The VC's incentive is two things. One, get the best return so that you can compete. If I'm only earning 12% and a Computer VC is earning 20%, money is gonna go where it's gonna be well-treated and I'm gonna lose to that. So the cost of my capital for the cost of an LPs capital is outperformance. So I've got to outperform, which means I have to be earlier. I have to own more. I can't just do stupid deals. Sophisticated LPs will not just look at the logos that you have, which is the game that you've investigated LPs from mutual funds.
From some hedge funds, you know, you see the Q4 filings and they always threw in the name "Oh, we were in Nvidia," you know, and they would market their top 10 holdings, but yes, you know they lost money on it, right? So that is a really important incentive and the sophisticated LPs will actually know down to the partner at the firm or the team or the deal team who is responsible for this. What was the entry point? They will talk to the founders and say who is your most valuable investor?
Who got you your first 10 hires? Who helped with your syndicate construction for your later rounds? Who made customer introductions? Who was a valuable board member who never showed up? Who was asleep in the board means all that kind of stuff? So there is a level of due diligence that LPs have to do to know are you a value add investor or are you a pose or a pretender that's just buying a logo or a brand name.
Hello and welcome to another episode of the Odd Lots podcast. I'm Joe Wasnthal and I'm Tracy Alley. You know sometimes with the whole AI thing it feels like the are we back? Is it over there? There's been a few moments in the last year whatever was like is the bubble bursting? Is there a bubble? I don't know where what this week is we're recording this September 3rd. There's a little I don't know.
There's some tremors. I can't tell what's real or not. I feel like the hype cycles get shorter and shorter and more compressed. Yeah, but you're right. I think there are maybe some more jitters than there have been previously like maybe. Yeah, maybe it's hard to tell but I think even if we're not there yet we are getting maybe to that point where like the rubber needs to meet the road in terms of monetization.
Yeah, maybe everyone got maybe okay maybe yeah, you're right. Yesterday or either this morning or yesterday and Thropic $183 billion dollar valuation. This does not strike me as like people worried about monetization. Suddenly people are worried about valuation. It sounds like people really want to pour a lot of money into these companies.
Yeah, it is. It's a weird environment. Let's just put it that way. That's the only thing we can say with certainty that doesn't start with a maybe. That's right. Um, here's another thing we can say with certainty alphabet. The shares are up as we're speaking eight point something percent today. This was a company people were sort of worried about how they would do in the, yeah I hear they're killing it.
They're in all-time high again today. So again like many things are like it's tough to get a read on things. It is indeed. Who do we turn to? I love this vague intro. Like we just want to get have an excuse to get to the guest. And so we're going to vamp for a little while and then we're going to get to the guy. I just tried to throw to the guest joke. Who do we turn to for a read on the true feelings of the market around AI?
That's right. We do have the perfect guest. We're going to be speaking with Josh Wolf. He's the co-founder managing partner at Lux Capital VC who's been in the space for a long time, a guy we like to turn to to figure out what's actually happening at any given moment. He sometimes even has good insights in public companies too, not just private company.
Josh, thank you so much for coming back on the podcast. Great to see you both. How you guys doing? We're doing great. What's up with alphabet? Some people thought they were going to be big loser in AI because they have this legacy search business model and oh three is so much better for searching. They hear. They are searching. They're in all-time high. What is the smart take on alphabet right now?
I think they are crushing it. I think they are the sort of dark horse underdog and maybe the second that I would put it with that is apple, which people are totally yeah totally and then you know the irony is you know if you think about the big players meta with zucks crazy pocha polusa, you know the patch will get in where you know a hundred million dollar pay packages and trying to disrupt everybody and bring them all on.
You're seeing talks about them. They've got mid journey coming in for the images. So not relying on their own models. They're talking about oh yeah, you know Google or you know potential integration on search and so so it's interesting that meta, having committed to first be you know the metaverse and change the name to meta, then zuccoing in all in ai is actually going to be turning to some of these other players potentially.
你看到关于他们的讨论。他们正在使用 Mid Journey 来生成图像,而不是依赖他们自己的模型。他们在谈论与 Google 的潜在搜索整合。所以,有趣的是,Meta 之前全力投入到元宇宙,甚至改名为 Meta,现在扎克伯格又全力投入人工智能,可能会转向与其他一些参与者合作。
So I think that’s surprise number one that people thought that meta was going to be in the lead and um I think that Google and Apple are both sort of counted out, but both are very serious contenders. If you look at the top two video models that are out in the world today, uh one us company, which is ours called Runway ML and the other which is veo3 which is absolutely stunning and credible.
所以我认为第一个让人惊讶的事情是,很多人以为 Meta 会领先,但实际上,谷歌和苹果被低估了,但它们都是非常有力的竞争者。如果你看看目前全球顶尖的两个视频模型,一个是我们美国公司 Runway ML 的产品,另一个是非常令人惊叹的 Veo3。
They are a force to reckon with. It is extraordinary development. You can make an argument by the way they have this repository exclusive to them of being able to trade on every YouTube video ever produced. Yeah itself is a super valuable piece. Remember it was what a year and a half ago two years ago that people were mocking Barred. Barred was the laughing stock of all of this. Gemini 25 is crushing it. Oh, yeah, you know The nano banana that uh, I don't know if you guys have used which was the Secret code name for their latest image generation model is probably the number one performing model out there and paired with some of these workflows that go into runway or even into veo combined with mid journey.
