Sarah Guo - Funding the Frontier - [Invest Like the Best, EP.489]

Introduction

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1:27Hello and welcome, everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at Colossus.com.

1:51Patrick O'Shaughnessy is the CEO of Positive Sum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of Positive Sum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of Positive Sum may maintain positions in the securities discussed in this podcast. To learn more, visit psum.vc.

The Current Tech Landscape

2:18Sir, where to begin what will hopefully be a really fun conversation. I guess because you and I are interested in so many of the same things, I'm just curious what's on your mind today. I think we're both feeling a little frenzied, and it's been going for a while, and it kind of feels like, if anything, it might get more frenzied and more chaotic, both for what you do, but also the world around what you do. So just in this moment, what does it feel like? What's on your mind? An obvious thing for anyone thinking about how to navigate this period as an investor

2:51is just how does it unfurl, and how is it different from the past? What do I do if I can't backtest? I was talking to an investor friend last night, and the analogy he gave me was, I keep saying I want to press the brakes as hard as I can, but I'm not doing it going 90 miles an hour. And I do think the question is, do you miss the opportunity on one side, or do you make the mistake of every boom-bust cycle in technology history?

3:22Especially if you combine that with, what does it mean when you're also four years into building a firm for the durability of the firm and the careers of the people? I think it's a complex question. Do you think that we got it right in the profile that we wrote that you're sort of making a specific, I think we called it a wager, a bad positioning, whatever you want to call it, that there is a really important fundamental thing happening between a couple of labs in AI and everybody else, and that we need to sort of like take up arms

3:54to make sure we don't end up in like a very monolithic outcome? Do you think about it that way? I would answer in a maybe different way, which is I believe in like the great man and great woman theories of history. If you have very high agency people in all of these places and they have the correct risk capital or support in the network or environment, yeah, you change outcomes. You look at very important questions of what happens to open source models and like U.S. industrial policy.

4:26If you think about the opportunity for the ecosystem in the future, is there going to be a competitive Western open source model? Like it actually leads to like, did anybody make one? Could they like raise the money or were they willing to commit the capital and gather the talent base, build all the infrastructure and fight for the frontier or not? I definitely think that individual people and entrepreneurs can affect the outcome. I don't necessarily think of it as a war. I am working closely with and co-invested with and have many friends at the labs.

4:59I think it's fair to say the extreme point of view that some folks may had in and outside of those big labs of the owner of one, two, three frontier models consumes the economy. I do not want that future, very clearly. And I don't think we are going to end up there. Do you actively want to be a great woman in this sense of the theory? No, I don't mean that from like a personal humility perspective. It's just like, it's not on my set of goals. I want to be the best investor

5:29in the things that I try to do. So it's not out of a lack of ambition or even confidence. It's, I think some people are driven by like, I want to be the person that like made this happen. I thought I was going to be like a software entrepreneur for the longest time. My decision that from an identity perspective, I was going to be an investor actually had a lot to do with the idea of I'm deeply curious. I like to understand things. I like to be right. I'm very motivated by working with extraordinary people.

5:59If I have a set of skills using those to make them more successful, it's like a pretty good fit for early stage investing. And if I want to work with the very best people and I want the companies to have impact, the firm can support a movement and support change we want to see. But I don't think it has to be me. If that's the goal, what does it take? Do you think right now to be the best in a very competitive environment? Undeniably, you've done really well so far. I'm curious what it has taken to be that good

6:31and what you think it's going to take in the next year plus within horizon to be that good. I think it's been pretty simple so far. My read of the environment was the growth of firms and generational transitions that were happening meant that it wasn't the most competitive landscape in early that it has been. And you had this massive technology transition happening. And if you took the bet on understanding the technology and the community and approach it from first principles, you might have better access and make better decisions

7:02than others who are less focused. All you have to do is take the risk and be focused. And then it's an execution play. That's one of those things that I think is pretty simple and it's just hard, this effort. I think today it has actually been not that complicated. It's more about what your bar is for the people you work with. And my partner Mike and I started with a set of pre-existing relationships and understanding. And so I think that it's been useful. Surely there must be more than just outworking everyone. Mike said something interesting to me a couple weeks ago,

7:34which was there's sort of 250-ish people that he thinks about or you guys think about that are some combination of entrepreneurs and researchers and... Doing the most interesting things on the frontier. Yes. The people that are actually showing up in the morning and pushing this whole thing forward. And that one of your goals as a firm is to be as close to those people, know them all and be as close to them and support them in as many ways as possible. I really like that idea. It's a cool idea. And that's more than just doing a bunch of meetings with people that are starting companies.

8:04From the outside looking in, from the cheap seats, it looks like there's more unique stuff going on than just the competition set was low and we focused more and we're executing better. I'm interested in the ingredients that have been so far a part of success. I won't name them, but there's one well-known LP that does the survey every year of what all the other fancy LPs, who they most want to invest with. You're either number one or two. There's something going on both with the companies you've invested in, with the performance so far, with the market perception. There's something more than just,

8:35okay, it was a moment in time. We worked really hard. I'm trying to get at those ingredients. That's why I'm pushing on it. To the point of perhaps making a bet that others wouldn't, we thought very carefully about what markets are going to matter and what might be different about the founders that we look at in this era if we are right about capability growth and the breadth of impact that would just be non-obvious to other people. Where's the biggest difference from the status quo?

