Lex Fridman Podcast - #49 - Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot

The following is a conversation with Elon Musk, Part 2, the second time we spoke on the podcast,

with parallels, if not in quality, than an outfit, to the objectively speaking greatest

sequel of all time, Godfather Part 2. As many people know, Elon Musk is a leader of Tesla,

SpaceX, Neuralink, and the Boring Company. What may be less known is that he’s a world

class engineer and designer, constantly emphasizing first principles thinking and taking on big

engineering problems that many before him will consider impossible. As scientists and engineers,

most of us don’t question the way things are done, we simply follow the momentum of the crowd.

But revolutionary ideas that change the world on the small and large scales happen when you

return to the fundamentals and ask, is there a better way? This conversation focuses on the

incredible engineering and innovation done in brain computer interfaces at Neuralink.

This work promises to help treat neurobiological diseases to help us further understand the

connection between the individual neuron to the high level function of the human brain.

And finally, to one day expand the capacity of the brain through two way communication

with computational devices, the internet, and artificial intelligence systems.

This is the Artificial Intelligence Podcast. If you enjoy it, subscribe by YouTube,

Apple Podcasts, Spotify, support on Patreon, or simply connect with me on Twitter

at Lex Friedman, spelled F R I D M A N. And now, as an anonymous YouTube commenter referred to

our previous conversation as the quote, historical first video of two robots conversing without

supervision, here’s the second time, the second conversation with Elon Musk.

Let’s start with an easy question about consciousness. In your view, is consciousness

something that’s unique to humans or is it something that permeates all matter, almost like

a fundamental force of physics? I don’t think consciousness permeates all matter. Panpsychists

believe that. Yeah. There’s a philosophical. How would you tell? That’s true. That’s a good point.

I believe in scientific methods. I don’t know about your mind or anything, but the scientific

method is like, if you cannot test the hypothesis, then you cannot reach meaningful conclusion that

it is true. Do you think consciousness, understanding consciousness is within the

reach of science of the scientific method? We can dramatically improve our understanding of

consciousness. You know, hot press to say that we understand anything with complete accuracy,

but can we dramatically improve our understanding of consciousness? I believe the answer is yes.

Does an AI system in your view have to have consciousness in order to achieve human level

or superhuman level intelligence? Does it need to have some of these human qualities that

consciousness, maybe a body, maybe a fear of mortality, capacity to love those kinds of

silly human things? There’s a different, you know, there’s this, there’s the scientific method,

which I very much believe in where something is true to the degree that it is testably. So

and otherwise, you’re really just talking about, you know, preferences or untestable beliefs or

that, you know, that kind of thing. So it ends up being somewhat of a semantic question, where

we were conflating a lot of things with the word intelligence. If we parse them out and say,

you know, are we headed towards the future where an AI will be able to outthink us in every way?

Then the answer is unequivocally yes.

In order for an AI system that needs to outthink us in every way, it also needs to have

a capacity to have consciousness, self awareness, and understanding.

It will be self aware. Yes, that’s different from consciousness. I mean, to me, in terms of what

what consciousness feels like, it feels like consciousness is in a different dimension.

But this is this could be just an illusion. You know, if you damage your brain in some way,

physically, you get you, you damage your consciousness, which implies that consciousness

is a physical phenomenon. And in my view, the thing is that that I think are really quite,

quite likely is that digital intelligence will be able to outthink us in every way, and it will

simply be able to simulate what we consider consciousness. So to the degree that you would

not be able to tell the difference. And from the from the aspect of the scientific method,

it’s might as well be consciousness, if we can simulate it perfectly.

If you can’t tell the difference, when this is sort of the Turing test, but think of a more

sort of advanced version of the Turing test. If you’re if you’re talking to a digital super

intelligence and can’t tell if that is a computer or a human, like let’s say you’re just having

conversation over a phone or a video conference or something where you’re you think you’re talking

looks like a person makes all of the right inflections and movements and all the small

subtleties that constitute a human and talks like human makes mistakes like a human like

and you literally just can’t tell is this Are you video conferencing with a person or or an AI

might as well might as well be human. So on a darker topic, you’ve expressed serious concern

about existential threats of AI. It’s perhaps one of the greatest challenges our civilization faces,

but since I would say we’re kind of an optimistic descendants of apes, perhaps we can find several

paths of escaping the harm of AI. So if I can give you an example of an example of an example

of escaping the harm of AI. So if I can give you three options, maybe you can comment which do you

think is the most promising. So one is scaling up efforts on AI safety and beneficial AI research

in hope of finding an algorithmic or maybe a policy solution. Two is becoming a multi planetary

species as quickly as possible. And three is merging with AI and riding the wave of that

increasing intelligence as it continuously improves. What do you think is most promising,

most interesting, as a civilization that we should invest in?

