Sam Altman Reveals AGI PREDICITON DATE In NEW INTERVIEW (Sam Altman New Interview)

So Sam Altman recently had an interview at Howard University where he actually spoke about a variety of interesting topics. And there was a lot that he discussed that actually gives us an insight to things like education, the role of AI in the future, and of course, artificial general intelligence, which kind of gives us a gauge on where he's at in terms of what he's thinking. Now, the initial interview was actually done back in January, but it was only just released, which means that this interview is from literally four months ago. So that's of course, something to keep in mind. But nevertheless, let's take a look at the first section where Sam Altman actually gives his opinion on what will be the most important skill for people to learn in the future.

Strong agree with that. I think critical thinking, creativity, the ability to figure out what other people want, the ability to have new ideas, that in some sense that'll be the most valuable skill of the future. If you think of a world where every one of us has a whole company worth of AI assistants that are doing tasks for us to help us express our vision and make things for other people and make these new things in the world, the most important thing then will be the quality of the ideas, the curation of the ideas. Because AI can generate lots of great ideas, but need a human there to say, this is the thing other people want. And also humans, I think, really care about the human behind something. So when I read a book that I really love, the first thing I want to do is go read about that author. And if an AI wrote that book, I think I'll somehow connect to it, much less same thing. When I look at a great piece of art or if I am using some company's product, I want to know about the people that created that. So I think in both directions of humans knowing what other humans want, and also humans caring about the humans behind something. That'll be a super important skill. And so I think learning that ability to create, come up with new ideas, choose ideas from among the many options presented by an AI, that'll be very valuable. I agree with you. The tools will change. But I also think familiarity with the tools of today and this new way of using computers is really important. That'll be important for everyone, not just the tool builders, but everybody. Like in the same way that if you can't use a mobile phone, you're kind of at a huge disadvantage, but they're not that hard to use and people learn. But the earlier in your career you got familiar with a resilient life, the better you know, everybody in this room was familiar with it probably as long as you can remember. But I remember watching older people struggle with getting comfortable with a phone for the first time. As intuitive as I thought they were, I think human adaptability is remarkable. And so I'm very happy that people no longer think it's weird or impressive that we can talk to a computer like we talk to a human and it understands us and it talks back to us and it does things for us. But two years ago, almost no one believed that was going to be possible anytime soon. Two years ago, what happens now with using ChatGPT was the stuff of sci fi at best. And if you told the world this was going to be part of people's daily lives, two years later, I think they would have said, of course not.

You know, so at the end of that, we actually got Sam Altman to say that, you know, this is going to happen and it's not going to happen, you know, in the far future, which does mean that, you know, AI is growing as quickly as some people expect it to be. And I think that this means that the future systems that OpenAI do have in mind are clearly going to be some of the most capable systems that we've ever seen and might even exceed some people's wildest predictions on what they're able to do. Now, this is something that we've, you know, widely speculated on for quite some time, but hearing Sam Altman say himself is something that is pretty reassuring and something that he also said that, you know, in terms of the most important skills that you can have for the future is, of course, I think there are two most important skills. Now, I do discuss this on the second channel where I talk about post AGI economics, which is just, you know, how the economy is going, going to move forward in terms of the job market and in terms of where people are going to gain their economic agency from and their economic value from. And one of the key things that he does talk about is of course, number one, thinking about what other humans want and being able to provide that is going to, of course, be an essential skill, because humans are going to need a lot of different things than they do need now. And of course, number two, focusing on the humanness aspect, which is something that I've been trying to do. But because in the framework that I've adapted and in the framework that I talk about for post AGI, that we're moving towards humanness is of course, something that I know people enjoy. For example, even on this channel, something that I try my hardest not to do, unless I'm completely ill, is, of course, use AI to do any of the content creation. And this is because I truly believe that people value what other humans create. And this is something that I've seen time and time again. Usually when you see AI generated artwork, it's frowned upon you. Usually if there's an AI voiceover, people don't like listening to it as much. Of course, there are some exceptions, but I think humanness in the future for the workplace is most certainly going to be something that is valued quite a ton. Because if we're moving to a future where AI is going to be, I guess you could say, outplacing humans one to one, I think humans are going to value other humans quite a lot. It's going to be something that I think we're going to see. And by focusing on that, it's definitely going to allow you to have a lot more value in terms of just, you know, rather than automating completely everything that's.