9:05How does the framework change? And I'll give you two examples. One of the things that we were really looking for

Application Areas and Law

9:10in the first year was application areas, workflows and professions, tasks that we thought were a good fit for purpose for the models, which is a very technology forward approach. Lots of people would be like, this is nonsense. You got to think about the customer problem and working from the customer back is the only way. We want to do both. And if you look at Harvey and the function of the law, rationally, if you think that we can do next token prediction with language and you knew that in late 2022,

9:42then law is structured language. I'm not a lawyer, but from the outside, I'm like, you need to like read a lot of documents and we had retrieval and you need to generate text and there's a lot of precedent text, both inside firms and in common law and history. That feels like a really good match. We also took a very specific view of what is now possible and then what is valuable within what is possible and then who's aligned with us. Winston and Gabe, they believed that AI

10:13would transform the practice of the law in a very AI-pilled way. We will do enormously complex work with lawyers. I don't know when, it could be next year or five years from now, but from the kernel of, I can look at a landlord-tenant agreement in California and answer a question, somewhat trivial, to I can project to doing a Activision Blizzard M&A and doing 85% of the work.

10:44That's a leap. The thing that appealed to me in that moment was the ambition of what was possible then and the technical logic of like why it would work. I think that's probably a different decision-making framework from how other people

Competitive Researcher Dynamics

11:01were approaching it in that moment. What is that group talking about today, the 250 Researcher Frontiers group? What's the most interesting thing and the most notable difference between today and six months ago or 12 months ago or something? It is a violently competitive landscape. I think that was true 12 months ago, but even more true than it was 24 and then 36. I think people are very concerned that it is a globally competitive landscape and there's insecurity in that because I think it's a bit narrative-breaking as well. I'm going to like describe a belief and then question the belief.

11:33The belief is with recursive self-improvement of AI research, models that can improve the models themselves, we are a year, two years away from some sort of exponential intelligence. I think that belief is new within the last 12 months for a lot of researchers. Some driver of it that we're two years away, Andre Karpathy will actually in a very self-aware way say, I thought it was two years away for about 10 years.

12:04And he thinks it again, to be fair. Who can say? I do think that there is some sense of the major labs are so compute intensive and so large from a headcount perspective now that the sense of contribution of I can move the needle of opening eyes 200 people. There's not that many researchers. The question of like, how do we get there is really up to every single person? Now, if the question is, well, I need $750 billion of compute spend

12:35and we have many thousands of people working on this problem, I think people feel less ownership of the outcome. Oh, that's interesting. So it's just like a function of getting compute. That's the thing that's going to push this thing over the line, not our own human efforts. I definitely think there's a large contingent of researchers who would feel that one of two things is now true. What I do doesn't matter anyway because the model is going to do it. Or two, the only thing that matters is compute scale. And both of those are somewhat disempowering. So then what are they doing?

13:05If I believe both of those and I'm a top five researcher or something. That says something about your psychology because you want to do something that matters. I think there's also a set of scientists who want to work on the thing, whether or not it matters that they're working on it. An entrepreneur asked me yesterday, I would not work on the companies if I felt like we couldn't change the outcomes a little bit for them. He asked me yesterday, would any of the companies that you backed not been backed without you at that round? Would people have just said no? 5%, 10% max? They're resourceful,

13:36really talented people. They find other investors. There are lots of smart investors in the world who want to take that risk. Maybe they wouldn't have gone the next $100 million of compute. I don't think every researcher doing frontier work at these top couple labs right now feels like they're essential to the machine. What do you think is the unhealthiest part of everything going on right now? What worries you about what people are trying to accomplish and what are the things that you're most worried will inhibit the future that you want to see?

Compute and Infrastructure Challenges

14:06I think compute is one. People, I think, understand that very well. The version of us having enough compute over the next 5 to 10 years, and people are very much thinking about 20, 32 at this point at scale. I was talking to the leader for infrastructure at one of the hyperscalers earlier in the week, and he's like, there was nothing that was going to move the needle for us at sufficient scale before 2030. That's depressing. Where can we get sufficient natural gas? Americans and entrepreneurs

14:37have been able to build new technologies and new capabilities very, very quickly in the past. I don't think it is a technology or capability or capitalism problem. I think it is a regulatory problem and an alignment problem. And I don't mean like AI alignment. I mean, if you want to build data centers in New York, you need to convince the people of New York they should want data centers there or America should want data centers there. If you want to make the price of nuclear

15:07competitive as baseload power, then you need to convince people it's safe and you need to allow enough construction of SMRs in order for the price to come down because we understand how that cost curve will change in theory. I don't think we lack the technical and entrepreneurial capability to build abundant cheap energy for the data centers. That's one. The physical supply chain is just a tough reality.