I think there’s a lot of tremendous amount of investment going on in AI, where there’s a lack

of investment is in AI safety. And there should be in my view, a government agency that oversees

anything related to AI to confirm that it is does not represent a public safety risk,

just as there is a regulatory authority for the Food and Drug Administration is that’s for

automotive safety, there’s the FAA for aircraft safety, which I really come to the conclusion that

it is important to have a government referee or referee that is serving the public interest

in ensuring that things are safe when when there’s a potential danger to the public.

I would argue that AI is unequivocally something that has potential to be dangerous to the public,

and therefore should have a regulatory agency just as other things that are dangerous to the public

have a regulatory agency. But let me tell you, the problem with this is that the government

moves very slowly. And the rate of the rate, the usually way a regulatory agency comes into being

is that something terrible happens. There’s a huge public outcry. And years after that,

there’s a regulatory agency or a rule put in place, take something like, like seatbelts,

it was known for a decade or more that seatbelts would have a massive impact on safety and save so

many lives in serious injuries. And the car industry fought the requirement to put seatbelts in

tooth and nail. That’s crazy. Yeah. And hundreds of 1000s of people probably died because of that.

And they said people wouldn’t buy cars if they had seatbelts, which is obviously absurd.

Yeah, or look at the tobacco industry and how long they fought any thing about smoking. That’s part

of why I helped make that movie. Thank you for smoking. You can sort of see just how pernicious

it can be when you have these companies effectively achieve regulatory capture of government. The bad

people in the community refer to the advent of digital super intelligence as a singularity.

That is not to say that it is good or bad, but that it is very difficult to predict what will

happen after that point. And then there’s some probability it will be bad, some probably it’ll

be it will be good. We obviously want to affect that probability and have it be more good than bad.

Well, let me on the merger with AI question and the incredible work that’s being done at Neuralink.

There’s a lot of fascinating innovation here across different disciplines going on. So the flexible

wires, the robotic sewing machine, that responsive brain movement, everything around ensuring safety

and so on. So we currently understand very little about the human brain. Do you also hope that the

work at Neuralink will help us understand more about our about our human brain?

Yeah, I think the work in Neuralink will definitely shed a lot of insight into how the brain, the mind

works. Right now, just the data we have regarding how the brain works is very limited. You know,

we’ve got fMRI, which is that that’s kind of like putting us, you know, stethoscope on the outside

of a factory wall and then putting it like all over the factory wall and you can sort of hear

the sounds, but you don’t know what the machines are doing, really. It’s hard. You can infer a few

things, but it’s very broad brushstroke. In order to really know what’s going on in the brain,

you really need you have to have high precision sensors. And then you want to have stimulus and

response. Like if you trigger a neuron, what, how do you feel? What do you see? How does it change

your perception of the world? You’re speaking to physically just getting close to the brain,

being able to measure signals, how do you know what’s going on in the brain?

Physically, just getting close to the brain, being able to measure signals from the brain

will give us sort of open the door inside the factory.

Yes, exactly. Being able to have high precision sensors that tell you what individual neurons

are doing. And then being able to trigger a neuron and see what the response is in the brain.

So you can see the consequences of if you fire this neuron, what happens? How do you feel? What

does it change? It’ll be really profound to have this in people because people can articulate

their change. Like if there’s a change in mood, or if they can tell you if they can see better,

or hear better, or be able to form sentences better or worse, or their memories are jogged,

or that kind of thing. So on the human side, there’s this incredible general malleability,

plasticity of the human brain, the human brain adapts, adjusts, and so on.

So that’s not that plastic, to be totally frank.