That's a Hollywood thing. And this is a significant change the world has just gone through. I think this is probably. Well, certainly this is the most significant change to how we use computers since the touchscreens on mobile phones. But I think it'll probably be much, much bigger than that. You'll be able to just say, tell a computer like you would tell a friend or an employee, I need this thing to happen, or what do you think about this? Or can you help me out with this? Or how do you think about this? And it'll just do it for increasingly complex definitions of it. Right now, it can maybe write some code for you, edit a paper for you, help you analyze things, but someday it'll write a whole program for you, do a whole research project for you, help you come up with new ideas someday, not in the far future. So I think this is a very.

Big deal and something that Sam Altman did talk about. The last bit that I want to just reference once again, is, of course, he said that computers are basically going to just be able to do something that you want. And this is something that we previously spoken about before, where we know that OpenAI is, of course focusing on agents in the future. So, of course, OpenAI are pretty much the market leader in terms of what they've been able to do with AI systems across the board. And it seems that in the future, when we have systems where we're able to say, okay, I need you to go ahead and do this, and I need you to go ahead and do that. And it's not just a back and forth Interface where the AI actually takes 10 steps to complete several different tasks across a range of, you know, subfields. It's going to be really fascinating to see how far that potential is pushed to see what an AI system can really do versus what it can do today. And I think, you know, for the future that's going to be something that's rather fascinating.

Sure. That happens with every technological revolution. And even though I'm confident we're going to gain much more than we lose, doesn't mean we're not losing something. And we're all philosophers for good reason. I'll tell you what I think we're not going to lose, which is I think we are not going to lose two things, the value and depth of human relationships, how much we care about other humans. I think people get excited to talk to AI friends for a while and that'll be part of the future for sure. But you hear people who do that a lot say, man, there's really something about knowing it's another human. And this is like deeply biologically wired in us. And I don't think going anywhere we're going to, we are, we are so, yeah, so deeply wired to care about other humans. What other, other humans think, what other humans do. The connection we have with other humans, we're not going to lose that.

So one of the things that Sam Altman, of course just talk about there was something that we previously spoke about was of course the humanness. Now I think the reason that a lot of people are trying to talk about, you know, humanness in terms of one to one human relationships is because there's been like a slight trend that most people haven't been paying attention to unless you're actively engaging it in yourself. And that is of course this company here. So you can see that this is Character AI, which is basically a company that, you know, is nearly catching up to ChatGPT in terms of the users. And the reason that most people are actually talking about Character AI in terms of the app and how active the user is, is because we have so many people that are engaging with things that aren't human. And a lot of people are, you know, talking about how people are engaging with AI girlfriends and how it's becoming an increasingly, increasingly worrying trend because people are engaging with things that, you know, right now aren't that good in terms of impersonating what a human could do. But in terms of the future, we know that these systems are going to get More and more lifelike. They're going to have better voices, probably real time. I mean, so it's like, you know, people are wondering that, you know, is that going to be something that, you know, goes on even worse in the future? I think it probably is going to be. Considering the fact that there's already societal issues that, you know, that exist between men and women in society. I'm not going to really get into those issues there. But, you know, there's always going to be issues. And if people now have something where they don't need to talk to, you know, which either, whichever. The point I'm trying to make here, guys, is that if you now have a system where you don't need to engage with another human in order to get some emotional connection, the problem is, is that now you never need to ever talk to another human again. And that leads us to a situation where some humans might just stop playing the game altogether in terms of talking to another human. And that's, you know, an entirely another issue. But like I said before, I think overall humanness will still be one of the most important things, because like I said before, you know, discussing with how, you know, running this channel and many other, you know, industries, when things are created by AI, it is kind of frowned upon. And I think humans do want to engage and interact with other humans.

