빌 게이츠 AI 혁명과 초지능의 시사점

빌 게이츠는 초지능은 피할 수 없으며 AI 혁명이 인류를 변화시켜 도전과 기회를 가져올 것이라고 믿습니다.

### 빌 게이츠의 AI 혁명 초지능, 생산성, 그리고 미래
* 🧠 빌 게이츠는 **"초지능이 다가오고 있습니다. 그 속도를 늦출 수 있는 확실한 방법은 없으며, 현재 사용 가능한 기술은 이미 판도를 바꾸고 있습니다."**라고 말합니다.
* 🚀 AI 혁명은 **"현재 진행 중인 가장 중요한 일"**입니다. 매우 극적인 방식으로 인류를 변화시킬 것입니다.
* 👂 미래에는 **"딥 AI로 구동되는 개인 에이전트"**가 **"경영 비서, 친구 또는 전문가"의 역할**을 하게 될 것입니다.
* 🌍 게이츠는 AI를 **"가장 큰 글로벌 문제를 해결할 수 있는 도구"**로 보고 **"초풍요"의 미래를 상상합니다.
* 🏥 AI는 **"의료와 교육의 모든 측면에 도움이 될 것"**이며, **"엄청난 혁신"**을 가져올 것입니다.
* 💰 AI의 '진입 장벽'은 **"매우 낮은"** 수준이며, **"경쟁이 치열한"** 환경입니다.
* 🗳 AI는 **"잘못된 정보와 편견을 강조하고 서로 다른 견해를 연결하는 데"** 사용될 수 있으며, 잠재적으로 **"우리 모두가 잘 지낼 수 있도록"** 도울 수 있습니다.
* 🏆 AI의 첫 번째 **"획기적인 응용"**을 예측하기는 어렵지만, 게이츠는 현재의 기능을 **"놀랍다"**고 생각합니다.
* 📚 게이츠는 회고록을 집필 중이며, **첫 번째 권은 Microsoft 초창기까지의 삶**을 다룰 예정입니다.

I'm Rufus Grisim, and this is the next big idea today. Bill Gates on AI: the path to Superintelligence and what it means for all of us. I suspect that every moment in human history has felt pivotal, precarious, as if anything could happen, certainly in the last few hundred years. But it also must be true that some moments are more pivotal than others; this is one of those moments. We've seen the impact of transformative technological change; the internet has sped the world up, and social media, now on most every phone and most every hand, has polarized our communities, hyperbolized our politics. And now we are in the early moments of the AI Revolution. What will the next decade bring? There are few people I would rather ask this question than Microsoft co-founder and global philanthropist Bill Gates. Bill's been at the forefront of the race to build machines that can empower humans for 50 years, ever since he declared his mission to put a computer on every desk in every home. He was instrumental in driving the

development of personal computing in the 80s. The growth of the internet in the 90s, and more recently leading the charge to eradicate malaria and other diseases. In the last few years, he's been on the front lines of Microsoft's partnership with OpenAI and the development of GPT. How is it, you may be wondering, that Bill Gates has ended up joining us today? Well, for the last few months, I've been reading a book that's being published serially by Harvard Business Review. It's called AI First, and it features interviews with folks like Reed Hoffman, Mustafa Suleyman, Sam Altman, and Bill, who collectively make the case that AI isn't overhyped, it's underhyped. We thought it would be interesting to not just interview the co-authors of this book, career technologist Andy Sack, an old friend of mine, and former Starbucks Chief Digital Officer Adam Brotman, and they suggested inviting one of their most interesting interviewees, Bill Gates. And so, what's Bill's take on the AI Revolution? Superintelligence is coming.

there's no clear way to slow it down, and the technology available today is already a game-changer. This is largely a good thing. We can harness AI to solve our biggest global problems. We are likely to live in decades to come in a world of superabundance, but it will take vigilance to make sure it's the world we want for ourselves and generations to come. Bill Gates, welcome to the next big idea. Thank you, Bill. Andy and Adam and I were just talking about the digital transformations we've seen in our own lives in the last 40 years, and you haven't just seen these transformations, you've played an instrumental role in moving them forward. You've said that the demo you saw last September of GPT-4 was mind-blowing. Was it more mind-blowing than the first demo of the graphical user interface that you saw at Xerox PARC in 1980? I'd say yes. I mean, I'd seen graphical interface prior to the Xerox PARC stuff, and

um, that, you know, was an embodiment that helped motivate a lot of what Apple and Microsoft did, uh, with personal computing in the, you know, the decade after that. Uh, you know, people kind of take it for granted today that that we have those interfaces, but, you know, compared to unlocking a, a, a new type of intelligence that can read and write, uh, graphics interface is, is clearly less impactful, uh, which is saying a lot. Well, I, I was interested to learn that AI is not a new interest of yours, um, you were intrigued as a student way back in the 70s and, uh, I gather you, you wrote a, I think a letter to your parents and said effectively, Mom, Dad, I may miss out on the AI Revolution if I start this company, which is the company that became Microsoft. The AI Revolution took a little longer than maybe, maybe you might have guessed back then. Now it's happening. What interested you about AI in those early days and, and is it becoming what you'd imagined back then? Well, certainly anybody who writes

