Possible: Bill Gates on possibility, AI, and humanity

28:55And then battery storage is a challenge. And so you and I have invested in some fusion things together. Say a little bit about what's the hope and the possibilities for fusion. Fusion is where you take the big atoms like uranium and as they split, you get energy. And fusion is where you take the small atoms, primarily hydrogen, as you put them together, you release energy. The middle of the periodic table is the most stable, and so you're getting relativistic energy through that mass decrease. Fusion is very difficult. It involves, you know, temperatures that are like the center of the sun, you know, millions of degrees.

29:43And so that's plasma physics, which we know a lot more about. You know, we're using AI tools to study those things. And now there's a variety of techniques, tokamak, which Commonwealth Fusion System is using, being the one with the most credible schedule for, say, 10 years from now. Most of the others are probably more like 15 years away. But at some point, fusion energy will be extremely cheap. And it doesn't have the same waste problems that fission does. I think those are solvable problems and I'm investing in that because that's more like a six-year time frame if everything went perfectly.

30:30So society as a whole, even though a lot more money is coming into it, we're still underinvesting in fission and fusion given that the value of cheap electricity specifically is so fundamental to society. I mean, if somebody says to you, oh, we have a water shortage. No, there's a lot of water. It just takes energy to move that water and desalinate it. So if energy is cheap, you have infinite, wonderful water everywhere in the world. But the energy is too expensive right now to do that at scale. Even recycling things. Why can't we, atoms don't leave the planet, tiny bit of hydrogen, but it's all there.

31:14And the reason we don't is that the energetic costs of restoring things to their original state is too high. Well, one of the, for our listeners, a TerraPower, super awesome way of kind of actually using nuclear fission waste as fuel. And so getting a compounding effect is one of the things that you guys have been working on for a number of years, maybe even 10. Yeah, 2006 is when the fission company TerraPower got started. Yeah, exactly. Now, one of the things that always bemuses me about some of the current public dialogue around AI is like, oh, is this going to accelerate climate change because of the electricity cost?

31:52And I think what most of these people are not realizing how we can also use AI to help us with climate. So because if we can get a lot more intelligence applied to various problems, that can help us with climate. Say a little bit about how you're thinking in that arena. You know, the extra electricity load is, you know, it's there, but it's like a 10 % add-on. And it'll challenge the way that we do green accounting a little bit. And I wish Fission and Fusion were sooner because this sort of gold rush for AI backend capacity is kind of the next eight years. And even fission will only be able to make a modest contribution in the 2030 timeframe to that electricity supply.

32:44So the value of AI in solving the scientific problems of, okay, how do you grow, how do you make plants more productive? Okay, you model photosynthesis and you model how you change the plant genetics in order to double the productivity. That's a very profound advance, improving photocytic efficiency. In fact, you know, because it's kind of a far out thing, the foundation is the primary funder of that. As we show that it can work, okay, other people will come into that. But anyway, AI for material science, biology, it is a gigantic accelerator. So take whatever green product you think is going to be the hardest to get the zero green premium.

33:35Rethink how hard that's going to be because the AI tools are so phenomenal at accelerating all of these paths of innovation. Yeah. And actually, one of the things I've been thinking about is that while it's a big electricity cost for training these scale learning machines, once you have that intelligence, like that's how we've made everything is through intelligence. Once you have that intelligence to amplify across the board, like applying that to climate change has got to be like there's got to be some multiplier effect of we get this much actually savings and carbon and other kinds of things through the application of this electricity.

34:13I don't know what the multiplier will end up being, but I'm certain it's there. No, it's absolutely there. There are some goals like not going above 1.5 degrees that even with AI being a net positive contributor, because of the difficulty of scaling in all the areas in all the countries, some of those goals we will miss. But we will avoid the level of heating that would be disastrous. And we will need to do some adaptation, particularly in poor countries. So I want to switch gears. Another area where I think you're probably best known is global health. And I think it's an area where AI can do so much.

35:03And my husband is a public health data scientist, so he's particularly excited about this area of the interview. You have focused on the eradication of disease. And I think, but fact check me, in 1980, the WHO declared that smallpox was eradicated. And that's the first and only disease that we have eradicated. You've said, let's tackle polio. Let's tackle malaria. How do you pick? What is the next disease you're going to tackle? Like, what an amazing ambition. And then how do you go after it? Yeah. So most diseases, we're going for a burden reduction. Only very few diseases should you try to go for eradication because it's very, very hard to get to zero.

