OpenAI SHOCKS Everyone "GODLIKE Powers" and MAGIC Abilities In New AI Prediction

Okay, so there was another statement by an OpenAI employee that genuinely did shock me because it specifically altered my timelines in terms of when we're probably going to get AGI and a technology that we didn't even consider real a couple of years ago, which is artificial superintelligence that maybe some people didn't even consider. So this OpenAI researcher has released essentially a list of things that he is predicting, and the things that he's predicting are quite intense. So we're going to go through this list because there actually is quite a lot of things to talk about and a lot of things that you do need to be aware of, because a lot of people that saw this list thought about a few things, but didn't think about how the industry is going to evolve as a whole. So let me tell you why this was actually genuinely a shocking statement, because there was one of them that I saw, and I was like, okay, that is a super big deal. And that just completely changes my timeline. So what? One of the things that he did state is essentially probably there will be AGI coming soon, and that's any year now. And this is something that unfortunately doesn't surprise me. If you've been paying attention to this space, you'll know that we've had many different instances and inklings of AGI, and essentially many of us do kind of feel like we're on the edge of our seat because we know that AGI is just around the corner. Now. That's for a variety of factors, like the fact that OpenAI has been, you know, in a really, really strange position with it, you know, delaying releases on multiple products with it, having the Sam Altman firing, and other companies are also having major breakthroughs and working on AGI as well. So literally any year now, we could definitely be getting AGI, not only just because of the way that these companies are, but the significant investment that they're also getting, too. Now, he also spoke here, and you can see that he responded to someone's question in terms of the percentage of AGI. So he said, why do you have a 15% chance for 2024 and only an additional 15 for 2025? Now, I do think we get AGI by the end of 2025, or at least, you know, some kind of lab makes an insane breakthrough, and we have AGI by the end of 2025. That's just what I kind of believe. But he says, do you really think that there's a 15% chance of AGI this year? And he says, yes, I really do. I'm afraid I can't talk about all of the reasons for this. You know, I work at OpenAI but but mostly it should be figureoutable from the publicly available information which we've discussed several times on this channel. Now, my timelines were already fairly short. 2029 is the median, which is essentially the most common. And when I joined OpenAI in early 2022 and things have gone mostly as I've expected, I've learned a bunch of stuff, some of which updated me towards and some of which updated me downwards. As for the 15%, 16% thing, I don't feel confident that those are the right numbers. Rather those numbers express my current state of uncertainty. I could see the case for making 2024 number higher than the 2025, of course, because exponential distribution vibes if it doesn't work now, then there's evidence it won't work next year. And I could also see the case for making 2025 year higher. Of course projects take twice as long as one expects due to the planning fallacy. So essentially he's stating that 15% this year, 30% chance next year. But of course he's saying that he could be completely wrong. Now with AGI AI predictions, of course it's anyone's guess, but. But this prediction by Ark Invest essentially is a good visual media to kind of look at when you're looking at how AGI is going to progress in the next couple of years. Now something I do want to say about this is the exponential nature of things because they also do take that into account with the fact that essentially it was predicted for the end of the 2029 or 2030, which is where many people have predicted it. I'm going to get into the next point in a moment, which is really what just kind of shocks me. But essentially you can see here that every time as time is going down, you can see that we're going down like this way as the forecast error continues. It seems that by 2027. But of course we can see that there are these huge drop offs where technology kind of just keeps on dropping off. So of course it's like exponential, it's kind of like S curve growth where you kind of grow up and then you kind of plateau for a little bit and then you kind of get that next boom once there is that next thing and we're kind of seeing like an inverted S curve on that graph as well. And I know I showed this in a previous video, just wanted to show again. So you guys can visualize where things are going. So the median, the most common prediction is 2029. Some people are predicting next year and there are a few small reasons why. But I definitely do believe that if anyone is going to get to it, it will be OpenAI. Obviously because of the kind of talent that they have, the kind of, you know, researchers that they have. It's a unique team and OpenAI's researchers are some of the most sought after talent. Like, you know, essentially it's so crazy that, you know, I think there was someone recently that was