Economies. In San Francisco, we have the spirit to take risks, to seek out whats new and different. We search for the next great idea. We dont just have the dreamers who look beyond whats possible, but we also have the builders with the talent to make the dream a reality. For decades, the San Francisco bay area has provided added the culture, the talent and the spirit to change the world. The spirit of apec, of finding Common Ground and of power, of economic collaboration , and of celebrating diverse cultures, reflects that same spirit of innovation. It is a spirit that has driven San Francisco and the bay area to become the economic engine of the world. It is the spirit that will continue to propel businesses from across the Asia Pacific Region to be part of what is happening right here, right now. We are in the spring of yet another innovative boom in San Francisco, driven by the rapid rise of Artificial Intelligence science. We have more ai job openings of any major city in the country. Of the top 20 ai companies in the world, eight are located right here in San Francisco. The conversations happen in this city and the conversation is happening here today. These these are the ideas that are going to transform our world in the decades to come. Future generations will look back on these discussions as the start of something in entirely new and its happening all right here in San Francisco. It economies, industry and Society Change rapidly. We google was started out of a garage down highway 101 freeway meadow was a website for rating classmate appeared agencies openai was virtually unheard of last year at this time. Now chatgpt has 100 million users. Google has over a billion users and meta has over 3 billion users. The entire world is using products imagined and built out right here to discuss all of this, we are going to hear about the future of ai from former secretary of state john kerry and salesforce ceo marc benioff, whose companies have been a leader in our city and in efforts to transform the world through innovation in. But first, it is my pleasure to introduce the next panel, a Group Representing the very best of how we dream in San Francisco. So people who take time to listen for new ideas, who envision what that idea can become, who creates successful and thriving businesses, but also make life better for people around the globe. Please join me in welcoming Laurie Powell jobs of the emerson collective. Chris cock of meta, James Manyika of google and sam altman of open ai. Okay i feel like you guys are a little far away. Did we bunch up . It does feel a little far. Does it feel free to gather in for our for our conversation foreign hi everyone. Good afternoon. I am very very pleased to be here at and hosting the discussion of one of the most important topics in technology and around the world. Artificial intelligence. The era of generative ai is moving at breathtaking pace, making step function changes rapidly in a short amount of time. Its an astonishing time to be alive, and it feels different from other disruptive technologies. This year alone, design discussions have ranged from some possibilities of apoc elliptic doom to the exhilarating promise of unprecedented advancements. As these technologies are speaking and conversing with us, creating images and challenging our understanding of human intent emergence. However many questions remain around around how we can best utilize these ai as humans for the good of humanity and to craft a future thats equitable, responsible and aligned with our core values. To discuss this critical topic, as the mayor said, were fortunate to be joined today by three of the worlds leading thinkers and developers of ai chris cox, chief product officer of meta. James manyika, googles svp of Research Technology and society, and sam altman, ceo of openai. Lets give them a warm welcome. Well, colleagues, ai is a wondrous technology fauci researchers are using ai to create new proteins and discover new drugs. Ai tutors may transform the way that children are educated. Their their potential financial, male workforce and climate benefits that we can imagine and those that we cant imagine. And there are risks. But before we get into the existence, risks and the Regulatory Environment that wed all like to see, id like to begin the conversation with looking through your eyes for a minute. Chris james and sam, why are you devoting your life to this work . We can start with any of you, but since i can see you. Chris yeah, im happy to start. I mean, its funny. I started studying ai back in 2001 and back when i was a lot more arcane of a science than i think it is today. Yeah. And i remember being first attracted to it because. Because it felt to me like our ability to understand learning would help us understand ourselves. Would help us understand how we learn in our own consciousness and part of whats been so interesting about it today is that the technology thats allowing ai to start to be really good is modeled after the way our minds work. You know, you dont teach a kid, i have two little kids, like you dont teach a kid. This is a noun and this is a verb and this is how you put a prepositional phrase together. You just speak to them and they learn through experiencing the world. Yeah. And i think part of why this is such an exciting period for ai is were starting to see that the technologies were building are start to become a little bit closer to the way we learn, which is through exposure to one another. And by building them that way. I believe has the promise of making the technology really humane and really modeled after the way that we interact with the world in our own judgments about whats right and wrong and our own judgments about what feels good and what doesnt feel good. So i think over the years weve come to a pretty neat place. And like you said, i think we all feel the sort of the excitement, but also at the same time, the importance of discipline and