This Week in Startups - Reid Hoffman on AI's "crescendo moment," regulation and real-world applications | E1739

Episode Date: May 10, 2023

Reid Hoffman joins Jason to discuss AI's current "crescendo moment," and its ability to amplify human capabilities (1:50). Then, they discuss AI regulation, real-world use cases, and much more! (25:55) (0:00) Reid Hoffman joins Jason (1:50) AI’s “crescendo moment,” (12:48) Release - Get your first month free at https://release.com/twist (14:20) AI's ability to amplify human capability  (24:21) Microsoft for Startups Founders Hub - Apply in 5 minutes for six figures in discounts at http://aka.ms/thisweekinstartups (25:55) Regulating AI  (35:35) Veed - Head to https://www.veed.io/pricing?utm_campaign=TWIS&utm_medium=Marketing&utm_source=YouTube and start creating professional-quality videos in minutes! (36:45) The future of AI startups and Inflection AI's mission (44:01) AI's real-world applications  (48:20) Compensating creators and real-world uses for AI (57:27) Google's ability to compete in the AI race  FOLLOW Reid: https://twitter.com/reidhoffman FOLLOW Jason: https://linktr.ee/calacanis Subscribe to our YouTube to watch all full episodes: https://www.youtube.com/channel/UCkkhmBWfS7pILYIk0izkc3A?sub_confirmation=1 FOUNDERS! Subscribe to the Founder University podcast: https://podcasts.apple.com/au/podcast/founder-university/id1648407190

I believe we will have a personal assistant for any professional informational task, which is professional task. I process information. You do something with you. You make an investment decision. Write a memo, write a prescription, something like that. Two to five years for every professional activity. Now, what the adoption will look like, will it be useful to essential?

There's a variety of things. But as an amplifier, as amplification intelligence versus artificial intelligence, it is off the charts amazing. This weekend startups is brought to you by Release. Large enterprises pose unique challenges for SaaS startups. Unlock customers with unique needs for private and single-tenant hosting without the toil of DIY with release delivery. Get your first month free at release.com slash twist. The Microsoft for Startups Founders Hub helps all founders build a better startup at a lower cost from day one.

Startups get up to $150,000 in Azure credits, access to free OpenAI credits, free dev tools like GitHub, technical advisory, access to mentors and experts, and so much more. There is no funding requirement and it only takes minutes to join. Sign up today at a.k.m.s slash this week in startups. And Veed makes it super easy for anyone, yes, you, to create great video. filled with amazing features like templates, auto subtitles, text formatting, auto resizing, a full suite of AI tools, and much more. Veed gives you the tools to engage your audience on any platform. Head to Veed.io to start creating incredible video content in minutes. I'll just say to everybody, it's just great to have Reed Hoffman back on the program.

You know, Reed as one of the founding members of PayPal, co-founder and CEO of LinkedIn, which is just become a juggernaut. 875 million members, almost a billion now. And he's a partner at Greylock, board member at Microsoft, and now the co-founder of Infliction AI. So it's just great to have you back on the program. The last time you were on, God, I'm trying to remember. I came to see you at LinkedIn when I was just starting this program. Exactly. And we just talked about life and all that kind of stuff. So, God, there's so much to talk about. Just when I say LinkedIn, and you look back on what you built there, and I say 875 million members and going to a billion, it's just quite extraordinary. Is it not the staying power of LinkedIn? What do you attribute

it to, just the network effect? Well, so by the way, one of the great things about doing this interview today is May 5th, it's the 20th anniversary of the LinkedIn public launch. We are doing this discussion on that. So, you know, that's a cool little milestone in, you know, my life and the world life, you know, world history. I think a lot of the, you know, LinkedIn is a turtle that made it. And, you know, it's, it's partially because it stayed really true to a mission. It's like, this is the role we plan people's lives. This is the thing we do. We're about, you know, time efficiency and time saving, not time spending. Or about amplifying what you're doing in your, you know, job search or your career or your work or information about that.

We're not doing anything else. We just keep going at it. Even when in the very earliest days, you know, launching, you know, you'll remember this because we're both old men of the internet. It's true. The, you know, May 5th, 2003, when we launched, the hot thing was Friendster. Yes. And literally, the only way that I could get journalists to talk about us was to talk about us as friendster but for business, which is totally nonsensical. It's like there is no Friendster but for business.

It's like saying, you know, like pizza, but for driving your car. You're like, no. Okay. Not enough. Sure. It is just a. also how they've just kept the feature build going, like the, if you want to advertise or if you want to hire people, it just works amazing. And I have been playing with chat GPT4 and plugins.

And I don't know about you. But if you were to look at how exciting this is for two old men of the internet, a hundred years, I think old between the two of us here. We remember dial-up. We remember PC on everybody's desk, office, windows, the GUI, cloud, mobile, and broadband. 300 bod. Like, most people don't have any idea what we're talking about. My first modem was a Ventil, 300, 300, then I got the Hays 1,200 and 2400. Man, those were upgrades. Yes, exactly.

But when you look at what has happened in the last, call it 90 days, with chat GPT for plugins, auto GPD. how does this compare in your mind the tingly feeling you probably got when you got your first PC or used the first Windows interface or used a mobile phone, iPhone, or cloud computing or broadband even?

How does this compare to you? I think it's the crescendo moment. When I say this is bigger than the internet or bigger than mobile or bigger than cloud, it's because it's building on all of them. It's the tsunami that you're surfing at the top of it. And it's very similar to, but I think your lens is correct.

Because the first time you were playing with a, you know, a PC was like, oh my God. Like there's all these things this can do. And you just kind of like, like your very first Metaverse was playing with the PC. It's like you were kind of virtually transported in this thing. And I think AI, the current scale compute, because it's really a kind of application of scale compute, which given its cognitive functions is a good thing to call it, you know, artificial intelligence. but it's really like this kind of scale compute discovering things that we had never we'd never gotten anything even close to this before and the way that it's kind of human

amplification is you know just kind of super interesting and so you know so that that that aha moment like I remember when I was playing with GPD4 last year July and August that was on the board of open AI and I started like doing prompts and questions and I was like oh this is good. This is amazing. Right. You know, and it's not to say you don't worry about the concerns and, you know, human amplification. You also, I think all the risks stuff should really be human implication of bad actors, like what happens with bad actors using it. We can get to that as as relevant. But it's like, oh my gosh, now there's superpowers. Like I have superpowers where I can create an image where I couldn't create an image before. I have superpowers where I can say,

I would like to create an epic poem about Jason. and, you know, his quest to make, you know, poker the relevant lens into thinking about investing. And like, make that an epic poem. And I can do it now. Right. Because it's like the superpower, which is really amazing. Anyway, so it is the most significant moment of technology in our lives so far. And maybe in our lives on the whole story. Our lifetimes. I mean, I, I am exactly where you are. I can't stop playing with this stuff. I can't stop talking to people about it.

