Elon Musk: A future worth getting excited about | Tesla Texas Gigafactory interview | TED

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2022-04-18 ・ TED


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Elon Musk: A future worth getting excited about | Tesla Texas Gigafactory interview | TED

9,964,451 views ・ 2022-04-18

TED


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00:00
Chris Anderson: Elon Musk, great to see you.
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How are you?
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Elon Musk: Good. How are you?
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CA: We're here at the Texas Gigafactory the day before this thing opens.
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It's been pretty crazy out there.
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Thank you so much for making time on a busy day.
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I would love you to help us, kind of, cast our minds,
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I don't know, 10, 20, 30 years into the future.
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And help us try to picture what it would take
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to build a future that's worth getting excited about.
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The last time you spoke at TED,
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you said that that was really just a big driver.
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You know, you can talk about lots of other reasons to do the work you're doing,
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but fundamentally, you want to think about the future
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and not think that it sucks.
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EM: Yeah, absolutely.
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I think in general, you know,
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there's a lot of discussion of like, this problem or that problem.
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And a lot of people are sad about the future
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and they're ...
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Pessimistic.
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And I think ...
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this is ...
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This is not great.
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I mean, we really want to wake up in the morning
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and look forward to the future.
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We want to be excited about what's going to happen.
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And life cannot simply be about sort of,
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solving one miserable problem after another.
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CA: So if you look forward 30 years, you know, the year 2050
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has been labeled by scientists
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as this, kind of, almost like this doomsday deadline on climate.
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There's a consensus of scientists, a large consensus of scientists,
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who believe that if we haven't completely eliminated greenhouse gases
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or offset them completely by 2050,
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effectively we're inviting climate catastrophe.
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Do you believe there is a pathway to avoid that catastrophe?
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And what would it look like?
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EM: Yeah, so I am not one of the doomsday people,
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which may surprise you.
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I actually think we're on a good path.
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But at the same time,
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I want to caution against complacency.
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So, so long as we are not complacent,
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as long as we have a high sense of urgency
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about moving towards a sustainable energy economy,
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then I think things will be fine.
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So I can't emphasize that enough,
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as long as we push hard and are not complacent,
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the future is going to be great.
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Don't worry about it.
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I mean, worry about it,
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but if you worry about it, ironically, it will be a self-unfulfilling prophecy.
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So, like, there are three elements to a sustainable energy future.
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One is of sustainable energy generation, which is primarily wind and solar.
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There's also hydro, geothermal,
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I'm actually pro-nuclear.
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I think nuclear is fine.
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But it's going to be primarily solar and wind,
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as the primary generators of energy.
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The second part is you need batteries to store the solar and wind energy
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because the sun doesn't shine all the time,
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the wind doesn't blow all the time.
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So it's a lot of stationary battery packs.
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And then you need electric transport.
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So electric cars, electric planes, boats.
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And then ultimately,
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it’s not really possible to make electric rockets,
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but you can make the propellant used in rockets
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using sustainable energy.
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So ultimately, we can have a fully sustainable energy economy.
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And it's those three things:
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solar/wind, stationary battery pack, electric vehicles.
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So then what are the limiting factors on progress?
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The limiting factor really will be battery cell production.
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So that's going to really be the fundamental rate driver.
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And then whatever the slowest element
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of the whole lithium-ion battery cells supply chain,
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from mining and the many steps of refining
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to ultimately creating a battery cell
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and putting it into a pack,
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that will be the limiting factor on progress towards sustainability.
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CA: All right, so we need to talk more about batteries,
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because the key thing that I want to understand,
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like, there seems to be a scaling issue here
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that is kind of amazing and alarming.
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You have said that you have calculated
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that the amount of battery production that the world needs for sustainability
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is 300 terawatt hours of batteries.
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That's the end goal?
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EM: Very rough numbers,
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and I certainly would invite others to check our calculations
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because they may arrive at different conclusions.
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But in order to transition, not just current electricity production,
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but also heating and transport,
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which roughly triples the amount of electricity that you need,
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it amounts to approximately 300 terawatt hours of installed capacity.
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CA: So we need to give people a sense of how big a task that is.
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I mean, here we are at the Gigafactory.
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You know, this is one of the biggest buildings in the world.
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What I've read, and tell me if this is still right,
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is that the goal here is to eventually produce 100 gigawatt hours
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of batteries here a year eventually.
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EM: We will probably do more than that,
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but yes, hopefully we get there within a couple of years.
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CA: Right.
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But I mean, that is one --
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EM: 0.1 terrawat hours.
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CA: But that's still 1/100 of what's needed.
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How much of the rest of that 100 is Tesla planning to take on
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let's say, between now and 2030, 2040,
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when we really need to see the scale up happen?
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EM: I mean, these are just guesses.
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So please, people shouldn't hold me to these things.
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It's not like this is like some --
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What tends to happen is I'll make some like,
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you know, best guess
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and then people, in five years,
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there’ll be some jerk that writes an article:
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"Elon said this would happen, and it didn't happen.
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He's a liar and a fool."
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It's very annoying when that happens.
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So these are just guesses, this is a conversation.
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CA: Right.
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EM: I think Tesla probably ends up doing 10 percent of that.
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Roughly.
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CA: Let's say 2050
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we have this amazing, you know, 100 percent sustainable electric grid
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made up of, you know, some mixture of the sustainable energy sources
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you talked about.
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That same grid probably is offering the world
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really low-cost energy, isn't it,
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compared with now.
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And I'm curious about like,
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are people entitled to get a little bit excited
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about the possibilities of that world?
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EM: People should be optimistic about the future.
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Humanity will solve sustainable energy.
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It will happen if we, you know, continue to push hard,
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the future is bright and good from an energy standpoint.
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And then it will be possible to also use that energy to do carbon sequestration.
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It takes a lot of energy to pull carbon out of the atmosphere
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because in putting it in the atmosphere it releases energy.
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So now, you know, obviously in order to pull it out,
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you need to use a lot of energy.
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But if you've got a lot of sustainable energy from wind and solar,
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you can actually sequester carbon.
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So you can reverse the CO2 parts per million of the atmosphere and oceans.
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And also you can really have as much fresh water as you want.
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Earth is mostly water.
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We should call Earth “Water.”
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It's 70 percent water by surface area.
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Now most of that’s seawater,
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but it's like we just happen to be on the bit that's land.
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CA: And with energy, you can turn seawater into --
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EM: Yes.
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CA: Irrigating water or whatever water you need.
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EM: At very low cost.
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Things will be good.
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CA: Things will be good.
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And also, there's other benefits to this non-fossil fuel world
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where the air is cleaner --
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EM: Yes, exactly.
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Because, like, when you burn fossil fuels,
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there's all these side reactions
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and toxic gases of various kinds.
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And sort of little particulates that are bad for your lungs.
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Like, there's all sorts of bad things that are happening
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that will go away.
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And the sky will be cleaner and quieter.
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The future's going to be good.
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CA: I want us to switch now to think a bit about artificial intelligence.
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But the segue there,
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you mentioned how annoying it is when people call you up
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for bad predictions in the past.
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So I'm possibly going to be annoying now,
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but I’m curious about your timelines and how you predict
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and how come some things are so amazingly on the money and some aren't.
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So when it comes to predicting sales of Tesla vehicles, for example,
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you've kind of been amazing,
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I think in 2014 when Tesla had sold that year 60,000 cars,
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you said, "2020, I think we will do half a million a year."
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EM: Yeah, we did almost exactly a half million.
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CA: You did almost exactly half a million.
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You were scoffed in 2014 because no one since Henry Ford,
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with the Model T, had come close to that kind of growth rate for cars.
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You were scoffed, and you actually hit 500,000 cars
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and then 510,000 or whatever produced.
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But five years ago, last time you came to TED,
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I asked you about full self-driving,
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and you said, “Yeah, this very year,
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I'm confident that we will have a car going from LA to New York
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without any intervention."
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EM: Yeah, I don't want to blow your mind, but I'm not always right.
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CA: (Laughs)
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What's the difference between those two?
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Why has full self-driving in particular been so hard to predict?
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EM: I mean, the thing that really got me,
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and I think it's going to get a lot of other people,
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is that there are just so many false dawns with self-driving,
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where you think you've got the problem,
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have a handle on the problem,
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and then it, no, turns out you just hit a ceiling.
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Because if you were to plot the progress,
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the progress looks like a log curve.
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So it's like a series of log curves.
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So most people don't know what a log curve is, I suppose.
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CA: Show the shape with your hands.
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EM: It goes up you know, sort of a fairly straight way,
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and then it starts tailing off
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and you start getting diminishing returns.
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And you're like, uh oh,
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it was trending up and now it's sort of, curving over
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and you start getting to these, what I call local maxima,
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where you don't realize basically how dumb you were.
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And then it happens again.
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And ultimately...
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These things, you know, in retrospect, they seem obvious,
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but in order to solve full self-driving properly,
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you actually have to solve real-world AI.
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Because what are the road networks designed to work with?
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They're designed to work with a biological neural net, our brains,
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and with vision, our eyes.
