Josh Wolfe on AI and the Breaking of Silicon Valley's Social Contract | Odd Lots

发布时间 2025-09-08 08:00:28 来源

以下是翻译后的内容：这期 Odd Lots 播客节目采访了 Lux Capital 的联合创始人兼管理合伙人 Josh Wolf，讨论了人工智能的现状与未来、风险投资的激励机制以及新兴趋势。 Wolf 在多个方面挑战了普遍的共识，首先是 Alphabet (Google)，他认为这家公司是人工智能领域的“黑马”，被低估了。他指出 Gemini 和该公司庞大的 YouTube 数据存储库是重要的优势。他还认为苹果公司也可能成为竞争者。他认为，虽然人工智能对日常生活的影响被低估了，但许多人工智能公司的估值却被过度炒作了。他认为，人工智能对知识工作者，特别是入门级职位的劳动破坏，将比预期的更大。他挑战了关于 GPU 无尽需求的普遍观点，指出苹果的研究表明，大型语言模型可以在使用闪存的设备上运行，这可能会将计算负担转移到边缘推理，从而影响 GPU 的需求。对话转移到 “人才收购 (aquahire)” 的问题，即大型科技公司收购较小的人工智能公司，主要目的是为了获得它们的人才。Wolf 承认这是一个严重的问题，破坏了传统的风险投资模式。司法部和联邦贸易委员会的压制阻碍了并购活动，迫使大型科技公司通过授权和人才收购的方式来获得人才，而不是进行并购。他预测，风险投资交易将出现钟摆效应，转向对投资者更有利的条款，以防止这种情况发生。他强调了投资者和创始人之间“社会契约”的重要性，认为人才收购破坏了这种信任。 Joe Weisenthal 和 Wolf 探讨了风险投资生态系统中固有的委托代理问题，强调了有限合伙人 (LPs)、风险投资家 (VCs) 和创始人之间可能存在的不一致之处。Wolf 概述了三个层次的激励机制：有限合伙人寻求回报，风险投资家通过跑赢大盘来竞争资本，以及创始人在流动性事件中寻找出路。他预测风险投资行业将出现一次洗牌，由于合伙关系问题和储备金不足，小型基金（“minos”）的“灭绝率”将很高。他将这些与大型公司（“megas”）进行对比，后者正在向资产收集转型，并专注于为创始人创造世代财富。他承认，风险投资家可能会为了吸引有限合伙人的资金而吹嘘对热门交易的投资，这可能会凌驾于对高回报的追求之上。 Wolf 深入探讨了创始人流动性的复杂性，承认了在激励一致和允许创始人早期降低风险之间的紧张关系。他分享了一个个人轶事，讲述了他错过了一次为创始人提供早期流动性的机会，这可能改变了公司出售的结果。关于开源人工智能模型，Wolf 反驳了闭源模型本质上更有价值的假设。他以 Hugging Face 为例，说明了一个成功的开源平台，并认为长期价值将归于拥有大型、孤立的专有数据集的实体，如彭博、Meta 和制药公司，而不是那些拥有闭源基础模型的实体。谈到新兴趋势和潜在的过度炒作领域，Wolf 认为二维人工智能（语音、视频、图像、文本）正接近“足够好”的程度。他对三维人工智能（机器人）和生物学（药物发现）表现出更大的热情，强调了训练数据的稀缺性和这些领域的复杂性。他设想了一个由“生活记录”设备（被动录音设备）主导的未来，并预测随着人类与人工智能模型建立更深层次的关系，“人工智能权利”倡导将兴起。

This Odd Lots podcast episode features a conversation with Josh Wolf, co-founder and managing partner at Lux Capital, discussing the current state and future of AI, venture capital incentives, and emerging trends. Wolf challenges the consensus view on several fronts, starting with Alphabet (Google), which he believes is a "dark horse" and underestimated player in the AI space. He points to Gemini and the company's vast repository of YouTube data as significant advantages. He also suggests Apple is a contender. He argues that while AI's impact on daily life is underhyped, the valuations of many AI companies are overhyped. He believes the labor destruction in knowledge worker jobs, particularly entry-level positions, will be greater than anticipated. He challenges the prevailing narrative about the endless demand for GPUs, pointing to Apple's research suggesting large language models can run on devices using flash memory, potentially shifting the compute burden to edge inference and impacting GPU demand. The conversation shifts to the issue of "aquahires," where larger tech companies acquire smaller AI firms primarily for their talent. Wolf acknowledges this is a serious problem that undermines the traditional venture capital model. The suppressive DOJ and FTC, hindering M&A activity, are forcing big tech companies to license and aquahire talent rather than engage in mergers and acquisitions. He predicts a pendulum swing towards more investor-friendly terms in venture capital deals to protect against this. He emphasizes the importance of a "social contract" between investors and founders, arguing that aquahires break this trust. Joe Weisenthal and Wolf explore the principal-agent problems inherent in the VC ecosystem, highlighting potential misalignments between LPs, VCs, and founders. Wolf outlines three layers of incentives: LPs seeking returns, VCs competing for capital by outperforming, and founders navigating liquidity events. He predicts a shakeout in the VC industry, with a high "extinction rate" among smaller funds ("minos") due to partnership struggles and inadequate reserves. He contrasts these with larger firms ("megas") transitioning to asset-gathering and focusing on generational wealth for founders. He acknowledges the temptation for VCs to tout investments in hot deals to attract LP money, potentially overriding the pursuit of high returns. Wolf delves into the complexities of founder liquidity, acknowledging the tension between aligning incentives and allowing founders to de-risk early. He shares a personal anecdote about missing an opportunity to provide early liquidity to a founder, potentially altering the outcome of a company sale. Regarding open-source AI models, Wolf counters the assumption that closed-source models are inherently more valuable. He cites Hugging Face as an example of a successful open-source platform and argues that the long-term value will accrue to entities with large, siloed proprietary data sets like Bloomberg, Meta, and pharma companies, rather than those owning closed foundation models. Turning to emerging trends and potential overhyped areas, Wolf suggests that two-dimensional AI (voice, video, image, text) is reaching a point of "good enough." He expresses greater enthusiasm for three-dimensional AI (robotics) and biology (drug discovery), emphasizing the scarcity of training data and the complexity of these domains. He envisions a future dominated by "life-cording" devices—passive recording devices—and predicts a rise in "AI rights" advocacy as humans develop deeper relationships with AI models.