I had Brian Chesky on on Wednesday. He's just totally all in. And he's rethinking the entire conception of Airbnb. I had Aaron from Box on. He's just turned the entire company around and pivoted towards that. And then here you and I are talking about it in the same light, which is this isn't a drill. I gave everybody on the company, my investment company, Chechipty before, had a I'll sign up for it. About five of the 20 in the last, call it 60 days, have started taking

large swaths of work and offloading it and getting phenomenal results in a technology that's crashing constantly. The plugins don't work. The web page surfing doesn't work. It's got all those clunky kind of things at it. So let me ask you this just because it's fun to have the crystal wall. For white collar workers this year, and again, it's not a scare tactic. It's just pragmatic. what percentage of work that you and I do as investors and entrepreneurs, communicators, and just people on our teams, if they dedicate themselves to this, what percentage of their workload could be offloaded to chat GPT4 in 2023? It spends a little bit on the job. Yes. And, you know, because like, for example, if your report writing or your, you know, notes minute taking, then the answer is probably in the 50 to 80 percent.

you know, although by the way, you may still be doing it. You just mean now be doing it a lot better within that time frame. Like what used to take you three hours to do now will take you 15 minutes and you may still say, well, I'm going to take another hour and make it a lot better. Put a little polish on it, right. Exactly. You know, Amplified add some creativity, put some questions in, other kinds of things. You know, in our venture business, I think very little.

You know, it's not to say that it's very little later. but very little 2023. And it's partially because, like, if you look at GPD4, what it is a stunning superpower on, it's like a research assistant that instantly delivers a synthetic, kind of a synthesis in summary result about a prompt that, you know, kind of in your pocket. Now, obviously, it's creative and it can generate a Star Trek episode

and do other kinds of things as ways of doing it. And then that's all, so it's not just like a report, but it really takes all this stuff and kind of creates a synthesis of it. Now, one of the weird things about what we do in venture is we are looking for that needle in a haystack. We're looking for the extraordinarily different things. So you say, well, say I was investing in a new area, which I don't really do, and I was going and go, oh, now I'm going to start investing in MRNA application companies. Then actually, by the way, using it as a researchist as it could be used to like, well, what are the key issues that I should look at when I'm looking at this company? You got like the world smartest assistant associates it next to you, catching you up.

Right. Going right now right away. Now, of course, there's some hallucination, so you have to pay some attention to it and occasionally, but it's immediate and right there. And so that's really helpful. But of course, if I was turning to do like MRNA kind of drug discovery investment, then I would have to go to your guys podcast and all in. Because like casually is a dumb way to be doing investing. And so it would help kind of get into it. But once you had expertise, like one of the questions I asked, GPD4 last August when I was playing with this because I was like, okay, you know, how much is this job replacement on stuff? All right. Well, how would Reed Hoffman make money by investing in artificial intelligence was my prompt? And it gave what was like kind of I'd call it an MBA professors, you know, business school professors analysis that doesn't really, it was very smart person, but doesn't really understand venture capital. So it was like, right, well, you would look at the areas

that had the largest TAMs and you would look at which products and services had the greatest substitution or alternative impact because of this AI technology, then you would go find teams that were capable of addressing that, and then you would invest in those teams, and that's what you would do. And you're like, well, that makes total coherent sense. It's a coherent pitch, and that's not what we do. Exactly. It's like telling Tarantino how to make a movie. It's like, yes, you do need a camera. You need film and you do edit it. Yes. Thank you. Yes. Exactly. Thank you.

Whereas what we do is we look for the really kind of stunningly bold idea from an entrepreneur that says, look, I recognize this new chance of going to market, this new kind of product, maybe it's a replacement. The fact that it happens to be a large tam or not now isn't really the relevant question. The relevant question is what future tam's look like. Could you reduce a market? Yes. So there's all this stuff about the way we look at it.

Yes. That is not that. And so you're like, okay, great. You know, not yet. not a useful tool. It will be, I believe, we will have a personal assistant for any professional informational task,

which is professional task. I process information. You do something with you. You make an investment decision. Write a memo, write a prescription, something like that. Two to five years for every professional activity. Now, what the adoption will look like,

will it be useful to essential? There's a variety of things. But as an amplifier, as amplification intelligence versus artificial intelligence, Yeah. It is off the charts amazing. And that's part of the reason why, you know, as you know, I published a book with it, you know, six weeks ago or something.

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What a domain name. R-E-L-E-A-S-E-E-A-S-E-E-D-com slash twist. It's up to $10,000 in value at release. com slash twist. I think the human augmentation, right, this amplification, this becoming a mutant, becoming the 10-X developer, that's here right now. I mean, it just feels like all of a sudden you can fly. And it's like, oh, wow, I thought only Superman could fly.

And it's like, no, no, all members of Justice League can now fly. And as, but one example of that, have you seen the code interpreter that they launched over the weekend and played with that yet? No, I haven't. So code interpreter lets you open a CSV file. You use the code interpreter. I just started taking random CSV files I found on, like, public information websites. One of them was like number of electric vehicles on hybrids, you know, VIN numbers, whatever, it's on some public thing. and I said, tell me about this.

And it was like, or tell me trends about it. Give me some charts. And it just starts spewing out charts. And I'm like, okay, that's a data scientist job. And I gave a speaking of the other day. And there was a data scientist there who did the data science for this 100-person hospitality company. And I showed him this live on stage at their offsite.

