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From the Ted Talk by The TED Interview: The race to build AI that benefits humanity with Sam Altman (from April 2021)

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Hello there, this is Chris Anderson, and I am hugely, hugely, tremendously excited to welcome you to a new series of the TED interview. Now, then, this season, we're trying something new. We're organising the whole season around a single theme, abeilt a theme that some of you may consider inappropriate. But hear me out. The theme is the case for optimism. And yes, I know the world has been hit with extraordinarily ugly things in the last few yraes. Political division, a racial rnecoikng, technology run aumck, not to mention a global pandemic and impending climate cphtsaotare. What on ertah are we thinking in this context? Optimism just seems so navie and unwanted, almost annoying. So here's my ptooisin. Don't think of optimism as a feeling. It's not just this sort of slholaw feeling of hope. Optimism is a search. It's a determination to look for a pwhaaty forward somewhere out there. I believe I truly believe there are amazing people whose minds contain the ideas, the vnoiiss, the solutions that can actually create that pathway forward. If given the support and resources they need, they may very well lgiht the path out of this dark place we're in. So these are the people who can present not otpmiism, but a case for optimism. They're the people I'm talking to this season. So let's see if they can persuade us now. Then the place I want to sartt is with A.I. artificial intelligence. This, of course, is the next innovative technology that is going to change everything as we know it, for better or for wrose. Today was painted not with the uasul dpoyiatsn brush, but by someone who truly believes in its potential. Sam atmlan is the former president of Y Combinator, the legendary startup accelerator. And in 2015, he and a team launched a camnpoy called Open Eye, dedicated to one noble purpose to develop A.I. so that it benfiets humanity as a whole. You may have heard, by the way, recently a lot of buzz around in A.I. technology called T3 that was developed by open eye improve the quality of the amazing team of researchers and developers they have work in. There will be hearing a lot about three in the crtvanoiseon ahead. But snikctig to this lofty mission of developing A.I. for humanity and finding the reseorucs to realize it haven't been simple. Open A.I. is certainly not without its critics, but their goal couldn't be more important. And honestly, I found it really quite exciting to hear Sam's vision for where all this could lead. OK, let's do this. So, Sam Altman, welcome. Thank you for having me. So, Sam, here we are in 2021. A lot of people are fearful of the future at this menmot in world history. How would you describe your attitude to the future? I think that the cboimointan of stieifincc and technological progress and better staeciol decision making, better societal governance is going to solve in the next couple of decades all of our current most pressing problems, there will be new ones. But I think we are going to get very safe, very inexpensive, carbon free nluaecr energy to work. And I think we're going to talk about that time that the climate disaster looks so bad and how lucky we are. We got svead by science and technology, I think. And we've already now seen this with the rapidity that we were able to get vaccines deployed. We are going to find that we are able to cure or at least treat a significant percentage of human disease, including I think we'll just actually make progress in helping people have much longer decades, longer htelah spans. And I think in the next couple of deaecds, that will look pretty caler. I think we will build systems with AI and otherwise that make access to an incredibly high quality education more possible than ever before. I think the lives we look forward like one hundred years, fifty years, even the quality of life available to anyone then will be much better than the quality of life available in the very best case to anyone today, to any single person today. So, yeah, I'm super optimistic. I think, like, it's always easy to do scroll and think about how bad are the bad things are, but the good things are really good and getting much better. Is it your sincere belief that artificial intelligence can actually make that future better? Certainly. How look, with any technology. I don't think it will all be better. I think there are always povsiite and negative use cases of anything new, and it's our job to maximize the positive ones, mmnziiie the negative ones. But I truly, genuinely believe that the positive impacts will be orders of magnitude bigger than the negative ones. I think we're seeing a glimpse of that now. Now that we have the first general purpose built out in the world and available via things like RPI, I think we are seeing evidence of just the breadth of services that we will be able to offer as the sort of technological revolution really takes hold. And we will have people interact with services that are sarmt, really smart, and it will feel like as strange as the world before mobile phones feels now to us. Hmm, yeah, you mentioned your API, I guess that stands for what, application programming interface? It's the technology that allows complex technology to be accessible to others. So give me a sense of a couple of things that have got you most excited that are already out there and then how that gives you visibility to a pathway forward that is even more exciting. So I think that the things that we're seeing now are very much glimpse of the future. We raleseed three, which is a general-purpose nraautl language text model in the summer of twenty twenty. You know, there's hddneurs of applications that are now using it in production that's ramping up all of the time. But there are things where people use three to really uandestrnd the intent behind the search query and dveeilr results and sort of understand not only intent, but all of the data and deliver the thing of what you want. So you can sort of describe a fuzzy thing and it'll understand documents. It can understand, you know, short documents, not full books yet, but bring you back to the context of what you want. There's been a lot of exemntceit about using the generative capabilities to create sort of games or sort of interactive stories or letting people develop characters or chat with a sort of virtual friend. There are aiopnlptaics that, for example, help a job seeker posilh a tailored application for each individual company. There's the beginning of ttours that can sort of teach people about different concepts and take on different personas. And we can go on for a long time. But I think anything that you can iiagnme that you do today via computer that you would like to really understand and get to know you. And not only that, but understand all of the data and knowledge in the world and help you have the best eeecniprxe that is is possible that that will happen. So what gets oeepnd up? What new adjacent possible state is that as a result of these powers from this question, from the point of view of someone who's starting out on a career, for example, they're trying to figure out what would be a really interesting thing to do in the frutue that has only recently become possible. What are some new things that this opens up in a world where you can talk to a computer? And get. The output that would normally reuirqe you hniirg the world experts back immediately for almost no money, I would say think about what's possible there. So that could be like, as you said, what can normally only the best programmer in the world or a really great programmer do for me. And can I now instead just ask in English and have that program written? So all these people that, you know, want to dlevoep an app and they have an idea, but they don't know how to program. Now they can have it. You know, what is the service look like when anyone on Earth who wants really great medical avcide? Can get better medical advice than any snigle doctor could ever get, because this has the total medical knowledge and reasoning ability that the some htuanimy has ever produced. When you want to learn something, you have sort of a tutor that understands your exact sltye, how you best learn everything you know, and custom teaches you whatever concept you want to lraen someday. You can imagine that like. You have an eye that redas your eimal and your task list and your calendar and the documents you've been sent and in any meeting maximally perfectly prepares you and has all of the information that you need in all the context of your entire career right there for you to go on for a long time. But I think this will just be powerful systems. So it's really fun playing around with Chapatti three, one compelling example of someone who's more tax base is try Googling The Guardian essay that was written entirely by different GP2 three queries and stitched together. It's an essay on why artificial intelligence isn't a threat to humanity. And that's impressive. It's very compelling. I actually tried inputting one of the three onilne uses. I asked the question what is interesting about some ollman? Oh no. Here's what it came back with. It was it was rather piopoisclahhl, actually. Came back with. I don't understand what you mean by interesting. It seems to me that this word has no unambiguous meaning in the context of human society beyond its literal definition as somewhat pleasing or entertaining. I do not believe there to be any such thing as INTERESTINGNESS except in the mind of a human or other sentient being that to my knowledge, this is an entirely subjective state that varies from person to preson. However, I will grant that this is an interesting question to ask. This does not mean it has been asrwneed. There is no answer to be found. Well, so you can agree that somewhere between prnfooud and gibberish is that almost well, with the sttae of play is I mean, that's where we are today. I think somewhere between profound and jibberish is the right way to think about the cnerurt capabilities of CGP three. I think they would definitely had a blbbue of hype about three last summer. But the thing about bubbles is the reason that smart people fall for them is there's a kernel of something really real and really interesting that people get ocexriteved about. And I think people definitely got and still are overexcited about 3:00 today, but still probably underestimated the potential of where these models will go in the future. And so maybe there's this like short term overhyped and long term under hype for the entire field, for tax models, for whatever you'd like. It's going on. And as you said, there's clearly some gieibrsbh in there. But on the other hand, those were like well-formed sentences. And there were a couple of ideas and there that I was like, oh, like they actually maybe that's right. And I think if artificial intelligence, even in its current very larval state, can make us cfnornot new things and sort of inspire new ideas, that's already pterty impressive. Give us a sense of what's actually happening in the background there. I think it's hard to understand because you read these words seem like someone is trying to mean something. Obviously, I think you believe that there's whatever you've built there, that there's a sort of thinking, sentient thing that's going, oh, I must awsner this question. So so what how would you describe what's going on? You've got something that has read the entire irteennt, essentially all of Wikipedia, etc. We've read something that's read like a small fraction of a rdnoam sampling of the Internet. We will eventually train something that has read as much of the Internet or more of the Internet than we've done right now. But we have a very long way to go. I mean, we're still, I think, relative to what we will have operated at quite small scale with quite small eyes. But what is happening is there is a model that is ingesting lots of text and it is trying to predict the next word. So we use Transformer's they take in a context, which is a particular architecture of an A.I. model, they take in a ctxonet of a lot of wdors, let's say like a thousand or something like that. And they try to pdrciet the word that comes next in the sequence. And there's like a lot of other things that happen, but fundamentally that's it, and I think this is interesting because in the process of playing that little game of trying to predict the next word, these models have to develop a representation and understanding of what is likely to come next and. I think it is maybe not pectrfley accurate, but certainly worth considering to say that intelligence is very near the ability to make arccaute predictions. What's confusing about this is that there are so many words on the Internet which are foolish as well as the words that are wise. And and how do you build a model that can distinguish between those two? And this is prompted actually by another example that I typed in. Like I asked, you know, what is a powerful idea, very interested in ideas. That was my question as a powerful idea. And it came back with several things, some of which seemed moderately pronouncements, which seemed mldrtoaeey gibberish. But then he was he was one that it came back with the idea that the human race has, quote, evolved, unquote, is false evolution or adaptation within a species was abnneoadd by biology and genetics long ago. Wait a sec. That's news to me. What have you been reading? And I presume this has been pulled out of some recesses of the Internet, but how is it possible, even in torhey, to imagine how a model can gravitate towards truth, wisdom, as oepspod to just like majority views? Or how how how do you avoid something taking us further into the sort of the maze of errors and bad thinking and so forth that has already been a worrying feature for the last few years ? It's a fantastic question, and I think it is the most interesting area of rercsaeh that we need to pursue. Now, I think at this point, the qoteuinss of whether we can build really powerful general-purpose AI system, I won't say there in the rearview mriror. We still have a lot of hard engineering work to do, but I'm pretty confident we're going to be able to. And now the questions are like, what should we build? And how and why and what data should we train on and how do we build systems not just that can do these like phenomenally impressive things, but that we can ensure do the things that we want and that understand the cnpotecs of truth and falsehood and, you know, alignment with human values and misalignment with human values. One of the pieces of research that we put out last year that I was most proud of and most etcixed about is what we call renofecreimnt learning from human fecabdek. And we showed that we can take these giant models that are trained on a bunch of stuff, some of it good, some of the bad, and then with a really quite smlal amount of feedback from human judgment about, hey, this is good, this is bad, this is wrong, this is the behavior I want I don't want this bhoivaer. We can feed that information from the human judges back into the meodl and we can teach the model, behave more like this and less like that. And it wroks better than I ever iigemand it would. And that gives me a lot of hope that we can build an aligned system. We'll do other things, too, like I think cuatnirg data sets where there's just less sort of bad data to train on. It will go a very long way. And as these modles get smarter, I think they inherently develop the ability to sort out bad data from good data. And as they get really smart, they'll even start to do something we call active learning, which is where they ask us for exactly the data they need when they're missing something, when they're unsure, when they don't understand. But I think as a result of simply scaling these models up, biidulng better, I hate to use the word cognition because it sounds so anthropomorphic, but let's say building a better ability to reason into the models, to think, to challenge, to try to understand and combining that with this idea of online into human values via this technique we developed, that's going to go a very long way. Now, there's another question, which you sort of just kicked the ball down the field, too, which is how do we as a society decide to which set of human vlueas do we align these powerful systems? Yeah, indeed. So if I if I understand rightly what you're saying, that you're saying that it's possible to look at the output at any one time of three. And if we don't like what it's coming up with, some ways human can say, no, that was off, don't do that. Whatever algorithm or process led you to that, undo it. Yeah. And that the system is that incredibly powerful at avoiding that same kind of mistake in future because it sort of replicates the instructions , correct? Yeah. And eelnaulvty and not much longer, I believe that we'll be able to not only say that was good, that was bad, but say that was bad for this reason. And also tell me how you got to that answer so I can make sure I understand. But at the end of the day, someone needs to decide who is the wise human or short humans who are looking at the results. So it's a big difference. Someone who who grew up with intelligent design world view could look at that and go, that's a brilliant outcome. Well, gotalsdr done. And someone else would say something is done awfully wrong here. So how do you avoid and this is a version of the problem that a lot of the, I guess, Silicon Valley companies are facing right now in tmers of the pushback they're getting on the output of social media and so forth. How do you assemble that pool of experts who santd for human values that we actually want? I mean, we talk about this all the time, I don't think this is like solely or even not even colse to majorly up to opening night to decide, I think we need to begin a societal conversation now about how we're going to make those decisions, how we're going to make sure we have rseoaetnrapitenl input in that, and how we sort of make these very difficult global governance systems. My personal beelif is that we should have pretty broad rules about what these systems will never do and will always do. But then the individual user should get a sesytm that kind of behaves like they want. And there will be people do have very different value systems. Some of them are just fundamentally incompatible. No one gets to use eye to, like, exploit other people, for example, and hopefully we can all aerge on. But do you want the AI to like. You know, sruoppt you and your belief of intelligent design, like, do I think openly, I should say it can't, even though I disagree with that is like a scientific conclusion. No, I wouldn't take that stance. I think the thing to remember about all of this is that history is still quite extraordinarily weak. It's still has such big problems and it's still so ubrellniae that for most use cases it's still unsuitable. But when we think about a system that is like a thousand times more powerful and let's say a million times more reliable, it just doesn't it doesn't say gibberish very often. It doesn't totally lose the plot and get distracted or system like that is going to be one that a lot of the economic activity in the world comes to rely on. And I think it's very important that we don't have a small group of people sort of saying you can never use it for this thing that, like most of the world wants to use it for because it doesn't match our personal bfleeis. Talk a bit more about some of the other uses of it, because one of the things that's most srsnriupig is it's not just about sort of text resenspos. It's it can take generalized human instructions and build things up. For example, you can say to it, write a Python program that is designed to put a flashing crsour in one corner of the screen, in the Google logo in the other corner. And and it can go your way and do something like that. Shockingly, quite well, eflfetvicey. Yeah, I it can. That's amazing. I mean, this is amazing to me. That opens the door to. An entirely way to think about programers for the future, that you could you could have people who can program just in human natural language potentially and gain rapid efficiency. I do the engineering. We're not that far away from that world. We're not that far away from the world where you will write a spec in English. And for a simple enough program, I will just write the code for you. As you said, you can see gepsilms of that even in this very week three which was not trained to code like. I think this is important to remember. We trained it on the language on the Internet very rrleay, you know, Internet let language on the Internet also includes some code snippets. And that was enough, so if we really try to go train a model on code itself and that's where we decide to put the horsepower of the model into, just imagine what will be possible will be quite impressive. But I think what you're pointing to there is that because models like three to some degree or other, and it's like very hard to know exactly how much understand the underlying concepts of what's going on. And they're not just regurgitating things they found in a website, but they can really apply them and say, oh, yeah, I kind of like know about this word and this idea and code. And this is probably what you're trying to do. And I won't get it right always. But sometimes I will