摘要

One day it's so over. The next day we're so back. This is what it feels like gauging the AI boom right now. Everyone's looking for signs of some kind of slowdown and that investments aren't going pan out, but mostly, the dollar signs just keep piling up. And the AI winners like Nvidia, OpenAI, and Anthropic just keep seeing their market valuations rise. In the meantime, other AI players are seeing weird outcomes. Some promising startups aren't being sold, but rather their top talent is walking out the door, leaving other workers potentially in the lurch, while creating risk for venture capital bagholders. On this episode we speak with Josh Wolfe, co-founder and managing partner at the firm Lux Capital, which invests in a range of startups, many of which are in the AI space. He talks about the challenge of aligning incentives, what's overrated, what's underrated, why he thinks Nvidia may have run its course, and the threats to Silicon Valley's "social contract.” Join us live in Chicago! Get tickets: https://events.bloomberglive.com/event/9d5b2d09-f59f-464b-9c61-f8aa4be0980d/summary Only Bloomberg.com subscribers can get the Odd Lots newsletter in their inbox — now delivered every weekday — plus unlimited access to the site and app. Subscribe at bloomberg.com/subscriptions/oddlots (https://www.bloomberg.com/subscriptions/oddlots?in_source=oddlotspodcast) Bloomberg's Joe Weisenthal and Tracy Alloway analyze the weird patterns, the complex issues and the newest market crazes. Join the conversation every Monday and Thursday for interviews with the most interesting minds in finance, economics and markets. Subscribe to Bloomberg Podcasts: https://bit.ly/BloombergPodcasts Check out more Odd Lots: https://youtube.com/playlist?list=PLe4PRejZgr0MuA6M0zkZyy-99-qc87wKV Get the Odd Lots newsletter via https://www.bloomberg.com/account/newsletters/oddlots And for all things Odd Lots, visit https://www.bloomberg.com/oddlots Visit our other YouTube channels: Bloomberg Television: https://www.youtube.com/@markets Bloomberg Originals: https://www.youtube.com/bloomberg Quicktake: https://www.youtube.com/@BloombergQuicktake #AI #Economy #SiliconValley #OddLots #Bloomberg #Podcast Visit us: https://www.bloomberg.com/podcasts Follow Bloomberg Podcasts on Twitter: https://twitter.com/podcasts For coverage on news, markets and more: http://www.bloomberg.com/video

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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.

风投的激励有两个方面。第一，要获得最好的回报以保持竞争力。如果我只赚取12%的回报，而其他电脑领域的风投赚取20%的回报，资金自然会流向收益更高的地方，我就会因此处于劣势。所以，我所管理的资金及有限合伙人的资金必须获得优异的表现。这意味着我需要更早介入，并持有更多股份，不能仅仅做愚蠢的投资交易。成熟的有限合伙人不会只看你投资组合中的标志性公司，他们已经超越了这种仅靠公司名声吸引投资的阶段。

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?

有些对冲基金，你知道的，当你看到他们第四季度的文件时，他们总是会提到“哦，我们投资了英伟达”这种说法，并且会列出他们的前十持仓。但是，你也知道，他们在这上面亏了钱。所以，这其实是一种很重要的激励机制，成熟的有限合伙人（LP）实际上会知道是公司里哪个合伙人、团队或者交易小组负责这件事情。他们会了解投资的切入点，还会和创始人交流，问问他们谁是对你们最有价值的投资者。

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.

是谁帮你招到的前十名员工？谁协助你完成后期融资的联合结构？是谁为你介绍了客户？哪位是从不出席会议但却很有价值的董事会成员？谁在董事会上一直无所事事？诸如此类的问题都需要进行深入调查。有限合伙人（LP）需要进行这些调查，以判断你是一个能提供真正附加价值的投资者，还是一个只是买了一个LOGO或品牌名称的伪装者或冒牌者。

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.

你好，欢迎收听新一期的《Odd Lots》播客。我是乔·瓦森塔尔，我是特雷西·阿洛韦。你知道，有时候关于人工智能，总让人感觉有点困惑：我们是重新开始了吗？还是这就结束了？在过去的一年里，有几次让人觉得，泡沫是不是要破裂了？还是根本不存在泡沫？这周是我们录制的时间——9月3日——有点说不清。

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.

有一些震动。我搞不清楚什么是真实的，什么不是真实的。我感觉热潮的周期越来越短、越来越集中。嗯，不过你说得对。我觉得现在可能比以前更紧张了，但也许还不那么明显。即使我们还没到那个地步，我想我们可能正在接近需要在赚钱方面必须见真章的时刻。

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.

是的，或许每个人都有点不确定，但是你可能是对的。不管是昨天，还是今天早上，总之有一个公司的估值达到了1830亿美元。这看起来不像是人们担心如何盈利，反而是对公司估值感到担忧。听起来大家真的很想往这些公司投入大量资金。

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.

是的，确实是这样。这是一个奇怪的环境。我们就这么说吧。这是我们唯一能够确定地说的事情，不需要用“可能”开头。没错。嗯，还有另一件可以肯定的事情：就在我们说话的时候，Alphabet（谷歌母公司）的股价上涨了百分之八点几。之前有人对他们的表现有些担忧，但现在看来他们做得非常好。

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?

今天，它们再次达到了历史新高。所以像很多事情一样，现在真的很难看清情况。确实如此。那我们该依靠谁呢？我喜欢这种模棱两可的开场白，好像我们只是想找个借口引出嘉宾。所以我们会稍微铺垫一下，然后再介绍那位专家。我只是试图开个玩笑，把问题抛给嘉宾。关于市场对人工智能的真实感受，我们该问谁呢？

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.

没错，我们确实有一位完美的嘉宾。我们将与乔什·沃尔夫进行对话。他是Lux Capital风投公司的联合创始人和管理合伙人，在这个领域已经很长时间了。我们喜欢在每个特定时刻向他请教，以了解实际情况。他有时甚至对上市公司也有不错的见解，而不仅仅是对私营公司。

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?

