42
  Speaker 3: I can certainly see to see the appeal the robots
• 5:45
  Speaker 3: will bill to make anyone else you know, as long
• 5:47
  Speaker 3: as you don't just on it being in a particular location,
• 5:50
  Speaker 3: you can have Robsill be able to build you a counsel.
• 5:53
  Speaker 3: So but the reason for pandect dexterity is we won't
• 5:57
  Speaker 3: be able to do like surgery and precision medical actions.
• 6:03
  Speaker 4: So imagine a world where everyone has access to the best.
• 6:06
  Speaker 3: Search literally everyone, and Optimus will have the level of
• 6:10
  Speaker 3: precision that is frankly superhuman and will be able to
• 6:13
  Speaker 3: do medical procedures of very sophisticated medical procedures, any medical procedure,
• 6:18
  Speaker 3: perhaps things that really humans can't even do because they're
• 6:21
  Speaker 3: too they're too difficult.
• 6:22
  Speaker 4: And that will be available to anyone.
• 6:25
  Speaker 3: People often talk about liminating poverty in providing great medical care,
• 6:29
  Speaker 3: but they never actually have a solution, and money doesn't
• 6:32
  Speaker 3: solve it because there are only so many it's a
• 6:34
  Speaker 3: very limited number of great doctors and surgeons.
• 6:37
  Speaker 4: They don't grow on trees, but now they don't get
• 6:40
  Speaker 4: built in factories.
• 6:40
  Speaker 1: So I sent you a year or two ago an
• 6:43
  Speaker 1: article about a young man who was an interview in
• 6:45
  Speaker 1: Barns and he was thirty three at the time, and
• 6:47
  Speaker 1: he'd become a portfolio manager and he lost his legs
• 6:50
  Speaker 1: to a It was a Paralympic performer and he lost
• 6:54
  Speaker 1: his legs to man eating bacteria. And I said, is
• 6:56
  Speaker 1: there anything we can do to get him out of
• 6:58
  Speaker 1: the wheelchair? And you said yes to is in three
• 7:01
  Speaker 1: or four years we can give him an optimus body
• 7:04
  Speaker 1: and then we can use you know, transistors in his head,
• 7:09
  Speaker 1: in his brain, so let him function as a normal person,
• 7:12
  Speaker 1: dance and sing and walk and run. Have we been
• 7:15
  Speaker 1: able to make progress in that area.
• 7:17
  Speaker 3: Yeah, So that's a compost of bovine companies. One is
• 7:20
  Speaker 3: being neural Link and the other being Tesla. Neural Link
• 7:23
  Speaker 3: is also making good progress. Now has I think over
• 7:26
  Speaker 3: ten patients with neuralink implants and these people who didn't
• 7:30
  Speaker 3: have the ability to remove their farms or legs in
• 7:32
  Speaker 3: some cases were completely locked in like speck step hooking.
• 7:35
  Speaker 3: And they can now communicate and think as quickly, almost
• 7:39
  Speaker 3: as quickly as we're communicating right now, which is very cool.
• 7:43
  Speaker 3: And that's that's going to continue to accelerate. What we
• 7:45
  Speaker 3: can do is a neuralink implant that is taking signals
• 7:49
  Speaker 3: from the motor cortex brain and also receiving signals from
• 7:52
  Speaker 3: the semato quarters. Amatter of sensory cortex and then give
• 7:56
  Speaker 3: someone uh who's lost their legs fimis legs and so
• 8:01
  Speaker 3: you I mean, we're really getting like the six million
• 8:04
  Speaker 3: dollar man here, I mean from back in the day.
• 8:06
  Speaker 4: I don't know if you watched that show, but I
• 8:07
  Speaker 4: watched it.
• 8:08
  Speaker 2: Watch I watched it.
• 8:09
  Speaker 4: Yeah, that was pretty hmmm.
• 8:10
  Speaker 3: Yeah, And we can actually give someone superhuman cybor capabilities
• 8:15
  Speaker 3: like the six million dollar man, but less than six
• 8:17
  Speaker 3: million dollars in the next day at age. I mean
• 8:20
  Speaker 3: six million dollars back then was fourteen in these days
• 8:23
  Speaker 3: it's leg millon. But we're much less than that. I mean,
• 8:27
  Speaker 3: like for something that that would be reasonable and affordable,
• 8:30
  Speaker 3: you know, it might be well like sixty thousand dollars
• 8:33
  Speaker 3: type of thing, and you can take signals from neural
• 8:35
  Speaker 3: laying to mind that would be transmitting to legs, and
• 8:37
  Speaker 3: transmit those to the attached optimous robot legs and he
• 8:40
  Speaker 3: would actually be able to run fast than a human,
• 8:43
  Speaker 3: just like six million dollar.
• 8:45
  Speaker 1: Man in ruralin sounds really exciting, It sounds unbelievably excited.
• 8:49
  Speaker 2: The switch to XAI. So three years ago, you.
• 8:54
  Speaker 1: Were here and you would either just purchased or about
• 8:57
  Speaker 1: to purchase, you know, Twitter, which you've renamed X. And
• 9:01
  Speaker 1: you were widely criticized for that.
• 9:03
  Speaker 4: And yes it was right.
• 9:05
  Speaker 1: In fact, you even mentioned here on stage that you
• 9:08
  Speaker 1: didn't want to have anyone else be angry at you
• 9:11
  Speaker 1: because you had enough people trying to kill you already totally.
• 9:15
  Speaker 1: So you were buying you were buying X and it
• 9:18
  Speaker 1: was forty two billion dollars I think, and you were
• 9:20
  Speaker 1: in the process of raising money. And I called you
• 9:23
  Speaker 1: up and you hadn't called me to solicit me. And
• 9:25
  Speaker 1: I called you up and I said, I would like
• 9:28
  Speaker 1: to invest with you one hundred million dollars in this
• 9:31
  Speaker 1: and it was sixty million dollars for one of our
• 9:34
  Speaker 1: funds and forty million for me. And and you said really,
• 9:38
  Speaker 1: said yeah, You said really, And I said yeah.
• 9:43
  Speaker 2: And you told me that you thought.
• 9:45
  Speaker 1: I would make a double and I said, well, I
• 9:48
  Speaker 1: hope so, but to me, it felt like you made
• 9:51
  Speaker 1: us eight billion dollars in Tesla and be not very
• 9:54
  Speaker 1: appropriate if I didn't support this new venture that you
• 9:57
  Speaker 1: were doing. So we invested and then the day that
• 10:00
  Speaker 1: we pay the money, we marked it down seventy So man, this.
