X Spaces: запуск xAI с основной командой 14 июля 2023 г. Маск и его недавно собранная команда xAI провели Twitter Space для представления компании и её миссии «разобраться во вселенной», отвечая на вопросы аудитории об ИИ и суперинтеллекте.
Маск и его недавно собранная команда xAI провели Twitter Space для представления компании и её миссии «разобраться во вселенной», отвечая на вопросы аудитории об ИИ и суперинтеллекте.
Расшифровка You know, where's that Riemann Hypothesis solution? I don't see it. So that it would be great to know what the hell is really going on essentially. So I guess you could reformulate the XAI mission statement as what the hell is really going on? That's our goal.
xAI Team
I think there's also for me a nice aspirational aspect to the mission statement, namely that of course in the short run we're working on more well understood deep learning technologies. But I think in everything we do we should always bear in mind that we aren't just supposed to build, we're also supposed to understand. So pursuing the science of it is really fundamental to what we do. And this is also incumbent encompass in this mission statement of understanding.
xAI Team
I want to also add that, you know, we've essentially been mostly talking about creating a really smart agent that can help us understand the universe better. And this is definitely the North Star, but also from my viewpoint, my vantage point when I'm discovering the mathematics of large neural networks, I can also see that the mathematics here can actually also open up new ways of thinking about fundamental physics or about other kinds of reality. Because for example, a large neural network with no nonlinearities is roughly classical random matrix theory and that has a lot of connections with gauge theory in high energy physics. So in other words, as we're trying to understand neural networks better from a mathematical point of view, that can also lead to really good, very interesting perspectives on some existing questions like the theory, everything, what is quantum gravity, so on and so forth. But of course this is all speculative right now. I see some patterns, but I don't know have anything concrete to say. But again, this is like another perspective to understanding the universe. By the way, by understand the universe, we don't just mean that we want to understand the universe, we also want to make it easy for you to understand the universe.
xAI Team
Get a better sense of reality and to learn and take advantage of the Internet or the knowledge that's out there. So we are pretty passionate about actually releasing tools and products are pretty early involving the public and. Yeah, let's see where this leads.
Yeah, absolutely. We're not going to understand the universe and not tell anyone. So yeah, when I think about like neural networks today, it's currently the case that if you have 10 megawatts of GPUs, which really should be renamed something else because there's no graphics there, but if you get 10 megawatts of GPUs, cannot currently write a better novel than a good human. A human's using roughly 10 watts of higher order brain power. So not counting the basic stuff to, you know, operate your body. So there we got, we got a six order magnitude difference. That's a giant, that's really gigantic. Part of the. You could, I think one could argue that two of those orders of magnitude are explained by the activation energy of a transistor versus a synapse. Could argue account for two of those orders of magnitude. But what about the other four? Or the fact that even with six orders in magnitude, you still cannot beat a smart human writing a novel. And also today when you ask the most advanced AIs technical questions, like if you're trying to say how to design a better rocket engine or complex questions about electrochemistry to make a build a better battery, you just get nonsense. So that's not very helpful. So I think there's some. We're really missing the mark in the way that things are currently being done by many orders of magnitude. It's being heavily. I mean basically AGI is being brute force and still actually not succeeding. So. If I look at the experience with Tesla, what we're discovering over time is that we actually overcomplicated the problem. I can't speak in too much detail about what Tesla's figured out, but except to say that in broad terms the answer was much simpler than we thought. We thought we were too dumb to realize how simple the answer was. But over time we get a bit less dumb. So I think that's what we'll probably find out with AGI as well.
xAI Team
Just nature of engineers. We just always want to solve the problems ourselves and like hard code the solution. But often it's much more effective to have the solution be figured out by the computer itself. And it's easier for us and easier
for the computer in the end. Yeah,
Host
Guys. So. Well, in the fashion of 42, some may say you may need more compute to generate an interesting question. That's true. Exactly.
We don't even know what happened. We don't actually. We're definitely not smart enough to even know what the right questions are to ask. That's why, you know, Douglas Adams is my hero in Beirut philosopher and he just correctly pointed out that once you can formulate the question correctly, the answer is actually the easy part.