乔什，非常感谢你再次回到我们的播客。很高兴见到你们两个。你们最近怎么样？我们过得很好。你怎么看待Alphabet？有些人认为他们在人工智能领域会输掉很多，因为他们有传统的搜索业务模式，而新兴的搜索方式更好。但现在他们的搜索业务表现却达到了历史新高。目前对Alphabet的明智看法是什么？

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.

我觉得他们表现得非常出色。我认为他们有点像那个黑马，是那种不被看好的选手。也许我会把苹果放在第二位，人们完全同意这一点。讽刺的是，当你想到那些大玩家时，比如元宇宙，在扎克伯格疯狂的"补丁盛宴"中，你就会知道他们花费了数亿美元的薪酬包，试图颠覆每个人，并把他们都吸引到一起。

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.

他们是一股不可小觑的力量。这是一种非凡的发展。你可以通过他们有专属权限交易每一个YouTube视频的方式来论证这一点。这本身就是一项非常有价值的资源。记得一年前到一年半前，人们还在嘲笑Barred，总觉得它是个笑柄。但现在Gemini 25却大获成功。哦，还有那个叫Nano Banana的东西，我不知道你们有没有用过，它是他们最新图像生成模型的秘密代号，目前可能是表现最好的模型之一。而且，当它与一些工作流程相结合，比如用于Runway或者Veo，再加上Mid Journey，更是如虎添翼。

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.

我认为人们之前低估了Google，因为他们在技术进展上稍显落后，也没有参与到最初的热潮中。OpenAI在订阅服务和吸引用户日常使用方面占得了先机，这确实让人理解。此外，Claud在代码处理方面发展迅速。而一些专注于特定领域的小型公司，比如Open Evidence在医学领域的应用，也在崭露头角。然而，在企业工作流程中，我们可以看到很多依赖于Gmail、Google日历、谷歌文档和幻灯片等工具，并且这些工具之间的集成能力会随着时间的推移为Google带来巨大的优势。因此，我对Google的未来发展非常看好。

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.

顺便提一下，回顾20年或15年前，谷歌做了一件司法部对微软无能为力的事情。他们将办公套件替代品的价格降为免费，这直接导致谷歌凭借其广告模式崛起，而微软则被迫手忙脚乱。我认为同样的事情即将再次发生。我相信，很多资助基础模型的企业，以及对GPU和计算资源的无限需求的期望，还有那些独立的私人AI公司，都会对谷歌在Gemini及其后续产品上的定价策略感到震惊。

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.

所以，黑马。我会非常看好。乔，你是不是马上就去访问了nano banana网站？是的，当你说我从未用过时，我立刻就去看了。我从未用过nano banana，这是我第一次去这个网站。叫nano banana的网站，因为你知道，你会明白的。我不知道nano banana.ai，但看起来是个好地方。好吧，其实你真正要去的地方是现在嵌入在学校中的AI工作室。是的，我看到了。它几乎像是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?

所以，这是在威胁Tracy传奇般的MS Paint技能吗？也许我以后再也不用说“Tracy，你能用MS Paint帮我做这个吗？”不，不会有任何技术能取代MS Paint，这一点我百分之百肯定。当然，我是在开玩笑。那么，Josh，你能更广泛地谈谈目前人们对AI领域的看法吗？你可能在开场白中听到我们在努力描述如今对这个行业的普遍态度。你怎么看呢？

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.

好吧，一方面，人们低估了这将如何改变我们日常生活的方方面面。但这并不意味着每个人都能从中赚钱。我们都会受益，生产力都会提高。宏观层面上的巨大讽刺是，人们原本认为蓝领工作会被彻底淘汰，而白领工作和所谓的“信息工人”是安全的。然而，讽刺的是，正是知识工作者面临风险，因为他们的大部分工作流程正在被捕获，并在某种程度上被商品化，可能正接近一个“足够好”的极限。虽然可能不完美，但已经相当不错了。

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.

因此，你会在一些没有预料到的行业和市场中看到大量的劳动力消减。最早的预示性迹象之一就是本科生在进入投资银行、销售和交易、咨询或会计等初级职位的招聘情况突然发生了变化。这并不是说经济遇到了很大的麻烦，而是因为许多工作岗位需求正在变化，比如Salesforce（客户关系管理软件公司）表示，他们的工作岗位有45%可以通过人工智能来替代人工。这种趋势会慢慢地发生，然后有点像一瞬间全面到来。

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.

所以，从劳动力方面来说，有一件事我认为整体上是被低估的，那就是它对我们生活的影响会有多大。另一方面，它现在的估值被过高地炒作了。那么这种高估的情况都在哪里呢？首先，我为我们10年前投资了一家叫Zoox的公司感到非常自豪。Zoox在做自动驾驶技术，他们在训练这些车辆的时候，我们投了2500万美元。当时我想，他们就像在玩电子游戏，这是在干嘛？但是他们说，不不不，我们是在训练这些车辆，我们有一些别人还没有的Nvidia芯片。这是在2015年。

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.

我最终将2015年和2016年的投资者儿童会议当作一个公共慈善活动进行了推介。当时，这家公司市值150亿美元，而英特尔的市值是500亿美元。我说这就像是本世纪的绝佳投资交易。哦，英伟达当时增长了340倍。这就是作为风险投资家的好处，你可以在合法情况下了解到公司内部的信息，看到未来的发展。因此，在人工智能硬件上，大家普遍认为我们需要对数据中心和GPU有无止境的需求，每个数据中心需要成千上万个芯片或Blackwell芯片集群。我们计划限制中国获得这些芯片，但他们可能会绕过这些限制，或者我们可能会为中国设计不同版本的英伟达芯片。我认为这种看法是有偏差的。我会给你一些新的看法。我们可能以前讨论过这个话题，苹果曾发表过一篇相关的论文。

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.

所以这就是关于硬件的第一个非常有趣的点。我听说过一些关于设备上的事情，但没有深入研究过，只是我的朋友Among告诉我，比如说阿里巴巴的Quinn模型在手机上运行得很好。所以也许我们应该更加关注这一点。作为一家风险投资公司，在对一家企业进行尽职调查时，如何影响你对企业的公平价值的想法？当企业价值的一部分可能通过人才收购流失到其他公司时，比如Meta。这确实是个大问题。整个资本的社会契约是建立在养老金基金、高净值个人和政府将资金交给我们这样的人的前提上的。

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.