So there’s a firm structure, but nevertheless, there’s some plasticity. And the open question is,

sort of, if I could ask a broad question is how much that plasticity can be utilized. Sort of,

on the human side, there’s some plasticity in the human brain. And on the machine side,

we have neural networks, machine learning, artificial intelligence, it’s able to adjust

and figure out signals. So there’s a mysterious language that we don’t perfectly understand

that’s within the human brain. And then we’re trying to understand that language to communicate

both directions. So the brain is adjusting a little bit, we don’t know how much, and the

machine is adjusting. Where do you see, as they try to sort of reach together, almost like with

an alien species, try to find a protocol, communication protocol that works? Where do

you see the biggest, the biggest benefit arriving from on the machine side or the human side? Do you

see both of them working together? I think the machine side is far more malleable than the

biological side, by a huge amount. So it’ll be the machine that adapts to the brain. That’s the only

thing that’s possible. The brain can’t adapt that well to the machine. You can’t have neurons start

to regard an electrode as another neuron, because neurons just, there’s like the pulse. And so

something else is pulsing. So there is that elasticity in the interface, which we believe is

something that can happen. But the vast majority of the malleability will have to be on the machine

side. But it’s interesting, when you look at that synaptic plasticity at the interface side,

there might be like an emergent plasticity. Because it’s a whole nother, it’s not like in the

brain, it’s a whole nother extension of the brain. You know, we might have to redefine what it means

to be malleable for the brain. So maybe the brain is able to adjust to external interfaces. There

will be some adjustments to the brain, because there’s going to be something reading and simulating

the brain. And so it will adjust to that thing. But most, the vast majority of the adjustment

will be on the machine side. This is just, this is just, it has to be that otherwise it will not

work. Ultimately, like, we currently operate on two layers, we have sort of a limbic, like prime

primitive brain layer, which is where all of our kind of impulses are coming from. It’s sort of

like we’ve got, we’ve got like a monkey brain with a computer stuck on it. That’s that’s the

human brain. And a lot of our impulses and everything are driven by the monkey brain.

And the computer, the cortex is constantly trying to make the monkey brain happy.

It’s not the cortex that’s steering the monkey brains, the monkey brain steering the cortex.

You know, the cortex is the part that tells the story of the whole thing. So we convince ourselves

it’s, it’s more interesting than just the monkey brain. The cortex is like what we call like human

intelligence. You know, it’s just like, that’s like the advanced computer relative to other

creatures. The other creatures do not have either. Really, they don’t, they don’t have the

computer, or they have a very weak computer relative to humans. But it’s, it’s like, it sort

of seems like surely the really smart thing should control the dumb thing. But actually,

the dumb thing controls the smart thing. So do you think some of the same kind of machine learning

methods, whether that’s natural language processing applications are going to be applied for the

communication between the machine and the brain to learn how to do certain things like movement

of the body, how to process visual stimuli, and so on. Do you see the value of using machine

learning to understand the language of the two way communication with the brain? Sure. Yeah,

absolutely. I mean, we’re neural net. And that, you know, AI is basically neural net.

So it’s like digital neural net will interface with biological neural net.

And hopefully bring us along for the ride. Yeah. But the vast majority of our intelligence will be

digital. Like, so like, think of like, the difference in intelligence between your cortex

and your limbic system is gigantic, your limbic system really has no comprehension of what the

hell the cortex is doing. It’s just literally hungry, you know, or tired or angry or sexy or

something, you know, that’s just and then that communicates that that impulse to the cortex and

tells the cortex to go satisfy that then love a great deal of like, a massive amount of thinking,

like truly stupendous amount of thinking has gone into sex without purpose, without procreation,

without procreation. Which is actually quite a silly action in the absence of procreation. It’s

a bit silly. Why are you doing it? Because it makes the limbic system happy. That’s why. That’s why.

But it’s pretty absurd, really. Well, the whole of existence is pretty absurd in some kind of sense.

Yeah. But I mean, this is a lot of computation has gone into how can I do more of that with

procreation not even being a factor? This is, I think, a very important area of research by NSFW.

An agency that should receive a lot of funding, especially after this conversation.

I propose the formation of a new agency. Oh, boy.

What is the most exciting or some of the most exciting things that you see in the future impact

of Neuralink, both in the science, the engineering and societal broad impact?