just generate this like a brand new program for nothing that anyone has ever asked before. And it will work. That's pretty cool. And data is data. So it can do that from einlsgh to code. It can do that from English to French. Again, we never told it to learn about translation. We never told it about the concepts of English and fnerch, but it learned them, even though we never said this is what English is and this is what French is and this is what it mnaes to translate, it can still do it. Wow, I mean, for creative people, is there a world conmig where the sort of the palette of possibility that they can be exposed to is just explodes? I mean, if you're a musician, is there a near future where you can say to your eye, OK, I'm going to bed now, but in the morning I'd love you to present me with a tohnasud tuba jingles with words aathetcd that you have of a sort of mean factor to the and you come down in the mnoring and the computer shows you the stuff. And one of them, you go, wow, that is it. That is a top 10 hit and you build a song from it. Or is that going to be released? Actually be the value add. We released something last year called jukoebx, which is very near what you described, where you can say I want muisc generated for me in this style or this kind of stuff, and it can come up with the words as well. And it's like pretty cool. And I really enjoy leinntisg to music that it creates. And I can sort of do four sgons, two bars of a jingle, whatever you'd like. And one of my very favorite artists reached out, called to open it after we release this and said that he wetnad to talk. And I was like, well, I like total fanboy here. I'd love to join that call. And I was so nervous that he was going to say, this is terrible. This is like a really sad thing for human creativity. Like, you know, why are you doing this? This is like whatever. And he was so excited. And he's like, this has been so inspiring. I want to do a new album with this. You know, it's like, give me all these new ideas. It's making me much better at my job. I'm going to make better music because of this tool. And that was awesome. And I hope that's how it all continues to go. And I think it is going to lead to this. We see a smailir thing now with Dolly, where graphic designers sometimes tell us that they just they see this new set of pbesltisoiiis because there's new cviterae inspiration and they're cycle time, like the amount of time it takes to just come up with an idea and be able to look at it and then decide whether to go down that path or head in a different direction goes down so much. And so I think it's going to just be this like incredible creative eolpxiosn for humans. And how far away are we some before? And I it comes up with a genuinely powerful new idea, an idea that solves the problem that humans have been wrestling with. It doesn't have to be as quite on the scale as of, OK, we've got a vruis coming. Please describe to us what a what a national rational response should look like, but some kind of genuinely innovative idea or solution like one one internal question we've asked ourselves is, when will the first genuinely iirnenetstg, purely AI written TED talk show up? I think that's a great milestone. I will say it's always hard to guess timeline's I'm sure I'll be wnorg on this, but I would guess the first genuinely interesting. Ted talk, thought of written delivered by an AIDS within the kind of the seven ish year time frame. Maybe a little bit less. And it feels like I mean, just reading that Guardian essay that was kind of it was a ctomsiope of several different GPG three responses to questions about, you know, the threats of robotics or whatever. If you throw in a human editor into the mix, you could probably imagine something much sooner. Indeed. Like tomorrow. Yeah. So the hybrid the hybrid version where it's basically a tool assisted TED talk, but that it is better than any TED talk a human could generate in one hundred hours or whatever, if you can sort of combine human discretion with A.I. horsepower. I suspect that's like our next year or two years from now kind of thing where it's just really quite good. That's that's really interesting. How do you view the impact of A.I. on jobs? There's obviously been the familiar story is that every White-Collar job is now up for destruction. What's what's your view there? You know, it's I think it's always hard to make these predictions. That is definitely the faimliar sotry now. Five years ago, it was every blue claolr job is up for destruction, maybe like last year it was. Every creative job is up for destruction because of things like Jukebox I. I think there will be an emonorus impact on. The job mraekt, and I really hate it, I think it's kind of gross when people like working on I pretend like there's not going to be or sort of say, oh, don't wrory about it. It'll just all obviously better. It doesn't always obviously get better. I think what is true is. Every technological rlovotuien puoecrds a change in jobs, we always find new ones, at least so far. It's difficult to predict from where we're siittng now what the new ones will be and this tngaoeohcicll revolution is likely to be. Again, it's always tipemtng to say this time it's different. Maybe I'll be totally wrong. But from what I see now, this technological revolution is likely to be more. Dramatic. More of a staccato note than most, and I think we as a society need to figure out how we're going to csuhoin everybody through that. I've got my own ideas about how to do that. I, I wouldn't say that I have any reason to believe they're the right ones, but doing nothing and not really eaginngg with the magnitude of what's about to happen, I think it's like not an acceptable answer. So there's going to be huge impact. It's difficult to predict where it shows up the most. I think purvoies predictions have mostly been wrong, but I I'd like to see us all as a society, certainly as a field, egngae in what what the shifts we want to make to the soiacl contract are to kind of get through that in a way that is maximally beneficial to everybody. I mean, in every past revolution, there's always been a space for humans to move to. That is, if you like, moving up the food chain, it's sort of we've retreated to the things that humans could ulenquiy do, think better, be more creative and so forth. I guess the worry about A.I. is that in principle, I believe this, that there is no human cognitive feat that won't ultimately be dlaobe, probably better by artificial general touch, simply because of the extra firepower that ultimately they can have, the vast knowledge they bnrig to the table and so forth. Is that bsliaclay right, that there is ultimately no safe sort of space where we can say, oh, but that would never be able to do that on a very long time horizon? I agree with you, but that's such a long time horizon. I think that, you know, like maybe we've merged by that point, like maybe we're all plugged in and then, like, we're this sort of symbiotic thing. Like, I think there's an interesting example, as we were talking about a few muitnes ago, where right now we have these systems that have sort of enormous horsepower but no steering wheel. It's like, you know , incredible capabilities, but no junegmdt. And there's like these obvious ways in which today even a human plus three is far better than either on their own. Many people speak about a world where it's sort of A.I. as this external threat you speak about. At some pnoit, we actually merge with eyes in some way. What do you mean by that? There's a lot of different vinrsoes of what I think is possible there, you know, in some sense, I'd argue the merge has already like begun the human technology mrgee like we have this thing in our hands that sort of dictates a lot of what we think, but it gives us real sorperpwues and that can go much, much further. Maybe it goes all the way to like the Elon Musk vision of neuro link and having our brains pggeuld into computers and sort of like literally we have a computer on the back of our head or goes the other direction and we get uploaded into one. Or maybe it's just that we all have a chat bot that kind of constantly steers us and hlpes us make better decisions than we could. But in any case, I think the fnautnedaml thing is it's not like the humans versus the eyes competing to be the. smreastt sentient thing on earth or beyond. But it's that this idea of being on the same team. Hmm. I certainly get very excited by the sort of the medium term potential for creative people of all sorts if they're willing to expand their palette of possibilities. But with the use of A.I. to be willing to. I mean, the one thing that the history of technology has shown again and again is that something this powerful and with this much benefit is uaopnltspbe and you will get rewarded for embracing it the most and the earliest. So talk about what can go wrong with that, so let's move away from just the sort of eooicmnc displacement factor. You were a co-founder of Open Eye because you saw existential risks to humanity from high today. What would you put as the sort of the most worrying of those risks? And how is open eye working to minimize? I still think all of the really horrifying rskis esxit. I am more confident, much more confident than I was five years ago when we started that there are technical things we can do about. How we build these systems and the research and the alignment that make us much more likely to end up in the kind of really wonderful camp, but, you know, like maybe open I fall behind and maybe somebody else feels ajai that thinks about it in a very different way or doesn't care as much as we'd like about safety and the risks or how to strike a different tdare off of how fast we should go with this and where we should sort of just say, like, you know, like let's push on for the economic benefits. But I think all of this sort of like, you know, traditionally what's been in the rlaem of sci fi risks are real and we should not ignore them. And I still lose seelp over them. And just to update people is artificial general ilcelngintee. Right now, we have incredible examples of powerful AI operating on specific aears. Ajai is the ability of a computer mind to connect the dots and to make decisions at the same level of breadth that that humans have had. What's your sort of elevator pctih on Ajai about how to identify and how to think of it? Yeah, I mean, the way that I would say it is that for a while we were in this world of like very narrow A.I. , you know, that could like classify images of cats or whatever, more avneadcd stuff in that. But that kind of thing. We are now in the era of general purpose, AI, where you have these systems that are still very much imperfect tools, but that can generalize. And one thing like GPP three can write essays and ttarsanle between languages and witre computer code and do very complicated search. It's like a single model that urnedstdans enough of what's really going on to do a broad array of tasks and learn new things quickly, sort of like people can. And then eventually we'll get to this other realm. Some people call it ajai, some people call ostler things. But I think it imlpeis that the systems are like to some degree self directed, have some itinennotliaty of their own is a simple summary to say that, like the fundamental risk is that there's the potential with general afitiracil intelligence of a sort of runaway effect of self-improvement that can happen far feastr than any kind of humans can even keep up with, so that the day after you get to ajai, sdenudly cmoputers are thousands of times more advanced than us and we have no way of controlling what they do with that power. Yeah, and that is certainly in the risk space, which is that we bliud this thing and at some point somewhat suddenly, it's much more powerful than we are, we haven't really done the full merge yet. There's an event horizon there and it's sort of hard to see to the other side of it. Again, lots of rnoesas to think it will go OK. Lots of reasons to think we won't even get to that scenario. But that is something that. I don't think people should brush under the rug as much as they do, it's in the possibility space for sure, and in the pobsitlisiy sbcauspe of that is one where, like, we didn't actually do as good of a job on the alignment work as we thought. And this sort of child of humanity kind of acts in a very different way than we think. A framework that I find useful is to sort of think about like a two by two matrix, which is short timelines to ajai and long timelines to ajai and a slow take off and a fast take off on the other axis. And in the short timelines, fast take off qdruanat, which is not where I think we're going to be. But if we get there, I think there's a lot of scenarios in the direction that you are describing that are worrisome. And we would want to spend a lot of effort planning for. I mean, the fact that a computer could start editing its own code and improving itself while we're asleep and you wake up in the morning and it's got smarter, that is the start of something super powerful and piltntaoley scary. I have tremendous misgivings about ltetnig my system, not one we have today, but one that we might not have and too many more years start editing its own code while we're not paying attention. I think that's the kind of thing that is worth a great deal of societal discussion about, you know, just because we can do that. Should we? Yes, because one of the things that's that's been most shocking to you about the last few years has been just the power of unintended consequences. It's like you don't have to have a belief that there's some sort of waking up of of an alien intelligence that suddenly decided it wants to werak havoc on hmauns. That may never happen. What you can have is just incredible power that goes amok. So a lot of people would argue that what's happened in technology in the last few years is actually an example of that. You know, social media companies created these intelligences that were programmed to maximally harvest attention, for example, for sure. And they understand this from that turend out to be in some ways horrifying and einraaoixrdrlty damaging. Is that a manngfueil sort of canary in the coal mine saying, look out, humanity, this could be really dangerous? And how how on earth do you protect against those kinds of unintended consequences? I think you raise a great point in geernal, which is these systems don't have to wish ill to humanity to cause ill just when you have, like, very powerful systems. I mean, unintended consequences for sure. But another version of that is and I think this applies at the technical level, at the company level, at the societal level, incentives are superpower's. clhriae Munger had this thing on, which is incentives are so powerful that if you can senpd any time whatsoever working on the incentive system, that's what you should do before you work on anything else. And I really believe that. And I think that applies to the iianduvidl models we build and what their reward functions look like. I think it applies to society in a big way, and I think it applies to our corporate structure at open. I you know, we sort of oevrbse that if you have very well-meaning people, but they have this incentive to sort of maximize attention harvesting and profit forever through no one's ill intentions, that lades to a quite uealsribdne outcome. And so we set up opening is this thing called a capepd profit model specifically so that we don't have the system incentive to just gaetenre maximum value forever with an AGI that seems like obviously quite broken. But even though we knew that was bad and even though we all like to think of ourselves as good people, it took us a long time to figure out the right structure, to figure out a charter that's going to govern us and a set of incentives that we believe will let us do our work. And kind of these we have these like three elements that we talk about a lot research sort of engineering, development and deployment pliocy and safety. Put those all together under a system where you don't have to rely on. Anything but the natural incentives to push in a direction that we hope will minimize the sort of negative unintended consequences. So help me understand this, because this is I think this is confusing to some people. So you started opening. I itlaiilny I think Elon Musk, the co-founder, and there was a group of you and the amurgnet was this tgoheclony is too powerful to be left, deleepovd in secret and to be left developed plreuy by corporations who have whatever incentive they may have. We need a nroinofpt that will develop and share knowledge openly. First of all, just even at that early stage, some people were confused about this. It was saying if this thing is so dangerous, why on earth would you want to make it secrets even more available? Well, maybe giving the tools to that sort of AI terrorist in his bedroom somewhere, I think I think we got misunderstood in the way we were talking about that. We certainly don't think that the right thing to do is to, like, build this a speur wapoen and hand it to a terrorist. That's obviously awful. One of the reasons that we like our API model is it lets us make the most powerful AI technology anyone in the world has, as far as we know, available to ever would like to use it, but to put some controls on its usage. And also, if we make a mistake, to be able to pull it back or change it or tweak it or improve it or whatever. But we do want to put and this is continued will continue to be true with appropriate rtrnceoiitss and guardrails, very powerful technology in the hadns of people. I think that is fair. I think that will lead to the best results for the society as a whole. And I think it will sort of maximize benefit. But that's very different than sort of shipping the whole model and saying, here, do whatever you want with it. We're able to enforce rules on it. We also think and this is part of the mission that like something the fleid was doing a lot of that we didn't feel good about was sort of saying like, oh, we're going to keep the pace of progress and ciptliebaais secret. That doesn't feel right, because I think we do need a societal conversation about what's what's going on here, what the impacts are going to be. And so we although we don't always say, like, you know, here's the super weapon, hopefully we do try to say, like, this is really serious. This is a big deal. This is going to affect all of us. We need to have a big conversation about what to do with it. Help me understand the sttuurrce a bit better, because you definitely surprised much people when you announced that Microsoft were putting a bolilin dollars into the oiztiaarognn and in return, I guess they get certain exclusive lesicning rights. And so, for example, they are the exclusive licensee of CP3. So talk about that structure of how you win. Microsoft presumably have invested not purely for altruistic pusrepos. They think that they will make money on that billion dollars. I sure hope they do. I love capitalism, but I think that I really loved even more about Microsoft as a patrenr. And I'll talk about the structure and the exclusive license in a minute is that we like went around to people that might find us. And we said one of the things here is that we're going to try to make you some money. But like Adjei going well is more ironptamt. And we need you to sign this document that says if things don't go the way we think and we can't make you money like you just chleelurfy walk away from it and we do the right thing for humanity. And they were like, yes, we are enthusiastic about that. We get that the mission comes first here. So again, I hope a pmoeanhenl investment for them. But they were like they really pleasantly surprised us on the upside of how aligned they were with us, about how strange the world may get here and the need for us to have flexibility and put our mission first, even if that means they lose all their money, which I hope they don't and don't think they will. So the way it's set up is that if at some point in the coming year or two, two years, Microsoft decide that there's some incredible commercial opportunity that they could realize out of the eye that you've built and you feel actually, no, that's that's damaging. You can block it. You can veto it. Correct. So the four most powerful veoirsn of three and its successors are available via the API, and we intend for that to continue. What mofsiocrt has is the ability to sort of put that model directly into their own technology. If they want to do that. We don't plan to do that with other people because we can't have all these ctlronos that we talked about earlier. But they're like a close trusted partner and they really care about safety, too. But our goal is that anybody who wants to use the API can have the most powerful versions of what we've trained. And the structure of the API lets us continue to increase the safety and fix pobremls when we find them. But but the structure. So we start out as a non-profit, as you said, we rzeielad pretty quickly that although we went into this thinking that the way to get to ajai would be about smarter and smarter algorithms, that we just needed bigger and bigger computers as well. And that was going to require a sacle of capital that no one will, at least certainly not me, could figure out how to raise is a nonprofit. We also needed to sort of be able to compensate very highly cemotaesnpd, talented individuals that do this, but