AI investments, VC ecosystem geography, and VC hypocrisy | E1956

0:00Jason, I know you're in mourning. how are you holding up uh with the knicks uh we had a great season it was a battle of attrition uh you know if we had had our full complement of all-stars oj mitch randall uh at heart we would have demolished the pacers they would have been swept or gentlemen's uh sweep we've made it through this uh series i was looking to come to a game with you jason when i'm in new york in a couple weeks but we had you got to get deeper in the season in the playoffs i you know i got lucky i got to go to two of the games versus the the 76ers uh with david adelman uh who's one of the owners and a friend now and that was a great rivalry i'm sure that rivalry will happen next year in the pacers uh you know now they're on our list but anyway this isn't this week in knickerbockers or the nba this is liquidity where we talk about we have the conference coming up in two weeks yes we'll be in napa in two weeks what's the latest on the conference it's just a great group We got a last minute surge of people who wanted to come.

1:02We tried to accommodate as many as possible. I'm trying to keep it. I was trying to keep it to 100. It's probably like more like a 125 right now, but it's just GPs and LPs, high net worth individuals who are angel investors and LPs and then everybody in between. And it's just a way for us as a community to get together, have important discussions without founders in the room, without service providers in the room, just focused on that lpgp startup investing and support uh system and how we look at the world and it's going to be a lot of like sunday monday tuesday night poker late at night uh you know activities incredible restaurants incredible presentations and just really like a really well utilized 72 hours of your life so you get in there sunday night we end on wednesday with a brunch it's just really productive uh in terms of work so if you're going to take a couple of days off and you're a gp or an lp this is the event to go to i'm going to do it twice a year i want to bring it to uh maybe la new york abu dhabi dubai you know other places in the world where people are getting into capital management and so yeah i'm going to be looking for partners around the world to do this very cool what people have been asking me what the buy-in is for the poker games We're going to have, I think, five or six tables this year.

2:24There'll be two or three tables dedicated to learning. The big game will probably be$100,$200. And these are all points. We're not playing for actual cash. It's points. It's not Molly's game. It's not Molly's game. Low stakes, everything for charity. Yeah. And it'll just be a lot of fun. Excellent. Well, we have a great show today. I'm excited to get started. Let's do it. This Week in Startups is brought to you by Squarespace. Turn your idea into a new website. Go to squarespace.com slash twist for a free trial. When you're ready to launch, use offer code twist to save 10 % off your first purchase of a website or domain.

3:06Open phone. Create business phone numbers for you and your team that work through an app on your smartphone or desktop. Twist listeners can get an extra 20 % off any plan for your first six months at openphone.com slash twist. And Lemon.io, hire pre-vetted remote developers. Get 15 % off your first four weeks of developer time at Lemon.io slash twist. Welcome back to this week's Liquidity Podcast. With me today, I have Michael Eisenberg from Olive. Next, we have Jaime Mattis from Envariantes, a venture fund of funds. Of course, we have Jason Calacanis from The Launch Fund. I'm your moderator, David Weisberg, co-founder of 10x Capital.

3:52Today, we have several great topics to discuss. Pitchbook has released data detailing the breakdown of AI investments by category. A well-known CEO lashes out at VC Hypocrisy, we discuss. And we take a look at fundraising by region. Bay Area is in first place, but there are several surprising results. Let's dive right in. PitchBook has released data summarizing the total amount of capital invested in AI in 2023 across several different use cases. We talk about those use cases often on the show. We have vertical applications, which have raised$27.8 billion in 2023, with horizontal platforms taking down$27.1 billion, autonomous machines raising$3 billion, and AI and ML semiconductors raising$2.4 billion.

4:36Michael, you're right in the thick of the AI ecosystem. system. What's your strategy at Aleph when it comes to AI? And what kind of startups are you looking to back? So we've actually been doing this AI thing since 2013. In fact, in the original slide of the first Aleph fundraising deck, we talked about it. We went out to pitch LPs. The argument we made was just like Benchmark Capital, where I was previously got started in 1994 when the internet came along. So it was time for a new fund in Israel to take advantage of this AI, machine vision, deep learning revolution. That was in 2013. In fact, the first AI investment we made was in 2013-14, which was a company called Windward Maritime AI, now publicly traded in the UK.