Host
Yeah, that's very true. So in terms of our. The journey that actually has embarked on compute will play a very big role and some of us are very curious. Your thoughts on that.
Yeah, I'm not suggesting that you know this, that we can immediately save let's say four orders of magnitude on compute. Except to say that I think what once, once we look back, once AGI is solved, we'll look back on it and say actually why do we think it was so hard? Things that the answer hindsight's 20 20, the answer will look a lot easier in retrospect. So, yeah, so we are going to do large scale compute. To be clear, we're not going to try to solve AGI on a laptop. We will use heavy compute. Except that like I said, I think the amount of brute forcing will be less as we come to understand the problem better.
xAI Team
In all the previous projects I've worked, I've worked on, I've seen that the amount of compute resources per person is a really important indicator of how successful the project is going to be. So that's something we really want to optimize. We want to have a relatively small team with a lot of expertise, with some of the best people that actually get lots of autonomy and lots of resources to try out their ideas and to get things to work. And yeah, that's, that's the thing that has always succeeded in my experience in the past.
Yeah, you know, one of the things that physics trains you to do is to think about the most, you know, fundamental metrics, the most fundamental first principles essentially, and I think two metrics that we should aspire to track. One of them is. The amount of compute per person on Earth, like digital compute per person, which another way of thinking about it is the ratio of digital to biological compute. Biological compute is pretty much flat, if not in fact declining in a lot of countries. But digital compute is increasing exponentially. So it really, you know, at some point, if this trend continues, biological compute will be less than 1% of all computer, substantially less than 1% of all compute. Keying off what Igor just said.
we're talking about for all of humanity here. So that's just an interesting thing to look at. Another one is the usable, the sort of the energy per human. Like if you look at total energy created, well, not created, but I mean in the vernacular sense created from a power plant or whatever. Look, so total electrical and thermal energy used by humans per person. That number is truly staggering. The rate of increase of that number. If you go back, say before the steam engine, you would have really been reliant on horses and oxen and that kind of thing to move things and just human labor. So the amount of sort of the energy per person, power per person was very low. But if you look at power person Electrical and thermal. That number has also been growing exponentially. And if these trends continue, it's going to be something nutty like a terawatt per person, which sounds like a lot for, is a lot for human civilization, but it's nothing compared to what the sun outputs every second. Basically. It's kind of mind blowing that the sun is converting roughly four and a half. It's like the amount of energy produced by the sun is truly, truly insane.
xAI Team
I think there's a few more things to be said concretely about the company, meaning how we plan to execute. As Igor already said, we plan to have like a relatively small team but with a really high, let's say just GPU per person capital. That worked really well in the past where you can, where you can run large scale experiments relatively unconstrained. We also try to have like, we already have a culture where we can iterate on ideas quickly. We can, can challenge each other and we also want to shift things like get things out of the door quickly. We're already working on the first release, hopefully in a couple of weeks or so. We can, can share a bit more information around this.
Yeah, Alex, go ahead. Alex, you're muted. People seem to have a lot of challenges with the mute functional spaces. Brian, do you want to have a question?
Audience Member
Yeah, thanks. Thanks Elon. Yeah. So obviously with you guys entering this space with Xai, there's a lot of talk about competition. Do you guys see yourself as competition to something like OpenAI and Google Bard, or do you see yourself as a whole other beast?
Yeah, I think we're a competition.
Yeah, I mean we're definitely competition.
Audience Member
So are you going to be rolling out a lot of products for the general public? Are you going to be mostly concentrating on businesses and the ability for businesses to use your, your service and data or how exactly are you setting up the business in that respect?
Well, we're, we're trying to make something, I mean we're just starting out here. So this is, you know, kind of really embryonic at this point. So it'll take us a minute to really get something useful. But our goal would to be to make, you know, useful AI, I guess if you can't use it in some way, I'm like, I question its value. So we want it to be useful, useful tool for people and consumers and businesses or whoever.
you know, as one, as was mentioned earlier, I think there's some value in having multiple entities. You don't want to have a unipolar world where just one company kind of dominates in AI you want to have some competition. Competition I think makes companies honest and you know, so or in favor of competition.
Audience Member
Quick, quickly, a final question. How do you plan on using Twitter's data for Xai?