Neuralink, I think, at first will solve a lot of brain related diseases. So it could be anything

from like autism, schizophrenia, memory loss, like everyone experiences memory loss at certain points

in age. Parents can’t remember their kids names and that kind of thing. So it could be anything

from like autism, schizophrenia, memory loss, like everyone experiences memory loss at certain points

in age. Parents can’t remember their kids names and that kind of thing. So there’s a tremendous

amount of good that Neuralink can do in solving critical damage to the brain or the spinal cord.

There’s a lot that can be done to improve quality of life of individuals. And those will be steps

to address the existential risk associated with digital superintelligence. Like we will not be

able to be smarter than a digital supercomputer. So therefore, if you cannot beat them, join them.

And at least we won’t have that option.

So you have hope that Neuralink will be able to be a kind of connection to allow us to merge,

the wave of the improving AI systems. I think the chance is above zero percent.

So it’s non zero. There’s a chance. And that’s what I’ve seen. Dumb and Dumber.

Yes. So I’m saying there’s a chance. He’s saying one in a billion or one in a million,

whatever it was, a dumb and dumber. You know, it went from maybe one in a million to improving.

Maybe it’ll be one in a thousand and then one in a hundred, then one in ten. Depends on the rate

of improvement of Neuralink and how fast we’re able to do make progress.

Well, I’ve talked to a few folks here that are quite brilliant engineers, so I’m excited.

Yeah, I think it’s like fundamentally good, you know,

giving somebody back full motor control after they’ve had a spinal cord injury.

You know, restoring brain functionality after a stroke,

solving debilitating genetically oriented brain diseases. These are all incredibly

great, I think. And in order to do these, you have to be able to interface with neurons at

a detailed level and you need to be able to fire the right neurons, read the right neurons, and

and then effectively you can create a circuit, replace what’s broken with

with silicon and essentially fill in the missing functionality. And then over time,

we can develop a tertiary layer. So if like the limbic system is the primary layer, then the

cortex is like the second layer. And as I said, obviously the cortex is vastly more intelligent

than the limbic system, but people generally like the fact that they have a limbic system

and a cortex. I haven’t met anyone who wants to delete either one of them. They’re like,

okay, I’ll keep them both. That’s cool. The limbic system is kind of fun.

That’s where the fun is, absolutely. And then people generally don’t want to lose their

cortex either. They’re like having the cortex and the limbic system. And then there’s a tertiary

layer, which will be digital superintelligence. And I think there’s room for optimism given that

the cortex, the cortex is very intelligent and limbic system is not, and yet they work together

well. Perhaps there can be a tertiary layer where digital superintelligence lies, and that will be

vastly more intelligent than the cortex, but still coexist peacefully and in a benign manner with the

cortex and limbic system. That’s a super exciting future, both in low level engineering that I saw

as being done here and the actual possibility in the next few decades. It’s important that

Neuralink solve this problem sooner rather than later, because the point at which we have digital

superintelligence, that’s when we pass the singularity and things become just very uncertain.

It doesn’t mean that they’re necessarily bad or good. For the point at which we pass singularity,

things become extremely unstable. So we want to have a human brain interface before the singularity,

or at least not long after it, to minimize existential risk for humanity and consciousness

as we know it. So there’s a lot of fascinating actual engineering, low level problems here at

Neuralink that are quite exciting. The problems that we face in Neuralink are material science,

electrical engineering, software, mechanical engineering, microfabrication. It’s a bunch of

engineering disciplines, essentially. That’s what it comes down to, is you have to have a

tiny electrode, so small it doesn’t hurt neurons, but it’s got to last for as long as a person. So

it’s going to last for decades. And then you’ve got to take that signal, you’ve got to process

that signal locally at low power. So we need a lot of chip design engineers, because we’re going to

do signal processing, and do so in a very power efficient way, so that we don’t heat your brain

up, because the brain is very heat sensitive. And then we’ve got to take those signals and

we’re going to do something with them. And then we’ve got to stimulate the back to bidirectional

communication. So somebody’s good at material science, software, and we’ve got to do a lot of

that. So somebody’s good at material science, software, mechanical engineering, electrical

engineering, chip design, microfabrication. Those are the things we need to work on.

We need to be good at material science, so that we can have tiny electrodes that last a long time.

And it’s a tough thing with the material science problem, it’s a tough one, because

you’re trying to read and simulate electrically in an electrically active area. Your brain is

very electrically active and electrochemically active. So how do you have a coating on the

electrode that doesn’t dissolve over time and is safe in the brain? This is a very hard problem.