5:20In 2015, we backed Lemonade, which is the first AI insurance company. And so what I think is new in the world is actually not AI, but LLMs. And those two terms have become conflated in current discourse. And we have, in general, avoided foundation models. in a big way. I'm in the Gavin Baker camp on that, that this is the fastest depreciating asset in the history of technology. And our focus since day one has been using AI to transform existing legacy industries. So super vertical focused, vertically integrated focused. And we've kind of attacked this kind of application layer. And we'll talk about it later.

5:59We talked about the companies, but we did Dream AI, which is building kind of AI to protect critical infrastructure in nation states and spines, which does AI for book publishing and lemonade and insurance, etc. And that's kind of been our strategy since day one, and we've stuck to it. Yeah, you mentioned it's that's the fastest depreciating asset. That seems to be a view that a lot of people are having in the last month or so. What made you determine that early on? In general, when we think about data, we ask the following question, do you have any data that is proprietary? Because that gives you edge at the end of the day.

6:34And so So if you look at our, again, early on investments, Windward handled maritime data, and it's paying off in spades, by the way, because nobody could accumulate that data. Much of it was proprietary. We can do things with it that nobody else can. The LLM race is a race to access all of the world's data. Inevitably, that's not going to be informed by something that's proprietary. So the moat on the business is very low. And I think there's kind of two ways to look at venture-backed businesses over time. One is growth. That's the obvious one. The second one is kind of Michael Mabusian's model, which I think Bill Gurley's covered many times before, which is about competitive advantage or cap, as he calls it.

7:12And we think competitive advantage comes from having proprietary data and deep integration up and down the vertical stack in this space. So, for example, if you look at Windward, they started actually tracking ships doing nefarious activity at sea. It was bought by governments. Ultimately, that moved into supply chain because boats move at sea for supply chain. And now it's handling container management using AI and automating the hell out of the way freight forwarders and others handle containers at sea and the ships that come in. So it's super, super, super high moat to this business because it's 11 years of collecting proprietary data and then applying it and integrating it into systems.

7:54The same is true of Lemonade, which is we have the super proprietary data around insurance when everybody else is working off the same kind of data that they purchased. And because we built this through interactions, we're just better at pricing, better at risk management, and our operating costs are significantly lower, and it's all proprietary. Jaime, you're a venture fund of funds, which means you invest in the top emerging managers in the space. We're really bleeding edge when it comes to AI. What is the next wave of AI startups, and where does Alpha accrue in the space? fantastic. So one thing all of us, I think, agrees, this is going to be one of the best vintages in the history of VC, and a good portion of it will be the impact of AI and economy.

8:41From Invariantes, we built this amazing puzzle of 20 VC funds and 35 startups. We have exposure with this strategy for more than 600 startups. And we are likely to have exposure to 100 and 120 startups doing something around AI. So when we focus our efforts in AI through the fund managers we bet on or the direct tickets we do, we are focused on five waves or five spaces in AI. The first one, I think, is hardware and semiconductors. This is one of the strongest space, and we have seen amazing companies like Brock doing something really great. Here, we do the pigs and shovels bet from invariante side, and we bet one good example is Lambda Labs.

9:35They are building this amazing GP cloud infrastructure for engineering and research teams, and they are doing really great. Then we have the second space for us is the infrastructure or platform space of AI. There are some really great companies doing interesting things besides big LLMs that are more focused on the consumer side of the market. There's, for example, Contextual. They are building this enhanced model for enterprise use that is more reliable, more accurate, more secure, has governance and a lot of stuff for the sector specific. So we are really bullish on that part as well. So 50 % of our portfolio will be to those two spaces in the AI ecosystem.

10:17But then we have the vertical side of AI. We are betting on four spaces, health tech, fintech, or financial services. I think future of work and mostly with voice recognition has a strong potential for AI applications. And then I think the last sector is still a work in progress. Besides that, we also invest in the horizontal side of AI. Here we see more transversal or more general purpose applications. There's a really cool company out of Colombia operating in the States called DAPTA. They are building this automation platform that has this quick integration with all the suite of application business use on the day-to-day basis.