software is thinking about what human cognition is able to achieve, and you know, making that comparison. And when I was in high school, you know, there were things like Shakey the robot at Stanford Research Institute, which should engage in reasoning and come up with an execution plan and move, you know, figure out to move the ramp and go up the ramp and grab the blocks. And, you know, it felt like some of these key capabilities, whether it was speech recognition, image recognition, you know, would be fairly solvable. You, there were a lot of attempts and so-called rule-based systems and things that just didn't capture the richness. And so, in our respect for human cognition, you know, constantly goes up as we try to match pieces of it. But we saw with machine learning techniques, we could match vision and speech recognition, you know, so that's powerful. But the Holy Grail that even after those advances, you know, I kept highlighting was the ability to read and represent knowledge like humans did was just, you know, nothing was good at all.

you know then language translation came down, but still that was a very special case, thing. But you know, GPT-4 in a very deep way, far beyond GPT-3, you know, showed that we could access and represent knowledge. And it's, you know, the fluency in many respects, although not the accuracy, is already superum. Yeah, it's just astounding. We never would have guessed that moving the chess pieces on the chess board would be harder than becoming a better chess player than Kasparov. But, but it's interesting to see how, what the challenges turn out to be. And as you said, that Xerox Park demo set the agenda for Microsoft for maybe the next 15 years, right? The development of Windows and Office. And do you think that the impact of what's happening right now in AI is going to set the agenda for the next many decades? And even more so, it's absolutely the most important thing going on. It'll shape Humanity in a very dramatic way. It's at

the same time that we have, you know, synthetic biology and Robotics, you know, being controlled by the AIS, you know, so we have to keep in mind those other things, but the dominant, uh, change agent will be AI. In 1980, you had a light bulb moment when you famously declared there will be a computer in every home, on every desk. What do you think the equivalent is, is for AI? Do you think, do you think we'll have an AI advisor in, in every ear? Well, the form factor, the hardware form factor doesn't matter that much, but the idea of the earbud that's both adding audio and canceling out audio and enhancing audio clearly will be a very primary form factor. Just like glasses, uh, that can project sort of arbitrary video into your visual field, uh, will be, you know, sort of the embodiment of how you're interacting. But the personal agent, you know, that I've been writing about for decades, that's, you know, Superior to a human insistent in that it's, uh, tracking and reading all

the things that you wanted to read um, and you know just there to help you and understands the context enough that you know silly things like you don't trust software today to even order your email messages. It's in a, you know, stupid dumb time-ordered form because the contextual understanding of okay, what am I about to do next, what's the nature of the task that these messages relate to. You don't trust software to combine all of the, you know, new information in including uh new Communications. You know you go to your mail and that's time ordered, you go to your text and that's time ordered, you go to your social network and that time ordered. I mean computers are operating at a, a almost trivial level of semantics in terms of understanding what's your intent when you sit down with the machine or helping you with your activities. And now that they can essentially read like a white collar worker, uh, that interface will be entirely agent-driven. You know agent executive assistant agent mental therapy agent friend agent girlfriend agent.

expert all driven by uh deep Ai, and it seems like it will be useful in proportion to how much it knows about us. And I imagine at some point in the not too distant future, probably all four of us will be asked if we want to turn on audio so our AI assistant can effectively like listen to our whole life, right? And I would think that there'll be benefits to do that because we'll get good counsel, good advice. Um, do you think that's true, and do you think will you turn it on when invited to turn on the audio? Well, computers today see every email message that I write, um, and certainly digital channels are seen, you know, all my online meetings and phone calls. So you're already disclosing into digital systems a lot about yourself. And so yes, the value added of the agent in terms of summarizing that meeting or helping me with those follow-ups, um, you know, be phenomenal, and the agent will have different modes in terms of which of your

information. It's able to operate with so there will be partitions that um you have, but for your essentially executive assistant agent, you know you won't exclude much at all from that partition ruus before we go further down the agent pathway. One question that I've been thinking about since our interview with you, Bill, for AI first, in which you talked about really comparing your experience at Xerox Park versus your experience experiencing chat bt4. So, of I, I think you're in the most unique position, there probably a couple of other people that I could think of, but you're in the most unique um position to have the set of understanding of computer technology as well as building business and how computers affect human beings. I'm curious if you're if what you said in this conversation, which was chbt, was as big, it sounded like you even said it was bigger than your Xerox Park moment. What does that make you think about when you think about your grandchild's life and what advice

do you have for the sort of the next generation of leaders for tackling the challenges that are unique to AI. I'm sort of curious about that perspective. You know there's certainly novel problems in that other Technologies develop slower and the upper bound of their capabilities is pretty identifiable. I mean you know yes mechanization made farming more efficient and so people worried about okay where's the labor demand come and over time that question was answered very succinctly even though at the time you know there were Generations that never had to experience that or adjust to it. You know so this technology is in terms of its capability is and it will reach even modulo reliability will reach superhuman levels. We're not there today if you put in the the reliability constraint a lot of the the new work is adding a level of metacognition that done properly will solve the sort of erratic nature of the genius that is easily available today in the white collar realm and over time in the blue collar