And he said, that's about half of what I do all day is these requests. And I said, guess what? Now you don't have to do the requests you're getting. People can do them themselves and then come to you for the more sophisticated. one, he said, oh my God, thank you, because I'm like a month behind on getting people this basic stuff. So everybody is going to be able to be a data scientist. Now, not to his level. Maybe they're 60%. But boy, does that change everything? Yes. And by the way, it helps him be a lot better, too. Because as he refines on the, okay, what questions you really ask, what data

should you really look at? How do you look at this data the right way? All of those kinds of questions, it makes us all better, it improves our capabilities. Yeah, it is truly fascinating. I guess everybody wants to talk about the downside of it. So I think we should hit that right now real quick, because what the consensus with smart people I've been talking to is this is augmenting everybody, making everybody more efficient, and we got a hell of a product roadmap.

So what Aaron Levy said today is, yeah, this is going to make everybody 30%. That was his number. Brian Chesky picked the same number. I had picked the same number. picked 30, Brian said 30 or 40, and Aaron said 20 to 30. So you're like, okay, and you said something similar, depending on the job, it could be 50, could be 80, or maybe you go back and put another hour into it. Everybody who is in the industry understands, this is going to just make us get through the backlog of product roadmap, customer service, whatever the issues

in your organization are. You're just going to move 30% faster a year, which means compounding, everybody's going to be twice as efficient every two or three years, maybe you could speak to what would be your most charitable, hey, don't worry about the AI. It's going to just make us all amazingly better at our jobs and there's so many more problems us off. And then maybe you could steal them on the other side, which is, hey, maybe we've got to think this through

because I know that Biden had some people over today at the White House to talk about this. Yeah, I think it was yesterday. Was it yesterday? Yeah, it was yesterday. And so, let's see. I'm fundamentally a believer that this will be really great. for the vast majority of people.

And even to say, look, in the case where you say, you know, okay, customer service, cost center, well, actually, in fact, hit a bunch of jobs. Even in that, you say, well, but you can make AI to give skills, upskill, retrain, other kinds of things. You know, like, you know, well, maybe I can join sales or maybe I can do other things as kind of ways of doing this. And that is part of, I think, the reason why I'm ultimately bullish.

And I think the positive of it, it is an amplifier to human capability, just like you'd say, you know, every smartphone has a medical assistant, has a tutor for everything, you know, has a, you know, kind of a personal, you know, AI assistant for, you know, whatever problem you're trying to navigate and kind of help you with it. And I think that's, you know, that's enormously, you know, kind of, you know, kind of amplifying. Like you could even like say, well, I was driving. somewhere and my car kind of broke down and I can ask the personally eye about it going, okay, these are what I see the symptoms of, you know, what should I do? Right. Like what's going on? Hugely, hugely beneficial across all of these angles. And that's the positive. And a little bit of the reason I was in it is like, look, you know, like you said,

well, 50% of the work of my job goes away. It's like, well, not necessarily as much as the really bad parts. And then you can amplify it to getting a higher standard and what you're doing. and that's really good. Well, and what's really interesting about what you said there, I just want to amplify two things. One, you're getting rid of your chores, the things that are the most arduous,

which then you're going to find, as a human, more creative things to do. If you're doing customer support, well, maybe you're doing customer training. Maybe you're doing customer success now. You moved up from just telling people how to log in, reset their password.

The second thing you said, though, was actually the first person I've heard say this, well, if this is this good to replace your job or a large portion of it, it's good enough to retrain you for another job. Exactly. That's actually a very important insight. I think that people, you're the first person I've heard to actually say that.

Yeah. No, exactly. Because it's like, we can make it part of the solution. So then when you get to the downsides, you go look, the, I think the two most obvious downsides are it's transition. And the majority of human beings don't like transition. They like feeling comfortable where they are. Yeah.

You know, that's going to be anxiety producing, you know, concerning because it might be the in transitions, it's like, well, we laid off those five people. And so you're one of those five people. It's like, oh, that's hard. That's difficult. And so, you know, like we as a society,

government society, companies, tech companies and need to help with these transitions a lot. That's part of the reason why I've been thinking about that and tutors and reschedule it, you know, matching and giving you career advice and all the rest of the stuff. The second thing is, you know, these tools are superpowers. And part of the superpowers is you put, you know, superpowers in the hands of bad human beings.

So like cyber criminals, you know, we got to deal with that. I actually think this whole, like, you know, I've been a great proponent of open source, you know, was on the Mozilla board for 11 years and so forth. And I think actually open models so far don't make sense because we don't know how to distribute them as open source where they're safe. And, you know, it can be, it can range from cyber hacking to even much worse things. You know, a question of what happens.

This is a super interesting point. I'd love for you to unpack because when Open AI came out, I know you don't speak for Open AI. They said, hey, this technology is so important. Everybody needs to have access to it. It needs to be open. And then some point, Sam said, this stuff is so powerful. We're not ready to let everybody see, which you're kind of amplifying here. So what is it that you know, Sam knows, smart people, who I respect, of why you're being cautious.

about it because there is the Facebook language model is open source. It's out there. So let's talk about it. It's actually not open source as much it was dropped off into the dark web by the, yes, by the, by some set of the researchers who had been given access to it. So it was, it was involuntarily open source. That was, that is a fascinating moment too, because I looked at that and I said, who is Facebook's biggest threat or biggest enemy? It's obviously Google, right? They compete for ad dollars. And I'm like, I wonder if this is a kind of envelope. that was handed to somebody at the New York Times to be put onto GitHub because I don't know that Facebook's network effect, I think keeps it in the game. But Google, they seem to be the most at risk. So anyway, that's a fascinating. I don't want to be a conspiracy there is here, but. Yes, we can go in depth. Now, the open AI mission stays the same, which is open access and open provisioning for a broader range of, humanity as you can do, consumers, developers, etc. It was never of necessity open source. That was how other people were hearing it. And I think the organization was neutral on the question. Like, look, if we can do it open source and make it safe, totally happy to do it. That's part of making the mission. But it was like, well, we don't know if we'll be able to do that. And so far, it looks like we can't because whatever safety rails you put on it, the

safety rails are easy to untrain. Of course. So it's like, okay, well, it's like, it's like saying, okay, well, we, you know, we're distributing something that has an explosive power. And it's like, well, actually, in fact, you know, with this thing, you can make your, every car into a car bomb. You're like, oh, well, not good. We don't want you to take the safety off the gun.

