Reid Hoffman says the AI race is not a cage match

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1:24When you think about open AI and thrumping, well, if you believe that AI has the impact of applying intelligence with the scale and price of electricity across everything, these are going to be two of the major providers of that. We tend to want to tell these stories as cage matches. You know, well, one of them's going to win and the other one's not. You're like, well, actually, in fact, there's a lot of room for both of them to win incredibly. Almost every dinner conversation I'm at, like the big question is, can you make sense of the valuation of these companies? So what should my answer be?

1:58Think of it as a little bit like internet valuations. Some of them will have turned out to be insane and go to zero. And some of them will have turned out to be way too low and have gone up a lot higher. And then the trick is, which ones? Reid Hoffman is one of the leading tech investors of our time, and I'm lucky to call him a mentor and a friend. He's co-founder of LinkedIn and has backed so many influential startups. Plus, he served on the board of Microsoft for a decade. He's recently said he's turning his focus to Manus AI, his AI drug discovery company. With Anthropic and OpenAI on the path to going public and SpaceX surpassing a$2 trillion valuation after its IPO, I needed a check-in with Reid.

2:46So we hopped on to talk about what's signal and what's noise in the AI race and so much more. I'm Rana El-Khalyubi, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution.

3:08Hi, Reid. Welcome again to Pioneers of AI. Hi. My absolute pleasure. It is always so great to have you on the show. It's been a while since we last chatted. And as with everything in the AI world, lots of updates. So I'm excited to catch up. Likewise. So I want to start with some personal updates on your end. So after a decade of serving on the Microsoft board, you departed from the board. Actually, I just said I wouldn't stand for re-election, which means I'm on it through the end of the year. But yes. Okay. Okay. Okay. But you largely did that because you are going back to founder mode and focusing on MANA.

3:45So tell us more about that. I'm actually really intrigued by that. Well, you know, when Ujwal, Sid, and I had been doing the work in the last couple months, and we're beginning to see some small molecule proposals from our AI drug discovery engine that our computational chemists are looking at and going, oh, my God, that's really interesting. And that could work. And I said, okay, I've really got to make sure that this thing is navigating and, you know, building these things really matters. And so I got to focus on this and, you know, kind of talked to Satya. I said, look, it's been a long time.

4:21I'm always a friend and an ally. We'll continue to help even afterwards. But I'd really like to spend my time more on building, on, you know, being a founder than essentially, you know, kind of being a governance person. And, you know, I can still help when, you know, as a matter of fact, you know, Satya and I were just on the phone today talking about some piece of strategy. Yeah, amazing. As you reflect on the Microsoft board, anything that stands out, any takeaways, any reflections, insights? It's been a couple things. I mean, one of the things is obviously the LinkedIn acquisitions, one of the epic M &A of history in terms of, you know, growth and impact and revenue, you know, having high operating margin, et cetera.

5:11Also continuing to be successful, right? A lot of, you know, LinkedIn is thriving still, right? And that's not to be taken for granted. Exactly. Yeah. And then, you know, kind of helping, you know, the, you know, kind of navigate the organization to buying GitHub, which, you know, was bought, you know, well over revenue in terms of comparable prices. But the strategic part of it and how that plays into the whole coding revolution now and so forth is really key. You know, facilitating conversations of trust between OpenAI and Microsoft. You know, those are some fun highlights. Yeah. So incredible.

5:49Okay. So I want to spend a little bit of time on the big news in AI. So the SpaceX IPO was on June 12th. It was only in February when SpaceX and XAI merged, right? And a big part of SpaceX's IPO story is actually an AI strategy and an AI narrative. And it seems that they want to vertically own and integrate the AI supply chain, whether it's compute, data centers, the model, Grok, Cursors acquisition, which as we record this, It was announced just 48 hours ago. I would love your take on what that all means. Well, in a sense, SpaceX talking about itself as an AI company is somewhat honest by the fact that, well, we bought XAI and what we're going to do is use our market cap to try to buy our way into being an AI company is essentially what it's trying to do.

6:38And so it's not surprising that, you know, whatever it is, X days after the IPO, we're using our market cap to buy a cursor. And I wouldn't be surprised if there were others as well because SpaceX isn't an AI company. XAI is, as Elon himself has described, it's a complete train wreck for its kind of building of foundational models and other kinds of things. And all the founders are left. It's on its third restart, et cetera. And so if you look at the revenue in SpaceX, it's the, oh, we're going to be charging Anthropic a lot for compute. So you're like, oh, you're a premium priced core weave. I get it, which is not an AI company.