realm as well so yes this is this is a huge milestone um that uh some of those past things are helpful too but um it's novel enough that nobody nobody's faced uh the policy issues which are mostly of a very positive nature in terms of uh White Collar labor productivity. What's the thing that excites you the most about the invention well all these shortages there's no organization that faces white collar shortage as much as the Gates Foundation where we look at Health in uh subsaharan Africa or other development countries or you know lack of teachers who can engage you in a deep way you know ideally in your native language um and so the idea that modulo whatever the the server cost is that by using the mobile phone infrastructure that you know continues to drive pretty significant penetration even in in very poor countries the idea that medical advice and personal tutors can be delivered uh where you know because it's meeting you in your language and your semantics there isn't like some big

training thing that's taking place there you just pick up your phone and listen uh you know to to what it's saying so you know it's very exciting uh to take the tragic lack of resources that uh particularly people in developing countries have to deal with and and you you've been working for your 20 years on the Gates Foundation and really tackling uh these issues of global Health Care education climate change um do you think that I mean we're just speaking to education and Healthcare do you think that AI will be an accelerant that will make it possible to accomplish in 5 or 10 years what it took the last 20 years to accomplish or how how meaningful do you think the the the the acceleration is likely to be in these areas well the very tough problems of some you know diseases that we don't have great tools for AI will help a lot the last 20 years we you know was pretty miraculous in that we cut child to death in half from 10 million a year to 5

million a year that was largely by using getting tools like certain vaccines. Uh, to be cheaper and making sure they were getting to all the world's children. And so that was kind of loow hanging fruit and now we have, you know, tougher issues but with the AIS. Um, the Upstream Discovery part of, okay, why do kids get malnourished or and why has it been so hard to make an HIV vaccine. Yes, we can be, you know, way more, uh, optimistic about those, those huge breakthroughs. You know, AI will help us with every aspect of these things, the, the advice, the delivery, the diagnosis, um, the scientific discovery piece is, is, you know, moving ahead at a, a pretty incredible clip. Um, and the Gates Foundation's, you know, very, very involved in funding quite a bit of that. Yeah, the, uh, we had, we had, uh, your friend Saul Khan on the show recently and, uh, got the chance to spend a bunch of time with K Migo and was, I was just astonished by what that can do. I know, I know you were.

recently in New Jersey, um, visiting schools that are implementing, uh, KH Academy's new programs. And, and that's, uh, that's pretty exciting. This idea that, that, that improving education at scale for billions of people, the impact of that is, is, is pretty hard to, hard to measure. Yeah, I mean Sal's book is, you know, doesn't say, okay, what world are we educating kids for. It's just if all AI was, was available in education, you know, that's pretty miraculous because you have the other things shifting at the same time. It's, you know, a little more confusing but, you know, that realm where he says, okay, what if it was just an education, uh, you know, it's incredibly positive. Yeah, well, that's, that, that gets to the personal part of, of, of your, you know, I think you have a new granddaughter. I know Adam has a seven-year-old and when we think of this question of like, what, what does it look like, um, I mean fantastic that our kids will have an Aristotle level private tutor, um, to, to, to help, uh, you.

know further accelerate their educational process. But there is the question of like what will what will they need to know to be effective in the world. Um and uh my kids and Andy's kids are a little older, but I know Adam you've got a younger daughter. And yeah, Bill you got a new granddaughter. It's interesting because Bill I wanted to come at this room a slightly different direction, but since you brought it up she, you know, she's um able to really she watches me use whisper mode on Chacha PT. She's, she's you know, seen me live in an AI world, and it's fascinating to watch her be very comfortable with the voice interface, especially at her age. It's actually easier for her to do voice interface than you know she's still learning how to spell. I mean she just figured out how to read. So um I thought that was an interesting call look into you know how much is this going to be not just natural language chat but even voice chat versus point and click. But Bill

was going to ask you something about the direction. It maybe come out this from a slightly different direction. Which is what do you think about this debate? There's a little bit of a debate going on. Maybe that's too strong of a word about whether or not the fact that all these Frontier or Foundation models have sort of clustered at their benchmarks around chat bt4. And there's a, you know, there are some people that are on the side that, you know, we're plateauing or something like that. And then there's but most of the smartest researchers I follow tend to still say with the fact that the scaling laws are going to continue to apply for at least the next couple years. I'd love to get your take on a. Where do where do you come out on that on that discussion? And B do you find yourself rooting for it to Plateau or do you are you like emotionally agnostic because of some of the concerns around the technology? Well, the, the, the big Frontier is not so much scaling. We have, you know, probably two more turns of

the crank on scaling where by accessing video data and getting very good at synthetic data that we can scale up probably you know two more times. That's not the most interesting Dimension. The most interesting Dimension is what I call metacognition where understanding how to think about a problem in a broad sense and step back and say, Okay, how important is this answer? How could I check my answer? You know, what external tools would help me with this? The overall cognitive strategy is so trivial today that you know it's just generating through constant computation each token in sequence, and it's mind-blowing that that works at all. It does not step back like a human and think, Okay, I'm going to write this paper and here's what I want to cover. Here's okay, I'll put some facts in here. Here's what I want to do for the summary. And so you see this limitation when you have a problem like various math things like a Sudoku puzzle where just generating that upper leftand thing first it causes it to be wrong on.