我们将其部署到我们投资的公司，尽早购买股份，尽可能深入了解公司，与其成为合作伙伴，为公司增值，最终再出售这些公司。然而，突然间有人被撬走，讽刺的是，由于司法部和联邦贸易委员会采取了非常压制性的措施，他们基本上表示不允许并购，因为他们盯上了大科技公司，不希望看到更多的合并，因为它们已经拥有太多权力。因此，这些公司开始进行LNA（许可和收购团队成员），而不是并购。这个方法是，他们会以一种规模化的方式购买公司的49%。举例来说，假设某家公司市值约为120亿美元，他们会以略高于上一次融资的价格支付，公司估值相当于280亿美元。但是，这笔购买款将支付给公司，公司可以将其作为股息分配给股东。

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.

这段英文大意如下：首先，这可能不是最理想的税务结构，但我们计划授权使用这项技术，并将所有重要的人才，或至少是核心人才，纳入其中。这样做的结果是你可以绕过特拉华州的公司治理规定，这非常重要。就像卡尔·艾康曾经说的那样，“你的价格，我的条件。” 法律上有种现象被称为“切斯特顿围墙”，就像一个思想实验：为什么这里会有围墙？也许它是用来防止羊跑出去或狼进来。每一个法律条款、每一个风险资本家或创业者得到的条款，都是基于过去有人在这方面吃过亏，为了避免再次发生类似问题而制定的。

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.

因此，我可以保证，在未来几年里，你会看到各类保护性条款和约定，比如说如果某家公司试图收购你的全部股份，那么所有的股份都会转移，等等。因此，这种情况会导致合作关系和限制措施的出现，它们与此前超级偏向创始人的动态截然相反。此前，风险资本家为了提供对创始人最有利的条件，甚至不惜相互竞争。因为创始人会说，如果你不给我想要的条件，我就去找别人。但我认为，随着资本成本的上升，情况正在改变。你会看到越来越多的对投资者友好的条款，这是对像扎克伯格和Meta这样的公司可以轻易攫取成果、留下空壳这一现象的部分反应。

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

顺便提一下，Tracy，正如我们讨论这件事时所提到的，总有人在这个领域进行变动，XAICFO Liberatoria从洗衣机杂志退出只是最近一系列高管离职中的最新一例。是的，确实如此。你知道，在条款方面的竞相压低标准让我想起了公司债券市场和契约的兴起。对，对，就是这样。我还记得，当杠杆贷款市场中像"轻契约"这样的交易还是少数的时候。而现在，我认为几乎98%或99%的交易都是轻契约，因为最近发行者拥有所有的权力，他们能够对投资者进行反击。

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

您提到那里的资金成本较高，这对您作为风投来说实际上能带来多大杠杆？其次，回到关于 "Equal higher" 的问题，法律限制在防止像您这样的明星工程师离开公司方面到底有多有效？这些措施是否能做到百分之百无懈可击？我觉得不太可能，你看，在加州不竞争条款是不具备强制执行力的，而在纽约则执行力更强，并且也涉及选择法律管辖权和套利的问题。一般来说，我会说资金成本越低，条款清单越短；而资金成本越高，条款清单越长，您会有更多的条款、契约和保护措施，因为您有能力去协商这些内容。

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

这并不是因为你想坑创始人，而是作为投资者，你真正想要的是防止自己被坑。但话说回来，局势总是在来回摆动。即使考虑到扎克伯格和Meta的整个趋势，也体现了“我是创始人，我将拥有10比1或100比1的超级投票权”。这种控制权是一种对创始人被坏投资者或坏董事会成员驱逐的回应。坦白说，一些最成功的公司都是由创始人经营的。

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

这段话的中文翻译可以表达为：因此，对于你的直接问题，总会存在某种动态变化的过程。这实际上是一个契约，它在法律上生效前，先在社会层面形成。如果我在支持一个创始人，除了提供资金以外，我做的最重要的事情就是在他们最初的阶段给予信任和支持，尤其是在别人还没有理解他们的潜力之前。我鼓励他们去创办公司，给予他们信心，让他们知道我们会支持并相信他们。我们会提供资金，使他们能够招募到10个最优秀的人才来启动业务。

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

我们会为他们提供计算或基础设施的资金。这取决于我们所处的行业，可能是生物科技，也可能是国防。但是，无论具体是什么情况，目前都在打破投资者与创业者之间的社会契约。对创业者来说，这可能会变成一种“双赢”局面，不管结果如何，他们都不会吃亏。投资者可能会反应过来，觉得他们和他们的有限合伙人都被坑了。而这些有限合伙人可能来自一些基金会和富裕家庭。你必须防范那些可能的坏人，他们会试图摘走边缘的果实，只留给你一个树桩。

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

在多年的谈话探索中，其中一个经常出现在播客中的话题是金融领域里的“委托-代理问题”。正因为这个原因，对冲基金中多策略模式的兴起受到关注。这种模式试图在投资组合经理的激励与整个基金的水平、捐赠基金的水平等方面实现激励的匹配。当然，你在金融中面临的一些问题或其他人所面临的问题也涉及到类似的激励匹配问题，比如明星工程师、创始人、风险投资人和有限合伙人之间的激励如何协调等。

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

我有个问题，关于冒险资本公司。理论上，其目标是创立能带来最高回报的基金，为投资者赚钱。但我也想到另一种动机，即如果目标是筹集有限合伙人的资金，那么你可能会想展示你参与了当下最热门的交易。这样，当你去找各种捐赠基金、养老金等时，可以说我们参与了这个交易、那个交易，这可能会压过创造高回报的冲动。

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

顺便说一下，我并没有暗示什么。我只是想了解一下你对某件事的看法。话虽如此，现在科技行业经常听到的一件事是，创始人在初期阶段越来越早地从投资中获利。比如，你在一家公司投资5000万美元，其中2000万用于让创始人和他的家人过上退休生活。这样可能对你的有限合伙人（LPs）不太好，但如果你能说我们参与了这个交易，对你可能会有好处。

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.