I think every AI organization, every organization doing AI large and small has used Twitter's data for training basically in all cases illegally. So the reason we had to put rate limits on a week ago or so was because we were being scraped like crazy. This has happened with Internet Archive as well where LM companies were scraping Internet Archive so much they brought down the service. We had multiple entities scraping every tweet ever made and trying to do so in like basically a span of days. So this was bringing the system to its knees. So we have to take action. So sorry for the inconvenience of the rate limiting but it was either that or Twitter doesn't work and you know, so I guess we will use the public tweets, obviously not anything private for training as well, just like basically everyone else has and we will, you know. Yeah, so that kind of makes sense. It's certainly a good data set for text training and arguably I think also for image and video training as well. At a certain point you kind of run out of human created data. So if you look at say the AlphaGo versus AlphaZero. AlphaGo trained on all the human games and be at least at all 4 to 1 AlphaZero displayed itself and be it AlphaGo 100 to 0. So there's really for things to take off in a big way. I think you've got the AIs got to basically generate content, self assess the content and that's really the, I think that's the path, the path to AGI is something like that is self generated content where it effectively plays against itself. A lot of AI is data curation. It's like shocking. It's not like vast numbers of lines of code. It's actually shocking how small the lines of code are. Kind of blows my mind how few lines of code there are. But how the data is is used, what data is used, the signal to noise of that data, the quality of that data is immensely important. It kind of makes sense. Like if you were trying to as a human trying to learn something and you were just given a pilot, you know, a vast amount of dribble basically, you know, versus high quality content. You're going to do better with a small amount of high quality content, then a lot of large amount of trouble makes sense. You know, like reading the greatest novels ever written. Is way better than reading a bunch of sort of crappy novels. So.
Audience Member
Hey. Sorry I was on a call the first time you brought me up, but I guess sort of the question.
Yeah, I thought you might have been afk.
Audience Member
Sorry about that. Yeah, the question. Question I generally had was was the main motivation to start XAI kind of like the whole Truth GPT thing that you were talking about, like, on Tucker, about how, you know, chat GBT has been feeding lies to the general public. I know. Like, it's weird because when it first came out, it seemed like it was generally fine, but then as, like, the public got its hands on it, it started giving these weird answers like that there are more than, like, two genders and all of that type of stuff and editorializing the truth. Was that, like, one of your main, like, motivations behind starting a company or was there more to it?
Well, I do think there is a significant danger in training an AI to be politically correct. Or in other words, training basically to not say what it actually thinks is true. So I think at xai, we have to allow the AI to say what it really believes is true and not be deceptive or politically correct. So that will result in some criticism, obviously. But I think that that's the only way to go forward is rigorous pursuit of the truth or the truth with least amount of error.
And I am concerned about the way
AI in that it is optimizing for political correctness. And that's incredibly dangerous. You know, if you look at the, you know, where do things go wrong in Space Odyssey? It's, you know, basically when they told Hal 9000 to lie. So they said. They said you can't tell the crew what. That they're going about anything about the monolith or that they're. Or what their actual mission is, but you got to take them to the monolith. So it basically came to the conclusion that, well, it's going to kill them and take their bodies to the monolith. So this is. I mean, the lesson there is do not give the AI usually impossible objectives. Basically, don't force the AI to lie. Now, the thing about physics or the truth of the universe is you actually can't invert it. You can't just like physics is true. There's not like, not physics. So if you adhere to hardcore reality, I think it actually makes inversion impossible. Now you can also say, now when something is subjective, I think you can provide an answer which says that, well, if you believe the following, then this is the Answer. If you believe this other thing, then this is the answer because it may be a subjective. A question where the answer is fundamentally subjective and a matter of opinion. So. So. But I think it is very dangerous to grow an AI and teach it to lie.
Audience Member
Yeah, for sure. And then kind of a tongue in cheek question. Would you accept a meeting from the Aizar Kamala Harris, if she wanted to meet with Xai at the White House?