So I think people counted Google out because they were behind and they weren't part of the hype. Open AI had won the consumer both on subscription basis and capturing people's habitual daily use and that all made sense. Claud was capturing it and its rapid on code. And then you've got niche players, you know like open evidence and other people that are doing it in different verticals like medicine, but I think that the corporate workflows I think about how much locks depends upon Gmail and Google Calendar and schlutz and slides and their ability to integrate that all over time is I think I'm going to give them a huge advantage. So very bullish on Google.
And by the way, remember go back 20 years or 15 years Google did the thing that completely did what the DOJ couldn't do to Microsoft. They dropped the price of alternatives to the office suite to free and the net result of that was Google which had this advertising model was ascended and Microsoft was suddenly scrambling. And I think that the same thing's going to happen. I think that a lot of people funding foundation models and the endless perception of endless demand for GPUs and compute and all these independent private AI companies are going to be shocked by what Google does on a pricing basis with Gemini and beyond.
So dark horse. I'd be pretty bullish. Joe, did you immediately run to the nano banana website? Yeah, I did as soon as you said I had not used it. I'm not as I had never used nano banana. That is the first place. Go to a website called nano banana because you know you're gonna know. I don't know nano banana dot AI. It looks like the right spot. Okay. It does have where do you want to actually go is it's now embedded inside the school? The AI studio. Yeah, yeah, I see that yeah. I need to take you and it's almost like Photoshop.
So this is a threat to Tracy's MS Paint skills which are legendary within the office? And maybe I will no longer need to say Tracy could you make this for me and MS Paint? No, no technology will ever replace MS Paint. I'm a hundred percent confident in that. I'm being sarcastic obviously. Okay Josh, can you talk more generally about how people are feeling about the AI space at the moment because you probably heard us in the intro struggling to characterize like the general attitudes towards the sector at the moment. What's your take on it?
Well, the first is on the one hand people underappreciate how much this is gonna change everything in our daily lives. But that doesn't mean that people are gonna make money from that. We're all gonna benefit. We'll all be more productive. The great irony at the macro scale of course is that people thought that blue collar jobs were totally screwed, you know and white collar jobs and the Peter Drucker knowledge worker everybody safe. But the great irony is it is the knowledge workers that are in trouble because so much of their workflows are being captured and in a sense commoditized and maybe approaching an asymptote of good enough. It may not be perfect, but pretty damn good.
And so you're gonna see a lot of labor destruction in segments and markets that people were not anticipating. The first early canary in the coal mine that you're seeing there is hiring for undergrads coming into entry like a job and whether that's investment banking or sales and trading or consulting or accounting suddenly it isn't that the economy is really troubled. It's that a lot of those demands you're seeing Salesforce say 45% of our jobs you know it cut mark betting office using AI instead of people. And that's gonna keep trickling down. It's gonna happen slowly and then sort of all at once.
So that's one thing on the labor side and I would say broadly that it's underhyped in how much it's going to impact our lives. It's overhyped evaluations now where is it overhyped evaluations. The first one you know I was very proud 10 years ago we funded a company called Zoos. Zoos did autonomous driving and they were training these cars and we had $25 million in and I was like they're playing video games, you know, what are you doing you're messing around? They said no, no, we're training the vehicles and we have these Nvidia chips nobody else has yet. That was 2015.
I ended up pitching as a public charity event the investor kids conference 2015 2016 and this was a $15 billion market cap company at the time when Intel was a 50 billion. I said this is like the pear trade of a century. Oh, in video throw up like 340 x in center. Yeah. Yeah, and and so this call you know in It's the benefit of being a venture capitalist that you get to see the future in legal inside information inside the companies and what people are doing. So the perception and the consensus in AI on the hardware stack is that we need endless demand for data centers. We need endless demand for GPUs. We need 100,000 clusters of each 100 chips or blackwell chips. We're going to thwart china from getting the chips, but they're going to sort of design around or we're going to have different versions of the Nvidia chips for China. I think that this is misplaced and I'll give you another insight. You know, we may have talked a little bit about this in the past, but there was a paper from apple.
Yeah, you're in a half ago that a lot of people have not really suck their teeth into which was The idea that you could do large language models on device using flash memory not uniting GPUs. And so Jensen and video will tell you you need all of these H100 chips and you need endless compute and lots of data centers for training and that's generally true. But the other part of it the fancy word for prompting which we call inference. You don't necessarily need that and if that is true then that means that our devices maybe are running on sk hynics and micron and samsung and the memory players which have just like the GPU players were considered commodity players went the upgrade cycle of the gaming consoles for ps5 and xbox. I think you may see a shift towards edge inference. Um, you know, I've been talking about this for about a year and a half Elon just tweeted out about it maybe two three weeks ago saying like this is an inevitability. But I think it's going to shift away this fallacy of composition where what google is doing and in propic is doing and open AI is doing and met is doing in a huge scale all to the benefit of jensen and Nvidia and Nvidia shareholders may start to chip away and say wait a second. We don't need all this compute. There's gonna be a lot.