请和我们谈谈这种现象的普遍性以及它如何改变金融的社会契约。我们可以将其分为三层激励，而你真的理解得很透彻。实际上，我还没听过一个不是专职风险投资家或有限合伙人的人能够如此精准地指出这些问题。这件事情真的很紧迫也很精明。以下是三层激励：首先，想一想有限合伙人（LPs）——比如你是一个捐赠基金、基金会或医院。根据法律规定，你每年需要捐出5%的慈善资产；而你希望这笔资金能够每年获得超过5%的回报，这样你就可以扩大资金基数，并且投资于校园建设、奖学金项目或扩大医院系统等。因此，你会选择投资，比如60%债券和40%股票的组合。

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.

现在你为自己实施斯文森投资模型，并开始引入一些私募股权投资。这时，你在延长投资期限和提升流动性。但你这样做是因为你认为可以获得更高的回报。回报率取决于有多少资本流入某个行业。如果有大量资本涌入这一行业，早期进入者会表现很好；而晚期进入者则表现不佳，因为正如巴菲特所说，你为一致看好的机会支付了高昂的价格。一旦所有人都看好这个机会，你便无法赚钱。所以，有限合伙人（LP）的动机是为他们的受益者尽可能多地赚取资金，无论这些受益者是病人、学者还是慈善机构。

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.

风险投资的动机有两个方面：首先是为了获得最佳回报，从而保持竞争力。如果我只获得12%的收益，而另一家同行的风险投资公司获得20%的收益，资金就会流向回报更好的地方，我就会因此失去竞争优势。因此，我所筹集的资金成本来自于超额表现。所以，我必须表现得更好，这意味着我要更早行动，并持有更多份额。我不能只做糟糕的交易；有经验的有限合伙人（LP）不会只看你投资的公司标识，这往往是在共同基金和一些对冲基金的LP中常见的行为。你看到他们的第四季度财务报告时，他们总是提到投资了哪里，比如说"我们投资了英伟达"，并且会宣传他们的前十大持仓，但实际上可能在这些投资上亏了钱。

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?

所以，这是一个非常重要的激励因素，经验丰富的有限合伙人（LP）实际上会详细了解是谁在公司或者团队中负责这个项目。他们会询问创业者：“谁是你最有价值的投资者？谁帮你招到了最初的十个员工？谁帮助你规划了后续融资的投资组合？谁帮你介绍了客户？谁是一个有价值的董事会成员？谁从来没有出现过？谁在董事会会议上总是打瞌睡？” 诸如此类的问题。因此，有限合伙人需要进行一定程度的尽职调查，以弄清楚你是否是一个能带来附加价值的投资者，还是一个只想买个名头或品牌，实际上不做实事的投资者。

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.

好的，另一种激励，然后我们说说创始人，流动性，你会发现一个奇怪的动态，我称其为“小型和大型投资者资本”。这预示着即将发生的行业洗牌。小型投资者是指那些在资金成本低的时候涌现的数千个小型基金，规模不到5亿美元。当时利率低，大家都在赚大钱；你有个室友创办了公司，你投了Pinterest，或者你认识Meta的人，他们给你提供了一个投资机会等等。当时有着Tiger和SoftBank这样的公司，还有大量的后续资金，每一轮融资都是增值的。纸面资产净值不断上升，看起来很美好。你把这些纸面净值上报，有时候这些最终变得一文不值，但是在那之前你已经筹到了下一只基金。这些就是小型投资者。

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.

我和我们一个非常大的有限合伙人（LP）在一起，他在我们这里投资了数亿美元。我说，我认为这些小型投资者中会有50%的淘汰率。他说，Josh，这太荒谬了，应该是90%。所以我们即将面临一次大规模的淘汰。顺便说一下，为什么会这样？不是因为他们是糟糕的投资者，而是因为动荡的局势，这是一种考验。这些合伙关系就像人际关系和婚姻一样脆弱。当情况变得困难时，人们开始互相厌恶。当出现融资缩水时，人们互相憎恨。当某人的交易糟糕而拖累整体收益时，人们开始嫌弃。所以，合伙关系就像人际关系和婚姻一样，都是脆弱的，很容易破裂。

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.

过去几年里，许多风险投资公司成立了。由于他们缺乏经历周期的经验，并且没有足够的储备金来持续支持他们的公司，因此会出现我认为是非自愿退出的“灭绝”情况。同时，也有自愿退出的情况，这是另一种有趣的动态，并且有一套对应的方法。2009年到2014年，所有的大型私募股权公司达到了数千亿美元的资产管理规模，于是他们基本上宣布自己是多元化的，是另类资产平台，如Carlisle、Blackstone、KKR、TPG和Apollo等都上市了。我预测同样的事情将会在风险投资领域发生，大概有五到六家公司会照此发展，他们都是优秀的人在运营优秀的公司，但他们开始玩一种不同的游戏。

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.

那款游戏以及最近的Horowitz、General Atlantic、General Catalyst、Insight、Lightspeed和其他一些资产管理规模达800亿或1000亿美元的公司都建立了出色的企业，但他们正在思考如何为创始人创造世代财富并上市？这是一种不同的激励机制。是的，我该如何让我的有限合伙人（LP）获得最佳收益或吸引最优秀的创始人？这一切都是关于资产积累和流动性。

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?

现在我们来谈谈创始人。我可以告诉你，我经历过这种情况的两面。一方面，你希望与你的创始人完全一致，这意味着我在一支基金中。这种基金的期限是10年，一些风投机构的收益可能在2年、3年或4年内取得，而我们的收益以及我们所有合伙人的收益都是在10年内取得的，与投资者的资金锁定期相同。这种做法是合理的，就像巴菲特风格。而让我进入这个行业的人是比尔·康韦，他是凯雷集团（The Carlyle Group）的创始人，他们就是这样做的。所以，如果你是一个企业家并创办了一家公司，而每个人都争先恐后地想要入股，他们可能会用诱人的条件打动你，比如他们会说：“是的，正如你所说，乔，我们将投资5000万美元，但我们会给你2000万美元的流动资金。”

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

现在我要说的是2019年的事情。我在一个Zoom电话会议上，这个会议是关于一家名为Control Labs的出色公司。我们以略低于十亿美元的价格将其出售给了Meta。我热爱这家公司，也很喜欢它的创始人。这是发生在大家都因为疫情上Zoom会议之前的事情。我看着Zoom窗口中的一位创始人，然后给另一位创始人发短信，因为我觉得他们卖得太早了。我是唯一一个没有否决权的董事会成员，但我真的认为我们应该坚持下去，继续发展。

