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20VC: Who Wins in AI; Startup vs Incumbent, Infrastructure vs Application Layer, Bundled vs Unbundled Providers | From 150 LP Meetings to Closing $230M for Fund I; The Fundraising Process, What Worked, What Didn't and Lessons Learned with Tomasz Tunguz

发布时间 2023-04-21 07:26:24    来源

摘要

Tomasz Tunguz is the Founder and General Partner @ Theory Ventures, just announced last week, Theory is a $230M fund that invests $1-25m in early-stage companies that leverage technology discontinuities into go-to-market advantages. Prior to founding Theory, Tom spent 14 years at Redpoint as a General Partner where he made investments in the likes of Looker, Expensify, Monte Carlo, Dune Analytics, and Kustomer to name a few. Tom also writes one of the best blogs and newsletters in the business which can be found here. In Today's Episode with Tomasz Tunguz We Discuss: Founding a Firm: The Start of Theory: Why did Tom decide to leave Redpoint after 14 years to found Theory? What are 1-2 of his biggest lessons from Redpoint that he has taken with him to his building of Theory? What does Tom know now that he wishes he had known when he started investing? 2. From 150 LP Meetings to Closing $230M: Raising a Fund I How would Tom describe the fundraising process? How many meetings with LPs did he have? How many did he know previously? What documents did he share with LPs? Did he have a dataroom? How did he use it? How did Tom create a sense of urgency to compel LPs to come into the fund? How does Tom feel about the debate between one close and multiple closes? What was the #1 reason LPs said no to investing? What worked and Tom would do again for the next raise? What did not work and he would change for the next raise? 3. Where Will Value Accrue in the Next Decade of AI: Startup vs Incumbent: Will incumbents embrace AI before startups are able to acquire distribution? Infrastructure vs Application Layer: Where will the majority of value accrue in the next decade; infrastructure or application layer? Bundled or Unbundled: Will bundled services be the dominant consumer and enterprise choice or will unbundled specialized solutions win? 4. AI and The World Around It: How does Tom believe AI could save the US economy? Why does Tom believe Google are the losers in the AI race? Which incumbents have responded best to AI? Why does Tom believe we will be in a worse macro place at the end of the year than we are now?

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中英文字稿  

I think at the foundational model layer, that's a big boys game or a big girls game. The odds of success are going to be significantly higher at the application layer because the diversity of needs there is greater. We faced with a technology that could actually replicate the post-war surplus out of World War II. I think Google had a rude awakening where, to some extent, they developed in-house but ignored. So it's a classic innovator's dilemma.
我认为在基本模型层面上，这是一项大人物的游戏。在应用层面上，成功的几率要高得多，因为那里的需求多样性更大。我们面临着一项技术，它实际上可以复制第二次世界大战后的过剩。我认为谷歌经历过一个粗鲁的觉醒时刻，在某种程度上，他们是在内部开发，却忽视了外部机遇。因此，这是一个经典的创新者困境。

This is 20VC with me Harry Stebings. Now the last time I had Tom Tunger's on the show was seven years ago. As he's become a dear friend and last week he announced his new $230 million fund. Theory Ventures. No one deserves this more than Tom and it made me so so happy to see. Prior to founding theory, Tom spent 14 years at Red Point as a general partner where he made investments in the likes of Luka, Expansify Monte Carlo, Junanelitics and customer to name a few.
大家好，我是Harry Stebings，欢迎收听本期的20VC。上次我请到Tom Tunger是七年前的事了。经过这么长时间，他已经成为我的好朋友。上周，他宣布创建了一支新的投资基金，总额为2.3亿美元，名为Theory Ventures。我非常高兴看到他能够获得这个机会，没有人比他更值得了。在创建Theory Ventures之前，Tom在Red Point投资公司担任了14年的总合伙人，他曾经在Luka、Expansify Monte Carlo、Junanelitics和Customer等公司做出过投资。

But before we dive into the show, Dave, help me talk about Coda. Coda is the doc that brings it all together and how it can help your team run smoother and be more efficient. I know this because Coda helps me. At 20VC, we use Coda for all of our research for every episode so all team members essentially can work on the schedule all in one dog seamlessly built by Coda. And here's how Coda can help your team run smoother and be more efficient. Coda allows your team to operate on the same information and collaborate like my team does all in one Coda place. By putting date in one centralized location, regardless of format, it eliminates so many road blocks that can just stop your team in their tracks. This is really what slows down productivity and collaboration. With Coda, your team can operate on the same information and collaborate in one place to get projects across the finish line faster. Help your team run more smoothly, more efficiently with Coda. Get started today for free. Head over to coder.io slash 20VC. That's coder.io and get started today for free. Coda.io slash 20VC.
在我们深入讨论节目之前，Dave，请帮我谈一谈Coda。Coda是将所有内容整合在一起的文档，它可以帮助团队更顺畅地运作，提高效率。我知道这是因为Coda帮助了我。在20VC中，我们使用Coda来进行所有剧集的研究，因此所有团队成员基本上都可以在一个由Coda无缝构建的日程表上工作。以下是Coda如何帮助您的团队更顺畅地运作并提高效率的方法。Coda允许您的团队在同一位置操作相同的信息并进行协作，就像我的团队一样。通过将数据放置在一个集中的位置，无论其格式如何，它都可以消除许多可能会阻碍您团队进展的障碍。这是真正影响生产力和协作的因素。使用Coda，您的团队可以在同一位置操作相同的信息并协作，以更快地完成项目。使用Coda帮助您的团队更顺畅地运作并提高效率。现在免费开始使用。请访问coder.io/20VC。

And some of the youth tools we cannot live without. Angel list is fast becoming the center of the venture ecosystem. So for startups, Angel list reduces the friction of capital management, banking and fundraising all in one place. Teams can focus on scaling and let Angel list handle the rest. Thousands of startups have moved their cap tables to Angel list in the past year. Angel list also supports large venture funds and their teams with an automated software first approach and the best customer service in the industry. Fun managers can focus on making great deals, while Angel list handles reporting, taxes, compliance and more. What's more, with the recent release of Angel list network banking for fun managers and investors, your deposits are secure with the most trusted banks for maximized FDIC coverage and mitigated single-bank risk. If you're ready to scale your startup or fund with the platform of the center of it, visit Angel list.com forward slash 20VC to get started.
我们无法生存的一些青年工具。Angel list 正迅速成为风险生态系统的中心。对于初创企业来说，Angel list 在一个地方减少了资本管理、银行业务和筹款的摩擦，团队可以专注于扩大规模，让 Angel list 处理其余事项。在过去的一年中，成千上万的初创企业已将其资本表转移至 Angel list。Angel list 还以自动化软件为首要方法，并提供业内最好的客户服务，支持大型风险基金及其团队。基金经理可以专注于做出伟大的交易，而 Angel list 则处理报告、税收、合规等方面。此外，随着 Angel list 网络银行最近的发布，基金经理和投资者的存款将与最值得信赖的银行合作，以最大化覆盖 FDIC 范围并减少单一银行风险。如果您准备利用这个平台扩大您的初创企业或基金，请访问 Angel list.com 20VC 开始吧。