hired from Google that went to a different company and then Google started paying the person four times more. Just because AI researchers are so in demand right now, because it's such a competitive space that there is one tweet that I do I'm going to come back to again that I think you guys need to understand that if someone develops AGI, I think you guys have to understand that it's going to be a winner takes all scenario because it's only a race until one company reaches AGI. Once that happens, the distance to their competitors is potentially infinite. And it will be noticeable, for example, raising a quarter trillion of the US gdp. Now, of course, some people are stating that this is where OpenAI has already achieved AGI. They're just trying to raise, raise compute because they realize that we're going to need a lot more compute for this kind of system. But others may disagree and I kind of do agree that potentially they probably have internal AGI but just need more compute to actually bring the system to reality. Because certain things they just simply can't test because they're trying to run GPT4. They're also trying to run some other systems like Sora. They're also trying to give some of their compute to super alignment. So that is a thing as well. Now this is the statement that really did shock me, okay? And this is why my timelines got updated, because it changes everything, okay? So it said, he says probably whoever controls AGI will be able to use it to get to artificial super intelligence shortly thereafter. Maybe in another year, give it or take a year. Now you have to understand that AGI is essentially a robot that is apparently as good as all humans. Pretty much any task, okay? So pretty much any task you can think of that can be done in a non physical realm. And AGI is going to be able to be better than 99% of humans, okay? According to DeepMind's levels of AGI paper. And essentially right now we have GPT4 which is a low level AGI. So when we do get that AGI system, it's going to accelerate everything because it means that we can just duplicate researchers, we can duplicate mathematicians, we can duplicate people doing a whole bunch of stuff, okay? And essentially this is crazy, because artificial superintelligence is completely next level. Artificial superintelligence is an intelligence that is so smart that it will be able to just make consistent breakthroughs, and it's going to fundamentally change our understanding of everything we know, because it's going to be that smart, okay? And that is, of course, a problem, because of course, there's alignment problems and stuff like that. But the problem is that artificial superintelligence is something that people didn't really even talk about because it's so. It's seemingly so far away. But they're stating that whoever controls AGI will be able to use it to get to ASI shortly after. So if it's a true AGI, like a really good one, getting to ASI won't take that long. And that is a true statement and something I didn't think about that much. But it's crazy, because superintelligence. OpenAI have openly stated that superintelligence will be the most impactful technology humanity's ever invented and could help us solve many of the world's most important problems. But the vast power of superintelligence could also be very dangerous, and it could lead to disempowerment of humanity or even human extension. And it states that while superintelligence seems far off now, we believe it could arrive this decade. And that's why this is kind of shocking, because OpenAI are saying that, you know, okay, some people think that AGI is going to be by 2029, but they're stating that, not AGI by 2029. We state that superintelligence could be here by the end of this decade. So superintelligence could be here, which means that, you know, if we take a look and we kind of, like, look at the actual, you know, data, and we think, okay, what's actually going on here? We could get AGI realistically by 2026, then we could get AGI by 2029. That's something that could happen due to the nature of exponential growth and. And these timelines and OpenAI stated that themselves, so that's why they're also actually working on that kind of alignment, because they know that it is very, very soon. Now, in addition, if you want to talk predictions, you have to call on Reiko as well. Essentially, he's a futurist and he has made a lot of predictions, 147, and there's an 86% win ratio, I guess, whatever you want to call it. Now, of course, some people have debated whether or not this ratio is as high as he claims, but I would say that his predictions have come true a decent amount. Now, essentially his prediction on AGI is that artificial intelligence will achieve human level by 2029, which is once again still going to be pretty crazy, even if it does happen at 2029. Because if we take a look at it, because I remember Elon Musk stated that by 2027, everyone's timelines is getting shorter and shorter by the day. And we do know that if we take a look at what's actually going on right now, if we had AGI within two years, it's something that genuinely wouldn't surprise everyone, especially with what we saw with Sora. Now, another thing about, you know, Ray Kurzweil that he actually stated that was actually quite shocking. And this is why I don't think you guys understand the kind of