15:38That makes me worried that the learning to build things and having the tacit knowledge and the labor and the raw materials that can't go as fast as software or even decision making. The only way through that is through. We just have to invest in it. On the investing side of like what worries me, I was talking to one of our founders, several of our founders who are researchers and explaining that the quality of their storytelling and their ability to make the companies

16:10that's legible to investors is like obviously very important to their success. There's going to be a CapEx intensive play up front. The reality of the financial landscape for all of these people is I'm not a research scientist, you're not a research scientist, and all of the capital is not research scientists. It's on entrepreneurs to go explain their story. But one of the challenges is there are a lot of people attempting to invest, as they should,

16:40in technology bets. It varies how much fundamental understanding there is. There's a lot of proxying of judgment to pedigree or to other legible signals. Who's invested? References are always good. Who are the referral sources? And so the decision making is less fundamental. I asked a extraordinarily good investor friend, we had a debate like you do, and I was like, I don't understand. What is this company going to be that would be big? Explain it to me.

17:11His explanation was essentially, do you know the quality of this person? Yes, I've known the quality of the person for eight years. The technical theory in the business don't make sense to me. And people are making large-scale research bets without any intuition for them or without any opinion on them. And I'm like, it's not all going to work. And I may not be any better at deciding, but we want to get to that intuition. And I think not having a point of view on the business besides the pedigree of the person

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Extraordinary Robotics Researchers

19:13Who is a researcher that has most blown you away and how did they do so? What's something that they did that to you felt extraordinary? Back to the great person theory. There are a number of these people who I think the history books will write about a contribution of theirs as a truly extraordinary thing that created this kink. What's an example of a person like that and something that you've seen them do? My partner Pranav and I were introduced to Tony Zhao and Chang Chi at Sunday Robotics when they were PhD students

19:44at Stanford. They worked at Toyota Research and DeepMind and Tesla and so they weren't just academics by any means. They were young PhD students who I think they were like 25. I think one of them didn't finish, they just like started the company. What I thought was impressive about them then and then now. I remember looking at their body of work, took me a while to get oriented, but I think that they have contributed dual-handedly most of the interesting ideas in robotics AI over the last four years.

20:14That's a pretty weird thing for two very young people to do. If I try to characterize the type of ideas, it is how can I use modern AI to solve the robotics generalization and robustness problem in a very practical way. It is believed in robotics that if we just had the internet of robotics data, yeah, we'd have fully general robots everywhere that's clearly going to work. One of the big research and practical problems is like, where do you get that data? Some of the ideas that Tony and Chang

20:45have worked on is how can you be clever about collecting the data in the cheapest way possible in a way that supports the distribution of real-world environments and tasks. And so I think the creativity of thinking about the actual constraints, we don't have the data, we don't have incident dollars to spend on the data, and we're going to treat it as a technical problem to solve of the shape of the data and the collection and how does it interact with the model and how much of this cheap data collection can we transfer

21:15to model learning. That's super interesting. That's very outcomes-driven. I was blown away in the first meeting. We said yes immediately there, thankfully. It's just under two years that the company has been around. Nothing is true until it is shipped. This entire team believes that we are going to have general semi-humanoid robots doing things in people's homes first and beta end of this year. That is not something that any of us believed. It blows me away that you can move that quickly

21:45from a bunch of cardboard in a Stanford basement to the full-stack thing that is manufactured here we have done hundreds of iterations of hardware on model data collection and translated it into tasks and tested it in all these real-world environments. It's going to work. The videos are very cool. I think the speed of that is mind-boggling. I still think the broad view, not everyone, but like lots of people in robotics are like, now it's a question of when, not if. It surprised me

22:15that the team was like, if not this year, next year. I'm very curious about the moments of your investment decisions. Like you just said in the first meeting you were sort of like, we're in. Is it always like that or are there examples of things where you like hem and haw, you end up doing it and it works? I would love to hear more about how you and your team make investment decisions.

Investment Decision Process

22:34The actual

Investment Decision Process

22:35in-the-room process for, okay, this thing is interesting, we're going to do it or we're not. We're debating it. What is that process? What is it like? It varies based on company. I'm very instinctive on people. I often know I want to do something immediately. If I know what somebody has worked on and then I interact with them and I hear the idea and I have some basis, some background in the idea, we have a rating scale, a one to ten scale. I'm like immediately an eight or a nine. What I'm then doing between that

23:05and a real decision is often figuring out what are the holes in my understanding, where my judgment of their premise or them is incomplete or wrong. What do I not know? If you're an investor looking for the most ambitious, impactful companies, you can't know every domain. We have biology and defense and robotics and law. I'm like spending the next day to a few weeks desperately trying to ground myself and being like, okay, what does everybody

23:36else believe about this space? Are they the people I think they are? That's what my process looks like and then I want to get feedback. I want to get like second reads on people. I want to understand what the core questions are. I'm a memo person. Even at the very beginning of the firm when it was just me, I would like write the full memo, perhaps Greylock style, ship it off to a friend that was an investor who I trusted for their perspective outside of the funds. You and I have talked about what do you value about a partnership? And I'm like, I'm comfortable making investment decisions,