And finally, Brax. Since his founding, Brax has been committed to helping startups launch and scale faster at every stage of growth from MVP to IPO. Today, Brax is all in one financial stack, is used by one in four US startups and counting. I get to speak to founders all day and I know how crucial it is for them to have the right financial stack. Brax gives you fast access to a high yield business account where you can safely store and move your cash while getting up to 6 million in FDIC protection. Lately, it's been all too clear how important that is. Plus, you get high-limit corporate cards, easy-expandence tracking and automated bill pay. To learn more about the all in one financial stack for startups, visit Brax.com forward slash 20VC. That's B-R-E-X.com slash 20VC.
最后，提到Brax公司。自其成立以来，Brax一直致力于帮助初创公司在从MVP到IPO的每个增长阶段更快地推出和扩张。今天，Brax是一个全方位的金融堆栈，被四分之一的美国初创公司使用，且数量在不断增加。我整天都在与创始人交流，我知道对于他们来说拥有正确的财务工具是多么重要。Brax为您提供快速访问高收益企业账户的机会，您可以在这里安全地存储和转移现金，同时获得高达600万美元的FDIC保护。最近，这一点变得更加清晰了。此外，您还可以获得高限额企业卡、易于扩展的支出跟踪和自动账单支付。要了解更多有关初创公司全方位的金融堆栈的信息，请访问Brax.com/20VC。这是B-R-E-X.com/20VC。

You learn now, arrived at your destination.
现在你已经学会了，抵达了目的地。

Tom, it is such a joy to have you on the show. I just checked and it is 2016 when you were lost on the show. So, seven years ago, I've missed you dearly, my friend, but thank you so much for joining me today.
汤姆，你能来参加这个节目真是太让人高兴了。我刚刚查了一下，在2016年你在这个节目上消失了。所以，七年前，我很想念你，我的朋友，但是今天非常感谢你能加入我。

Thanks for having me back, Harry. I can't believe it's been seven years. Time flies. Look at you. Huge audience. New fans. Look how far you've come. It's incredible.
谢谢你让我回来，哈利。我真的不敢相信已经过去了七年。时间飞速流逝。看看你现在的成就，你的观众群巨大，新粉丝不断涌现，你的成长有目共睹，真是不可思议。

That is so, so kind. But I want to start with, obviously we recently found a theory such an exciting time. I want to dive in. First, why did you decide to leave Rapp Point and why did you decide to start on your own?
那真是太好了。但是，我想首先说的是，显然我们最近发现了一种理论，这是非常令人兴奋的时刻。我想深入探讨一下。首先，您为什么决定离开Rapp Point，为什么决定自己创业呢？

Yeah, at a great time at Rapp Point it was there for 15 years. Learned from many wonderful people. After that amount of time, I decided that after seeing so many founders start companies that I really wanted to start one of my own.
好的，在Rapp Point的时光非常美好，我在那里度过了15年，学到了很多优秀的人的东西。然而在这段时间之后，我决定开始自己创业，因为我看到了许多创始人创办公司的成功案例，我也非常想有自己的公司。

When I was about 17, I started a little company. And over the last 15 years, maybe more, 20 years, I've watched all these startups grow. I wanted to have that feeling for myself. And I also wanted to experiment a bit more. And everybody has an idea about how they want to create their own business. And I've been a student of startups for a long time. And so I really wanted to build a venture firm in a slightly different way. In September of last year, jumped in and then we were off to the races.
我大约十七岁时开始了一家小公司。在过去的十五年甚至更长时间里，我观察到很多初创公司的成长。我想要自己也能拥有那种感觉。而且我还想进行更多的实验。每个人都有自己建立自己事业的想法。而我已经是创业的学生了很长时间。所以我真的很想以稍微不同的方式建立一家风险投资公司。去年九月，我开始实践，然后我们就开始起步了。

You mentioned that, like, the learnings in the 15 years. If there are one or two big takeaways for you from your time at Rapp Point, I'm asking you to distill 15 years of lessons in a short sound bite. But what would they be? And how does that influence how you think about building theory moving forward? Yeah, so I really believe in thesis driven investing. And what that means is going deep in a space and spending six, nine, 12 months researching it and really understanding it. As a board member, I will never know about as much about a space as a founder. But if I can deeply understand a space, then I think I can be a very helpful board member.
您提到了在15年里学到的东西。如果您从在Rapp Point的时间中汲取了一两个重要的教训，我要求您把15年的经验凝缩成一个简短的关键词。具体来说，这些教训会对您如何思考未来的理论构建产生什么影响？我非常相信投资的前提是建立投资理论。这意味着深入研究一个领域，花费6个月、9个月、12个月的时间去研究和了解它。作为一个董事会成员，我永远不会像创始人一样完全了解某个领域。但是如果我能深入了解一个领域，我认为我可以成为一个非常有帮助的董事会成员。

That's one of the reasons why theory is called theory. I really believe in concentration. The industry is governed by a power law. And the more dollars you can have closer to the y-axis of a speak on the power law, the better your returns will be. And so I wanted to set up a firm that was set up for thesis driven concentration. That was a whole idea. This in portfolio construction is what gets me out of bed in the morning.
这就是为什么理论被称为理论的原因之一。我非常相信专注。这个行业受权力法则所支配。你能够在权力法则的演讲中让更多的美元靠近y轴，你的回报就越好。因此，我想建立一家为基于论点的专注而成立的公司。这是一个完整的设想。这就是我每天早上都会热血沸腾地涉足投资组合建设的原因。

When I was peeing my language, I want to start there. This is like a process that's shrouded in much opacity. And we just see fundraisers announced. So I wanted to talk about the fundrais. How many meetings did it take to close out the fund, my friend? It took about 150 LP meetings. The fundraising market was a very challenging one over the last couple of months, I'd say. But it took about meeting about 150 LP's.
当我谈论我的语言时，我希望从那里开始。这就像一个充满不透明性的过程，我们只看到宣布募资的消息。所以我想谈谈募资。我的朋友，关闭基金需要多少次会议？大约需要150个有限合伙人会议。过去几个月，募资市场非常具有挑战性。但是需要会见大约150个有限合伙人。

I thought about it just like a regular software sales process, right? Where sales assisted 15% close rate. So built a funnel and a pipeline that was large enough with 15% close. The probability that we could hit our target. And we were very lucky where we exceeded the target. We raised a hard cap and ended up at about 230.
我认为这就像一个普通的软件销售过程一样，对吧？在销售协助下，能够实现15%的关闭比率。因此，我建立了一个大到足以达到15%关闭率的销售漏斗和管道。这样我们就有可能达到我们的目标。我们很幸运，超过了目标。我们设定了一个硬顶并最终达到了大约230的销售额。

So 150 meetings, I'm fascinated. How many of those did you know before the raise itself? I probably knew about 40 of them, 40 to 50. How many of them committed having not known you before? Because I always say invest in lines, not dots, and the importance of building that relationship outside of the fundrais. How many committed and having not known you? So about 50% of the capital was for new relationships, about half of the capital.
我对你参加了150场会议感到着迷。在提高筹资前，你有多少认识的人参加了这些会议？我大约认识40到50个人。其中有多少人在不认识你之前就承诺了资金支持？因为我总是说要在筹资之外建立良好的关系，投资于长远的价值。有多少人没有认识你就承诺了资金支持？大约一半的资金来自新的关系，约占总资金的50%。