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And so in order to make it work with computers,
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you basically need to solve real-world AI and vision.
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Because we need cameras
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and silicon neural nets
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in order to have self-driving work
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for a system that was designed for eyes and biological neural nets.
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You know, I guess when you put it that way,
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it's sort of, like, quite obvious
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that the only way to solve full self-driving
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is to solve real world AI and sophisticated vision.
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CA: What do you feel about the current architecture?
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Do you think you have an architecture now
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where there is a chance
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for the logarithmic curve not to tail off any anytime soon?
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EM: Well I mean, admittedly these may be infamous last words,
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but I actually am confident that we will solve it this year.
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That we will exceed --
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The probability of an accident,
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at what point do you exceed that of the average person?
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I think we will exceed that this year.
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CA: What are you seeing behind the scenes that gives you that confidence?
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EM: We’re almost at the point where we have a high-quality
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unified vector space.
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In the beginning, we were trying to do this with image recognition
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on individual images.
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But if you get one image out of a video,
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it's actually quite hard to see what's going on without ambiguity.
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But if you look at a video segment of a few seconds of video,
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that ambiguity resolves.
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So the first thing we had to do is tie all eight cameras together
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so they're synchronized,
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so that all the frames are looked at simultaneously
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and labeled simultaneously by one person,
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because we still need human labeling.
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So at least they’re not labeled at different times by different people
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in different ways.
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So it's sort of a surround picture.
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Then a very important part is to add the time dimension.
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So that you’re looking at surround video,
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and you're labeling surround video.
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And this is actually quite difficult to do from a software standpoint.
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We had to write our own labeling tools
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and then create auto labeling,
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create auto labeling software to amplify the efficiency of human labelers
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because it’s quite hard to label.
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In the beginning, it was taking several hours
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to label a 10-second video clip.
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This is not scalable.
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So basically what you have to have is you have to have surround video,
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and that surround video has to be primarily automatically labeled
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with humans just being editors
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and making slight corrections to the labeling of the video
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and then feeding back those corrections into the future auto labeler,
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so you get this flywheel eventually
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where the auto labeler is able to take in vast amounts of video
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and with high accuracy,
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automatically label the video for cars, lane lines, drive space.
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CA: What you’re saying is ...
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the result of this is that you're effectively giving the car a 3D model
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of the actual objects that are all around it.
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It knows what they are,
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and it knows how fast they are moving.
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And the remaining task is to predict
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what the quirky behaviors are that, you know,
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that when a pedestrian is walking down the road with a smaller pedestrian,
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that maybe that smaller pedestrian might do something unpredictable
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or things like that.
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You have to build into it before you can really call it safe.
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EM: You basically need to have memory across time and space.
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So what I mean by that is ...
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Memory can’t be infinite,
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because it's using up a lot of the computer's RAM basically.
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So you have to say how much are you going to try to remember?
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It's very common for things to be occluded.
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So if you talk about say, a pedestrian walking past a truck
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where you saw the pedestrian start on one side of the truck,
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then they're occluded by the truck.
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You would know intuitively,
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OK, that pedestrian is going to pop out the other side, most likely.
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CA: A computer doesn't know it.
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EM: You need to slow down.
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CA: A skeptic is going to say that every year for the last five years,
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you've kind of said, well,
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no this is the year,
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we're confident that it will be there in a year or two or, you know,
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like it's always been about that far away.
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But we've got a new architecture now,
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you're seeing enough improvement behind the scenes
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to make you not certain, but pretty confident,
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that, by the end of this year,
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what in most, not in every city, and every circumstance
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but in many cities and circumstances,
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basically the car will be able to drive without interventions
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safer than a human.
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EM: Yes.
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I mean, the car currently drives me around Austin
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most of the time with no interventions.
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So it's not like ...
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And we have over 100,000 people
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in our full self-driving beta program.
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So you can look at the videos that they post online.
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CA: I do.
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And some of them are great, and some of them are a little terrifying.
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I mean, occasionally the car seems to veer off
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and scare the hell out of people.
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EM: It’s still a beta.
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CA: But you’re behind the scenes, looking at the data,
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you're seeing enough improvement
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to believe that a this-year timeline is real.
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EM: Yes, that's what it seems like.
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I mean, we could be here talking again in a year,
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like, well, another year went by, and it didn’t happen.
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But I think this is the year.
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CA: And so in general, when people talk about Elon time,
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17:36
I mean it sounds like you can't just have a general rule
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17:39
that if you predict that something will be done in six months,
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actually what we should imagine is it’s going to be a year
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or it’s like two-x or three-x, it depends on the type of prediction.
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17:49
Some things, I guess, things involving software, AI, whatever,
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17:52
are fundamentally harder to predict than others.
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Is there an element
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that you actually deliberately make aggressive prediction timelines
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to drive people to be ambitious?
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Without that, nothing gets done?
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EM: Well, I generally believe, in terms of internal timelines,
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18:09
that we want to set the most aggressive timeline that we can.
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Because there’s sort of like a law of gaseous expansion where,
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18:17
for schedules, where whatever time you set,
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18:20
it's not going to be less than that.
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18:22
It's very rare that it'll be less than that.
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But as far as our predictions are concerned,
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18:28
what tends to happen in the media
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18:29
is that they will report all the wrong ones
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18:31
and ignore all the right ones.
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18:33
Or, you know, when writing an article about me --
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18:38
I've had a long career in multiple industries.
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18:40
If you list my sins, I sound like the worst person on Earth.
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18:43
But if you put those against the things I've done right,
360
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18:46
it makes much more sense, you know?
361
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18:48
So essentially like, the longer you do anything,
362
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2753
18:51
the more mistakes that you will make cumulatively.
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18:55
Which, if you sum up those mistakes,
364
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1793
18:56
will sound like I'm the worst predictor ever.
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19:00
But for example, for Tesla vehicle growth,
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3879
19:04
I said I think we’d do 50 percent, and we’ve done 80 percent.
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19:08
CA: Yes.
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19:10
EM: But they don't mention that one.
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19:12
So, I mean, I'm not sure what my exact track record is on predictions.
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3754
19:16
They're more optimistic than pessimistic, but they're not all optimistic.
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19:19
Some of them are exceeded probably more or later,
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19:24
but they do come true.
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19:28
It's very rare that they do not come true.
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19:31
It's sort of like, you know,
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3212
19:34
if there's some radical technology prediction,
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19:38
the point is not that it was a few years late,
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19:40
but that it happened at all.
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19:43
That's the more important part.
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19:45
CA: So it feels like at some point in the last year,
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19:49
seeing the progress on understanding,
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19:54
the Tesla AI understanding the world around it,
382
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19:57
led to a kind of, an aha moment at Tesla.
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20:00
Because you really surprised people recently when you said
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20:03
probably the most important product development
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20:06
going on at Tesla this year is this robot, Optimus.
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20:10
EM: Yes.
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20:11
CA: Many companies out there have tried to put out these robots,
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3211
20:14
they've been working on them for years.
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20:16
And so far no one has really cracked it.
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2294
20:18
There's no mass adoption robot in people's homes.
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3795
20:22
There are some in manufacturing, but I would say,
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3170
20:25
no one's kind of, really cracked it.
393
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2711
20:29
Is it something that happened
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1794
20:31
in the development of full self-driving that gave you the confidence to say,
395
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3587
20:35
"You know what, we could do something special here."
396
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2461
20:37
EM: Yeah, exactly.
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20:38
So, you know, it took me a while to sort of realize
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20:41
that in order to solve self-driving,
399
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2919
20:44
you really needed to solve real-world AI.
400
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2169
20:47
And at the point of which you solve real-world AI for a car,
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3045
20:50
which is really a robot on four wheels,
402
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2502
20:53
you can then generalize that to a robot on legs as well.
403
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4421
20:58
The two hard parts I think --
404
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1418
20:59
like obviously companies like Boston Dynamics
405
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2586
21:02
have shown that it's possible to make quite compelling,
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2878
21:05
sometimes alarming robots.
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1626
21:06
CA: Right.
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1210
21:08
EM: You know, so from a sensors and actuators standpoint,
409
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3295
21:11
it's certainly been demonstrated by many
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3253
21:14
that it's possible to make a humanoid robot.
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2086
21:16
The things that are currently missing are enough intelligence
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5547
21:22
for the robot to navigate the real world and do useful things
413
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3086
21:25
without being explicitly instructed.
414
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2252
21:27
So the missing things are basically real-world intelligence
415
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4129
21:31
and scaling up manufacturing.
416
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2503
21:34
Those are two things that Tesla is very good at.
417
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2419
21:37
And so then we basically just need to design the specialized actuators
418
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6006
21:43
and sensors that are needed for humanoid robot.
419
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2335
21:46
People have no idea, this is going to be bigger than the car.
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3045
21:50
CA: So let's dig into exactly that.
421
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1918
21:52
I mean, in one way, it's actually an easier problem than full self-driving
422
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3587
21:56
because instead of an object going along at 60 miles an hour,
423
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3795
22:00
which if it gets it wrong, someone will die.
424
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2544
22:02
This is an object that's engineered to only go at what,
425
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2586
22:05
three or four or five miles an hour.