35:46And right now with polio, we're in Afghanistan, we're in Gaza, we're in Somalia, we're in DRC, and we're having to execute high coverage vaccination campaigns against misinformation and violence in the toughest places in the world. So it's very, very hard. Polio's close. There's one called Guinea Worm, which is confined to Africa, where President Carter just got to 100. He's been a champion of that. So we're hoping he'll be alive not only to vote in the election, but also to come to the Guinea Worm celebration party. It's going to take a couple of years, so he's going to have to hang on a little longer.

36:32So the magic thing that happened at the turn of the century was people got serious about global health, about really measuring, okay, kids die of diarrhea, but what caused that diarrhea? They die of pneumonia, malaria. Okay, it's more clear what that is. But even though there's no market, the people who die of malaria, half a million kids a year, it's not like you can make a business case of, hey, go to Silicon Valley and do a malaria startup and look at that spreadsheet. The line that says life saved will look good, but the line that says profit will have a lot of red numbers because they can't afford these tools.

37:12So medical science is very distorted towards rich world conditions and even amongst rich world conditions towards cancer and a few other things. So the incentive system is in a potential could be improved. But the Gates Foundation, that's our place we come to fill in, is that the things that aren't market-driven, like getting diarrheal vaccines cheap enough for all the kids of the world, not just the rich kids who don't have diarrhea, but that also used to be a half million, now down to 100 ,000. So as we went from 10 million under five deaths per year at the turn of the century to 5 million, diarrhea was one of our best.

37:54Pneumonia, we got a vaccine out for that, which was a very expensive vaccine that we worked with all the vaccine companies, Western and Asian, to get those prices down. And so we're basically driven by the inequity where we say, why do mothers die in childbirth 20 times as much in Africa? Why do kids die 50 times as much in their first five years in poor countries, particularly Africa, but also Southeast Asia? And so we're taking all of those and saying, OK, let's find the best scientists. Let's understand the field conditions. Is this stuff deliverable? Will it be accepted? You know, we have crazy ways of killing mosquitoes.

38:41That alone doesn't get rid of malaria, but if you treat a lot of humans and the reinfection rate has been massively reduced, then you can get to the point the U.S. got to because we had malaria where you've cleared during the low season. That's the winter here and the dry season there. You've actually cleared the pyrocyte. So there's no humans. so there's no reinfection taking place. And in the next, hopefully, well less than 20 years, we have five years now we need to do the tools. So our goal is to finish polio during this five years and then with new tools get the credibility to get the world to fund a malaria eradication starting in 2030.

39:28Totally awesome.

39:38One of the other projects we work on together is AI and drug discovery. And so this is one of the ones I think we may actually even begin to see some of the earliest kind of global benefit from. So what areas of AI drug discovery are you kind of most focused on and think can make a kind of a global health difference? Yeah, so understanding protein and molecular shape space is a perfect AI problem because we have databases, the protein database that, you know, we have 150 ,000 molecules, we know the shapes. And so we've trained AI on those, their ability to predict the shapes and therefore the druggable sites in these proteins.

40:25You know, that is accelerating medical discovery. There was actually a company called Schrodinger that was doing it pre-AI, but now there might be 20 times as many people and progressing much faster because AI is very, very well suited to this. And eventually, AI won't just model the low level what the shape is, but it'll model the cell and the organ and the organism. And so even complex disease dynamics, you know, it's beyond human understanding to map out all the different things that go on. The AI models, as you gather the data, which will be the limiting factor, will help you understand, you know, overnutrition, malnutrition way better than we do today.

41:17So, you know, most things put aside neurological in the next 10 to 20 years, I would say the likelihood of dramatic medical advances, even in the neurological one thing, Alzheimer's, I'd say those will be solved. And I love talking to these companies about, okay, which part of the problem they're solving. I mean, one of the things that strikes me is I feel like it's super fashionable today to be, oh, the world is terrible. The world's a dumpster fire. It's getting worse. The past 30 years have been horrible. The next 20 are horrible. And yet talking to you, I'm like, no, stop. If we actually look at the data, things have been getting better, especially in global health over the last 30 years.

42:00and often because of AI, the future is bright. There's so much that can happen. And you just sort of touched on not just sort of the technological progress, but also some of the sort of bureaucratic, some of the other things that perhaps AI or else can unlock. Are there things that AI can unlock that are just boring, administrative, or helping healthcare workers that aren't sort of about cutting edge technology, but are other ways that AI can help in the public health field? You know, in the same way that the microcomputer revolution allowed me at a young age to think, okay, computing will be free.