Can I ask for the starting checks that are the hardest to get? When you think about the strategy there, did you go for large institutional anchors first? Or did you go for the friendlies who are much more likely to say yes? I went for the large institutional anchors. I had some relationships there. So the LPAC has five members. And if I could fill two members of the LPAC right out at the gate, then that would assuage a lot of concerns from new rail peas because there were institutional backers from the beginning, and that they were wonderful.
我可以问一下最难获得的起始检查吗？在你考虑制定战略的时候，是先找到大型机构的支持者，还是优先寻找更有可能答应的友好人士？我优先选择了大型机构的支持者，因为我在那里有一些关系。LPAC由五名成员组成。如果我从一开始就在LPAC中填补两名成员，那么这将缓解很多新铁路豌豆的顾虑，因为一开始就有机构的背书，并且他们很出色。

They took many reference calls on my behalf and gave me a lot of advice through the process. It's kind of like if you think about finding a lead for a series A or a series B, if you can find that lead who then does the diligence, and then we'll talk to everybody else who comes in and guides you, it sets out the process really well. It's a little bit different because most venture firms are basically large party rounds. It's just the number of investors you're talking about 15 to 25, 30 sometimes. And so it doesn't really have that dynamic of a lead, but the LPAC is basically the limited partner advisory council of the board. It's the closest thing that I think you can get to, unless you have super concentrated LP base.
他们代表我进行了许多参考调查，并在整个过程中给了我很多建议。这有点像你想找到A轮或B轮的领头人，如果你能找到那个领头人然后进行尽职调查，然后我们会跟所有其他人谈话并指导你，这将很好地确定过程。这有点不同，因为大多数风险投资公司基本上是大型派对轮。你谈论的只是投资者的数量，有时候是15到25、30个。所以它并没有真正具有领头人的动态，但LPAC基本上是董事会的有限合伙人顾问委员会。这是我认为你可以得到的最接近的东西，除非你有超级集中的LP基础。

Did you have a limit on check size? Often when I was raising people were like, oh, don't let them invest more than 20% of the fund. Did you have a limit on how much they could invest as a percent of the fund? I did, yeah. I think the largest LP is no more than 12% of the fund. So there's different theories here. So one of the wonderful things in raising this fund was I got to see startup land all is beauty and glory, the number of people who reached out who I wouldn't have thought to help and talk about their journey and their experience and their fund construction was amazing.
你有关于支票金额有限制吗？在我筹集资金的过程中，经常有人说，不要让他们投资的金额超过基金的20%。你有没有规定他们在基金中投资的百分比上限？是的，我有。我认为最大的有限合伙人不超过基金的12%。因此，这里有不同的理论。在筹集这个基金的过程中，其中一个美妙的事情是我可以看到创业公司的美好与荣耀，有很多我之前没有想过帮助的人主动联系我，分享他们的经历和基金结构，这是令人惊人的。

And so I learned about funds where they're $200 million fund with 80% of the capital from two LPs was super concentrated. And then there are other funds that are the opposite where it's just lots of small checks. And then you have people in the middle. Having that breadth, it was just absolutely eye opening to understand that there are many different ways of creating a venture firm, at least on the capital formation side.
于是我了解了一些基金，其中一家有2亿美元的基金，80%的资本来自两个有限合伙人，非常集中。还有其他一些基金则相反，只有很多小额的支票。还有一些人处于中间。通过这种广度，我彻底认识到，至少在资本形成方面，有许多不同的创建风险投资公司的方式，这让我大开眼界。

I'm glad you went with the 12%, I think diversification is important. So I'm thrilled that you went for the ladder. What did you give for all the materials? Did you send pitch decks to everyone beforehand? Did you have data rooms? How did you think about getting the right materials in place for the raise?
我很高兴你选择了12%，我认为多样化很重要。所以我很高兴你选择了阶梯投资。你为所有材料付出了多少代价？你事先向所有人发送了演示文稿吗？你有数据室吗？你如何考虑为筹集资金做好正确的材料准备？

I prepared a data room. There was a track record in there at pitch deck, a bio, some of the blog posts that I'd written, some metrics that I put together. So I set up a brief and a bio. And that was theory one. That was the outbound email. If I had been introduced, I would send them my bio and then the deck. The idea was to use those materials as pre-qualification. So some LPs prefer not to invest in solar GPs. Different LPs have different mandates. They might only invest in the US. They might prefer early stage, later stage. And the idea was to qualify, just like an SDR would. And so those briefing materials, that was the entire purpose. And I used a doc send and I didn't allow downloading because I wanted to understand where people were in the pitch deck, where they were stopping. And that informed the way that I would pitch them if they decided that they wanted to meet.
我准备了一个数据室。里面有一份记录、一个幻灯片、一个传记、我写的一些博客文章和一些指标。于是我设置了一个简短的介绍和传记。这是理论一。也就是发出的初步邮件。如果我是被介绍的，我会先发送我的传记，然后再发送幻灯片。这个想法是使用这些材料作为初步资格认证。因此，一些有限合伙人可能不愿意投资太阳能总公司。不同的有限合伙人有不同的授权要求。他们可能只想在美国投资。他们可能更喜欢早期阶段，后期阶段。这个想法就是想进行资格认证，就像 SDR 一样。所以这些简报材料，那就是它的全部用途。我使用了文档发送功能，并且不允许下载，因为我想了解人们在接受幻灯片时的选择情况。这影响了我在他们决定要见面时如何向他们推销的方式。

That's so interesting. So I always have this contrarian view and I always advise people to not send the deck beforehand. And the reason I say that is because they look for a reason to say no. They'll go, Ah, well, actually he's the sister of him and we want a generalist. Ah, he's only focused on North America. The truth is they might have those preconditions before. But when they meet you and they see how brilliant you are, all of those can go away. And so don't give them a reason to say no before they have the chance to hear how inspiring and brilliant you are.
这太有趣了。所以我总是有这种相反的观点，并且我总是建议人们不要事先发送演示文稿。我这样说的原因是因为他们会寻找拒绝的理由。他们会说，“噢，事实上他是他的姐姐，而我们需要一位综合人才。 噢，他只关注北美。”事实上，他们可能在之前就有这些先决条件。但当他们见到你并看到你有多么出色时，所有这些都可以消失。所以在他们还没有听到你的激励人心和卓越才能之前，不要给他们拒绝的理由。

I think that's brilliant wisdom. I didn't follow. Do you know what I mean? And then afterwards once you get them bored in, you can be like, Hey, I'd love to show you more. I'm going to send you our deck as a follow-up and it also gives you a reason to follow up more than one would normally have. There's a lot of wisdom there. The other reason is if you're raising a first time fund it's really a bit about the individuals more than it is anything else. And so to plan the materials at a time, maybe you don't have the opportunity to let yourself shine. So I could see that.
我认为这是很棒的智慧。我没有听懂，你知道我是什么意思吗？之后，一旦你让他们对此感到无聊，你可以说：“嘿，我很愿意向你展示更多内容。我将会发送我们的项目简报作为后续跟进，并且这也提供了一个比平常更多的跟进理由。这其中有很多智慧。另一个原因是，如果你正在筹集第一次基金，它真的更多的关于个体而不是其他的东西。因此，有计划地准备材料，也许你就没有机会展示自己的特点。所以我能够理解这点。