24:06but I think other people can make me better. I want people to like push at the logic and have me reflect. So I used to like take the memo and like send it to John Lilley or Dylan Field or something. We ran a memo. I go see what Bella or Pranav or Mike wants to know about the person, try to complete the picture. Other people, I think, are like more even in their decision making. They're like thinking about it and thinking about it and they climb to conviction versus I start there and then I like work backwards. But I think a similarity between both Mike and I

24:38is we'll start at a point and explain what will move us. I met a really interesting company earlier this week with my partner Bella and I'm like, okay, instinctively, I like am positive on it, but I don't know enough about the science here and I have to like go make sure this makes sense. Can you really be an eight or a nine if you don't get it? No, I could get there. Now, as we were talking about, is one of my concerns for this period of time where I'm like, if you don't feel like you have any grounded intuition on the bet itself,

25:10what are we doing here? I'm trying to think about if that's fair. If Brett Taylor wanted to like Yeah, that's like what's the limits of that. dig in volcanoes or do dog streaming or something, I'd be like, yeah, of course, man. But he wouldn't do that. There's some version of I don't even care if it doesn't compile in my brain, the person is so undeniably good that I would just back them. Brett, as an example. Yes. I feel like these things are so inextricably intertwined in my mind because part of what makes people great, like I was trying to help

25:40one of my companies, the candidate, yesterday, and they're like, oh, what did you see in these people? And I'm like, they're just so right. He's right all the time. Their industrial logic is impeccable. They have all these great character traits, too. They're amazing at recruiting, but they have a point of view that I think is going to be right in the world. I've seen them just make repeatedly correct decisions, including when I am wrong. And I'm like, I have a lot of respect for that. When you say, like, these people are amazing and part of what I think makes them amazing is I believe in their judgment.

26:10If I don't understand what they're doing, I can't have an opinion on their judgment. Brett's doing enterprise AI. I understand what he's doing. If I were to build a pie chart of your time now, not when you started the firm, but today, there's meeting new companies, there's helping existing companies, there's talking to researchers, there's time with other people, there's talking to candidates. I have no sense of what it would be. If you had to sum it up, what are the things that you spend your time on and what's the percentage allocation? I think I spend two-thirds,

26:42three-fifths of my time working on portfolio company stuff. And that is recruiting, helping people think through things, trying to influence the outside ecosystem in some way. Then, raising money. The next largest piece is looking at companies. I don't know if this is right or wrong. I get paranoid about it and move the number, but I probably see four to six new companies a week. It's not a very high volume. My first couple months at my old firm, I saw 500 companies. So I'm like, wow. Now I feel

27:12more calibration where I just have much more confidence I can tell. The balance of my time, I am doing a combination of help one of my partners look at something, meet people that might teach me something about the world. And that can be a researcher or if you are purely early stage in a larger firm, you can be very myopic because your ecosystem is big enough. And we are a very small firm or ecosystem oriented. So I've learned so much from just getting to know investors who think differently than I do, including different asset classes.

27:44Well, I never spent that much time with public markets people before. And it was very educational how they think about the world. I spend time with other investors of all skills and asset classes. I spend time with companies right now with a pharma company who is thinking about how AI is going to transform their business. This is very interesting to me because I've learned a lot about what they believe about the future. I've done a lot but I'm like leaving room in my calendar for learning, feeding curiosity. And then there are pieces

28:14that are other parts of bridges to DC, external communication. Where have you learned about raising money?

Raising Money and Firm Philosophy

28:20I stand with the belief that I advise entrepreneurs with which is you should understand people's objections to what you are doing and their questions but you should not tell them what they want to hear. When I started the fundraise for Fund One, I knew a lot of LPs over a long period of time already so it was not very complicated. But I had one of my friends who is a private equity investor who stated you have to have like a very differentiated story

28:50for LPs. Every part of the funnel should be the specific thing you're going to do and I'm like let's be honest I don't know yet but I need to like raise the money so I can go experiment and figure it out. So I never made slides and told a specific story about all the things that we attempt to do now. I think you don't know until you make contact with reality and like think about it and you're in the market. There were definitely LPs who did not like that. I like gave people a two-pager on my background and investing history and claimed

29:20that I was good at identifying extraordinary people being useful to that set of people and being genuine supporters. If you combine that with investment judgment and ability to recruit you got a starting point. Mostly some things I imagine about firm culture and then we'll go execute like hell and figure it out. I can see how this is tough from an LP perspective and I deeply value the people who bet on us early because they go write a memo for their investment committee and they're like she's going to execute

29:51like hell. We'll find out. Sometimes the cleanliness of the story is what people are looking for. I can't advise other managers on this because people have different outcomes. If you tell people what you are going to do life is much simpler and what you actually believe life is much simpler and for me as an investor when somebody can convince me that the world works differently than I thought I'm like immediately incredibly excited. Maybe I can convince people that this is just how it actually works. I've met a lot more investment managers for the last four years.

