Elon Musk: Neuralink, AI, Autopilot, and the Pale Blue Dot | Lex Fridman Podcast #49
 The following is a conversation with Elon Musk, part two, 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 two. 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 AI. 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. Yeah. Panpsychists believe that. There's a philosophical... How would you tell? That's true. That's a good point. I believe in scientific methods. I don't blow 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 or the scientific method? We can dramatically improve our understanding of consciousness. I would be hard pressed 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 this scientific method which I very much believe in, where something is true to the degree that it is testably so. Otherwise, you're really just talking about preferences or untestable beliefs or that kind of thing. 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, 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, what consciousness feels like, it feels like consciousness is in a different dimension. But this could be just an illusion. If you damage your brain in some way physically, you damage your consciousness, which implies that consciousness is a physical phenomenon, in my view. The things that I think are really quite likely is that digital intelligence will be able to outthink us in every way, and it will suddenly be able to simulate what we consider consciousness to a degree that you would not be able to tell the difference. And from the aspect of the scientific method, it might as well be consciousness if we can simulate it perfectly. If you can't tell the difference, and this is sort of the Turing test, but think of a more sort of advanced version of the Turing test. 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 a conversation over a phone or a video conference or something where 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. Talks like human makes mistakes like a human, and you literally just can't tell. Are you video conferencing with a person 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 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 the most promising, most interesting as a civilization that we should invest in? I think there's a 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 does not represent a public safety risk, just as there is a regulatory authority for the Food and Drug Administration, there's NETSA for automotive safety, there's the FAA for aircraft safety. Where it generally comes to the conclusion that it is important to have a government referee or a referee that is serving the public interest in ensuring that things are safe 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 it governs very slowly. And the rate of, 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. It takes something like seat belts. It was known for a decade or more that seat belts would have a massive impact on safety and save so many lives and serious injuries. And the car industry fought the requirement to put seat belts in tooth and nail. That's crazy. And hundreds of thousands of people probably died because of that. And they said people wouldn't buy cars if they had seat belts, which is obviously absurd. Or look at the tobacco industry and how long they fought anything 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 the government is trying to make it work. How pernicious it can be when you have these companies effectively achieve regulatory capture of government. The bad. People in the AI community refer to the advent of digital superintelligence 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 that there's some probability it will be bad, some probability it will be good. Or else they 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, the 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 the human mind, about the brain? Yeah, I think the work in Neuralink will definitely shed a lot of insight into how the brain, the mind works. Right now, there's just the data we have regarding how the brain works. It's very limited. We've got fMRI, which is that that's kind of like putting a 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 stimulation sensors. You want to have stimulus and response. Like if you trigger a neuron, 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 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 it's not that plastic, to be totally frank. So there's a firm structure, but nevertheless, there is some plasticity. And the open question is, so 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 benefit arriving from on the machine side or the human side? Do you see both of them working together? I actually think the machine side is far more malleable than the biological side by a huge amount. So it will 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 the neuron just, it'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 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. 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 the vast majority of the adjustment will be on the machine side. This is just, it has to be that, otherwise it will not work. Ultimately, we currently operate on two layers. We have sort of a limbic, like prime primitive brain layer, which is where all of our impulses are coming from. It's sort of like we've got like a monkey brain with a computer stuck on it. 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 brain. It's the monkey brain steering the cortex. But the cortex is the part that tells the story of the whole thing. So we convince ourselves it's more interesting than just the monkey brain. The cortex is the part that's called human intelligence. That's like the advanced computer relative to other creatures. Other creatures do not have, really, they don't have the computer, or they have a very weak computer relative to humans. But 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, you know. But the vast majority of our intelligence will be digital. So think of it 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. And then that impulse to the cortex and tells the cortex to go satisfy that. Then a lot of a great deal of like a massive amount of thinking, like truly stupendous amount of thinking, has gone into sex. Without purpose, without provocation, without any kind of thinking has gone into sex. Without purpose, without procreation. Which is actually quite a silly action in the absence of procreation. It's a bit silly. So 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. If 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. So 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 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 that will be those steps along the way. And then ultimately, it's intended to address the existential risk associated with digital super intelligence. 