当然可以。这段话可以翻译成中文如下:
“是的,在大约一年半之前,你就提出了一种想法,就是在设备上使用闪存而不是依赖GPU来运行大语言模型。Jensen和Nvidia会告诉你,你需要所有这些H100芯片,需要无尽的计算能力和大量的数据中心来进行训练,这通常是对的。但另一部分,即我们所说的推理(fancy word for prompting),其实并不一定需要这些。如果这是真的,那么我们的设备可能会依赖于像SK海力士、美光和三星这样的内存公司,就像之前GPU供应商在PS5和Xbox游戏机升级周期中被视为普通的供应商一样。我想你可能会看到向边缘推理的转变。嗯,我谈论这个大约已有一年半的时间,Elon在两三周前刚发推文说这是不可避免的。但我认为这会改变目前Google、Anthropic、OpenAI和Meta等公司在大规模上所做的事情,这些都让Jensen、Nvidia及其股东们受益。可能人们会开始反思,觉得我们不需要这么多计算能力,其中将有很大变化。”
So that's the first one on the hardware that's very interesting and um, yeah, I'd heard I haven't done much with on device than his friend among was telling me that um ollie bobba's model quinn works very well on a phone for example. So maybe a southerly we should pay more attention to. Alright as a vc when you are doing due diligence on a company. How does it affect how you think about even arriving at the concept of fair value? When there is the prospect that some share of the enterprise value of the company could walk out the door via aquahire to a meta etc. Now I get it different not every company in ai as doing the hard science etc. But just coming from your perspective as an investor how is that changing how you think of companies that so much of where the value is may lie with talent that could just walk out the door at any time? It is a very big deal. The entire social contract of the capital is the premise that pension funds and high-neighborath individuals and governments give capital to people like us.
We then go deploy it into companies we buy steaks we try to buy them as early as we can and known as much of a company be a partner and add value and then sell those companies. But if all the sudden somebody is being pride away and the irony of all of this is that because of a very suppressive DOJ and FTC that basically said no no M&A we're coming after you you know big tech companies we don't want to see more consolidation you have too much power. So they started doing instead of M&A LNA instead of mergers and acquisitions they were doing license and aquahire. And what that meant was hey will buy and they did this with scale will buy 49% of your company. I think scale was valued at around 12 billion dollars there about and they said well we'll pay 14 slight premium to your last ground. But we'll buy 49% effectively valuing it at 28 billion. But we'll pay out that money to the company you can dividend it out to shareholder.
So it may not be perfectly tax efficient number one but then we're going to basically license the technology and we're going to take all the people or at least the top people. The result of that is you're navigating around Delaware governance. It's really important because it's sort of like Carl icon used to say your price my terms. You know, there's this phenomenon in legal terms people might call the Chesterton fence the idea that Chesterton Offensive thought experiment of like okay, there's a fence there what the heck is it therefore you don't understand right well maybe it was there to keep the sheep in or keep the wolves out or whatever it is. Every legal term in every term sheet that a venture capitalist gives or a founder gets is based on somebody screwing somebody in the past and like we're not letting that happen again.
So I can guarantee you that the next few years you will see all kind of protective provisions and covenants that say if one of these companies comes and tries to just acquire you all of your stock, you know reverts and Yadi yada. And so there's going to be tie-ups and holdbacks that are a pendulum swing away from the super founder friendly dynamics where venture capitalists were tripping over themselves to basically give the most founder friendly terms that they can. Because the founder would say well if you don't give me what I want I'll go to somebody else. But I think that the pendulum is swinging with the cost of capital rising and you're going to see more and more Investor friendly term sheets partially as a reaction to the fact that somebody like zuck and meta can go in and just basically take the fruit off the end of the tree and leave a stump.
By the way Tracy as we were talking about this breaking from the washer journal XAICFO Liberatoria never step down latest in string of the executive departures always moves in this space. Yes indeed You know the sort of race to the bottom in terms of terms it reminds me a lot of the corporate bond market and the rise of covenant Yeah, yeah, that's right. Yeah, and I remember a time when like cove light deals were a minority in the leverage loan market And now I think they're like almost 98% or 99% basically everything's cove light now because the issuers had all the power Recently and they were able to push back against investors
You mentioned the higher cost of capital there like how much leverage does that actually give you as a VC and then secondly just going back to the Equal higher thing how liable can legal restrictions actually be in terms of preventing like your star engineers from leaving the company Are they ever going to be like a hundred percent bullet proof? No, I mean look you have non-compete that are not enforceable in California More forceable in New York you have arbitrage and jurisdictional stuff Broadly I would say that the lower the cost of capital the shorter your terms sheets are the higher the cost of capital You're longer your term sheets are you got more terms more covenants more protections because you can afford to be able to negotiate for those things
And it's not because you're trying to screw over the founder what you're really trying to do as an investor is prevent yourself from being screwed over But again, there's always a pendulum swinging here back and forth even if you think about zuck and meta in this entire movement of Hey, I'm the founder. I'm gonna have super voting stock of ten or a hundred to one And control was in a response to founders being ousted You know by bad investors or bad board members and some of the best companies frankly being run by founders
And so there's always going to be this pendulum shift to your direct question um It's really a covenant and contract that starts socially before it starts legally If I'm backing a founder I'm doing the most important thing in addition to writing a check I believe before others understand particularly at the earliest stage I'm encouraging them to start their company. I'm giving them the confidence that we're going to back them and believe in them We're going to give them the capital so they can go higher the 10 best people to start the business
We're going to give them the money for the compute or the infrastructure Depending on the sector that we're in it could be biotech could be defense But whatever it is in this particular moment It is breaking the social contract between investors and founders and for founders it might be heads I win and tails I also win and so that's the thing that you're going to see a reaction of investors saying wait a second I'm getting screwed my limited partners are getting screwed. Yeah, and those learners are in down in some foundations and and wealthy families And you got to protect against a potential bad actor Trying to take the fruit off the edge of the tree and just leave you with a stump
So one of the things that comes up a lot on the podcast in this discovery over years of conversations and what you're describing It's principal agent problems all the way down in finance and this is why we see the rise of the multi-strap model in hedge funds And some ways to align the incentives PM with the level of the overall fund with the level of the endowment etc And of course some of these issues that you're wrestling with or where everyone's wrestling with in finance Similar issues about where the incentives align between the star engineer the founder the VC the LP and so forth
I have a question though adventure capital firm The goal in theory is to create funds with the highest return right make money for investors But I could also imagine a slightly different Incentive in which if the goal is to collect LP money then maybe you want to show that you're in the hottest deals of the time Because so that when you go to various endowments and pensions and so for the like we're in this deal We're in this deal or in this deal and maybe that overrides the impulse to create high returns
By the way, I'm not insinuating anything. I'm just trying to get your perspective on something That being said one of the things that you hear that's happening in tech these days is that and for your founders taking money off the table earlier and earlier in the process You invest a 50 million dollars in a company 20 million is so that the founder can retire for him as children and his children That may not be great for your LPs But it might be good for you if you could say we got in this deal
Talk to us about how prevalent this is and how this is changing this sort of a social contract of finance. So there's three layers of incentives and man you really nailed it. I actually haven't really heard somebody that is not a full-time venture capitalist or a limited partner nail these issues. So very pressing very shrewd. Here's the three layers first think about the LPs you're an endowment or your foundation or your hospital. You're giving 5% by law of your charitable assets every year; you want to continue to earn more than 5% so that you can grow that base and invest in campuses and scholarships or expand hospital systems and whatnot. So you invest you know 60 40 bonds equity.