42:39Therefore, what would an individual do with free computing? And, you know, Paul Allen and I kind of saw that and said, okay, software is the only thing that will hold that back. Whereas older people kind of thought, ooh, computers are expensive. And so the idea of, oh, it'll be doing spreadsheets or word processor, they'd be like, are you kidding me? That's just too expensive. Here, it's even more mind-blowing that you could say white-collar worker capability. And eventually, although robotics is still very specialized, eventually horizontal blue-collar productivity will be very inexpensive. So I take an MRI diagnosis that a friend has.

43:24And, you know, ChatGPT does such a good job of explaining it, you know, and showing where it got that material. The creativity, the fluency is kind of mind blowing. And so all of us should have this crutch of, yes, if you just want to know what fertilizer is, Wikipedia was good. But if you want to know what a trip with a 16-year-old for four days with a budget of$4 ,000 to Italy in August looks like, nobody wrote that thing. But the AI, if it's connected up properly, it is mind-blowingly good at those things. So we're already all, you know, in our life of writing poems or speeches or understanding or having complex materials summarized, you know, we're already getting a huge benefit.

44:23And, you know, that, you know, a lot of white collar work, you know, should already be either more productive or, you know, drive towards higher quality. So actually, one of the things this conversation is reminding me of that I haven't actually ever asked you is, so, you know, there was this decade or so of a lot of focus on personalized medicine. Where are we at currently on that? Is that improving? Is the promise of that turning out at all? I always am put off by people's fascinations with N equals one medicines. You know, half a million kids die of malaria. You know, millions of people are diagnosed every year with Alzheimer's.

45:09So I'm just the impersonalized medicine guy. I'm like, you know, the world does not have the resources to do N equals one solutions. If some super rich person, you know, funds that, maybe it helps the scientific discovery path. But, you know, I couldn't bring myself to be involved with that because it's so unjust to take finite resources. Eventually, yes, understanding everyone's genetics and saying, okay, your drug dose is different because of this. And so, you know, I'm kind of taking a provocative position on this. The science that goes under that name is very good science. The people who work on that are very well intended.

45:57It's just, you know, we have rare diseases. We've created such an incentive for them versus widespread conditions. We're not really allocating that effectively, particularly, I mean, the insane stuff is the diseases of the poor countries. So can you actually say more about, you've traveled recently, Africa, Asia, all over, about the conditions with healthcare workers on the ground? What have you seen there and how can we help improve them? Well, people should understand that most people in sub-Saharan Africa never meet a doctor. Not when they're born, not when they're sick, not when they die. And so this is not a doctor's thing.

46:41So your image of healthcare, healthcare for most people in those countries is primary healthcare. A modestly trained person who can give you some antibiotics, bed net, vaccines, very, very importantly, to give a pregnant woman their prenatal checks. Now we'll get an ultrasound evaluation and we'll see, OK, which 10 percent of pregnancies might be complicated. And then the woman does need to get to somewhere where there's trained personnel who could do a C-section. So we can see with this AI-trained ultrasound, is it going to be a complicated pregnancy? And the predictions are stunningly accurate and go to all that trouble, which you couldn't afford to do for all pregnancies.

47:31And, you know, so the greatest shortage of doctors in the world is there. And so the idea that in native language through your smartphone, which, okay, not everybody has, but time's on our side, even in the poor countries on this, you will get health advice. And a lot of the diagnostic tools will be available at a point of care where individuals can take – a lot of people experience this with lateral flow COVID tests. Now we're trying to convert those to be point of care, but molecular tests and still super cheap, but also more sensitive, more accurate. And so healthcare is, you know, it's in a, we only have$100 per person per year versus in the US where we spend$15 ,000 per person per year.

48:27So it's, you know, it's 150 times different. And, you know, in fact, there is triage involved in, okay, which things should you treat? Now, even things like blood pressure, cholesterol, obesity, my hope is that not only are the cost of those treatments going down, we're also going to put them into forms where it's like yearly dosing. And so the cost in the delivery system of getting GLP-1 to all Africans, you know, 10, 15 years from now, you know, we'll be able to do that. So in addition to the elevation of humanity through all forms of kind of global medicine and what is actually, in fact, healthcare, education is another area that you and the foundation work on intensely.