• 10:06
  Speaker 3: Is this is how I know your a true friend
• 10:08
  Speaker 3: run because this is a you know, I do regard
• 10:14
  Speaker 3: to you as.
• 10:14
  Speaker 4: A as a true, true, entrusted friend.
• 10:16
  Speaker 3: And you know, the test of friendship I got more
• 10:20
  Speaker 3: to the storyship. The test of friendship is is who
• 10:27
  Speaker 3: supports you when the chips are down and the tans
• 10:30
  Speaker 3: are tough and everyone's against you.
• 10:31
  Speaker 4: That's a real friend and that's you run.
• 10:33
  Speaker 2: Thank you.
• 10:34
  Speaker 1: So so we did invest that one hundred mark down
• 10:37
  Speaker 1: to thirty and then about a year later we started
• 10:39
  Speaker 1: getting phone calls from edge funds who always seem to
• 10:42
  Speaker 1: know things we're not supposed to know.
• 10:45
  Speaker 4: Yeah, yeah, they do, right, And.
• 10:48
  Speaker 1: They started saying, I'd like to buy your stock for
• 10:51
  Speaker 1: what you paid for it, and I said, I think
• 10:52
  Speaker 1: I'd rather wait to say in which I did. And
• 10:55
  Speaker 1: then and then change the name to X and change
• 10:59
  Speaker 1: the configuration of business. And then from that you bought
• 11:05
  Speaker 1: Twitter and it came together in a social network along
• 11:08
  Speaker 1: with this, and all of a sudden, we have a
• 11:11
  Speaker 1: business that has incredible data. Did you buy this for
• 11:15
  Speaker 1: the data that no one knew about? But their data
• 11:18
  Speaker 1: with six hundred million people talking with each other, it's
• 11:20
  Speaker 1: a physical.
• 11:21
  Speaker 2: Data that no one else has.
• 11:22
  Speaker 1: And then you started rock, which is based on our
• 11:25
  Speaker 1: data and everyone else doesn't have that, they got digital stuff.
• 11:29
  Speaker 1: And then when they have grock, then we need more
• 11:32
  Speaker 1: data centers, and you're building those. And in a space
• 11:35
  Speaker 1: of a very short time, less than months, you built
• 11:39
  Speaker 1: a data center which is four times as large as
• 11:42
  Speaker 1: anyone else on the planet, twenty five thousand what other
• 11:46
  Speaker 1: people had in CPUs, and we built it in GPUs
• 11:50
  Speaker 1: one hundred thousand more powerful. And then you know, now
• 11:55
  Speaker 1: we're going to go to hundreds of that. But the
• 11:58
  Speaker 1: bottom line is the investment that we made. We put
• 12:00
  Speaker 1: up more money and we have a total of three
• 12:02
  Speaker 1: hundred and fifty million dollars invested over the past two
• 12:05
  Speaker 1: or three years, and now it's worth seven hundred million dollars.
• 12:07
  Speaker 2: Everything you touch is like that. It's the most unbelievable
• 12:11
  Speaker 2: thing I've ever seen.
• 12:12
  Speaker 1: So so everyone's investment in technology, and we are investing
• 12:17
  Speaker 1: in in the technology person best engineer on the planet.
• 12:21
  Speaker 1: So thank you very much. So the vision is the
• 12:23
  Speaker 1: question is did you buy X Did you do my Twitter?
• 12:27
  Speaker 1: Because of the data?
• 12:28
  Speaker 2: Is that? Did you have all this in your head
• 12:30
  Speaker 2: before you did it?
• 12:31
  Speaker 3: Not? Really, No, I just bought Twitter because I thought
• 12:33
  Speaker 3: it was having a negative effect on civilization and just
• 12:38
  Speaker 3: sort of pushing ideas that were anti civilizational. You know,
• 12:43
  Speaker 3: it's sort of having Short captured by the far left.
• 12:46
  Speaker 3: That's it's fair to say the radical left. I mean,
• 12:49
  Speaker 3: they wouldn'tn't regard themselves as such, but it was captured
• 12:52
  Speaker 3: by group of people whose vedical beliefs are those of
• 12:58
  Speaker 3: you know, deeply San Francisco book, which is about as
• 13:00
  Speaker 3: des get in America, that that that it wasn't a
• 13:03
  Speaker 3: good forum for debate because they suspended many people on
• 13:08
  Speaker 3: the right, including the president, as as a miracle is
• 13:11
  Speaker 3: sitting president, which is really unprecedented.
• 13:15
  Speaker 4: President.
• 13:15
  Speaker 3: I think we need to have a public square where
• 13:18
  Speaker 3: there's a true freedom of speech, and freedom speech is
• 13:22
  Speaker 3: freedom of speech is the bedrock of democracy. If there's
• 13:25
  Speaker 3: no freedom of speech, people kindot make an informed vote,
• 13:28
  Speaker 3: and if you can't make an yourform vote, you don't
• 13:30
  Speaker 3: have a real democracy. So that's the purpose of acquiring
• 13:34
  Speaker 3: twitters who try to bring it more to the center.
• 13:37
  Speaker 3: There's been no no left wing voices have been banned
• 13:39
  Speaker 3: or anything like that or suppressed. But what you're trying
• 13:43
  Speaker 3: to do is give equal weight to all parts of
• 13:46
  Speaker 3: the country so that they can be a public count
• 13:49
  Speaker 3: square where people can exchange ideas and hopefully not preserved violence.
• 13:53
  Speaker 4: I think that's that's fundamental.
• 13:56
  Speaker 3: To I think it's one of the It's like free
• 13:59
  Speaker 3: speech because the bedrock democracy is. It's why it's the
• 14:01
  Speaker 3: first Amendment. Is people came from countries where if they
• 14:04
  Speaker 3: could be killed or imprisoned what they said. And in fact,
• 14:09
  Speaker 3: this is happening all around the world, as even in
• 14:11
  Speaker 3: places like Writin. So that's anyway I didn't because I
• 14:18
  Speaker 3: felt like the civilizational risks had to be addressed. I mean,
• 14:21
  Speaker 3: if America is not strong, then what the businesses matter.
• 14:25
  Speaker 3: America is a central pillar that holds up a Western civilization,
• 14:28
  Speaker 3: and if that pillar falls, everything falls.