seriousness about making sure that the way we usher it into the world is responsible. Yeah of course. And for you, is this because its been a 20 year period for you . Focus on this is this to you your lifes work . Its certainly what ive spent the most of my life on. I mean, i started at facebook back in 2005, so i was one of our, i think, 13 engineers or 14th engineers. And most of my work there has been in trying to Design Software that gives people the content they care about that connects them to their friends and family. And if you go back to at least to our company history, i think similar to google, the fundamental innovation was really about getting good at recommending content for each person, personalizing content, understanding vast amounts of data, helping each person get uniquely the stuff they care about. And so for me, that was i that was sort of behind the scenes that was really important. And part of whats starting to happen now is people are becoming, i think, having contact with it by talking to it. I think thats part of what chatgpt brought us for the first time is like, oh, now i can talk to it. Yeah and i think that embodiment is part of what sort of like taking this tech thats been around for a little while and suddenly giving it a mode of interacting with with each other. Yeah. Hey, james, what about you . And you. You actually came. You were studying ai and went to mckinsey and then decided to make a real career pivot. Well, its wonderful to be here with sam and chris and you, laurene, as always, im looking forward to the conversation. For me, laurene, the very first thing i ever published in my whole life was in 1992. I was an undergraduate. It was a paper on training and modeling neural networks. That was the first thing i ever published in my whole life. I then went on after that to do a phd in ai and robotics at oxford and at the time, by the way, it was a very different time for the field. My advisors actually advised me not to put the word ai in my dissertation because no one would take me seriously. So we called it something else. But when i look back from that time to where we are, are the progress has been extraordinary. Its been extraordinary. We, you know, in the intervening time i was at mckinsey looking at these big problems in society, key things about economic growth, productivity, anti Climate Change and so forth. So part of what was realizing that i actually has a possibility of helping us to tackle all of these things. So what i get very excited and when i think about the work were doing at google, for example, you know, there are several areas that kind of motivate me, excite us. The possibility of actually helping people in very assistive ways. Do some of the most imaginative, creative endeavors, learn languages, speak languages, get past access barriers, linguistic difficulty. I will help with that. Yeah. The possibility that in fact we could actually transform economy is all the stuff that i spend my time Mckinsey Global institute thinking about productivity growth, expanding Prosperity Party how do we Power Company size economies, sectors. I will help with that. Then i think about science, the possibility of having these extraordinary breakthrough innovation engines to advance science. You mentioned proteins. I think its quite stunning thing that, you know, my colleagues at deepmind, alphafold, was able to predict the protein structure of all 200 million proteins known to science and then make that available to everybody. Its astonishing. Its astounding. But then i think also about some of our pressing challenges today. Think about access to Maternal Health in low Income Countries and communities. Think about Climate Change. You spend a lot of time thinking about the effects of Climate Change. Think about all the things we see in california wildfires. You know, the mayor can talk a lot about what we see in california. So all of these things gives us the possibility of actually addressing and enhancing how we tackle all of this. This is what motivates me and excites me. Definitely my lifes work and what i always wanted to work on since i was a little kid. I studied it in school. It wasnt working at the time. I got kind of sidetracked for a while, but as soon as it looked like we had an attack vector, it was very clear that this was what i wanted to work on. I think this will be the most transformative and beneficial technology. Humanity has yet invented. I i think more generally the 2020s will be the decade where humanity as a whole begins the transition from scarcity to abundance. We will have abundant intelligence that far surpassed our expectations. Same thing for energy, same thing for health. Few other categories too. But the sort of technological change happening now that is going to so change the constraints of the way we live and the sort of economy and social structures and whats possible. I think this is like going to be the greatest leap forward that weve had yet far yet so far. And the greatest leap forward of any of the of the big technological revolutions weve had so far. So im super excited and i cant imagine anything more exciting to work on. And on a personal note, like four times now in the history of openai, the most recent time was just in the last couple of weeks ive gotten to be in the room when we sort of like push the front, the sort of the veil of ignorance back and the frontier of discovery forward and getting to do that is like the professional honor of a lifetime. So thats just its so fun to get to work on that. And its remarkable, though, that for each of you, youve been working on this for decades. And so but now we find ourselves in a particular moment of inflection. So i wonder if you can help ground the audience in in understanding the ai lab landscape. So how does how does each of you think of where we are with the technology in the Development Overall development of generative ai . James feel free. Yeah, im happy to start. I