49:24And, you know, obviously people have encountered AI a lot with this, you know, it's kind of like, you know, what does it mean? What are some of the kind of maybe more surprising or other kinds of use of AI in education, whether it's, you know, kind of a globally available tutors or other kinds of, what are some of the AI for education for the world that's kind of captured some of your attention? Well, I think the first thing to admit is that tech lovers like myself have talked about the benefit of technology being used in education for our whole career. And the actual benefit for the average student has been very, very modest.

50:07If you're a motivated student who can get on Khan Academy two hours a night or watch YouTube videos about photosynthesis, wow, people like ourselves, we are able to learn in a way that's unprecedented. There's a company called The Great Courses where when I'm on the treadmill, I love watching those things. Just so much great stuff out there. But the current math achievement of a high school graduate in the U.S. is not better than 100 years ago. It's not like medicine where there's new tools and new understanding. If I said, oh, in 1900, the best math teacher was then, you couldn't contradict me because it may be true.

50:54And so we've done a lot. And, you know, I'm a believer. But AI, because of the fluency and personalization, I think we can have very high aspirations of how we mix social experience in the classroom, experiences with the teacher, and working on your own, that correcting your pronunciation as you read things. Immediately telling you, no, you didn't get this math problem right. You know, not turning in homework so two days later after the poor teacher spent all this time, you're like, well, was that a manipulation error or was that a conceptual understanding error? The AI, and Con Amigo is on the cutting edge of this, but there's others like CK-12 Mini, that it'll say, yes, those two minuses, you didn't cancel those properly as opposed to, no, you set the problem up wrong because these two trains, you didn't get the when they pass each other algebraic equation properly.

52:00And so the idea that it will learn how a tutor keeps students motivated, using the domain like sports or health or construction that the student can relate to, the promise of having fantastic personal tutors in the inner city U.S. and in poor countries is super exciting. and talk about an area that's underfunded, global education is. And the magic formula for countries uplifting themselves is to have good health and good education and then their economy grows, their tax collection grows, and they're very self-sufficient. And that's why we want to help countries get out of the poverty trap, not because it's an endless guilt thing, but if we help them get there, not only morally, but economically, stability, many good things flow from those countries being well off.

53:01Global education is a very underdeveloped field, but particularly now with AI, I'm encouraging philanthropists to get in and showing that there are things like structured pedagogy where the teacher's given a very clear way of teaching that we are seeing some very good results. You know, I really appreciate, I think some people are like, oh, the boy who cried wolf. It's like, you told me 20 years ago that, you know, MOOCs were going to do it or that whatever. And so, you know, people are skeptical. It's like, are we, you know, are we finally there? Can you tell us more about the First Avenue Elementary School in Newark?

53:43And obviously, you're super concerned about equity. Is this something that is replicable that could scale? Well, so I love Khan Academy, but it was mostly used by motivated students. And so for the last, I think it's like eight years, they've been saying, okay, how do we get into the classroom? How do we work with the teachers, explain the stuff? You know, yes, the computers, the internet stuff is getting more pervasive. The pandemic actually helped a bit with that. So Saul and I were amongst the first two people who OpenAI was nice enough to let us mess around with early chat GPT-4. And a lot of the cool things like having it write songs and poems.

54:24Actually, Saul taught me that stuff. I was like, I wouldn't have known to ask. It can write like Shakespeare? Wow. And so he, you know, has put a lot of con resources in. He gets support from the Gates Foundation and many others, has created this Con Amigo. And last school year, he had it in a small number of schools, but including this Newark, New Jersey school. And so I went there to meet the teachers, to meet the students and see, you know, so you meet a kid who clearly is ahead of his class. and sort of the factory-based model of, you know, 30 kids in a classroom, you definitely have a problem where you need to do remediation and catch kids up, but you're also pained by that kid who's ahead, you know, and maybe checking out or being disruptive.

55:20And yet, you know, you think, wow, we want to drive that. So the personal tutor aspect allows that student to sometimes be off on his own, sometimes helping the other students. And this, you know, Khan dashboard along with Khan Amigo, which is seen, you know, so when you walk in and you're a teacher in the morning, instead of people handing in homework, you have to deal with it, you just go to your dashboard and say, okay, who connected in last night? How many hints did they need? How far did they get in the progression? and you're giving feedback, you can have the parents connected up to that.

55:59Even the thing where a paper gets turned in, you don't turn in the paper, you turn in the AI session. So you can just say to the AI, okay, how much did the student do? What's your suggestion on how we get them to either help with the first draft or help with the grammar or the logic? So it's great to see it being there and seeing it in person reminded me of embedding it in. And always with teachers, whenever you have some new thing, there's maybe 10 % of the teachers that latch on to it and you get these great results. And then when you tell the other 90%, you must use this, those results almost always just disappear.