426
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2002
22:07
And so a mistake, there aren't lives at stake.
427
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3003
22:10
There might be embarrassment at stake.
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1835
22:12
EM: So long as the AI doesn't take it over and murder us in our sleep or something.
429
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5130
22:17
CA: Right.
430
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1167
22:18
(Laughter)
431
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1168
22:20
So talk about --
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22:22
I think the first applications you've mentioned
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22:25
are probably going to be manufacturing,
434
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1919
22:27
but eventually the vision is to have these available for people at home.
435
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3462
22:30
If you had a robot that really understood the 3D architecture of your house
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6298
22:36
and knew where every object in that house was
437
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5005
22:41
or was supposed to be,
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1334
22:43
and could recognize all those objects,
439
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2837
22:46
I mean, that’s kind of amazing, isn’t it?
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2253
22:48
Like the kind of thing that you could ask a robot to do
441
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3295
22:51
would be what?
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1168
22:52
Like, tidy up?
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1209
22:54
EM: Yeah, absolutely.
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1460
22:57
Make dinner, I guess, mow the lawn.
445
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2252
22:59
CA: Take a cup of tea to grandma and show her family pictures.
446
1379416
4379
23:04
EM: Exactly. Take care of my grandmother and make sure --
447
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4296
23:08
CA: It could obviously recognize everyone in the home.
448
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2628
23:12
It could play catch with your kids.
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1877
23:13
EM: Yes. I mean, obviously, we need to be careful
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2294
23:16
this doesn't become a dystopian situation.
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2545
23:20
I think one of the things that's going to be important
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2544
23:23
is to have a localized ROM chip on the robot
453
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3504
23:26
that cannot be updated over the air.
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3045
23:29
Where if you, for example, were to say, “Stop, stop, stop,”
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2794
23:32
if anyone said that,
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1460
23:33
then the robot would stop, you know, type of thing.
457
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2419
23:36
And that's not updatable remotely.
458
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1960
23:38
I think it's going to be important to have safety features like that.
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3253
23:42
CA: Yeah, that sounds wise.
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1501
23:43
EM: And I do think there should be a regulatory agency for AI.
461
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2961
23:46
I've said that for many years.
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1460
23:48
I don't love being regulated,
463
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1418
23:49
but I think this is an important thing for public safety.
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2711
23:52
CA: Let's come back to that.
465
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1377
23:53
But I don't think many people have really sort of taken seriously
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4463
23:58
the notion of, you know, a robot at home.
467
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2752
24:00
I mean, at the start of the computing revolution,
468
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2294
24:03
Bill Gates said there's going to be a computer in every home.
469
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2878
24:06
And people at the time said, yeah, whatever, who would even want that.
470
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3295
24:09
Do you think there will be basically like in, say, 2050 or whatever,
471
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3670
24:13
like a robot in most homes, is what there will be,
472
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4170
24:17
and people will love them and count on them?
473
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2419
24:20
You’ll have your own butler basically.
474
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1836
24:22
EM: Yeah, you'll have your sort of buddy robot probably, yeah.
475
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3920
24:27
CA: I mean, how much of a buddy?
476
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1585
24:28
How many applications have you thought,
477
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2627
24:31
you know, can you have a romantic partner, a sex partner?
478
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2836
24:34
EM: It's probably inevitable.
479
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2127
24:36
I mean, I did promise the internet that I’d make catgirls.
480
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2794
24:39
We could make a robot catgirl.
481
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2044
24:42
CA: Be careful what you promise the internet.
482
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2168
24:44
(Laughter)
483
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2253
24:47
EM: So, yeah, I guess it'll be whatever people want really, you know.
484
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4963
24:52
CA: What sort of timeline should we be thinking about
485
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3670
24:56
of the first models that are actually made and sold?
486
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3837
25:01
EM: Well, you know, the first units that we intend to make
487
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3712
25:05
are for jobs that are dangerous, boring, repetitive,
488
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4629
25:10
and things that people don't want to do.
489
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1919
25:11
And, you know, I think we’ll have like an interesting prototype
490
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3044
25:15
sometime this year.
491
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1210
25:16
We might have something useful next year,
492
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2627
25:18
but I think quite likely within at least two years.
493
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2836
25:22
And then we'll see rapid growth year over year
494
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2169
25:24
of the usefulness of the humanoid robots
495
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2544
25:27
and decrease in cost and scaling up production.
496
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2711
25:29
CA: Initially just selling to businesses,
497
1529857
1961
25:31
or when do you picture you'll start selling them
498
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2670
25:34
where you can buy your parents one for Christmas or something?
499
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4295
25:39
EM: I'd say in less than ten years.
500
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1710
25:41
CA: Help me on the economics of this.
501
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2837
25:43
So what do you picture the cost of one of these being?
502
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3211
25:47
EM: Well, I think the cost is actually not going to be crazy high.
503
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3295
25:51
Like less than a car.
504
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1251
25:53
Initially, things will be expensive because it'll be a new technology
505
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3254
25:56
at low production volume.
506
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1210
25:57
The complexity and cost of a car is greater than that of a humanoid robot.
507
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3670
26:01
So I would expect that it's going to be less than a car,
508
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4212
26:05
or at least equivalent to a cheap car.
509
1565935
1835
26:07
CA: So even if it starts at 50k, within a few years,
510
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2461
26:10
it’s down to 20k or lower or whatever.
511
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2336
26:13
And maybe for home they'll get much cheaper still.
512
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2335
26:15
But think about the economics of this.
513
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1877
26:17
If you can replace a $30,000,
514
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4254
26:22
$40,000-a-year worker,
515
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2795
26:24
which you have to pay every year,
516
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1669
26:26
with a one-time payment of $25,000
517
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3044
26:29
for a robot that can work longer hours,
518
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2920
26:32
a pretty rapid replacement of certain types of jobs.
519
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4004
26:36
How worried should the world be about that?
520
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2211
26:39
EM: I wouldn't worry about the sort of, putting people out of a job thing.
521
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3503
26:42
I think we're actually going to have, and already do have,
522
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3336
26:46
a massive shortage of labor.
523
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1377
26:47
So I think we will have ...
524
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2919
26:54
Not people out of work,
525
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1209
26:55
but actually still a shortage labor even in the future.
526
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2836
26:58
But this really will be a world of abundance.
527
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4630
27:03
Any goods and services will be available to anyone who wants them.
528
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4964
27:08
It'll be so cheap to have goods and services, it will be ridiculous.
529
1628790
3211
27:12
CA: I'm presuming it should be possible to imagine a bunch of goods and services
530
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4046
27:16
that can't profitably be made now but could be made in that world,
531
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4421
27:20
courtesy of legions of robots.
532
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2628
27:23
EM: Yeah.
533
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1460
27:25
It will be a world of abundance.
534
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1794
27:26
The only scarcity that will exist in the future
535
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2502
27:29
is that which we decide to create ourselves as humans.
536
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3170
27:32
CA: OK.
537
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1168
27:33
So AI is allowing us to imagine a differently powered economy
538
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4338
27:38
that will create this abundance.
539
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2127
27:40
What are you most worried about going wrong?
540
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2086
27:42
EM: Well, like I said, AI and robotics will bring out
541
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6006
27:48
what might be termed the age of abundance.
542
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2544
27:51
Other people have used this word,
543
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1960
27:54
and that this is my prediction:
544
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1668
27:55
it will be an age of abundance for everyone.
545
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3212
27:59
But I guess there’s ...
546
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2544
28:03
The dangers would be the artificial general intelligence
547
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4547
28:08
or digital superintelligence decouples from a collective human will
548
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5256
28:13
and goes in the direction that for some reason we don't like.
549
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3504
28:17
Whatever direction it might go.
550
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2128
28:20
You know, that’s sort of the idea behind Neuralink,
551
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3420
28:24
is to try to more tightly couple collective human world
552
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3045
28:27
to digital superintelligence.
553
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4463
28:33
And also along the way solve a lot of brain injuries and spinal injuries
554
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5755
28:39
and that kind of thing.
555
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1168
28:40
So even if it doesn't succeed in the greater goal,
556
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2336
28:42
I think it will succeed in the goal of alleviating brain and spine damage.
557
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5588
28:48
CA: So the spirit there is that if we're going to make these AIs
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28:51
that are so vastly intelligent, we ought to be wired directly to them
559
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3253
28:54
so that we ourselves can have those superpowers more directly.
560
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4421
28:59
But that doesn't seem to avoid the risk that those superpowers might ...
561
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4421
29:05
turn ugly in unintended ways.
562
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2586
29:08
EM: I think it's a risk, I agree.
563
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1626
29:09
I'm not saying that I have some certain answer to that risk.
564
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6256
29:16
I’m just saying like
565
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2294
29:18
maybe one of the things that would be good
566
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3545
29:22
for ensuring that the future is one that we want
567
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5672
29:27
is to more tightly couple
568
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3253
29:31
the collective human world to digital intelligence.
569
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3754
29:36
The issue that we face here is that we are already a cyborg,
570
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4129
29:40
if you think about it.
571
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1252
29:41
The computers are an extension of ourselves.