anything above a certain complexity. So we're going to get the scaling benefits, but at the same time, the various actions to change the underlying reasoning algorithm from the trivial that we have today to more human-like metacognition. That's the big frontier. It's a little hard to predict how quickly that'll happen. You know, I've seen that we will make progress on that next year, but we won't completely solve it for some time after that. So your genius will get to be more predictable now in certain domains combined domains. We are getting to the point of being able to show extreme accuracy on some of the math or even some of the health-type domains, but the open-ended thing will require general breakthroughs on metacognition. And do you think that metacognition will involve building in a looping mechanism so there's so the AI develops an ability to ruminate as we Homo sapiens do um and is there I've

heard some people like Max Tark suggest that that that could be part of what makes us conscious. Is this ability to have conversations with ourselves, yeah. Consciousness may relate to metacognition. It's, you know, it's not a phenomena that is subject to measurement so it's always tricky. And you know, clearly these digital things are unlikely to have any such equivalent. Um, but you know, it is the big frontier that and it will be humanik in terms of knowing to work hard on certain hard problems and having a sense of confidence and a ways of checking what you've done, yeah. Phil, I was going to just ask about the second part of Adam's question. Do you find yourself rooting like given this? I mean, one of the things that I'll just say in the process of writing and interviewing you for AI first as well as Reed Hoffman and Sam Alman, Mustafa, it's been an education for it, you know, it's been an education for Adam and I.

come away from these conversations regularly going, Oh my goodness, um, and, and I'm blown away at the pace. Like, I'm paying attention every day to the pace of the technological advance by really, um, many different companies, bit large, large companies. There's a lot of money, there's a lot of talent being poured into us, and so the pace of the development is, and, and the potential impact of that technological advance, um, astounded by and have some, Li limited understanding, um, that was where I was getting at with my question that you're uniquely positioned to actually have some, some point of view on your own grocking of like, are you do you think we're moving too fast, uh, I know there's no really slowing it down, what do you do about the fact that we're moving at what the speed that we're moving, um, so it sort of is what it is, but I'm just sort of curious how you interpret that, you know, if we knew how to slow it down a lot of people would probably say, Okay, let's, you know, consider doing that, um.

you know, as Mustafa writes in his book, the incentive structures don't really have some mechanism that's all that plausible of how that would happen given the individual and uh company and even government level. Thing if the government level incentive structure was understood, you know, that alone might might be enough. Um, and you know, like the people who say, Oh, it's fine that it's open source, you know, they're willing to say, Well, okay, if it gets, you know, too good, maybe we'll stop open sourcing it. But you know, will they know what that is, uh, and would they really say, Okay, maybe the next one, um, you know? So you pretty quickly go to, Let's not let people with Mal intent benefit, you know, from having a better AI than, uh, you know, the sort of defense, good intent side of, you know, cyber defense or, uh, war defense or bioterror defense. Um, you know, you're not, you know, you're not going to completely put the genie back in the bottle, and and yet that means that you

know somebody with negative intent will be empowered in a in a new way, so perhaps not a good idea for the most sophisticated AI models to be open source. In your judgment, given this global environment, yeah, and people sort of seed that point in principle, but then when you try to get to say, Okay, specifically, uh, where would you apply that? it gets a bit less clear. I mean, Adam and I were talking yesterday about how even if it were possible, hypothetically, to stop AI development exactly where it is right now, it would probably take 10 years of Forum 3 and other folks helping companies and individuals figure out how to apply the technology that currently exists, right? I mean, the, we already have an AI that's powerful enough, I think, to have profound implications. Uh, it, it feels, it feels like we could easily benefit from 5 to 10 years just thinking of all the useful applications of the, the, the level of AI we have today. Do you think so? I'm not sure about that because you know it's

pretty clear you know I want to make an image. Okay, what do I have to learn? I have to learn English. Uh, this is the software meeting us, not us meeting the software, you know, so it's not like there's some new menu, you know, file, edit, window, help, and oh, you got to learn that you have to type the formula into the cell. This is you saying, hm, I wish I could do data an analysis to see which of these, you know, products is responsible for a slowdown, and it understands exactly what you're saying. So the idea that there's a impedance of adoption, uh, it's not the normal thing. Yes, company processes, um, that are very used to doing things the old way, uh, will have to adjust, but if you look at, you know, Tes support, Tes sales, uh, data analytics, you know, give somebody a week of watching an advanced user, and you know, say no manual of any kind, just you know, learn by example of how the stuff has been used, the uptake assuming there's no limit in terms of

the you know server capacity that connects these things up. Which I don't expect, certainly in rich countries, there'll be a gigantic limitation there. And you're talking about an adoption rate that won't be overnight, but it won't be like, you know, 10 years for us. Uh, you know, the number of things I take human translation, the idea that a free product provides arbitrary audio and text human translation. I mean, that was a holy grail of, oh my God, if you ever had a company that could do that, it would collect, you know, tens of billions in revenue and, you know, solve the tower of Babel. And here, you know, kind of a small AI company is providing that as an afterthought free feature. Um, right, totally, it's, you know, pretty wild. And you say, Well, oh, how are people going to adapt to free translation? I don't think it's going to take them that long to know, Hey, I want to know what that guy was saying. Uh, and you know, you can separate the two audio channels with earbuds or something.