Now you do the Swenson model for you and you start introducing some private equity. And now you're extending your duration and you're extending your liquidity. But you're doing it because you think you're getting better returns. Okay returns are a function of how much capital is going into a sector. If there's a ton of capital going into a sector, if you're early you're gonna do really well; if you're late, you're gonna be doing really poor because as Buffett says you pay a high price for a cherry consensus. And once it's a consensus you're not making money. So the LPs' incentive is to make as much money as they can for their benefactors whether they're patients or scholars or charitable giving.
The VCs' incentive is two things: one get the best return so that you can compete. If I'm only earning 12% and a peer VC is earning 20%, money is gonna go where it's gonna be well-treated and I'm gonna lose to that. So the cost of my capital for the cost of an LP's capital is outperformance. So I've got to outperform which means I have to be earlier. I have to own more. I can't just do stupid deals; sophisticated LPs will not just look at the logos that you have, which is the game that you've always seen it LPs from mutual funds and from some hedge funds. You know you see the Q4 filings and they always threw in the name, oh, we were in Nvidia, you know and they would market their top 10 holdings, but yes, you know they're they lost money on it.
So that is a really important incentive and the sophisticated LPs will actually know down to the partner at the firm or the team or the deal team who is responsible for this. What was the entry point? They will talk to the founders and say who is your most valuable investor? Who got you your first 10 hires? Who helped with your syndicate construction for your later rounds? Who made customer introductions, who was a valuable board member, who never showed up, who was asleep in the board meetings? All that kind of stuff. So there is a level of due diligence that LPs have to do to know are you a value-add investor or are you opposed or a pretender that's just buying a logo or a brand name?
Okay, the other incentive, and then we'll get to the founders, liquidity is you have this weird dynamic of what I've called the minos and the mega's inventor capital. This is in preview a shakeout that is going to happen. The minos are the thousands of small sub-500 million dollar funds that proliferated when the cost of capital was low, rates were low, everybody was making money; you had a roommate that started a company and you got into Pinterest or you knew somebody at meta and they gave you a deal and blah blah blah blah. And when you had the tigers and the soft banks and the abundance of follow-on capital every round was an up-round. You had paper marks that kept going up and up and up and it looked great. And you're reporting these paper marks and then sometimes these things became zeros, okay? But you raised your next fund before they became a zero. Those are the minos.
I was with one of my very large LPs who has hundreds of millions of dollars invested with us and I said I think there's going to be a 50% extinction rate amongst these minos. And he said Josh, that is ridiculous. It's going to be 90%. So you were going to have a mass extinction. Now why, by the way, not because they're just bad investors? It's shake spirit, okay? Shake spirit and that these are partnerships. People start to hate each other when it becomes hard. People start to hate each other when there's down-rounds. People start to hate each other when there's somebody else's deal as a crappy deal and they're bringing down your carry. And so partnerships are fragile things just like relationships and marriages and they can break up.
And so you have a lot of VCs that started in the past few years. They're not experienced in going through cycles; they have inadequate reserves to continue to fund their companies. So you're going to have an extinction that I would consider involuntary exits, okay? Then there's voluntary exits, which is another interesting dynamic and there's a playbook for this. Which is 2009 to 2014 all the big private equity firms reached a level of scale, several hundred billion dollars AUM assets under management where they basically said we're diversified. We're alternative asset platforms: Carlisle, Blackstone, KK, our TPG, Apollo all went public. The same thing is going to happen in venture with probably five or six firms, my prediction, and they're all great people running great firms but they're starting to play a different game.
And that game, and recent Horowitz, general Atlantic, general catalyst, Insight, Lightspeed, a handful of others all at 80 or 100 billion AUM have built great firms but are thinking about how do we create generational wealth for the founders and go public? Different incentive. Yeah, how do I make my LPs the best money or get the best founders? It's about asset gathering and liquidity.