572
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3963
29:46
And when we die, we have, like, a digital ghost.
573
1786697
3003
29:49
You know, all of our text messages and social media, emails.
574
1789742
3545
29:53
And it's quite eerie actually,
575
1793329
2002
29:55
when someone dies but everything online is still there.
576
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3295
29:59
But you say like, what's the limitation?
577
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1919
30:00
What is it that inhibits a human-machine symbiosis?
578
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5171
30:06
It's the data rate.
579
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1210
30:07
When you communicate, especially with a phone,
580
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2169
30:09
you're moving your thumbs very slowly.
581
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2919
30:12
So you're like moving your two little meat sticks
582
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2878
30:15
at a rate that’s maybe 10 bits per second, optimistically, 100 bits per second.
583
1815393
5922
30:21
And computers are communicating at the gigabyte level and beyond.
584
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5130
30:26
CA: Have you seen evidence that the technology is actually working,
585
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3170
30:29
that you've got a richer, sort of, higher bandwidth connection, if you like,
586
1829657
3587
30:33
between like external electronics and a brain
587
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2836
30:36
than has been possible before?
588
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1668
30:38
EM: Yeah.
589
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1210
30:41
I mean, the fundamental principles of reading neurons,
590
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5422
30:46
sort of doing read-write on neurons with tiny electrodes,
591
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3921
30:50
have been demonstrated for decades.
592
1850386
2169
30:53
So it's not like the concept is new.
593
1853306
4254
30:57
The problem is that there is no product that works well
594
1857602
4754
31:02
that you can go and buy.
595
1862398
2503
31:04
So it's all sort of, in research labs.
596
1864942
2586
31:08
And it's like some cords sticking out of your head.
597
1868738
5672
31:14
And it's quite gruesome, and it's really ...
598
1874410
3253
31:18
There's no good product that actually does a good job
599
1878539
4088
31:22
and is high-bandwidth and safe
600
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1876
31:24
and something actually that you could buy and would want to buy.
601
1884545
3253
31:29
But the way to think of the Neuralink device
602
1889550
3921
31:33
is kind of like a Fitbit or an Apple Watch.
603
1893512
3546
31:37
That's where we take out sort of a small section of skull
604
1897934
4713
31:42
about the size of a quarter,
605
1902647
1584
31:44
replace that with what,
606
1904273
2252
31:46
in many ways really is very much like a Fitbit, Apple Watch
607
1906525
5673
31:52
or some kind of smart watch thing.
608
1912239
2378
31:56
But with tiny, tiny wires,
609
1916035
4171
32:00
very, very tiny wires.
610
1920247
1877
32:02
Wires so tiny, it’s hard to even see them.
611
1922124
2044
32:05
And it's very important to have very tiny wires
612
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2210
32:07
so that when they’re implanted, they don’t damage the brain.
613
1927296
2836
32:10
CA: How far are you from putting these into humans?
614
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2878
32:14
EM: Well, we have put in our FDA application
615
1934136
4463
32:18
to aspirationally do the first human implant this year.
616
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4296
32:23
CA: The first uses will be for neurological injuries
617
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3545
32:26
of different kinds.
618
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1293
32:28
But rolling the clock forward
619
1948192
1543
32:29
and imagining when people are actually using these
620
1949777
4046
32:33
for their own enhancement, let's say,
621
1953864
2628
32:36
and for the enhancement of the world,
622
1956534
1877
32:38
how clear are you in your mind
623
1958452
1460
32:39
as to what it will feel like to have one of these inside your head?
624
1959912
5339
32:45
EM: Well, I do want to emphasize we're at an early stage.
625
1965251
3920
32:49
And so it really will be many years before we have
626
1969171
6048
32:55
anything approximating a high-bandwidth neural interface
627
1975261
6673
33:01
that allows for AI-human symbiosis.
628
1981934
3670
33:07
For many years, we will just be solving brain injuries and spinal injuries.
629
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4255
33:11
For probably a decade.
630
1991777
2169
33:14
This is not something that will suddenly one day
631
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3504
33:18
it will have this incredible sort of whole brain interface.
632
1998451
4713
33:25
It's going to be, like I said,
633
2005041
1501
33:26
at least a decade of really just solving brain injuries
634
2006542
3921
33:30
and spinal injuries.
635
2010504
2127
33:32
And really, I think you can solve a very wide range of brain injuries,
636
2012631
3754
33:36
including severe depression, morbid obesity, sleep,
637
2016385
6799
33:43
potentially schizophrenia,
638
2023225
1252
33:44
like, a lot of things that cause great stress to people.
639
2024518
3712
33:48
Restoring memory in older people.
640
2028773
3003
33:51
CA: If you can pull that off, that's the app I will sign up for.
641
2031817
3796
33:56
EM: Absolutely.
642
2036363
1293
33:57
CA: Please hurry. (Laughs)
643
2037698
2169
33:59
EM: I mean, the emails that we get at Neuralink are heartbreaking.
644
2039867
4880
34:05
I mean, they'll send us just tragic, you know,
645
2045122
4088
34:09
where someone was sort of, in the prime of life
646
2049251
2336
34:11
and they had an accident on a motorcycle
647
2051629
3795
34:15
and someone who's 25, you know, can't even feed themselves.
648
2055466
5797
34:21
And this is something we could fix.
649
2061263
2378
34:24
CA: But you have said that AI is one of the things you're most worried about
650
2064391
3587
34:28
and that Neuralink may be one of the ways
651
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2878
34:30
where we can keep abreast of it.
652
2070940
3837
34:35
EM: Yeah, there's the short-term thing,
653
2075528
3545
34:39
which I think is helpful on an individual human level with injuries.
654
2079115
3920
34:43
And then the long-term thing is an attempt
655
2083077
2544
34:45
to address the civilizational risk of AI
656
2085663
6006
34:51
by bringing digital intelligence
657
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3921
34:55
and biological intelligence closer together.
658
2095673
2669
34:58
I mean, if you think of how the brain works today,
659
2098384
2377
35:00
there are really two layers to the brain.
660
2100803
2002
35:02
There's the limbic system and the cortex.
661
2102847
1960
35:04
You've got the kind of, animal brain where --
662
2104849
2127
35:06
it’s kind of like the fun part, really.
663
2106976
1877
35:08
CA: It's where most of Twitter operates, by the way.
664
2108853
2502
35:11
EM: I think Tim Urban said,
665
2111355
1710
35:13
we’re like somebody, you know, stuck a computer on a monkey.
666
2113107
4463
35:18
You know, so we're like, if you gave a monkey a computer,
667
2118320
3587
35:21
that's our cortex.
668
2121949
1210
35:23
But we still have a lot of monkey instincts.
669
2123159
2168
35:25
Which we then try to rationalize as, no, it's not a monkey instinct.
670
2125369
3754
35:29
It’s something more important than that.
671
2129165
1918
35:31
But it's often just really a monkey instinct.
672
2131083
2127
35:33
We're just monkeys with a computer stuck in our brain.
673
2133252
3378
35:38
But even though the cortex is sort of the smart,
674
2138883
2919
35:41
or the intelligent part of the brain,
675
2141844
1793
35:43
the thinking part of the brain,
676
2143679
2419
35:46
I've not yet met anyone who wants to delete their limbic system
677
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3712
35:49
or their cortex.
678
2149852
1168
35:51
They're quite happy having both.
679
2151020
1543
35:52
Everyone wants both parts of their brain.
680
2152605
2002
35:56
And people really want their phones and their computers,
681
2156025
2669
35:58
which are really the tertiary, the third part of your intelligence.
682
2158736
3503
36:02
It's just that it's ...
683
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1627
36:03
Like the bandwidth,
684
2163908
2294
36:06
the rate of communication with that tertiary layer is slow.
685
2166202
4629
36:11
And it's just a very tiny straw to this tertiary layer.
686
2171665
3796
36:15
And we want to make that tiny straw a big highway.
687
2175502
2753
36:19
And I’m definitely not saying that this is going to solve everything.
688
2179298
3545
36:22
Or this is you know, it’s the only thing --
689
2182885
3503
36:26
it’s something that might be helpful.
690
2186430
3754
36:30
And worst-case scenario,
691
2190517
1711
36:32
I think we solve some important brain injury,
692
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3503
36:35
spinal injury issues, and that's still a great outcome.
693
2195773
2586
36:38
CA: Best-case scenario,
694
2198359
1167
36:39
we may discover new human possibility, telepathy,
695
2199568
2419
36:42
you've spoken of, in a way, a connection with a loved one, you know,
696
2202029
4671
36:46
full memory and much faster thought processing maybe.
697
2206742
5005
36:51
All these things.
698
2211747
1335
36:53
It's very cool.
699
2213540
1210
36:55
If AI were to take down Earth, we need a plan B.
700
2215542
5423
37:01
Let's shift our attention to space.
701
2221006
3545
37:04
We spoke last time at TED about reusability,
702
2224593
2086
37:06
and you had just demonstrated that spectacularly for the first time.
703
2226720
3212
37:09
Since then, you've gone on to build this monster rocket, Starship,
704
2229974
5922
37:15
which kind of changes the rules of the game in spectacular ways.