• 14:32
  Speaker 2: So you were one of the founders, the two founders of.
• 14:36
  Speaker 1: CHATCHBT and you know open AI and you had a
• 14:39
  Speaker 1: disagree and it was founded as a charity, and it
• 14:41
  Speaker 1: was your idea that you wanted to make sure, you know,
• 14:44
  Speaker 1: freedom of speech and all the things that you deem
• 14:46
  Speaker 1: important for good lives on our planet were followed safety.
• 14:51
  Speaker 1: The other founder, what he tried to do and did
• 14:54
  Speaker 1: was accomplished, is that he got control even though it
• 14:57
  Speaker 1: was your money, and he got control and you and
• 15:00
  Speaker 1: he said, you know, I would like you to stay,
• 15:03
  Speaker 1: and he said, I want to go. I don't want
• 15:05
  Speaker 1: to be a part of this, and uh. And he
• 15:08
  Speaker 1: offered you some ownership and you said I don't want it.
• 15:11
  Speaker 1: And so here you walk away from an ownership of
• 15:14
  Speaker 1: chat GBT. So you're obviously not doing all this stuff
• 15:18
  Speaker 1: for money. I mean you are, but I mean that's
• 15:20
  Speaker 1: not But I mean if you if you were only
• 15:23
  Speaker 1: about money, you would have never left something that's worth
• 15:26
  Speaker 1: five hundred billion dollars by itself. And so here you're
• 15:31
  Speaker 1: forming this new entity Grock to accomplish what you wanted
• 15:39
  Speaker 1: Chat GIBT to accomplish.
• 15:40
  Speaker 2: But you think that we have an advantage.
• 15:42
  Speaker 1: In this because of the data, because of the compute,
• 15:45
  Speaker 1: because of what and what are you going to do
• 15:47
  Speaker 1: with this?
• 15:48
  Speaker 2: Ultimately?
• 15:49
  Speaker 1: If you talk about connecting physical worlds and digital what
• 15:52
  Speaker 1: does that mean?
• 15:53
  Speaker 3: Yeah, Well, just going back to opening a for a second,
• 15:56
  Speaker 3: the reason I found it Opening Eye was because I
• 15:59
  Speaker 3: was concerned so of my conversations with Larry Page, used
• 16:02
  Speaker 3: to be a close friend of mine, that he was
• 16:04
  Speaker 3: not sufficially concerned about the dangers of AIS really came
• 16:07
  Speaker 3: to a head when at my birthday party, he, in
• 16:10
  Speaker 3: front of a large group of people, called me a
• 16:12
  Speaker 3: species for favoring.
• 16:15
  Speaker 4: Humanity over computers. I think that's problem. I was like, Larry,
• 16:22
  Speaker 4: what side are you on?
• 16:25
  Speaker 3: It sounds like you're on the side of the computers,
• 16:27
  Speaker 3: but you really need to be on team humanity here.
• 16:29
  Speaker 4: You know. After that, I was like, Okay, this is it.
• 16:31
  Speaker 3: We've got to have some counterbalance to Google, because Larry
• 16:34
  Speaker 3: doesn't seem to care if humans to make it or not.
• 16:36
  Speaker 3: So I thought, what's the opposite of Google. It would
• 16:39
  Speaker 3: be an open source nonprofit. And that's where the word
• 16:42
  Speaker 3: open in opening eye comes from. It it means open source.
• 16:45
  Speaker 3: And and then I provided. I provided all the money
• 16:48
  Speaker 3: beginning like what are the series APC rounds, and recruited
• 16:53
  Speaker 3: the key people like Elisi's guy, and put them everything
• 16:56
  Speaker 3: out of I actually even got them to deal with
• 16:57
  Speaker 3: Microsoft with with such actially got I got such to
• 17:01
  Speaker 3: donate some time from Azure and for all that, I
• 17:04
  Speaker 3: did not seek any financial reward back whatsoever. And the
• 17:09
  Speaker 3: reason I actually took down the offer for shares is
• 17:11
  Speaker 3: because I mean I felt like what shares and why?
• 17:14
  Speaker 3: Like nonprofits supposed to have shares these last time I checked,
• 17:17
  Speaker 3: not space nonprofits. They're not supposed to be big yourself
• 17:20
  Speaker 3: in richment. So that's why I tuned down the offer
• 17:23
  Speaker 3: of shares because it doesn't seem morally illegally defenseful with
• 17:27
  Speaker 3: with Xai, and we are startying late with Xai, and
• 17:29
  Speaker 3: ever only two and a half years before basically designing
• 17:34
  Speaker 3: from behind.
• 17:35
  Speaker 4: We al somewhat have been underdoing, but pretty good with.
• 17:38
  Speaker 3: Technology though I don't want to put myself in back here,
• 17:41
  Speaker 3: but I have pretty good with technology, and we are
• 17:42
  Speaker 3: advancing bester than any other way. And I think the
• 17:45
  Speaker 3: for technology adventures, the winner ultimately is the one that
• 17:48
  Speaker 3: is able to move the fastest.
• 17:50
  Speaker 1: So we're optimizing for the best technology, and we're doing
• 17:54
  Speaker 1: something different than others, others in a digital world and
• 17:57
  Speaker 1: we're physical through digital with move meant and visual and
• 18:02
  Speaker 1: other people can't match that.
• 18:04
  Speaker 2: And also we have the real time data. What does
• 18:06
  Speaker 2: that mean? Why should we do better than everyone else?
• 18:08
  Speaker 2: Why are we going to win?
• 18:09
  Speaker 1: Why are we going to at least be different than
• 18:11
  Speaker 1: everyone else? So we have a really strong business.
• 18:14
  Speaker 4: Well for sure, I think it doesn't make a strong business.
• 18:16
  Speaker 3: Actually, not too worried about that because even a small
• 18:21
  Speaker 3: player that is successful in AI will be worth a
• 18:23
  Speaker 3: lot because they will cut to result and productivity to
• 18:25
  Speaker 3: the economy.
• 18:26
  Speaker 4: So it's actually pretty easy to.
• 18:29
  Speaker 3: Achieve a got pretty easy, But I mean it's not
• 18:32
  Speaker 3: There will be many companies that are worth sustainably, some
• 18:36
  Speaker 3: one hundred billion dollars sustainably.
• 18:38
  Speaker 4: Then several question of like well how do we achieve
• 18:40
  Speaker 4: the lead? That comes down to three things. Are you
• 18:44
  Speaker 4: able to.