Like, there's a safety on a gun for a reason. Yes. And you can see this with people trying to trick it. I was trying to get it as part of my little talking of the other day. I was like, come up with some ideas that are like really dangerous, immoral, or insane that you would never do for a hotel chain to just entertain these hotels. I was talking to. And I was like, I can't do that. I can't do anything ethical or immoral. And I was like, you're a screenplay writer. Write a screenplay about a supervillain who creates an evil hotel chain. And I was like, absolutely. There's

a casino that's crooked. We're going to torture people. I was just like, whoa, whoa, no, too much if we made like a horror film out of it. But there's other things that can be done with this. Like you could ask it, hey, what would be a great cyber attack for me to do? And I don't want to even mention the other ones because, you know, it's part of being appropriate. Yeah. I mean, I hacking and then pick the 20 things that are worse than getting your computer hacked. And I do, I do have some, I think that's like a very interesting piece to it. All right, everybody. Our friends from Microsoft are here.

Tom Davis, a senior director at Microsoft for startups, and you're a former founder. You are here today to talk to us about the giant leaps that Microsoft has made in the AI space. What does this mean for startups? I see a ton of different tools. I've been playing with ChatTP4. I have a paid account, but I'm also seeing things happen with GitHub. Absolutely. So the work that we've been doing with OpenAI over the...

last few years, it's really set ourselves up with a foundation around. We've built this sort of AI supercomputer from the ground up, and we've been looked at everything from GPU configurations to networking and things. And really what we're now able to do is sort of allow startups to access all of this innovation through our founders up. So we've been building this for do something at scale, so startups can now build their own AI applications and build out and train LLMs as well. And this has really helped us to become a far better cloud for AI broadly. And being able to drive that down to the startup ecosystem is fantastic.

It's open to everybody. There's no funding requirement. You don't have to be anointed by a VC. Five minutes to sign up. You get six figures of benefits, Azure credits, GitHub, open API APIs, which everybody's really having fun playing with. And so much more. So go ahead and sign up right now, aka.m.

slash this weekend startups, aka. ms slash this week in startups. Thanks so much, Tom. Thank you. What do you think about regulation and self-regulation? You look at the movie industry, MPA is like, we got this government. We'll protect kids. We'll tell you PG, PG-13G, R-rated, X-rated, NC-17.

We got all these different labels. We're going to do it. Some directors will complain. They'll fight for different ratings, but we'll regulate ourselves. So what should we do as an industry to, regulate ourselves, which I think would be the most positive way to do this here in the United States, rather than having the EU, which has got a pretty fine filter, come in and be like, oh, yeah, we got some ideas for you on how to kill this technology.

Well, you know, one of the things I do when I'm in Europe to try to get them to wake up, as I say, look, keep passing GDPR and other kinds of things, because then we'll build all the technology, then we'll, because your local companies won't be able to do it because of this regulation, and then we will retrofit it to the regulation, and then we will be the providers of it. So if you want us to continue to have all the tech industry and this stuff, just keep on your current path. It's great for us. And I don't say that because I want them to do that.

I actually want them to think, actually, in fact, it would be great to have a healthy, vibrant European tech industry where, you know, some set of different kinds of cultural norms and values, you know, very good ones based within Western democracies, would also be present and present in the marketplace of products and ideas and other kinds of things, that would be good to do. But it doesn't do, it doesn't, by saying, you know, you're not allowed to take risk, you have to ask for permission first, you have all these impediments for trying risks and so forth. You know, obviously some impediments for trying risks is good. But like, you know, like the, hey, if we don't really know if it would be okay or a little bad, then fine, give it a shot. as opposed to, look, when we know it's going to be bad or it has a risk of being very bad, no, okay, then we should be more controlling.

And so I think, look, I think the MPA is the thing I've been kind of advocating for for, you know, decade on the tech stuff is to say, hey, and, you know, part of the challenge is how do we get together in a way that's not, you know, anti-competitive, you know, we need some, you know, kind of clearance from the government is like, look, this kind of coordination on these issues is not anti-competition, but actually, in fact, pro-health. and society on these things. I think that part of the question is to say, you know, our future is actually much safer and much better.

Like, you know, when you look at, you know, kind of open AI training GPD2, 3, 3.3.3.4, you know, etc. Actually, in fact, it gets alignment better, it has better safety training on that stuff. As we're getting to the future, the future is better. So actually, in fact, keeping pace and going towards the future, actually in fact we have more tools and more ability to do like advanced safety things there.

Like I think it's part of it. I also think that, you know, like the classic thing is people say, well, I'm worried you're worried about the jobs. And you're like, well, but the only way you can prepare for that is by getting into it. You can't prepare for what the steam engine or the automobile does for industry other than getting into it. Yeah. And so you want to ask the questions. You want to help with the transitions and all the rest of those parts of doing it. but like this is an illusion of saying,

well, then we'll just sit down and we'll, and we'll study it and we'll know what it is. You're like, that doesn't work. No, you can read science fiction. Just go watch Blade Runner.

You get an idea of where this is going. You know, and like, you got to use it. Yeah. And by the way, we can steer away from the things that you think are bad in Blade Runner as we're going

and as we're learning what the things are. And so you have to have a predisposition to act, experiment, and then kind of modify. And so, you know, there is obviously, a certain amount self-regulation that comes in these companies that have employees that

care about things that have long-term interests of customers and share prices and market positions and brand that they actually care about. And there's a lot of, you know, kind of, you know, things where they're careful about risks because they don't want to have, you know, those things come back and make big things. That doesn't cover everything. That's, you know, that's not and so therefore I think that some coordination is good. I think, and I think the biggest question that we actually really need, if you look at right now what the risk are with AI, it's like, okay, there's already just a ton of these open source models are out there that are pretty powerful. Yeah.

And that's, that's already there. And so the question is, is how do we play forward from that? And what is, what does safety and transition look like? And what people are, I think, are most worried about his jobs, but then they get wrapped up in, like, you know, people beating the existential drum risk or, you know, which, you know, it's like, okay, there's a lot of bad reasoning about that. And it doesn't mean, can you say there's zero percent chance of existential risk? I'm like, well, no, I can't say there's zero percent.