705
2235938
4046
37:20
Tell us about Starship.
706
2240025
1543
37:22
EM: Starship is extremely fundamental.
707
2242486
1877
37:24
So the holy grail of rocketry or space transport
708
2244405
5839
37:30
is full and rapid reusability.
709
2250286
1793
37:32
This has never been achieved.
710
2252121
1418
37:33
The closest that anything has come is our Falcon 9 rocket,
711
2253580
3337
37:36
where we are able to recover the first stage, the boost stage,
712
2256959
5213
37:42
which is probably about 60 percent of the cost of the vehicle
713
2262214
4630
37:46
of the whole launch, maybe 70 percent.
714
2266885
2920
37:50
And we've now done that over a hundred times.
715
2270347
3170
37:53
So with Starship, we will be recovering the entire thing.
716
2273517
6131
37:59
Or at least that's the goal.
717
2279690
1543
38:01
CA: Right.
718
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1209
38:02
EM: And moreover, recovering it in such a way
719
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3128
38:05
that it can be immediately re-flown.
720
2285696
2628
38:08
Whereas with Falcon 9, we still need to do some amount of refurbishment
721
2288365
3462
38:11
to the booster and to the fairing nose cone.
722
2291869
2919
38:16
But with Starship, the design goal is immediate re-flight.
723
2296790
4880
38:22
So you just refill propellants and go again.
724
2302212
3671
38:28
And this is gigantic.
725
2308302
2335
38:30
Just as it would be in any other mode of transport.
726
2310679
2878
38:33
CA: And the main design
727
2313557
1752
38:35
is to basically take 100 plus people at a time,
728
2315351
6006
38:41
plus a bunch of things that they need, to Mars.
729
2321357
3837
38:45
So, first of all, talk about that piece.
730
2325611
1960
38:47
What is your latest timeline?
731
2327613
3462
38:51
One, for the first time, a Starship goes to Mars,
732
2331116
3379
38:54
presumably without people, but just equipment.
733
2334536
2211
38:57
Two, with people.
734
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1877
38:59
Three, there’s sort of,
735
2339041
2252
39:01
OK, 100 people at a time, let's go.
736
2341335
2711
39:04
EM: Sure.
737
2344546
1126
39:05
And just to put the cost thing into perspective,
738
2345714
3796
39:09
the expected cost of Starship,
739
2349510
4754
39:14
putting 100 tons into orbit,
740
2354306
2002
39:16
is significantly less than what it would have cost
741
2356350
4880
39:21
or what it did cost to put our tiny Falcon 1 rocket into orbit.
742
2361271
4505
39:27
Just as the cost of flying a 747 around the world
743
2367611
4671
39:32
is less than the cost of a small airplane.
744
2372282
2419
39:35
You know, a small airplane that was thrown away.
745
2375244
2586
39:37
So it's really pretty mind-boggling that the giant thing costs less,
746
2377871
6048
39:43
way less than the small thing.
747
2383961
1460
39:45
So it doesn't use exotic propellants
748
2385421
4587
39:50
or things that are difficult to obtain on Mars.
749
2390050
2461
39:52
It uses methane as fuel,
750
2392928
3962
39:56
and it's primarily oxygen, roughly 77-78 percent oxygen by weight.
751
2396890
5798
40:03
And Mars has a CO2 atmosphere and has water ice,
752
2403313
3587
40:06
which is CO2 plus H2O, so you can make CH4, methane,
753
2406942
3378
40:10
and O2, oxygen, on Mars.
754
2410362
1794
40:12
CA: Presumably, one of the first tasks on Mars will be to create a fuel plant
755
2412197
3963
40:16
that can create the fuel for the return trips of many Starships.
756
2416201
4255
40:20
EM: Yes.
757
2420497
1168
40:21
And actually, it's mostly going to be oxygen plants,
758
2421665
2920
40:24
because it's 78 percent oxygen, 22 percent fuel.
759
2424626
5965
40:31
But the fuel is a simple fuel that is easy to create on Mars.
760
2431300
3712
40:35
And in many other parts of the solar system.
761
2435512
2586
40:38
So basically ...
762
2438098
1293
40:39
And it's all propulsive landing, no parachutes,
763
2439933
3796
40:43
nothing thrown away.
764
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1460
40:46
It has a heat shield that’s capable of entering on Earth or Mars.
765
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6632
40:53
We can even potentially go to Venus.
766
2453530
1752
40:55
but you don't want to go there.
767
2455324
1501
40:56
(Laughs)
768
2456867
1543
40:59
Venus is hell, almost literally.
769
2459161
2210
41:02
But you could ...
770
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1460
41:04
It's a generalized method of transport to anywhere in the solar system,
771
2464041
4838
41:08
because the point at which you have propellant depo on Mars,
772
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2836
41:11
you can then travel to the asteroid belt
773
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1919
41:13
and to the moons of Jupiter and Saturn
774
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3128
41:16
and ultimately anywhere in the solar system.
775
2476887
2919
41:19
CA: But your main focus
776
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2753
41:22
and SpaceX's main focus is still Mars.
777
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3670
41:26
That is the mission.
778
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2211
41:28
That is where most of the effort will go?
779
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3920
41:33
Or are you actually imagining a much broader array of uses
780
2493278
4672
41:37
even in the coming, you know,
781
2497991
2628
41:40
the first decade or so of uses of this.
782
2500619
3253
41:44
Where we could go, for example, to other places
783
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2252
41:46
in the solar system to explore,
784
2506750
1919
41:48
perhaps NASA wants to use the rocket for that reason.
785
2508710
4338
41:53
EM: Yeah, NASA is planning to use a Starship to return to the moon,
786
2513423
5131
41:58
to return people to the moon.
787
2518595
1794
42:01
And so we're very honored that NASA has chosen us to do this.
788
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4422
42:07
But I'm saying it is a generalized --
789
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4337
42:11
it’s a general solution
790
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2377
42:14
to getting anywhere in the greater solar system.
791
2534027
5172
42:19
It's not suitable for going to another star system,
792
2539241
2502
42:21
but it is a general solution for transport anywhere in the solar system.
793
2541785
3879
42:25
CA: Before it can do any of that,
794
2545706
1585
42:27
it's got to demonstrate it can get into orbit, you know, around Earth.
795
2547332
3295
42:30
What’s your latest advice on the timeline for that?
796
2550627
5005
42:35
EM: It's looking promising for us to have an orbital launch attempt
797
2555632
3921
42:39
in a few months.
798
2559595
2002
42:43
So we're actually integrating --
799
2563015
3545
42:46
will be integrating the engines into the booster
800
2566602
2961
42:49
for the first orbital flight starting in about a week or two.
801
2569605
3586
42:53
And the launch complex itself is ready to go.
802
2573942
6465
43:00
So assuming we get regulatory approval,
803
2580741
3670
43:04
I think we could have an orbital launch attempt within a few months.
804
2584453
6464
43:10
CA: And a radical new technology like this
805
2590959
2002
43:13
presumably there is real risk on those early attempts.
806
2593003
2544
43:15
EM: Oh, 100 percent, yeah.
807
2595589
1251
43:16
The joke I make all the time is that excitement is guaranteed.
808
2596882
3837
43:20
Success is not guaranteed, but excitement certainly is.
809
2600719
2794
43:23
CA: But the last I saw on your timeline,
810
2603513
2378
43:25
you've slightly put back the expected date
811
2605932
2962
43:28
to put the first human on Mars till 2029, I want to say?
812
2608935
4380
43:33
EM: Yeah, I mean, so let's see.
813
2613815
3128
43:36
I mean, we have built a production system for Starship,
814
2616985
3504
43:40
so we're making a lot of ships and boosters.
815
2620489
3295
43:43
CA: How many are you planning to make actually?
816
2623784
2210
43:46
EM: Well, we're currently expecting to make a booster and a ship
817
2626036
5714
43:51
roughly every, well, initially, roughly every couple of months,
818
2631792
3503
43:55
and then hopefully by the end of this year, one every month.
819
2635295
3670
43:59
So it's giant rockets, and a lot of them.
820
2639007
2711
44:01
Just talking in terms of rough orders of magnitude,
821
2641760
2419
44:04
in order to create a self-sustaining city on Mars,
822
2644179
3504
44:07
I think you will need something on the order of a thousand ships.
823
2647724
4421
44:12
And we just need a Helen of Sparta, I guess, on Mars.
824
2652187
6381
44:19
CA: This is not in most people's heads, Elon.
825
2659319
2211
44:21
EM: The planet that launched 1,000 ships.
826
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1961
44:24
CA: That's nice.
827
2664574
1168
44:25
But this is not in most people's heads,
828
2665784
1877
44:27
this picture that you have in your mind.
829
2667661
1918
44:29
There's basically a two-year window,
830
2669621
1752
44:31
you can only really fly to Mars conveniently every two years.
831
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2919
44:34
You were picturing that during the 2030s,
832
2674292
4797
44:39
every couple of years,
833
2679089
1376
44:40
something like 1,000 Starships take off,
834
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3003
44:43
each containing 100 or more people.