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, to ride the wave of the improvement of the brain. I think the chance is above zero percent. So it's non zero. Yes, there's a chance. And that's what I've seen. Dumb and dumber. Yes. Yeah, 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. It depends on the rate of improvement of Neuralink and how fast we're able to do, make progress. You know, well, I've talked to a few folks here that are quite brilliant engineers, so I'm excited. Yeah, I think it's 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 then effectively, you can create a circuit, replace what's broken with silicon, and essentially fill in the missing functionality. And then over time, we can have, we develop a tertiary layer. So if like the limbic system is the primary layer, then the cortex is like the second layer. And I said that, you know, 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. Yeah, that's what the fun is. Absolutely. And then people generally don't lose the cortex either. Right, so they like having the cortex and the limbic system. Yeah. And then there's a tertiary layer, which will be digital superintelligence. And I think there's room for optimism given that the cortex is very intelligent and the 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 the 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 singularity and things become just very uncertain. It doesn't mean that they're necessarily bad or good, but 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. But 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. You have to have a tiny electrode. It's so small it doesn't hurt neurons, but it's got to last for as long as a person. So it's got to last for decades. 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's very heat sensitive. Then we've got to take those signals, we're going to do something with them, and then we've got to stimulate the back to so you can have bidirectional communication. 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. 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. 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. 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 large numbers of people. It needs to scale large numbers of people because I think ultimately we want the future to be determined by a large number of humans. Do you think this has a chance to revolutionize surgery, period? Neurosurgery and surgery all across? Yeah, for sure. It's got to be like Lasik. If Lasik had to be hand done, done by hand by a person, that wouldn't be great. It's done by a robot. The ophthalmologist just needs to make sure your head's in the right position and then they can 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 we think about the future of our civilization. It's 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 think it's a smart parking feature. 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. Right. 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're just really trying to make people's lives easier with autonomy. But now that you mention it, I think it will be an eye-opener to people about robotics, because they've really never seen, most people have never seen a robot. And there are hundreds of thousands of Teslas, 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 thinking with each iteration of autopilot. You can see it's uncertain about this, or it gets, 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, 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 on 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, at 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 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 as far safer than a person right now. The probability of an injury or an 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. The first time you learned to drive, probably wasn't jumping on market streets, San Francisco, that'd be crazy. You learn to drive in the parking lot, 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 kind of know where the stop street is, worst-case, you can geocode it and then use visualization to see where the line is and stop 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, how to do that. So the hardest thing is having accurate representation of the physical objects in vector space. So taking the visual input, primarily visual input, some sonar and radar, and then creating an accurate vector space representation of the objects around you. Once you have that, you can start to see the objects around you. So you can see the objects around you, an accurate vector space representation of the objects around you. Once you have an accurate vector space representation, the plan 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. Cars in like Grand Theft Auto or something, they work pretty well. They drive down the road, they don't crash, pretty much unless you crash into them. That's because they've got an accurate vector space representation of where the cars are, and then they're rendering that 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's state, driver sensing? And we have driver sensing with the torque on the wheel. That's right. 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 great. 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, we can do both at the same time. That's great. I just met with Andrew and wife of Carl Sagan, Oh yeah. who were doing it to 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 too trapped in there, like squabbles amongst humans. And just don't think of the big picture. They take civilization and not continue existence for granted. They 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 3.7 billion miles away. And as you're talking about the pale blue dot, that picture, the earth takes up less than a single pixel in that image. Yes. And 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. It's funny, the universe appears to be 13.8 billion years old. Earth is like four and a half billion years old. You know, 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 planets 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 FG 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% of Earth's gravity. We need a giant boost to get off 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, whoever was, lived out their lives. The aggregate of our joy and suffering, thousands of confident religions, ideologies, and economic doctrines, the every hunter and forager, 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. Every saint and sinner in the history of our species lived there, on a mode of dust suspended in a sun beam. 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. 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.
 The following is a conversation with Elon Musk, part two, 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 two. 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 AI.
 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.
 Yeah. Panpsychists believe that. There's a philosophical...
 How would you tell?
 That's true. That's a good point.
 I believe in scientific methods. I don't blow 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
 or the scientific method? We can dramatically improve our understanding of consciousness.