• 18:45
  Speaker 3: Attract the best talent? Are you able to bring the
• 18:47
  Speaker 3: most amount of AI hardware online? Can you can you
• 18:50
  Speaker 3: bring GPUs online faster than anyone else? And we've already
• 18:54
  Speaker 3: demonstrated that we can do that. Jensen Monk himself said
• 18:57
  Speaker 3: that he was blown away by half past exciting to
• 19:00
  Speaker 3: Stata Center.
• 19:01
  Speaker 1: Jensen said, there's only one human on the planet who
• 19:03
  Speaker 1: could have done that.
• 19:04
  Speaker 2: That's you. Yes, it made us think about are you
• 19:07
  Speaker 2: really human?
• 19:10
  Speaker 4: I keep talking about I'm an alien, but nobody believes me.
• 19:14
  Speaker 3: I mean when I got my green clod and said
• 19:16
  Speaker 3: alien registration part So I mean, you know I have
• 19:19
  Speaker 3: I grow from the government.
• 19:23
  Speaker 4: Actually, I've got some relatively.
• 19:25
  Speaker 3: Rare skills these days in America, getting hardware.
• 19:30
  Speaker 4: I mean, if you look at the biggest successes.
• 19:33
  Speaker 3: In manufacturing in America since World War Two, by far
• 19:36
  Speaker 3: our Tesla in spaces.
• 19:37
  Speaker 1: So so to stay Sam Grock for another minute. So
• 19:41
  Speaker 1: the idea of connecting physical and digital is that that's
• 19:46
  Speaker 1: different digital digital figuring out who wants to buy what
• 19:51
  Speaker 1: we're doing something entirely different.
• 19:52
  Speaker 2: Is that fair?
• 19:53
  Speaker 3: I wouldn't say we're doing some up. We're doing we're
• 19:55
  Speaker 3: doing some things that are the same some things that
• 19:57
  Speaker 3: are different. But saying, like the elements that define success
• 20:02
  Speaker 3: for an AA company or won the talent to the hardware,
• 20:06
  Speaker 3: how much AI hardware can you bring to bear that
• 20:09
  Speaker 3: that's actually a very big deal, and we've shown that
• 20:11
  Speaker 3: we're the best at doing that at XAI.
• 20:13
  Speaker 4: And then third, unique access to data.
• 20:15
  Speaker 3: And for that we've got the x system formerly the
• 20:18
  Speaker 3: Twitter system, which is by far the best source of
• 20:20
  Speaker 3: real time data in the world. So that those are
• 20:23
  Speaker 3: some pretty significant assets. And I think we're going to
• 20:26
  Speaker 3: come up with some very innovative ideas. And I have
• 20:28
  Speaker 3: more ideas in mind that I know what to do with. Frankly,
• 20:30
  Speaker 3: I think we'll make some moves that are not on
• 20:32
  Speaker 3: the chess board that people don't anticipate in some creative moves,
• 20:35
  Speaker 3: and like I said, so I should point out but
• 20:38
  Speaker 3: growk Right now, Rock heavy is still the smartest AI
• 20:42
  Speaker 3: best of my knowledge, I recommend coming it out. Crock
• 20:45
  Speaker 3: Foy heavy is where we sporn several agents so they
• 20:48
  Speaker 3: work in parallel and they compare their output like a
• 20:50
  Speaker 3: study group and give you the final conclusion. And it
• 20:52
  Speaker 3: keeps getting better. And now we've gone training on Rock five.
• 20:55
  Speaker 3: Rock five I think will be the smartest AI in
• 20:59
  Speaker 3: the world, my significant margin on every metric without exception.
• 21:04
  Speaker 4: I might be wrong, but I think that will be
• 21:07
  Speaker 4: the case, and that will be in Q.
• 21:08
  Speaker 3: One sometimes Grack five, yes, I and Grock five is
• 21:13
  Speaker 3: the first time where I thought, well, we have a
• 21:15
  Speaker 3: non zero chance of achieving artificial general intelligence.
• 21:19
  Speaker 4: Not that it's a high chance.
• 21:21
  Speaker 3: I can't it like ten percent, but that's what my
• 21:25
  Speaker 3: biological neural name comes up with, which still means ninety
• 21:28
  Speaker 3: percent chance to be don't.
• 21:29
  Speaker 4: But I've never thought that before, and so for.
• 21:31
  Speaker 3: The first time I think, like, well, this this really
• 21:33
  Speaker 3: could be general intelligence at least a small chance. Rock
• 21:36
  Speaker 3: five will really be something special and it'll be both
• 21:39
  Speaker 3: extremely intelligent and extremely intelligence and extremely fast. So one
• 21:44
  Speaker 3: of the things that we're doing that I think is
• 21:45
  Speaker 3: interesting is Rocklipedia, which we're going to rename down the
• 21:49
  Speaker 3: road to incite to be Encyclopedia galact in of Isaac
• 21:54
  Speaker 3: Asimov and Douglas Adams. We both mentioned that, and the
• 21:58
  Speaker 3: idea of behind the fact Galactica is to create an
• 22:02
  Speaker 3: open source repository of all knowledge, like a distillation of
• 22:07
  Speaker 3: whole knowledge, and an open source meaning anyone can access it,
• 22:09
  Speaker 3: anyone can use it, and if other people want to
• 22:11
  Speaker 3: train on it, they can do so.
• 22:13
  Speaker 4: And then we want to create copies of this.
• 22:15
  Speaker 3: And distribute these copies throughout Earth and even put them
• 22:17
  Speaker 3: on the Moon and Mars and out of deep space
• 22:20
  Speaker 3: as in a way sort of a modern day Library
• 22:23
  Speaker 3: of Alexandria. It was the great tragedy that the Library
• 22:26
  Speaker 3: of Alexandria wrote down what was bunt down. And in
• 22:29
  Speaker 3: order to preserve this knowledge, I think we want to
• 22:32
  Speaker 3: literally enter it in stone and sort of stone stone
• 22:35
  Speaker 3: like my microplaunch, and distribute it widely. So the worst
• 22:38
  Speaker 3: case scenario future civilization, you can see what we learned
• 22:41
  Speaker 3: and pick things up from there.
• 22:43
  Speaker 1: So is there a major breakthrough that you can describe
• 22:46
  Speaker 1: that allows us to do this with grap five.
• 22:48
  Speaker 2: Is it just speed?