835
2683552
1960
44:45
That picture is just completely mind-blowing to me.
836
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5464
44:51
That sense of this armada of humans going to --
837
2691393
3378
44:54
EM: It'll be like "Battlestar Galactica," the fleet departs.
838
2694813
2878
44:57
CA: And you think that it can basically be funded by people
839
2697691
2794
45:00
spending maybe a couple hundred grand on a ticket to Mars?
840
2700485
3254
45:03
Is that price about where it has been?
841
2703739
2752
45:07
EM: Well, I think if you say like,
842
2707367
1627
45:08
what's required in order to get enough people and enough cargo to Mars
843
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4755
45:13
to build a self-sustaining city.
844
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2586
45:17
And it's where you have an intersection
845
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1919
45:19
of sets of people who want to go,
846
2719296
2669
45:21
because I think only a small percentage of humanity will want to go,
847
2721965
5047
45:27
and can afford to go or get sponsorship in some manner.
848
2727012
3754
45:31
That intersection of sets, I think,
849
2731391
1710
45:33
needs to be a million people or something like that.
850
2733101
2461
45:36
And so it’s what can a million people afford, or get sponsorship for,
851
2736646
3754
45:40
because I think governments will also pay for it,
852
2740442
2377
45:42
and people can take out loans.
853
2742819
3003
45:45
But I think at the point at which you say, OK, like,
854
2745864
3712
45:49
if moving to Mars costs are, for argument’s sake, $100,000,
855
2749618
6381
45:56
then I think you know, almost anyone can work and save up
856
2756041
5172
46:01
and eventually have $100,000 and be able to go to Mars if they want.
857
2761213
4045
46:05
We want to make it available to anyone who wants to go.
858
2765300
2669
46:10
It's very important to emphasize that Mars, especially in the beginning,
859
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4171
46:14
will not be luxurious.
860
2774434
1293
46:15
It will be dangerous, cramped, difficult, hard work.
861
2775727
5672
46:22
It's kind of like that Shackleton ad for going to the Antarctic,
862
2782025
3170
46:25
which I think is actually not real, but it sounds real and it's cool.
863
2785237
3336
46:28
It's sort of like, the sales pitch for going to Mars is,
864
2788865
2878
46:31
"It's dangerous, it's cramped.
865
2791785
2878
46:35
You might not make it back.
866
2795956
1501
46:38
It's difficult, it's hard work."
867
2798750
1543
46:40
That's the sales pitch.
868
2800293
1168
46:41
CA: Right.
869
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1168
46:42
But you will make history.
870
2802712
1252
46:44
EM: But it'll be glorious.
871
2804756
1585
46:47
CA: So on that kind of launch rate you're talking about over two decades,
872
2807050
3462
46:50
you could get your million people to Mars, essentially.
873
2810554
3628
46:54
Whose city is it?
874
2814224
1126
46:55
Is it NASA's city, is it SpaceX's city?
875
2815392
1918
46:57
EM: It’s the people of Mars’ city.
876
2817352
1627
47:01
The reason for this, I mean, I feel like why do this thing?
877
2821106
4629
47:05
I think this is important for maximizing
878
2825735
4338
47:10
the probable lifespan of humanity or consciousness.
879
2830115
3044
47:13
Human civilization could come to an end for external reasons,
880
2833201
4004
47:17
like a giant meteor or super volcanoes or extreme climate change.
881
2837247
5172
47:24
Or World War III, or you know, any one of a number of reasons.
882
2844045
5756
47:32
But the probable life span of civilizational consciousness
883
2852929
2878
47:35
as we know it,
884
2855849
1585
47:37
which we should really view as this very delicate thing,
885
2857475
3129
47:40
like a small candle in a vast darkness.
886
2860645
2711
47:43
That is what appears to be the case.
887
2863356
2962
47:47
We're in this vast darkness of space,
888
2867777
3379
47:51
and there's this little candle of consciousness
889
2871197
3421
47:54
that’s only really come about after 4.5 billion years,
890
2874659
4463
47:59
and it could just go out.
891
2879164
2002
48:01
CA: I think that's powerful,
892
2881166
1376
48:02
and I think a lot of people will be inspired by that vision.
893
2882584
2836
48:05
And the reason you need the million people
894
2885420
2127
48:07
is because there has to be enough people there
895
2887547
2169
48:09
to do everything that you need to survive.
896
2889758
2419
48:13
EM: Really, like the critical threshold is if the ships from Earth stop coming
897
2893136
6840
48:20
for any reason,
898
2900018
2544
48:22
does the Mars City die out or not?
899
2902604
4379
48:27
And so we have to --
900
2907400
2086
48:29
You know, people talk about like, the sort of, the great filters,
901
2909527
3129
48:32
the things that perhaps, you know,
902
2912697
3087
48:35
we talk about the Fermi paradox, and where are the aliens?
903
2915825
2711
48:38
Well maybe there are these various great filters
904
2918536
2294
48:40
that the aliens didn’t pass,
905
2920872
1418
48:42
and so they eventually just ceased to exist.
906
2922290
4588
48:46
And one of the great filters is becoming a multi-planet species.
907
2926920
3128
48:50
So we want to pass that filter.
908
2930674
2210
48:54
And I'll be long-dead before this is, you know, a real thing,
909
2934302
6006
49:00
before it happens.
910
2940350
1251
49:01
But I’d like to at least see us make great progress in this direction.
911
2941601
5297
49:07
CA: Given how tortured the Earth is right now,
912
2947315
2503
49:09
how much we're beating each other up,
913
2949859
2878
49:12
shouldn't there be discussions going on
914
2952737
2795
49:15
with everyone who is dreaming about Mars to try to say,
915
2955573
4171
49:19
we've got a once in a civilization's chance
916
2959786
5172
49:24
to make some new rules here?
917
2964958
2002
49:27
Should someone be trying to lead those discussions
918
2967002
3753
49:30
to figure out what it means for this to be the people of Mars' City?
919
2970755
3879
49:35
EM: Well, I think ultimately
920
2975093
1376
49:36
this will be up to the people of Mars to decide
921
2976469
2211
49:38
how they want to rethink society.
922
2978722
4045
49:43
Yeah there’s certainly risk there.
923
2983101
1627
49:45
And hopefully the people of Mars will be more enlightened
924
2985395
4630
49:50
and will not fight amongst each other too much.
925
2990066
2711
49:54
I mean, I have some recommendations,
926
2994279
1752
49:56
which people of Mars may choose to listen to or not.
927
2996031
3962
50:00
I would advocate for more of a direct democracy,
928
3000035
2794
50:02
not a representative democracy,
929
3002829
2211
50:05
and laws that are short enough for people to understand.
930
3005040
2711
50:08
Where it is harder to create laws than to get rid of them.
931
3008168
5380
50:14
CA: Coming back a bit nearer term,
932
3014424
1668
50:16
I'd love you to just talk a bit about some of the other possibility space
933
3016134
3462
50:19
that Starship seems to have created.
934
3019596
3712
50:23
So given --
935
3023349
1377
50:24
Suddenly we've got this ability to move 100 tons-plus into orbit.
936
3024768
3503
50:29
So we've just launched the James Webb telescope,
937
3029230
3170
50:32
which is an incredible thing.
938
3032400
2002
50:34
It's unbelievable.
939
3034444
1126
50:35
EM: Exquisite piece of technology.
940
3035612
1793
50:37
CA: Exquisite piece of technology.
941
3037447
1627
50:39
But people spent two years trying to figure out how to fold up this thing.
942
3039115
3504
50:42
It's a three-ton telescope.
943
3042660
1335
50:44
EM: We can make it a lot easier if you’ve got more volume and mass.
944
3044037
3170
50:47
CA: But let's ask a different question.
945
3047207
1877
50:49
Which is, how much more powerful a telescope could someone design
946
3049084
6756
50:55
based on using Starship, for example?
947
3055882
2878
50:59
EM: I mean, roughly, I'd say it's probably an order of magnitude more resolution.
948
3059469
4546
51:04
If you've got 100 tons and a thousand cubic meters volume,
949
3064057
3211
51:07
which is roughly what we have.
950
3067268
1585
51:08
CA: And what about other exploration through the solar system?
951
3068895
3545
51:12
I mean, I'm you know --
952
3072482
2169
51:14
EM: Europa is a big question mark.
953
3074692
2670
51:17
CA: Right, so there's an ocean there.
954
3077403
1794
51:19
And what you really want to do is to drop a submarine into that ocean.
955
3079239
3295
51:22
EM: Maybe there's like, some squid civilization,
956
3082534
2294
51:24
cephalopod civilization under the ice of Europa.
957
3084869
3212
51:28
That would be pretty interesting.
958
3088123
1626
51:29
CA: I mean, Elon, if you could take a submarine to Europa
959
3089749
2711
51:32
and we see pictures of this thing being devoured by a squid,
960
3092460
3629
51:36
that would honestly be the happiest moment of my life.
961
3096131
2544
51:38
EM: Pretty wild, yeah.
962
3098716
1377
51:40
CA: What other possibilities are out there?