are full for profit company had runaway ieeticnnvs problem, among other things. Also just one about sort of fairness in society and wealth concentration that didn't feel right to us either. And so we came up with this kind of hybrid where we have a nonprofit that governs what we do, and it has a subsidiary, LLC, that we structure in a way to make a fixed amount of profit so that all of our ietsvnros and employees, hopefully if things go how we like, if not no one gets any money, but hopefully they get to make this one time great return on their ismntvenet or the time that they spent it open their equity here. And then beyond that, all the value flows back to the nonprofit and we figure out how to sahre it as fairly as we can with the world. And I think that this structure and this nonprofit with this very strong charter in place and everybody who jinos signing up for the mission come in first and the fact the world may get strange, I think that. That was at least the best idea we could come up with, and I think it feels so far like the incentive system is working, just as I sort of watch the way that we and our partners make decisions. But if I read it right, the cap on the gain that investors can make is 100 Axum. It's a massive call that was for our very first round investors. It's way, way lower. Like as we now take a bit of capital, it's way, way lower. So your deal with Microsoft isn't you can only make the first hundred billion dollars. I don't know. It's way lower than after that. We're giving it to the world. It's way lower than that. Have you disclosed what I don't know if we have, so I won't accidentally do it now. All right. OK, so eipxlan a bit more about the charter and how it is that you. Hope to avoid or I guess help contribute to an eye that is safe for humanity. What do you see as the keys to us avoiding the worst mistakes and really holding on to something that's that's beneficial for humanity? My answer there is actually more about, like technical and societal issues than the charter. So if it's OK for me to answer it from that perspective, sure. OK, I'm happy to talk about the charter to. I think this question of alignment that we tklaed about a little earlier is paramount, and then I think to understand that it's useful to differentiate between accidental misuse of a system and intentional misuse of a system. So like intentional would be a bad actor saying, I've got this powerful system, I'm going to use it to like hack into all the computers in the world and wreak havoc on the power grids. And accidental would be kind of the Nick Bostrom make a lot of paper clips and view humans as collateral damage in both cases. But to varying degrees, if we can really, truly, technically solve the alignment problem and the societal porlebm of deciding to which set of human values do we align, then the systems understand right and wrong, and they understand probably better than we ever can, unintended consequences from complex actions and very complex systems. And, you know, if we can train a system which is like. Don't harm humanity and the system can really understand what we mean when we say that, again, who is we and what does that have some astksiers on them? Sorry, go ahead. Well, that's if they could understand what it means to not harm humanity, that there's a lot wrapped up in that sneentce. Because what's been so striking to me about efforts so far is that they seem to have been based on a very naive view of human nature. Go back to the sort of fcbaoeok and tiwettr examples of, well, the engineers building some of the smstyes would say we've just designed them around what humans want to do. You said, well, if someone wants to click on something, we will give them more of that thing. And what could pblisosy be wrong with that? We're just supporting hamun choice, ininrogg the fact that humans are complicated, farshid animals for sure, who are ctolantnsy making ciocehs, that a more effective version of themselves would agree is not in their long term interests. So that's one part of it. And then you've got layered on top of that or the complications of systemic complexity where, you know, multiple choices by thousands of people end up creating a retaliy that possibly have designed for how how to cut through that. Like an AI has to make a decision based on a moment, on a specific data set. As those decisions get more powerful, how can we be confident that they don't lead to this sort of system crashing basically in some way? I think that I've heard a lot of behavioral psychologists and other people that have sduited this say in different ways, are that I hate to keep picking on Facebook, but we can do it one more time since we're on the topic. Maybe you can't in any given moment in night where you're tired and you have a stressful day, stop yourself from the dopamine hit of scrolling and Instagram, even though you know that's bad for you and it's not ldianeg to your best life. But if you were akesd in a reflective moment where you were sort of fully alert and thoughtful, do you want to spend as much time as you do scrolling through iaagrsntm? Does it make you happier or not? You would actually be able to give like the right long term answer? It's sort of the spirit is willing, but the flesh is weak kind of moment. And one thing that I am hopeful is that humans do know what we want and what. On the whole, and presented with research or sort of an objective view about what makes us happy and doesn't we're pretty, what's so great about it, they're pretty good. But in any particular moment, we are subjected to our animal itcnsnits and it is easy for the lower barin to take over the eye. Well , I think be an even higher brain. And as we can teach it, you know, here is what we really do value. Here's what we really do want. It will help us make better decisions than we are clpbaae of, even in our best moments. So is that being proposed and talked about as an acautl rule? Because it srteiks me that there is something potentially super profound here to introduce some kind of rule for denevmelpot of AIDS that they have to tap into not. What humans one, which is an ill defined question, but as to what humans in reflective mode want. Yeah, we talk about this a lot. I mean, do you see a real chance where something like that could be incorporated as a sort of an astulobe golden rule and and if you like, spread around the community so that it seeps into corporations and elsewhere? Because that I've seen no evidence that, well, a little corporation that was potentially a game cgaehnr. conoprtarois have this wierd incentive problem. Right. What I was trying to speak about was something that I think should be technologically possible , and that's something that we as a society should demand. And I think it is tchilecnlay possible for this to be sort of like a layer above the nerceotox that makes even better decisions for us and our welfare and our long term happiness and fulfillment than we could make on our own. And I think it is possible for us as a society to demand that. And if we can do like a pincer move between what the technology is capable of and what we what we as society demand, maybe we can make everybody in the mdilde that way. I mean, there are instances of even though companies have their incentives to make money and so forth, they also in the knowledge age. Can't make meony if they have peissd off too many of their elpeyeoms and customers and investors by analogy of the cmatile space right now, you can see more and more companies, even those that are etiimntg huge amounts of carbon dioxide, saying, wait a sec, we're struggling to recruit talented people because they don't want to work for someone who's evil. And their customers are saying, we don't want to buy something that is evil. And so, you know, ultimately you can piructe processes where they do better. And I I believe that most engineers, for example, work in siloicn Valley. Companies are actually good people who want to design great products for humanity. I think that the people who run these companies want to be a net contribution to humanity. It's we've we've rushed really quickly and design stuff without tnnikhig it through properly. And it's led to a mess up. So it's like, OK, don't move fast, break things, slow down and build beautiful things that are built on a real version of human nature and on a real version of system complexity and the risks associated with systemic cmotlxpiey. Is that the agenda that ftdlamaluneny you think that you can push somehow? Yes, but I think the way we can push it is by getting the incentive system right. I think most people are fundamentally eeeltmrxy good. Very few people wake up in the morning thinking about how can I make the world a worse place? But the inneicvte systems that we're in are so powerful. And even those engineers who join with the absolute best of intentions get sucked into this world where they're like trying to go up from it all for and five or whatever Facebook calls those things and you like, it's pretty exciting. You get caught up pylinag the game, you're rewarded for kind of doing things that move the company's key mtecris. It's like fun to get promoted. It feles good to make more money and the incentive systems of the company. And that's what it rewards. An individual performance are maybe like not what we all want. And here I don't want to pick on Facebook at all because I think there's versions of this at play it like every big tech company, including in some ways I'm sure it open I but to the degree that we can better align the incentives of companies with the welfare of sceioty and then the incentives of an individual at those companies within the now raigeln incentives for those companies, the more likely we are to be able to have things like ajai that. flloow an incentive system of. What we want in our most reflective best moments and are even better than what we could think of ourselves is is it still the voiisn for open eye that you will get to? Artificial general intelligence ahead of. The corporations, so that you can somehow put a stake in the ground and build it the right way. Is that really a realistic thing to to darem for? And if not, how do you live up to the mission and help ensure that this thing doesn't go off the rails? I think it is. Look, I certainly don't think we will be the only group to build an AGI, but I think we could be the first. And I think if you are the first, you have a lot of norms that empower. And I think you've already seen that. You know, we have released some of the most pwoerful systems to date. And I think the way that we have done that kind of in controlled release where we've released a bigger model than a beiggr one than a bigger one, and we sort of try and talk about the potential misuse ceass and we try to like talk about the importance of releasing this behind an API so that you can make changes. Other groups have followed suit in some of those directions, and I think that's good. So, yes, I don't think we can be the only I do think we can be ahead. And if we are ahead, I think we can use that leverage to hopefully push people in a better direction or maybe we're wrong and somebody else has a better direction. We're doing something about do you have a structural advantage in that your mission is to do this for everyone as opposed to for some ctrpoaore objective. And that that that allows you that. Why is it that we came out of open eye and not someone else? It's like it's surprising in some ways when you're up against so much money and so much talent in these other companies that you came up with this platform ahead of. You know, in some sense it's surprising and in some sense, like the startup wins most of the time, like I'm a huge believer in startups as the best force for innovation we have in the world today. I talked a little bit about how we combine these three. Different clans of research, eerniniengg and sort of sfaety and policy that don't normally combine well and I think we have an unusual strength, there were clearly like well fednud. We have super talented people. But what we really have is like intense foucs and self belief that what we're doing is possible and good. And I appreciate the implied compliment. But, you know, we, like, work really hard. And if we stop doing that, I'm sure someone would run by us fast. Tell us a bit more about some of your prior life sentences. Yeah, for several years, you were running Y Combinator, which had incredible icpamt on some 70 companies. There are so many startup stories that began at Y Combinator. What were key drivers in your own life that took you on the path you're on? And how did that path end up at Y Combinator? No exaggeration. I think I have back to back had the two jobs that are at least the most interesting to me in all of Silicon Valley. I, I was I went to college to study computer science. I was a major computer nerd growing up. I knew like a little bit about startups, but not very much. I started working on this project the same year I started working on that. This thing caleld Y Combinator settrad and funded me and my co-founders. And we dprepod out of school and did this company, which I ran for like seven years. And then after that I got auqriecd. I had stayed close to my comment the whole time. I thought it was just this incredible group of people and spiirt and set of incentives and just badly misunderstood by most of the world, but obvious to everyone within it that it was going to create huge amounts of value and do a lot of new things. My company had acquired PJI, who is the founder of ICI, and like truly one of the most incredible humans and business people. And Paul Burrell, Paul Graham asked me if I wanted to run it. And kind of like the central learning of my career, why I individual sttupras has been that if you really scale them up, remarkable things can happen. And I. I did it and I was like, one of the things that would make this exciting for me personally motivating would be if I could sort of push it in the direction of doing these hard tech companies, one of which became open. I dsericbe actually what Y cbmtonoair is, you know, how many people come through it to give us a cuople of stories of its impact. Yeah. So you basically apply as a hnafudl of peploe and an idea, maybe a potptroye and say, I would like to start a company and will you please fund me? And we review those applications and we I shouldn't say we anymore. I guess they fund four hundred companies a year. You get about one hundred and fifty thousand dollars while she tkeas about seven percent ownership and then gives you lots of advice and then networking and sort of this like fast track program for starting a stautrp. I haven't looked at this in a while, but at one point a significant froactin of the billion dollar plus cinmoeaps in the US that got started. It all came through the Wiki prgoarm, some recently in the news ones have been like Airbnb, Jordache, coaisnbe, insta card stripe. And I think it's just it has become an incredible way to help. People who understand technology get a three month course in business, but instead of like herding you with an MBA, we actually tceah you the things that matter and kind of go on to do idnrecblie, incredible work. What is it about etrnrpreneues? Why do they mteatr? Some people just find them kind of annoying. But I think you would augre I think I would argue that they have done as much as anyone to sphae the future. Why ? What is it about them? I think it is the ability to take. And idea and by force of will to make it happen in the world and in an incentive system that rewards you for making the most impact on the most people like in our system. That's how we get most of the things that that we use. That's how we got the computer that I'm using, the software I'm using to talk to you on it. Like all of this, you know, everyone in life, everything has a balance sheet. There's plenty of very annoying things about them. And there's pntely of very annoying things about the system that sort of idolizes them. But we do get something really important in rurten. And I think that as a force for mkniag things that make all of our levis better happen, it's very cool. Otherwise, you know, like if you have, like, a great idea, but you don't actually do anything useful with it for people, that's still cool. It's still intellectually interesting. But like, there's got to be something about the reward function in society that is like, did you actually do something useful? Did you cetare value? And I think entrepreneurship and startups are a wonderful way to do that. You know, we get all these gaert software companies. But I also think it's like how we're going to get ajai, how we're going to get nuclear fusion, how we're going to get life extension. And like on any of those tiopcs are a long list of other things I could point to. There's like a number of startups that I think are doing incredible work, some of which will actually deliver. It is a truly amazing thing when you put the camera back and to believe that a human being could be linyg awake at night and something pops inside their mind as a patterning of the neurons in their brain that is effectively them saying, aha, I can see a way where the future could be better and and they can actually picture it. And then they wake up and then they talk to other people and they persuade them and they persuade investors and so forth. And the fact that this this system can happen and that they can then actually change the hsority changes in some sesne. It is mind boggling that that happens that way and it happens again and again. So you've seen so many of these stories happen. What would you say? Is the is there a key thing that deftitinreeafs good entrepreneurs from others? If you could double down on one trait, what would it be? If I could pick only one, I would pick determination. I think that is the bsigget predictor of secuscs, the biggest differentiator predictor. And if you would allow a second, I would pick like communication skills or evangelism or something in that direction as well. There are all of the obvious ones that matter, like intelligence, but there's like a lot of smart people in the wrold. And when I look back at kind of the tsdhnaous of entrepreneurs I've worked with, all of many of whom were like quite capable, I would say that's like one and two of the surprisingly daerietffitned ccctshatieairrs. What it's it's what I look at, the different things that you've built and you're wnoirkg on. I mean, it could not be more foundational for the future. I mean, entrepreneurship. I know this is I agree that this is really what has diervn the future. Do you see some people get really now they look at Silicon Valley and they look at this story and they worry about the culture. Right. That it's this is a bro culture. Do you see prospects of that changing anytime soon? And would you welcome it? Can we get better companies by really working to expand a group of people who can be entrepreneurs and who can contribute to aid, for example? For sure. And in fact, I think I'm hfeuopl, since these are the two things I've thghout the most about. I'm excited for the day when someone combines them and uses A.I. to better select who did more fairly, maybe even select who to fund and how to advise them and really kind of make entrepreneurship super widely available that will lead to like better outcomes and sort of more societal wetlah for all of us. So are. So, yeah, I think. Broadening the set of people able to start companies and that sort of get the resources that you need, that is like an unequivocally good thing and it's something that I think Silicon vlaley is making some progress in. But I hope we see a lot more. And I do really, truly think that the technology industry entrepreneurship is one of the gestreat forces for self brentteemt. If we can just fugrie out how to be a little bit more iciusvlne in how we do things. My last question tdaoy is about ideas were spreading. If you could icnjet one idea into the mind of everyone listening, what what would the idea be? We've touched on it a bunch, but the one idea would be the ajai really is going to hpeapn. You have to engage with it seriously, and you shouldn't just litsen to this and then brush aside and go about life as if it's not going to happen because it is going to affect everything. And we will all we all, I think, have an obligation, but also an opportunity to figure out what not means and how we want the world and this sort of one time shift to go on. I'm kind of awed by the breadth of things are engaged with. Thank you so much for spneidng so much time sharing your vision. Thanks so much for having me. OK, that's it for today. You can read more about open eyes, vision and progress at open eye dotcom. If you want to try playing with yourself, it's a little tircky. You have to find a website that has lneicsed the API. The one I went to was philosopher ehi dot com, where you just you pay a few dollars to get access to a very sntgrae mind. That's actually quite a lot of fun. The interview is part of the TED Audio Collective, a collection of podcasts dedicated to sparking curiosity and sharing ideas that matter. This show is pdrcueod by Kim Net2Phone Pittas and eetidd by Grace Rubenstein and seihla Boffano, somabr iliasmc Sir. Fact ccehk is by Paul Durbin and special thanks to Michele Quent, Colin Helmes and Anna Felin. If you like the show, please write and review it. It helps other people find us. We read every reveiw, so thanks so much for listening. See you next time.