I can't say there's zero percent on asteroids either or on nuclear weapons or on natural biology or on man-made biology. There's a whole stack of things I can't say there's zero percent on. Yeah. But I actually can tell you there's a whole bunch of controls that make it extremely unlikely. Yeah. And so navigating those controls is a good thing. And you do that by proceeding. And I think the nuclear example is, you know, it's different.

Obviously, none of these analogies are going to be perfect because you have materials that we then, once we realized, hey, Manhattan Project, we got the bomb first, a lot better than certain other people getting the bomb first. I can tell you that, because they would have used it slightly differently. It was an imperative for us to get that bomb first. Now, it's horrific that we dropped two of them on Japan, obviously, and this is one of the worst scenarios you could ever imagine. But since that time, the regulation, and by the way, people debate that whether the war would have ended and which would have been a more compassionate thing. That's, I think, above both of our pay grades. But they did get control of the material. They did get the world to say, you know, we need to get around a table here and discuss this. How many of these should we have? Which country should be allowed to have these? And once we got to eight, nine, 10 countries. It was like, you know what? No mas. Nobody else needs to have these. We're going to take a pause here. And that feels like I think we're getting to very quickly with this, which is some of the models require a lot of hardware. And hardware is to me in some ways, perhaps you tell me if I'm right or wrong here, could be, maybe you need to have a license. You have to know your

customer when you're taking money over borders. Maybe you want to have one of these Nvidia 100s. like, yeah, maybe you need to be registered, have insurance. If you want to buy certain guns, you got to get licensed. So what's practical here? I think we have the framework of like, yeah, we got to move forward. But have you heard any practical suggestions of who should take some of the responsibility? Should it be Azure or AWS or Google when they put this out there and they say, hey, listen, if you want access to this, here's a code of ethics, here's a code of behavior, here's the terms of service, and you need to have insurance, you need to have a driver's license, just to even have access to this, or is it just going to be a free-for-all?

I think the kind of hardware and compute centers is a very good thing. We obviously have to figure out how to do this in an international basis, not just kind of U.S. unilateral. I think that the question around, you know, when large-scale compute is being deployed on this stuff is one of the areas where some, you know, kind of collaboration is potentially very useful on this. Once again, it's kind of like, okay, well, I could see how to do it right now, because, the largest scale compute is Microsoft and Google, you know, together with, you know, their various, you know, allies and adjacents, you know, like Open AI and whatnot. But, you know, I think part of the thing is that will obviously, that's end years before other chips are created, not just the Nvidia chips, TPUs, you know, large-scale compute centers

are stood up in various places and so forth. And so kind of getting into all that, I think, is a kind of a really useful thing. Unfortunately, I think the parallel is a little bit more, biology than it is nuclear because it's kind of hard to like right now it's pretty easy 10 years from now it's pretty hard it's like well you know like to that kind of scale compute how do you actually in fact really know what's going on if you have a you know kind of a bad state actor that's kind of set up a big data center in some way more's law makes it so this stuff runs on old iPhones in a cluster you know like yeah so we have to figure that out of as we go. I don't think we are without tools on it. And it's kind of like the equivalent of,

you know, well, did we ever thought we could get a rocket that could actually get us, you know, launch something to the moon? You know, no, but we figured out as we go. And so, you know, I think that's the thing. And I think one of the good things about all the discourse is, like all of the people that I'm associated with who are building the stuff, are intensely focused on not just the great opportunities, but also navigating risk. And I myself have participated in a number of off-sites, sometimes where we have to have lawyers present to make sure that, you know, it's like there's no antitrust thing going on here. Really? Right.

It's just, hey, how do we make this stuff safe? Can we share safety concerns and safety test harnesses and, you know, which things should we be looking for in order to make that work? And how does that, you know, which places, you know, and will compete in products and markets and prices and all the rest of them. we're not going to talk about any of that stuff here. We'll talk about the stuff that we can do to make sure we mitigate downsides. And I think that's super important to do. Okay, listen, I'm doing six video podcasts a week, and I can tell you dealing with video is 10 times more expensive and time consuming than audio, especially if you're trying to turn video content into social clips. But video is an incredibly powerful way to get your message across.

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lets you do it all. Head to VED.I.O to start creating professional quality videos in just minutes. That's VEED.I.O to sign up today. I have been meeting with a lot of founders. Everybody's incorporating this. I've had no less than a half dozen instances where companies that were pursuing an AI strategy using chat chippy teeth came to me and said, uh, at the pace open AI is going. I think we, uh, don't need to exist. We need to pivot. And I said, well, you know, they're not going to create like the most vertical applications in the world. There are the roadway, uh, which is how Brian Chesky said it to me. It's like, you know, there's going to be like multiple highways here. You can take her car on

multiple highways and the experience of the consumer is in the car, the bus, whatever. And the highway is the infrastructure. I'm curious in how you're seeing this come together. You started inflection AI, and I guess you co-founded that and your venture firm is in, and you were at OpenAI. You came off the board, I understand, because this is going to be conflict city, makes total sense, if I'm correct there. How is, is chat GPT just going to run the table, this for-profit slash non-profit slash hybrid kind of situation? Are they just going to run the table on every startup and be the ultimate vertical of everything, or is there going to be room and they're not ambitious enough to say, you know what, we're just going to build the everything app. We're going to build,

you know, Elon's X.com and do everything. How do you think about that as an investor? And then we'll talk a little bit about what you're doing with inflection. And does inflection worry about that? So I think, look, Open AI is definitely an 800-pound gorilla. Awesome. They have a great mission, a great team, a bunch of other things. They're going to be providing APIs across a number of things. So, you know, those APIs then create kind of an open access to a whole bunch of developers and a whole bunch of consumers and a variety of tech. Then other companies that might want to be a monopolist in that area can't do it. So I think that's all super awesome. But they're one company of about 450 people.

They have a nonprofit primary research agenda on beneficial artificial intelligence and AGI specifically to do this. And they're not in, they're not trying to. to create a whole bunch of business stuff. Matter of fact, part of the arrangement that they have with Microsoft is when you get to like, well, we're provisioning enterprises and so forth. You know, Microsoft's doing a lot more of that. And Microsoft's not exclusive in the open AI stuff, but just they're, you know, kind of building it out, putting it on Azure, you know, these kinds of things.