 I would be hard pressed 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 this scientific method which I very much believe in,
 where something is true to the degree that it is testably so.
 Otherwise, you're really just talking about preferences or untestable beliefs or that kind
 of thing. 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, 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, what
 consciousness feels like, it feels like consciousness is in a different dimension.
 But this could be just an illusion. If you damage your brain in some way physically,
 you damage your consciousness, which implies that consciousness is a physical phenomenon,
 in my view. The things that I think are really quite likely is that digital intelligence will
 be able to outthink us in every way, and it will suddenly be able to simulate what we consider
 consciousness to a degree that you would not be able to tell the difference.
 And from the aspect of the scientific method, it might as well be consciousness if we can
 simulate it perfectly. If you can't tell the difference,
 and this is sort of the Turing test, but think of a more sort of advanced version of the Turing test.
 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 a conversation over a phone or a video conference or something
 where 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.
 Talks like human makes mistakes like a human, and you literally just can't tell.
 Are you video conferencing with a person 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 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 the most promising, most interesting as a civilization that we should invest in?
 I think there's a 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 does not represent a public safety risk, just as there is a regulatory
 authority for the Food and Drug Administration, there's NETSA for automotive safety, there's the
 FAA for aircraft safety. Where it generally comes to the conclusion that it is important to have a
 government referee or a referee that is serving the public interest in ensuring that
 things are safe 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 it governs very slowly. And the rate of,
 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. It takes something like seat belts. It was known for a decade or more that seat belts
 would have a massive impact on safety and save so many lives and serious injuries.
 And the car industry fought the requirement to put seat belts in tooth and nail.
 That's crazy. And hundreds of thousands of people probably died because of that.
 And they said people wouldn't buy cars if they had seat belts, which is obviously absurd.
 Or look at the tobacco industry and how long they fought anything 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 the government is trying to make it work.
 How pernicious it can be when you have these companies effectively
 achieve regulatory capture of government. The bad. People in the AI community refer to the advent of
 digital superintelligence 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
 that there's some probability it will be bad, some probability it will be good.
 Or else they 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, the 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 the human mind, about the brain?
 Yeah, I think the work in Neuralink will definitely shed a lot of insight into how the brain,
 the mind works. Right now, there's just the data we have regarding how the brain works.
 It's very limited. We've got fMRI, which is that that's kind of like putting a 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 stimulation sensors.
 You want to have stimulus and response. Like if you trigger a neuron, 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 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 it's not that plastic, to be totally frank. So there's a firm structure, but nevertheless,
 there is some plasticity. And the open question is, so 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 benefit arriving from on the machine side or the
 human side? Do you see both of them working together? I actually think the machine side is
 far more malleable than the biological side by a huge amount. So it will 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
 the neuron just, it'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 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. 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 the vast majority of the adjustment will be on the machine side.
 This is just, it has to be that, otherwise it will not work. Ultimately, we currently operate on two
 layers. We have sort of a limbic, like prime primitive brain layer, which is where all of our
 impulses are coming from. It's sort of like we've got like a monkey brain with a computer stuck on
 it. 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 brain. It's the monkey brain steering the cortex.
 But the cortex is the part that tells the story of the whole thing. So we convince ourselves it's
 more interesting than just the monkey brain. The cortex is the part that's
 called human intelligence. That's like the advanced computer relative to other creatures.
 Other creatures do not have, really, they don't have the computer, or they have a very weak
 computer relative to humans. But 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, you know. But the vast majority of our intelligence will be digital.
 So think of it 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. And then that impulse to the cortex and tells the cortex to go satisfy that.
 Then a lot of a great deal of like a massive amount of thinking, like truly stupendous amount of thinking, has gone into sex.
 Without purpose, without provocation, without any kind of
 thinking has gone into sex. Without purpose, without procreation.
 Which is actually quite a silly action in the absence of procreation. It's a bit silly.
 So 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.
 If 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.
 So 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 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 that will be those steps along the way.
 And then ultimately, it's intended to address the existential risk associated with
 digital super intelligence. 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, to ride the wave of the improvement of the brain.
 I think the chance is above zero percent.