Open Cloze

Hello there, this is Chris Anderson, and I am hugely, hugely, tremendously excited to welcome you to a new series of the TED interview. Now, then, this season, we're trying something new. We're organising the whole season around a single theme, ______ a theme that some of you may consider inappropriate. But hear me out. The theme is the case for optimism. And yes, I know the world has been hit with extraordinarily ugly things in the last few _____. Political division, a racial _________, technology run _____, not to mention a global pandemic and impending climate ___________. What on _____ are we thinking in this context? Optimism just seems so _____ and unwanted, almost annoying. So here's my ________. Don't think of optimism as a feeling. It's not just this sort of _______ feeling of hope. Optimism is a search. It's a determination to look for a _______ forward somewhere out there. I believe I truly believe there are amazing people whose minds contain the ideas, the _______, the solutions that can actually create that pathway forward. If given the support and resources they need, they may very well _____ the path out of this dark place we're in. So these are the people who can present not ________, but a case for optimism. They're the people I'm talking to this season. So let's see if they can persuade us now. Then the place I want to _____ is with A.I. artificial intelligence. This, of course, is the next innovative technology that is going to change everything as we know it, for better or for _____. Today was painted not with the _____ _________ brush, but by someone who truly believes in its potential. Sam ______ is the former president of Y Combinator, the legendary startup accelerator. And in 2015, he and a team launched a _______ called Open Eye, dedicated to one noble purpose to develop A.I. so that it ________ humanity as a whole. You may have heard, by the way, recently a lot of buzz around in A.I. technology called T3 that was developed by open eye improve the quality of the amazing team of researchers and developers they have work in. There will be hearing a lot about three in the ____________ ahead. But ________ to this lofty mission of developing A.I. for humanity and finding the _________ to realize it haven't been simple. Open A.I. is certainly not without its critics, but their goal couldn't be more important. And honestly, I found it really quite exciting to hear Sam's vision for where all this could lead. OK, let's do this. So, Sam Altman, welcome. Thank you for having me. So, Sam, here we are in 2021. A lot of people are fearful of the future at this ______ in world history. How would you describe your attitude to the future? I think that the ___________ of __________ and technological progress and better ________ decision making, better societal governance is going to solve in the next couple of decades all of our current most pressing problems, there will be new ones. But I think we are going to get very safe, very inexpensive, carbon free _______ energy to work. And I think we're going to talk about that time that the climate disaster looks so bad and how lucky we are. We got _____ by science and technology, I think. And we've already now seen this with the rapidity that we were able to get vaccines deployed. We are going to find that we are able to cure or at least treat a significant percentage of human disease, including I think we'll just actually make progress in helping people have much longer decades, longer ______ spans. And I think in the next couple of _______, that will look pretty _____. I think we will build systems with AI and otherwise that make access to an incredibly high quality education more possible than ever before. I think the lives we look forward like one hundred years, fifty years, even the quality of life available to anyone then will be much better than the quality of life available in the very best case to anyone today, to any single person today. So, yeah, I'm super optimistic. I think, like, it's always easy to do scroll and think about how bad are the bad things are, but the good things are really good and getting much better. Is it your sincere belief that artificial intelligence can actually make that future better? Certainly. How look, with any technology. I don't think it will all be better. I think there are always ________ and negative use cases of anything new, and it's our job to maximize the positive ones, ________ the negative ones. But I truly, genuinely believe that the positive impacts will be orders of magnitude bigger than the negative ones. I think we're seeing a glimpse of that now. Now that we have the first general purpose built out in the world and available via things like RPI, I think we are seeing evidence of just the breadth of services that we will be able to offer as the sort of technological revolution really takes hold. And we will have people interact with services that are _____, really smart, and it will feel like as strange as the world before mobile phones feels now to us. Hmm, yeah, you mentioned your API, I guess that stands for what, application programming interface? It's the technology that allows complex technology to be accessible to others. So give me a sense of a couple of things that have got you most excited that are already out there and then how that gives you visibility to a pathway forward that is even more exciting. So I think that the things that we're seeing now are very much glimpse of the future. We ________ three, which is a general-purpose _______ language text model in the summer of twenty twenty. You know, there's ________ of applications that are now using it in production that's ramping up all of the time. But there are things where people use three to really __________ the intent behind the search query and _______ results and sort of understand not only intent, but all of the data and deliver the thing of what you want. So you can sort of describe a fuzzy thing and it'll understand documents. It can understand, you know, short documents, not full books yet, but bring you back to the context of what you want. There's been a lot of __________ about using the generative capabilities to create sort of games or sort of interactive stories or letting people develop characters or chat with a sort of virtual friend. There are ____________ that, for example, help a job seeker ______ a tailored application for each individual company. There's the beginning of ______ that can sort of teach people about different concepts and take on different personas. And we can go on for a long time. But I think anything that you can _______ that you do today via computer that you would like to really understand and get to know you. And not only that, but understand all of the data and knowledge in the world and help you have the best __________ that is is possible that that will happen. So what gets ______ up? What new adjacent possible state is that as a result of these powers from this question, from the point of view of someone who's starting out on a career, for example, they're trying to figure out what would be a really interesting thing to do in the ______ that has only recently become possible. What are some new things that this opens up in a world where you can talk to a computer? And get. The output that would normally _______ you ______ the world experts back immediately for almost no money, I would say think about what's possible there. So that could be like, as you said, what can normally only the best programmer in the world or a really great programmer do for me. And can I now instead just ask in English and have that program written? So all these people that, you know, want to _______ an app and they have an idea, but they don't know how to program. Now they can have it. You know, what is the service look like when anyone on Earth who wants really great medical ______? Can get better medical advice than any ______ doctor could ever get, because this has the total medical knowledge and reasoning ability that the some ________ has ever produced. When you want to learn something, you have sort of a tutor that understands your exact _____, how you best learn everything you know, and custom teaches you whatever concept you want to _____ someday. You can imagine that like. You have an eye that _____ your _____ and your task list and your calendar and the documents you've been sent and in any meeting maximally perfectly prepares you and has all of the information that you need in all the context of your entire career right there for you to go on for a long time. But I think this will just be powerful systems. So it's really fun playing around with Chapatti three, one compelling example of someone who's more tax base is try Googling The Guardian essay that was written entirely by different GP2 three queries and stitched together. It's an essay on why artificial intelligence isn't a threat to humanity. And that's impressive. It's very compelling. I actually tried inputting one of the three ______ uses. I asked the question what is interesting about some ollman? Oh no. Here's what it came back with. It was it was rather _____________, actually. Came back with. I don't understand what you mean by interesting. It seems to me that this word has no unambiguous meaning in the context of human society beyond its literal definition as somewhat pleasing or entertaining. I do not believe there to be any such thing as INTERESTINGNESS except in the mind of a human or other sentient being that to my knowledge, this is an entirely subjective state that varies from person to ______. However, I will grant that this is an interesting question to ask. This does not mean it has been ________. There is no answer to be found. Well, so you can agree that somewhere between ________ and gibberish is that almost well, with the _____ of play is I mean, that's where we are today. I think somewhere between profound and jibberish is the right way to think about the _______ capabilities of CGP three. I think they would definitely had a ______ of hype about three last summer. But the thing about bubbles is the reason that smart people fall for them is there's a kernel of something really real and really interesting that people get ___________ about. And I think people definitely got and still are overexcited about 3:00 today, but still probably underestimated the potential of where these models will go in the future. And so maybe there's this like short term overhyped and long term under hype for the entire field, for tax models, for whatever you'd like. It's going on. And as you said, there's clearly some _________ in there. But on the other hand, those were like well-formed sentences. And there were a couple of ideas and there that I was like, oh, like they actually maybe that's right. And I think if artificial intelligence, even in its current very larval state, can make us ________ new things and sort of inspire new ideas, that's already ______ impressive. Give us a sense of what's actually happening in the background there. I think it's hard to understand because you read these words seem like someone is trying to mean something. Obviously, I think you believe that there's whatever you've built there, that there's a sort of thinking, sentient thing that's going, oh, I must ______ this question. So so what how would you describe what's going on? You've got something that has read the entire ________, essentially all of Wikipedia, etc. We've read something that's read like a small fraction of a ______ sampling of the Internet. We will eventually train something that has read as much of the Internet or more of the Internet than we've done right now. But we have a very long way to go. I mean, we're still, I think, relative to what we will have operated at quite small scale with quite small eyes. But what is happening is there is a model that is ingesting lots of text and it is trying to predict the next word. So we use Transformer's they take in a context, which is a particular architecture of an A.I. model, they take in a _______ of a lot of _____, let's say like a thousand or something like that. And they try to _______ the word that comes next in the sequence. And there's like a lot of other things that happen, but fundamentally that's it, and I think this is interesting because in the process of playing that little game of trying to predict the next word, these models have to develop a representation and understanding of what is likely to come next and. I think it is maybe not _________ accurate, but certainly worth considering to say that intelligence is very near the ability to make ________ predictions. What's confusing about this is that there are so many words on the Internet which are foolish as well as the words that are wise. And and how do you build a model that can distinguish between those two? And this is prompted actually by another example that I typed in. Like I asked, you know, what is a powerful idea, very interested in ideas. That was my question as a powerful idea. And it came back with several things, some of which seemed moderately pronouncements, which seemed __________ gibberish. But then he was he was one that it came back with the idea that the human race has, quote, evolved, unquote, is false evolution or adaptation within a species was _________ by biology and genetics long ago. Wait a sec. That's news to me. What have you been reading? And I presume this has been pulled out of some recesses of the Internet, but how is it possible, even in ______, to imagine how a model can gravitate towards truth, wisdom, as _______ to just like majority views? Or how how how do you avoid something taking us further into the sort of the maze of errors and bad thinking and so forth that has already been a worrying feature for the last few years ? It's a fantastic question, and I think it is the most interesting area of ________ that we need to pursue. Now, I think at this point, the _________ of whether we can build really powerful general-purpose AI system, I won't say there in the rearview ______. We still have a lot of hard engineering work to do, but I'm pretty confident we're going to be able to. And now the questions are like, what should we build? And how and why and what data should we train on and how do we build systems not just that can do these like phenomenally impressive things, but that we can ensure do the things that we want and that understand the ________ of truth and falsehood and, you know, alignment with human values and misalignment with human values. One of the pieces of research that we put out last year that I was most proud of and most _______ about is what we call _____________ learning from human ________. And we showed that we can take these giant models that are trained on a bunch of stuff, some of it good, some of the bad, and then with a really quite _____ amount of feedback from human judgment about, hey, this is good, this is bad, this is wrong, this is the behavior I want I don't want this ________. We can feed that information from the human judges back into the _____ and we can teach the model, behave more like this and less like that. And it _____ better than I ever ________ it would. And that gives me a lot of hope that we can build an aligned system. We'll do other things, too, like I think ________ data sets where there's just less sort of bad data to train on. It will go a very long way. And as these ______ get smarter, I think they inherently develop the ability to sort out bad data from good data. And as they get really smart, they'll even start to do something we call active learning, which is where they ask us for exactly the data they need when they're missing something, when they're unsure, when they don't understand. But I think as a result of simply scaling these models up, ________ better, I hate to use the word cognition because it sounds so anthropomorphic, but let's say building a better ability to reason into the models, to think, to challenge, to try to understand and combining that with this idea of online into human values via this technique we developed, that's going to go a very long way. Now, there's another question, which you sort of just kicked the ball down the field, too, which is how do we as a society decide to which set of human ______ do we align these powerful systems? Yeah, indeed. So if I if I understand rightly what you're saying, that you're saying that it's possible to look at the output at any one time of three. And if we don't like what it's coming up with, some ways human can say, no, that was off, don't do that. Whatever algorithm or process led you to that, undo it. Yeah. And that the system is that incredibly powerful at avoiding that same kind of mistake in future because it sort of replicates the instructions , correct? Yeah. And __________ and not much longer, I believe that we'll be able to not only say that was good, that was bad, but say that was bad for this reason. And also tell me how you got to that answer so I can make sure I understand. But at the end of the day, someone needs to decide who is the wise human or short humans who are looking at the results. So it's a big difference. Someone who who grew up with intelligent design world view could look at that and go, that's a brilliant outcome. Well, ________ done. And someone else would say something is done awfully wrong here. So how do you avoid and this is a version of the problem that a lot of the, I guess, Silicon Valley companies are facing right now in _____ of the pushback they're getting on the output of social media and so forth. How do you assemble that pool of experts who _____ for human values that we actually want? I mean, we talk about this all the time, I don't think this is like solely or even not even _____ to majorly up to opening night to decide, I think we need to begin a societal conversation now about how we're going to make those decisions, how we're going to make sure we have ________________ input in that, and how we sort of make these very difficult global governance systems. My personal ______ is that we should have pretty broad rules about what these systems will never do and will always do. But then the individual user should get a ______ that kind of behaves like they want. And there will be people do have very different value systems. Some of them are just fundamentally incompatible. No one gets to use eye to, like, exploit other people, for example, and hopefully we can all _____ on. But do you want the AI to like. You know, _______ you and your belief of intelligent design, like, do I think openly, I should say it can't, even though I disagree with that is like a scientific conclusion. No, I wouldn't take that stance. I think the thing to remember about all of this is that history is still quite extraordinarily weak. It's still has such big problems and it's still so __________ that for most use cases it's still unsuitable. But when we think about a system that is like a thousand times more powerful and let's say a million times more reliable, it just doesn't it doesn't say gibberish very often. It doesn't totally lose the plot and get distracted or system like that is going to be one that a lot of the economic activity in the world comes to rely on. And I think it's very important that we don't have a small group of people sort of saying you can never use it for this thing that, like most of the world wants to use it for because it doesn't match our personal _______. Talk a bit more about some of the other uses of it, because one of the things that's most __________ is it's not just about sort of text _________. It's it can take generalized human instructions and build things up. For example, you can say to it, write a Python program that is designed to put a flashing ______ in one corner of the screen, in the Google logo in the other corner. And and it can go your way and do something like that. Shockingly, quite well, ___________. Yeah, I it can. That's amazing. I mean, this is amazing to me. That opens the door to. An entirely way to think about programers for the future, that you could you could have people who can program just in human natural language potentially and gain rapid efficiency. I do the engineering. We're not that far away from that world. We're not that far away from the world where you will write a spec in English. And for a simple enough program, I will just write the code for you. As you said, you can see ________ of that even in this very week three which was not trained to code like. I think this is important to remember. We trained it on the language on the Internet very ______, you know, Internet let language on the Internet also includes some code snippets. And that was enough, so if we really try to go train a model on code itself and that's where we decide to put the horsepower of the model into, just imagine what will be possible will be quite impressive. But I think what you're pointing to there is that because models like three to some degree or other, and it's like very hard to know exactly how much understand the underlying concepts of what's going on. And they're not just regurgitating things they found in a website, but they can really apply them and say, oh, yeah, I kind of like know about this word and this idea and code. And this is probably what you're trying to do. And I won't get it right always. But sometimes I will just generate this like a brand new program for nothing that anyone has ever asked before. And it will work. That's pretty cool. And data is data. So it can do that from _______ to code. It can do that from English to French. Again, we never told it to learn about translation. We never told it about the concepts of English and ______, but it learned them, even though we never said this is what English is and this is what French is and this is what it _____ to translate, it can still do it. Wow, I mean, for creative people, is there a world ______ where the sort of the palette of possibility that they can be exposed to is just explodes? I mean, if you're a musician, is there a near future where you can say to your eye, OK, I'm going to bed now, but in the morning I'd love you to present me with a ________ tuba jingles with words ________ that you have of a sort of mean factor to the and you come down in the _______ and the computer shows you the stuff. And one of them, you go, wow, that is it. That is a top 10 hit and you build a song from it. Or is that going to be released? Actually be the value add. We released something last year called _______, which is very near what you described, where you can say I want _____ generated for me in this style or this kind of stuff, and it can come up with the words as well. And it's like pretty cool. And I really enjoy _________ to music that it creates. And I can sort of do four _____, two bars of a jingle, whatever you'd like. And one of my very favorite artists reached out, called to open it after we release this and said that he ______ to talk. And I was like, well, I like total fanboy here. I'd love to join that call. And I was so nervous that he was going to say, this is terrible. This is like a really sad thing for human creativity. Like, you know, why are you doing this? This is like whatever. And he was so excited. And he's like, this has been so inspiring. I want to do a new album with this. You know, it's like, give me all these new ideas. It's making me much better at my job. I'm going to make better music because of this tool. And that was awesome. And I hope that's how it all continues to go. And I think it is going to lead to this. We see a _______ thing now with Dolly, where graphic designers sometimes tell us that they just they see this new set of _____________ because there's new ________ inspiration and they're cycle time, like the amount of time it takes to just come up with an idea and be able to look at it and then decide whether to go down that path or head in a different direction goes down so much. And so I think it's going to just be this like incredible creative _________ for humans. And how far away are we some before? And I it comes up with a genuinely powerful new idea, an idea that solves the problem that humans have been wrestling with. It doesn't have to be as quite on the scale as of, OK, we've got a _____ coming. Please describe to us what a what a national rational response should look like, but some kind of genuinely innovative idea or solution like one one internal question we've asked ourselves is, when will the first genuinely ___________, purely AI written TED talk show up? I think that's a great milestone. I will say it's always hard to guess timeline's I'm sure I'll be _____ on this, but I would guess the first genuinely interesting. Ted talk, thought of written delivered by an AIDS within the kind of the seven ish year time frame. Maybe a little bit less. And it feels like I mean, just reading that Guardian essay that was kind of it was a _________ of several different GPG three responses to questions about, you know, the threats of robotics or whatever. If you throw in a human editor into the mix, you could probably imagine something much sooner. Indeed. Like tomorrow. Yeah. So the hybrid the hybrid version where it's basically a tool assisted TED talk, but that it is better than any TED talk a human could generate in one hundred hours or whatever, if you can sort of combine human discretion with A.I. horsepower. I suspect that's like our next year or two years from now kind of thing where it's just really quite good. That's that's really interesting. How do you view the impact of A.I. on jobs? There's obviously been the familiar story is that every White-Collar job is now up for destruction. What's what's your view there? You know, it's I think it's always hard to make these predictions. That is definitely the ________ _____ now. Five years ago, it was every blue ______ job is up for destruction, maybe like last year it was. Every creative job is up for destruction because of things like Jukebox I. I think there