963
3100426
2795
51:43
Like, it feels like if you're going to create a thousand of these things,
964
3103263
4379
51:47
they can only fly to Mars every two years.
965
3107642
3212
51:50
What are they doing the rest of the time?
966
3110895
2169
51:53
It feels like there's this explosion of possibility
967
3113106
4671
51:57
that I don't think people are really thinking about.
968
3117777
2461
52:00
EM: I don't know, we've certainly got a long way to go.
969
3120238
2628
52:02
As you alluded to earlier, we still have to get to orbit.
970
3122866
2752
52:05
And then after we get to orbit,
971
3125618
1752
52:07
we have to really prove out and refine full and rapid reusability.
972
3127412
6006
52:14
That'll take a moment.
973
3134085
1210
52:19
But I do think we will solve this.
974
3139090
1752
52:22
I'm highly confident we will solve this at this point.
975
3142969
2711
52:26
CA: Do you ever wake up with the fear
976
3146014
1793
52:27
that there's going to be this Hindenburg moment for SpaceX where ...
977
3147849
3462
52:31
EM: We've had many Hindenburg.
978
3151811
1460
52:33
Well, we've never had Hindenburg moments with people, which is very important.
979
3153313
3670
52:37
Big difference.
980
3157025
1251
52:38
We've blown up quite a few rockets.
981
3158776
1710
52:40
So there's a whole compilation online that we put together
982
3160486
3504
52:44
and others put together,
983
3164032
1710
52:45
it's showing rockets are hard.
984
3165742
1960
52:47
I mean, the sheer amount of energy going through a rocket boggles the mind.
985
3167744
3795
52:51
So, you know, getting out of Earth's gravity well is difficult.
986
3171581
3503
52:55
We have a strong gravity and a thick atmosphere.
987
3175126
2377
52:59
And Mars, which is less than 40 percent,
988
3179422
3921
53:03
it's like, 37 percent of Earth's gravity
989
3183426
2711
53:06
and has a thin atmosphere.
990
3186179
1626
53:08
The ship alone can go all the way
991
3188097
2002
53:10
from the surface of Mars to the surface of Earth.
992
3190141
2419
53:12
Whereas getting to Mars requires a giant booster and orbital refilling.
993
3192602
4755
53:17
CA: So, Elon, as I think more about this incredible array of things
994
3197774
4796
53:22
that you're involved with,
995
3202612
1835
53:24
I keep seeing these synergies,
996
3204489
4296
53:28
to use a horrible word,
997
3208826
1877
53:30
between them.
998
3210745
1168
53:31
You know, for example,
999
3211955
1167
53:33
the robots you're building from Tesla could possibly be pretty handy on Mars,
1000
3213122
5756
53:38
doing some of the dangerous work and so forth.
1001
3218920
2169
53:41
I mean, maybe there's a scenario where your city on Mars
1002
3221089
2669
53:43
doesn't need a million people,
1003
3223758
1460
53:45
it needs half a million people and half a million robots.
1004
3225218
2711
53:47
And that's a possibility.
1005
3227971
1835
53:49
Maybe The Boring Company could play a role
1006
3229847
2211
53:52
helping create some of the subterranean dwelling spaces that you might need.
1007
3232100
5380
53:57
EM: Yeah.
1008
3237480
1210
53:58
CA: Back on planet Earth,
1009
3238982
1501
54:00
it seems like a partnership between Boring Company and Tesla
1010
3240525
3211
54:03
could offer an unbelievable deal to a city
1011
3243778
3879
54:07
to say, we will create for you a 3D network of tunnels
1012
3247699
4504
54:12
populated by robo-taxis
1013
3252245
2252
54:14
that will offer fast, low-cost transport to anyone.
1014
3254539
4254
54:18
You know, full self-driving may or may not be done this year.
1015
3258835
2878
54:21
And in some cities, like, somewhere like Mumbai,
1016
3261713
2794
54:24
I suspect won't be done for a decade.
1017
3264549
2043
54:26
EM: Some places are more challenging than others.
1018
3266634
2294
54:28
CA: But today, today, with what you've got,
1019
3268928
2378
54:31
you could put a 3D network of tunnels under there.
1020
3271306
4254
54:35
EM: Oh, if it’s just in a tunnel, that’s a solved problem.
1021
3275601
2795
54:38
CA: Exactly, full self-driving is a solved problem.
1022
3278438
2502
54:40
To me, there’s amazing synergy there.
1023
3280982
3045
54:44
With Starship,
1024
3284068
1752
54:45
you know, Gwynne Shotwell talked about by 2028 having from city to city,
1025
3285820
5339
54:51
you know, transport on planet Earth.
1026
3291200
1752
54:52
EM: This is a real possibility.
1027
3292952
1627
54:57
The fastest way to get from one place to another,
1028
3297290
2961
55:00
if it's a long distance, is a rocket.
1029
3300293
1793
55:03
It's basically an ICBM.
1030
3303087
1377
55:05
CA: But it has to land --
1031
3305673
1335
55:07
Because it's an ICBM, it has to land probably offshore,
1032
3307675
3879
55:11
because it's loud.
1033
3311596
1168
55:12
So why not have a tunnel that then connects to the city with Tesla?
1034
3312805
6632
55:20
And Neuralink.
1035
3320897
1126
55:22
I mean, if you going to go to Mars
1036
3322065
1626
55:23
having a telepathic connection with loved ones back home,
1037
3323733
2878
55:26
even if there's a time delay...
1038
3326611
1501
55:29
EM: These are not intended to be connected, by the way.
1039
3329238
4088
55:33
But there certainly could be some synergies, yeah.
1040
3333326
2419
55:35
CA: Surely there is a growing argument
1041
3335787
2294
55:38
that you should actually put all these things together
1042
3338081
2711
55:40
into one company
1043
3340792
2127
55:42
and just have a company devoted to creating a future
1044
3342960
4296
55:47
that’s exciting,
1045
3347298
1460
55:48
and let a thousand flowers bloom.
1046
3348758
1627
55:50
Have you been thinking about that?
1047
3350426
1627
55:53
EM: I mean, it is tricky because Tesla is a publicly-traded company,
1048
3353429
3253
55:56
and the investor base of Tesla and SpaceX
1049
3356724
5255
56:02
and certainly Boring Company and Neuralink are quite different.
1050
3362021
3379
56:05
Boring Company and Neuralink are tiny companies.
1051
3365441
2503
56:08
CA: By comparison.
1052
3368569
1418
56:10
EM: Yeah, Tesla's got 110,000 people.
1053
3370321
3629
56:14
SpaceX I think is around 12,000 people.
1054
3374283
2503
56:17
Boring Company and Neuralink are both under 200 people.
1055
3377161
4546
56:21
So they're little, tiny companies,
1056
3381749
3170
56:24
but they will probably get bigger in the future.
1057
3384961
2252
56:27
They will get bigger in the future.
1058
3387213
1710
56:29
It's not that easy to sort of combine these things.
1059
3389632
2544
56:33
CA: Traditionally, you have said that for SpaceX especially,
1060
3393761
2878
56:36
you wouldn't want it public,
1061
3396639
1418
56:38
because public investors wouldn't support the craziness of the idea
1062
3398057
4296
56:42
of going to Mars or whatever.
1063
3402395
1418
56:43
EM: Yeah, making life multi-planetary
1064
3403813
2044
56:45
is outside of the normal time horizon of Wall Street analysts.
1065
3405898
5881
56:51
(Laughs)
1066
3411779
1001
56:52
To say the least.
1067
3412864
1209
56:54
CA: I think something's changed, though.
1068
3414073
2586
56:56
What's changed is that Tesla is now so powerful and so big
1069
3416701
2753
56:59
and throws off so much cash
1070
3419495
2461
57:01
that you actually could connect the dots here.
1071
3421998
3503
57:05
Just tell the public that x-billion dollars a year, whatever your number is,
1072
3425501
4546
57:10
will be diverted to the Mars mission.
1073
3430089
3420
57:13
I suspect you'd have massive interest in that company.
1074
3433551
3462
57:17
And it might unlock a lot more possibility for you, no?
1075
3437054
4922
57:22
EM: I would like to give the public access to ownership of SpaceX,
1076
3442018
5797
57:27
but I mean the thing that like,
1077
3447815
2711
57:30
the overhead associated with a public company is high.
1078
3450568
5130
57:38
I mean, as a public company, you're just constantly sued.
1079
3458284
2711
57:41
It does occupy like, a fair bit of ...
1080
3461037
3003
57:45
You know, time and effort to deal with these things.
1081
3465958
3546
57:49
CA: But you would still only have one public company, it would be bigger,
1082
3469504
3628
57:53
and have more things going on.
1083
3473174
1752
57:54
But instead of being on four boards, you'd be on one.
1084
3474967
2711
57:57
EM: I'm actually not even on the Neuralink or Boring Company boards.
1085
3477720
3337
58:02
And I don't really attend the SpaceX board meetings.
1086
3482099
3671
58:06
We only have two a year,
1087
3486103
1210
58:07
and I just stop by and chat for an hour.
1088
3487313
2211
58:13
The board overhead for a public company is much higher.