We are going from a world in which intelligence is limited and expensive to abundant and cheap. And if you think about how much any of you could do if you had a massive amount of cognitive labor at your disposal to build the ideas you want to see happen, to be useful to other people, to provide services and advice, you know, right now you can hire people and you can coordinate them, and it's kind of difficult and very expensive. And most people in the world cannot afford nearly as much. Let's call it cognitive service as they like. You know, not many people can afford great lawyers, for example. That's a very specialized, very expensive kind of cognitive service. If the cost of that, the availability of that comes down by a factor of 100 or a factor of 10,000. And not just for legal advice, because I don't think anyone needs, like lots more legal back and forth, but for all the stuff we do want, great entertainment, great products and services, everything else, great education, great medical care, that is a profound shift to the world. So we're super excited about that. And I think that everyone can feel what the magnitude of that transformation looks like. Your second point is actually not a question that I've been asked many times. And I think it's a great one, so I appreciate it. One of the things that I learned at YC Y Common Air and also what I learned as I was like a kid studying the history of technology, is you can never go too far making a technology easy to use and accessible. Every, you know, every like, 10% easier to use. You can make a technology maybe twice as many people use it, or they use it twice as much, or there's this huge thing. And so we had this technology that we knew was pretty cool. We didn't know quite how much people were going to like it, but we had a sense they were. And we put it out first in an API and like, some nerds had a good time with it, but not very many. And it was kind of like unknown in the world. We put GPT3 out in the API. I think it was in, like, June, maybe it was July of 2020, something like that. And, you know, people built stuff and other. But we started thinking then about, like, what is. What is the best, simplest, most natural user interface that we can build on this? And I'd had this observation that computers had trended over time to be as close to the way we interact with other humans or we interact with. With our physical world as possible. So you started out with like, punch cards to program computers. I don't know how those people did it. It sounds amazing to me. Like, what an unnatural way to use a computer. And they're like, literally like sorting these things out on the floor. Wild. But they did it. And then you had command lines, and that was like, a little better. There's somewhat of like a kind of framework. I can see for that. But I'm grateful. I never really had to use those computers. And then you have the graphical user interface. And now finally we're getting something towards more like, something the way we interact with the world. And a lot of people started to use it. And we knew how to point at things. And the mouse was a reasonable analog for that. The keyboard was kind of fake, but it was like, good enough. And this idea that we had these windows and graphical information displayed to us, like we look at the world, we look at a screen. There were images that all kind of worked. The smartphone was then a. A huge revolution. We got to get rid of that keyboard and that mouse and just use our hands, like, again, much closer to how we use the world. And so we were thinking about what was next in that. And Sci Fi had predicted this. So it shouldn't have taken us as long to figure it out as it did. But you really just want a computer you can talk to like you talk to a human. We are so finely tuned to use language and the nuance and sophistication of language, imprecise though it is, all of the problems with it that it has, we can communicate at a very high bandwidth, enormously complex ideas with language. And so we said, well, what if we just go back to this idea of chatbots? People tried it earlier. The problem was the chatbot didn't really understand you. Maybe now it can. Let's try to build that. And then building the chatbot itself, the chat interface itself is obviously trivial, but the question was, how do we tune the underlying model to be really helpful to you and really good at conversation?

So, yeah, right there you can see Sam Altman talked about the evolution of the kind of systems that we've interacted with and how they've gotten better over time. And you know, that this might be the final. I wouldn't even say final, actually, if you're discussing Neuralink, but I think this is the step before the final. I wouldn't say integration with humans, but the final way that humans are going to interact with technology. Because I would say now we're moving to that stage where, you know, nearly everything is going to probably be, you know, interacting with humans in a natural language setting. I mean, you know, some people are saying that in the future you won't need to code. You're going to be able to just say, you know, code me this program, you know, fix this code, yada, yada, yada, or go build me this program, which is very, very simple in interacting in a natural language way. And in the future, of course, I'm talking about, you know, the final stage where you're probably going to have like, know, a neuralink device or something. It's just going to be able to think and it's going to be able to interpret that immediately and go ahead and do the work. So I think, you know, the movement from, you know, how we interact with systems now to how we interact with systems in the future is very telling for how OpenAI build their next systems. Because he actually also did say that he wants it to be very, very easy for everyone to use. And the easiness and the ease of use in terms of the UI design that they're going to be doing and just how the entire system works, I think it's going to be really, really simple to engage with and interact with, even with regards to many of the way that if you're trying to build an agent now. There's a lot of code involved, there's a lot of complexity involved. So I think OpenAI are going to solve that in the future. So it will be interesting to see how they do tackle that problem. But like I said, I think OpenAI, one of the key things that I think most people do miss is that OpenAI are also not just a fantastic company that does amazing AI research, they're actually a company that is focused on building really, really good products, which means that the services that they provide are far superior than any other company in terms of the fact that even if they have a better AI system, OpenAI can usually present it in a better way. And I think that's something that's really, really underrated and something that most people don't take into account. Because whilst yes, some other Systems have beaten GPT4 in the benchmarks, I think in the future, just the ease of use of the systems is going to be something that really is a point where OpenAI do manage to stand out.