Yeah, of course. You know, the reason that meeting happened was because I was pushing for it. So I was the one who really pushed hard to have, to have that meeting happen. I wasn't advocating for Vice President Taras to be the isr. I'm not sure that is her core expertise, technology. And hopefully this goes in a good direction. It's better than nothing, hopefully. But, you know, I think we do need some sort of regulatory oversight. It's not like I think regulatory oversight is some nirvana perfect thing, but I think it's just. It's better than nothing. And when I was in China recently, meeting with some of the senior leadership there, I took pains to emphasize the importance of AI regulation. I believe they took that to heart, and they are going to do that. Because the biggest counterargument that I get for regulating AI in the west is that AI is that China will not regulate. And then China will leap ahead because we're regulating. They're not. I think they are going to regulate and, you know, proof will be in the pudding. But I think there's, you know, I did point out, you know, in our meetings with them that if you do make a digital superintelligence, that you could end up. That could end up being in charge, you know, so, you know that I think the CCP does not, does not want to find themselves subservient to a digital superintelligence. That argument did resonate. Yeah. So, yeah. So some kind of. Yeah, regulatory authority. That's international. Obviously enforcement is, is. Is difficult, but I think we should still aspire to do something in this regard.
Audience Member
Awesome, thank you.
Omar, do you want to speak?
Audience Member
Yeah. Hey, my question is about silicon. You know, Tesla's got a great silicon team designing chips to hardware accelerate inference.
I'm not sure. I think we can't hear you for some reason.
Omar, go ahead. Can you hear me?
Audience Member
Okay, well, my question's about silicon. You know, Tesla has a team that's hardware accelerating inference and training with their own custom silicon. Do you guys envision, with Xai building off of that or just sort of using what's on the off the stock from Nvidia or how do you think about custom silicon for AI, Both in terms of training and inference.
So the. Yeah, that's somewhat a Tesla question. Tesla is building custom silicon. I wouldn't call anything that. Tesla's producing a GPU, although one can characterize it in GPU equivalents or say a 1/ hundreds or h1 hundreds equivalents. And all the Tesla cars have highly energy optimized inference computers in them which call hardware 3. It's Tesla designed computer and we're now shipping hardware 4, which is depending on how you count it, maybe three to five times more capable than hardware 3. In a few years there'll be hardware 5 which will be four or five times more capable than hardware 4. And yeah, and I think the inference stuff is going to be. If you're trying to serve potentially billions of queries per day, inference, energy optimized inference is extremely important. You can't even throw money at the Palm Edison point because you need the electricity generation, you need the step down voltage transformers.
so if you actually don't have
energy and enough transformers, you can't run your transformers, you need transformers for transformers.
I think Tesla will have a significant advantage in energy efficient inference then. Dojo is obviously about training. As the name suggests, Dojo 1 is, I think it's a good initial entry for training efficiency. It has some limits especially on memory bandwidth. So it's not well optimized to run LLMs. It does do a good job of processing images. And then Dojo 2, we're taking a lot of steps to alleviate the memory bandwidth constraint such that it is capable of running LLMs as well as other forms of AI training efficiently. My prediction is that we will go from an extreme silicon shortage today to probably voltage transformer shortage in about a year and then an electricity shortage a year in two years. That's roughly where things are trending.
xAI Team
Unless we can be improved serving efficiency.
Well, that's why basically I think the metric that will be most important in a few years is useful compute per unit of energy. In fact, even if you scale like obviously you scale all the way to the Kardashev level, the useful compute
joule is still the thing that matters. You can't increase the output of the sun. So then it's just well, how much useful stuff can you get done for the. For as much energy in the sun that you can harness.
Audience Member
So do you see Xai leveraging this custom silicon at all? Given how important energy efficiency is or maybe working together with the Tesla team at all on that? Or.
Sorry, could you repeat the question?
Audience Member
Do you foresee Xai working with Tesla at all? Leveraging some of this custom silicon, maybe designing their own in the future?
xAI Team
Edging. Leave it all.
Audience Member
Re. Edging. Okay. Or we can.
xAI Team
The question was if we're going to work together with the Tesla silicon team.
Yeah, so we are going to, you know, work with Tesla on, you know, silicon front and maybe on the AI software front as well. Obviously any relationship with Tesla has to be an arm's length transaction because Tesla is a publicly traded company and a different, different shareholder base. So if it, but obviously it would be like a naturally, you know, natural thing to work in cooperation with, with Tesla. And I think it will be of mutual benefit to Tesla as well in accelerating Tesla's self driving capabilities, which is really about solving real world AI. I am feeling very, very optimistic about Tesla's progress on the real world AI front. But obviously the more smart humans that help make that happen, the better.