• 22:50
  Speaker 1: Is it more compute and therefore we are more and
• 22:53
  Speaker 1: now more you know, information we can train on.
• 22:56
  Speaker 2: What is the.
• 22:57
  Speaker 1: Breakthrough that allows us to to have is ten percent
• 23:01
  Speaker 1: chance for a GI Is there is there a breakthrough?
• 23:04
  Speaker 2: Or is just speed and access to data?
• 23:06
  Speaker 4: Act just it will be the largest models, best maneral.
• 23:09
  Speaker 3: So this is this is a six trillion parameter model,
• 23:12
  Speaker 3: whereas Rock three and four are based on a three
• 23:14
  Speaker 3: trillion parameter model. More of about the six trillion parameters
• 23:18
  Speaker 3: will have a much higher intelligence density for gigabyte than
• 23:22
  Speaker 3: Rock fall. I think this is an important metric to
• 23:26
  Speaker 3: think about intelligence for gigabyte and.
• 23:27
  Speaker 4: Intelligence for trillion operations.
• 23:30
  Speaker 3: We've learned a lot the quality of the data that
• 23:33
  Speaker 3: we're training on with Rock five business here. It's also
• 23:37
  Speaker 3: inherently multimodal, so it's XT, pictures, video, audio, bits. It's
• 23:43
  Speaker 3: going to be much better at tool use and effect
• 23:46
  Speaker 3: creating tools to be more effective at answering questions and understanding.
• 23:53
  Speaker 3: Its vision will be extremely good. It'll have real real time,
• 23:57
  Speaker 3: real time. But which is I think really fundamentally important
• 24:00
  Speaker 3: thing that none of the other anis can understand real
• 24:02
  Speaker 3: time video. I think if you can't do that, which
• 24:04
  Speaker 3: is humans can obviously do, you're you really can't achieve
• 24:09
  Speaker 3: a GI.
• 24:10
  Speaker 2: Every one of these.
• 24:11
  Speaker 3: There's some special source items that I there's some special
• 24:14
  Speaker 3: source items that I can't talk about in the public
• 24:16
  Speaker 3: from obviously you can't can't give away you.
• 24:19
  Speaker 4: Know, all the secrets here just between us.
• 24:22
  Speaker 3: But but but we have a few a few other
• 24:24
  Speaker 3: special things that are that are in the works.
• 24:28
  Speaker 4: For Rock five, it's really really going to feel sentient.
• 24:33
  Speaker 1: So but there is no when we're Grock five, when
• 24:36
  Speaker 1: you're talking about the advances, there is no limit. So
• 24:39
  Speaker 1: when we're groped, five is better than Rock four, which
• 24:41
  Speaker 1: is better than Rock three. But so so it keeps going.
• 24:44
  Speaker 1: So once we get to sentient levels, we go two
• 24:47
  Speaker 1: sentient five sent ten sentent millions.
• 24:50
  Speaker 3: Right the sentence book grow, I mean, which really mind blowing.
• 24:58
  Speaker 3: It's how far candasing teams to to your point, well,
• 25:01
  Speaker 3: how far does it go? I think it goes immensely
• 25:05
  Speaker 3: for almost incomprehensibly For that almost does go incomprehensibly far,
• 25:11
  Speaker 3: Like we see a path to putting one hundred gigawatts
• 25:15
  Speaker 3: per year of solo powered AI satellite into orbit and
• 25:20
  Speaker 3: and having this would be actually the lowest cost way
• 25:23
  Speaker 3: to power and operate.
• 25:25
  Speaker 4: The AI at a very large scale.
• 25:29
  Speaker 3: For reference, the United States consumes roughly four hundred and
• 25:33
  Speaker 3: sixty gigawatts an average per year because that average powerlel
• 25:36
  Speaker 3: the US is border.
• 25:37
  Speaker 2: Sixty together whole country, the whole country.
• 25:39
  Speaker 4: All electricity of all sources in the US.
• 25:41
  Speaker 2: Yes, and you're talking about one hundred being.
• 25:43
  Speaker 3: It well roughly of the US electricity out. We have
• 25:46
  Speaker 3: a we have a plan mapped out to do that.
• 25:48
  Speaker 3: It gets crazy.
• 25:49
  Speaker 1: So so here's what a treeum planets like Earth in
• 25:56
  Speaker 1: the world in a solar system whatever you call it,
• 26:00
  Speaker 1: truly and in that trillion So Big Bang was fourteen
• 26:03
  Speaker 1: billion years ago, thirteen billion years and planet are planets
• 26:07
  Speaker 1: only four billion years old, So there must be other planets.
• 26:10
  Speaker 1: They are like ours with all the minerals oxygen, hydrogen, silicon, carbon.
• 26:17
  Speaker 1: So life here has been extinguished four times. And presumably
• 26:21
  Speaker 1: you feel that other places, other civilizations, other planets.
• 26:26
  Speaker 2: Then we'll get off of this exists and are.
• 26:29
  Speaker 1: They planets where the beings there are part human or
• 26:34
  Speaker 1: park carbon and park metal.
• 26:36
  Speaker 3: Well, I think we'd like to find out. I'd like
• 26:37
  Speaker 3: to find out. I mean, my philosophy is one of curiosity.
• 26:41
  Speaker 3: I just want to know what's what's going on in
• 26:43
  Speaker 3: this unit? Is the standindable? Is the standard aysics correct
• 26:46
  Speaker 3: about the beginning of the universe?
• 26:48
  Speaker 4: Is heat death at the end of the universe? Other
• 26:50
  Speaker 4: other aliens organizations? Can we talk to them? And what
• 26:53
  Speaker 4: questions should we be asking you about reality? And we
• 26:55
  Speaker 4: don't know that.
• 26:55
  Speaker 3: So that's my is to expand consciousness to better understand unibuse.
• 27:02
  Speaker 1: So let's go to away from the universe, back to
• 27:05
  Speaker 1: Tesla again.
• 27:06
  Speaker 2: And you said that around here, back on grounds and.
• 27:12
  Speaker 1: So you said that our expertise is in making things better, faster,
• 27:18
  Speaker 1: cheaper than other people. And when I started investing in
• 27:20
  Speaker 1: Testa and we started investing in Tesla, you were telling
• 27:23
  Speaker 1: us that that it's the machine that makes, the machine
• 27:26
  Speaker 1: that's most important, the machine that makes. So you're into
• 27:29
  Speaker 1: machine learning, machine technology then, which is fifteen years ago.