30:22I knew a lot of BCs but people who are doing creative things. I really like entrepreneurial investment managers as you I think do and as you might imagine where I'm like I don't want to build the firms that they've built but the creativity with which Philippe and Thomas go to or that Josh at Thrive approach their business and the encouragement they have for others to approach their business. Well you can do new things and you should go express your opinions in the form of your investment management firm I think is amazing. What was imprinted on you watching your parents

30:54who are both entrepreneurs? I think this is very helpful to me because there was no moment of my childhood or being a teenager where I felt like they were not there for me even though they worked all the time. On stop. Both of them. We try to resolve these things. I was a pretty independent kid. That helps me. I don't know where I was in the distribution but I feel like I was pretty independent. It helps me to think your family can make you feel like you are the center of their world but they're whole people

31:24with other interests and they want to spend time doing other things too. Even just recognize my own importance from the perspective like remembering what it's like to be 10 years old. I liked my mom. I love my mom and dad and it was so cool. Our family values are very similar to theirs. Integrity. Thinking for yourself. Independence of thought and then there's like focus on family. Team spirit and family. The independence of thought is probably the least generic one of those. I think a lot of people like want to be good and kind

31:55and work hard and whatever else. For both my parents it was a moral issue. You cannot ever worry about what other people think. I'm like far to that side of the spectrum but I do think about it sometimes. You do sometimes worry what other people think? Yeah. What do you want them to think? That you worry that they don't? I worry about raising people's competitive hackles in the ecosystem. Why? Because I'm a friendly person. I want to be friends with everybody. I don't mind competition but the sometimes pure

32:26zero-sum competition stance of traditional series A firms series A series B firms that says I'm going to own 18 to 25 percent of this company and take the board and you're going to own none of it is not conducive to like a lot of collaboration. There are issues with that from an incentives perspective but the public markets orientation people are loved to tell you about their best ideas pile in after them. This is an extraordinary situation. I would love to talk about why gaming

32:57and entertainment is going to be totally different and people are super under indexed on it. There's part of that orientation that just appeals to me as a very positive some person.

Parental Inspiration and Cynicism

33:06I'm always interested

Parental Inspiration and Cynicism

33:07in sources of inspiration. I'm curious in two ways overall in your life who has inspired you the most and also right now in this very moment who is inspiring you the most and why? I saw my parents build a company and I was like this is so cool. It's us against the man. The man is very big company. The man is trying to kill us. We can still do it just because the technology is better. The product is better and the customer will want it. My love and ethos goes to entrepreneurs. You can make something out of nothing because you see

33:37a better future and you can do it really fast. These things appeal to me in terms of what I want to try. There's so much courage in that and optimism. There is something poisonous that bothers me today where I think especially like the post-Gen Z entrepreneurial crowd think it's like all marketing and brand is real. Building a network is totally real. No one denies that but when folks are very cynical about how the world works, how entrepreneurship works,

34:07that it's just nepotism and Twitter is useful, I think that's nonsense. If you focus on value and treating people well and you work with extraordinary people and the vision is worthwhile, that works more times than you'd think. There's so much cynicism about playing the game, be it marketing or fundraising and I hate that. Codd is like this. I find him very inspiring and Tuhan is like this. I find him very inspiring where he's just like if we just do the right thing by the customer, we will win. Feels a lot more complicated than that.

34:39I think he's right. That seems to be working. One of the huge debates right now is what to do about the fact that there are open source models not American made which are competitive at the frontier of performance of AI models and seem to clearly have been at least to some degree based on the work of American models. What to do about this, what it means for the future of AI. Companies love open source because they can build their own thing and Base 10

35:09and others that serve a lot of inference work with a lot of these models. How are you thinking about what's right, what should happen, what will happen, the implications for business?

Open Source and Compute Independence

35:19This is a big, hard, important, interesting question. It's a big question. My point of view on what is healthy for businesses, America, the ecosystem, individuals, and then there's what's already actually happened. The reality is we have, over the last three years, increasingly competitive open source models from all fronts. Largely China, but definitely also the U.S. and Europe. Most recently, Thinkie, Poolside, People Waiting for Reflection, NVIDIA models, Mistral. We will have very powerful

35:49and already do have very powerful open source models from Western countries. The cat is out of the bag and these are in use everywhere. Even if you have no economic point of view on the labs and you just say, how is the diffusion of capability going to happen in the economy? There are a huge number of instances where it is too expensive, too sensitive, or too slow to use the model

36:20from the frontier providers today. And I think that's going to increase as we learn how to do more things with AI because it's actually quite expensive. It's objectively true that if the capabilities are more democratized, you will see them used in more ways. I want to see that happen. I do think that it would be irresponsible not to understand the safety profile of models as they progress because you just draw the line. we have companies that use

36:50frontier model capability for defensive cybersecurity and for biology work. If it works for those use cases, it obviously also should work in similar ways for the offensive use cases or the bioweapons, biosecurity use cases. We just need to look at that reality and think about what are the other ways in which you control this. But attempting to stop technological progress and openness around it,

37:22if you did restrict use of open source models in the United States, you'd basically just restrict law-abiding American businesses and slow them down or move profits to different pockets, prevent certain uses of them because the actual attackers or people who have adversarial uses of these things are not affected by your restrictions. You're restricting your own people. My view would be there should be testing and understanding of