Feedback, where we take the base model and get it to behave in a certain way. And that requires both deciding how it should behave and then getting people to sort of say, this is a good response, this is not a good response, or this, you know, this fits the specification and this doesn't. And having diverse representation at all of those steps is very important. And also figuring out and agreeing as a society on what the behavior should be. I know I've mentioned this a few times, but it's such a big challenge. Getting that right requires such a diverse input of voices to do it. I think that'll be critical to the field going forward. Okay, thank you. Thank you.

There has been two sides of the spectrum. On one side there has been Google's Woke AI, which is where it's so progressive that it unfortunately portrays history inaccurately, which is of course a problem, because you don't want history to be portrayed inaccurately because inaccuracy is just not what we're aiming for with AI systems. And then on the other side, you don't want AI systems to be so regressive in the sense that it goes in the other direction. So we do want a fair balance. And this is something that I think is going to be pretty hard to fix because it's something that AI systems, I'm not sure they're inherently understanding of what humans always want. Now, this also brings me to another problem that I was reading about in a research paper, which is the idea of model collapse. So essentially this paper actually does. It's not really talking about woke AI and that kind of stuff, but it does talk about something that's pretty similar. And I guess this is kind of the problem. It's kind of like a similar area and basically it talks about model collapse. So essentially the widespread use of AI systems like LLMs, which we talk about all the time, could lead to a narrowing of human knowledge over time as these models tend to generalize and focus on content, which is pretty common and popular information, rather than the rare and specialized knowledge which, which we usually sometimes are exposed to, which furthers discoveries. And just it's a more broader picture. And this knowledge collapse could actually harm innovation and lead to a less rich understanding of the world and the diversity of ideas get lost. Because essentially what we have is AI systems that are cheaper. A lot of people produce content with AI and because the AI is so centralized in terms of its beliefs and always kind of generalizes with the same kind of answers which we can have this kind of problem in the future, which is. I'm not sure how they're going to solve this problem. I think they're going to have to. It's probably going to be some synthetic data set and probably some testing on trying to understand where the distribution lies in terms of the variations where AI is generating content. So I think it's going to be interesting to see how this goes in the future because these AI systems are going to become more and more widespread. And as they become more and more widespread, these hallucinations and the less diverse the content is in terms of the ideas, in terms of the innovation and in terms of, you know, certain things which are, you know, in certain industries and certain topics that just really niche pieces of information. I think AI systems won't talk about it that much. And this is something that I've noticed myself when talking to AI systems. Like, I will know a lot about a topic and sometimes I'll ask an AI just to make sure that it knows. And sometimes it won't even bring up a certain point. And I'm like, what about this? Why didn't you bring up this? And it's like, oh yeah, I do remember that. And it's like, just because it was on the niche end of the spectrum, like it was just on the tail end of the distribution, the AI system sometimes forget to include it. So that's also something that you guys should know as well. When you're using ChatGPT sometimes it doesn't always give you the entire picture. It just gives you the centralized distribution of information that it has. So it's always important to still do research on top of ChatGPT because a lot of times it does miss some of the key points you do miss and it's only really centralized. So. Hi, thank you. My name is Kiton, I'm a sophomore comp science major here. And my question is actually tended towards AGI because the future after AI indefinitely will become AGI and how artificial intelligence has emotions or we're able to learn from itself. And you know, that's where the potential risks come in with, you know, AI actually having emotions and being able to like, well, the risk potentially. So I'm going to ask where OpenAI is at in terms of AGI and how do you plan on balancing out the risks and benefits?