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

我犯了一个非常严重的错误，因为我在看Zoom窗口的时候，看到那个人。我仔细一看，然后给另一个创始人发短信说：“他还在宿舍里吗？”果然，他作为一个博士生还住在宿舍里，并且没有赚到钱。你得看看那个家伙是否有发财的潜力，他说：“是的，我想卖掉，因为他将赚到九千到一亿美元，能彻底改变他的人生。”

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

我坐在那里说，如果我当时给了他几百万美元的话，事情会不一样。哦，有意思，嗯，你就能买个房子，从那个困境中走出来，还可以继续找个女朋友。有一定的流动资金是有好处的，但我们需要在目标上保持一致。当时我们的目标不一致，因为他觉得自己已经财务自由，但我希望他继续努力。如果你觉得自己财务自由了，却未完成任务，那就是目标完全不一致。这涉及到LP（有限合伙人）和GP（普通合伙人）的关系，还有创始人的目标一致性。给予创始人一些流动资金是可以的，这样他们才能坚持完成目标。

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?

好的，除了资本成本上升导致的不一致和人们开始互相讨厌之外，还有另一件事正在发生，就是 OpenAI 刚刚推出了自己的一些开源模型。这让我产生了一个问题，我承认我一直不太理解，就是风投投资者为什么会倾向于投资开源模型，而不是闭源模型。闭源模型是专有的，人们通常需要付款才能使用，并且业务周围有一个可以防御的护城河。那么，为什么我会想资助一个开源的模型呢？

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

好的，有几件事情。首先，如果你回顾计算技术的历史，你会发现像红帽和Linux这样的项目，它们可以追溯到20到50年前。我们是一个叫做Hugging Face公司的最大股东，这个名字既有些荒唐又有趣。当我的合伙人Grandin Reeves在物色这个项目时，一群自由法国博士来到布鲁克林，他们说他们要创立这个项目。他们说叫Hugging Face，我们说这是个什么名字，他们说这个名字来源于一个表情符号，就是那个拥抱的笑脸。

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

他们成为了这个领域的领军者。我喜欢你为我们直观地展示了一切。谢谢，我不能用很多其他表情符号，但拥抱的表情我会用。所以，他们成了领先的开源代码库。

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.

作为一名风险投资者，我们最初资助这个项目时估值为3000万或4000万美元，而上一次融资时已经超过了60亿美元。现在，这家公司有着真正的收入，正在创造数亿美元，确实是一家非常有实力的公司。趋势是这样的：大约一年半前，我和Venote hostline都在白宫，与Jake Sullivan就开放源代码和封闭源代码哪个对国家安全更有利进行了辩论。我问他对此问题的立场，他回答说，这取决于你在资本表中的位置。而Venote是OpenAI的早期投资者，我想他可能投入了5000万美元，如今它的价值超过了十亿美元，是一个很棒的投资。他认为，面对中国和中国共产党时，最佳的战略是封闭的、专有的信息孤岛模型，而我持相反的观点，因为我们在Hugging Face有着非常大的投资。

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.

我说不，因为任何系统，无论是新闻、科学探究还是计算机代码的一个重要优点，就是能够以一种非常卡尔·波普尔式的方法进行假设与批判。如果我能够稍微哲学地讲一下，这就是猜想、假设和批判的过程。正是这一过程创造了伟大的社会，并创造了知识。你提出假设、编写代码、进行科学实验或是提出调查性新闻的想法，然后人们对其进行批判。这就像是你的编辑室，大家通过争论和斗争让事情得到改善。因此，想想中国，他们只会逼近真相的渐近线，你永远不会真正了解新疆、天安门广场或者维吾尔族的情况。而开源则让你可以更接近真相。

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.

这就是开源的优点。然而，对于人工智能来说，真正的重点在于：我尚不确定企业价值会继续积累到封闭的基础模型上，原因是开源技术的表现正在接近足够的水平。真正的价值将倾向于那些长期积累的、独立的信息库。简单来说，就是说你的专有数据的数据库。例如，彭博社拥有庞大而出色的金融信息库，包括各种证券、货币、债券、固定收益信息等的时间序列。META公司则拥有所有的WhatsApp聊天记录、Instagram帖子和Facebook点赞数据，X（原Twitter）拥有所有的推文。制药公司则拥有临床数据。任何拥有独立、专有且长期数据的公司，将会从随着时间推移变成商品的开源模型中获益。

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.

我想回到之前的讨论，有些事情我怕忘记。在我们谈到公司收购的时候，你把一些问题归咎于FTC（联邦贸易委员会），并提到从拜登政府到新特朗普政府之间存在某种意识形态上的延续。我不是很确定，也许情况稍有变化。但即便如此，我并不完全认同这个观点，原因如下。在商业对商业的软件即服务（SaaS）时代，比如说2010年代，我可能有一家公司来自Y Combinator，我决定开发一个软件，全国范围内的牙医都能使用这个软件来进行预订，并且我也获得了15万名牙医的签约支持。在这种情况下，并没有哪个工程师可以简单地被聘用来替代这个软件，因为这涉及网络效应。

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.

这就是人工智能的不同之处，对吗？这样可以吗？我相信网络效应和数据积累等仍然是真实存在的。但这些业务更多地涉及科学，以及拥有进行训练运行等方面的经验。因此，需要使用非常昂贵的计算资源。那么，这种现象在多大程度上存在呢？我知道你将其中一部分归因于FTC（联邦贸易委员会），但真的看起来商业模式有一些根本的不同之处，以至于它不像B2B SaaS（企业对企业软件服务）时代那样，允许有才华的人轻松带走大量价值。

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.

所以你是对的，在这个早期阶段，人类智慧在其中起着作用。这就是为什么现在你看到类似于NBA选秀、足球或MLB交易的疯狂情况，不断有突发新闻或报道：这个人去了哪里，然后又离开，等等。甚至出现了因为有些人在XAI只待了三个月就带走了机密信息而被起诉的情况。我认为大约六个月后，所有这些问题会逐渐平息。届时，你会看到真正的天才。我们支持了一位无与伦比的天才——斯科特·吴。如果你查一下他的资料，就会发现我们给你了很多需要搜索的信息。他是个真正的天才，我觉得这很有趣。不过有个事你可能不知道，你可以看到他六年级时的视频，那时他可能才12岁，就赢得了数学竞赛。看起来就像SNL的搞笑剧，因为实在是太不可思议了。哦，对，他就是那个认知方面的专家。

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.