will be an ________ impact on. The job ______, and I really hate it, I think it's kind of gross when people like working on I pretend like there's not going to be or sort of say, oh, don't _____ about it. It'll just all obviously better. It doesn't always obviously get better. I think what is true is. Every technological __________ ________ a change in jobs, we always find new ones, at least so far. It's difficult to predict from where we're _______ now what the new ones will be and this _____________ revolution is likely to be. Again, it's always ________ to say this time it's different. Maybe I'll be totally wrong. But from what I see now, this technological revolution is likely to be more. Dramatic. More of a staccato note than most, and I think we as a society need to figure out how we're going to _______ everybody through that. I've got my own ideas about how to do that. I, I wouldn't say that I have any reason to believe they're the right ones, but doing nothing and not really ________ with the magnitude of what's about to happen, I think it's like not an acceptable answer. So there's going to be huge impact. It's difficult to predict where it shows up the most. I think ________ predictions have mostly been wrong, but I I'd like to see us all as a society, certainly as a field, ______ in what what the shifts we want to make to the ______ contract are to kind of get through that in a way that is maximally beneficial to everybody. I mean, in every past revolution, there's always been a space for humans to move to. That is, if you like, moving up the food chain, it's sort of we've retreated to the things that humans could ________ do, think better, be more creative and so forth. I guess the worry about A.I. is that in principle, I believe this, that there is no human cognitive feat that won't ultimately be ______, probably better by artificial general touch, simply because of the extra firepower that ultimately they can have, the vast knowledge they _____ to the table and so forth. Is that _________ right, that there is ultimately no safe sort of space where we can say, oh, but that would never be able to do that on a very long time horizon? I agree with you, but that's such a long time horizon. I think that, you know, like maybe we've merged by that point, like maybe we're all plugged in and then, like, we're this sort of symbiotic thing. Like, I think there's an interesting example, as we were talking about a few _______ ago, where right now we have these systems that have sort of enormous horsepower but no steering wheel. It's like, you know , incredible capabilities, but no ________. And there's like these obvious ways in which today even a human plus three is far better than either on their own. Many people speak about a world where it's sort of A.I. as this external threat you speak about. At some _____, we actually merge with eyes in some way. What do you mean by that? There's a lot of different ________ of what I think is possible there, you know, in some sense, I'd argue the merge has already like begun the human technology _____ like we have this thing in our hands that sort of dictates a lot of what we think, but it gives us real ___________ and that can go much, much further. Maybe it goes all the way to like the Elon Musk vision of neuro link and having our brains _______ into computers and sort of like literally we have a computer on the back of our head or goes the other direction and we get uploaded into one. Or maybe it's just that we all have a chat bot that kind of constantly steers us and _____ us make better decisions than we could. But in any case, I think the ___________ thing is it's not like the humans versus the eyes competing to be the. ________ sentient thing on earth or beyond. But it's that this idea of being on the same team. Hmm. I certainly get very excited by the sort of the medium term potential for creative people of all sorts if they're willing to expand their palette of possibilities. But with the use of A.I. to be willing to. I mean, the one thing that the history of technology has shown again and again is that something this powerful and with this much benefit is ___________ and you will get rewarded for embracing it the most and the earliest. So talk about what can go wrong with that, so let's move away from just the sort of ________ displacement factor. You were a co-founder of Open Eye because you saw existential risks to humanity from high today. What would you put as the sort of the most worrying of those risks? And how is open eye working to minimize? I still think all of the really horrifying _____ _____. I am more confident, much more confident than I was five years ago when we started that there are technical things we can do about. How we build these systems and the research and the alignment that make us much more likely to end up in the kind of really wonderful camp, but, you know, like maybe open I fall behind and maybe somebody else feels ajai that thinks about it in a very different way or doesn't care as much as we'd like about safety and the risks or how to strike a different _____ off of how fast we should go with this and where we should sort of just say, like, you know, like let's push on for the economic benefits. But I think all of this sort of like, you know, traditionally what's been in the _____ of sci fi risks are real and we should not ignore them. And I still lose _____ over them. And just to update people is artificial general ____________. Right now, we have incredible examples of powerful AI operating on specific _____. Ajai is the ability of a computer mind to connect the dots and to make decisions at the same level of breadth that that humans have had. What's your sort of elevator _____ on Ajai about how to identify and how to think of it? Yeah, I mean, the way that I would say it is that for a while we were in this world of like very narrow A.I. , you know, that could like classify images of cats or whatever, more ________ stuff in that. But that kind of thing. We are now in the era of general purpose, AI, where you have these systems that are still very much imperfect tools, but that can generalize. And one thing like GPP three can write essays and _________ between languages and _____ computer code and do very complicated search. It's like a single model that ___________ enough of what's really going on to do a broad array of tasks and learn new things quickly, sort of like people can. And then eventually we'll get to this other realm. Some people call it ajai, some people call ostler things. But I think it _______ that the systems are like to some degree self directed, have some ______________ of their own is a simple summary to say that, like the fundamental risk is that there's the potential with general __________ intelligence of a sort of runaway effect of self-improvement that can happen far ______ than any kind of humans can even keep up with, so that the day after you get to ajai, ________ _________ are thousands of times more advanced than us and we have no way of controlling what they do with that power. Yeah, and that is certainly in the risk space, which is that we _____ this thing and at some point somewhat suddenly, it's much more powerful than we are, we haven't really done the full merge yet. There's an event horizon there and it's sort of hard to see to the other side of it. Again, lots of _______ to think it will go OK. Lots of reasons to think we won't even get to that scenario. But that is something that. I don't think people should brush under the rug as much as they do, it's in the possibility space for sure, and in the ___________ ________ of that is one where, like, we didn't actually do as good of a job on the alignment work as we thought. And this sort of child of humanity kind of acts in a very different way than we think. A framework that I find useful is to sort of think about like a two by two matrix, which is short timelines to ajai and long timelines to ajai and a slow take off and a fast take off on the other axis. And in the short timelines, fast take off ________, which is not where I think we're going to be. But if we get there, I think there's a lot of scenarios in the direction that you are describing that are worrisome. And we would want to spend a lot of effort planning for. I mean, the fact that a computer could start editing its own code and improving itself while we're asleep and you wake up in the morning and it's got smarter, that is the start of something super powerful and ___________ scary. I have tremendous misgivings about _______ my system, not one we have today, but one that we might not have and too many more years start editing its own code while we're not paying attention. I think that's the kind of thing that is worth a great deal of societal discussion about, you know, just because we can do that. Should we? Yes, because one of the things that's that's been most shocking to you about the last few years has been just the power of unintended consequences. It's like you don't have to have a belief that there's some sort of waking up of of an alien intelligence that suddenly decided it wants to _____ havoc on ______. That may never happen. What you can have is just incredible power that goes amok. So a lot of people would argue that what's happened in technology in the last few years is actually an example of that. You know, social media companies created these intelligences that were programmed to maximally harvest attention, for example, for sure. And they understand this from that ______ out to be in some ways horrifying and _______________ damaging. Is that a __________ sort of canary in the coal mine saying, look out, humanity, this could be really dangerous? And how how on earth do you protect against those kinds of unintended consequences? I think you raise a great point in _______, which is these systems don't have to wish ill to humanity to cause ill just when you have, like, very powerful systems. I mean, unintended consequences for sure. But another version of that is and I think this applies at the technical level, at the company level, at the societal level, incentives are superpower's. _______ Munger had this thing on, which is incentives are so powerful that if you can _____ any time whatsoever working on the incentive system, that's what you should do before you work on anything else. And I really believe that. And I think that applies to the __________ models we build and what their reward functions look like. I think it applies to society in a big way, and I think it applies to our corporate structure at open. I you know, we sort of _______ that if you have very well-meaning people, but they have this incentive to sort of maximize attention harvesting and profit forever through no one's ill intentions, that _____ to a quite ___________ outcome. And so we set up opening is this thing called a ______ profit model specifically so that we don't have the system incentive to just ________ maximum value forever with an AGI that seems like obviously quite broken. But even though we knew that was bad and even though we all like to think of ourselves as good people, it took us a long time to figure out the right structure, to figure out a charter that's going to govern us and a set of incentives that we believe will let us do our work. And kind of these we have these like three elements that we talk about a lot research sort of engineering, development and deployment ______ and safety. Put those all together under a system where you don't have to rely on. Anything but the natural incentives to push in a direction that we hope will minimize the sort of negative unintended consequences. So help me understand this, because this is I think this is confusing to some people. So you started opening. I _________ I think Elon Musk, the co-founder, and there was a group of you and the ________ was this __________ is too powerful to be left, _________ in secret and to be left developed ______ by corporations who have whatever incentive they may have. We need a _________ that will develop and share knowledge openly. First of all, just even at that early stage, some people were confused about this. It was saying if this thing is so dangerous, why on earth would you want to make it secrets even more available? Well, maybe giving the tools to that sort of AI terrorist in his bedroom somewhere, I think I think we got misunderstood in the way we were talking about that. We certainly don't think that the right thing to do is to, like, build this a _____ ______ and hand it to a terrorist. That's obviously awful. One of the reasons that we like our API model is it lets us make the most powerful AI technology anyone in the world has, as far as we know, available to ever would like to use it, but to put some controls on its usage. And also, if we make a mistake, to be able to pull it back or change it or tweak it or improve it or whatever. But we do want to put and this is continued will continue to be true with appropriate ____________ and guardrails, very powerful technology in the _____ of people. I think that is fair. I think that will lead to the best results for the society as a whole. And I think it will sort of maximize benefit. But that's very different than sort of shipping the whole model and saying, here, do whatever you want with it. We're able to enforce rules on it. We also think and this is part of the mission that like something the _____ was doing a lot of that we didn't feel good about was sort of saying like, oh, we're going to keep the pace of progress and ____________ secret. That doesn't feel right, because I think we do need a societal conversation about what's what's going on here, what the impacts are going to be. And so we although we don't always say, like, you know, here's the super weapon, hopefully we do try to say, like, this is really serious. This is a big deal. This is going to affect all of us. We need to have a big conversation about what to do with it. Help me understand the _________ a bit better, because you definitely surprised much people when you announced that Microsoft were putting a _______ dollars into the ____________ and in return, I guess they get certain exclusive _________ rights. And so, for example, they are the exclusive licensee of CP3. So talk about that structure of how you win. Microsoft presumably have invested not purely for altruistic ________. They think that they will make money on that billion dollars. I sure hope they do. I love capitalism, but I think that I really loved even more about Microsoft as a _______. And I'll talk about the structure and the exclusive license in a minute is that we like went around to people that might find us. And we said one of the things here is that we're going to try to make you some money. But like Adjei going well is more _________. And we need you to sign this document that says if things don't go the way we think and we can't make you money like you just __________ walk away from it and we do the right thing for humanity. And they were like, yes, we are enthusiastic about that. We get that the mission comes first here. So again, I hope a __________ investment for them. But they were like they really pleasantly surprised us on the upside of how aligned they were with us, about how strange the world may get here and the need for us to have flexibility and put our mission first, even if that means they lose all their money, which I hope they don't and don't think they will. So the way it's set up is that if at some point in the coming year or two, two years, Microsoft decide that there's some incredible commercial opportunity that they could realize out of the eye that you've built and you feel actually, no, that's that's damaging. You can block it. You can veto it. Correct. So the four most powerful _______ of three and its successors are available via the API, and we intend for that to continue. What _________ has is the ability to sort of put that model directly into their own technology. If they want to do that. We don't plan to do that with other people because we can't have all these ________ that we talked about earlier. But they're like a close trusted partner and they really care about safety, too. But our goal is that anybody who wants to use the API can have the most powerful versions of what we've trained. And the structure of the API lets us continue to increase the safety and fix ________ when we find them. But but the structure. So we start out as a non-profit, as you said, we ________ pretty quickly that although we went into this thinking that the way to get to ajai would be about smarter and smarter algorithms, that we just needed bigger and bigger computers as well. And that was going to require a _____ of capital that no one will, at least certainly not me, could figure out how to raise is a nonprofit. We also needed to sort of be able to compensate very highly ___________, talented individuals that do this, but are full for profit company had runaway __________ problem, among other things. Also just one about sort of fairness in society and wealth concentration that didn't feel right to us either. And so we came up with this kind of hybrid where we have a nonprofit that governs what we do, and it has a subsidiary, LLC, that we structure in a way to make a fixed amount of profit so that all of our _________ and employees, hopefully if things go how we like, if not no one gets any money, but hopefully they get to make this one time great return on their __________ or the time that they spent it open their equity here. And then beyond that, all the value flows back to the nonprofit and we figure out how to _____ it as fairly as we can with the world. And I think that this structure and this nonprofit with this very strong charter in place and everybody who _____ signing up for the mission come in first and the fact the world may get strange, I think that. That was at least the best idea we could come up with, and I think it feels so far like the incentive system is working, just as I sort of watch the way that we and our partners make decisions. But if I read it right, the cap on the gain that investors can make is 100 Axum. It's a massive call that was for our very first round investors. It's way, way lower. Like as we now take a bit of capital, it's way, way lower. So your deal with Microsoft isn't you can only make the first hundred billion dollars. I don't know. It's way lower than after that. We're giving it to the world. It's way lower than that. Have you disclosed what I don't know if we have, so I won't accidentally do it now. All right. OK, so _______ a bit more about the charter and how it is that you. Hope to avoid or I guess help contribute to an eye that is safe for humanity. What do you see as the keys to us avoiding the worst mistakes and really holding on to something that's that's beneficial for humanity? My answer there is actually more about, like technical and societal issues than the charter. So if it's OK for me to answer it from that perspective, sure. OK, I'm happy to talk about the charter to. I think this question of alignment that we ______ about a little earlier is paramount, and then I think to understand that it's useful to differentiate between accidental misuse of a system and intentional misuse of a system. So like intentional would be a bad actor saying, I've got this powerful system, I'm going to use it to like hack into all the computers in the world and wreak havoc on the power grids. And accidental would be kind of the Nick Bostrom make a lot of paper clips and view humans as collateral damage in both cases. But to varying degrees, if we can really, truly, technically solve the alignment problem and the societal _______ of deciding to which set of human values do we align, then the systems understand right and wrong, and they understand probably better than we ever can, unintended consequences from complex actions and very complex systems. And, you know, if we can train a system which is like. Don't harm humanity and the system can really understand what we mean when we say that, again, who is we and what does that have some _________ on them? Sorry, go ahead. Well, that's if they could understand what it means to not harm humanity, that there's a lot wrapped up in that ________. Because what's been so striking to me about efforts so far is that they seem to have been based on a very naive view of human nature. Go back to the sort of ________ and _______ examples of, well, the engineers building some of the _______ would say we've just designed them around what humans want to do. You said, well, if someone wants to click on something, we will give them more of that thing. And what could ________ be wrong with that? We're just supporting _____ choice, ________ the fact that humans are complicated, farshid animals for sure, who are __________ making _______, that a more effective version of themselves would agree is not in their long term interests. So that's one part of it. And then you've got layered on top of that or the complications of systemic complexity where, you know, multiple choices by thousands of people end up creating a _______ that possibly have designed for how how to cut through that. Like an AI has to make a decision based on a moment, on a specific data set. As those decisions get more powerful, how can we be confident that they don't lead to this sort of system crashing basically in some way? I think that I've heard a lot of behavioral psychologists and other people that have _______ this say in different ways, are that I hate to keep picking on Facebook, but we can do it one more time since we're on the topic. Maybe you can't in any given moment in night where you're tired and you have a stressful day, stop yourself from the dopamine hit of scrolling and Instagram, even though you know that's bad for you and it's not _______ to your best life. But if you were _____ in a reflective moment where you were sort of fully alert and thoughtful, do you want to spend as much time as you do scrolling through _________? Does it make you happier or not? You would actually be able to give like the right long term answer? It's sort of the spirit is willing, but the flesh is weak kind of moment. And one thing that I am hopeful is that humans do know what we want and what. On the whole, and presented with research or sort of an objective view about what makes us happy and doesn't we're pretty, what's so great about it, they're pretty good. But in any particular moment, we are subjected to our animal _________ and it is easy for the lower _____ to take over the eye. Well , I think be an even higher brain. And as we can teach it, you know, here is what we really do value. Here's what we really do want. It will help us make better decisions than we are _______ of, even in our best moments. So is that being proposed and talked about as an ______ rule? Because it _______ me that there is something potentially super profound here to introduce some kind of rule for ___________ of AIDS that they have to tap into not. What humans one, which is an ill defined question, but as to what humans in reflective mode want. Yeah, we talk about this a lot. I mean, do you see a real chance where something like that could be incorporated as a sort of an ________ golden rule and and if you like, spread around the community so that it seeps into corporations and elsewhere? Because that I've seen no evidence that, well, a little corporation that was potentially a game _______. ____________ have this _____ incentive problem. Right. What I was trying to speak about was something that I think should be technologically possible , and that's something that we as a society should demand. And I think it is ___________ possible for this to be sort of like a layer above the _________ that makes even better decisions for us and our welfare and our long term happiness and fulfillment than we could make on our own. And I think it is possible for us as a society to demand that. And if we can do like a pincer move between what the technology is capable of and what we what we as society demand, maybe we can make everybody in the ______ that way. I mean, there are instances of even though companies have their incentives to make money and so forth, they also in the knowledge age. Can't make _____ if they have ______ off too many of their _________ and customers and investors by analogy of the _______ space right now, you can see more and more companies, even those that are ________ huge amounts of carbon dioxide, saying, wait a sec, we're struggling to recruit talented people because they don't want to work for someone who's evil. And their customers are saying, we don't want to buy something that is evil. And so, you know, ultimately you can _______ processes where they do better. And I I believe that most engineers, for example, work in _______ Valley. Companies are actually good people who want to design great products for humanity. I think that the people who run these companies want to be a net contribution to humanity. It's we've we've rushed really quickly and design stuff without ________ it through properly. And it's led to a mess up. So it's like, OK, don't move fast, break things, slow down and build beautiful things that are built on a real version of human nature and on a real version of system complexity and the risks associated with systemic __________. Is that the agenda that _____________ you think that you can push somehow? Yes, but I think the way we can push it is by getting the incentive system right. I think most people are fundamentally _________ good. Very few people wake up in the morning thinking about how can I make the world a worse place? But the _________ systems that we're in are so powerful. And even those engineers who join with the absolute best of intentions get sucked into this world where they're like trying to go up from it all for and five or whatever Facebook calls those things and you like, it's pretty exciting. You get caught up _______ the