is GRE oh Jesus open AI you have had several years of experience at open AI what's your story and history there yeah so I was at open AI for uh for roughly five years uh for the last I think it was a couple years you know I I I I I I was uh vice president of research there um probably myself and ilas suger were the ones who you know really kind of set the set the research Direction around 2016 or 2017 I first started to really believe in or at least confirm my belie Bel
in the scaling hypothesis when when IL famously said to me the thing you need to understand about these models is they just want to learn the models just want to learn um and and and and again sometimes there are these One S there are these one sentences these Zen cones that you hear them and you're like ah that that explains everything that explains like a thousand things that I've seen and then and then I I you know ever after I have this visualization my head of like you optimize the models in the right way you
point the models in the right way they just want to learn they just want us the problem regardless of what the problem is so get out of their way basically get out of their way yeah don't impose your own ideas about how they should learn and you know this is the same thing as Rich Sutton put out in a bitter Lon or G put out in the scaling hypothesis you know I think generally the dynamic was you know I got I got this kind of inspiration from uh from from from Ilan from others folks like
Alec gradford who did the the original uh uh gpt1 uh and then uh ran really hard with it me me and my collaborators on gpt2 gpt3 RL from Human feedback which was an attempt to kind of deal with the early safety into durability things like debate and amplification heavy on interpretability so again the combination of safety plus scaling probably 2018 2019 2020 those those were those were kind of the years when myself and my collaborators probably um you know mo mo many many of whom became co-founders of ropic kind of really had had had a
vision and like and like drove the direction why'd you leave why' you decid to leave yeah so look I'm going to put things this way and I you know I think it I think it ties to the to to the race to the top right which is you know in my time at open AI what i' come to see as I'd come to appreciate the scaling hypothesis and as i' come to appreciate kind of the importance of safety along with the scaling hypothesis the first one I think you know open AI was was getting was
getting on board with um the second one in a way had always been part of of open ai's messaging um but uh you know over over many years of of the time the time that I spent there I think I had a particular vision of how these how we should handle these things how we should be brought out in the world the kind of principles that the organization should have and look I mean there were like many many discussions about like you know should the or do should the company do this should the company do
that like there's a bunch misinformation out there people say like we left because we didn't like the deal with Microsoft false although you know there was like a lot of discussion a lot of questions about exactly how we do the deal with Microsoft um we left because we didn't like commercialization that's not true we built gpt3 which was the model that was commercialized I was involved in commercialization it's it's more again about how do you do it like Civilization is going down this path to very powerful AI what's the way to do it that is
CAU cous straightforward honest um that builds trust in the organization and in individuals how do we get from here to there and how do we have a real vision for how to get it right how can safety not just be some we say because it helps with recruiting um and you know I think I think at the end of the day um if you have a vision for that forget about anyone else's Vision I don't want to talk about anyone else's Vision if you have a vision for how to do it you should go off
and you should do that Vision it is incredibly unproductive to try and argue with someone else's Vision you might think they're not doing it the right way you might think they're they're they're dishonest who knows maybe you're right maybe you're not um uh but uh what what you should do is you should take some people you trust and you should go off together and you should make your vision happen and if your vision is compelling if you can make it appeal to people some you know some combination of ethically you know in the market uh
you know if if you can if you can make a company that's a place people want to join uh that you know engages in practices that people think are are reasonable while managing to maintain its position in the ecosystem at the same time if you do that people will copy it um and the fact that you were doing it especially the fact that you're doing it better than they are um causes them to change their behavior in a much more compelling way than if they're your boss and you're arguing with them I just I don't
know how to be any more specific about than that but I think it's generally very unproductive to try and get someone else's Vision to look like your vision um it's much more productive to go off and do a clean experiment and say this is our vision this is how this is this is how we're going to do things your choice is you can you can ignore us you can reject what we're doing or you can you can start to become more like us and imitation is the sincerest form of flattery um and you know that
that that plays out in the behavior of customers that pays out in the behavior of the public that plays out in the behavior of where people choose to work uh and again again at the end it's it's not about one company winning or another company winning if if we or another company are engaging in some practice that you know people people find genuinely appealing and I want it to be in substance not just not just in appearance um and you know I think I think researchers are sophisticated and they look at substance uh and then
other companies start copying that practice and they win because they copied that practice that's great that's success that's like the race to the top it doesn't matter who wins in the end as long as everyone is copying everyone else's good practices right one way I think of it is like the thing we're all afraid of is the race to the bottom right in the race to the bottom doesn't matter who wins because we all lose right like you know in the most extreme world we we make this autonomous AI that you know the robots enslave
us or whatever right I mean that's half joking but you know that that is the most extreme uh uh thing thing that could happen then then it doesn't matter which company was ahead um if instead you create a race to the top where people are competing to engage in good in good practices uh then you know at the end of the day you know it doesn't matter who ends up who ends up winning doesn't even matter who who started the race to the top the point isn't to be virtuous the point is to get the
system into a better equilibrium than it was before and and individual companies can play some role in doing this individual companies can can you know can help to start it can help to accelerate it and frankly I think individuals at other companies have have done this as well right the individuals that when we put out an RSP react by pushing harder to to to get something similar done get something similar done at at at other companies sometimes other companies do something that's like we're like oh it's a good practice we think we think that's good
we should adopt it too the only difference is you know I think I think we are um we to be more forward leaning we try and adopt more of these practices first and adopt them more quickly when others when others invent them but I think this Dynamic is what we should be pointing at and that I think I think it abstracts away the question of you know which company's winning who trusts who I think all these all these questions of drama are are profoundly uninteresting and and the the thing that matters is the ecosystem that
we all operate in and how to make that ecosystem better because that constrains all the players and so anthropic is this kind of clean experiment built on a foundation of like what concretely aisat should look like we're look I'm sure we've made plenty of mistakes along the way the perfect organization doesn't exist it has to deal with the the imperfection of a thousand employees it has to deal with the imperfection of our leaders including me it has to deal with the imperfection of the people we've put we've put to you know to oversee the imperfection
of the of the leaders like the like the board and the long-term benefit trust it's it's all it's all a set of imperfect people trying to aim imperfectly at some ideal that will never perfectly be achieved um that's what you sign up for that's what it will always be but uh uh imperfect doesn't mean you just give up there's better and there's worse and hopefully hopefully we can begin to build we can do well enough that we can begin to build some practices that the whole industry engages in and then you know my guess is
that M multiple of these companies will be successful and dropic will be successful these other companies like ones I've been at the past will also be successful and some will be more successful than others that's less important then again that we we align the incentives of the industry and that happens partly through the race to the top partly through things like RSP partly through again selected surgical regulation [Music] openi
