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.