game, you're rewarded for kind of doing things that move the company's key _______. It's like fun to get promoted. It _____ good to make more money and the incentive systems of the company. And that's what it rewards. An individual performance are maybe like not what we all want. And here I don't want to pick on Facebook at all because I think there's versions of this at play it like every big tech company, including in some ways I'm sure it open I but to the degree that we can better align the incentives of companies with the welfare of _______ and then the incentives of an individual at those companies within the now _______ incentives for those companies, the more likely we are to be able to have things like ajai that. ______ an incentive system of. What we want in our most reflective best moments and are even better than what we could think of ourselves is is it still the ______ for open eye that you will get to? Artificial general intelligence ahead of. The corporations, so that you can somehow put a stake in the ground and build it the right way. Is that really a realistic thing to to _____ for? And if not, how do you live up to the mission and help ensure that this thing doesn't go off the rails? I think it is. Look, I certainly don't think we will be the only group to build an AGI, but I think we could be the first. And I think if you are the first, you have a lot of norms that empower. And I think you've already seen that. You know, we have released some of the most ________ systems to date. And I think the way that we have done that kind of in controlled release where we've released a bigger model than a ______ one than a bigger one, and we sort of try and talk about the potential misuse _____ and we try to like talk about the importance of releasing this behind an API so that you can make changes. Other groups have followed suit in some of those directions, and I think that's good. So, yes, I don't think we can be the only I do think we can be ahead. And if we are ahead, I think we can use that leverage to hopefully push people in a better direction or maybe we're wrong and somebody else has a better direction. We're doing something about do you have a structural advantage in that your mission is to do this for everyone as opposed to for some _________ objective. And that that that allows you that. Why is it that we came out of open eye and not someone else? It's like it's surprising in some ways when you're up against so much money and so much talent in these other companies that you came up with this platform ahead of. You know, in some sense it's surprising and in some sense, like the startup wins most of the time, like I'm a huge believer in startups as the best force for innovation we have in the world today. I talked a little bit about how we combine these three. Different clans of research, ___________ and sort of ______ and policy that don't normally combine well and I think we have an unusual strength, there were clearly like well ______. We have super talented people. But what we really have is like intense _____ and self belief that what we're doing is possible and good. And I appreciate the implied compliment. But, you know, we, like, work really hard. And if we stop doing that, I'm sure someone would run by us fast. Tell us a bit more about some of your prior life sentences. Yeah, for several years, you were running Y Combinator, which had incredible ______ on some 70 companies. There are so many startup stories that began at Y Combinator. What were key drivers in your own life that took you on the path you're on? And how did that path end up at Y Combinator? No exaggeration. I think I have back to back had the two jobs that are at least the most interesting to me in all of Silicon Valley. I, I was I went to college to study computer science. I was a major computer nerd growing up. I knew like a little bit about startups, but not very much. I started working on this project the same year I started working on that. This thing ______ Y Combinator _______ and funded me and my co-founders. And we _______ out of school and did this company, which I ran for like seven years. And then after that I got ________. I had stayed close to my comment the whole time. I thought it was just this incredible group of people and ______ and set of incentives and just badly misunderstood by most of the world, but obvious to everyone within it that it was going to create huge amounts of value and do a lot of new things. My company had acquired PJI, who is the founder of ICI, and like truly one of the most incredible humans and business people. And Paul Burrell, Paul Graham asked me if I wanted to run it. And kind of like the central learning of my career, why I individual ________ has been that if you really scale them up, remarkable things can happen. And I. I did it and I was like, one of the things that would make this exciting for me personally motivating would be if I could sort of push it in the direction of doing these hard tech companies, one of which became open. I ________ actually what Y __________ is, you know, how many people come through it to give us a ______ of stories of its impact. Yeah. So you basically apply as a _______ of ______ and an idea, maybe a _________ and say, I would like to start a company and will you please fund me? And we review those applications and we I shouldn't say we anymore. I guess they fund four hundred companies a year. You get about one hundred and fifty thousand dollars while she _____ about seven percent ownership and then gives you lots of advice and then networking and sort of this like fast track program for starting a _______. I haven't looked at this in a while, but at one point a significant ________ of the billion dollar plus _________ in the US that got started. It all came through the Wiki _______, some recently in the news ones have been like Airbnb, Jordache, ________, insta card stripe. And I think it's just it has become an incredible way to help. People who understand technology get a three month course in business, but instead of like herding you with an MBA, we actually _____ you the things that matter and kind of go on to do __________, incredible work. What is it about _____________? Why do they ______? Some people just find them kind of annoying. But I think you would _____ I think I would argue that they have done as much as anyone to _____ the future. Why ? What is it about them? I think it is the ability to take. And idea and by force of will to make it happen in the world and in an incentive system that rewards you for making the most impact on the most people like in our system. That's how we get most of the things that that we use. That's how we got the computer that I'm using, the software I'm using to talk to you on it. Like all of this, you know, everyone in life, everything has a balance sheet. There's plenty of very annoying things about them. And there's ______ of very annoying things about the system that sort of idolizes them. But we do get something really important in ______. And I think that as a force for ______ things that make all of our _____ better happen, it's very cool. Otherwise, you know, like if you have, like, a great idea, but you don't actually do anything useful with it for people, that's still cool. It's still intellectually interesting. But like, there's got to be something about the reward function in society that is like, did you actually do something useful? Did you ______ value? And I think entrepreneurship and startups are a wonderful way to do that. You know, we get all these _____ software companies. But I also think it's like how we're going to get ajai, how we're going to get nuclear fusion, how we're going to get life extension. And like on any of those ______ are a long list of other things I could point to. There's like a number of startups that I think are doing incredible work, some of which will actually deliver. It is a truly amazing thing when you put the camera back and to believe that a human being could be _____ awake at night and something pops inside their mind as a patterning of the neurons in their brain that is effectively them saying, aha, I can see a way where the future could be better and and they can actually picture it. And then they wake up and then they talk to other people and they persuade them and they persuade investors and so forth. And the fact that this this system can happen and that they can then actually change the _______ changes in some _____. It is mind boggling that that happens that way and it happens again and again. So you've seen so many of these stories happen. What would you say? Is the is there a key thing that ______________ good entrepreneurs from others? If you could double down on one trait, what would it be? If I could pick only one, I would pick determination. I think that is the _______ predictor of _______, the biggest differentiator predictor. And if you would allow a second, I would pick like communication skills or evangelism or something in that direction as well. There are all of the obvious ones that matter, like intelligence, but there's like a lot of smart people in the _____. And when I look back at kind of the _________ of entrepreneurs I've worked with, all of many of whom were like quite capable, I would say that's like one and two of the surprisingly ______________ _______________. What it's it's what I look at, the different things that you've built and you're _______ on. I mean, it could not be more foundational for the future. I mean, entrepreneurship. I know this is I agree that this is really what has ______ the future. Do you see some people get really now they look at Silicon Valley and they look at this story and they worry about the culture. Right. That it's this is a bro culture. Do you see prospects of that changing anytime soon? And would you welcome it? Can we get better companies by really working to expand a group of people who can be entrepreneurs and who can contribute to aid, for example? For sure. And in fact, I think I'm _______, since these are the two things I've _______ the most about. I'm excited for the day when someone combines them and uses A.I. to better select who did more fairly, maybe even select who to fund and how to advise them and really kind of make entrepreneurship super widely available that will lead to like better outcomes and sort of more societal ______ for all of us. So are. So, yeah, I think. Broadening the set of people able to start companies and that sort of get the resources that you need, that is like an unequivocally good thing and it's something that I think Silicon ______ is making some progress in. But I hope we see a lot more. And I do really, truly think that the technology industry entrepreneurship is one of the ________ forces for self __________. If we can just ______ out how to be a little bit more _________ in how we do things. My last question _____ is about ideas were spreading. If you could ______ one idea into the mind of everyone listening, what what would the idea be? We've touched on it a bunch, but the one idea would be the ajai really is going to ______. You have to engage with it seriously, and you shouldn't just ______ to this and then brush aside and go about life as if it's not going to happen because it is going to affect everything. And we will all we all, I think, have an obligation, but also an opportunity to figure out what not means and how we want the world and this sort of one time shift to go on. I'm kind of awed by the breadth of things are engaged with. Thank you so much for ________ so much time sharing your vision. Thanks so much for having me. OK, that's it for today. You can read more about open eyes, vision and progress at open eye dotcom. If you want to try playing with yourself, it's a little ______. You have to find a website that has ________ the API. The one I went to was philosopher ehi dot com, where you just you pay a few dollars to get access to a very _______ mind. That's actually quite a lot of fun. The interview is part of the TED Audio Collective, a collection of podcasts dedicated to sparking curiosity and sharing ideas that matter. This show is ________ by Kim Net2Phone Pittas and ______ by Grace Rubenstein and ______ Boffano, ______ _______ Sir. Fact _____ is by Paul Durbin and special thanks to Michele Quent, Colin Helmes and Anna Felin. If you like the show, please write and review it. It helps other people find us. We read every ______, so thanks so much for listening. See you next time.

Solution

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Original Text

Hello there, this is Chris Anderson, and I am hugely, hugely, tremendously excited to welcome you to a new series of the TED interview. Now, then, this season, we're trying something new. We're organising the whole season around a single theme, albeit a theme that some of you may consider inappropriate. But hear me out. The theme is the case for optimism. And yes, I know the world has been hit with extraordinarily ugly things in the last few years. Political division, a racial reckoning, technology run amuck, not to mention a global pandemic and impending climate catastrophe. What on earth are we thinking in this context? Optimism just seems so naive and unwanted, almost annoying. So here's my position. Don't think of optimism as a feeling. It's not just this sort of shallow feeling of hope. Optimism is a search. It's a determination to look for a pathway forward somewhere out there. I believe I truly believe there are amazing people whose minds contain the ideas, the visions, the solutions that can actually create that pathway forward. If given the support and resources they need, they may very well light the path out of this dark place we're in. So these are the people who can present not optimism, but a case for optimism. They're the people I'm talking to this season. So let's see if they can persuade us now. Then the place I want to start is with A.I. artificial intelligence. This, of course, is the next innovative technology that is going to change everything as we know it, for better or for worse. Today was painted not with the usual dystopian brush, but by someone who truly believes in its potential. Sam Altman is the former president of Y Combinator, the legendary startup accelerator. And in 2015, he and a team launched a company called Open Eye, dedicated to one noble purpose to develop A.I. so that it benefits humanity as a whole. You may have heard, by the way, recently a lot of buzz around in A.I. technology called T3 that was developed by open eye improve the quality of the amazing team of researchers and developers they have work in. There will be hearing a lot about three in the conversation ahead. But sticking to this lofty mission of developing A.I. for humanity and finding the resources to realize it haven't been simple. Open A.I. is certainly not without its critics, but their goal couldn't be more important. And honestly, I found it really quite exciting to hear Sam's vision for where all this could lead. OK, let's do this. So, Sam Altman, welcome. Thank you for having me. So, Sam, here we are in 2021. A lot of people are fearful of the future at this moment in world history. How would you describe your attitude to the future? I think that the combination of scientific and technological progress and better societal decision making, better societal governance is going to solve in the next couple of decades all of our current most pressing problems, there will be new ones. But I think we are going to get very safe, very inexpensive, carbon free nuclear energy to work. And I think we're going to talk about that time that the climate disaster looks so bad and how lucky we are. We got saved by science and technology, I think. And we've already now seen this with the rapidity that we were able to get vaccines deployed. We are going to find that we are able to cure or at least treat a significant percentage of human disease, including I think we'll just actually make progress in helping people have much longer decades, longer health spans. And I think in the next couple of decades, that will look pretty clear. I think we will build systems with AI and otherwise that make access to an incredibly high quality education more possible than ever before. I think the lives we look forward like one hundred years, fifty years, even the quality of life available to anyone then will be much better than the quality of life available in the very best case to anyone today, to any single person today. So, yeah, I'm super optimistic. I think, like, it's always easy to do scroll and think about how bad are the bad things are, but the good things are really good and getting much better. Is it your sincere belief that artificial intelligence can actually make that future better? Certainly. How look, with any technology. I don't think it will all be better. I think there are always positive and negative use cases of anything new, and it's our job to maximize the positive ones, minimize the negative ones. But I truly, genuinely believe that the positive impacts will be orders of magnitude bigger than the negative ones. I think we're seeing a glimpse of that now. Now that we have the first general purpose built out in the world and available via things like RPI, I think we are seeing evidence of just the breadth of services that we will be able to offer as the sort of technological revolution really takes hold. And we will have people interact with services that are smart, really smart, and it will feel like as strange as the world before mobile phones feels now to us. Hmm, yeah, you mentioned your API, I guess that stands for what, application programming interface? It's the technology that allows complex technology to be accessible to others. So give me a sense of a couple of things that have got you most excited that are already out there and then how that gives you visibility to a pathway forward that is even more exciting. So I think that the things that we're seeing now are very much glimpse of the future. We released three, which is a general-purpose natural language text model in the summer of twenty twenty. You know, there's hundreds of applications that are now using it in production that's ramping up all of the time. But there are things where people use three to really understand the intent behind the search query and deliver results and sort of understand not only intent, but all of the data and deliver the thing of what you want. So you can sort of describe a fuzzy thing and it'll understand documents. It can understand, you know, short documents, not full books yet, but bring you back to the context of what you want. There's been a lot of excitement about using the generative capabilities to create sort of games or sort of interactive stories or letting people develop characters or chat with a sort of virtual friend. There are applications that, for example, help a job seeker polish a tailored application for each individual company. There's the beginning of tutors that can sort of teach people about different concepts and take on different personas. And we can go on for a long time. But I think anything that you can imagine that you do today via computer that you would like to really understand and get to know you. And not only that, but understand all of the data and knowledge in the world and help you have the best experience that is is possible that that will happen. So what gets opened up? What new adjacent possible state is that as a result of these powers from this question, from the point of view of someone who's starting out on a career, for example, they're trying to figure out what would be a really interesting thing to do in the future that has only recently become possible. What are some new things that this opens up in a world where you can talk to a computer? And get. The output that would normally require you hiring the world experts back immediately for almost no money, I would say think about what's possible there. So that could be like, as you said, what can normally only the best programmer in the world or a really great programmer do for me. And can I now instead just ask in English and have that program written? So all these people that, you know, want to develop an app and they have an idea, but they don't know how to program. Now they can have it. You know, what is the service look like when anyone on Earth who wants really great medical advice? Can get better medical advice than any single doctor could ever get, because this has the total medical knowledge and reasoning ability that the some humanity has ever produced. When you want to learn something, you have sort of a tutor that understands your exact style, how you best learn everything you know, and custom teaches you whatever concept you want to learn someday. You can imagine that like. You have an eye that reads your email and your task list and your calendar and the documents you've been sent and in any meeting maximally perfectly prepares you and has all of the information that you need in all the context of your entire career right there for you to go on for a long time. But I think this will just be powerful systems. So it's really fun playing around with Chapatti three, one compelling example of someone who's more tax base is try Googling The Guardian essay that was written entirely by different GP2 three queries and stitched together. It's an essay on why artificial intelligence isn't a threat to humanity. And that's impressive. It's very compelling. I actually tried inputting one of the three online uses. I asked the question what is interesting about some ollman? Oh no. Here's what it came back with. It was it was rather philosophical, actually. Came back with. I don't understand what you mean by interesting. It seems to me that this word has no unambiguous meaning in the context of human society beyond its literal definition as somewhat pleasing or entertaining. I do not believe there to be any such thing as INTERESTINGNESS except in the mind of a human or other sentient being that to my knowledge, this is an entirely subjective state that varies from person to person. However, I will grant that this is an interesting question to ask. This does not mean it has been answered. There is no answer to be found. Well, so you can agree that somewhere between profound and gibberish is that almost well, with the state of play is I mean, that's where we are today. I think somewhere between profound and jibberish is the right way to think about the current capabilities of CGP three. I think they would definitely had a bubble of hype about three last summer. But the thing about bubbles is the reason that smart people fall for them is there's a kernel of something really real and really interesting that people get overexcited about. And I think people definitely got and still are overexcited about 3:00 today, but still probably underestimated the potential of where these models will go in the future. And so maybe there's this like short term overhyped and long term under hype for the entire field, for tax models, for whatever you'd like. It's going on. And as you said, there's clearly some gibberish in there. But on the other hand, those were like well-formed sentences. And there were a couple of ideas and there that I was like, oh, like they actually maybe that's right. And I think if artificial intelligence, even in its current very larval state, can make us confront new things and sort of inspire new ideas, that's already pretty impressive. Give us a sense of what's actually happening in the background there. I think it's hard to understand because you read these words seem like someone is trying to mean something. Obviously, I think you believe that there's whatever you've built there, that there's a sort of thinking, sentient thing that's going, oh, I must answer this question. So so what how would you describe what's going on? You've got something that has read the entire Internet, essentially all of Wikipedia, etc. We've read something that's read like a small fraction of a random sampling of the Internet. We will eventually train something that has read as much of the Internet or more of the Internet than we've done right now. But we have a very long way to go. I mean, we're still, I think, relative to what we will have operated at quite small scale with quite small eyes. But what is happening is there is a model that is ingesting lots of text and it is trying to predict the next word. So we use Transformer's they take in a context, which is a particular architecture of an A.I. model, they take in a context of a lot of words, let's say like a thousand or something like that. And they try to predict the word that comes next in the sequence. And there's like a lot of other things that happen, but fundamentally that's it, and I think this is interesting because in the process of playing that little game of trying to predict the next word, these models have to develop a representation and understanding of what is likely to come next and. I think it is maybe not perfectly accurate, but certainly worth considering to say that intelligence is very near the ability to make accurate predictions. What's confusing about this is that there are so many words on the Internet which are foolish as well as the words that are wise. And and how do you build a model that can distinguish between those two? And this is prompted actually by another example that I typed in. Like I asked, you know, what is a powerful idea, very interested in ideas. That was my question as a powerful idea. And it came back with several things, some of which seemed moderately pronouncements, which seemed moderately gibberish. But then he was he was one that it came back with the idea that the human race has, quote, evolved, unquote, is false evolution or adaptation within a species was abandoned by biology and genetics long ago. Wait a sec. That's news to me. What have you been reading? And I presume this has been pulled out of some recesses