7:18But the reason why they're saying they're an AI company is because they're going to go buy a bunch to try to become an AI company. And I think what investors are buying or holding on in this was that they're going to go spend a lot of equity capital on buying a bunch of AI assets and seeing if they can be cobbled together. You could almost think of it as the IAC of AI in terms of how it's playing. So I'd say it's TBD, watch this space, but use the market cap to buy AI companies and try to buy your way into relevance. So Anthropic and OpenAI have also both filed for IPO with the SEC, and both are expected to also be historically giant offerings.

7:58Now, you're an investor in both of these companies. So I think my first question for you is, do you think the order and the timing of these IPOs, both of them, are important in relation to each other? I'm sure the two companies do, right? There's definitely a lot of rivalry between the companies, you know, and there's the theory of, you know, who gets out first and do you absorb the capital? I don't think it matters. I actually think there's a lot of room for both. I think they naturally have categories that they're very strong in. There's obviously everything that's going on with, you know, code and its applications.

8:34and, you know, Anthropics clearly testing the waters on expanding and, you know, design and legal and whatnot. And OpenAI with ChatGPT is clearly the front-end search Google kind of equivalent and is also testing the waters on other things and is coming up strong on, you know, Codex is actually insufficiently talked about as a really compelling coding product. As a matter of fact, it's kind of stunning how much it's CloudCode and Codex. Like one of the questions in the SpaceX acquisition of Cursor is like, Cursor seems to be had its bright star some number of months ago and seems to be fading over the horizon.

9:12So what the theory is that it doesn't completely fade over the horizon is an interesting one. But we tend to want to tell these stories as cage matches. You know, well, one of them is going to win and the other one's not. And you're like, well, actually, in fact, there's a lot of room for both of them to win incredibly. Like almost every dinner conversation I'm at, like the big question is, oh, how can you make sense of the valuation of these companies? So what should my answer be when I get asked this question? Well, think of it as a little bit like internet valuations. Some of them will have turned out to be insane and go to zero.

9:48And some of them will have turned out to be way too low and have gone up a lot higher. And this is what happens when you have high growth, fast moving, you know, tech companies of which the AI is most of it. And so, you know, it's like, you know, look at what Google became from being an internet company. And then other things bombed for being too early and other things. And so I think there'll be a number of these valuations that'll just be like, oh, yeah, you paid a lot for that and that turned into zero. But I think there will be others. For example, when you think about open AI and the robotics, why should it be valued in the same trillion-dollar company that these others are?

10:23And the answer is, well, if you believe that AI has the impact of applying intelligence with the scale and price of electricity across everything, and these are going to be two of the major providers of that. And what's more, you can already see some of the revenue really, really well. And frequently, the revenue comes later. like in the open AI category, you know, like advertising. Because like, for example, Google's early theory of revenue was we're going to sell enterprise servers. And it's like, well, that didn't work. And then it's like, oh, AdWords, you know, thus far best business model invented in human history.

11:02So, you know, if you're like all the valuations are crazy, you're wrong. If you said some of the valuations are crazy, you're right. And then the trick is which ones? Which ones? Yeah. Yeah. I think the other question that comes up a lot is, do we care whether these companies are profitable or not? Is venture at the moment and maybe eventually the public markets, are we subsidizing the cost of AI and the cost of tokens? Like, how do you make sense of that? Well, we're definitely subsidizing it for growing. You know, kind of a modern exemplar, speaking of, you know, trillion-dollar companies, is Amazon, which was unprofitable and barely profitable for a very long time and yet has an amazing strategic position and continues to be that.

11:49So, it doesn't matter if they're profitable to IPO. It does matter that companies become profitable and then eventually become, you know, seriously profitable. But, you know, part of valuations, which most people don't appreciate, is like it's future expected terminal value. So you go, well, this thing is so strategically important, it's going to exist for a very, very long time and continue to grow and have an important market position. Even if its revenues are modest or its profitability is wobbly, that still makes a very valuable company. I guess the learning, too, is you're not always able to predict what these revenue models or business models are going to look like anyway, right?

12:30Yes. It's going to evolve. It is evolving. Yeah. Part of the thing is, is there some possibility? Because if you said there's the 3 % possibility it becomes an AdWords, that's huge. I'll be right back with more of my conversation with Reid Hoffman.

13:06The business world is moving faster than ever. And when change hits, we need to learn in real time. On Rapid Response, you'll hear candid conversations with CEOs and leaders making tough calls about AI, human talent, responsibility, and the bottom line, how they navigate uncertainty, pressure, and high stakes moments. I'm Bob Safian, former editor-in-chief of Fast Company, and I'll be your host as each episode breaks down what you need to know right now. You can find Rapid Response wherever you get your podcasts.