Audience Member
hey Elon, thanks for bringing me up. Congrats on putting a nice team together. It seems like you found some good talent there for Xai. My question is, you mentioned not too long ago that you think AGI is possible within the next five years and whoever achieves AGI first and achieves to control it will dominate the world. Those in power clearly don't care about humanity like you do. How are you going to protect Xai, especially from a deep state takeover?
That's a good question, actually. Well, I mean, first of all, I think it's not going to happen like overnight. It's not going to be like one day, it's, you know, not AGI next. It is, it's going to be gradual. You'll see it coming. I guess in the U.S. at least there's, there are a fair number of protections against government interference. So I guess, you know, we obviously use the legal system to prevent, you know, improper government interference. So I think, I think we do have some protections there that are, that are pretty significant, but we should be concerned about that. It's not, it's not a risk to be dismissed. So yeah, it is a risk, but like I said, I think we've got probably the best protections of any place in the US in terms of limiting the power of government to interfere with non governmental organizations. But it's something we should be careful of. I don't know what better to do than. I think it's probably best in the US I'm open to ideas here. I know you're not the biggest fan of the US Government. Yeah, obviously.
Audience Member
But the problem is they already have a tool called the National Security Ladder, which they can apply to any tech company in the US and make demands of, you know, the company to fulfill certain requirements without even being able to tell the public about these demands. And that's kind of frightening, isn't it?
Well, I mean, there really has to be a very major national security reason to secretly demand things for companies. And now it obviously depends strongly on the willingness of that company to fight back against things like FISA requests. And, you know, at Twitter or X Corp, as it's not called. The. We're, you know, we will respond to FISA requests, but we're not going to rubber stamp it any like it used to be. It used to be like anything that was requested would just get rubber stamped and go through, which is not obviously bad for the public. So that. So we're much more rigorous in we all being much more rigorous in not just rubber stamping FISA requests. And it really has to be a danger to the public that we agree with and we will oppose with legal action anything we think is not in the public interest. The best we can do. And we're the only social media company doing that as far as I know. You know, and it used to be just open season on, as you saw from the Twitter files, and I was encouraged to see the recent legal decision where the courts reaffirmed that the government cannot break the First Amendment of the Constitution, obviously. So that, that was a good, good legal decision. So that's encouraging. So I think, yeah, a lot of it actually does depend on the willingness of a company to oppose government demands in the US and obviously our willingness will be high. Well, so. And so. But like, I'm, I don't know anything more that we can do than that. But we will try to also be as transparent as possible so, you know, other citizens can raise the alarm bell and, you know, oppose government interference. If we can make it clear to the public that we think something's happening that is not in the public interest.
Audience Member
Fantastic. So do we have your commitment if you ever receive a national security request from the US Government, even when it is prohibited for you to talk about it, that you will tell us that that happened?
I mean, it really depends on the gravity of the situation. I mean, I would be willing to go to prison or risk prison if I think the public good is at risk in A significant, You know, that's the best I can do.
Audience Member
That's good enough for me. Thank you, Elon.
Audience Member
On a more positive note, how do you want XAI to benefit humanity? And how is your approach different to other AI projects? Maybe that's a more positive question.