Tom, what was the biggest reason that people said no? You mentioned the solo GP album of that. What was the biggest reason people were like, ah, no for us? Yeah, so solo GP is one. There's keep-person risk. And so some LPs are just not comfortable having a single person. It would be the general partner. The other challenge was timing. I was raising during a time when the public markets had been down, but the private market valuations had remained elevated. And so the combination of those two put a lot of LPs in a place where they didn't really understand the nature of their portfolios. If you thought you were 50-50 public private and then the public's fell by half. All of a sudden you were three quarters private, one quarter public. But the private market was going to be written down, but hadn't been written down. And so one of the biggest reasons was just need more time in order to understand where my portfolio is so that I can figure out allocation in the future to this asset class.
汤姆，人们最主要的理由是什么导致我们没能得到资金支持呢？你提到了《Solo GP》的专辑，但是人们拒绝的最主要原因是什么呢？ 嗯，《Solo GP》是其中之一，还有就是保持人员风险。因此，一些有限合伙人不愿意让一个人来管理整个合伙基金。另一个挑战是时间问题。我在一个时期进行募资，当时公共市场已经下跌了，但是私募市场的估值却保持高位。因此，这两个因素的结合使得很多有限合伙人无法真正理解自己的投资组合本质。如果你认为你的投资组合是50-50的公共市场和私募市场，但是公共市场下跌了一半，你就会发现你的投资组合变成了三分之三私募市场，三分之一公共市场。但是，在那个时刻，私募市场的估值还没有调整，所以最主要的原因之一就是需要更多的时间来了解我的投资组合，以便未来能够更好地配置资产。

Which LPs class did you predominantly raise from? Because if you enter letting down the funds in particular, that was a big scene that was troubling for a lot of them. And also they have mandated net outflows because they have scholarships and maintenance for sites. Was it predominantly endowment funds? How did you think about the different LPs classes? Barry Eggers from Life Speed, he has a great blog post on the ideal construction of a venture fund. And he talks about ideally you want to have about 30% fund to funds, ideally 30% endowments and foundations and then 10% pension funds, healthcare plans, etc. That was the advice that I got from a handful of other LPs. And so that was my sort of mental model when I went out. And the ultimate LPs base is roughly that. It's predominantly US.
你主要从哪个LP类别筹集了资金？因为如果你特别注意到资金投入，这对很多人来说会是个大问题。另外，他们还必须遵循净流出的规定，因为他们有奖学金和站点维护费用。它主要是捐赠基金吗？你是如何考虑不同的LP类别的？Life Speed的Barry Eggers在他的博客文章中谈到了一个风险基金的理想结构。他说，理想情况下，你希望有大约30%的资金来自基金，30%来自捐赠基金和基金会，然后有10%的养老基金、医疗计划等。这是我从其他几个LP得到的建议。所以那是我在外面时的心理模型。最终的LP基础大致如此。它主要是美国的。

First close, second close, final close. How did you approach the closing mechanisms? There is this sort of aura around at first and only close. No one really explained it to me. I talked to one friend who is an executive at a public-itreate company raised a venture fund. And he said he had 15 closes.
首要结束、次要结束和最终结束。你是怎么处理这些结束机制的？第一和第二个结束似乎有一种神秘感。没有人真正向我解释过。我和一个在一家公共IT公司担任高管、筹集风险资本基金的朋友聊过，他说他有15次结束。

And so every time an LP would commit, he would have a close. And his perspective was, somebody signed up. It doesn't cost many more to close them and have them wire and we'll just keep going. And then there are other investors who said, ideally having a single close means you raise for a position of strength. And we had a single close, but the purpose of a close date is just to drive people in unison to a cadence that you're trying to set. There's nothing magical about it. There's nothing terrible about having multiple closes. It's just a way of organizing a particular process.
因此，每次有一位有限合伙人做出承诺，他都会完成交易。他的想法是，有人注册了，关闭他们并让他们汇款并不会产生很大的成本，我们只需要继续进行即可。还有其他的投资者说，理想情况下，只进行一次关闭就能增强筹集资金的实力。虽然我们只进行了一次关闭，但关闭日期的目的只是使人们以协调一致的方式参与到你想要设定的节奏中。关于有多次关闭没有什么神奇的地方，也没有什么可怕之处。这只是组织特定过程的一种方式。

That close date is drawn out of thin air and it's driven by how strong we have an auction you can develop and what your LP relationships look like. But it's a vanity metric for VCs. I think one of the biggest mistake managers make out shoes. They gather loads of people who say yes. They don't close them and they leave them hanging. And then a month later they come back and say, hey, Tom, you committed to my fund and you were like, oh, I forgot about that.
这个固定的截止日期只是凭空设定的，它取决于我们拍卖的实力以及你与有限合伙关系的发展。但对于风险投资家来说，这只是一种虚荣指标。我认为，经理们犯下的最大错误之一就是聚集了很多人说“是”，但却没有最终确定他们，于是他们被搁置了。一个月后他们又回来说：“嘿，汤姆，你答应参加我的基金了”，而你却像是：“哦，我忘了这件事了。”

My actually kind of allocated the money elsewhere. And it was actually two months ago now. That happens a lot, which is don't let it go stale. I always say close as soon as you can, as fast as you can to not let it go sales. It totally with you. And it shows momentum. Right. If somebody asks, how much of you close, you want to show a level of progress and it gives you a reason to come back to people. And like you said before, a reason to email people.
我实际上把那笔钱分配到了其他地方，而且实际上已经两个月前了。这种情况经常发生，所以不要让它变得陈旧。我总是说尽快尽快关闭以避免它变得过时。这完全符合你的想法。它显示了您的势头。对吧，如果有人询问您接近多少，您需要展示进展水平，这给您一个与人交流的理由。就像您之前说的，这也是给人发电子邮件的理由。

So I think this mistake around a single close is completely misplaced. Did you do anything to drive urgency in the LP base? Because as you said, the single closes one way to do it in terms of ensuring that people move faster down pipe. Did anything else work for you in terms of just ensuring there was efficiency in urgency in the process? Every time I had another verbal commit, I emailed the LP base and I gave them the update.
我认为这种关于单次关闭的错误完全不合适。你有没有采取任何措施来促进LP群体的紧迫感？因为你所说的，单次关闭是确保人们在管道中更快地前进的一种方式。除此之外，你还有什么其他有效的方法来确保流程中的紧迫感和效率吗？每次我获得另一个口头承诺，我都会向LP群体发电子邮件并通知他们更新情况。

Can I write this blog post a long time ago talking about when you're fundraising what you want to convince people of is inevitability that the company or the fundraising round, its positive conclusion is inevitable. And so any data point that you can provide to investors that supports that is hugely helpful. When you say, Hey, this person just committed or we just got another great institution. For me as someone who's already committed, I'm like, Oh, actually, Tom's going to be a winner. I should introduce him to more people.
我可以写一篇博客文章，讲述当你筹资时，你想要说服人们的是公司或筹资轮成功结局的必然性。因此，任何能够支持这一点的数据都极为有用。当你说，“嘿，这个人刚刚承诺了”或“我们刚刚获得了另一个伟大的机构”时，对于已经承诺的人来说，这些消息会让我觉得Tom会成为赢家。我应该向更多人介绍他。