13:53All right, so let's talk about what this all means for early stage AI startups. Do you think, back to kind of these IPOs and where this is going, how does this change how we think about both how we evaluate defensibility in these AI innovation ecosystems and also what should we be looking for? The change of defensibility and the change of what kinds of things lead to sustaining value, people tend to be overly dramatic and say it all goes out the window. And that is certainly not the case. But on the other hand, a bunch of things that used to be strong defensive modes don't. And so part of the reason why people were talking about the syspocalypse is because they went, well, the previous dynamic with SaaS companies was, you know, it ultimately cost a billion dollars to build the baseline tech that everyone would use.

14:40you chip away and eventually get a ecosystem and customer base and then challengers it's very expensive to come to because you're continuing to grow your customer base while they have to spend a billion dollars and then get the first you know couple customers and then you go well if all of a sudden it doesn't cost a billion dollars to make one of these things the product feature set of what's useful to them may change radically because individual companies may want things deeply personalized in ways that they can do it with the coding agents themselves. And then so therefore the economic model, which was I could be, you know, have a high operating margin because switching is very expensive.

15:17It's like, oh, I don't want to pay you that operating margin anymore. And competitors can come in and hence SaaSpocalypse. Now, the reason why the SaaSpocalypse is overly stated, and it kind of plays the defensive moat question that you have, the real question is not short all SaaS. The real question is short any SaaS that's not aggressive and driven, committed to become AI native and buy the SaaS that is as a direction. And that then kind of gives you some code to also what moats might be. There's a bunch of this kind of standard defenses that I think will continue in the current age. Now, the interesting question is which things will add in?

15:52And I wouldn't be surprised if there were new kinds of moats. You know, people have speculated, will there be data moats? Maybe, especially on things that are like real time oriented or like you can only serve the product if you have this particular data versus training data motes, which I tend to think would be a little bit more skeptical of. You know, how do network effects play in? You know, how does that work? I think there's a set of different questions there. There's the kind of like, in some senses, brand and trust matters a whole lot more. So if you've established a brand and trust and gotten through the noise, you know, how does that matter?

16:28So I think there's a stack of things that matter there. I do think it's one of the things that you and I love about both being founders and investors is that, hey, when you're throwing up all the cards in the air, it takes taking intelligent probability risk-adjusted bets, working with speed, you know, kind of making it happen. And, you know, that's fun. Yeah, that is fun. But, you know, we still believe that there is a lot of potential in vertical AI startups. So like startups that are coming in with deep domain expertise to solve and reimagine workflows in, I don't know, antiquated industries.

17:03But, or maybe it's an and, I think of, you know, let's take the legal industry, for example. Three, four years ago, we saw a whole bunch of legal AI companies and they've been quite successful. But then recently, Anthropic just released their legal agents, essentially, which is essentially what these companies were doing. And so I don't know if I would invest in a legal AI startup today, right? And I think that applies to a lot of these vertical industries. So that is definitely kind of a question mark. Well, I think you have to ask a couple of questions because if it's just like your company is a thin wrapper on a model, You know, you're basically just waiting around until the model company, you know, kind of decides to go first party.

17:50And they may still allow you to run and all the rest. And maybe you'll switch to, oh, I'll be using the Chinese open source, you know, Kimi as a way of doing this, which, you know, is kind of what Cursor ended up doing off Cloud Code. But it's not as good. And by the way, part of the reason why these startups are so valuable, whether it's, you know, coding or legal, is because they're dealing in very high economic value. And so the difference is you say, well, you know, Kimi's almost as good. It's 85 % as good. It's like in high economic value things, 85 % kind of rounds to zero, right? So it really has to be something that is not – A non-obvious problem to be solved or – Well, it has to be something that it isn't just that the model company can just literally almost kind of tell its model, go close the loop and learn everything about this and then just offer the product, right?

18:40It could be that you're integrating data sources that's fundamentally not really available to anybody, including the model companies. And so, for example, even if Anthropic decided, I'm going to start doing Airbnb, it couldn't do that, right? And so take what Sid Ujwal and I are doing with Manas. It's like, no, you can't just go, now, Claude, tell us about biological molecules that might actually, in fact, detect and prevent and or cure leukemia. It doesn't work that way. Right. And actually, this is also, this is my thesis anyway, but I'd love your take. I'm very excited about world models because I don't see Anthropic and OpenAI and kind of the big LLMs going into, they could with enough funding.