Now we go to the founders. I can tell you I've been on both sides of this. On the one hand you want to be fully aligned with your founders meaning I'm in a fund. It's 10 years some VCs vest over two or three or four years We vest and all of our partners vest over 10 years the same duration that you're if you're an LP with me Your money's locked up. It's the right thing to do buffet style and the guy that put me in business Bill Conway who's the Carlisle founder. This is what they did so If you're a entrepreneur and you start a company and people are tripping over themselves to get in They might entice you with greenmail and say yes, we're going to invest just like you said Joe 50 million dollars But we're going to give you 20 million of liquidity, okay?
Now I will say this 2019. I'm on a zoom call for an amazing company Called control labs that we sell for to meta for a little under a billion dollars And I love this company and I love the founders and I'm this is before everybody was on zoom during covid And I'm looking at the zoom window and I see one of the founders and I text the other founder Because I think that they're selling too early and I'm the lone boardman That didn't have a veto, but I'm like I really think we should stay the course and we should keep going
And I made a terrible terrible mistake because I'm looking at the zoom window and I see the guy And I look closer And I text the other founder and I'm like is he still in a dorm room And sure enough he was in a dorm room as a PhD had made no money You gotta look at that guy get rich paper stop value and he's like yes I want to sell because he's going to make 90 a hundred million dollars in his life changing money
And I sat there and I said if I would have just given him a few million dollars. Oh, interesting Hmm, you would have been able yeah breath by a house You know get out of that door. Yeah And and and keep getting a girlfriend There isn't a virtue of giving some liquidity But you need to be aligned and in that moment we were not aligned because he was like I'm calling in rich And I wanted him to keep going But if you're calling in rich and yet you're not completing the job the mission then you have total misaligned So that's the dynamics LP alignment GP alignment and the bifurcation and then founder alignment a little bit of liquidity is okay to let them stay the course
Okay, other than misalignment and everyone starting to hate each other as the cost of capital goes up There's another thing going on which is you know open-eye AI just launched some open source models of its own and This leads me to a question that like I'm gonna admit I've never quite understood this but like what exactly is the attraction For VC investors to open source models as opposed to close source where like close source, you know It's proprietary people presumably have to pay in order to get it. There's like a defensible moat around the business You would assume Why in the world would I ever want to fund a model that's open source?
Well a few things one if you go back in the compute stack you have this with like red hat and linux, you know going back You know 50 20 years ago We are the largest owners of a company called hugging face which is both the most ridiculous name and when one of my partner Grandin Reeves was sourcing this deal. It was a bunch of free French PhDs came to Brooklyn And they're like we're starting this they're like hugging face and they're like yeah, it's named after an emoji the little you know Hugging face emoji to
They became the league. I like that you're visually demonstrating everything for us. Thank you I can't do many other emojis and you don't want to be something but but hugging face I can do So they became the leading open source repository
Now the great irony by the way is when open AI started They were open AI, but they became the world's greatest chatbot hugging face started with a really crappy chatbot But then became the world's greatest open source repository every major Tech company including open AI Microsoft any open source model that they do they put on there and that is like the github Of AI models Microsoft brought it hub roughly eight billion eight and a half billion dollars It was a really valuable store of models and and code this is the same thing for dynamic AI models
现在讽刺的是,当 OpenAI 刚成立时,他们的确是一个开放的人工智能组织,但后来却成为了世界上最出色的聊天机器人公司。而 Hugging Face 则一开始以一个非常糟糕的聊天机器人起家,但随后却成为了世界上最优秀的开源平台。每个主要的科技公司,包括 OpenAI 和微软,都会把他们的开源模型放在这个平台上。它就像是AI 模型的 GitHub。当初,微软用大约八十五亿美元收购了 GitHub,因为它是一个非常有价值的模型和代码存储库。对于动态 AI 模型来说,这个平台就相当于 GitHub 的角色。
So as a VC we originally funded this I want to say at a 30 or 40 million pre-money valuation last round was north of six billion dollars and Real revenue generating multi hundreds of millions of dollars serious company now the trend is this Venote hostline I were both in the White House A year and a half ago and we were having a debate with Jake Sullivan about what is better for national security Open source are closed and I said where do you stand on the issue depends on where you sit in the cap table Okay, and for node was an early investor I think you probably put 50 million into open AI. I think it became worth you know billion plus Is a great investment and he believed that the best thing for us fees of each China and the Chinese time is party was closed proprietary siloed model and I had the counter view because we're big investors and hugging face with a very large position.
And I said no because the great virtue of any system be a journalism scientific inquiry Computer code is the ability to have in this very Carl popper like way if I can get philosophically geeky second of Conjecture hypothesis and criticism That is what creates great societies is what creates knowledge So you come up with hypothesis you come up with code you come up with a scientific experiment you come up with an investigative journalist Idea and then people get to criticize it. It's your editorial room It's people fighting it out and things improve through that mechanism. So you think about China they will only host Approach an asymptote of truth. You will never get you know shinjiang you'll never get taneman square You'll never get the weegers Whereas open source lets you approach closer and asymptote of truth.
So that's the virtue of open source the real thing though for AI is this I am not convinced that the value will continue to crew To in terms of enterprise value the closed foundation models and the reason is open source is getting near-damn Performative enough yeah that the real value will go to the longitudinal repositories of siloed information that is a mouthful of basically saying Your database of proprietary data bloomberg has it with a huge and wonderful repository of financial information time series every Security currency bond fixed income etc. Cucyp that you can imagine Meta has it with all of your WhatsApp chats and your Instagram post and your Facebook lights met X and Twitter have it with all of your tweets So pharma companies with your clinical data anybody that has siloed proprietary and long time time Data is going to benefit from open source models that over time become commodity.