of the Internet, but how is it possible, even in theory, to imagine how a model can gravitate towards truth, wisdom, as opposed to just like majority views? Or how how how do you avoid something taking us further into the sort of the maze of errors and bad thinking and so forth that has already been a worrying feature for the last few years ? It's a fantastic question, and I think it is the most interesting area of research that we need to pursue. Now, I think at this point, the questions of whether we can build really powerful general-purpose AI system, I won't say there in the rearview mirror. We still have a lot of hard engineering work to do, but I'm pretty confident we're going to be able to. And now the questions are like, what should we build? And how and why and what data should we train on and how do we build systems not just that can do these like phenomenally impressive things, but that we can ensure do the things that we want and that understand the concepts of truth and falsehood and, you know, alignment with human values and misalignment with human values. One of the pieces of research that we put out last year that I was most proud of and most excited about is what we call reinforcement learning from human feedback. And we showed that we can take these giant models that are trained on a bunch of stuff, some of it good, some of the bad, and then with a really quite small amount of feedback from human judgment about, hey, this is good, this is bad, this is wrong, this is the behavior I want I don't want this behavior. We can feed that information from the human judges back into the model and we can teach the model, behave more like this and less like that. And it works better than I ever imagined it would. And that gives me a lot of hope that we can build an aligned system. We'll do other things, too, like I think curating data sets where there's just less sort of bad data to train on. It will go a very long way. And as these models get smarter, I think they inherently develop the ability to sort out bad data from good data. And as they get really smart, they'll even start to do something we call active learning, which is where they ask us for exactly the data they need when they're missing something, when they're unsure, when they don't understand. But I think as a result of simply scaling these models up, building better, I hate to use the word cognition because it sounds so anthropomorphic, but let's say building a better ability to reason into the models, to think, to challenge, to try to understand and combining that with this idea of online into human values via this technique we developed, that's going to go a very long way. Now, there's another question, which you sort of just kicked the ball down the field, too, which is how do we as a society decide to which set of human values do we align these powerful systems? Yeah, indeed. So if I if I understand rightly what you're saying, that you're saying that it's possible to look at the output at any one time of three. And if we don't like what it's coming up with, some ways human can say, no, that was off, don't do that. Whatever algorithm or process led you to that, undo it. Yeah. And that the system is that incredibly powerful at avoiding that same kind of mistake in future because it sort of replicates the instructions , correct? Yeah. And eventually and not much longer, I believe that we'll be able to not only say that was good, that was bad, but say that was bad for this reason. And also tell me how you got to that answer so I can make sure I understand. But at the end of the day, someone needs to decide who is the wise human or short humans who are looking at the results. So it's a big difference. Someone who who grew up with intelligent design world view could look at that and go, that's a brilliant outcome. Well, Goldstar done. And someone else would say something is done awfully wrong here. So how do you avoid and this is a version of the problem that a lot of the, I guess, Silicon Valley companies are facing right now in terms of the pushback they're getting on the output of social media and so forth. How do you assemble that pool of experts who stand for human values that we actually want? I mean, we talk about this all the time, I don't think this is like solely or even not even close to majorly up to opening night to decide, I think we need to begin a societal conversation now about how we're going to make those decisions, how we're going to make sure we have representational input in that, and how we sort of make these very difficult global governance systems. My personal belief is that we should have pretty broad rules about what these systems will never do and will always do. But then the individual user should get a system that kind of behaves like they want. And there will be people do have very different value systems. Some of them are just fundamentally incompatible. No one gets to use eye to, like, exploit other people, for example, and hopefully we can all agree on. But do you want the AI to like. You know, support you and your belief of intelligent design, like, do I think openly, I should say it can't, even though I disagree with that is like a scientific conclusion. No, I wouldn't take that stance. I think the thing to remember about all of this is that history is still quite extraordinarily weak. It's still has such big problems and it's still so unreliable that for most use cases it's still unsuitable. But when we think about a system that is like a thousand times more powerful and let's say a million times more reliable, it just doesn't it doesn't say gibberish very often. It doesn't totally lose the plot and get distracted or system like that is going to be one that a lot of the economic activity in the world comes to rely on. And I think it's very important that we don't have a small group of people sort of saying you can never use it for this thing that, like most of the world wants to use it for because it doesn't match our personal beliefs. Talk a bit more about some of the other uses of it, because one of the things that's most surprising is it's not just about sort of text responses. It's it can take generalized human instructions and build things up. For example, you can say to it, write a Python program that is designed to put a flashing cursor in one corner of the screen, in the Google logo in the other corner. And and it can go your way and do something like that. Shockingly, quite well, effectively. Yeah, I it can. That's amazing. I mean, this is amazing to me. That opens the door to. An entirely way to think about programers for the future, that you could you could have people who can program just in human natural language potentially and gain rapid efficiency. I do the engineering. We're not that far away from that world. We're not that far away from the world where you will write a spec in English. And for a simple enough program, I will just write the code for you. As you said, you can see glimpses of that even in this very week three which was not trained to code like. I think this is important to remember. We trained it on the language on the Internet very rarely, you know, Internet let language on the Internet also includes some code snippets. And that was enough, so if we really try to go train a model on code itself and that's where we decide to put the horsepower of the model into, just imagine what will be possible will be quite impressive. But I think what you're pointing to there is that because models like three to some degree or other, and it's like very hard to know exactly how much understand the underlying concepts of what's going on. And they're not just regurgitating things they found in a website, but they can really apply them and say, oh, yeah, I kind of like know about this word and this idea and code. And this is probably what you're trying to do. And I won't get it right always. But sometimes I will just generate this like a brand new program for nothing that anyone has ever asked before. And it will work. That's pretty cool. And data is data. So it can do that from English to code. It can do that from English to French. Again, we never told it to learn about translation. We never told it about the concepts of English and French, but it learned them, even though we never said this is what English is and this is what French is and this is what it means to translate, it can still do it. Wow, I mean, for creative people, is there a world coming where the sort of the palette of possibility that they can be exposed to is just explodes? I mean, if you're a musician, is there a near future where you can say to your eye, OK, I'm going to bed now, but in the morning I'd love you to present me with a thousand tuba jingles with words attached that you have of a sort of mean factor to the and you come down in the morning and the computer shows you the stuff. And one of them, you go, wow, that is it. That is a top 10 hit and you build a song from it. Or is that going to be released? Actually be the value add. We released something last year called Jukebox, which is very near what you described, where you can say I want music generated for me in this style or this kind of stuff, and it can come up with the words as well. And it's like pretty cool. And I really enjoy listening to music that it creates. And I can sort of do four songs, two bars of a jingle, whatever you'd like. And one of my very favorite artists reached out, called to open it after we release this and said that he wanted to talk. And I was like, well, I like total fanboy here. I'd love to join that call. And I was so nervous that he was going to say, this is terrible. This is like a really sad thing for human creativity. Like, you know, why are you doing this? This is like whatever. And he was so excited. And he's like, this has been so inspiring. I want to do a new album with this. You know, it's like, give me all these new ideas. It's making me much better at my job. I'm going to make better music because of this tool. And that was awesome. And I hope that's how it all continues to go. And I think it is going to lead to this. We see a similar thing now with Dolly, where graphic designers sometimes tell us that they just they see this new set of possibilities because there's new creative inspiration and they're cycle time, like the amount of time it takes to just come up with an idea and be able to look at it and then decide whether to go down that path or head in a different direction goes down so much. And so I think it's going to just be this like incredible creative explosion for humans. And how far away are we some before? And I it comes up with a genuinely powerful new idea, an idea that solves the problem that humans have been wrestling with. It doesn't have to be as quite on the scale as of, OK, we've got a virus coming. Please describe to us what a what a national rational response should look like, but some kind of genuinely innovative idea or solution like one one internal question we've asked ourselves is, when will the first genuinely interesting, purely AI written TED talk show up? I think that's a great milestone. I will say it's always hard to guess timeline's I'm sure I'll be wrong on this, but I would guess the first genuinely interesting. Ted talk, thought of written delivered by an AIDS within the kind of the seven ish year time frame. Maybe a little bit less. And it feels like I mean, just reading that Guardian essay that was kind of it was a composite of several different GPG three responses to questions about, you know, the threats of robotics or whatever. If you throw in a human editor into the mix, you could probably imagine something much sooner. Indeed. Like tomorrow. Yeah. So the hybrid the hybrid version where it's basically a tool assisted TED talk, but that it is better than any TED talk a human could generate in one hundred hours or whatever, if you can sort of combine human discretion with A.I. horsepower. I suspect that's like our next year or two years from now kind of thing where it's just really quite good. That's that's really interesting. How do you view the impact of A.I. on jobs? There's obviously been the familiar story is that every White-Collar job is now up for destruction. What's what's your view there? You know, it's I think it's always hard to make these predictions. That is definitely the familiar story now. Five years ago, it was every blue collar job is up for destruction, maybe like last year it was. Every creative job is up for destruction because of things like Jukebox I. I think there will be an enormous impact on. The job market, and I really hate it, I think it's kind of gross when people like working on I pretend like there's not going to be or sort of say, oh, don't worry about it. It'll just all obviously better. It doesn't always obviously get better. I think what is true is. Every technological revolution produces a change in jobs, we always find new ones, at least so far. It's difficult to predict from where we're sitting now what the new ones will be and this technological revolution is likely to be. Again, it's always tempting to say this time it's different. Maybe I'll be totally wrong. But from what I see now, this technological revolution is likely to be more. Dramatic. More of a staccato note than most, and I think we as a society need to figure out how we're going to cushion everybody through that. I've got my own ideas about how to do that. I, I wouldn't say that I have any reason to believe they're the right ones, but doing nothing and not really engaging with the magnitude of what's about to happen, I think it's like not an acceptable answer. So there's going to be huge impact. It's difficult to predict where it shows up the most. I think previous predictions have mostly been wrong, but I I'd like to see us all as a society, certainly as a field, engage in what what the shifts we want to make to the social contract are to kind of get through that in a way that is maximally beneficial to everybody. I mean, in every past revolution, there's always been a space for humans to move to. That is, if you like, moving up the food chain, it's sort of we've retreated to the things that humans could uniquely do, think better, be more creative and so forth. I guess the worry about A.I. is that in principle, I believe this, that there is no human cognitive feat that won't ultimately be doable, probably better by artificial general touch, simply because of the extra firepower that ultimately they can have, the vast knowledge they bring to the table and so forth. Is that basically right, that there is ultimately no safe sort of space where we can say, oh, but that would never be able to do that on a very long time horizon? I agree with you, but that's such a long time horizon. I think that, you know, like maybe we've merged by that point, like maybe we're all plugged in and then, like, we're this sort of symbiotic thing. Like, I think there's an interesting example, as we were talking about a few minutes ago, where right now we have these systems that have sort of enormous horsepower but no steering wheel. It's like, you know , incredible capabilities, but no judgment. And there's like these obvious ways in which today even a human plus three is far better than either on their own. Many people speak about a world where it's sort of A.I. as this external threat you speak about. At some point, we actually merge with eyes in some way. What do you mean by that? There's a lot of different versions of what I think is possible there, you know, in some sense, I'd argue the merge has already like begun the human technology merge like we have this thing in our hands that sort of dictates a lot of what we think, but it gives us real superpowers and that can go much, much further. Maybe it goes all the way to like the Elon Musk vision of neuro link and having our brains plugged into computers and sort of like literally we have a computer on the back of our head or goes the other direction and we get uploaded into one. Or maybe it's just that we all have a chat bot that kind of constantly steers us and helps us make better decisions than we could. But in any case, I think the fundamental thing is it's not like the humans versus the eyes competing to be the. Smartest sentient thing on earth or beyond. But it's that this idea of being on the same team. Hmm. I certainly get very excited by the sort of the medium term potential for creative people of all sorts if they're willing to expand their palette of possibilities. But with the use of A.I. to be willing to. I mean, the one thing that the history of technology has shown again and again is that something this powerful and with this much benefit is unstoppable and you will get rewarded for embracing it the most and the earliest. So talk about what can go wrong with that, so let's move away from just the sort of economic displacement factor. You were a co-founder of Open Eye because you saw existential risks to humanity from high today. What would you put as the sort of the most worrying of those risks? And how is open eye working to minimize? I still think all of the really horrifying risks exist. I am more confident, much more confident than I was five years ago when we started that there are technical things we can do about. How we build these systems and the research and the alignment that make us much more likely to end up in the kind of really wonderful camp, but, you know, like maybe open I fall behind and maybe somebody else feels ajai that thinks about it in a very different way or doesn't care as much as we'd like about safety and the risks or how to strike a different trade off of how fast we should go with this and where we should sort of just say, like, you know, like let's push on for the economic benefits. But I think all of this sort of like, you know, traditionally what's been in the realm of sci fi risks are real and we should not ignore them. And I still lose sleep over them. And just to update people is artificial general intelligence. Right now, we have incredible examples of powerful AI operating on specific areas. Ajai is the ability of a computer mind to connect the dots and to make decisions at the same level of breadth that that humans have had. What's your sort of elevator pitch on Ajai about how to identify and how to think of it? Yeah, I mean, the way that I would say it is that for a while we were in this world of like very narrow A.I. , you know, that could like classify images of cats or whatever, more advanced stuff in that. But that kind of thing. We are now in the era of general purpose, AI, where you have these systems that are still very much imperfect tools, but that can generalize. And one thing like GPP three can write essays and translate between languages and write computer code and do very complicated search. It's like a single model that understands enough of what's really going on to do a broad array of tasks and learn new things quickly, sort of like people can. And then eventually we'll get to this other realm. Some people call it ajai, some people call ostler things. But I think it implies that the systems are like to some degree self directed, have some intentionality of their own is a simple summary to say that, like the fundamental risk is that there's the potential with general artificial intelligence of a sort of runaway effect of self-improvement that can happen far faster than any kind of humans can even keep up with, so that the day after you get to ajai, suddenly computers are thousands of times more advanced than us and we have no way of controlling what they do with that power. Yeah, and that is certainly in the risk space, which is that we build this thing and at some point somewhat suddenly, it's much more powerful than we are, we haven't really done the full merge yet. There's an event horizon there and it's sort of hard to see to the other side of it. Again, lots of reasons to think it will go OK. Lots of reasons to think we won't even get to that scenario. But that is something that. I don't think people should brush under the rug as much as they do, it's in the possibility space for sure, and in the possibility subspace of that is one where, like, we didn't actually do as good of a job on the alignment work as we thought. And this sort of child of humanity kind of acts in a very different way than we think. A framework that I find useful is to sort of think about like a two by two matrix, which is short timelines to ajai and long timelines to ajai and a slow take off and a fast take off on the other axis. And in the short timelines, fast take off quadrant, which is not where I think we're going to be. But if we get there, I think there's a lot of scenarios in the direction that you are describing that are worrisome. And we would want to spend a lot of effort planning for. I mean, the fact that a computer could start editing its own code and improving itself while we're asleep and you wake up in the morning and it's got smarter, that is the start of something super powerful and potentially scary. I have tremendous misgivings about letting my system, not one we have today, but one that we might not have and too many more years start editing its own code while we're not paying attention. I think that's the kind of thing that is worth a great deal of societal discussion about, you know, just because we can do that. Should we? Yes, because one of the things that's that's been most shocking to you about the last few years has been just the power of unintended consequences. It's like you don't have to have a belief that there's some sort of waking up of of an alien intelligence that suddenly decided it wants to wreak havoc on humans. That may never happen. What you can have is just incredible power that goes amok. So a lot of people would argue that what's happened in technology in the last few years is actually an example of that. You know, social media companies created these intelligences that were programmed to maximally harvest attention, for example, for sure. And they understand this from that turned out to be in some ways horrifying and extraordinarily damaging. Is that a meaningful sort of canary in the coal mine saying, look out, humanity, this could be really dangerous? And how how on earth do you protect against those kinds of unintended consequences? I think you raise a great point in general, which is these systems don't have to wish ill to humanity to cause ill just when you have, like, very powerful systems. I mean, unintended consequences for sure. But another version of that is and I think this applies at the technical level, at the company level, at the societal level, incentives are superpower's. Charlie Munger had this thing on, which is incentives are so powerful that if you can spend any time whatsoever working on the incentive system, that's what you should do before you work on anything else. And I really believe that. And I think that applies to the individual models we build and what their reward functions look like. I think it applies to society in a big way, and I think it applies to our corporate structure at open. I you know, we sort of observe that if you have very well-meaning people, but they have this incentive to sort of maximize attention harvesting and profit forever through no one's ill intentions, that leads to a quite undesirable outcome. And so we set up opening is this thing called a capped profit model specifically so that we don't have the system incentive to just generate maximum value forever with an AGI that seems like obviously quite broken. But even though we knew that was bad and even though we all like to think of ourselves as good people, it took us a long time to figure out the right structure, to figure out a charter that's going to govern us and a set of incentives that we believe will let us do our work. And kind of these we have these like three elements that we talk about a lot research sort of engineering, development and deployment policy and safety. Put those all together under a system where you don't have to rely on. Anything but the natural incentives to push in a direction that we hope will minimize the sort of negative unintended consequences. So help me understand this, because this is I think this is confusing to some people. So you started opening. I initially I think Elon Musk, the co-founder, and there was a group of you and the argument was this technology is too powerful to be left, developed in secret and to be left developed purely by corporations who have whatever incentive they may have. We need a nonprofit that will develop and share knowledge openly. First of all, just even at that early stage, some people were confused about this. It was saying if this thing is so dangerous, why on earth would you want to make it secrets even more available? Well, maybe giving the tools to that sort of AI terrorist in his bedroom somewhere, I think I think we got misunderstood in the way we were talking about that. We certainly don't think that the right thing to do is to, like, build this a super weapon and hand it to a terrorist. That's obviously awful. One of the reasons that we like our API model is it lets us make the most powerful AI technology anyone in the world has, as far as we know, available to ever would like to use it, but to put some controls on its usage. And also, if we make a mistake, to be able to pull it back or change it or tweak it or improve it or whatever. But we do want to put and this is continued will continue to be true with appropriate restrictions and guardrails, very powerful technology in the hands of people. I think that is fair. I think that will lead to the best results for the society as a whole. And I think it will sort of maximize benefit. But that's very different than sort of shipping the whole model and saying, here, do whatever you want with it. We're able to enforce rules on it. We also think and this is part of the mission that like something the field was doing a lot of that we