So I think that there will be a major set of things. And if you're a theory of the game is, I am going to directly compete with Open AI, you'd better have a good theory of the case, just a little bit like if you say, well, I'm going to launch a desktop search engine, you better have a good theory of the case. It's not impossible to do. It's a challenging Everest mountain, better come equipped, have a good competitive theory, good risk theory, a good reason why you're doing something that they won't be doing. But by the way, among them, you already shadowed, which is there's a ton of stuff that businesses need,

that human beings need, that open AI is not going to do directly. And even the Open AI BPIs, even if they go, they're helpful for it, well, we take a whole bunch of work in order to get there. So, for example, you know, I have two portfolio companies that are doing great work here, a Coda, which is kind of like, how do you kind of power meetings and work? I love Cota, yeah. And, you know, they've got a whole bunch of super cool open AI, AI integrations. Tome, which is doing slideshows, you know, kind of does both images and text on this stuff,

has a whole bunch of, you know, interesting integrations here. And look, if you're saying, I'm just building a thin front end. Like, I'm going to do a blog posting thing. And it's just going to be a thin front end. And it's like, well, then you better have a theory of the game because they're going to keep advancing the thing. And you'd better think, okay, I'm going to keep advancing with them or whatever your theory is.

So you have to build something substantive. So I think there's tons of applications. I also think, you know, for example, what we're doing with inflection, which if you look at kind of chat chvety, it's oriented at like kind of, more of equivalent of a kind of a search engine. Like, here's a list answer to every question. It's an instant Wikipedia like answer. Great.

Well, but there's a lot of stuff in human experience and navigation that goes, like, use this example. You say, well, you go, a friend's pet, you know, beloved pet just died. How should I comfort them? Right. Well, you go, and here's seven things that you might consider, you know, one, two, three, four, five, six, seven. Show empathy, yeah.

Yeah. Yeah, exactly. And then on the other hand, you could have. what Pye does with inflection is something to say, oh, well, you know, look, you know your friend better than I do. You know, what do you think your friend might appreciate about you're being present or kind of emotionally connected? What kind of gesture?

And you say, well, I'm not really sure. Like, well, have you thought about just like having coffee with them and seeing how they're doing? You know, like, oh, that might be good. Or, you know, is something that, you know, is kind of bringing over something that is a treasured memory. Like you, a lot of picture about, you know, the two of you with the pet and say, you know, I feel the echo of your pain here, but the love was so intense. Yeah.

And you know, something like, like, and do that through a dialogic process that's kind of more emotion oriented and path oriented and discussion oriented with you, which is part of the pie theory of the world, like having a personal artificial intelligence to navigate everything you're doing in your life to help you be out in the world, be talking to people, being interacting. And is that the mission for this new startup? Yep. Yeah.

So it's to, if I reflect it back to you, you know, you use Google Bard, you use Poe from Quora, you use chat GPT4. You ask it something. Gives you back a pretty great response, but it's pretty, you know, it's not having a dialogue with you asking follow-up questions. You get your response and that's it. Yes. There's no follow-up question. So it's not being inquisitive or it's not being interested in you and why you ask that question. So you're kind of closing the loop on that.

That's pretty brilliant. What a good idea. Yeah. No, well, I credit Mustafa and the team. I am a co-founder. I helped, but the team is amazing. I mean, Mustafa has, you know, since co-founding Deep Mind has been doing this stuff for years. So he picked, you know, the key people who were both amazing technologies, but get this kind of how to be, how do you tune not just to IQ, but to EQ?

And how do you tune not just to get answers, but to have a conversation and questions? and that's what they've been working really intensely on. I had Keith from Tom on the show last week. I basically just told my producers, anybody who demo something interesting related to AI, just get them on the show same day. I'll talk to them for 15 minutes, I'll talk to them for 50 minutes,

whatever it is. And they saw Tom doing this like presentations. And we did one where we were like, you're making a venture capital pitch deck. And it's for somebody doing web apps and AI firms or a pharma or crypto. And it was like, whoa, if you had never written a pitch deck for venture, you just got a quick education and it's laid out.

And then now you're on slide seven. You're like, you know what, that theme doesn't work for me. That's a little too cyberpunk. Let's go with something that's a little more banky and more trustworthy. And I was like, well, this is going to get really interesting, really fast. What do you think about interfaces like voice? We had Syria and Alexa. They were supposed to solve all these problems for us.

And I asked at a conference recently, like, what did you do? What was the last thing you did with it? And it was like, I called somebody. I asked Siri to call somebody. I asked Siri to change the song. I asked Siri to set an alarm or a timer. And it's like, after that, or tell a joke, it's basically people are done with Siri and Alexa. This piece, and we talk, you get this really good concept of this is the crescendo.

How does the fact that we have absolutely nailed speech recognition and we, we've nailed computer visualization. You're building this pithing. We all saw the movie her. You know, people are working on robotics. You and I, you know,

know, Boston Dynamics, whatever. There's a lot of interesting research on artificial faces and hands giving you, you know, feedback.

Where does this all go in terms of closing the loop on, you know, like an actual, dare I say, like replicant. Uh-huh. Um,

well, right now, I mean, one of the things we pay a lot of attention to is where would it move from being a tool to being a creature, to being an entity? And there's a great kind of Star Trek episode in this and the next generation called The Measure of a man, which is about data and so forth. It's the one I most recommend people watch.

And look, we have to pay attention to that because it's totally possible. It's not the kind of Bozoville of all I asked it was conscious and it said yes. Yeah. Right. Congratulations. She passed a during test. Yes. But I think that we have to pay attention to those things and navigate appropriately for them. But I think we're a fair ways away. I mean, most of the discussion about where it becomes an entity is a lot of discussion about emergent properties. And look, it's, again, not zero percent possible. You know, like it's again, not zero percent.