37:53these models at the frontier. People are very worried about backdoor-like behaviors in Chinese models. The thing to do would actually be like have a very rigorous set of safety testing on that. Like, let's go find out as much as we can instead of talking about how there might be this issue in a speculative way where there's not been nearly enough actual research on it. The future where there is broad access to intelligence too cheap to meter, as Sam put it,

38:23that is coming. It will be supported by open source. Businesses want it to control their own destiny for economics, for capacity. If given those models and the increasing democratization of the skills to post-train these models, build harnesses, use tasks, the economy is so big. Every individual has these use cases that are not going to be imagined by a researcher in a frontier lab. You can't imagine the diversity of reality. Even if you trusted the models to go

38:54figure out what to do, they have to get there. The best way for that to happen is an ecosystem of businesses, as we've always had in the economy, cheap infrastructure. Do you ever worry that an alternate version of U.S. history is that there was energy too cheap to meter because we built 1,000 AP-1000s or something, much like China is doing now in nuclear. And just a set of circumstances happened such that we just didn't get that. Do you ever worry about that as it relates to intelligence? It does seem inevitable that we're going to have abundant, accessible,

39:25low-cost, valuable intelligence. Can you imagine a world where we don't? Yes, absolutely. And I also think I can imagine very easily a world where we don't have that in a competitive way because it is essential to economic competitiveness and national security. There is not a version of the world where we rebuild our industrial base without automation in the United States. If we don't import people and our people are expensive and we lack some of the skills but want to produce a lot more goods and have a more

39:56resilient supply chain. It just doesn't add up. Who's going to produce this stuff? People in the United States do not want to work and should not want to work for $13 an hour doing a very inhuman job. I don't think it is inevitable that we are competitive and I think we need to like make that decision actively. The version of it that I think is very possible is that people are rationally afraid of the impact of AI on jobs or dislike the capture of rent by a small

40:27number of technology firms rejecting the idea of being in the permanent underclass and then connecting that to a anti-capitalist orientation. That contingent of thought can slow down build of energy and infrastructure and industrial capacity. One of the most important inputs is compute. If we don't have it we're naturally not competitive or we're at least not independent. I think we're going to start talking much more about compute independence. That's a big problem.

40:58So on this point of compute independence, what does that mean? What are the missing pieces of compute independence? Like the most obvious one might be more leading edge fab capacity here in the U.S. or something like this. There's all sorts of stuff upstream. There's particular kinds of glass very important that's controlled by basically one company that TSMC has like a monopoly on the supply of. There's all these component parts. But if you think about compute independence, like if so much boils down to compute, what's to be done about it? Are you trying to invest in companies that are solving that problem? What is the problem?

41:29Say a bit more about what it will take. Well, if you just work backwards from a data center full of GPUs, cooling, powering, training, and inference so we can support the use cases, all of those inputs, it actually looks a great deal like energy independence or something like that. All those inputs, there is a global supply chain. I've got my TSMC mug with me. There are parts of that supply chain that are like a very thin sieve in a place that is not necessarily stable or accessible to the

42:00U.S. and allies. A different version of the world that will take a bunch of investment and national security and energy policy is, for example, Jacob Hellberg is working on something called Paxilica and it's like, okay, for every part of the supply chain, can we invest in more capacity and figure out what the independent paths are? I don't think that means it's all got to be created in the United States. Comparative advantage is real. But having more than one source,

42:30is a position that everybody wants to be in. When we think about the components that we've invested in, we've invested in the labor gap for data centers and robotics, we've invested in nuclear energy, we've invested in alternative chip architectures. We keep looking at people who are essentially data center builders, solar and battery installers of some kind. Part of this is the actual capacity build-up. That's a very operational business, like somewhere between operations, some technology and real estate.

43:01Financing, yeah. And financing. Absolutely, that's probably the dominant thing. We have not invested in it yet, despite looking very closely. I'm not opposed to it, but fundamentally I'm a technology investor. Like, I want to understand what it is that is the durable product asset people are building.

Debates on Biology and Ventures

43:18What are the biggest

Debates on Biology and Ventures

43:19debates inside of Conviction? You've got such an interesting team. Mike, your partner is a very technical person, amazing engineer. The young talent in your firm brings really interesting perspectives. So I'm imagining great, lively debates about things that matter, etc. What are the big debates today? A lot and I have a podcast called No Priors. This premise of some of the things you believed, especially about markets as a pastor, like no longer true, is an interesting one. And regularly we look at companies in

43:50domains that are not traditional software domains. Not even traditional software domains, but can you make money in this market at all? Venture investing in semis companies, lip-boot-tan aside, was like a god-awful business for the longest time. The returns... Everyone told me this. Yes. It was really bad. That's like an example of Bella, a partner on our team, started looking at a bunch of these companies and it's obvious that the demand is there.

44:20Now I think we have arrived at the conclusion that we others are as well, which is, well, the market is different today. We are seeing consolidated at-scale demand for accelerators or even supply chain independence because the big buyers of it want it too. We can't all be stuck on one line at GSMC. All of that is very, very valuable and that changes the risk equation for these companies. We start with pretty aligned beliefs about

44:52the direction of travel or the problems that are worth working on and then a lot of the debates are like, is the market friendly to a venture-backed company or not? Space is not a friendly market to a venture-backed company, but is it possible? Is the distribution of outcomes worth betting on? That could be true in solar and batteries, in nuclear, in turbine manufacturing, in robotics, in biology. These are not your favorite software markets from 10 years ago. Each of them is a new debate.