And then how do you collect those signals in a way that is most efficient? Because you really

just have very tiny amounts of power to process those signals. And then we need to automate the

whole thing so it’s like LASIK. If this is done by neurosurgeons, there’s no way it can scale to

a large number of people. And it needs to scale to a large number of people, because I think

ultimately we want the future to be determined by a large number of humans. Do you think that

this has a chance to revolutionize surgery period? So neurosurgery and surgery all across?

Yeah, for sure. It’s got to be like LASIK. If LASIK had to be done by hand by a person,

that wouldn’t be great. It’s done by a robot. And the ophthalmologist kind of just needs to make

sure your head’s in the right position, and then they just press a button and go.

SmartSummon and soon Autopark takes on the full beautiful mess of parking lots and their human

to human nonverbal communication. I think it has actually the potential to have a profound impact

in changing how our civilization looks at AI and robotics, because this is the first time human

beings, people that don’t own a Tesla may have never seen a Tesla or heard about a Tesla,

get to watch hundreds of thousands of cars without a driver. Do you see it this way, almost like an

education tool for the world about AI? Do you feel the burden of that, the excitement of that,

or do you just think it’s a smart parking feature? I do think you are getting at something

important, which is most people have never really seen a robot. And what is the car that is

autonomous? It’s a four wheeled robot. Yeah, it communicates a certain sort of message with

everything from safety to the possibility of what AI could bring to its current limitations,

its current challenges, it’s what’s possible. Do you feel the burden of that almost like a

communicator educator to the world about AI? We were just really trying to make people’s

lives easier with autonomy. But now that you mentioned it, I think it will be an eye opener

to people about robotics, because they’ve really never seen most people never seen a robot. And

there are hundreds of thousands of Tesla’s won’t be long before there’s a million of them that

have autonomous capability, and the drive without a person in it. And you can see the kind of

evolution of the car’s personality and, and thinking with each iteration of autopilot,

you can see it’s, it’s uncertain about this, or it gets it, but now it’s more certain. Now it’s

moving in a slightly different way. Like, I can tell immediately if a car is on Tesla autopilot,

because it’s got just little nuances of movement, it just moves in a slightly different way.

Cars on Tesla autopilot, for example, on the highway are far more precise about being in the

center of the lane than a person. If you drive down the highway and look at how at where cars

are, the human driven cars are within their lane, they’re like bumper cars. They’re like moving all

over the place. The car in autopilot, dead center. Yeah, so the incredible work that’s going into

that neural network, it’s learning fast. Autonomy is still very, very hard. We don’t actually know

how hard it is fully, of course. You look at the most problems you tackle, this one included,

with an exponential lens, but even with an exponential improvement, things can take longer

than expected sometimes. So where does Tesla currently stand on its quest for full autonomy?

What’s your sense? When can we see successful deployment of full autonomy?

Well, on the highway already, the the probability of intervention is extremely low.

Yes. So for highway autonomy, with the latest release, especially the probability of needing

to intervene is really quite low. In fact, I’d say for stop and go traffic,

it’s far safer than a person right now. The probability of an injury or impact is much,

much lower for autopilot than a person. And then with navigating autopilot, you can change lanes,

take highway interchanges, and then we’re coming at it from the other direction, which is low speed,

full autonomy. And in a way, this is like, how does a person learn to drive? You learn to drive

in the parking lot. You know, the first time you learn to drive probably wasn’t jumping on

August Street in San Francisco. That’d be crazy. You learn to drive in the parking lot, get things

get things right at low speed. And then the missing piece that we’re working on is traffic

lights and stop streets. Stop streets, I would say actually also relatively easy, because, you know,

you kind of know where the stop street is, worst case in geocoders, and then use visualization to

see where the line is and stop at the line to eliminate the GPS error. So actually, I’d say it’s

probably complex traffic lights and very windy roads are the two things that need to get solved.

What’s harder, perception or control for these problems? So being able to perfectly perceive

everything, or figuring out a plan once you perceive everything, how to interact with all the

agents in the environment in your sense, from a learning perspective, is perception or action

harder? And that giant, beautiful multitask learning neural network, the hottest thing is

having accurate representation of the physical objects in vector space. So transfer taking the

visual input, primarily visual input, some sonar and radar, and and then creating the an accurate

vector space representation of the objects around you. Once you have an accurate vector space

representation, the planning and control is relatively easier. That is relatively easy.