But, you know, it's kind of what I see actually happening with these AIs, and this is part of the reason. why I wrote this book impromptu is it's amazingly better and better savants, which is part of the thing that creates the amplification intelligence or the amplification of human abilities, or an aha moment. And so for every current visible future, I mean, I don't mean forever, but from where we're currently building, it's all tools. And it's one of the reason why I say, well, would you put the AI in charge of a mission critical system? Well, no, not yet. I might have it as a personal assistant to a human who's in charge of a critical system. Yes. Sure. And check the work. Yes. Right. But like when I say, nope, it's in charge of its own

critical system? No, not unless I really had no other option. Now, for example, if you get to questions about how do we improve humanity a whole bunch, say you can put a medical assistant on every smartphone. Of course it'd be better with a medical system with a nurse or medical system with doctor and so forth. But there are billions of people on this planet. you do not have access to those. Would you rather have them have something where they might say, sounds like you have an infection, you should go get some penicillin. Yeah.

Can you go get penicillin? Right. And maybe they can, but maybe they can. And maybe you've just made a huge difference for a mother with her child. And it's like, look, and of course they should say, if you can ever talk to a doctor, do so. Yes. Do that first.

And by the way, like, for example, people say, well, our teacher. is going to be put out. No, we're going to have amplification intelligence for teachers too. Imagine how great a teacher can be now that they have a grading assistant, right? Yeah, or like, hey, what can I do tomorrow to engage this particular student? And it's like, oh, well, that student likes, you know, Marvel superheroes. Maybe we should make a physics agenda for them and a test and a project for them based upon the physics of, you know, Iron Man suit. And it's like, okay, great, can you make that for me? And now this kid's totally engaged because it's in the genre they love.

Exactly. So getting to all of those things is right now, line of sight. Line of sight, we can see it. The pace is bonkers here. Can you, do you remember a time when this pace occurred in our careers? No, we have the crescendo of acceleration. It's because it builds on. Without the internet, you couldn't have it.

Without mobile and cloud competing, you couldn't have it because it's off the scale, compute stuff without Wikipedia with the semantic data like a lot of this training data yes so that opens up another pandora's box i'm a content creator for life and i care very deeply about content creators having their work compensated and um taking care of we saw stable diffusions getting sued uh github's got a lawsuit of some open source folks for uh co-pilot uh barry diller was like listen this is the moment to stand up and the writers guild is fighting to have no chat gpt in the writer's room as of the strike yesterday, I saw. So it's coming to a head here. What's a reasonable framework given your 30 years in the internet business being there from 300 bod till today

for a framework for compensating, getting permission or otherwise making it fair? Forget about the laws around fair use, but let's talk about the term fair, as we all know it. What would be fair for the people who answer questions on Cora if they're going to be part of a language model? What would be fair to photographers or Quentin Tarantino's scripts or every episode of South Park or every episode of Johnny Carson being used to write more jokes today? What would be fair in your mind? Well, I think the usual thing is to say, you know, what would be the kind of licensing regime? And, you know, obviously we could do like Creative Commons, have some tags. about what it could be used for or not used for.

You know, I think people, although kind of mistake that what really going on here is it trains on massive amounts of data, they tend to go, no, no, no, it's my specific data. And you're like, no, no, no, no, it trains on massive amounts of data. And that's actually what, you know, fine-tuning in specific cases, medical,

other kinds of things, very useful. And, you know, say, well, okay, I may even have my data available in a search result, but it's not available for a training thing without a economic arrangement. And then you might have economic arrangements that are kind of off the shelf. It's just like, hey, you pay us X and you can do it,

you know, as kind of ways of doing it or, you know, something that's kind of more automatable in that. Programmable, like robots.txte. You can search my website. You don't. Craigslist. Craig Newmark was always very clear. My data.

You can't index it. Zuck was very clear. Our data, you can't index it. Sorry, Google. Yep. And if they don't want to be in the training data, that's their right. Yes, exactly. And I think you'll see training data commons where the large players will say, hey,

this swath of data will allow it because we're all building better products for this stuff. And I think that there may even be some stuff that really matters from a human standpoint. Like you really do want to train a bunch of these things on a bunch of medical data. We'll have to obviously figure out how to make sure, you know, really make sure people. PII and other kinds of things, you know, don't come back to bite you. But can you imagine, like, you're training the stuff on, like, cancer stuff? And, like, we're advancing what we could be doing on cancer. Like, that could be awesome. We could solve problems we are not aware of. There could be precursors to people getting cancer that if we just took every cancer patient

and index their history, obviously, personal information we stripped out. But you could just ask it, just like I did with that CSV of, you know, some EV data and some VIN numbers, you could just, chat GPT4 or whatever model, what are the trends in this? And it might be like, it's very interesting. People who live in these places have more breast cancer.

And it's like, yeah, that's because there were PCBs dropped into a river or something or people from this demographic. We might find things that we're uncomfortable with. And I think that's pretty scary to people too. Yeah,

but you know, it's partially, you know, how we make progress. And, you know, like, for example,

part of progress did result in a bunch of external that has climate change. Most people don't look straight at it and say, it's 8 billion people with hundreds of millions, maybe even a billion in the middle class. That is what does that. And by the way, in doing that,

you're like, well, who's to say 8 billion people isn't like, you're going to shuffle yourself off the mortal coil? It's like, you know, like, okay, but now we just need to apply the same techniques to solving it. It's like, yeah, it's a real problem. Let's solve it now. And so, and, you know, like, for example, those of us who are private individuals, like, I've been investing in fusion power for the last eight years because, like, well, if you get

carbon, cheap and cheap energy, you can do everything from decarbonization to desalcidification of ocean. Unlimited water, control, every control, yeah, free food eventually, because food is a function of water and energy. Exactly. So it's like, okay, let's tackle, like, like, I think it's almost, you know, criminal that every major government isn't going, like, this is our 10 plus tens of billions of plus fusion programs. Now, by the way, distributed through innovators in a network is generally speaking a much better way to do this.

That's part of the reason why we see all these innovation within that kind of context. And that kind of thing is, I think, a really important thing to do. There is, by the way, an AI application. I'm not sure it's yet good on fusion, but they are beginning to say, hey, could we use AI to figure out the containment of the fusion. Wow. Interesting, right? It may not work, but it's again, like, well, like, that's how across everything,

protein folding and disease solving, everything else. What if it just points you in the right direction and says, like, over here? And it's like, over here is the planet that's inhabitable closest to our solar system. It's like, okay, there's our, or, you know, hey, how do you create a biosphere? It's like, well, maybe something over here. at least it would just take the subset of, you know, the problem set down to something manageable. And again, if we're 30%, if everybody's 30% more efficient, including the people working on fusion, well, that's pretty powerful.