 So it's non zero.
 Yes, there's a chance.
 And that's what I've seen.
 Dumb and dumber.
 Yes.
 Yeah, 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.
 It depends on the rate of improvement of Neuralink and how fast we're able to do, make progress.
 You know, well, I've talked to a few folks here that are quite brilliant engineers, so I'm excited.
 Yeah, I think it's 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 then effectively,
 you can create a circuit, replace what's broken with silicon, and essentially fill in the missing functionality.
 And then over time, we can have, we develop a tertiary layer.
 So if like the limbic system is the primary layer, then the cortex is like the second layer.
 And I said that, you know, 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.
 Yeah, that's what the fun is. Absolutely.
 And then people generally don't lose the cortex either.
 Right, so they like having the cortex and the limbic system.
 Yeah.
 And then there's a tertiary layer, which will be digital superintelligence.
 And I think there's room for optimism given that the cortex is very intelligent and the 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 the 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 singularity and things become just
 very uncertain. It doesn't mean that they're necessarily bad or good, but 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.
 But 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. You have to have a tiny electrode. It's so small it doesn't hurt
 neurons, but it's got to last for as long as a person. So it's got to last for decades.
 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's
 very heat sensitive. Then we've got to take those signals, we're going to do something with them,
 and then we've got to stimulate the back to so you can have bidirectional communication.
 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.
 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.
 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. 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
 large numbers of people. It needs to scale large numbers of people because I think ultimately we
 want the future to be determined by a large number of humans. Do you think this has a chance to
 revolutionize surgery, period? Neurosurgery and surgery all across? Yeah, for sure. It's got to
 be like Lasik. If Lasik had to be hand done, done by hand by a person, that wouldn't be great.
 It's done by a robot. The ophthalmologist just needs to make sure your head's in the right position
 and then they can 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 we think about the
 future of our civilization. It's 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 think it's a smart parking feature. 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.
 Right. 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're just really trying to make people's lives easier with autonomy. But now that
 you mention it, I think it will be an eye-opener to people about robotics, because they've really
 never seen, most people have never seen a robot. And there are hundreds of thousands of Teslas,
 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 thinking
 with each iteration of autopilot. You can see it's uncertain about this, or it gets,
 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,
 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 on 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, at 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 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 as far safer than a person right now. The probability of an injury or an 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. The first time you learned to drive, probably wasn't jumping on market streets,
 San Francisco, that'd be crazy. You learn to drive in the parking lot, 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 kind of know where the stop street is,
 worst-case, you can geocode it and then use visualization to see where the line is and stop
 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, how to do that.
 So the hardest thing is having accurate representation of the physical objects in vector space.
 So taking the visual input, primarily visual input, some sonar and radar, and then creating
 an accurate vector space representation of the objects around you. Once you have that,
 you can start to see the objects around you. So you can see the objects around you,
 an accurate vector space representation of the objects around you. Once you have an accurate
 vector space representation, the plan 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. Cars in like Grand Theft Auto or something, they work pretty well. They drive down the road,
 they don't crash, pretty much unless you crash into them. That's because they've got an accurate
 vector space representation of where the cars are, and then they're rendering that 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's state, driver sensing?
 And we have driver sensing with the torque on the wheel.
 That's right.
 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 great. 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, we can do both at the same time. That's great.
 I just met with Andrew and wife of Carl Sagan,
 Oh yeah.
 who were doing it to 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 too trapped in there, like squabbles amongst humans.
 And just don't think of the big picture. They take civilization and not continue existence for
 granted. They 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 3.7 billion miles away. And as you're talking about the
 pale blue dot, that picture, the earth takes up less than a single pixel in that image.
 Yes.
 And 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. It's funny, the universe appears to be 13.8 billion years old. Earth is like four and a half
 billion years old. You know, 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 planets 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 FG 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% of Earth's gravity. We need a giant boost to get off 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, whoever
 was, lived out their lives. The aggregate of our joy and suffering, thousands of confident
 religions, ideologies, and economic doctrines, the
 every hunter and forager, 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. Every
 saint and sinner in the history of our species lived there, on a mode of dust suspended in a sun
 beam. 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.
 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.