Thanks for the question. It's, you know, that is probably the thing we think the most about. I, I think AGI is now like a such a fuzzy term and people use it in so many different ways. What you're asking about I think is closer to what I would call like super intelligence. Not something that can do the jobs that a human can do, but, but say something that can do research, do AI research itself maybe, as well as all of OpenAI's researchers, and use that to self improve. And how we think about what the world will look like when we get to that level and how we make sure we confront the risk of such a system, which are very hard to do. We have new teams that help us think about being prepared for that world. Also technical safety work to think about how we can make sure humans stay in control of systems that are more capable than we are. I think it's somehow both going to be stranger than it seems and also in some other way much more continuous and much more like the world today. Humans will still be in control, but what any human can do and certainly what any group of humans or nation can do will be like vastly, vastly improved. And part of the reason that we try to talk about this, even though it scares people or they think we're crazy or both, is if we're right, this is a huge deal and really important. It's going to impact all of us in a huge way. And we want the world to have this conversation now. Like we know that ChatGPT isn't that powerful. We know if it was just going to be chatgpt, none of these things really matter. But given the steepness of the curve that we're on, of the exponential, we want the world to have this conversation so we jointly decide how to balance those risks and benefits.

Thank you. Just to ask, how close do you think you are, though, to achieving all that?

It's super hard to say. I hesitate to give. I'm always happy to make predictions about what will happen, but when in research in particular, is super hard. But I would say that in this decade we get to very powerful systems. I personally don't believe towards that, like, thing that can do is AI research as well as OpenAI. But I've been wrong before. But I would say, like, very powerful systems that a lot of people will say, like, okay, for what I want to call AGI, this is a version of it, an early version by the end of this decade, that'd be my guess, but could be much longer.

Thank you. So here we have Sam Altman's deadline. Well, not really deadline, just a vague definition. And I think Sam Altman, rightly so, is of course very vague in his predictions because he doesn't want to be be someone that's known to continually blast out dates. And then, of course, when they don't happen, it's like, you know, a knock in terms of your reputation by not being able to deliver on set dates. But he does say that pretty much by the end of this decade we should be able to get an AGI system which is not far away. Six years is really, really quickly, if we've seen how quickly the past years have gone. I remember Covid like it was yesterday. So, you know, six years is not that long in terms of getting to an AGI system. And of course, the point is as well, this kind of systems that we're going to be getting before that will be also pretty fascinating as well. So that is, of course, you know, something that he did say. He did, of course, leave a caveat in there by stating that it could be, you know, much, much longer. And of course it could be, you know, there are pretty much anything could happen with, you know, the way Earth is at the moment. But the point is, is that he also does discuss superintelligence, which is of course an AI system that is able to do research at the level of OpenAI's engineers and then improve itself. So we did get kind of definition in that aspect. But it is going to be kind of interesting to see how the developments leading up to AGI will be considering, you know, we're progressively increasing in terms of the capabilities of these systems. Implications of AI. One that comes to my mind is deepfakes and online impersonation of people. So how do you think the industry as a whole can sort of mitigate that problem?

There's two different directions I can imagine that coming from. One is when people say something themselves or when they endorse a particular image, there's like a cryptographic signature other people can verify. And you say, this really is a picture I took or this really is a quote I said. And we as a society decide that, you know, we're just flooded with generated media and back to that point about humans caring about other humans, we're going to like have these networks of trust and we'll say, all right, you know what, if you didn't sign that photo, I'm going to assume it's not real. And if someone didn't sign it that I trust, that I trust, that I trust, and I don't have that chain, I'm going to assume it's not real. So that could happen. The other thing that could happen is that we have enough rules in place on the powerful AI systems that exist that there's a watermarking process that everybody kind of enforces. But with either of those paths, there will be a huge amount of generated content on the Internet. And I think society is just very quickly going to evolve to understand not to take it too seriously.

Simon also does discuss here something that is quite interesting and I think this is something that there needs to definitely be some kind of regulation because currently the problem is with AI generated images is that we don't have a one stop solution in terms of verifying whether or not an image is real or whether or not an image is absolutely fake. And currently there's this big discussion on how we're going to get to that solution. And Sam Altman does talk about applying some kind of digital ID to that image in order to verify whether or not that image was taken by an AI system or not. And I think that this is something that is really important because as these systems get increasingly more comprehensive, as they get easier to use, you know, I mean right now, you know, mid journey, it's pretty easy to use your log on to discord, yada yada yada. But as we get to systems where you can just literally say, hey, create me 1500 images of XYZ and it's able to blast out high quality images within seconds, I think we're going to need some kind of system like Google's synthetic id where any major AI text to image AI system is able to pretty much convincingly have some kind of digital watermark that you can then run through some other system that notices if it's digitally altered or not. So I think whichever company manages to come up with that is probably going to be a winner, or it's probably going to be some kind of legislation in the future that I think we will definitely see, because it only takes one picture to have a devastating impact on what people do believe.