11:05And they are doing more on solution approach rather than a tool approach. So that's really exciting because it generates faster adoption in the market and quicker product market fit. And then last but not least, I think the autonomous vehicles and robotics, I think it's one with the most potential in terms of AI. We did a strong bet on a Canadian startup called Optimotive. They are building this incredible workforce, robotic workforce for extreme environments. So if you see the AI landscape as an ecosystem with our portfolio strategy, we're trying to rely on power law distribution. So to seek that alpha, we are trying to do this really disciplined bet across funds, across direct tickets, and trying to weigh that 20 % of our portfolio on this sector.

12:03And I think we will be able to find two or three companies, outlying companies, gain all those outsized returns we are looking for. All right, startups, you ever notice how successful businesses are constantly evolving? They're constantly adding new features and you get that product velocities. Well, that's why I am all in on Squarespace and you should be too. My pals at Squarespace keep adding new features and revolutionizing their platform all the time. week after week, month after month, year after year. And they've added AI. Squarespace Blueprint AI is amazing. It's their guided design system for building a new website.

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13:18And this blueprint AI tool is something to behold. Check out squarespace.com slash twist for a free trial. And when you're ready to launch, go to squarespace.com slash twist to get 10 % off your first website or domain purchase at squarespace.com slash twist. Jason, you just made a big bet on Athena, which is basically outsourcing and they're using human in the loop AI. So they're not an AI company, but they're using a lot of AI tools to make their EA, their executive assistants much more effective. Are you seeing these kind of AI assisted startups start to emerge that are not pure play AI? yeah that investment's our largest investment of the year uh jonathan the co-founder was the co-founder of thumbtack which i was the first investor in and i'm the first investor in athena uh you can go to athenawow.com and uh get like a discount or whatever um and they they are i think a company that will be looked at ultimately as an ai company what they're doing right now is matching you with a virtual assistant in manila the top 0.1 percent of the knowledge workers there and then as they train them on how to use ai tools and they work with you over time i think what you'll see is repetitive tasks um those uh individuals who are your executive assistants will kind of do the automation for you automatically and so i think that is a clue as to who's going to be the winner in the ai space all of these big bets that people made on foundational models i think are going to be one x investments in a lot of cases and so if you look at inflection getting gutted and bought by microsoft without getting bought to avoid like ftc or you know whatever fcc scrutiny um they are an example of i think people and humane ai is getting sold for parts it looks like i think a lot of those big bets people made because you have open source open ai and just major players building these models the models are going to be coming down to zero uh and then it is a game of data and features and focus around the customer experience which i think open you see in what open ai is doing right now their last announcement for the omni uh last week was really focused around user experience and the product itself microsoft's announcement was around laptops that have chips that allow you to record your desktop, kind of like that startup rewind AI is doing, I think it's the name of it.

15:55And Microsoft's just building that into Windows, and you're going to need some power, you know, on your desktop to do that record your entire desktop. That's a whole nother ball of wax in terms of privacy. So then if those things all become commoditized, built into the operating system, you can kind of look at them like your address book or calculator, or your phone or your browser, I don't know that their startup investing vc opportunities there but there are definitely opportunities in startups like athena or you mentioned lemonade people with proprietary data sets uh who can then build experiences and products and services for businesses and consumers that are extraordinary but i think we're going to see a massive washout of this of these overfunded ai startups that'll be the theme of the next year because uh if you start raising at a 5 billion 10 billion dollar valuation you're raising hundreds of millions of dollars or billions of dollars what kind of revenue do you need to support that so once again there's a huge gap between the public markets valuation of these companies and the private market friskiness we see sometimes and we just saw with crypto uh a far caster, I guess, is the social network that's, you know, permissionless and distributed, etc.

17:12They just raised 150 million at a billion dollar valuation with 350 paying customers. But I think those customers, at least when I went through the walkthrough pay five bucks. So that might be 100 ,000, maybe it's 1000 times revenue. I don't know if they have a million dollars in revenue or what it is. So you got to be careful. If you start investing at the sky high valuations, and have a really good idea of what's going to happen in terms of filling in that revenue. Now, we don't know the terms, David, of those deals, right? There's protective provisions. They might have a 3x liquidation preference on them, participating preferred.