• 27:33
  Speaker 1: And now the average car I think it's fifteen minutes
• 27:38
  Speaker 1: or fifty seconds, forty seconds, sixty seconds, and we're now
• 27:42
  Speaker 1: thirty five seconds. Every thirty five seconds the car rolls
• 27:45
  Speaker 1: off and then you say that we're going to get
• 27:47
  Speaker 1: down to ten seconds, and you said it's a possibility
• 27:50
  Speaker 1: we can go to five five seconds. Every car is
• 27:54
  Speaker 1: rolling off a line. How does that happen?
• 27:57
  Speaker 4: I certainly see a path to achieving it.
• 27:59
  Speaker 3: Roughly five thousand millis second second time or five seconds,
• 28:02
  Speaker 3: which is only that's only really walking speed. That's like
• 28:06
  Speaker 3: sort of a past wall. One meter per second is
• 28:08
  Speaker 3: a past walk. The car's less than five meters long.
• 28:10
  Speaker 3: Five second cycle time. The cars will will be exiting
• 28:13
  Speaker 3: the line at voking speed, so it's you can run
• 28:16
  Speaker 3: away from them. It's not going to be like they're
• 28:18
  Speaker 3: coming out like bullets or something. So but as a
• 28:23
  Speaker 3: as a rougherl of thumb, that's you know, it's ten
• 28:25
  Speaker 3: thousand minutes in a week. If you're run twenty four
• 28:28
  Speaker 3: to seven operation and you get you know, let's say
• 28:30
  Speaker 3: ten cars per minute, you've got one hundred thousand cars weeks.
• 28:35
  Speaker 2: But the question is how come we're able to do this?
• 28:38
  Speaker 1: The other people just not care or they think that, gee,
• 28:41
  Speaker 1: if I do something, if I have this idea and
• 28:44
  Speaker 1: we try to implement it and it doesn't work, then
• 28:47
  Speaker 1: I'm not going to get promoted where I can get
• 28:48
  Speaker 1: fired or I'll get blamed. And if it works, then
• 28:51
  Speaker 1: I'm have to do a lot of extra work that
• 28:53
  Speaker 1: I wouldn't have to do it if it didn't work.
• 28:55
  Speaker 2: Why don't other.
• 28:55
  Speaker 1: People have, you know, a mindset of making things better?
• 29:01
  Speaker 1: The Chinese they've been great at copying us, and some
• 29:04
  Speaker 1: instance has probably even done better than us after they've
• 29:06
  Speaker 1: copied for the first time. How come do you think that
• 29:10
  Speaker 1: other people haven't been able to make the advances we have.
• 29:14
  Speaker 1: And even the guy from Ford has recently said, gee,
• 29:17
  Speaker 1: this people in China wouldn't give us compliments, but he
• 29:20
  Speaker 1: said the people and the Chinese have copied us. Those
• 29:23
  Speaker 1: people in China are doing great, which is really compliments
• 29:26
  Speaker 1: us because the reason they're doing great is because us.
• 29:28
  Speaker 2: So why don't other people do this? Why doesn't he
• 29:31
  Speaker 2: do that?
• 29:31
  Speaker 3: Most companies are incrementalist, you know, the management team wants
• 29:34
  Speaker 3: to do five percent maybe ten percent better than last
• 29:38
  Speaker 3: year as opposed to big risks that could fail. And
• 29:41
  Speaker 3: obviously I've done have a problem.
• 29:43
  Speaker 2: With taking big risks, yeah, i'd say.
• 29:48
  Speaker 3: And I like to use the tools of physics to
• 29:50
  Speaker 3: Aline's thank you know, when I was in the factory
• 29:52
  Speaker 3: one night I was looking at the factory and I
• 29:54
  Speaker 3: was like, you know this, this could be much more efficient,
• 29:57
  Speaker 3: It could be much faster. There's tried rough mass trying
• 30:00
  Speaker 3: to capeculate the volumetric efficiency of the factory.
• 30:03
  Speaker 4: So if you buy the.
• 30:04
  Speaker 3: Factory in cubic meters and say how many cubic meters
• 30:07
  Speaker 3: are doing something useful and surprisingly small percent, the volumetric.
• 30:10
  Speaker 4: Density is not very good.
• 30:12
  Speaker 3: And then the speed of the cars and the parts
• 30:15
  Speaker 3: moving is quite slow, generally limited by the speed at
• 30:18
  Speaker 3: which people can say attach break lights or a seat
• 30:22
  Speaker 3: or something like that.
• 30:23
  Speaker 4: So if you.
• 30:24
  Speaker 3: Densify the factory and improve the bolumetric efficiency, which is
• 30:28
  Speaker 3: helpful for performable production efficiency because things have the best
• 30:32
  Speaker 3: distance to move, just like just like a chip, you
• 30:34
  Speaker 3: densify circuits in a chip, you get more efficient. They
• 30:37
  Speaker 3: think a lot of factories not like to how do
• 30:39
  Speaker 3: you make your trip faster? Well, you bring circuits closer together,
• 30:42
  Speaker 3: make the smaller, and you increase the clock speed.
• 30:45
  Speaker 1: So Robin told me that you told her once, I
• 30:47
  Speaker 1: think of myself as a bit, and if I'm a bit,
• 30:51
  Speaker 1: how would I like to travel?
• 30:52
  Speaker 4: I mean a bit or an asset?
• 30:54
  Speaker 3: If it's if it's the software software, or I come
• 30:57
  Speaker 3: on a ship, I say, what's the journey of them?
• 30:59
  Speaker 4: What am I doing?
• 31:00
  Speaker 3: And if this journey doesn't make sense, I need to
• 31:02
  Speaker 3: fix that. And if the journey of the ad time
• 31:04
  Speaker 3: in the factory doesn't make sense, and need to fix it.
• 31:06
  Speaker 1: So when you say you're working on weekends, I spent
• 31:08
  Speaker 1: all my sundays working on a chip.
• 31:09
  Speaker 2: What does that mean? What do you do?
• 31:11
  Speaker 3: It's saturdays, but sometimes Sundays actually fast recent weekends.
• 31:17
  Speaker 4: Spend Sundays too.
• 31:18
  Speaker 3: The a I five chip, which is going to be
• 31:19
  Speaker 3: a great chick, you know, all of all tess the
• 31:22
  Speaker 3: hinges on that chick. That's that's the chick that goes
• 31:24
  Speaker 3: that we're going to our next generation of self driving cards,
• 31:27
  Speaker 3: and it's also essential for the Optimist robot.