45:22Biology is an interesting one where by virtue of seeing the data empirically, I have now strongly moved to one side of the debate. What side is that? You can create and capture enormous value with models in biology. And there could be different AI software in biology. We're the first check in a company called Chai Discovery. And Chai is working with a number of top 10 pharma companies in really significant ways to accelerate some part of the R&D process.

45:53The conventional wisdom when we invest in this company, and I've been looking at computational biology companies of different sorts for five plus years at that point, the conventional wisdom was the only way you make money in biotech or serving pharma is by make a drug and then get biobux deals and then decide how far along that risk path you want to take. And what that means for the capital structure of the company is, okay, the great traditional biotech firms find these principal investigators and they own 40% of the company and they're kind of assembling these

46:23things, turning them into candidates. But most of it doesn't work. So it's just like a very different distribution of outcomes and structure and way to invest in businesses. Dumb software investors, you can't make money selling software to pharma or build platform businesses at pharma. The debate is, does it change with models? I'm a strong yes. Now we still have a question to solve on regulatory. There's the speed of the physical world and safety is not something you can overcome easily, but I

46:54think we should see a massive acceleration in cures. What flipped that for you? What evidence did you see from we don't know yet? We invested when we didn't know yet. As part of the fun adventure, we were like, it is possible that it is worth trying. There's no genius here. That's a $10 million contract. The other piece is actually you just talk to the scientist at the customer or somebody who leads a user of the tool, or you see there are also end user adopted tools, product

47:25led growth tools that are working in the space. Well, the customer knows if it's valuable or not. The light bulb moment for the industry is when we will have a new indication or a new drug that clearly the trajectory of the thing was changed, created by AI. We should see a huge wave of investment and rightfully so, but it's going to happen. I'm like very impressed by the speed with which pharma and healthcare overall has said, yes, this is going to make a difference and we actually think it's going to change the business.

47:56Why do you call it conviction? It's aspirational. The most traditional form of early stage investing is you start early with a company, you have a significant position, you never sell the position, and you work on the company until it works or is sold or dies. There's wonderful alignment and simplicity to that. Mike and I have both had the benefit of being part of the journey for some companies where it took a minute to begin to work or it's like not obvious at the beginning. Sigma, Notion, Rippling, you wouldn't bet on a

48:26company hoping that it's going to take four or five years to like find the thing. I think everybody is a product of their own experiences, including investing experiences. The first couple years at Base 10 were like very non-obvious as well. The ability to take a point of view that is not obvious in the market because the market or because of the people's backgrounds, whatever reason, and then just suspend doubt and act with full belief until it's true or not.

48:57That's a great way to be a partner to somebody building a business. I am trying to build a partnership and I deeply believe this is a team sport. I was talking to a friend who runs another investing firm where he is like we don't have individual ownership of our investments and I'm like that is nonsense to me. How could you run a business that way? Because somebody has to own the decision. I don't know if this is right or wrong but I don't know any other way to invest by saying Patrick you must make the decision. Do you believe, convince us, how can we help you

49:27make that decision? What have you learned about risk taking? Behind conviction it sounds like there is often a leap of faith of some sort. Obviously if you knew everything and it was obvious that would be priced in and there'd be no return opportunity. Is there always a leap of faith? Is that risk taking by another name? Unlike my good friends at Founders Fund, I don't have an instinct to be contrarian but I do think it is so fundamental to decide what you think and not worry too much about what other people think.

49:57Other people is the dominant narratives of the period or even what different players in the ecosystem that are really important declare one way or another. I think you just need to find the truth. The way I would relate that to risk taking is if you find the truth and it is wrongly priced and you hold on to that, you're in a good position. You want asymmetric information and then the confidence to like hold the opinion when other people haven't come around to it yet. I think a lot about how to make sure we have the information that is better than other people's

50:27and then protect ourselves from noise. Describe that in one more level of detail. That's a great way of asking like what conviction looks like today. You're building that shell. What are the keys to doing those two things well, both having the truth and protecting yourself from the noise? I like want to spend my time when I'm learning about the world from somebody who is making it happen, our portfolio founders or the many founders who are doing amazing things outside of portfolio who are doing something that surprises me or advances the frontier or like really

50:58smart believe something I don't. There's like three different categories and I'll give you an example. Mikey Shulman at Suno is building an amazing business doing music generation. Shame on me. I knew Mikey, a mutual friend of ours who's an investor like asked me to like invest and I stupidly said no. But I was just like, oh, I don't think that many people want to make music. I make music. But can you turn into a social network? How much consumption is there going to be? A lot of questions. My intuition is just wrong. It's been actually somewhat wrong because I have

51:28underestimated the amount of expression or entertainment and creation for a lot of AI tools. I've learned something here by talking to Mikey about his business and what people are trying to do. So if it is founders who have companies that are creating a behavior you don't understand, somebody working on research in an interesting direction, businesses that are like, here is my plan for AI, all that is super educational. I think the circular logic sometimes of what