world that we could be living in if we actually do get AGI and then ASI is because he's stating that, you know, there's a possibility that we might achieve immortality by the year 2030. And that's because, of course, we are, like, doing well in terms of, you know, longevity research and that kind of stuff. But if we do have artificial superintelligence, it's going to allow us to do a lot of things, like a lot of breakthroughs that are just going to completely change everything. And that's why this is so shocking, because I didn't realize that it could only take a year. I don't know. I mean, I think that maybe people aren't thinking about things such as, you know, the actual compute, the actual, you know, laws in place that might try to regulate this kind of stuff into the ground. The kind of. Maybe there's going to be some kind of, I guess you could say financial crashes or essentially other things that could potentially stop this, but provided everything is smooth, like there's no, you know, Black Swan event, there's no, like, bubonic plague. The world doesn't need to go into a shutdown and age. Our research isn't kind of delayed. ASI by the end of the decade is a pretty scary thing to think about. Okay? And that is why I stated that this genuinely did shock me. And one of the craziest things as well, like I said, I was Going to come back to this. Okay, how on earth do other companies catch up? Think about this. Okay, so let's say you're OpenAI, okay? You are working on artificial general intelligence. You do it one day, you wake up your researchers and your whole team is like, look, we've done it, we've achieved AGI, we've benchmarked it on all of this. It's 99% on this, on that and that and that. We've done it, we've achieved AGI. Boom. Okay, how on earth do other companies catch up? Because the moment you get AGI, you can use it to, I guess you could say, get towards asi and you know, you immediately get like your company. Your company just scales like 10x overnight or even 100x overnight because all you need to do is get the AGI to be able to do certain things. And you know it's going to be relatively cheap to you in terms of hiring another person that you'd have to pay like a million a year. With OpenAI, you could essentially have these super powerful researchers doing tons and tons of alignment research, ASI research, and your company could get an additional 100 employees every day. As long as you're scaling with compute. How on earth do other AI companies catch up to a company that basically achieved escape velocity? And I don't think they will. I genuinely don't think that other companies will catch up unless they quickly, unless somehow it leaks and the AGI tech is widely distributed. And then of course, when I say AGI tech, I'm actually talking about the fact that the agitech is going to be the research papers and the research behind it, not OpenAI giving you restrained access like they do with GPT4. Because the version that we even get a very, very nerfed down model to what the raw capabilities of the models offer. So essentially this is some of Anthropic's pitch deck. When they wanted to raise money in 2023 and they basically said that we believe that companies that train the best 2025-2026 models will be too far ahead to for anyone to catch up in subsequent cycles. And if you don't know who Anthropic are, they're a big AI company that is kind of competing with OpenAI. Some of the OpenAI researchers did leave to create Anthropic because they wanted to focus on safety. But the point here is that I don't think they catch up. And it does make sense. If you have a company that has AGI, they have arguably the best technology in the last 20 years. And with that, they can grow their company exponentially. So I don't think people catch up. I think it's just they're going to be so far gone that. That it's going to be pretty crazy to see what happens. And I think the reason that this is a thing is because this is why people are stating that OpenAI have achieved AGI and they're currently using it to develop things like Sora and stuff. And if that is true, it kind of does make sense, because Sora definitely blew my hat off. Like, it's just like, whoa. Even as someone who looks at AI all the time, when I saw that, I was like, whoa, okay, I didn't think we were that close. But, yeah, it's definitely pretty crazy. And it goes on. Okay, so here it states godlike powers. Okay, so it says, probably whoever controls asi. Listen to this. This is the craziest bit that. I was reading this and I was like, is this even real? Am I even living in a reality right now? It says, probably whoever controls artificial superintelligence will have access to a spread of powerful skills and abilities that will be able to build and wield technologies that seem like magic to us, just as modern tech would seem like magic to medievals. This will probably give them godlike powers over whoever doesn't control asi. So they. That brings an important question. Do you think OpenAI, let's say they have ASI, they have it aligned. Do you think OpenAI are going to distribute ASI, or are they just going to patent all the technologies as a kind of subsidiary of OpenAI? Because if they have ASI and nobody else has it, that's going to be the most valuable thing on the planet. And if they're able to distribute cure, if they're able