1089
3493110
2837
58:15
CA: I think some investors probably worry about how your time is being split,
1090
3495988
3712
58:19
and they might be excited by you know, that.
1091
3499742
2669
58:22
Anyway, I just woke up the other day
1092
3502495
3253
58:25
thinking, just, there are so many ways in which these things connect.
1093
3505790
3420
58:29
And you know, just the simplicity of that mission,
1094
3509252
3837
58:33
of building a future that is worth getting excited about,
1095
3513130
3546
58:36
might appeal to an awful lot of people.
1096
3516676
3461
58:41
Elon, you are reported by Forbes and everyone else as now, you know,
1097
3521013
5381
58:46
the world's richest person.
1098
3526435
1752
58:48
EM: That’s not a sovereign.
1099
3528187
1293
58:49
CA: (Laughs)
1100
3529564
1001
58:50
EM: You know, I think it’s fair to say
1101
3530606
1835
58:52
that if somebody is like, the king or de facto king of a country,
1102
3532483
4671
58:57
they're wealthier than I am.
1103
3537154
1961
58:59
CA: But it’s just harder to measure --
1104
3539323
2711
59:02
So $300 billion.
1105
3542285
1418
59:03
I mean, your net worth on any given day
1106
3543744
3838
59:07
is rising or falling by several billion dollars.
1107
3547623
3045
59:10
How insane is that?
1108
3550710
2127
59:12
EM: It's bonkers, yeah.
1109
3552878
1168
59:14
CA: I mean, how do you handle that psychologically?
1110
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2586
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There aren't many people in the world who have to even think about that.
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EM: I actually don't think about that too much.
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59:22
But the thing that is actually more difficult
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59:26
and that does make sleeping difficult
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59:27
is that, you know,
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59:31
every good hour or even minute
1116
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59:35
of thinking about Tesla and SpaceX
1117
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59:39
has such a big effect on the company
1118
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59:41
that I really try to work as much as possible,
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59:45
you know, to the edge of sanity, basically.
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59:49
Because you know, Tesla’s getting to the point where
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59:54
probably will get to the point later this year,
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59:57
where every high-quality minute of thinking
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60:02
is a million dollars impact on Tesla.
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60:08
Which is insane.
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60:13
I mean, the basic, you know, if Tesla is doing, you know,
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60:17
sort of $2 billion a week, let’s say, in revenue,
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60:21
it’s sort of $300 million a day, seven days a week.
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4713
60:26
You know, it's ...
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1335
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CA: If you can change that by five percent in an hour’s brainstorm,
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that's a pretty valuable hour.
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60:37
EM: I mean, there are many instances where a half-hour meeting,
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I was able to improve the financial outcome of the company
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3378
60:45
by $100 million in a half-hour meeting.
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3629
60:50
CA: There are many other people out there
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2044
60:52
who can't stand this world of billionaires.
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2752
60:55
Like, they are hugely offended by the notion
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3921
60:59
that an individual can have the same wealth as, say,
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4588
61:03
a billion or more of the world's poorest people.
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61:07
EM: If they examine sort of --
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61:09
I think there's some axiomatic flaws that are leading them to that conclusion.
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61:15
For sure, it would be very problematic if I was consuming,
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4922
61:20
you know, billions of dollars a year in personal consumption.
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61:23
But that is not the case.
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61:24
In fact, I don't even own a home right now.
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2252
61:27
I'm literally staying at friends' places.
1146
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2336
61:30
If I travel to the Bay Area,
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1543
61:31
which is where most of Tesla engineering is,
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2085
61:33
I basically rotate through friends' spare bedrooms.
1149
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3795
61:38
I don't have a yacht, I really don't take vacations.
1150
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61:44
It’s not as though my personal consumption is high.
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61:49
I mean, the one exception is a plane.
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1793
61:51
But if I don't use the plane, then I have less hours to work.
1153
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2878
61:55
CA: I mean, I personally think you have shown that you are mostly driven
1154
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4129
61:59
by really quite a deep sense of moral purpose.
1155
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2502
62:01
Like, your attempts to solve the climate problem
1156
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5589
62:07
have been as powerful as anyone else on the planet that I'm aware of.
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4838
62:12
And I actually can't understand,
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62:14
personally, I can't understand the fact
1159
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1877
62:16
that you get all this criticism from the Left about,
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2461
62:18
"Oh, my God, he's so rich, that's disgusting."
1161
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2377
62:21
When climate is their issue.
1162
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2377
62:25
Philanthropy is a topic that some people go to.
1163
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2210
62:27
Philanthropy is a hard topic.
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1668
62:29
How do you think about that?
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1794
62:31
EM: I think if you care about the reality of goodness
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2711
62:34
instead of the perception of it, philanthropy is extremely difficult.
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3796
62:39
SpaceX, Tesla, Neuralink and The Boring Company are philanthropy.
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3921
62:43
If you say philanthropy is love of humanity,
1169
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3086
62:46
they are philanthropy.
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1668
62:49
Tesla is accelerating sustainable energy.
1171
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2878
62:52
This is a love -- philanthropy.
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3545
62:56
SpaceX is trying to ensure the long-term survival of humanity
1173
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3712
63:00
with a multiple-planet species.
1174
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1501
63:02
That is love of humanity.
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63:05
You know, Neuralink is trying to help solve brain injuries
1176
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4546
63:09
and existential risk with AI.
1177
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2294
63:12
Love of humanity.
1178
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1167
63:13
Boring Company is trying to solve traffic, which is hell for most people,
1179
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3504
63:16
and that also is love of humanity.
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2627
63:20
CA: How upsetting is it to you
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4296
63:24
to hear this constant drumbeat of,
1182
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3546
63:28
"Billionaires, my God, Elon Musk, oh, my God?"
1183
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2169
63:30
Like, do you just shrug that off
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2961
63:33
or does it does it actually hurt?
1185
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1627
63:36
EM: I mean, at this point, it's water off a duck's back.
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2794
63:39
CA: Elon, I’d like to, as we wrap up now,
1187
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2544
63:41
just pull the camera back and just think ...
1188
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3378
63:45
You’re a father now of seven surviving kids.
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3504
63:49
EM: Well, I mean, I'm trying to set a good example
1190
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2336
63:51
because the birthrate on Earth is so low
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1919
63:53
that we're facing civilizational collapse
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2043
63:55
unless the birth rate returns to a sustainable level.
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4838
64:01
CA: Yeah, you've talked about this a lot,
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1960
64:03
that depopulation is a big problem,
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2294
64:06
and people don't understand how big a problem it is.
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2460
64:08
EM: Population collapse is one of the biggest threats
1197
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2503
64:10
to the future of human civilization.
1198
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1752
64:12
And that is what is going on right now.
1199
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1877
64:14
CA: What drives you on a day-to-day basis to do what you do?
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2836
64:17
EM: I guess, like, I really want to make sure
1201
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3087
64:20
that there is a good future for humanity
1202
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3462
64:24
and that we're on a path to understanding the nature of the universe,
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5297
64:29
the meaning of life.
1204
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1168
64:30
Why are we here, how did we get here?
1205
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1960
64:33
And in order to understand the nature of the universe
1206
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4422
64:37
and all these fundamental questions,
1207
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3921
64:41
we must expand the scope and scale of consciousness.
1208
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3086
64:47
Certainly it must not diminish or go out.
1209
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1960
64:49
Or we certainly won’t understand this.
1210
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2211
64:51
I would say I’ve been motivated by curiosity more than anything,
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3587
64:54
and just desire to think about the future
1212
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4337
64:59
and not be sad, you know?
1213
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2544
65:03
CA: And are you?
1214
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1168
65:04
Are you not sad?
1215
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1251
65:06
EM: I'm sometimes sad,
1216
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1209
65:07
but mostly I'm feeling I guess
1217
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4505
65:12
relatively optimistic about the future these days.
1218
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2544
65:15
There are certainly some big risks that humanity faces.
1219
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3921
65:20
I think the population collapse is a really big deal,
1220
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2795
65:23
that I wish more people would think about
1221
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5130
65:28
because the birth rate is far below what's needed to sustain civilization
1222
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4964
65:33
at its current level.
1223
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1669
65:35
And there's obviously ...
1224
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3212
65:39
We need to take action on climate sustainability,
1225
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2877
65:42
which is being done.
1226
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1919
65:45
And we need to secure the future of consciousness
1227
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2294
65:47
by being a multi-planet species.
1228
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2252
65:51
We need to address --
1229
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1293
65:52
Essentially, it's important to take whatever actions we can think of
1230
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3212
65:55
to address the existential risks that affect the future of consciousness.
1231
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4796
66:00
CA: There's a whole generation coming through
1232
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2127
66:02
who seem really sad about the future.
1233
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1793
66:04
What would you say to them?
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66:07
EM: Well, I think if you want the future to be good, you must make it so.
1235
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3587
66:12
Take action to make it good.
1236
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2419
66:14
And it will be.
1237
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1209
66:17
CA: Elon, thank you for all this time.
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2211
66:19
That is a beautiful place to end.
1239
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1668
66:21
Thanks for all you're doing.
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1376
66:22
EM: You're welcome.
1241
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1210
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