Do you see what I mean? Totally. Absolutely. Exactly. So it never's not legit. I'm very deliberate about that. I'm going to reveal what would you say what with your race that you do again and what would you say did not work and you would change for next time? Yeah.
你明白我的意思吗？完全明白。绝对如此。就是这样，这从未不合法。我对此非常慎重。我将揭示你关于你的种族方面做了什么，哪些不起作用，下次你会怎么改变呢？是的。

So after I raised capital, I went and I talked to, I should have done this before, but I went and I talked to some of the most sophisticated capital formations people. I just asked them how they do their job and it was really interesting because the really sophisticated fundraisers, they're always in market. They're referencing LPs. They're building pipeline and that's a full-time job. And so I think one of the things that's really important is building long term relationships that worked really well for me.
所以在我筹资之后，我去和一些最精明的资本形成人士谈话，我应该在此之前做这件事，他们告诉我他们是如何打造他们的工作，这是非常有趣的，因为那些真正精明的资金筹集者总是处于市场中。他们参考LP（有限合伙人），建立渠道，这是一项全职工作。因此，我认为建立长期关系是非常重要的，这对我非常有效。

So I was really happy to have a lot of long term relationships that I could lean on. That was a really big deal. Things that didn't work so well, there are different geographies where LPs is a whole or more conservative and it took me a while to appreciate that. And so I probably spent more time traveling than I should have. And so next time there'll just be longer lead times on some of those geographies.
所以我非常开心有许多长期的关系可以依靠。这是非常重要的。有些事情不那么顺利，在不同的地域，有些有限合伙人比较保守，我花了一段时间才意识到这一点。所以我可能花了比应该更多的时间旅行。下一次，在这些地域，将会有更长的前导时间。

Did you find in-person what much more effectively than remote cools in terms of conversion and closing or actually not? No. No, there's no correlation. Boy, I'd have to go back and look, but maybe I want to say like a quarter to a third of the LPs I only met after they committed in person. And that's probably an overhang from COVID where a lot of funds were raised entirely virtually and people are comfortable.
你是否发现在面对转化率和签约方面，亲自会面比远程更有效呢？不是的。没有关联。可能我要回去看看，但我想说大约四分之一到三分之一的有限合伙人是在他们亲自承诺后才与他们见面的。这可能是因为 COVID 的影响，很多基金是完全虚拟地筹集的，人们感到很舒适。

I actually, the thing that I do is every week I meet two new LPs and with each LP meeting I say, hey Tom, I love this discussion. And then ones two other great LPs that think like you and you think I'd have a great discussion with and they go, oh, you've got to speak to Satish and Logan. Oh, that'd be fantastic. Which you might make in the intro. I'll send you a blurb now that you can forward. Of course, super happy to.
实际上，我每周都会见两位新的LP（有兴趣的投资者），在每次见面时，我都会说：“嗨，汤姆，我喜欢这个讨论。”然后我会问他们是否认识其他两位LP，他们也和汤姆一样思维敏捷，我可以和他们有一个很棒的讨论。他们会说“哦，你一定要和萨蒂什及洛根谈谈，那将会很棒。”有了介绍，我会马上给你发一段简介。当然，我非常愿意。

And the flywheel is self fulfilling. You're a machine, Harry. You now have this breath of experience raising theory in a pretty freaking hard market. What would you advise managers going out to raise? Having had the experience you have done with theory.
而且飞轮是自我实现的。你是一台机器，哈利。你现在拥有在相当困难的市场上提出理论的丰富经验。在这个理论方面有了经验之后，你会建议那些要进行筹资的经理们去做什么呢？

The point of LP diligence that was new from either in the process was the business model. I think in the last 11, 12 years where we've had this incredible mobile market, the portfolio construction hasn't mattered as much. But the volume of questions that I received consistently from LPs about, what are your assumptions on number of seeds, number of A's, the fatality rate, the multiples on those? How does that compare to the standard venture capital distribution? The number of questions that I got about that, I think suggests that it's really important to have a business model in your deck.
在LP的尽职调查中，与以往不同的是业务模式。在过去的11、12年中，我们经历了一个非常强大的移动市场，投资组合构建可能并不那么重要。但LP们持续不断地向我提出一些问题，比如你对种子数量、A轮数量、失败率和乘数的假设是什么？这与标准的风险投资分布相比如何？我所接受到的这些问题数量，表明在你的方案中拥有一个业务模式是非常重要的。

That I think has changed as a result of the cost of capital increase. I think it's sad that it wasn't always that given the fact that it was involved. That's just fucking under one of venture capital ecosystems. 2008, we were looking at financial plans and we were putting together financing rounds that were a function of the capital into the business. And then, in 2012, all of a sudden it was not about fundamentals anymore and it was really just about access.
我认为由于资本成本的提高，情况已经有所改变。考虑到它的参与，我认为这很遗憾，这只是风险投资生态系统中的一个麻烦。在2008年，我们正在研究财务计划，并组织融资轮，这与企业中的资本有关。然后，在2012年，突然间不再是关于基本原理，而是真正关于获取资本。

I love that discussion and so I wanted to dive into it because 230 million, that's the fun size. Wait, did you decide 230 million was the right amount to raise? It was all about portfolio construction. I ran a lot of math in order to figure out using historical venture data. I ran Monte Carlo simulations for optimal portfolio construction. How may I understand how many companies, how much for a national, how much for reserve?
我喜欢那个讨论，所以我想深入研究它，因为2.3亿美元，那是有趣的规模。等等，你决定筹集2.3亿美元是正确的金额吗？这全部关乎组合构建。我进行了大量的计算，以便使用历史风投数据来确定。我进行了蒙特卡罗模拟，以实现最佳的投资组合构建。我如何了解需要多少家公司、国家需要多少资金、备用基金需要多少？

It's about 12 to 15 portfolio companies, significant concentrations, so you probably have 40 to 50% of the fund in the top three holdings, maybe more. It's an unusual portfolio construction. Monte Carlo simulations bits out a couple of different dominant strategies and this is one of them.
这大约涉及12到15个组合企业，集中度较高，很可能有40%到50%的资金在前三大持股中，甚至会更高。这是一种不寻常的投资组合构建方式。蒙特卡罗模拟算法可以生成几种不同的主导策略，而这种策略就是其中之一。

This is the one that aligned with when we talked at the beginning about the way that I'd like to invest about being thesis driven and really understanding space. If you go deep into space and you can understand it, ideally you're in a place where you have a lot of conviction and you can keep investing and keep supporting a company.
这一点与我们最初谈到的我所喜欢的投资方式相契合，即以论点为驱动并真正理解领域。如果您深入研究某个领域并能够理解它，最理想的情况是您将具有很强的信念并且可以继续投资和支持一家公司。