17:48So maybe those folks, when they sell, they'll get 2x their investment on a$250 million investment. But anyway, that's a very dangerous, high-risk area that I think is going to be a lot of washouts. jay cal and i are around just a bubble in 96 97 2000 and he was at silicon alley as a measurement there's a lot of eyeball models that seem to be out there right now going back to that time and not enough people are around actually that that remember it right now but it really feels like that again in some of these categories explain the eyeball uh you know the engineer model i love that model uh multiply multiply your valuation by the number of engineers you hired They were literally comping in the late 90s, analysts like Wall Street analysts and certainly venture investors were comping using comparables on eyeballs and then assigning them some sort of future dollar value for what you can monetize.

18:43And at the same time, by the way, some of the platforms like AOL were often giving out ads and kind of monetizing it with warrants, so to speak, in somewhat of a circular model. Not only AOL, by the way, you know, AltaVista and others that people have long forgotten, Dogpile. And so these became proxy models. You probably remember the globe.com, Jason, which is a New York company. I wrote a seminal piece on them saying it's a bunch of hot air, and they put it in their autobiography of the time of how I destroyed the company when I was a journalist because I was like, this thing isn't worth 10 cents.

19:21Yeah. And that skepticism, which Jason is expressing then and is expressing now about these models, has kind of disappeared. And it turns out that somebody, if you want to get out of these as a venture investor and get liquidity at some point, at some point, the buy side has what to say about this. And the buy side buys future cash flows, not future eyeballs, or not even future GPUs that you happen to be running on and paying NVIDIA for. You need something proprietary, whether it's data or vertical integration or something, in order to be able to generate cash flow that ultimately generates returns from investors and the buy side is willing to invest in.

19:53And the great paradox of this, Michael, is when you look at what happened, it turns out eyeballs and attention were going to be monetizable. It's just who had the great mousetrap, the great solution to take that attention and turn it into actually the register ringing. That was Facebook, right? um and uh you know google you know they got people's attention when they were looking for information on the web and they figured out a device search put your intent in a box match that with an ad auction boom and then psychographics with facebook we know what you're looking at we know who's in your network we know what they're interested in we're going to use ai machine learning to try to just figure out the next best ad to show you and so somebody did figure both of those things out but there were hundreds of companies who didn't figure it out and those hundreds of companies were collectively worth you know i don't know hundreds of billions of dollars and then all of that got consolidated into two players maybe three google amazon and meta and so that's i guess the lesson here is where will all this activity get consolidated down into and if i were to make the bet it might be microsoft google and open ai uh meta twitter you know like the people who have the data people who have existing networks so i think it's like a a big player game right now and i'm i'm skeptical not to overstretch the comparison jason oh sorry but i wonder sometimes whether open ai is the equivalent of Overture, which kind of invented the business model that Google ended up capitalizing on because it had both the eyeballs and kind of the better mousetrap.

21:32Yeah, I think there's a chance OpenAI might become, on an economic basis, a complete washout because they have this like nonprofit kind of concept there. And then Microsoft has all these desktops. And Microsoft seems to be launching all the same products that OpenAI is in the same week. Google's doing it in the same week. Google has five, six, seven products with over a billion users, Chrome, Android, Google Search, Gmail, YouTube, right off the top of my head. These are services that have one or two or three billion users. What's going to happen when AI is just built into all of those? Well, we're seeing that with Meta putting the AI box at the top.

22:15We just saw it last week with Google for some searches, putting the search summary created by AI at the top. What does that do to OpenAI? I think OpenAI is going to be the first person up the hill. They get all the arrows. And then maybe they just are a nonprofit again. And all those users who are paying 20 bucks a month wind up moving, getting the same value from their Microsoft Office AI companion, Google built-in AI companion, that's free. Apple's AI companion, that's free. All that stuff may just be free and built in to those dominant players. So I wouldn't be surprised if OpenAI's valuation goes down from here.