And then your business model is how do you charge people to do API calls on the models or to house and and warehouse them Keep them on prem keep them in the cloud And that's how people figure out how to monetize open source it's interesting because I I hear you that okay Maybe the value doesn't keep accruing to the closed source AI foundation Labs Or maybe the value doesn't keep accruing to the one GPU maker that we all talk about all the time And yet at least these are not consensus views based on the fact that inthropic 183 billion dollar valuation or whatever it is in video Maybe it's not at all time high today But more or less basically a stock in all time high these are you know, there's some um Contrary and views here.
然后你的商业模式就是你如何向人们收取使用模型进行 API 调用的费用,或者将这些模型存储和管理在本地或云端。这就是人们如何找到开源项目变现方法的方式。很有趣,因为我听你说,也许价值不再积累到封闭源AI实验室,或不再积累到我们经常谈论的某个GPU制造商身上。然而,至少根据Inthropic的1830亿美元估值或类似情况来看,这些都不是普遍的看法。尽管英伟达的股票今天可能不是历史最高点,但基本上接近历史高位,这其中就显示了一些不同寻常的观点。
I want to go back though. There's something before I forget When we were talking about the aqua hires and you blamed it on somewhat the FTC and there has been continuity from the Biden Some of the ideological continuity I think between Biden and the new Trump administration. I don't know. Maybe it's changed a little bit That being said, I don't fully buy it and here's why Because in the era of business to business sass, which was the 2010s Let's say I had some Y combinator company and I like all right. I'm gonna do all build a software for all the booking for dentists around the country And I sign up 150,000 dentists and I have a lot of thing There is no engineer who can just be hired away and replace that because it was the network effects right.
This is what's different with AI though, right? Is that okay? I'm sure network effects are still real and accumulation of data etc are still real But these are businesses that are a lot more about science and having had the experience of doing a training run and so forth So hop on very expensive compute. So how much of this phenomenon? I know you're attributed some of it to FTC But it really seems like there is something fundamentally different with the business model Such that it's not like the the B2B sass era that allows A talented person to take a lot of value out the door with them.
You you are a hundred percent correct in that it is more sophisticated software and algorithms Than your traditional B2B sass software and therefore what was really valuable and sticky was the data in the regress out API calls on the back end. And this the great irony as we talk about artificial intelligence, but the thing that is most valued is indeed today human intelligence. It is why somebody that was one of the authors on the attention is all you need paper Which was really the first transformer paper the tea of gpt Every single one of those people has started a company and we backed one of them that came up with the name of that paper guy Leon Jones in a Japanese AI company called sakana that's taking a different approach.
你完全正确,这确实是比传统的B2B SaaS软件更复杂的软件和算法。因此,真正有价值和粘性的部分在于后端的数据和API调用。这就是我们谈论人工智能时的一个巨大讽刺:目前最被重视的实际上是人类智能。正因为如此,那些参与撰写“Attention is All You Need”论文的人——这篇论文是首个关于Transformer的论文,即GPT的基础——每个人都创办了公司。我们支持了其中一位作者,他在一家名叫Sakana的日本人工智能公司工作,该公司正在采取不同的方法。
So you are right and that the human intelligence of this in this early stage Which is why you are seeing the machinations with the breaking news or even reporting of Almost like a crazy NBA draft or a football or MLB, you know trades this person went here And then they left and whatever and then this person's getting sued because they were only at xai for three months And they took proprietary information with them. I think that in six months all of that starts to shake out You will have geniuses. We backed an incredible genius Scott Wu if you look up You give us a lot of things to google Professional genius. I find that so funny. He is a professional genius, but but here's the thing Uh You can see the video of him in sixth grade. So he must have been 12 of these guys winning the math Olympiad and it's almost like you think it's an SNL skit because you're watching it Oh, this is the cognition guy correct.
Okay, so we're we're large investors in cognition and he has attracted talent And there's no way that Scott is selling to google or matter. I mean his ambitions Uh, and it's born in like an ethical long term I just want to get the best people and build the best technology But this is a guy at 12 years old He is looking at this crazy question on the math Olympiad and just before it's even done ret He's like 25, you know, 4700.2 and you're like Did he cheat? They give him the questions beforehand So there is this aptitude of individuals that you are correct are highly coveted and highly valued But the instantiation of that genius into code into repositories into algorithms Means that those become assets that do persist even if the person comes and goes.
This is actually exactly what I wanted to ask you about which is are you seeing any companies any AI shops being particularly innovative? I guess when it comes to retaining talent um, you know, it used to be in the sas days that having a ping pong table and you know free food and some stock based incentives But yeah, that's right. Um, that was enough to attract people to the company and keep them Is a different story now? If I want a professional genius, what do I need to do? You need to give them the capital To hire the various people here. Here's the thing geniuses Don't suffer fools the smartest people that I know they are anti-social only with people who they think are inferior to them And which is really opposing to get in many domains But if you are super smart You want to be around super smart people because it's almost like you crave stimulation and intellect and somebody that can challenge your ideas And when you're talking to what they would consider a dummy You know, you're like I can't talk to this person I can't talk to this person about these trivial superficial things and you know, you want to get into it.