Every third year comes out of the compounding comes out of their roadmap. Okay. But you're saying governments, the fact that governments are not just throwing, you know, 10 billion, 100 billion at this while we're fighting crazy wars all over the planet and buying B2 bombers or whatever. it'd just be a lot easier to just solve the energy prices and have people stop fighting over water and food and energy. Yes. Like, let's solve energy, right? I mean, it's a super important thing.

By the way, a little footnote because, you know, early sci-fi film kind of misled everyone to think planet colonization is the important thing. I actually think that if you do all the math, actually, in fact, creating space habitats is going to be the actual thing. Silent running? Yeah, well, but obviously Hollywood always tends to be the horror version of it. Yeah. But like, you know, when you think about it and say, hey, what would you be doing if you were designing something from scratch in a space habitat as a way of doing it? And that's a much easier project than either a terraforming or B going lots of light years. Yeah.

I mean, have you seen Bruce Stern in Silent Running? No, I haven't. No, so you got to see silent running. 1972, it's, it's kind of Elon's original vision that got him into space, which is he wanted to put geo, what are they called geodesic domes? Oh, yeah. They wanted to, he wanted to back up the biosphere was E's first concept. Like, let's put everything up there. Well, the backup for seeds instead of seed lockers in some mountain.

Very silent running is the story of Bruce Stern's the character. And there's like an R2D2 in it years before, you know, Lucas came up with it. Watch it this weekend. It's like, well, it's part of that Logan's run era of like really interesting sci-fi, you know, Westworld. I'm trying to figure out what else was in that little cohort of like 70s sci-fi. But really fascinating. There's one-138. There's others.

Yeah. Yeah. So there's a bunch of them in there. Listen, this has been great. Thanks for coming back on the program. It's been, I'm trying to figure out when the last time you were on. Here we go. Oh, you weren't on that long ago.

You were on in February 2021. But then that, there was one time you were on before that. Yeah, that was because it was the time in the office because we were just carousing in the LinkedIn office. Yeah, I got this new podcast. Can I just talk to you about LinkedIn? And you're like, yeah, come down. I was like, yeah, let's do that. I'll get some microphones. And here we are with these podcasts. Crazy. Continued success with everything. It's great that you're working on at all. Anything we missed here or anything that is just keeping you up at night about this or just getting you super motivated or things you've seen that are super prescient in the space? No, I think we covered a lot of ground. We covered a lot of ground. We could easily do another hour. Right. I don't think, yes. Both our voices will be gone. What about Google?

This is, this was around the poker table last night. We had a big discussion. I know your team, Microsoft's. I got to be careful here. You're on the board of Microsoft. But just objectively, they seem to be going a little bit slow here. And there seems to be some risk aversion. Your new partner was the one of the guys from Deep Mind, right?

So what, what's your take on Google's progress here? Are they hopelessly behind? Are they going to catch up? they're certainly not hopelessly behind. I mean, they're a bunch of super smart people. They have compute infrastructure. A lot of the techniques that are being deployed right now were actually, in fact, developed or pioneered. You know, the first versions of the elements of were pioneered at Google.

So I think there's a bunch of stuff there and they have a whole bunch of very smart people, not least the deep mind crew, but also the brain crew and a bunch of others. And, you know, I think that's, you know, good for the world and all the rest. I do think they have a bit of an innovator's dilemma problem because, you know, people would kind of rather have an answer than 10 Blue Links in a lot of cases. And you see some of the thrashing about trying to figure that out, which is part of the thing. And, you know, it's good for them. I mean, they basically spent, you know, a decade plus feeling like they didn't have any competition.

And, you know, now, you know, having a game on is is good for the marketplace. Yeah. It's a kick in the butt. And you look at what happened with Microsoft missing mobile. That woke them up, right? And they were like, okay, can't miss the next thing. And this is the next thing. And they're not missing it.

So sometimes you need a little wake up call. I was looking at their assets that Gmail, docs, Chrome, Android, YouTube. You just look at those datasets. Like, you open up Gmail and forget about just like completing sentences. But if I could talk to my Gmail and have it give me trends of what's going on in my email box for the last 20 years or my documents. Or when I'm on YouTube, I say, hey, listen, I want to hear some interesting. discussions about sci-fi films from the 70s. I could type sci-fi films in the 70s and find

four things that are titled that, but there might be actual discussions where Quentin Tarantino in an interview pulls that out and make me a super cut of it, right? I was just brainstorming about and then Chrome knows, you know, so much about our behavior. There's a lot of opportunity there, but they seem to be playing not to lose and like maybe protecting the franchise. I think they got to forget about protecting the franchise. People will keep searching. but you got to put some chat GPT like boxes on the side of all of this stuff, man. I just think YouTube plus AI, the mind goes, whoa. Yeah, a whole bunch of smart people, a whole bunch of assets.

I think they have like seven properties that have over a billion Dow, right? Like, you know, it's like, okay, like just huge. And, you know, credit to Satya and the Microsoft team of like aggressively getting back in the game by being smart early and moving. And where's Apple on this? Because they're so precious. And we are now in a like, let's put this out here with the disclaimer. And Apple had serial this time.

I mean, I wonder like their perfectionism is going to be the enemy of progress here for them, you think? Yeah, for sure. I mean, look, just line up Siri versus chat, TBT, and go, oops. Oops. Or Alexa, yeah. Yeah. And not, yeah, or Alexa. And in, you know, like, for example, the fact that, you know, Apple's,

Cloud services are completely anemic. You know, like, they don't, they don't. I mean, there's, occurs, amazing company, amazing work on the chips, amazing stuff on the iPhone. I mean, of course. But like, look, these are the new tech waves. And the new tech waves actually, in fact, really matter. So.

Can't miss them. If you miss the wave, like, I mean, it can be just brutal. All right. Listen, it's great to have you back on the program, Reed Hoffman. Everybody check out. He's hiring for this new startup. And if you're interested in working there, you could Google or go to the website. What's the website?

Inflection.AI. All right. Go to the careers page there. I mean, developers around the world are like embracing this like nothing I've ever seen. So it seems like a pretty good place to go. They've got some pretty smart folks over there. So go get a job. And we'll see you all next time on this week's startups.

Bye bye.