and you know there you are and yes the quality of that a year from now and the coverage of, of say all African languages will get completed you know the foundations making sure that even obscure languages that are not written languages that were in partnership with others. Gathering the data for those. The Indian government's doing that for Indian languages so I don't think saying hey calm down it takes a long time uh to figure out you know how to utter the description of the birthday card you want you know and so it'll take you know 10 years for the legging person people to to switch their behavior well well we see. I think I think Sam Alman said on your on your podcast unconfused me which I enjoy uh that there're seeing a productivity Improvement of up to 300%. I think among their developers uh and in other sectors I think we've seen reports of you know 25 50% increases in productivity um so that just just getting that you know you know the great.

Gibson line the future is here. It's just not evenly distributed. It does feel like getting all companies to fully benefit from that level of productivity enhancement certainly will be a process of some kind. I was interested in your comment in the first chapter of AI first, which is about productivity. You said productivity isn't a mere measure of output per hour. It's about enhancing the quality and creativity of our achievements. What do you mean by that? Well, whenever you have a productivity increase, you can take your x% increase and increase the quantity of the activity, the quantity of the output, you can improve the quality of the output, or you can reduce the human labor hours that go in input. And so you always take those three things. You know, there are some things when they get more productive, like when the tire industry went from non-radial tires to radial tires, even though the cost per year of tire usage went down by a factor four, people didn't respond by saying

okay, I'm going to drive four times as much. So the demand elasticity for some things like computing or the quality of a news story, there's very high demand elasticity. If you can do a better job, you just leave the human labor hours alone and take most of it in the quality dimension. And then you have a lot of things where that's not the case at all, the appetite, you know, for miles driven, you know, did not change. So society is full of many things that are across that spectrum. And so whenever you have rapid productivity increases, you know, there was a memo inside Microsoft about how we were going to make databases so efficient that it would become a zero-sized market. Now in that case, we're still in the part of the curve where you have demand elasticity, but you know, someday, even in that domain, we'll get past incremental demand. I got one last question I can pop in here if

you were making a guess right now, and you mentioned healthcare and education. How would you respond to the question about, you know, what do you think the first big, I'll call it, breakthrough, you know, application will be like? For example, like one of the podcasts that Andy and I like to listen to, they were talking this weekend. They keep saying, Oh, we haven't seen, you know, the big breakthrough application. And I'm, you know, which is interesting because there's, I'm not sure that's true, but let's just take it for on its face value that we're still in the sort of, I'll call it, experimentation phase or whatever, which is what they were trying to say. I'd be curious to get your, what's your thought like, where do we see the first big, you know, the Uber like, if, if, if, like, you know, location services and mobile Cloud, the first big app was kind of Uber, and everyone talked about Uber being an example of that. It was probably before, before that, it was probably Google Maps, right? I was

probably map technology. Yeah, that's right, that's right. So we have when you just think out like, do you go right to education, health care, you know, where does your head go when you think, Oh, I'll bet you the first big breakthrough app, consumer app or even industrial app will be what? Well, I guess the naysayers are pretty creative to be able to say something hasn't happened. I mean, I agree, they don't think, you know, no, yeah, summarizing meetings or, you know, doing translation or making product programmers more productive. I mean, that's it, it's mind-blowing, you know, this is White Collar capability with a footnote that if, if in, in many open Ed scenarios, it's not as reliable as humans are. You can hire humans and they can go haywire and so you have some monitoring but that, you know, these things if it put into new territory are, you know, somewhat less, uh, predictable as there's some domains where we can bound what goes on like.

support calls or Tes sales calls, where you're not pushing off the edge, uh at all so I don't know, I I I just can't imagine what they're talking about that, you know, let me let me try and let me try and I think like you know, I think it's a the comment when people say that, not withstanding what you just said, Bill, they, they're creative and their naysaying capabilities, um, because I think that's your response is accurate, um, for sure, it's like when the car was developed, you know, you, it's the second order effect, when the car was developed, it could get you from point A to point B, um, and you might even be able to predict, uh, the development of roads and highways, etc., but you might not be able to predict Los Angeles or suburbs, um, and, uh, all, you know, drive-in movie theaters, and, and in the case of I think when in more modern, um, stance, the worldwide web came OG, and there were lots of brochure wear, and you know, there was, uh, travel agent.