• 31:29
  Speaker 4: So that chip program was in bad shape.
• 31:32
  Speaker 3: It wasn't it wasn't closing because it's it's quite an
• 31:35
  Speaker 3: ambitious trip to line and it really wasn't on a
• 31:37
  Speaker 3: path to success. And they also have the job program
• 31:40
  Speaker 3: which was doing it was also doing okay, but but
• 31:43
  Speaker 3: not on a path to be competitive for the video.
• 31:46
  Speaker 3: So I clapped. I collapsed the two programs into just
• 31:48
  Speaker 3: one program is to get everyone focused on a five chip,
• 31:51
  Speaker 3: which is essential continue to use in video for training,
• 31:54
  Speaker 3: but we need the AI five infant chip, which is
• 31:57
  Speaker 3: it's a very powerful ship, but it's also a very
• 32:01
  Speaker 3: low power compt. It doesn't use a lot of power.
• 32:05
  Speaker 3: It's performance for what is extremely good. You think, you know,
• 32:07
  Speaker 3: it's probably going to be at least for two to
• 32:10
  Speaker 3: three times better than in video influence for what at
• 32:15
  Speaker 3: the inference level in the car and the robot.
• 32:17
  Speaker 4: And you know, I don't know.
• 32:18
  Speaker 3: Half percent of the cost of an in video chip
• 32:21
  Speaker 3: something like that. So these are very important numbers to achieve.
• 32:25
  Speaker 3: Had to get the ship program back on track. So
• 32:28
  Speaker 3: that's about a time or two. And at this point
• 32:30
  Speaker 3: I have the entire physicook signe of the chip laid
• 32:33
  Speaker 3: out in memory.
• 32:33
  Speaker 4: I can visionize the whole thing.
• 32:34
  Speaker 1: So when you're talking about chip manufacturer, you say, we
• 32:39
  Speaker 1: might have to build some kind of a giant fab.
• 32:42
  Speaker 1: Presumably we would have a partner with TSMC or with Samsung,
• 32:46
  Speaker 1: who wouldn't do this by ourselves, and those guys have
• 32:48
  Speaker 1: been doing this for we would do it by ourselves.
• 32:50
  Speaker 1: And these are things that cost twenty billion, thirty forty
• 32:54
  Speaker 1: billion dollars and where do the people come from to do this?
• 32:57
  Speaker 1: How can we not have partners? Is your thought? To
• 33:01
  Speaker 1: have a partner to do it by ourselves altimately ten years,
• 33:04
  Speaker 1: there's not gonna be enough chips in the world to
• 33:07
  Speaker 1: accomplish what we're trying to do.
• 33:08
  Speaker 3: Yeah, First of all, I have bes respectful KSMC and Samsung,
• 33:12
  Speaker 3: and we've worked with both TSMC and Samsung until the
• 33:16
  Speaker 3: end at uh SpaceX. TSMC and Samsung are great companies
• 33:20
  Speaker 3: and we want them to make our trip as quickly
• 33:23
  Speaker 3: as they can and scale up to as high as.
• 33:25
  Speaker 4: Possible value that that they're comfortable doing.
• 33:27
  Speaker 3: But the it's it doesn't appear to be fast enough.
• 33:31
  Speaker 3: And you know, when I ask how long will it
• 33:34
  Speaker 3: take you start to finish to get a new tube
• 33:36
  Speaker 3: fat both they tell me by five years to get
• 33:38
  Speaker 3: to bluing production, And like five years to me is
• 33:40
  Speaker 3: in the community.
• 33:41
  Speaker 4: My my timelines to.
• 33:43
  Speaker 3: Me too, By the way, one year, two year and
• 33:47
  Speaker 3: a year three scale it wills to finish, so I
• 33:51
  Speaker 3: can't even see that three years. So then I'm like, damn, okay,
• 33:55
  Speaker 3: this is this is not going to be fast enough.
• 33:57
  Speaker 3: Now if they if they change their minds and say, yeah,
• 33:59
  Speaker 3: they're going to go faster and they want to provide
• 34:02
  Speaker 3: us with one hundred two hundred billion ah f C
• 34:04
  Speaker 3: year in the timeframe that we need.
• 34:06
  Speaker 4: That's great.
• 34:07
  Speaker 1: How could they not when they know that we're demand
• 34:10
  Speaker 1: and we are going to use the product in our
• 34:12
  Speaker 1: own product, How could they not want to be our supplier?
• 34:15
  Speaker 1: Or how could they not want to be partners with us?
• 34:17
  Speaker 1: I don't understand what they are partners. We're using both,
• 34:21
  Speaker 1: I mean to really expand capacity tremendously.
• 34:24
  Speaker 2: Why don't they do that?
• 34:25
  Speaker 3: From this standpoint, they are because you'll be using TSMC,
• 34:28
  Speaker 3: tai Wan, t sm C gives me Taiwan TSMC, Arizona
• 34:33
  Speaker 3: Korea song and the Texas fac song to the four faves,
• 34:39
  Speaker 3: and you know, from this standpoint they're moving like I'm
• 34:43
  Speaker 3: just saying that.
• 34:44
  Speaker 4: Nonetheless, it would be a limiting factor for us.
• 34:47
  Speaker 3: They're going as fast as they can from this standpoint,
• 34:49
  Speaker 3: there's Middleton the matter. They're just never at someone without
• 34:52
  Speaker 3: sets of company outsets, versions, that's the matter. It might
• 34:56
  Speaker 3: just be that the only way to get to scale
• 34:58
  Speaker 3: at the rate that we want to get to tail
• 34:59
  Speaker 3: is to to build up a real and or be
• 35:03
  Speaker 3: limited an output of optimized and self driving cars by the.
• 35:11
  Speaker 1: Obviously you're not going to those are two choices to
• 35:13
  Speaker 1: go to FSD. We don't have too much more time.
• 35:16
  Speaker 1: But FSD uh full full self driving. You know, we're
• 35:20
  Speaker 1: making these tremendous breakthroughs, it seems. And you said recently
• 35:26
  Speaker 1: that you didn't want to expand capacity for making cars
• 35:30
  Speaker 1: until you.
• 35:30
  Speaker 2: Were convinced that that was the case. You are now
• 35:33
  Speaker 2: convinced that's the case. And again here.