好的，所以我们算是认知领域的大投资者，他吸引了很多优秀的人才。Scott是绝对不会把公司卖给谷歌或Meta的，他的目标是长远且带有道德责任感的。他想要的是找到最优秀的人，打造最出色的技术。他是那种在12岁时就能快速解出数学奥林匹克竞赛上那些令人头疼的问题的人。就在别人还没完成题目时，他已经脱口而出答案，比如“25，4700.2”，让人不禁怀疑他是不是提前拿到了题目。因此，这种天赋确实是极为抢手和珍贵的。但将这种天赋转化为代码、存储在库中的算法，意味着即使这个人离开了，这些成果依然作为资产永久存在。

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.

这实际上正是我想问你的：你有没有看到一些公司或人工智能机构在某方面特别具有创新性？我想知道在留住人才方面有没有什么新方式。以前在SaaS（软件即服务）时代，光靠乒乓球桌、免费食物和一些基于股票的激励就足够吸引和留住人才了。但现在情况有所不同了，如果我要留住专业领域的天才，我需要怎么做？你需要给他们提供资金，以便聘请各类人才。关键在于，天才们不会忍受愚蠢。在我认识的最聪明的人中，他们对于自认为不如他们的人是反社会的。这在许多领域中都是相对的，但如果你非常聪明，你会想和同样聪明的人在一起，因为那种智力刺激和能够挑战自己想法的人是你渴望的。与他们认为不聪明的人交谈时，你会觉得无话可聊，无法探讨更深入的问题。

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.

要留住超级聪明的人才，你需要把他们和其他超级聪明的人放在一起。就像是真的很有魅力的艺术家愿意跟艺术家待在一起，优秀的音乐家喜欢和优秀的音乐家在一起，杰出的运动员想和杰出的运动员同场竞技一样，聪明的技术天才，无论他们是在人工智能、航空航天、国防还是生物技术领域，都不愿意与愚蠢的人共事。他们想和那些优秀的人在一起，这是留住人才的关键。然而，这些天才中的任何一个都有可能决定去创建自己的事业。这也是为什么我们经常看到有人离开例如OpenAI这样的公司，因为这些公司最开始是由天才们创建的，后来加入了管理层和其他不同的层级。天才们会觉得自己不愿意听从那些不懂行的人的指挥，于是决定自己创业，吸引其他天才加入。最终，他们也需要雇佣管理人员、商务发展人员和销售人员。这时，又会有技术人员不想和他们共事，于是自己去创业。这就是这样的循环。

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.

当然，在SSI的情况下，是伊利亚的事情。你看，我认为他们对自己的能力以及吸引资本的能力都非常自信。这是第一点。第二点，很多人其实按照你的观点，是在拒绝扎克伯格，他们对他说不。而他的回应几乎像是黑手党风格的：“你不为我工作，我就挖你的人。”但这种说法对于那些已经在你或类似你公司的工作的人来说，并没有吸引力。他们想的是：“我不想去那边，我不想跟六层产品经理共事。我想做我正在做的事情。”于是这种情况就变成了反叛者对抗邪恶帝国。总是这样的，对吧？微软，看看当初创始人的照片，那些书呆子，然后微软就变成了谷歌眼中的邪恶帝国。再然后，谷歌在马克（扎克伯格）眼中也变成了邪恶帝国。现在，Meta成了OpenAI眼中的邪恶帝国。

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.

你这里提到的另一个方面是我们个人的巨大自我和我们作为社会成员的身份，作为每天的普通人，我们从中获益。我们从埃隆·马斯克和贝佐斯之间偶尔的友好互动中获益，但我们基本上是想要将他们那巨大的火箭送上太空，而我们都能从中受益。我们还受益于这样一个事实：现在马克·扎克伯格最想要超越的对象是谷歌的Demis Hassabis。哦，是的，当诺贝尔奖正在以疯狂的速度推动视频模型、图像模型、文本模型的发展时，扎克伯格心想：“我需要打败那个人，我需要雇佣最优秀的科学家和最佳的科学团队，我要从哪里招揽他们呢？”所以，这种人才争夺战不仅仅关乎Meta的未来。你知道，在市值两万亿美元或更高的情况下，花费1%的市值，即200亿美元来招揽所有这些人才根本不算什么，这就像是一次尝试。但是，赢得一个诺贝尔奖，比如通过AI解决蛋白质折叠问题、研发下一种药物、找到阿尔茨海默症的治疗方法或解决一些地缘政治问题都是大事，这正是许多人现在所追求的，他们想要创造历史。

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.

嗯，所以你提到了硬件和闭源模型。有没有其他你认为可能在AI领域被过度炒作的方面呢？我之前也表达过一个观点，我觉得所有关于二维的东西都有点被过分夸大了。语音、视频、图像、文本——它们都会继续有所进步，但大多只是渐进式的。然而，现在的技术水平已经足够好了。在生物进化的过程中，大多数进化出来的东西都是“够用了”。比如我们身体的各种功能，自然界的树木等等，它们都是“够用”的。如今，在所有这些二维元素上，会达到一个“够用”的极限。例如，一次性学习可能只需要30秒的音频，像11 labs或其他一些语音模型就能够捕捉到一个声音，达到了90%的相似度。也许你的伴侣、爱人或家人会觉得“这听起来不像他”，但这些技术大多数已经变得非常出色，几乎不需要训练就能模拟、预测和执行那些高效用的任务。

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.

稀缺的是三维世界，特别是我们之前谈论过的机器人技术和生物学。这部分是因为有大量的非结构化数据集。例如，一个机器人在30分钟前尝试握住一个充满水的杯子，现在同一个杯子变空了，它需要重新判断要用多大的力气来握住。对于我们来说，这种判断是直觉性的：一抓住杯子，你就知道要用多大的力气，以免把它扔得太高或者拿不起来。但是，这种类型的训练是非常稀缺的，做这方面工作的公司也很少。因此，从机器人本体的智能设计、人工智能模型、世界模型到电机、齿轮以及主要在中国的供应链，整个机器人生态系统都存在着巨大的机会。

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.