Expedia came along, and that was all sort of like run-of-the-mill first-order effect, but people point at Uber as a second-order effect on the technology on that. That sort of was like, Oh, you couldn't have predicted that. Now maybe you could, maybe you couldn't. But that's what I think. That's what Adam's question, I think, is going for. When you look at AI, I mean, in many ways, search is the game of search has already changed, which is ubiquitous. Um, um, uh, consumer activity. Uh, and certainly, Chat GPT was a monumental, the fastest-growing technology, uh, adopted, uh, technology in our ever. So I don't, I'm not minimizing or giving credence than the Nays, but it's really about the second-order effects. Now we, yeah, we, you know, Chat GPT-3 was not that interesting. I mean, it was interesting enough that a few people that opened the eye felt the scaling effect would cross a threshold. And I, I didn't predict that, and very few people did. And we only

crossed that threshold less than two years ago. A year and a half in terms of General availability so we are very much in the people who are open-minded and you know are willing to try out new things are the ones using it but you know you just demo okay here's image editing and no I'm not teaching you 59 menus and dialogues in Photoshop to do editing. I'm telling you type get rid of that green sweater and people are like oh I don't know if I could do that. I mean that sounds very hard to me. Uh you know and when you show people that it's like what make that photo bigger. I didn't take I didn't take a shot that was bigger but I'd like the photo to be bigger so fill in the missing piece to make it bit and it's like what you know or patient follow-up you know where it calls you up and talks you about did you fulfill your prescription how are you feeling you know what are you doing I mean uh you

you people may get saturated if they really try and expose themselves to the various examples. I do think they'd be saturated. Oh my God, this is, you know, a lot of extremely concrete capability. And you think, okay, when I call up to ask about my taxes, when I want my medical bill explained, the white-collar worker is almost free-type mentality is the best way to kind of predict what this thing suffuses to. Even though I fully admit there's a footnote there that it's in some ways still a little bit of a crazy white-collar worker, but you know that we're going to get rid of that footnote over a period of years. I know one of those crazy white-collar workers who's a CEO of a company that's growing very quickly who asked his top salespeople what takes you the most time during this day, and they said writing drafting follow-up emails following sales calls, and he created an instance of GPT to, you know, pulled in

all their best practices. Best Communications automatically transcribes every phone call and automatically generates the follow-up email. And he's laying off half of his sales team so that the best half of his sales team can work because they can now work twice as efficiently. So there we have both a success story in the sense that it's a highly efficient and wildly impressive implementation of the technology, but there's for the other half of the sales team, it's not quite as exciting unless they can use new AI technologies to build a competing company or to do something else, which I guess, you know, gets to this broader question of like to what extent do we think this empowers the little guy versus the big guy. I mean, we're seeing that there just a few big companies seem to be the dominant players in the development of the technology, but on the other hand, it does seem that everyone has access to GPT-4 Omni now for free.

there's also an equalizing element. Well, it's important to distinguish two parts of economic activity. One is the economic activity building AI products, and both Bas level AI products, and then vertical AI products. And we can say for sure that the barriers to entry are uniquely low, uh, in that we're in this Mania period where, you know, somebody literally raised $6 billion dollars in cash, you know, for a company, and many others raised hundreds of millions, and you know, so the idea that there's, you know, there's never been as much Capital going into a new category, you could even say a new Mania category. I mean this makes the internet or the early Auto industry Mania look, you know, quite small in terms of the percentage of IQ and and the valuations, uh, you know that come out of this. I mean, you know, there was no company before the turn of the century that had ever been worth a trillion dollars. Here we have one ship company who doesn't make chips, it's a chip design company, uh, that in six months

adds a trillion dollars of value. Uh, you know that. And so, the dynamics within the AI space is both hyper-competitive but with lots of entry. And yes, Google and Microsoft have the most capital but, uh, that's not really stopping people either in the base capabilities or in those verticals. Once you leave the AI tools domain, which as big as it is, is a modest part of the global economy. How that gets applied to, okay, I'm a small hospital chain versus a big hospital chain. You know, now when I have these tools to that, you know, level the plane field or not, you would hope that it would, uh, and that you can offer it for the same price, or less, a far better level of service. All of these things are in the furtherance of getting the value down to the customer and, you know, figuring out early in an industry where the barriers are so that some of the improvements stick with companies versus perfect competition where it all goes to the end users. That's very hard, you know, to think.

Through, you know, like pick and shovels, is saying, Okay, look to the side Industries, uh, you know, as well as to the primary industry, you know, Savings and Loans did better than homebuilders, uh, because there was a more scarce, uh, capability there that, you know, a few did better than others. So, it's asking a lot, but you know, it's, it is, people are being forced to think about the competitive Dynamics in these other business es, you know, when you free up labor, that labor Society is essentially richer, uh, that, you know, through your tax system, you can take that labor and put it into, you know, smaller class size or, uh, helping the elderly better, you know, and you're net better off, uh, now for the person involved. They may like that transition or not, and it requires some political capacity to do that redirection, and you can, you know, have a view of our current trust in our political capacity, uh, to reach consensus and, uh, you know, create effective programs, but you know, it, it's the frontier of possibilities is improved by

increased productivity. You'd never want to run the clock backwards and say, you know, thank God we were less productive, uh, you know, 20 years ago. Do you think that, uh, we were talking earlier about the impossibility of, of slowing down or, or the great difficulty of slowing down the current pace of AI development? Do you think AI companies should be governed, and if so, by whom? By, by Boards, by government, by all of the above? Well, government is the only place where the overall well-being of society as a whole, you know, including against attack and, you know, Jud system that's fair and, you know, creating educational opportunities so the, you can't expect the private sector to walk away from Market-driven opportunity unless the government decides what the rules are. So this is, although the private sector should help educate government, work with government, uh, the governments will have to play a big role here, um, and you know, so that's a dialogue that people are investing in, um, now governments will, will take the things that are most