I also think in a venture environment that's going to be significantly different this ten years over the last ten years, setting up a venture firm to be able to consistently invest behind its companies. It provides founders a bit more comfort from their financial partner. So I similarly did the Math on Monte Carlo's and I found that at 23 companies you get something like 82 to 84% of the benefits of diversification.
我认为在未来十年里，创业环境会与过去十年显著不同，因此建立一个风险投资公司以便能够持续地投资于其公司，为创始人提供更多经济上的支持是非常有必要的。我也进行了蒙特卡罗模拟的计算，发现当投资23家公司时，您可以获得到类似于82%至84%的资产分散化好处。

What you're saying is that, actually, with deep thesis and deep thinking and a lot of time, you need less diversification because your ability to pick is significantly better. Correct. That's exactly right.
你的意思是，实际上，如果你有深入的研究和深思熟虑，并且花费了很多时间，你需要更少的多样化，因为你选择的能力会显著提高。对的，完全正确。

So we're doing series A's, what's the check size per company estimate? Yeah, it's about eight to 12 initially. Eight to 12 initially. Is the phone big enough given how large AI machine learning rounds are today being 30 to 50 million on a pre-seater receipt as we're seeing quite often now? We can flex. We're not in a position to be able to lead a 50 million to our series A. We could co-lead, so that's one way of doing it. And if you're raising a 50 million to our series A, you probably do want it from, I would say you probably do want it from two different PCs.
我们正在进行A轮投资，每个公司的投资金额大概是多少？是的，最初的投资额在8到12之间。鉴于如今AI机器学习轮次往往在3000万到5000万美元的前期收入中，这个金额是否足够大了？我们可以适应变化。我们无法在A轮领先投资5千万美元，但可以联投。如果你正在为A轮筹集5千万美元，很可能需要从两个不同的投资方获得资金。

Because we're so concentrated, we can focus our resources where we have the most conviction. How do you think about the decision on doubling down? We said there about kind of three companies could be say 50% of the capital base. What is that conviction building process that like to putting that much capital behind one of the three?
因为我们非常专注，所以可以将资源集中在我们最有信心的领域。你如何考虑加码的决定？我们说过，有三家公司可以占到资本基础的50％左右。当把这么多资金投入其中一个公司时，会采用何种确定信念的过程来建立信心呢？

It's a lot of diligence. We'll spend six, nine, twelve months researching a space like one of the themes that we have is the decade of data. So I've been investing in lots of different data companies for a long time. So one component is just really understanding the market, understanding the buyer base, the different segments, their needs. Another component is benchmarking companies.
这需要很多的勤奋和耐心。我们会花六个月、九个月甚至十二个月来研究某个领域，比如我们的主题之一是数据十年。我已经长期投资于许多不同的数据公司。所以其中一个组成部分就是真正理解市场，了解买家基础、不同的细分市场和他们的需求。另一个组成部分是对公司进行基准比较。

So I've been doing that for more than 10 years. I've got a pretty significant database of data points there. So just understanding on a relative basis, what is the ultimate performance? A third part is understanding what the exit markets look like in the entry prices and what is a reasonable multiple expectation over what period of time. On the exit market analysis, I go back and forth.
我已经做了这个超过10年了，积累了相当可观的数据库。所以，理解什么是最终的表现是相对简单的。第三部分是了解入门价格的退出市场和在什么期间内的合理倍增期望。在退出市场分析方面，我总是反复思考。

Is it worth doing because it's so variable? You could look back on the prior 24 months and say, it could be that or it could be today or it could be way, way worse. We can't project out 7, 10, 12 years. Is it valid doing it? Okay.
因为如此不稳定而值得做吗？您可以回顾过去的24个月，并说，可能是那样，也可能是今天，或者可能远远更糟。我们无法预测未来7年、10年、12年。这样做是否有效？好吧。

So the historical forward multiples about 5x, it's a little higher than that's about 545. And in the Hanehave quantitative easing, the top court telecoms are trading at 40 times. And today it's about maybe six. And so you can't go into a company today and say, okay, I'm going to project a 20 times forward multiple on this company at the time of IPO. If it's at 100 million growing at 70%. You just can't. It's really responsible because it's just completely unrealistic.
因此，历史上的前向倍数大约为5倍，略高于大约545倍。在汉内威夫量化宽松政策下，顶级电信公司的交易倍数为40倍。而今天可能是六倍左右。因此，你不能在今天进入一家公司并说：“好的，我要在这家公司IPO时预计20倍的前瞻倍数。如果其市值为1亿美元，增长率为70%。”这样做是不负责任的，因为这完全不现实。

If you've spent the majority of your time and venture during a time when you've had those kinds of multiples, you need to say, check on what do you think your return expectations are going to be given that it is a 4% ESOP employee stock option pool dilution by year and dilution created by other venture rounds and that. Going through that discipline, I think is as much just like I said, particularly for working in a team, it's just a really important discipline step.
如果你在那种高倍数的时期花费了大部分时间和投资，那么你需要考虑一下，以每年4%的员工股票期权池稀释为基础并考虑到其他风险资本回合的稀释情况，你认为你的回报预期会是什么样子。通过这种纪律性的思考，我认为对于团队协作来说，这是一项非常重要的纪律性步骤。

There's this awesome book called Super Forecasters that got him TedLo wrote. He talked about Enrico Fermi who created the atomic bomb. There was one of the team for the Manhattan Project and Fermi had this way of thinking which was all about conditional probabilities. It's called Fermization.
有一本很棒的书叫做《超级预测家》，是由TedLo所著。他谈到了创造原子弹的恩里科·费米。他是曼哈顿项目团队的一名成员，而费米的思维方式是关于条件概率的。这被称为费米化。

The idea is like just to numerate the conditional probabilities. In order for this generative AI company to succeed, the first thing it needs to do is hire a PhD team. Okay, what are the odds that they can do that? Then they need to raise a series A. Okay, what is up? The base rate for raising a series A from seed is about 60%. Then they need to raise a series B. Base rate is 50%. Then they need to do this and this. When you put it all together and then you tie it to your expected value and you come out with a big range of what you think the ultimate outcome can be. And each company is going to be different.
这个想法就是简单地数值化条件概率。为了让这个生成式人工智能公司成功，它需要做的第一件事就是雇用一支博士团队。好的，他们能做到的概率是多少？然后他们需要筹集系列A。好的，现在怎么样了？从种子轮筹集系列A的基本率约为60%。然后他们需要筹集系列B。基本率为50%。然后他们需要做这个和那个。当你把它们全部放到一起，把它们和预期价值联系起来，你就可以得出一大范围的结果。每个公司都会有所不同。

A marketplace has to do supplier acquisition, supply side acquisition and demand side acquisition. And so like that framework, at least for me, really helps me to think about what are the two or three key issues or questions that a company needs to answer over its timeline or over its lifetime. How do those odds change? And ideally, they improve and the more that they improve, the more comfortable one I have to be in concentrating.
一个市场需要进行供应商获取、供应方获取和需求方获取。因此，像这样的框架，至少对我来说，真正帮助我思考一家公司在其时间轴或生命周期内需要回答哪些关键问题或答案。这些机会如何改变？理想情况下，它们会改善，而且改善得越多，我就越有信心集中精力。