• 35:36
  Speaker 1: We're making these exponential leaps in making in these cars.
• 35:39
  Speaker 1: And you said that a very large percentage of people
• 35:43
  Speaker 1: who have actually paid for full self driving don't use it.
• 35:46
  Speaker 2: I've never tried it.
• 35:47
  Speaker 4: Yes, that's pretty well. How yeah, how we do how
• 35:51
  Speaker 4: to buy something? You want to try it type of thing.
• 35:54
  Speaker 2: It's amazing.
• 35:54
  Speaker 4: Yeah.
• 35:55
  Speaker 3: So we're now kind of insisting with customers for safety
• 36:00
  Speaker 3: we demonstrate full self drive because the numbers are uncomfortable
• 36:03
  Speaker 3: at scale that work with Now we're more or ten
• 36:07
  Speaker 3: billion miles driven that it's four times safer on full
• 36:13
  Speaker 3: self driving then they're not, so it's actually a big
• 36:18
  Speaker 3: improvement in safety. And so at this point we're just
• 36:23
  Speaker 3: insisting that we at least demonstrate self driving to customers
• 36:27
  Speaker 3: so they know how to use it and turn it
• 36:29
  Speaker 3: on for safety reasons, so.
• 36:32
  Speaker 1: It drives full self driving drives just like a person,
• 36:35
  Speaker 1: as opposed to having the code to look for every
• 36:39
  Speaker 1: circumstance that would happen and you had to you know,
• 36:43
  Speaker 1: this is a fire truck in front of us with
• 36:45
  Speaker 1: a bicycle attached to it, or someone walking his dog
• 36:48
  Speaker 1: while he's driving along. They have to identify everything with
• 36:51
  Speaker 1: a code. What AI does, what we do, as I
• 36:55
  Speaker 1: understand it, is to make sure that it's just like us.
• 37:00
  Speaker 2: The affairs.
• 37:02
  Speaker 3: Yes, the key to achieving pulls driving unsupervised full self
• 37:07
  Speaker 3: driving safe than the human is improving the AI software
• 37:10
  Speaker 3: in the car. We're confident that the a hardware that's
• 37:13
  Speaker 3: that's a trip that we designed currently made my sentence,
• 37:16
  Speaker 3: is capable of achieving a safety level unsupervised, meaning if
• 37:20
  Speaker 3: you're a sleep in the car at least two to
• 37:22
  Speaker 3: three times out of the average, right, maybe more, And
• 37:28
  Speaker 3: then with a I five we think achieve probably a
• 37:30
  Speaker 3: tanic improvement in safety.
• 37:33
  Speaker 4: So these are really big deals.
• 37:35
  Speaker 3: So, I mean, I think it's like it's a very
• 37:37
  Speaker 3: profound things that I'm saying here, and I really encourage
• 37:39
  Speaker 3: people to go out there and try it because of
• 37:41
  Speaker 3: self driving and see for yourself.
• 37:44
  Speaker 4: You can just go to any Taelis. They'll show to
• 37:46
  Speaker 4: you and it's not secret.
• 37:47
  Speaker 1: See everyone here. You're benefiting if you try this and
• 37:51
  Speaker 1: then buy it. But once you try it, you're going
• 37:53
  Speaker 1: to buy it. You should try it. And so I
• 37:57
  Speaker 1: want to close on what I mentioned this morning on
• 38:01
  Speaker 1: CNBC was that you're not doing this so you can
• 38:05
  Speaker 1: get enough money to buy a beach house.
• 38:08
  Speaker 2: You're doing You're doing this even mine.
• 38:12
  Speaker 4: Yeah that's right, but but but but you're doing.
• 38:15
  Speaker 1: This because you know, Harry Page was right, You're you're
• 38:20
  Speaker 1: a specious that you think humans should survive.
• 38:24
  Speaker 4: Yes, I'm a bachelor pro human.
• 38:29
  Speaker 1: I mean, so you're you're spending Actually, whether you're worth
• 38:34
  Speaker 1: another trillion dollars or four hundred bigs doesn't really matter.
• 38:37
  Speaker 2: What are you going to do with all this money
• 38:39
  Speaker 2: at the end?
• 38:39
  Speaker 3: What? What?
• 38:40
  Speaker 2: What's your plan? How do you want people to think
• 38:42
  Speaker 2: about you?
• 38:42
  Speaker 3: You know, mostly I need to have enough of ownership
• 38:44
  Speaker 3: with the companies to be able to continue to direct
• 38:46
  Speaker 3: their activities. But it's from a crystal consumption standpoint, I
• 38:50
  Speaker 3: don't actually do on any vacations, and I just sort of,
• 38:53
  Speaker 3: you know, medium sized house and and I actually a
• 38:56
  Speaker 3: tiny house.
• 38:56
  Speaker 4: At stall Base.
• 38:58
  Speaker 2: I've seen that house. It is tiny.
• 39:00
  Speaker 3: Yeah yeah, but actually people my friends might have come
• 39:04
  Speaker 3: to visit. Then they thought I was kidding. I'm like, no,
• 39:06
  Speaker 3: it's really about of eight thousand dollars. But I've done
• 39:09
  Speaker 3: a lot with the place.
• 39:10
  Speaker 1: Artificial turf in front a little white pitte of fans.
• 39:14
  Speaker 3: But like I said, with with A and robotics, there
• 39:16
  Speaker 3: will be abindance girl though people Actually, in fact, in
• 39:21
  Speaker 3: a benign scenario, it's gonna be interesting threshold that that
• 39:25
  Speaker 3: AI passes and the ancrobotics pass, where it's run out
• 39:28
  Speaker 3: of things to do for humans. Literally, it's it's completely
• 39:33
  Speaker 3: satiated all human ones. And then I guess you'll have
• 39:37
  Speaker 3: to start thinking about working for itself or I don't know. Overall,
• 39:40
  Speaker 3: want to take the set of actions that expand consciousness
• 39:44
  Speaker 3: into the future, so that the gopen Scala consciousness brokes tremendously,
• 39:50
  Speaker 3: and that we explore other star systems like in Star
• 39:53
  Speaker 3: Trek co places and we have gone before, and find
• 39:57
  Speaker 3: out if there are existing alien civilizations. For maybe there's
• 40:00
  Speaker 3: a long bit alien civilization, and we can look through
• 40:03
  Speaker 3: their understand what they were lying, and just generally understand
• 40:08
  Speaker 3: the universe.