22:52if i owned open ai stock right now if i was like an employee i would sell every share every share maybe i keep 10 i would literally if if i'm at open ai and i had a 10 million dollar package i would sell nine keep one million put that nine million into those other players i think one of the logical logical traps that people fall in vcs fall in is is this whole power law outcome where yes you could if you bet on all of them then you you could you could have a good portfolio the big logical trap there is that you still need that if you're going for one of every 30 companies to really be a breakout you need to have the right ownership you need to have the right entry point if your winner ends up being a 3x you invest at a 20 billion and it exits at 60 billion great but what about the other 29 companies that go to zero or return your capital so i think there's this matters backwards when i meet angel investors when i meet people who are starting their first fund or mlp somebody's new fund i just tell them entry price does matter and there's this fallacy entry price doesn't matter well if you pay you know let's just say y combinator prices for c companies we all know why combinator companies get a premium i see why combinator companies asking for 20 million dollar valuations with no revenue and then i see you know other non-yc companies that are at you know a half million in revenue and they want 15 million dollar valuations or 10 million dollar valuations i would rather invest in two of those than one yc company that doesn't mean yc companies aren't bad that are bad they might be even better teams in some cases um but then if you're building a portfolio strategy if you can make three times the number of bets or twice the number of bets and have shots on goals the chances of hitting the power log go up and so this is why people sometimes have their portfolios in their first fund go underwater these emerging managers do not have discipline around price.

24:45Yeah, and I agree with you, Jason. Discipline is the game we need to play regarding AI because there's a lot of asymmetry regarding valuations and there's a lot of noise around. We struggle every time we see a deal coming up in the investment committee. And I think you need, the trick here is to how to choose the winners and to wisely detect which is commodity, which is generating strong value. As Michael said, you need the value of the data set, the mode, the technological edge. And I think that's it's back to basics on AI and be really disciplined on your portfolio construction. And but mostly how to pick the AI winners.

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26:37Open Phone is going to port them over easy peasy, lemon squeezy, no extra cost. Head over to openphone.com slash twist to start your free trial and get 20 % off. Michael, you've been a VC for several decades. I'm very curious. Have you made more mistakes overpaying for companies that you got excited for or missing companies that because of valuation that you just... Michael's very, very old. I can tell you that. He's very old. He was like an old man when I met him in the 90s. He had like that old man energy. He's very senior. I'm joking with you. I think we're the same age. I think we're the same age.

27:10I was going to say that. Why do you always seem so much older than me? So much more mature. More kids. I got more kids. That's a recent way. Yeah. My hair is grayer. Look, I got the graying beard. Yeah. Yeah. I started to see that gray on my beard myself. Like what keeps you up at night? Other than my children and grandchildren? Yeah. Other than your children and grandchildren. When you get to this age and you've been doing this for so long, the statistics start to get against you. Like the kind of historical statistics in the venture business say that you're in your best years in your 30s and maybe early 40s.

27:43And this is a hustle business that you got to keep at every day and be excited and curious about. And so I'm questioning whether I can play at the top, you know, at the top of this business, you know, even though I'm just turned 53 this week. and so uh you've got to keep at it and i think you've got to be self-critical to be able to you know say okay can i do this job on behalf of my lps and my investors and and and together with my partners can i keep up with them it's it's not trivial and do i have kind of a supple enough mind still to keep making mistakes because if you don't make mistakes in this business you're not going to hit the big one and i think that's that's the biggest thing you know i think about that too uh i'm 53 we're the same age and you know you can and i've but i've only been investing this i'm just entering my second decade you've done it a lot longer than me you do have to think because it's a really important topic and jamie you probably have some stuff to say here um if you don't have the energy if you don't have the risk tolerance then you should hang it up i think that's like a very mature thing to do and i think we see that the problem of course is we need people who have battle scars and who can talk about the attention economy from the 90s and what the lessons are from that because the lessons from that are is somebody will figure it out most will not and the person who does figure it out you can't hold your equity in that company long enough you know like i was talking to freeberg he sold his google on the all in podcast he had sold his google after he left or whatever and you know he had said oh i made a calculation about it he didn't say what it was but i'm sure it's like painful and great companies you know come along every 10 years and you get a lot of good ones but the you know the breakouts the true breakouts that become worth in today's dollars over 100 billion dollars are so rare uh and and your signaling can get broken and that's why i think you need to do what sequoia did really well which is they have these stewards of the brand.