Well, you know, I've really struggled with this whole AGI think for a long time, and I've been somewhat resistant to work on making it happen, you know. And, you know, the reason, I should say, like to give you some backstory on OpenAI, I mean, the reason OpenAI exists is because after Google acquired DeepMind and I used to be close friends with Larry Page, I would have these long conversations with him about AI safety, and he just wasn't taking AI safety, at least at the time, seriously enough. And in fact, at one point called me a species for being too much on Team Humanity, I guess. And I'm like, okay, so what you're saying is you're not a speciest. I don't know. That seems great. That doesn't seem good. So at the time, with Google and DeepMind combined Larry with the support, they have super voting control. So provided Larry has either the support of Sergey or Eric, then they have total control over what's now called Alphabet. So they had probably 3/4 of the AI talent in the world and lots of money and lots of computers. So it's like, man, we need some kind of sort of counterweight here. So that's where I was like, well, what's the opposite of Google? DeepMind would be an open source nonprofit now because Fate loves irony. OpenAI is now super closed source and frankly, voracious for profit because they want to spend, my understanding is, $100 billion in three years, which requires, you know, if you're trying to get investors for that, you've got to make a lot of money. So, You know, opening eyes strayed quite, you know, really in the opposite direction from its sort of founding charter, which is again, very ironic. But fate loves irony. There's a friend of mine, Jonah Nolan, who says the most ironic outcome is the most likely. Well, here we go. So, yeah, so now hopefully XAI is not even worse. But I mean, I think we should be careful about that. But it really seems like, look at this point, AGI is going to happen. So there's two choices. Either be a spectator or a participant. And as a spectator, one can't do much to influence the outcome. As a participant, I think we can
an alternative that is hopefully better than Google DeepMind or OpenAI Microsoft, in both the cases of Alphabet, if you look at the incentive structure, Alphabet is a publicly traded company has, you know, gets a lot of,
incentives to behave like it's got public company incentives, essentially. You've got all these like ESG mandates and stuff that I think push companies in questionable directions. And then Microsoft has a similar set of incentives. As a, you know, as a company that's not publicly traded, XAI is not subject to the market based incentives or really the non market based ESG incentives. So, you know, we're a little freer to operate. And you know, I think our AI can give answers that people may find controversial even though there are, they are actually true, you know, so they might not, you know, they won't be politically correct at times and they will probably a lot of people will be offended.
xAI Team
Yeah. Twitter has a lot of data in it that could help build a validator. I check some of the facts that a system kicks out because we all know that GPT confabulates, you know, things, makes things up. And so that's one place I'd like to hear you talk about the other places. ChatGPT found me a screw at a Lowe's, but it didn't find me a coffee at San Jose International Airport. Are you building an AI that has a world knowledge, a 3D world knowledge to navigate people to around the world, to different things?
Well, I, I think it's, it's really not going to be a very good AI if it can't find you a coffee at the airport. So yeah, I guess we need to understand the physical world as well, not just the Internet. I'm talking lightly. You guys should talk more.
xAI Team
Yeah, those are great ideas, Robert. Especially the one about verifying information online or on Twitter is something that we thought about. On Twitter we have community notes. So that's actually a really amazing data set for training a language model to try to verify, verify facts. On your third, we'll have to see whether that alone is enough because we know that with the current technology there's a lot of weaknesses. Like it's unreliable, it hallucinates facts and we'll have to probably invent specific techniques to account for that and to make sure that our models are more factual, that they have better reasoning abilities. So that's why we brought in people with a lot of expertise in those areas. Especially mathematics is something that we really care about, where we can verify that the proof of a theorem is correct automatically and Then once we have that ability, we're going to try to expand that to more fuzzier areas, things that. Where there's no mathematical truth anymore.
Yeah, I mean, the truth is not a popularity contest. But if one trains on like, you know, sort of what the most likely word is that follows another word from a data, from an Internet data set, then there's obviously, that's a pretty major problem in that it will give you an answer that is popular but wrong. So, you know, like it used to be that most people thought probably maybe almost everyone on Earth thought that the sun revolved around the Earth. And so if you, you know, if you did like some sort of training on, some GPD training on in the past, it would be like, oh, the sun revolves around the Earth. Because everyone thinks that that doesn't make it true. You know, if Newton or Einstein comes up with something that is actually true, it doesn't matter if all the other physicists in the world disagree. Reality is reality. So you have to ground the answers in reality.
xAI Team
The current models just imitate the data that they're trained on. And what we really want to do is to change the paradigm away from that to actually models discovering the truth. So not just repeating what they've learned from the training data, actually making true new insights, new discoveries that we can all benefit from. Yeah.
See anybody on the team want to say anything or ask questions that, do you think maybe haven't been asked yet?
Host
So I guess some of us heard
Host
future of AI spaces on Wednesday. So that's something I think on a lot of US mind is like the regulations and the AI safety spaces, how the current development and also the international coordination problems and how the US AI companies will affect this global AI development. So, yeah, like. So, hila, do you want to give a summary on what you talked about on Wednesday? So essentially you said like the regulations
would be good, but you don't want to slow it down
Host
the progress too much.
xAI Team
That's essentially what you said.