I think it's Philly Blossom or one of the LaFonts says that if you know a market better than anyone else, you can pay a higher price than anyone else because you know more about it than anyone else. My question is to you, do you agree with that statement? And how do you think about your own price sensitivity?
我认为是菲利·布洛索姆或拉芬家族中的一位说过，如果你比其他人更了解市场，你可以支付比任何人都更高的价格，因为你比其他人更懂市场。我的问题是，你赞同这个说法吗？你如何看待自己的价格敏感度？

I think it's true because if you know more about a market, the range of expected outcomes is far more narrow, which means your certainty in making a bet is better. The result of that should be you should be willing to pay a higher price. The more you know that an option is in the money, the more valuable it is. I agree up to a point.
如果你了解市场的更多信息，预期结果的范围就会更窄，这意味着你在下注时更有把握。因此，你应该愿意支付更高的价格。你对一项选择的真正价值是越了解越多，那么它的价值也就越高。我同意这一点，但在某些程度上。

How do you think about your own price sensitivity and my ownership wise? Do you need 10%, you need 15%, how do you think about ownership sensitivity on a part of a company basis?
你认为自己的价格敏感度和我的所有权智慧如何？你需要百分之十还是百分之十五？你如何看待公司部分拥有权的敏感性？

Yeah, so I think where I put it is, it's important for us to have meaningful ownership because we're so concentrated. The idea is because we have such a small portfolio can spend a significant amount of time with each portfolio company.
我想，对于我们来说，拥有有意义的所有权非常重要，因为我们的投资组合非常集中。这个想法是因为我们的投资组合很小，所以可以花费大量时间与每个投资公司一起合作。

So ownership matters, ownership also matters, I think, with a form of returns. We want to have significant ownership. And the idea with the firm is that you don't need to have significant ownership out of the gate, but you can build a position over time.
所有权很重要，所有权也很重要，我认为，它与回报的形式有关。我们希望拥有重要的所有权。公司的想法是，你不需要一开始就拥有重要的所有权，但是你可以随着时间逐步建立你的地位。

And in terms of like multi-round investing, how do you think about it? Can you do a 5% ownership on a and then get 5 more at the b, 5 more at the c? How do you think about that cross cycle investing is a bit of a deal?
在多轮投资方面，你如何考虑呢？你能够在a上拥有5％的所有权，然后在b上再获得5％，在c上再获得5％吗？你如何看待跨周期投资是一个有点棘手的问题？ （简单解释：这是在问一个投资人如何管理资金，如何在不同投资回合中分配资金，在不同企业中持有不同的所有权。）

Yeah, so that's a tough configuration just because the dollar amounts that you're talking about just go up so significantly, right? 5% at the a, it's a hot a. So you're probably talking whatever it is, 5 at 100. And then the next round might be 200 or 300 and so to buy another 5%. You can do the math. I think about it a bit more as can you get 10% at the c? Maybe you can buy another 10 to 15% at the a and then buy another 5% at the b.
这是一个复杂的配置，因为你所谈论的金额实际上很显著增加了，对吧？在A轮可能是5%的股份，价格可能是100万美元。到了下一轮投资，价格可能是2或3亿美元，你需要再买入5%的股份。你可以计算一下，但要考虑的是你能否在C轮购买到10%的股份？也许你可以在A轮再买入10至15%的股份，然后在B轮再购买5%的股份。

With the concentration on a per company basis, to have such concentration you also have to not do per order or not concentrate capital in a lot of companies too, because you have to preserve dollars for the best. How do you think about that aspect of bluntly being a little bit more disciplined around the reserve dollars and not allocating to anything in the middle or underperforming?
通过集中精力处理每家公司，要达到这种集中，你还必须不按订单进行或不集中资本在太多公司中，因为你必须为最好的保留资金。您如何考虑在保留资金方面更加纪律严明，不将其分配给任何中间或表现不佳的内容？ 意思是说，要集中精力处理每家公司，需要把资金集中在一些最好的公司里，不要把资金分散在太多公司中。如果有必要，需要更加严格地控制资金的使用，确保只投资于表现良好的公司而不是中间或表现不佳的公司。

The business model of the firm affords both. So there's reserves for every company. The idea is with every business, there's a very sort of blunt instrument which is with every stock position that you have if you're any kind of investor, either you should either be a buyer or a seller. And if you're in the middle, you probably don't know enough about a business. The idea behind the concentrating reserves is we will run diligence processes on those existing portfolio companies in order to understand where to concentrate. And we also have the capital to support companies go up and down.
该公司的商业模式可以同时提供这两个方面的需求。因此，为每个公司都提供储备金。就投资者而言，在每一笔股票交易中，只能选择买或卖，没有中间地带。如果您不了解该业务，就不应进行交易。集中储备金的想法是，我们将对现有组合公司进行尽职调查，以了解何处集中投资。并且我们也有资金来支持公司的上涨和下跌。

One of the stories that I think hasn't been told enough is the snowflake series C and the series D almost didn't happen because the company was burning so much the gross margins were in a really rough place and there was a flat round in there somewhere and then it became as fast as growing software company in history. So one of the reasons for this portfolio construction is if you're in a radically different capital markets environment, you want a financial partner who has to wear with all to be able to support your cross multiple rounds. That snowflake route multiple on that finance. That was a big lesson that I learned at red point, the multiple on their financing is legendary. I would have died deep on that.
我认为尚未被讲述足够的故事之一是雪花系列C和系列D。几乎没有成立，因为公司烧钱很多，毛利润处于一个非常困难的位置，并且其中有一个平稳的轮廓，然后它成为历史上增长最快的软件公司。因此，此投资组合构建的原因之一是，如果你处于一个根本不同的资本市场环境中，你需要一个有足够的财务实力来支持你的多个轮次的金融合作伙伴。雪花的这种路线对它们的融资具有多个作用。这是我在红点学到的重要一课，他们的融资倍增是传奇的。我会在这方面深入学习。

What happened and what was the lesson fee? Snowflake at the time was competing with giants. So there was red shift and there was GCP and the company was growing very quickly and the market was there. The company had a really tough time and I can't remember exactly if it was a series B or the series C, but it was this middle round. Maybe it was a series C. The company was burning a ton of capital and couldn't raise money from the outside and it was the insiders that stepped up led that round because they believed in the business. And so the ultimate result was if you have an accurate thesis and you can find the right company and you have the way with all to be able to support that business through good times and bad, you can be disproportionately rewarded for it. I love that and I agree with it.
发生了什么事情，教训是什么？当时雪花正在与巨头竞争，有着红移和GCP，公司快速增长，市场很好。公司经历了很困难的时期，我记不清是B轮还是C轮了，可能是C轮。公司消耗了大量的资金，无法从外面筹款，最终是内部人士带头进行了这轮融资，因为他们相信这个公司的前景。因此，最终的结果是，如果您有准确的投资理念，可以找到正确的公司，并且具有强大的支持力量，可以在好时候和坏时候都支持该业务，您可以获得非常丰厚的回报。我喜欢并且赞同这个观点。