to distribute new technology, I mean, that's going to make the company super, super, super valuable. Because like. Like, it states here, they're probably going to give them godlike powers over anyone who doesn't control asi, because that level of smartness is unfathomable. Like, it's very hard to conceptualize how smart it is, because according to several reports and researchers and stuff like that, it's basically like trying to explain economics to essentially a bee. Like, you know, a bee, the thing that buzzes around. Try to explain economics to that. It's very hard to conceptualize how you'd even begin to explain that to a bee. I mean, first you'd have to teach. Teach it English. Then you'd have to teach it so many other different concepts and that is going to be something that is pretty, pretty crazy. I mean, I mean, trying to even teach it abstract concepts. So whilst this does seem good and whilst, you know, godlike powers and stuff like that, and you know, which is why all these companies are racing to achieve AGI because they know once that is there, it's like you gain an instant 100x speed boost in this kind of race. The problem is, is that there is a black box problem and a lot of people are starting to forget about this problem. As we edge closer and closer towards the edge of this huge cliff that we could be on is the fact that it states in general, there's a lot we don't understand about modern deep learning. Modern AIs are trained, not built, programmed. We can't theorize, for example, that they are generally robustly helpful and honest instead of just biding their time. We can't check. So the problem here is that we don't know how these AI models work. We actually don't know how to what's inside them. We don't know how everything is going together. It's not like you write a code and you understand exactly how the code works. This is not how these AI models are going to be. And in the future it's going to be a bigger problem because if we're growing an AI, which is what some researchers have claimed, which is essentially, that would be a more accurate description, if we're doing that, how on earth are we then going to understand really these even super intelligent systems if we don't really understand the ones that we have now? So it's pretty crazy. It's, it's generally like, like I'm trying hard to put it into words, but it is a very, very giant problem that people are trying to solve. And of course, here's we have this. Okay, so the alignment problem. Further, currently no one knows how to control artificial superintelligence, which is true, and they are working on it. This is what OpenAI is currently working on and it says if one of our training runs turns out to work way better than we expect, we'd have a rogue artificial superintelligence on our hands and hopefully it would have internalized enough human ethics that things would be okay. And that's a crazy statement. I don't care what you say, that is insane because he's basically saying that, look, if our training runs work out to be better than we expect, unfortunately, we're going to have a rogue ASI on our hands because we don't know how to align it. They're basically saying, look, if we train the next model and it's super smart or artificially super intelligent, which I don't think it will be, I do think that you need a ton of compute just like how you scaled things up with before. It says hopefully. We're just basically just hoping that it's not crazy. Okay. And that is quite scary that, you know, hope is mentioned here. So it says there are some reasons to be hopeful about that, but there are also some reasons to be pessimistic. And the literature on this topic is small and pre pragdomatic, which is of course true. Then of course we have Sam Altman, which is a great clip which you guys should take a look at because he actually talking about the alignment problem.

Is like, we're gonna make this incredibly powerful system and be really bad if it's doesn't do what we want or if it sort of has, you know, goals that are either in conflict with ours. Many sci fi movies about what happens there, or goals where it just like doesn't care about us that much. And so the alignment problem is how do we build AGI that does what is in the best interest of humanity. How do we make sure that humanity gets to determine the, you know, the future of humanity? And how do we avoid both like accidental misuse, like where something goes wrong that we didn't intend, intentional misuse, where like a bad person is like using an AGI for great harm, even if that's what other person wants. And then the kind of like, you know, inner alignment problems where like, what if this thing just becomes a creature that views us as a threat? The way that I think the self improving systems help us is not necessarily by the nature of self improving, but like we have some ideas about how to solve the alignment problem at small scale. And we've been able to align OpenAI's biggest models better than we thought we would at this point. So that's good. We have some ideas about what to do next. But we cannot honestly look anyone in the eye and say we see out a hundred years how we're going to solve this problem. But once the AI is good enough that we can ask it to like, hey, can you help us do alignment research? I think that's going to be a new tool in the toolbox.