concrete like what are the copyright rules or what are the abuses of deep fakes. Or you know in some applications does the unreliability say health diagnosis or um um hiring decisions. You know mean that you ought to move more slowly or or create some uh liability for those things. They'll tend to focus in on those short-term issues which you know that's fine. But you know the biggest issue has to do with the adjustments to productivity that overall you know should be a phenomenal opportunity if political capacity and the speed which which it was coming uh were were paired very well. Um our environment of of of polarization doesn't help the uh the effectiveness of our government. Um and I think you mentioned on your podcast that in a worst-case scenario we could imagine polarization you know breaking our democracy. Um do you think AI can help us all get along uh and if so how would it do that well it's such a powerful tool that at least we ought to consider in for all our tough problems where it can.

be beneficial or where it can exacerbate things. So, certainly, if somebody wants to understand, Okay, where did this come from? This article or this video, you know, can you - what is the providence? You know, is that probably a reliable source? Or is this information accurate? Or, you know, in general, in my news feed, you know, what am I seeing that, you know, somebody who's voting for the other side, what have they seen? And, you know, try to explain to me what has pushed them in that direction. You'd hope that, you know, sort of the - again, going back to the paradigm of white CER capability being almost free - that, you know, well-intended people who want to bridge those misunderstandings would have the tools of AI to highlight misinformation for them or highlight bias for them, or help them, you know, be in the mindset and understand, Okay, how do we bridge the different views of the world that we have? So, yes, although it sounds outlandish, it's like you

know when people say, Oh, let's use geoengineering for climate, they're like, Oh no, you always think you know technology might be the answer. And yeah, you know, I'm okay, I'm somewhat guilty of that. But here, the AI's are going to be both part of the solution, while if we're not careful, also potentially exacerbating these things. And you can almost say it's good that the blue-collar job substitution stuff is more delayed than the white-collar stuff, so that, you know, it's not just any one sector, and actually, it's the more educated sector that's seen these changes first. I hadn't thought of that. Okay, last question. You've said that a possible future problem that befuddles you is how to think about our purpose as humans in a world in which machines can solve problems better than we can. Do you--is this a nagging concern that continues to wrestle with? How do you think about it now? Well, I don't think somebody who spent, you know

68 years in a world of shortage, and you know, okay, we use market mechanisms to, you know, deal with the shortage. We use various incentive structures to innovate, to create more supply capacity. I doubt that either at that absolute age or having been immersed in such an utterly different environment that the ability to imagine, you know, this post-shortage, type world will come from anyone near my age. Um, so right, you know, I view it as a very important problem that people, people should contemplate, but no, I, I, that's not one that, um, I, I have the solution or would expect to have. Although, although you have some experience with living in a post-scarcity world, in the sense that you haven't had scarcity in your own personal life for a few years now. I haven't had financial scarcity, but yeah, you know, somebody who's had the enjoyment of being successful and sees problems out there like malaria or polio or measles, the satisfaction that, okay, the number of people who work on this, the amount of

research money for this is very very scarce, and so I feel a unique value added in taking my own resources and working with governments to orchestrate. Okay, let's not have any kids die of malaria. Let's not have any kids die of measles. So you're right financially that you know what I do for fun, you know, is a potential, uh, kind of thing that people can do, you know, play pickleball. Cue the machines. The fact the machines will be good at pickleball, you know, we that won't bother us. We'll, you know, still, uh, enjoy, uh, that as a a human thing. But the, you know, the satisfaction of helping out reduce scarcity, um, you know, that, that which is the thing that that motivates me, that also goes away. Yeah, yeah, yeah, yeah. So the true last question. I rumor has it you're working on a memoir. Can you tell us anything about that? Yeah, we announced that in next February, uh, sort of a a first volume that covers my life up till the first two or three years of

Microsoft about age 25 or so called source code will come out. So I'm working on editing that right now. Uh, since we're about to hit deadlines. But yeah, we got a good reception to the pre-announcement of the that first volume. Is GPT helping you out with that actually? No, um, you know, not because I'm against it or anything. I suppose in the end we maybe we should, but uh, no, it's still uh, we're being a little traditional in terms of how we're both writing and editing. Will there be two volumes or three volumes, you think? Three. So they're, you know, we'll probably wait three years before we do a second one. But you know, there's kind of a period. That's Microsoft oriented and a period that's, you know, sort of giving all the money away focused. Well, if you and Andy play enough pickleball, may maybe you'll, uh, live long enough to make a write a fourth volume. That's true. We hope so, you know.

making AI good we'll make that the the fourth volume exactly well Bill thank you so much uh for joining us today such an interesting conversation yeah fantastic thanks Bill

Bill Gates Reveals Superhuman AI Prediction

Next Big Idea Club

빌 게이츠는 초지능이 필연적이며 이미 전 세계 문제를 해결할 수 있는 잠재력을 가진 게임 체인저라고 믿습니다.