56:43And so, okay, how do we make this one, one that scales, you know, so that humility of how far we haven't come is even with AI, we will have to do that. But what I saw made me even more optimistic. So one of the things that people sometimes miss about the approach that you and the foundation bring to these problems is, you know, not just quantification of like, okay, cost per life saved, et cetera, but also the systems thinking. And so what are some of the kind of non-tech related levers for change in education? Like what are some policy things that either we as Americans or, you know, the world should be thinking about to improve education?

57:30And there's a lot of very good data about not having cell phones in the school and, you know, some great work going on there. There's very good data about boys should probably start later than they do. School, school day should start later. There's all the learning out of the charter school movement, which it's hard stuff because it shows that long school day, long school year are incredibly beneficial. Engaging the parents in a, you know, here's where your kid's having challenge and communicating with them. Although these digital tools are going to make that far easier for the parents who want to engage in that.

58:11You know, we're seeing now in communities where there are charters, even though most of the kids are in the public schools, those public schools essentially compete. They either adopt those practices or find their own ways. So, you know, there are places like New Orleans or D.C. or Austin where school performance is up. And so we ought to make sure that even as we try to put AI into this, some of those learnings are incorporated. I mean, amen. As a mother of three boys, I'm like, how are they going to compete with the girls? What is happening? So to switch gears from education, I think I'm going to steal one of your own questions, which is if you had the opportunity to meet with someone from the year 2100, what would your questions be for them?

59:00Wow. How did you deal with the AI challenge opportunity? You said earlier that I have this view that life is improving, which is objectively true. There's always footnotes like nuclear weapons, bioterrorism, and now AI needs to be added to that list. But the past 50 years, life in general, if you're a woman, if you're gay. I mean, it's kind of sad in a way that because we're so problem-oriented, we're not very reflective about, hey, 5 million kids a year aren't dying. You know, like you meet with climate people and they say, oh no, climate's going to ruin the world. Do you think you're going to go back to 10 million a year dying?

59:46No way. You're not going to go back. It is a super big headwind because of the impacts through agricultural. So, you know, I bring my, hey, the world is pretty good, but that 2100 person, I hope to hear how they avoided, I'll call it the four footnotes, AI, nuclear weapons, bioterror weapons, and polarization. You know, people being able to get along and cooperate, including in how governance adapts, in which AI will force governance to come up with a different way of taxing people and regulating things. And it's a little scary that it's happening at a time when the broad trust in government is at a very low point, both relatively and absolutely.

1:00:39What are some of the things that you think people should anticipate coming with AI in the next three to five years? Well, it's so mind-blowing. Sometimes it's hard to get your head around it. No one expected the white-collar thing to come before the blue-collar thing. So in Life 3.0, they have these hills where the computers are doing the easy things. And, you know, warehouse work, which we can't yet do, was down there in the lowlands and helping diagnose, you know, was way up the hill or writing legal briefs or code. And so we're surprised at that order. But the so-called blue-collar horizontal robot that can be told, go to this construction site and help, go to this restaurant, go to this hotel and clean the rooms, even if the price is such that in the home it only drops by for an hour, doesn't live there at first.

1:01:38Those things are, I believe, easily within the next decade. Well, and actually going back to your original vision of a PC on every desk with software that would help people do their work and lives and so forth. What do you think is going to come now? I think a lot of people haven't realized that part of what's happening with current AI is essentially the largest programming language will be natural language, e.g. English. And everyone will have a coding assistant, not just the PC, but a coding assistant. What do you think, going back to those kind of earliest, how do you think that will transform the world?

1:02:17Well, the ability to navigate data, you know, which a long time ago you had to have some IT guy write a thing and, you know, okay, what's the header and footer and, you know, report. There's a thing called RPG, report generation language. You know, in COBOL you have this section in the picture. Anyway, you know, a lot of that stuff, it's so obsolete. It just makes you laugh. The idea you can sit down and engage in a dialogue about data in a very rich way means that, you know, our ability to run businesses better, you know, understand bottlenecks, adapt to changing things will be so incredible.

1:03:01And it won't require custom software. And in fact, the whole complexion of the software market, how many applications will there be? At first, what we have is everybody adding AI to every application and saying, okay, pay me extra because now I got a little AI. But in fact, the number of applications you need, think of a college which has a scheduling app, a finance app, support the student app. That should all be one thing, that every encounter with the student to the college is all maintained in a rich way. So the software applications will be very different. And I'm trying to figure out, okay, how quickly does that happen?