19:29But it's such a different play for now anyway, which is why we're excited about the physical AI space and the world model space. So I think the good thing is the physical model space is that there's a whole bunch of stuff that's pretty unique that's outside of the data sets that OpenAI and Anthropic are doing. Including getting your own data for the physical AI world, right? Exactly, right? So the data for the physical world, what kind of actually, in fact, you know, compute fabric you need for that, what compute fabric works in the right kind of timeframe. You know, LLMs are still pretty bad at quote unquote real time, right?

20:11I mean, they try to hack it in various ways. So there may be a whole bunch of stuff there that creates something. But there's a reason why a lot of smart people are doing it. It's a good bet because it's like, well, here's a new area that's different than LLMs that could be really interesting. It's a risk-adjusted bet. Yeah, absolutely. I want to talk about the huge influx of capital that will happen with all these IPOs. So with the employees of these AI companies get a windfall from the IPOs, what does that mean again for early stage investing? What does it mean for funds like ours? What does it mean for, like, will we see a whole new slew of AI startups in the way that the PayPal mafia, right, kind of created?

20:53What do you think will happen as a ripple effect?

21:00So I don't really know fully what the ripple effect is. It does tend to be that when people make a pile of money, they tend to go into some philanthropy, which is a whole bunch of things, and some investing. And one of the things that I think has been not told as loudly as it should about kind of how the ecosystem of Silicon Valley got both so broad and deep is because when you had successful people, they stayed there. And then they've turned into angel investors and advisors the next thing. And then eventually the compounds, compounds, compounds. And so when my PayPal colleagues and I came out, we were like talking to each other, investing in things, starting things, et cetera.

21:45And so that will certainly happen because it's not just obviously the founders of each of these companies. But what happens is all the executives and everyone else tends to make a bunch of money. And the really interesting question is, well, what happens when you're like getting pitched ideas? Let's just be a little bit fanciful on this. Okay. An AI is pitching you for their business idea. And they're going to go execute this with a whole bunch of different compute fabric. and, you know, either you or you plus an AI or an AI is making the capital allocation decisions, because by the way, compute allocations will be capital allocation decisions, compute capable part of it.

22:27My guess is like, for example, in that universe, there's some deeply utility things about there being firms because the firms are running, you know, kind of competent, specialized AI with data and all the rest and all that. This is all similar to the startup landscape becoming highly variable. We now, of course, have the investing landscape changing shape, too. Yeah. Well, you touched on this with your conversation with Satya Nadella, the CEO of Microsoft. You talk about this idea of a hybrid human-AI organization. One question that I have is how do we decide what work gets done by humans and what work gets done by AI?

23:07and also in this like hybrid organization, how do you build things like trust and culture and mission and values that are so important to the success of any organization? Well, part of what has made capitalism so essential and so successful to humanity, to all the societies, has been that the allocation of resource decision tends to go to the things that drive quality up, price down, et cetera. And so the answer of like, how does work get allocated is like, well, where does the work get done at a certain amount of quality at a low price? Now, that being said, humans will always be, I think, central participants in this.

23:55And so the question will be is, well, how do we feel that we are in a collective market game that benefits enough of us in this game that we will all hold ourselves to this game. And so, you know, the kind of notion that human beings will say, well, okay, we're just less effective at everything. The AIs are more effective at everything. They should do everything. It's like, well, but we still have to have roles and have to participate. And so we'll be looking for those. But I think we will create the markets that enable that. Now, you mentioned legal before. I think one of the funny things is, and I don't think they should, but I think they will.

24:35I think lawyers will go, well, if it's law without a lawyer, it's not law. And so we have to be there, right? I spoke at this. It was like a partner event for a law firm. And I was talking about AI, obviously, which is why they invited me. But I was intrigued because I think there are lawyers who are like rethinking what a law firm looks like in the first place. And they're building it with a whole bunch of AI agents. And it's very interesting, right? They're just rethinking it from the ground up. Exactly. And by the way, that's what I think should happen. I think the notion that we, like, you know, a little bit like the Pope's great encyclical, it should be like, hey, be focused on what humanity at the center means.

25:19It just doesn't mean historic humanity at the center. It means a good role at the center in how the future is evolving. I'll be right back after this quick break.

25:52Okay, so I want to switch focus here, and I want to talk about politics. And I will timestamp this to say we had, you know, we're having this conversation on June 17th because politics is also moving fast these days, right? Or at least chaotic. Yeah, chaotic. They seem to love volatility. Yes. So I want to touch on this idea of a U.S. sovereign wealth fund for AI. Anytime Bernie Sanders and President Trump seem to be agreeing even a little, I'm like, okay, this must be interesting. So I would love your take on kind of Bernie Sanders' proposal, this idea of a sovereign wealth fund overseen by an independent source to tax some of the largest AI companies.