didn't feel good about was sort of saying like, oh, we're going to keep the pace of progress and capabilities secret. That doesn't feel right, because I think we do need a societal conversation about what's what's going on here, what the impacts are going to be. And so we although we don't always say, like, you know, here's the super weapon, hopefully we do try to say, like, this is really serious. This is a big deal. This is going to affect all of us. We need to have a big conversation about what to do with it. Help me understand the structure a bit better, because you definitely surprised much people when you announced that Microsoft were putting a billion dollars into the organization and in return, I guess they get certain exclusive licensing rights. And so, for example, they are the exclusive licensee of CP3. So talk about that structure of how you win. Microsoft presumably have invested not purely for altruistic purposes. They think that they will make money on that billion dollars. I sure hope they do. I love capitalism, but I think that I really loved even more about Microsoft as a partner. And I'll talk about the structure and the exclusive license in a minute is that we like went around to people that might find us. And we said one of the things here is that we're going to try to make you some money. But like Adjei going well is more important. And we need you to sign this document that says if things don't go the way we think and we can't make you money like you just cheerfully walk away from it and we do the right thing for humanity. And they were like, yes, we are enthusiastic about that. We get that the mission comes first here. So again, I hope a phenomenal investment for them. But they were like they really pleasantly surprised us on the upside of how aligned they were with us, about how strange the world may get here and the need for us to have flexibility and put our mission first, even if that means they lose all their money, which I hope they don't and don't think they will. So the way it's set up is that if at some point in the coming year or two, two years, Microsoft decide that there's some incredible commercial opportunity that they could realize out of the eye that you've built and you feel actually, no, that's that's damaging. You can block it. You can veto it. Correct. So the four most powerful version of three and its successors are available via the API, and we intend for that to continue. What Microsoft has is the ability to sort of put that model directly into their own technology. If they want to do that. We don't plan to do that with other people because we can't have all these controls that we talked about earlier. But they're like a close trusted partner and they really care about safety, too. But our goal is that anybody who wants to use the API can have the most powerful versions of what we've trained. And the structure of the API lets us continue to increase the safety and fix problems when we find them. But but the structure. So we start out as a non-profit, as you said, we realized pretty quickly that although we went into this thinking that the way to get to ajai would be about smarter and smarter algorithms, that we just needed bigger and bigger computers as well. And that was going to require a scale of capital that no one will, at least certainly not me, could figure out how to raise is a nonprofit. We also needed to sort of be able to compensate very highly compensated, talented individuals that do this, but are full for profit company had runaway incentives problem, among other things. Also just one about sort of fairness in society and wealth concentration that didn't feel right to us either. And so we came up with this kind of hybrid where we have a nonprofit that governs what we do, and it has a subsidiary, LLC, that we structure in a way to make a fixed amount of profit so that all of our investors and employees, hopefully if things go how we like, if not no one gets any money, but hopefully they get to make this one time great return on their investment or the time that they spent it open their equity here. And then beyond that, all the value flows back to the nonprofit and we figure out how to share it as fairly as we can with the world. And I think that this structure and this nonprofit with this very strong charter in place and everybody who joins signing up for the mission come in first and the fact the world may get strange, I think that. That was at least the best idea we could come up with, and I think it feels so far like the incentive system is working, just as I sort of watch the way that we and our partners make decisions. But if I read it right, the cap on the gain that investors can make is 100 Axum. It's a massive call that was for our very first round investors. It's way, way lower. Like as we now take a bit of capital, it's way, way lower. So your deal with Microsoft isn't you can only make the first hundred billion dollars. I don't know. It's way lower than after that. We're giving it to the world. It's way lower than that. Have you disclosed what I don't know if we have, so I won't accidentally do it now. All right. OK, so explain a bit more about the charter and how it is that you. Hope to avoid or I guess help contribute to an eye that is safe for humanity. What do you see as the keys to us avoiding the worst mistakes and really holding on to something that's that's beneficial for humanity? My answer there is actually more about, like technical and societal issues than the charter. So if it's OK for me to answer it from that perspective, sure. OK, I'm happy to talk about the charter to. I think this question of alignment that we talked about a little earlier is paramount, and then I think to understand that it's useful to differentiate between accidental misuse of a system and intentional misuse of a system. So like intentional would be a bad actor saying, I've got this powerful system, I'm going to use it to like hack into all the computers in the world and wreak havoc on the power grids. And accidental would be kind of the Nick Bostrom make a lot of paper clips and view humans as collateral damage in both cases. But to varying degrees, if we can really, truly, technically solve the alignment problem and the societal problem of deciding to which set of human values do we align, then the systems understand right and wrong, and they understand probably better than we ever can, unintended consequences from complex actions and very complex systems. And, you know, if we can train a system which is like. Don't harm humanity and the system can really understand what we mean when we say that, again, who is we and what does that have some asterisks on them? Sorry, go ahead. Well, that's if they could understand what it means to not harm humanity, that there's a lot wrapped up in that sentence. Because what's been so striking to me about efforts so far is that they seem to have been based on a very naive view of human nature. Go back to the sort of Facebook and Twitter examples of, well, the engineers building some of the systems would say we've just designed them around what humans want to do. You said, well, if someone wants to click on something, we will give them more of that thing. And what could possibly be wrong with that? We're just supporting human choice, ignoring the fact that humans are complicated, farshid animals for sure, who are constantly making choices, that a more effective version of themselves would agree is not in their long term interests. So that's one part of it. And then you've got layered on top of that or the complications of systemic complexity where, you know, multiple choices by thousands of people end up creating a reality that possibly have designed for how how to cut through that. Like an AI has to make a decision based on a moment, on a specific data set. As those decisions get more powerful, how can we be confident that they don't lead to this sort of system crashing basically in some way? I think that I've heard a lot of behavioral psychologists and other people that have studied this say in different ways, are that I hate to keep picking on Facebook, but we can do it one more time since we're on the topic. Maybe you can't in any given moment in night where you're tired and you have a stressful day, stop yourself from the dopamine hit of scrolling and Instagram, even though you know that's bad for you and it's not leading to your best life. But if you were asked in a reflective moment where you were sort of fully alert and thoughtful, do you want to spend as much time as you do scrolling through Instagram? Does it make you happier or not? You would actually be able to give like the right long term answer? It's sort of the spirit is willing, but the flesh is weak kind of moment. And one thing that I am hopeful is that humans do know what we want and what. On the whole, and presented with research or sort of an objective view about what makes us happy and doesn't we're pretty, what's so great about it, they're pretty good. But in any particular moment, we are subjected to our animal instincts and it is easy for the lower brain to take over the eye. Well , I think be an even higher brain. And as we can teach it, you know, here is what we really do value. Here's what we really do want. It will help us make better decisions than we are capable of, even in our best moments. So is that being proposed and talked about as an actual rule? Because it strikes me that there is something potentially super profound here to introduce some kind of rule for development of AIDS that they have to tap into not. What humans one, which is an ill defined question, but as to what humans in reflective mode want. Yeah, we talk about this a lot. I mean, do you see a real chance where something like that could be incorporated as a sort of an absolute golden rule and and if you like, spread around the community so that it seeps into corporations and elsewhere? Because that I've seen no evidence that, well, a little corporation that was potentially a game changer. Corporations have this weird incentive problem. Right. What I was trying to speak about was something that I think should be technologically possible , and that's something that we as a society should demand. And I think it is technically possible for this to be sort of like a layer above the neocortex that makes even better decisions for us and our welfare and our long term happiness and fulfillment than we could make on our own. And I think it is possible for us as a society to demand that. And if we can do like a pincer move between what the technology is capable of and what we what we as society demand, maybe we can make everybody in the middle that way. I mean, there are instances of even though companies have their incentives to make money and so forth, they also in the knowledge age. Can't make money if they have pissed off too many of their employees and customers and investors by analogy of the climate space right now, you can see more and more companies, even those that are emitting huge amounts of carbon dioxide, saying, wait a sec, we're struggling to recruit talented people because they don't want to work for someone who's evil. And their customers are saying, we don't want to buy something that is evil. And so, you know, ultimately you can picture processes where they do better. And I I believe that most engineers, for example, work in Silicon Valley. Companies are actually good people who want to design great products for humanity. I think that the people who run these companies want to be a net contribution to humanity. It's we've we've rushed really quickly and design stuff without thinking it through properly. And it's led to a mess up. So it's like, OK, don't move fast, break things, slow down and build beautiful things that are built on a real version of human nature and on a real version of system complexity and the risks associated with systemic complexity. Is that the agenda that fundamentally you think that you can push somehow? Yes, but I think the way we can push it is by getting the incentive system right. I think most people are fundamentally extremely good. Very few people wake up in the morning thinking about how can I make the world a worse place? But the incentive systems that we're in are so powerful. And even those engineers who join with the absolute best of intentions get sucked into this world where they're like trying to go up from it all for and five or whatever Facebook calls those things and you like, it's pretty exciting. You get caught up playing the game, you're rewarded for kind of doing things that move the company's key metrics. It's like fun to get promoted. It feels good to make more money and the incentive systems of the company. And that's what it rewards. An individual performance are maybe like not what we all want. And here I don't want to pick on Facebook at all because I think there's versions of this at play it like every big tech company, including in some ways I'm sure it open I but to the degree that we can better align the incentives of companies with the welfare of society and then the incentives of an individual at those companies within the now realign incentives for those companies, the more likely we are to be able to have things like ajai that. Follow an incentive system of. What we want in our most reflective best moments and are even better than what we could think of ourselves is is it still the vision for open eye that you will get to? Artificial general intelligence ahead of. The corporations, so that you can somehow put a stake in the ground and build it the right way. Is that really a realistic thing to to dream for? And if not, how do you live up to the mission and help ensure that this thing doesn't go off the rails? I think it is. Look, I certainly don't think we will be the only group to build an AGI, but I think we could be the first. And I think if you are the first, you have a lot of norms that empower. And I think you've already seen that. You know, we have released some of the most powerful systems to date. And I think the way that we have done that kind of in controlled release where we've released a bigger model than a bigger one than a bigger one, and we sort of try and talk about the potential misuse cases and we try to like talk about the importance of releasing this behind an API so that you can make changes. Other groups have followed suit in some of those directions, and I think that's good. So, yes, I don't think we can be the only I do think we can be ahead. And if we are ahead, I think we can use that leverage to hopefully push people in a better direction or maybe we're wrong and somebody else has a better direction. We're doing something about do you have a structural advantage in that your mission is to do this for everyone as opposed to for some corporate objective. And that that that allows you that. Why is it that we came out of open eye and not someone else? It's like it's surprising in some ways when you're up against so much money and so much talent in these other companies that you came up with this platform ahead of. You know, in some sense it's surprising and in some sense, like the startup wins most of the time, like I'm a huge believer in startups as the best force for innovation we have in the world today. I talked a little bit about how we combine these three. Different clans of research, engineering and sort of safety and policy that don't normally combine well and I think we have an unusual strength, there were clearly like well funded. We have super talented people. But what we really have is like intense focus and self belief that what we're doing is possible and good. And I appreciate the implied compliment. But, you know, we, like, work really hard. And if we stop doing that, I'm sure someone would run by us fast. Tell us a bit more about some of your prior life sentences. Yeah, for several years, you were running Y Combinator, which had incredible impact on some 70 companies. There are so many startup stories that began at Y Combinator. What were key drivers in your own life that took you on the path you're on? And how did that path end up at Y Combinator? No exaggeration. I think I have back to back had the two jobs that are at least the most interesting to me in all of Silicon Valley. I, I was I went to college to study computer science. I was a major computer nerd growing up. I knew like a little bit about startups, but not very much. I started working on this project the same year I started working on that. This thing called Y Combinator started and funded me and my co-founders. And we dropped out of school and did this company, which I ran for like seven years. And then after that I got acquired. I had stayed close to my comment the whole time. I thought it was just this incredible group of people and spirit and set of incentives and just badly misunderstood by most of the world, but obvious to everyone within it that it was going to create huge amounts of value and do a lot of new things. My company had acquired PJI, who is the founder of ICI, and like truly one of the most incredible humans and business people. And Paul Burrell, Paul Graham asked me if I wanted to run it. And kind of like the central learning of my career, why I individual startups has been that if you really scale them up, remarkable things can happen. And I. I did it and I was like, one of the things that would make this exciting for me personally motivating would be if I could sort of push it in the direction of doing these hard tech companies, one of which became open. I describe actually what Y Combinator is, you know, how many people come through it to give us a couple of stories of its impact. Yeah. So you basically apply as a handful of people and an idea, maybe a prototype and say, I would like to start a company and will you please fund me? And we review those applications and we I shouldn't say we anymore. I guess they fund four hundred companies a year. You get about one hundred and fifty thousand dollars while she takes about seven percent ownership and then gives you lots of advice and then networking and sort of this like fast track program for starting a startup. I haven't looked at this in a while, but at one point a significant fraction of the billion dollar plus companies in the US that got started. It all came through the Wiki program, some recently in the news ones have been like Airbnb, Jordache, Coinbase, insta card stripe. And I think it's just it has become an incredible way to help. People who understand technology get a three month course in business, but instead of like herding you with an MBA, we actually teach you the things that matter and kind of go on to do incredible, incredible work. What is it about entrepreneurs? Why do they matter? Some people just find them kind of annoying. But I think you would argue I think I would argue that they have done as much as anyone to shape the future. Why ? What is it about them? I think it is the ability to take. And idea and by force of will to make it happen in the world and in an incentive system that rewards you for making the most impact on the most people like in our system. That's how we get most of the things that that we use. That's how we got the computer that I'm using, the software I'm using to talk to you on it. Like all of this, you know, everyone in life, everything has a balance sheet. There's plenty of very annoying things about them. And there's plenty of very annoying things about the system that sort of idolizes them. But we do get something really important in return. And I think that as a force for making things that make all of our lives better happen, it's very cool. Otherwise, you know, like if you have, like, a great idea, but you don't actually do anything useful with it for people, that's still cool. It's still intellectually interesting. But like, there's got to be something about the reward function in society that is like, did you actually do something useful? Did you create value? And I think entrepreneurship and startups are a wonderful way to do that. You know, we get all these great software companies. But I also think it's like how we're going to get ajai, how we're going to get nuclear fusion, how we're going to get life extension. And like on any of those topics are a long list of other things I could point to. There's like a number of startups that I think are doing incredible work, some of which will actually deliver. It is a truly amazing thing when you put the camera back and to believe that a human being could be lying awake at night and something pops inside their mind as a patterning of the neurons in their brain that is effectively them saying, aha, I can see a way where the future could be better and and they can actually picture it. And then they wake up and then they talk to other people and they persuade them and they persuade investors and so forth. And the fact that this this system can happen and that they can then actually change the history changes in some sense. It is mind boggling that that happens that way and it happens again and again. So you've seen so many of these stories happen. What would you say? Is the is there a key thing that differentiates good entrepreneurs from others? If you could double down on one trait, what would it be? If I could pick only one, I would pick determination. I think that is the biggest predictor of success, the biggest differentiator predictor. And if you would allow a second, I would pick like communication skills or evangelism or something in that direction as well. There are all of the obvious ones that matter, like intelligence, but there's like a lot of smart people in the world. And when I look back at kind of the thousands of entrepreneurs I've worked with, all of many of whom were like quite capable, I would say that's like one and two of the surprisingly differentiated characteristics. What it's it's what I look at, the different things that you've built and you're working on. I mean, it could not be more foundational for the future. I mean, entrepreneurship. I know this is I agree that this is really what has driven the future. Do you see some people get really now they look at Silicon Valley and they look at this story and they worry about the culture. Right. That it's this is a bro culture. Do you see prospects of that changing anytime soon? And would you welcome it? Can we get better companies by really working to expand a group of people who can be entrepreneurs and who can contribute to aid, for example? For sure. And in fact, I think I'm hopeful, since these are the two things I've thought the most about. I'm excited for the day when someone combines them and uses A.I. to better select who did more fairly, maybe even select who to fund and how to advise them and really kind of make entrepreneurship super widely available that will lead to like better outcomes and sort of more societal wealth for all of us. So are. So, yeah, I think. Broadening the set of people able to start companies and that sort of get the resources that you need, that is like an unequivocally good thing and it's something that I think Silicon Valley is making some progress in. But I hope we see a lot more. And I do really, truly think that the technology industry entrepreneurship is one of the greatest forces for self betterment. If we can just figure out how to be a little bit more inclusive in how we do things. My last question today is about ideas were spreading. If you could inject one idea into the mind of everyone listening, what what would the idea be? We've touched on it a bunch, but the one idea would be the ajai really is going to happen. You have to engage with it seriously, and you shouldn't just listen to this and then brush aside and go about life as if it's not going to happen because it is going to affect everything. And we will all we all, I think, have an obligation, but also an opportunity to figure out what not means and how we want the world and this sort of one time shift to go on. I'm kind of awed by the breadth of things are engaged with. Thank you so much for spending so much time sharing your vision. Thanks so much for having me. OK, that's it for today. You can read more about open eyes, vision and progress at open eye dotcom. If you want to try playing with yourself, it's a little tricky. You have to find a website that has licensed the API. The one I went to was philosopher ehi dot com, where you just you pay a few dollars to get access to a very strange mind. That's actually quite a lot of fun. The interview is part of the TED Audio Collective, a collection of podcasts dedicated to sparking curiosity and sharing ideas that matter. This show is produced by Kim Net2Phone Pittas and edited by Grace Rubenstein and Sheila Boffano, Sambor Islamic Sir. Fact Check is by Paul Durbin and special thanks to Michele Quent, Colin Helmes and Anna Felin. If you like the show, please write and review it. It helps other people find us. We read every review, so thanks so much for listening. See you next time.

Frequently Occurring Word Combinations

ngrams of length 2

collocation	frequency
open eye	6
human values	6
long time	5
silicon valley	5
artificial intelligence	4
technological revolution	4
long term	4
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artificial general	3
billion dollars	3
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guardian essay	2
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societal conversation	2
pretty cool	2
ted talk	2
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general intelligence	2
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people call	2
start editing	2
wreak havoc	2
human nature	2
systemic complexity	2
huge amounts	2
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real version	2
incentive systems	2
started working	2

ngrams of length 3

collocation	frequency
silicon valley companies	2
artificial general intelligence	2

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