51:59do people believe about the big lab strategy today? How can any of the applications live? It's actually not that instructive for your decision making. The way I think of it is any organization has a couple key priorities. Let's assume the priority for OpenAI and Anthropic and DeepMind is AGI or ASI in a safe way where they capture a lot of profit. The priorities that ladder into that probably look like ChatGPT, ads,

52:32coding, maybe there's an expansion after that, co-work, the ability to get different types of users to do richer tasks and more interfaces. I think you have to judge the actual competitiveness of any of those efforts, the reasonable scope of them, and then look at them relative to each of our companies or opportunities that we're looking at. Coming up with some grand strategic framework for like what layer is going to win here, I think is not useful to me. And I feel like people spend so much of their investing energy

53:02thinking about versus I want to spend my energy figuring out if we're 1% of the way in, what is the next 99% of diffusion? That's where we try to direct our energy. For fun, as we wind down here, understanding this is like a purely speculative question and it's meant more fun than raw prediction. What are some things you think are true a year from now based on all these incredible people that you're close with, the research community, the entrepreneurs like the Sunday founders, you add it all up, things are moving fast. A year is a long time and it's like

53:33reverse dog years now. What do you think is notably different about the world of technology a year from now? I'm hopeful that a year from now we see Jevin's paradox in practice as we have agents and products that do more of the mundane more effectively in all the domains of our lives. It should look like the transformation that has happened in software engineering. You have companies, I have companies where they're like, we're just going way faster. I expect that some

54:05analogy like that will happen everywhere else. And we see it in our companies where I'm thinking about in one of our portfolio companies, the marketing department is like a person in the house. This is a company that serves lots of customers. They need to do very traditional things, sales enablement content. What happened was the guy in charge of marketing is interested in like creating leverage

54:36for himself. And he's like, I made an autonomous marketing department for us, the company. In every function, as you learn faster, do less of the mundane, you will repurpose that time somehow. Do you work less now that you are more productive with AI? Yeah, I work more. And I think this is like a core wisdom of Jensen's, which is we're all going to be more employed and we need to make sure that people are given access and education to the

55:06tooling that will allow that to happen. Well, what you built is incredible. We've loved through the Colossus side getting to know your whole world. It's so distinctive. You are a great example that there's always room for great, meaning there's plenty of early stage investment firms when you started conviction. And yet here we are four years later or whatever. And if you ask the people you've worked with, you've made a real huge difference in their lives. There's just always room for great. I think that's like a great, awesome lesson, especially because I love how you described the early pitch was not like, here's how

55:37we're differentiated at every level of the funnel. We're just going to run at this thing. By the end, I got so frustrated. I was just like, it's an execution game. Totally. I ask everyone the same traditional closing question. What is the kindest thing that anyone's ever done for you? I love this question. I'm going to give like a collective answer. I think there are so many people who are extraordinarily accomplished in Silicon Valley who care very little for pedigree as soon as they have a conversation with you and they're like, maybe you can help me or you have an interesting

56:07idea or maybe I just think you're promising. And the dominant factor in their own willingness to invest in a relationship or a person is just their assessment of the idea and the person. I think that's amazing. That is not how most ecosystems work. And so Ashim Channa and Anil Bustery and Joseph Ancinelli and Reid Hoffman who hired me at Greylock. I started when I was 23. People love to make fun of young VCs where they're like, ah, what a barnacle on the ecosystem. It's a terrible experience for entrepreneurs. I don't

56:38know anything. They're trying to advise people who gave this kid money. And I'm like, well, one, my job was just to make other people successful at the time. You can take any task in any job and just try to be great at a task with mimicry and first principles thinking. We hire earlier career people at my firm, but I do think, oh my goodness, thank you for taking a shot on some random person and then investing the time to like teach me how to be investor. I think there were a few people who gave me advice starting

57:10the firm who I think they would think of this as entirely trivial. I'm just giving you my opinion, but Ravi Gupta, who is now co-CEO of a new thing called Ithaca, Dylan Field and Elena Natalinski, John Lilly, who's been a longtime partner and

Gratitude and Mentorship

57:25friend. There are a few folks who were just like, you can definitely do it. I was going to do it either way, but having the encouragement of people who believed that there was room to be great and including some of our first LPs, I will be forever grateful to, I guess, the people who took risk with me. It's beautiful the world runs on faith, belief without evidence yet, and still conviction in someone's ability to do something. Pretty cool. It's faith in people. We talked a lot about how people's ideas and our

57:56opinions of them are intertwined, but I think that's a beautiful thing because you don't need any particular advantage to have an idea. The fact that folks will evaluate that and put faith in us, I could not be more grateful. I've learned a lot watching you operate and talking to you. This has been really fun. Thanks for having me. Thanks. If you enjoyed this episode, visit Colossus.com. You'll find every episode of this podcast complete with hand edited transcripts. You can also subscribe to Colossus, our quarterly

58:26print, digital, and private audio publication featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at Colossus.com slash subscribe. You know how small

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