29:42They curate talent. They trust young people to come in and work with founders and do those first round meetings. That's what I'm doing. I have an army right now of researchers, analysts, and associates, an army of them. And people don't know how many I have. I literally, we did 117 first meetings two weeks ago. I had to tell my team to slow down. i said 117 first meetings in one week i had this goal of like trying to hit that for a while but these young people have so much energy they're like yeah just five meetings today i'm like the vcs i know who are 53 like michael and i like if they do five meetings in a week it's a lot a lot of these folks i got people doing five come on six it's hard to do it's hard to keep your energy up for six meetings you know and then also the distractions of life kids You've got, you may have your nest egg right now.

30:35You might be managing your family office. All of these things draw your attention away. And so the way I figured it out is I have an army of young people. I'm talking like 22, 23, like extremely young, 24. And I didn't hire them based on their age. I just hired, you know, folks who are just out of school to train them up before they learn the mistakes of venture capital, the entitlement of venture capital. I want to train them in the hustle that I had as an angel investor. And so that hustling of, hey, I'm going to meet with 500 people in the next six months, and we're going to wind up investing in two of them.

31:10That ratio is a very hard ratio for people to actually execute on. It's very hard to execute on that. And I think old people can't. They just don't have the energy for it, you know, especially when they're 30, 40 years in and they have cynicism or, you know, too much signaling. and I had to tell them, what are the weirdest companies? What are the ones you had a hard time understanding? Start with that. Give me the ones that you love the founder, but don't understand the business. Those are the ones I'm most interested in. And that's what you have to really fight against when you're building a firm.

31:48Is this a codification of ideas? I literally just came from a dinner with founders that we arranged at Olive. I still have my glass of wine here. And I asked at the table, these are second timers i mean people have already sold their first company yeah and we had four of them at the table and the question i ask is what is the craziest idea you have right now that's the question i asked and uh nobody could answer the question and so i checked out and had another drink important lesson it's interesting because if you look this is historical and it's well known in yc uh the top outcomes were not very popular at the round whether it's coinbase dropbox instacart reddit same thing with the teal fellowship you had ethereum that you know some people believed in but a lot of people thought would never work yet figma um so yeah it's these companies that did not get as much heat during the time but they ended up being the biggest outcomes obviously airbnb a lot the people that invest in airbnb i think only he said only one investor keith or boy invested because he liked the idea every other investor invested because he liked the founders that's telling yeah and it was a pivot right they had different ideas they pivoted a little bit along the way they were selling uh cereal boxes and and jaime you you see hundreds of fund managers every year what's the sweet spot for motivation fund size what gets you really excited when you meet when you meet an emerging manager we analyze between 200 and 300 emerging managers each year So we are very good fund manager picker rather than startup pickers.

33:29What excites us about a fund manager first, I think their unique deal flow. I think having a unique deal flow, it's something that resonates on us. We always analyze their grit, their hustle, how they work, their craftsmanship around their portfolio strategy. for us is something that we double-click on every manager that we see. We measure their skin in the game because we all agree that VC is a long-term game with long-term people. So when we pick an emerging manager, we try to get this sweet spot between a$30 million fund all the way up to$100 and 150 because playing in our early stage play field, we see a lot of misalignment when there's a 200, 300, 500, a billion dollar fund trying to play on the early stage game.

34:30So we prefer or we tend to favor more emerging managers with small funds, but they are more aligned with the performance and the carry rather than the management fees. So we look for not only a strong team of complementary skills in the managers, but we know that it's really hard work to invest in early stage and pre-seed and seed. So we always analyze the team below them as well, because you need a strong team in order to win in VC. So I think those are the things that we always analyze. The fee structure, as you get more sophisticated in the space, you understand as well those things. But I think having that grace magically weird craziness of understanding BC and knowing that it's art and science and it's a people's game.

35:25So we tend to see those characteristics in our fund managers, and that's what excites us. And what we built, because having 20, 30 funds begins to get complicated, trying to measure the overlapping, we built this amazing puzzle of funds and we're almost near to zero overlapping. So that's an extreme work for us as well. How do you manage all those, if you have 30 or 40 portfolios or funds, how do you track all that? Do you have like an intern or an associate, just put them all into a Google sheet and consolidate them? Is there software to do that to figure out where, you know, how much you own?