그는 70년대부터 AI에 관심을 가져왔으며 최근의 발전, 특히 GPT-4의 개발에 깊은 인상을 받았습니다.

게이츠는 AI가 그래픽 사용자 인터페이스보다 더 큰 영향을 미칠 것으로 보고 있으며, 향후 수십 년간 인류를 극적인 방식으로 변화시킬 것으로 예측하고 있습니다.

AI의 미래와 일상 생활에 미치는 영향

AI는 앞으로 이어버드와 안경이라는 기본 폼 팩터를 기반으로 상호작용을 위한 주요한 변화의 주체가 될 것으로 예상됩니다.

개인용 AI 에이전트의 개발은 맥락을 추적하고, 읽고, 이해하는 데 있어 인간의 지능을 능가하여 잠재적으로 삶의 모든 측면의 일부가 될 것으로 예상됩니다.

개인화된 지원을 제공하는 AI의 능력과 노동 생산성 및 의료 조언에 대한 접근성 등 삶의 다양한 측면을 개선할 수 있는 잠재력은 빌 게이츠를 가장 흥분시키는 요소입니다.

AI가 글로벌 의료 및 교육에 미치는 영향

AI는 특히 질병과 백신과 같은 어려운 문제에 대한 새로운 솔루션을 발견하는 데 있어 글로벌 의료 및 교육 분야의 발전을 크게 가속화할 것으로 기대됩니다.

특히 수십억 명의 인구를 대상으로 한 대규모 교육에서 AI의 활용은 기적적인 영향을 미치는 것으로 여겨지지만, 아이들이 세상에서 효과적으로 살아가기 위해 무엇을 알아야 하는지에 대한 질문은 여전히 남아 있습니다.

AI 개발의 초점은 단순한 데이터 처리의 확장보다는 가장 흥미로운 차원으로 여겨지는 문제를 폭넓게 생각하는 방법을 이해하는 메타인지로 옮겨가고 있습니다.

AI는 인간과 더 유사한 메타인지를 향해 발전하고 있지만, 이를 달성할 수 있는 시점은 불확실합니다.

AI 기술의 급속한 발전으로 인해 그 발전 속도와 영향력에 대한 의문이 제기되고 있으며, 그 속도를 늦추는 방법에 대한 이해도 제한적입니다.

정교한 AI 모델이 오픈소스로 공개될 경우 미칠 영향에 대한 우려가 있으며, AI 개발을 중단하더라도 기존 기술을 어떻게 적용할지 고민해야 할 것입니다.

AI가 생산성과 업무의 미래에 미치는 영향

AI 도입률은 빠르게 증가할 것으로 예상되며, 특히 기술 부문에서 생산성을 크게 향상시킬 수 있는 잠재력을 가지고 있습니다.

AI를 통한 빠른 생산성 향상은 결과물의 품질과 창의성 향상은 물론 노동시간 단축으로 이어질 수 있지만, 그 영향은 산업마다 다릅니다.

의료, 교육, 소비자 앱 등 다양한 분야에서 생산성을 향상하고 새로운 기능을 제공하는 AI의 능력을 통해 획기적인 첫 번째 AI 애플리케이션의 잠재력이 존재합니다.

AI가 매출 및 경제 활동에 미치는 영향

GPT-3와 같은 AI 기술은 영업 효율성을 크게 개선하여 경우에 따라 인력 감축으로 이어지고 있습니다.

AI의 발전은 대기업과 중소기업 간의 역량 강화와 접근성 측면에서 격차를 만들고 있습니다.

AI 산업은 AI 제품 개발에 대한 진입 장벽이 낮아지면서 전례 없는 재정적 투자의 시기를 경험하고 있습니다.

AI가 사회와 정부에 미치는 영향

AI는 글로벌 경제에서 빠르게 성장하고 있으며, 특히 AI 도구 영역에서 치열한 경쟁과 광범위한 진입이 이루어지고 있습니다.

정부는 민간 부문의 참여와 협력에도 불구하고 사회 전반의 안녕을 보장하기 위해 AI 기업을 관리하는 데 중요한 역할을 할 것으로 예상됩니다.

AI는 잘못된 정보와 편견을 해결하고 서로 다른 세계관을 이해하고 연결할 수 있는 도구를 제공함으로써 사회적 격차를 해소하는 데 도움을 줄 수 있는 잠재력을 가지고 있습니다.

미래 과제 해결을 위한 AI의 역할

AI는 해결책의 일부이자 잠재적으로 미래의 문제를 악화시킬 수 있는 요소로 여겨지고 있으며, 교육 수준이 높은 부문에서 먼저 기술 변화를 경험하고 있습니다.

특히 희소성이 줄어들면서 기계가 문제를 더 잘 해결하는 세상에서 인간의 목적을 어떻게 정의할 것인가에 대한 고민이 있습니다.

빌 게이츠는 회고록을 집필 중이며, 첫 번째 권은 마이크로소프트 초창기까지의 삶을 다루고 있으며 총 3권을 출간할 계획입니다.