1:03:47It's incredibly beneficial that this software is more adapting to you, including creating user interfaces dynamically, than you going, okay, I use this software package for this, and then I go to this website and do this. You're a low-level clerk. Even looking at your email, the email is so stupid that you have to figure it out. It only can time sort the order. It doesn't know what's important. And then you have your messages, and you have to go back and forth, and you're the one who puts it in little folders and things. I thought the semantic level of interaction with the computer would be higher by now, even without AI.

1:04:24But now with AI, the idea that the very high-level tasks that I'm doing, I'm working on my budget, I'm considering buying a new home, that it will be working with you not at the spreadsheet cell level but at the, oh, let's break this task down in a high-level form. Here's what I can automatically go in and do for you. It's super revolutionary. You know, we'll all have an agent that is a utilitarian, help you get things done. You know, it reads everything you read, but the things you meant to read, it reads. And then, you know, your agent can figure out, okay, which parts of that are important enough to take your time to understand.

1:05:19We are now switching to rapid fire. I'll let Reid ask the first question. Is there a movie, song, or book that fills you with optimism for the future? Well, the betters angels of our nature, Stephen Pinker, sort of documents how violent death, you know, lifespan, education have gone. and, you know, there's some lessons of why we've done well. It doesn't guarantee, and he doesn't say, that's the future. But, you know, if you have one book which should get you back into the mindset of, okay, how far have we come? What should we feel good about? I'd recommend that one. Fabulous. And what is a question that you wish people asked you more often?

1:06:04How does malnutrition work? You know, a lot of things I think about are boring and we should solve without most people having to ever figure out toilets and nuclear reactors. And, you know, understanding disease, I'm surprised people aren't more curious. You know, when I first said, what do kids die of? I had a hard time finding out. And I would have thought, well, shouldn't we all be asking that kind of thing? It's more important than GDP. Exactly. I love it. So where do you see progress or momentum outside of your industry? And of course, that's very broad. That inspires you. Well, when India is an example of a country where, oh, there's plenty of things that are difficult there, the health, nutrition, education is improving.

1:06:59And they're stable enough and generating their own government revenue enough that it's very likely that 20 years from now, people will be dramatically better off. And it's kind of a laboratory to try things that then, once you prove them out in India, you can take to other places. And so our biggest non-U.S. office for the foundation is in India, and the most number of pilot rollout things we're doing anywhere in the world are with partners in India. You know, if you go there and you've never been, you might think, whoa, this is a chaotic place. And, you know, you're not used to so many levels of income all being on the street at the same time, but you will get a sense of the vibrancy.

1:07:46All right. Last question. Can you leave us with a final thought about what is possible to achieve if everything breaks our way in the next 15 years? And what's the first step to get there? The potential positive path is so good that it will force us to rethink how should we use our time? You know, you can almost call it a new religion or a new philosophy of, okay, how do we stay connected with each other, not addicted to these things that will make video games look like nothing in terms of the attractiveness of spending time on them. So it's fascinating that we will, the issues of disease and enough food, of climate, if things go well, those will largely become solved problems.

1:08:37And so the next generation does get to say, okay, given that some things that were massively in shortage are now not, how do we take advantage of that? Do we ban AI being used in certain endeavors so that humans get some, you know, like you don't want robots playing baseball probably because they'll be too good. So we'll keep them off the field. Okay, how broadly would you go with that? We are so used to this shortage world that I hope I get to see how we start to rethink these deep meaning questions. Bill, a tour de force. Thank you. Yeah, great talking to you.

1:09:33Possible is produced by Wonder Media Network. It's hosted by Ari Finger and me, Reid Hoffman. Our showrunner is Sean Young. Possible is produced by Katie Sanders, Edie Allard, Sarah Schleid, Adrienne Bain, and Paloma Moreno-Gimenez. Jenny Kaplan is our executive producer and editor. Special thanks to Soria Yalamanchili, Sayida Sapieva, Ian Ellis, Greg Beato, Parth Patil, and Ben Rallis. And a big thanks to Aubrey Bogdanovich, Ian Saunders, Christy Anthony, Alex Reed, Jen Krajasek, David Sanger, Larry Cohen, Alicia Salmond, Sean Simons, Denali Weiraman, Andrea Dramer, John Ryder, the whole team at Gates Ventures and Little Monster Media Company.