Basically, once you have accurate vector space representation, then you’re kind of like a video

game, like cars and like Grand Theft Auto or something like they work pretty well. They drive

down the road, they don’t crash, you know, pretty much unless you crash into them. That’s because

they’ve they’ve got an accurate vector space representation of where the cars are, and they’re

just and then they’re rendering that as the as the output. Do you have a sense, high level, that

Tesla’s on track on being able to achieve full autonomy? So on the highway? Yeah, absolutely.

And still no driver state, driver sensing? And we have driver sensing with torque on the wheel.

That’s right. Yeah. By the way, just a quick comment on karaoke. Most people think it’s fun,

but I also think it is a driving feature. I’ve been saying for a long time, singing in the car

is really good for attention management and vigilance management. That’s right.

Tesla karaoke is great. It’s one of the most fun features of the car. Do you think of a connection

between fun and safety sometimes? Yeah, you can do both at the same time. That’s great.

I just met with Andrew and wife of Carl Sagan, directed Cosmos. I’m generally a big fan of Carl

Sagan. He’s super cool. And had a great way of putting things. All of our consciousness,

all civilization, everything we’ve ever known and done is on this tiny blue dot.

People also get they get too trapped in there. This is like squabbles amongst humans.

Let’s not think of the big picture. They take civilization and our continued existence for

granted. I shouldn’t do that. Look at the history of civilizations. They rise and they fall. And now

civilization is all it’s globalized. And so civilization, I think now rises and falls together.

There’s no there’s not geographic isolation. This is a big risk. Things don’t always go up. That

should be that’s an important lesson of history. In 1990, at the request of Carl Sagan, the Voyager

One spacecraft, which is a spacecraft that’s reaching out farther than anything human made

into space, turned around to take a picture of Earth from 3.6 billion years ago. And that’s

a picture of Earth from 3.7 billion miles away. And as you’re talking about the pale blue dot,

that picture there takes up less than a single pixel in that image. Yes. Appearing as a tiny

blue dot, as a pale blue dot, as Carl Sagan called it. So he spoke about this dot of ours in 1994.

And if you could humor me, I was wondering if in the last two minutes you could read the words

that he wrote describing this pale blue dot. Sure. Yes, it’s funny. The universe appears to be 13.8

billion years old. Earth is like four and a half billion years old.

In another half billion years or so, the sun will expand and probably evaporate the oceans and make

life impossible on Earth, which means that if it had taken consciousness 10% longer to evolve,

it would never have evolved at all. It’s 10% longer. And I wonder how many dead one planet

civilizations there are out there in the cosmos.

That never made it to the other planet and ultimately extinguished themselves or were destroyed

by external factors. Probably a few. It’s only just possible to travel to Mars. Just barely.

If G was 10% more, it wouldn’t work really.

If G was 10% lower, it would be easy. Like you can go single stage from the surface of Mars all the

way to the surface of the Earth. Because Mars is 37% Earth’s gravity. We need a giant booster

to get off the Earth. Channeling Carl Sagan. Look again at that dot. That’s here. That’s home. That’s us.

On it, everyone you love, everyone you know, everyone you’ve ever heard of, every human being

who ever was, lived out their lives. The aggregate of our joy and suffering, thousands of confident

religions, ideologies and economic doctrines. Every hunter and farger, every hero and coward,

every creator and destroyer of civilization, every king and peasant, every young couple in love,

every mother and father, hopeful child, inventor and explorer, every teacher of morals, every

corrupt politician, every superstar, every supreme leader, every saint and sinner in the history of

our species lived there on a mode of dust suspended in a sunbeam. Our planet is a lonely speck in the

great enveloping cosmic dark. In our obscurity, in all this vastness, there is no hint that help

will come from elsewhere to save us from ourselves. The Earth is the only world known so far to harbor

life. There is nowhere else, at least in the near future, to which our species could migrate. This

is not true. This is false. Mars. And I think Carl Sagan would agree with that. He couldn’t even

imagine it at that time. So thank you for making the world dream. And thank you for talking today.

I really appreciate it. Thank you.

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