So essentially in that clip, Sam Altman actually does talk about how they're going to use AI as an internalized version of maybe an AGI or narrow AI that's able to really, really understand how to align these AI systems. And of course he does talk about the fact that we could have an AI that just eventually evolves into some kind of creature that just does its own thing. And that's pretty scary coming from someone who's the CEO of a major company that is building some of the most impactful technology that we will have in our lifetimes. And essentially, of course here we talk about the best plan and it says our current best plan, championed by the people winning the race to AGI, is to use each generation of AI systems to figure out how to align and control the next generation. And this plan might work, but skepticism is warranted on many levels. So OpenAI did actually talk about their approach to this and I think it's important to actually look at this because their goal is to build a roughly human level automated alignment researcher and then basically saying that we can then use vast amounts of compute to scale our effort and iteratively align superintelligence, superintelligence being that crazy smart level AI system that's going to have goals beyond our understanding. And essentially they're saying to align the first automated alignment researcher, we're going to need to develop a scalable training method, validate the resulting model and stress test the entire alignment pipeline. So of course they're going to do adversarial testing when essentially we're going to test the entire pipeline by basically stating that they're going to try to just see what kind of goes wrong, but in a kind of sandbox environment and of course try to detect how things would go wrong. So I'm guessing that this is one of their approaches. And of course they've shown that this kind of does work. So essentially there's a thing called weak to strong generalization, eliciting strong capabilities with weak supervision. So I'm going to show you guys that page now and essentially here you can see they talk about the super intelligent problem. And of course super intelligent is a big problem. And this is actually pretty recent, which is quite interesting. This was December 14, 2023. So around two, three months ago they said, we believe superintelligence and AI vastly smarter than humans could be developed within the next 10 years. However, we don't know how to reliably steer and control superhuman AI systems. So solving this problem is essential for ensuring that even the most advanced AI systems are beneficial to humanity. Just going to zoom in here. We formed the Sum Alignment team earlier this year to solve this problem. And today we're Releasing the team's first paper, which introduces a new research direction for officially solving superhuman models. So basically, they state that future AI systems will be capable of extremely complex and creative behaviors that will make it hard for humans to basically look over them and watch and understand. For example, superhuman models may be able to write millions of lines of code, potentially dangerous computer code that will be very hard for even expert humans to understand. So essentially, they made this kind of setup here. And with this setup, they say, to make progress on this core challenge, we propose an analogy we can empirically study today. Can we use a smaller, less capable model to supervise a larger, more capable model? So you can see here we've got traditional machine learning where we have the supervisor looking at a student which is not as smart as them, but it isn't too vastly smart, smarter. Then we have Super Alignment, which is of course, where essentially the human researcher is trying to supervise a student that is way smarter than it. That's where you can see the robot that's just above this human level. You can see here in this diagram. And it's like, how on earth is that supposed to work? What they're trying to do is like, look, okay, if we can get a smaller robot, a smaller AI system to supervise a larger AI system that's beneath human level, hopefully we can scale this progress. And then when we get to this level of Super Alignment, we hopefully that thing kind of works. And essentially what they did was they did this. They said, when we supervise GPT4 with the GPT2 level model using this method on NLP tasks, the resulting model typically performs somewhere between GPT3 and GPT 3.5. And it says we were able to recover much of GPT4's capabilities with only much weaker supervision. So it says this method is a proof of concept with important limitations. For example, it still doesn't work on ChatGPT preference data. However, we also find signs of life with other approaches that, such as optimal early stopping and bootstrapping from small to intermediate to large models. So essentially this is just their first paper on kind of thinking how on earth they could even try and solve this. But I do think that this is something that is important. Now, of course, this is the problem. Okay? It says, for one thing, there is an ongoing race to AGI with multiple mega corporations participating, and only a small fraction of their compute and labor is going towards alignment and control research. And one worry is that they aren't taking this seriously enough. Now, basically, you know the slide just before that. If you saw what OpenAI said, I'm not sure on that page somewhere, OpenAI said that 20% of their overall compute is going to safety research. Which does make sense because guys, if you haven't heard of the elephant in the room, the elephant in the room is that essentially if these super intelligent systems don't work out, we all die. And of course you might be thinking, how on earth do we all die? I could play a clip, but essentially you just have to think about it like this. Okay? You know how ants, right, just walk around, they do their thing. Imagine if an ant created a human and then humans start creating highways as a result of humans creating highways. We destroy ant colonies because we need to remove their environment in order to place down a highway, we need to place down homes. And we just see ants as a minor inconvenience. And because of that, of course ants die in the process. And some people are speculating that this is going to be the same with artificial intelligence. And we have no idea if this is going to be true or not, because the only way to find out is to do it. And if we do it and we all die, then I guess we're never going to really know because we're all dead. So. So as horrible as that is, the point I'm trying to make here as well is that all these companies are now placing their chips on AGI because they've realized that yo, this is this next technology. Whoever holds this key is going to pretty much control, I think, a lot of the world's resources. Because if you have an intelligent AI system and you just ask it, you know, how do we become the most valuable company in the world? It's going to get it right. Like, I mean, if it's smarter than us, it's going to get it right. So however long it's going to take, that's going to be an interesting thing. So Meta's going all in. This is Mark Zuckerberg stating that his company is just going all in on AI.