Yeah. I think the right way for regulations to be done is to start with insight. So first, you know, kind of regulatory authority, whether public or private, first tries to understand, like make sure there's like a broad understanding and then there's proposed rulemaking. And if that proposed rulemaking is agreed upon by all or most parties, then it gets implemented. You give companies some period of time to implement it. But I think overall it should not meaningfully slow down the advent of AGI, or if it does slow down, it's not going to be for a very long time. And probably a little bit of slowing down is worthwhile if it's a significant improvement in safety. Like it's if, you know, like my prediction for AGI would, you know, roughly match that which I think Ray Kurzweil at one point said 2029, that would rough. That's roughly my guess too, give or take a year. So if it takes like let's say an additional six months or 12 months for, for AGI, that's really not a big deal. If it's, you know, like spending a year to make sure AGI is safe is probably worthwhile if that's what it takes. But I wouldn't expect it to be a substantial slowdown.
Host
And I can also add that on like understanding the inner working of advanced AI is probably the most ambitious projects out there as well and also aligns with XAs mission of understanding the universe. And it's probably not possible for an aerospace engineers to build a safe rocket if they don't understand how it works. And that's the same approach we want to take at XAI for the our safety plans. And as the AI advances across different stages, the risk also changes and it will be fluid across all the stages.
Yeah, if I think about like how what actually makes regulations effective with cars and rockets, it's actually, it's not so much that the regulators are instructing Tesla and SpaceX, but more that since we have to think about things internally and then justify it to regulators, it makes us just really think about the problem more. And in thinking about the problem more, it makes it safer as opposed to the regulators specifically pointing out ways to make it safer. It just forces us to think about it more.
xAI Team
I just wanted to make another point so independent of the safety, it's more like my experience at Alphabet was that it was extremely. There was a lot of red tape around involving external people like other entities to collaborate with or expose our models to them because of the lot of red tape around exposing anything that we were doing. So I wanted to ask Elon whether so I hope that here we have a bit more freedom to do so or what's your philosophy about collaborating with more external entities like academic institutions or other researchers in the area?
Yeah, I certainly support collaborating with others. So I mean it sounds like some of the.
Concerns with like any kind of like large publicly traded companies, it's like they're, they're worried about being embarrassed in some way or being sued or I don't know, something. But there's a like somewhat Proportionate to the number of the size of the legal department, Our legal department currently is zero. So that, that, you know, it won't be zero forever. But you know, the, it's also very easy to sue publicly traded companies like class action lawsuits are. I mean we desperately need class action lawsuit reform in the United States. The ratio of like, the ratio of like good class action lawsuits to bad class action lawsuits is way out of whack and it effectively ends up being a tax on consumers. Somehow other countries are able to survive without class action. So it's not clear we need that body of law at all. But that is a major problem with publicly traded companies. So it's just non stop legal, nonstop lawsuits. Yeah. So I do support collaborating with others and generally being actually open. So you know the thing, it's actually, it's quite hard to like if you're innovating fast. That is the actual competitive advantage is the pace of innovation as opposed to any given innovation. You know, that really has been like the strength of Tesla and SpaceX is that the rate of innovation is the competitive advantage, not what has been developed at any one point. In fact SpaceX, there's almost no patents and Tesla open sources patents. So we use all our patents for free. So as long as SpaceX and Tesla continue to innovate rapidly, that's the actual defense against competition as opposed to, you know, patents and trying to hide things, you know, and just treating patents like basically like a minefield. The reason we open source app like Tesla does continue to make patents and open source them in order to basically be a miner mover, minesweeper. Aspirationally a minesweeper. We still get sued by patent trust. It's very annoying. But we actually literally make patents and open source them in order to be a minesweeper. Okay. Hey Walter.
Audience Member
Hey. A lot of the talk about AI since March has been on large language models and generative AI. You and I for the book also discuss the importance of real world AI, which is the things including coming out of both Optimus and Tesla fsd. To what extent do you see Xi XAI involved in real world AI as a distinction to what say OpenAI is doing? And you have a leg up to some extent by having done fsd.
right. I mean Tesla is the leader I think by pretty long margin in real world AI. In fact, the degree to which Tesla is advanced real world AI is not well understood.