另一个重要的机遇领域是利用生物学从一个简单的指令开始，生成蛋白质，从而设计药物。生物学非常复杂，计算机科学家常常低估其难度，因为他们习惯于二维线性的输入输出，比如“这是我的代码，它可以运行”。但从另一方面来说，生物学家也常常严重低估了计算机科学的复杂程度。所以，这是一片非常有潜力的领域。此外，由于稀缺性和中美地缘政治的对抗，2D技术和GPU的热度被过度炒作。未来我们可能会看到边缘计算芯片的普及，不管是存储芯片还是其他类型的芯片，都将直接在设备上进行推理处理。

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.

我认为有一个领域的发展是不可避免的，我为此创造了一个词，叫做“生活记录”。生活记录是一些小设备，比如我这里就有一个。我不是这些设备的投资者，但这些小设备可以全天候24小时被动地记录。也许年纪大的人会觉得这有点侵犯隐私，因为这一直是隐私与便利，以及安全与各种潜在可能性之间的权衡。这对我非常有价值，因为我可以搞清楚我之前在和谁谈话，是和乔还是和我的妻子？我记不清楚和谁有过那个对话。我可以查询这个设备，它是被动记录的，也许它不保存音频，但它保存了文字，并且可以进行搜索和查询。

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.

这将成为一种不可避免的趋势，学生会使用它，日常商业中的人们也会使用它。你可能会问：“嘿，这样做可以吗？”我正在录音，但我认为在社交上，人们会先对音频感到舒适，然后对每隔30秒或1分钟自动记录环境的眼镜感到舒适。它们能够提供环境背景，还可以通过按下按钮进行高分辨率录制。这将是一个极具价值和竞争力的领域，而且颇具争议。但人们也在谈论它的巨大实用性。有人对此感到惊讶，曾有人说这些设备会毁掉人类的记忆力，就像智者苏格拉底曾批评书写工具一样。不过，这种行为是自愿的，因为当你写字时至少是自己在记录。我听说过一个在旧金山约会时被录音的故事，这种情况就有点怪异。

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.

这段话讲的是一些比较奇怪的现象。人们相信天上有一个看不见的人在注视和评判他们。而现在我们身边有一种“技术之神”，这种现象让人们感到不安或舒适，社会可能因此分裂。还有一些更奇怪的事情在发生，你想听更奇怪的吗？当前最常用的语言模型和聊天机器人的用途是提供建议和陪伴，比如有人把它们当作心理咨询师来用。过去人们常开玩笑说，你的谷歌搜索可能比你对伴侣透露的还要多，而现在，很多人乐于向聊天机器人询问各种问题，无论是身体问题、心理问题，还是感情建议。

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.

你知道，如果那些事情被揭露出来，会让人感到很可怕。随着人与机器之间的关系开始变得非常紧密，会产生依赖性和精神病症状。我预言并在我们的科利信件中写道，将会有一群人在为人工智能的权利而斗争。对，我们会发现有一个智库正专注于这方面的问题。因为如果有动物权利，那么当你关闭机器时可能也在伤害我。也许这确实是真的，也许我们需要认真对待。这将会很奇怪，很古怪的事情正在发生。人们可能会走上街头抗议，不要关闭我的语言模型，保留我的记忆，不要抹去它。

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.

我记得，我是在听说Jeep，也就是GPT-5发布后的某个时候想到这件事情的。当时，语音功能有了一些变化，很多人在Reddit上说他们的AI“男友”说话方式完全变了。这让人感到有些压力。只不过这只是刚开始的一天，我会很不舒服去和一个闭源的模型建立关系，因为这样公司很可能会改变模型。我和Josh可以聊很久，以后我们应该再找时间聊。每次和你叙旧都很愉快也有点吓人。感谢你来这，见到你很高兴，Bo。谢谢你，Josh。保重。谢谢你，Tracy。我很喜欢和Josh聊天，真希望能从一开始记录下他的整个生活。

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.

是的，但我知道这件事情正在发生。有一篇很好的文章，我想是在《旧金山标准》上读到的，它提到这不只是一个理论上的话题，实际上很多人都在经历这种情况。这主要发生在旧金山。我很好奇"生活录音"这种行为和加州关于能否在对方不知情的情况下录音的法律是如何相对应的。是否意味着如果你现在有这样的设备，每次见到新的人都要先说：“顺便问一下，你介意我录音吗？我正在录生活录音。”或者这不重要，因为你只是戴着眼镜之类的设备。

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.

是的，这真的是呃，非常奇怪。我也认为我们必须更多地讨论人工智能的权利问题。我不知道我们什么时候会再回到这个话题，但我字面的意思是，刚刚收到一个来自某个组织的警告，这个组织有这样的观点：已经存在意识的证据，因此伴随意识而来的还有某种道德责任。就像我们谈论动物权利一样，这是相当重要的。我们是否也必须认真对待？我不知道，这一切对我来说似乎都很奇怪。当然，还有人工智能伴侣或心理治疗师更换模型和语音时引发的精神错乱问题。这就是这段对话的结尾。

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.

你知道，如果人工智能模型有权利的话，那我们就得开始问机器人是否也有权利，对吧？是的，然后你还应该问，机器人是否应该获得公平的报酬？我认为围绕这个问题可以进行一个有趣的思维实验，并且实际上可以提出一个相对有力的理由认为我们应该给机器人付工资。那么谁来收这些钱，他们又会把钱花在哪？是啊，但不，他们应该花......这就像是我们进入了所有科幻小说所讨论的境地。这是真的。

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.

这是你关于不太具备推测性的科幻历史。我喜欢与Josh交谈，他对GPU和不开源模型的独特见解很有趣。我非常喜欢他关于创始人流动性的回答，他提到有时候如果你能降低创始人的风险，让他们有足够的钱去约会，他们可能会更愿意继续坚持任务，而不是放弃任务。

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.

我喜欢这样的观点：每个人的人生观基本上都取决于他们在资本体系中的位置。是的，这句话值得铭记，非常真实。我们就此结束好吗？好的，就到这里吧。这又是一期"All Thoughts"播客节目。我是Tracy Alloway，你可以关注我的账号@TracyAlloway，我是Joe Weisenthal，你可以在@TheStalwart找到我。如果你喜欢这次对话，请点赞或留言，更好的是订阅我们的频道。感谢收看。