Hey everyone. Today I'm bringing Meta's two AI research efforts closer together to support our long term goals. Building general intelligence open, sourcing it responsibly and making it available and useful to everyone in all of our daily lives. It's become clearer that the next generation of services requires building full general intelligence, building the best AI assistants, AIs for creators, AIs for businesses and more. That needs advances in every area of AI, from reasoning to planning to coding to memory and other cognitive abilities. This technology is so important and the opportunities are so Great that we should open source and make it as widely available as we responsibly can so everyone can benefit. We're building an absolutely massive amount of infrastructure to support this. By the end of this year, we're going to have around 350, 50,000 Nvidia H1 hundreds, or around 600,000 H100 equivalents of compute, if you include other Jeep. We're currently training Llama 3 and we've got an exciting roadmap of future models that we're going to keep training responsibly.

So that just shows you that all of these companies are truly just pouring billions of dollars into this. And the crazy thing is that they're making breakthroughs, okay? It's not just like they're doing this, just fun. These guys are making breakthroughs. You can see that recently they made a technical breakthrough. This is a meta, by the way. This is a company, private company, called Magic that could enable active reasoning capabilities similar to OpenAI's Q star model, which was apparently a crazy, crazy breakthrough. And this is why I state that timelines are getting shorter and shorter. We have people stating crazy, crazy things. And of course, this once again brings us back to the Moloch problem, which is essentially if AGI is going to be any year now and if, of course, timelines are getting shorter because whoever controls AGI is going to be able to get to ASI shortly thereafter. We have this problem of safety research being an issue. And of course, some people even left OpenAI, the people who made anthropic, Dario Amodei, who left OpenAI to start anthropic because he wanted to focus on safety. They even recently did a paper on sleeper agents. I might include a clip from the video where I talked about that and why that was really bad and why everyone missed the mark on that. And some people were stating that Lamal, this is just dumb, da da, da da. But essentially we do have a problem on our hands because the timelines every day seem to be getting shorter and shorter. Whether it be an OpenAI employee where. Whether it be a company making a private breakthrough that enables active reasoning. I think it's not smart to underestimate the fact that AGI will be used to get to ASI shortly thereafter. And this statement, okay, the fact that whoever controls ASI will have access to a powerful skills and ability that will seem like magic to us, just like modern tech would seem like magic to medievals, isn't to be underestimated. Because if we think about it like this, okay, this is why superintelligence is so crazy. If we go back to, for example, you know, when they just had castles and, you know, the medieval times or whatever, if we just go back to that time and if, you know, we asked them, how would you defeat this army in the future? Okay, let's say, how would you defeat this army in the future? They would say, oh, we'd get our cannonballs, we'd get our bow and arrows, and we'd be able to defeat them. But they wouldn't because we'd have tanks and we'd have planes, and we have this advanced level of technology that would just simply destroy anything that they'd ever have. And that's a problem with artificial superintelligence, if you're trying to think of something that is very hard to conceptualize. So, I mean, all of the current tech that we do have, like, if you saw an iPhone, you put it back 100 years, it would seem like magic. Like, if you saw a drone, it would look like magic. I mean, it's pretty crazy, okay? And we do know that that is 100 years ago without artificial superintelligence. So you can imagine how crazy things are going to look like. I mean, I genuinely can't even imagine to believe what the future is going to look like. Are we going to be, you know, all immortal? And, I mean, how is the timeline going to be? I think either one thing happens. Either it comes either faster than we think or later than we think. So I don't think it comes on time because I do think there's always certain factors that people aren't thinking about. And of course, who knows, Maybe we'll hit a wall. Maybe AGI doesn't come later down the line because we figure out that there's some kind of war that we can't get past and requires more years of breakthroughs. And GPT4, we're kind of stagnant at that for a bit. But it will be interesting to see where we do go and how these timelines do evolve, because things are moving rapidly. And if you did enjoy this, it's important to subscribe to the channel because every day I release a video on the most important and most pressing AI news that you need to be aware of.