mean, i think its worth reminding ourselves that ai has actually been with us for a while. Actually, a lot of the progress started to happen in the early 2000 with things like image recognition, natural language processing and in fact, many people today, you know, even before sams extraordinary moment last year, were already using ai. So, for example, theres over a billion people who use Google Translate. Thats a i. If youre using search, thats ai. But i think there was a particular moment that that that is brought us here in 2017 when my colleagues at Google Research published a paper called attentions all you need it introduced called attentions all you need. Thats the paper that introduced these transformer based architectures that are the underpinnings of these Large Language Models. That paper was in 2017. A lot of things and rapidly accelerated from that moment. We all started to train these Large Language Models and they all started to do these very general things, not just narrow things, because remember before this we had what you might call narrow ai. You could do ai for speech synthesis , for image classification and all of these things. But these large language model systems suddenly be able to do very general things and things just accelerated. So i think that was a Pivotal Moment that has brought us to where we are and so where are we . Well, i think were at a place where we can talk about this, where these systems are now very broad. Theyre very general. Everything from writing poetry, composing music and all these things. Theyve also become whats now termed multimodal. So its not just language and text, but also images and video and all these things and coding. Its a very exciting time. Were starting to see them do very well on benchmark tests on how well do they do on kind of a range of cognitive tasks and capabilities. Theres something called big bench, which has Something Like 204 kind of metrics. You can evaluate. So theyre starting to be very, very, very good. But i think its worth pointing out that they still have some serious limitations, actually. So as amazing as all these general capabilities are, theres still mistakes, theres still mistakes. Factuality fauci and so forth. But these are things i think will get better. But those limitations are quite real. Thats why i think its very important to have a deeper understanding going for where we are now about what these systems are good at, what theyre not good at, how we solve and augment those capabilities, link them to other systems. But im actually pretty excited because the what i now call the scaling laws and im sure sam will also get into this, is as you scale these systems, they seem to get more capable, more powerful, and the possibilities are very, very exciting. I agree. Theyre very exciting. They they also can be very concerning. And for some people really frightening. So i want to read to you, sam, a quote from the wise public intellectual, yuval harari, who said, ai is the first tool in history that can create new ideas by itself. Theres a danger that we will spend all our effort on developing an ai at the time. We dont understand ourselves, which is right now, and then letting ai take over. And that would lead to human catastrophe. So we obviously dont want that. So that brings up this question of proper regulation and proper guardrails and i think having the industry be come together as it has and take some steps forward around how do we how do we think about this collectively. So the industry has taken a very healthy step forward by launching the frontier model forum. And just in the last two weeks weve had a lot of regulatory bodies come forward. We had the white house executive order, we had the bletchley declaration, we have the advisory body on ai that the un has convened. So id like each of you to talk a little bit about how you think about some of the existential threats like yuval has articulated and others as well as the state of regulation on whats whats proper, whats too much . How do we get it right now and then be open to evolving as the technology evolves. I had dinner with yuval in tel aviv and early june of this year. He was very concerned and i understand. And it i really do understand why if you have not been closely tracking the field, it feels like things just went vertical and we didnt you know, sure, people maybe were doing stuff before, but not not like people had these papers here. This model here, this narrow thing here. But people that use like Machine Translation dont really feel like theyre using ai and all of a sudden there was the sort of perception of like something has qualitatively changed. Now i can talk to this thing. Its like the star trek computer. I was always promised and i didnt expect it to like happen. Why this year . Why not a year ago . Why not in ten years . Like what . What happened . So i think a lot of the world has collectively gone through a lurch this year to catch up. Now like humans can do with many other things. People are like, yeah, man, wheres gpt five . What have you done for me lately . Weve already moved on and thats great. I think thats awesome. Thats a great human spirit. I hope we never lose. But the first time you hear about this or use it, it feels much more creature like than tool. Like yes. And then you get to use it more and you see how it helps you and you see what the limitations are. And its just like, okay, we have like another thing on the Technology Tree that has been unlocked. Now i do think this time its different in important ways. And this is maybe the first tool that can self improve in the way that we understand it. But we need new ideas is like i think were on a path to self destruction as a species, right now. We need new ideas. We need new technology. If we want to flourish for tens and hundreds and millions of hundreds of thousands of millions of years, more and i think a lot of people see the potential of that in ai. But its not