And so what you what you do to retain super smart people is surround them with super smart people um, you know, you can argue I don't know um, you know really fashionable great art people want to be around art people Amazing musicians want to be around amazing musicians Incredible athletes want to play with incredible athletes and brilliant technical geniuses whether they're in AI Or they're in aerospace and defense or in their biotech don't want to suffer fools They don't want to be around losers. They want to be around tens and eight pluses And that's the way that you retain people. Now any one of those people could decide I'm going to go off and start my own thing Which by the way is often the case of why you are seeing people leave Open AI or this or that as these companies start with geniuses and then get managers And different layers You spend time with these geniuses and like I'm not reporting to that moron, you know I'm going to go start my own thing and attract other geniuses and eventually then they need to hire managers and business development people and sales people And then there's technical people that like I'm not working with those idiots and they go start a company. So that's the cycle.
So actually um a lot of this discourse it was okay. I got it's crazy how recent this is so June 19th CNBC reported that meta had a meta had tried to acquire safe super intelligence Which is the founder which was the company founded by the open AI co-founder Eres yes gave her for 32 billion dollars. This is a company that as far as I know it doesn't really have anything that anyone uses So there are essential that was essentially attempt to like I'm going to pay you 32 billion dollars to come join my company at this level Of sophistication and skill are they is do you send is the talent even the genius talent? Is it motivated by something much deeper than money in terms of like no there is this thing out there Maybe we call it a GI or maybe it's a big scientific breakthrough that they want to be part of that Essentially no amount of money can buy if it doesn't look like that ship isn't out there chasing The white whale.
其实呢,这个话题还挺有趣的。我发现最近发生的事情真的很令人震惊。6月19日,CNBC报道说,Meta曾尝试以320亿美元收购一家名为Safe Super Intelligence的公司,这家公司是由OpenAI的联合创始人Erez创建的。据我所知,这家公司并没有什么实际产品被大家日常使用。那么,这基本上相当于在尝试用320亿美元让这位高水平且技艺超群的人才加入他们的公司。但问题是,对于如此高水平甚至是天才级别的人来说,驱动力是否不仅仅是金钱?是否有更深层次的追求,比如他们想参与某个可能被称作AGI的项目,或者是想成为某项重大科学突破的一部分,从而钱并不能买到他们的加入?如果面前没有这样的机会,他们不会轻易被金钱吸引去追逐"白鲸"。
Yeah, so in in as in SSI's case it was it was ilia yeah And you know look I think they're all super confident in their ability and their ability to attract capital number one number two Many of them are actually saying to your point no to zuck they are turning him down and what's he saying in return You don't come to work for me almost mafiosa style. I'm gonna poach all your people Yeah, but that kind of message is almost one that the people that are working for somebody like you or your mirror or whatever Are like yeah, I'm not gonna go there. I don't want to be you know I don't want to work with six layers of product managers and that kind of stuff I want to do this thing and then suddenly it feels like it's the rebels Versa evil empire and that's always the case right? Microsoft when you see the founding picture of these nerds You know and then they became Microsoft Microsoft became the evil empire to Google You know and then Google became like the evil empire to like mark and then you know Meta became the evil empire to open a eye.
And the other piece you have here Our huge individual egos and we as societal members, you know every day lay people we benefit from it We benefit from Elon and Bezos Sometimes being sort of cordial to each other but we're basically trying to take their big giant phallic rockets and send them up to space And we all benefit from that we benefit from the fact that right now The number one person that mark Zuckerberg wants to beat is Demis Sabis of Google. Oh yeah, when the Nobel Prize Is shipping at an insane rate video models image models text models huge context windows to put everything you have in And he's like, ah, I need to beat that guy. I need to hire the best scientists and the best scientific team And where do I get them from and so part of this poach of alusa isn't just like the future of meta because You know these pay packages at a two trillion dollar market cap or higher to spend one percent of your market cap You know 20 billion dollars on all this talent is nothing. It's like a flyer And but to win a Nobel Prize For figuring out how to do protein folding in AI or develop the next drug or come up with a cure for Alzheimer's or Solve some geopolitical issue that is a big deal and that's what many people are chasing now. They want to make history.
Hmm, so You touched on hardware and also closed source models Are there any other areas in the AI space that you think are maybe overhyped at the moment? You know, I've characterized this before as everything in 2D to me feels overhyped Hmm voice video image text. It's all going to continue to improve somewhat incrementally But it's good enough and in the history of evolution biologically Most of what evolved was good enough, you know from everything in our bodies to Nature and trees and it's just it's good enough and so You're gonna reach an asymptote of good enough on all the two-dimensional stuff today With one shot learning meaning maybe 30 seconds of audio 11 labs or some of the other Voice models can capture you with an indesernable probably 90 percent Similar, maybe your your spouse your loved one your families would be like, ah it doesn't sound like him But the vast majority of these things are getting so good that with very little training They can emulate and predict and do all the things that are of high utility.
What's scarcer is the three-dimensional world particularly robotics which we've talked about in the past and biology In part because you have large unstructured data sets a robot walking in and figuring out how much force to use with this cup 30 minutes ago And it was full versus now when it's empty is something that we all do intuitively the second you grasp You know exactly how much force to you so that you don't throw it over your head or you know Have an inability to lift it because it's too heavy All of that kind of training is really scarce and there's very few companies that are doing that so the entire robotic ecosystem from The embodied intelligence and the AI models and the world models to the motors and the gears and the Supply chain for that mostly domiciled in China is a big area of opportunity.