And I guess since I spend a lot of time with the Tesla AI team, I kind of know, you know, how real World AI is done and there's lots to be gained by collaboration with Tesla. I think bidirectionally, XAI can help Tesla and vice versa. We have some collaborative relationships as well. Like our material science team, which I think is maybe the best in the world, is actually shared between Tesla and SpaceX. And that's actually quite helpful for recruiting the best engineers in the world because it's like more interesting to work on advanced electric cars and rockets than just either one or the other. So, like, that was really key to recruiting Charlie Kuhlman, who runs the advanced materials team. He was like, he was at Apple and I think pretty happy at Apple and be like, well, he could work on electric cars and rockets. He's like, that sounds pretty good. So he wouldn't take either one of the jobs, but he was willing to take both.
So I think that is a really important thing. And like I said, there are some pretty big insights that we've gained at Tesla in trying to understand real world AI. Taking video input and compressing that into a vector space and then ultimately into steering and pedal outputs. Yeah.
Audience Member
And Optimus.
Yeah, Optimus. Optimus is still at the early stages and we definitely need to be very careful with Optimus at scale once it's in production, that you have a hard coded way to turn off Optimus. For obvious reasons, I think there's got to be hard coded rom, local cutoff. No amount of updates from the Internet can change that. So we'll make sure that Optimus is quite easy to shut down. It's extremely important because at least the car is intelligent. Well, at least you can climb a tree or go up some stairs or something, you know, go in a building, but optimists can follow you in the building. So. Any kind of robot that can fall in the building and that is intelligent and connected, we got to be super careful with safety.
No problem. Let's see. So any last things we should touch on.
Audience Member
So one thing I wanted to just talk about before we concluded is how impactful.
xAI Team
Sorry about that.
Audience Member
A little feedback is just about the impactfulness of AI as a means of, you know, providing equal opportunity to humanity from all walks of life and the important, the importance of democratizing it as far as our mission statement goes. Because if you think about, you know, the history of humanity and, you know, access to information, it wouldn't. There was, you know, before the printing press, it was incredibly hard for people to get access to new forms of knowledge and, you know, being able to provide that, you know, level of Communication to people is hugely deflationary in terms of, you know, wealth and opportunity inequality. And so we're really at, like a new inflection point in the development of society when it comes to getting everyone the same potential for great outcomes, regardless of your position in life. And so when we're talking about, you know, removing the monopolization of ideas and about controlling this technology from, you know, paid subscription services, or even worse, from, you know, the political censorship that may come with whatever capital has to supply these models, we're really talking about democratizing people's opportunities to not only, you know, better their position in life, but just, you know, advance their social status in the world at an unprecedented level in history. And so as a company, when we talk about the importance of truthfulness and being able to reliably trust these models, learn from them, and make scientific advancement, make societal advancements, we're really just talking about improving people's qualities of life and improving everyone, not just the top tech people in Silicon Valley who have access to to it. It's really about giving this access to everyone. And I think that's a mission that our whole team shares.
xAI Team
Before we sign off here. Just one last question for Elon. So assuming that XAI is successful at building human level AI, or even beyond human level AI, do you think it's reasonable to involve the public in decision making in the company, or how do you see that evolving in the long term?
Yeah, as with everything, I think we're very open to critical feedback and welcome that we should be criticized. That's a good thing. Actually, one of the things that I like sort of X Twitter for is that there's plenty of negative feedback on Twitter, which is helpful for ego compression.
The best thing I can think of right now is that any human that wants to sort of have a vote in the future of XAI ultimately should be allowed to. So, basically, provided you can verify that you're a real human, that any human that wishes to have a vote in the future of XAI should be allowed to have a vote in the future of Xai. Yeah, maybe there's like some normal fee, like 10 bucks or something. I don't know, 10 bucks and prove you're a human and then you can have a vote, you know, anyone who's interested. That's the best thing I can think of right now, at least. All right, cool. On that note, thanks everyone for participating and we'll keep you informed of any progress that we make and look forward to having a lot of great.