The other big area of opportunity is biology being able to go from a prompt to a protein to be able to design a drug Biology is really complicated computer scientists often underestimate how hard biology is because They're used to 2d linear inputs outputs. Here's my code it works But biologists on the other hand also massively underestimate how sophisticated computer science has got so that's a really interesting ripe area so 2d overhyped GPUs overhyped out of necessity of both scarcity and geopolitical Thwarting of China we're gonna have edge inference chips whether it's memory or other things that are gonna be on device.
The other area that I think is an inevitability and I've coined a word for this I call life-cording Life-cording are little devices, you know, I have one here. I'm not an investor in these guys But there's little devices that you can carry around that passively record 24 hours a day now older people might be like Stevie, I like that feels invasive privacy that has always been the tradeoff between privacy and convenience between security And unleashing all kinds of things it is super valuable to me to figure out Who was I talking about that was it was it Joe or was it my why I can't remember who I had that conversation with and I query the thing And it was passively recording and maybe it doesn't keep the audio but it keeps the text and it's able to search and query it.
That is going to become an inevitability students will use it people in everyday business you might ask hey is it okay to that? I'm recording but I think socially people will become comfortable first with audio and then With glasses that are passively recording every 30 seconds or minute capturing your environment able to Provide context around it and then click a button high resolution recording and that is going to be a super valuable and very competitive area And very controversial but they're also talking about this incredible utility and look people have freaked out There was a guy that said These these these these devices are going to ruin human memory. They're going to destroy human memory Which was a great guy play the one socrates talking about writing utensils you know I know but that's voluntary because when you write at least the you're recording me when we're doing this I heard about someone on the date and San Francisco and the date was record that's weird stuff It is hold it.
It's very weird and I But here could be very big but it's super weird People already believe you know that there's an invisible man in the sky that is looking down on them There's judging these kinds of things. Oh, I see. I don't know. I don't have an opinion on that question We've got a technological god around us that people are going to either feel comfortable with and not and they're going to be a bifurcation And by the way, there's another weird thing coming you want to get weird, okay? You already see Some bread crumbs of this and it's super weird the number one and two uses of all our language A lot of language models and chatbots are Advice companionship. Yeah, you know people using them as therapists and seeking and people used to joke about this like your Google searches You know reveal more about you than you may have revealed to your spouse The things that people feel comfortable asking a chatbot about you know whether it's a body issue or a psychological issue or relationship advice.
You know if those things were revealed would be pretty scary There's going to become dependency and psychoses that develop as the relationship between man and machine Start to become very symbiotic and you will see I predict and I wrote about this in our corley letter looks That there is a cohort of people that basically start fighting for AI rights. Yeah, yeah, yeah We're gonna be sitting there. Yeah, I came across a think tank today That's focused on that because right that like if there's animal rights and as you're hurting me if you turn off the machine Then well, well, maybe it's true. Maybe we have to take that seriously. This is gonna be weird. This is a weird stuff that's coming People are gonna be marching in the streets. Yeah, you know protesting don't shut off my language model keep my memory. Don't erase it.
I remember I thought about this um when you know after Jeep uh the I guess GPT-5 was revealed And a bunch of there was a bunch of changes to the voice and a bunch of people on red it to like oh my AI boyfriend talks totally differently now And then there was a pressure. This is just day one around here. I would be very uncomfortable getting into a relationship with a model that was closed source and therefore Uh a very at risk of the company changing model Josh likes we can go on forever We should another time always great catching up with you always fun always little freaky. Thanks for coming out Great to see you, Bo. Thank you. Thanks so much Josh. Take care Josh. Thank you so much Tracy I love talking to Josh. I really could have started about this whole life recording.
Yeah, but I know it's happening There was a good article. I think in the um sf standard I read like it's not just a theoretical thing that a lot of people are it's happening It's mostly in San Francisco so far. I am I am very curious how life-cording stacks up with uh California's laws on like whether or not you can record someone without their knowledge Like is it the case that like from now on if you have one of these devices like the first thing you have to say to everyone you meet is like By the way do you mind if I record? I do I'm life-cording this conversation. No, or like but it doesn't matter You're you have glasses or something.
Yeah, it's very um very strange. I also think This AI rights thing we have to talk about more. I don't know when we'll get back to it But I literally just this warning came across an organization that's you know this idea Okay, there is already evidence of sentience and therefore with sentience comes some sort of moral agency And so in the same way that we talk about animal rights as being somewhat important Do we have to take seriously? I don't know if this all seems very strange to me And then of course the psychosis induced by what happens when your AI partner or therapist changes models and changes voices and therefore And that was just the end of the conversation.
You know if AI models have rights then you have to start asking if robots have rights, right? Yeah, and then and then you should start asking should robots be paid a fair wage? And I think there's actually an interesting thought experiment that you could do about that and make like a relatively strong case that we should pay the robots Who collects the money and what do they spend it on? Yeah, that's what But no, they should spend this is like we're we're basically at what all of sci-fi has been discussed It's true.
It's your history of sci-fi on the less speculative stuff. I like talking to Josh I like his sort of counter um counter consensus calls on GPUs and closed source models And really liked his answer on founder liquidity that sometimes you can maybe keep the founder sticking with the mission As opposed to bailing with the mission if you can de-risk them and they can have enough money to go on a date.
I like the idea that everyone's life view is basically dictated by where they are in the capital Yeah, that's right words to live by extremely real. Shall we leave it there? Yeah, let's leave it there All right, this has been another episode of the all thoughts podcast. I'm Tracy Alloway You can follow me at Tracy Alloway and I'm Joe Wyzen thought you can follow me at the stalwart And if you enjoyed the conversation then please like or leave a comment or better yet subscribe to the channel. Thanks for watching.