I also didn't know actually that in terms of the series C. I do have two questions on like thesis driven investing, which is I always worry about confirmation bias, which is you develop the thesis and then you find something that aligns to it and you're like, this is it. And actually, theses can be wrong. How do you think about the dangers of confirmation bias and not just falling victim to your own predictions of the future model of the world? Yeah, totally. You can become enamored with a particular view of the world and in order to mitigate confirmation bias, you need to have many conversations. You just need to keep testing and keep pushing and at the end of the day, the great part about investing in B2B software is there's a buyer and neither they buy the software or they don't. And so the greatest sort of foil to confirmation bias is a lack of customer demand.
实际上，我也不知道在C系列中关于投资论文的两个问题。我总是担心证实偏见，即你制定了论文，然后找到了与之对应的东西，你会认为这就是答案。实际上，论文也可能是错误的。你如何考虑避免证实偏见的危险，而不仅仅是成为你自己预测未来世界模式的受害者呢？是的，你可能会沉迷于一种特定的世界观，为了减少证实偏见，你需要进行很多对话。你只需不断测试和推动，最终投资B2B软件的最大好处在于，有一个买家，他们要么购买软件，要么不购买。因此，对抗证实偏见的最好方法就是没有客户需求。

I have this view around the future of the marketing ecosystem being tied to the blockchain and this decentralized infrastructure. And I've been working on it for nine months. And the thing that I consistently look for is, okay, where's the pipeline? Who's the buyer? Who's willing to spend? Where are the experimental dollars? Where are the advertising agencies saying? And so I can come up with that idea consistently. But if I can't find a buyer for it, I can still have this beautiful vision glass pyramid, so to speak. But if I can't find a buyer, then I need to abandon the thesis or at least I did this ad for now.
我对营销生态系统未来绑定区块链和分散式基础设施有这样的观点，并已经致力于此九个月。我一直在寻找的是，哪里有流水线？谁是买家？谁愿意花钱？哪里有实验性的投资？广告公司在哪里？因此，我能够持续提出这个思想。但是，如果我找不到买家，我仍然可以拥有美丽的愿景金字塔。但是，如果我找不到买家，那么我需要放弃这个论点，或者至少暂时放弃。

So the question for lines to what you just said there about blockchain applied to marketing, which is timing. A lot of these can be right, but can just be too early. As I know, how do you think about bluntly market timing, especially on thesis where you can know too much ahead of market? You have to look for pipeline. So it all comes down to customer need, right? So pest our con versus Instacard or peep our versus Instacard, I think it's kind of a canonical example. The market timing, as long as you have a strong pipeline, you can have a lot of confidence. As long as you can extrapolate the needs of one buyer to another. And so that's why spending time and trying to get as broad of an understanding of as broad a cross section of the customer buyer population is absolutely essential in developing these thesis because somebody has to buy it at the end of the day.
这里的问题是关于区块链应用于市场营销的时间选择。很多时候选择是正确的，但也可能太早了。根据我的了解，您如何看待市场时间选择，特别是在您所了解的领域市场需要之前？您必须寻找下游卖家的需求。所以最终这归结于顾客的需求，对吧？例如 Pest our 对比 Instacard 或 Peep our 对比 Instacard，这是一个经典的例子。如果您有强大的下游需求，市场时间选择就不是问题。只要您能够将一个买家的需求推广到其他买家身上。因此，在制定这些策略时，投入时间并尽可能广泛地了解客户购买人群的需求是至关重要的，因为最终还是有人需要购买产品。

I do want to move to the future and discuss a way you're investing, but also some of the broader topics around it.
我确实希望讨论一下你正在投资的方式以及与此相关的更广泛的话题，但我也希望向未来迈进。

A question that I have, which I can't really find an answer to, but it's like when we think about the future, especially in terms of AI models, does the rise of large AI models mean the future of AI as an ecosystem is dominated by a single general model or one or two single general models, or will we have a decentralized fragmented ecosystem?
我的一个问题是，我真的找不到答案，当我们思考未来，特别是在AI模型方面，大型AI模型的兴起是否意味着AI生态系统的未来将被一个单一的通用模型或一个或两个单一的通用模型所支配，还是我们将拥有一个去中心化的分散生态系统？

I think you have both. I think the analogy of Apple and Linux is really useful here, Apple and Windows, where you'll have a one system that is basically fully integrated and closed and then you'll have another world where people are building little open source models. And some people believe that there's going to be a single dominant model.
我认为你都拥有。我认为拿苹果和 Linux 的比喻在这里非常有用，以及苹果和 Windows ，在一个系统基本上是完全集成和封闭的，然后你会有另一个世界，人们在构建一些开源模型。有些人相信将会有一个单一的主导模型。

I'm of the mind that there's probably an interface that, if you look at Microsoft, Jarvis, you look at Lange and fix here. Any of these companies where they take an input and then they are basically mediator across a bunch of different models for different purposes. I think that's probably going to be the dominant model, at least in the consumer world.
我认为可能存在这样一种接口，如果你看看微软、Jarvis，还有Lange和Fix等公司，它们接受输入并在不同的模型之间充当中介。我认为这可能会成为主要的模式，至少在消费者领域。

And then in the enterprise world, you'll have the Stripe Twilios, who are creating platforms where it's very simple for developers to get started with large language models. And then you'll have like full enterprise services firms where a big fortune 500 just wants a problem solved. So Pepsi needs a generative model for whatever reason. They don't have the disappoint, they want the whole thing in a box.
在企业界中，有一些公司像Stripe和Twilios，他们正在创建简单易用的平台，帮助开发者使用大型的语言模型。同时还有专门的企业服务公司，他们可以为大型500强企业解决各种问题。举个例子，比如Pepsi公司需要一个生成模型来完成某个任务，他们无法自己研发，因此像这样的服务公司可以提供整体解决方案。

And so you know, this really nice spectrum. I think at the foundational model layer, that's a big boys game or big girls game. Because of the capital intensity required both for training and the GPU access and all those kinds of things. So maybe there's a start up or two that's able to raise a couple billion dollars in order to compete. I think it's more at the application layer.
所以，你需要知道的是，这是一个非常美妙的光谱。我认为，在基础模型层面上，这是一个大人物的游戏，因为训练和GPU访问所需的资本密集度以及所有这些事情。因此，可能有一个或两个初创企业能够筹集数十亿美元以竞争。我认为更多的是在应用层面。

I ran this analysis. So in Web2, if you take the top three clouds and you look at their market cap, so AWS, GCP and Azure, it's about a 2.1 trillion dollar market cap just for the cloud business. And then if you take the top 100 publicly traded cloud companies both on B2C and B2B side, Netflix and service now, they have equivalent market cap about 2.1 trillion for both. So I wanted the infrastructure layer, I wanted the application layer. Market cap is basically equivalent. The difference is the infrastructure layer, there are three businesses and at the application layer, there are 100.
我进行了这个分析。因此，在Web2中，如果你看看三大云计算服务商AWS、GCP和Azure的市值，它们的市值约为2.1万亿美元的云业务。如果你再看看B2C和B2B两个方面的前100家公开交易的云公司，如Netflix和Service Now，它们的市值相当于2.1万亿美元。所以我想要基础架构层和应用层。市值基本上是相同的，区别在于基础架构层有三个业务，应用层有100个。

If the analogy holds as an investor, it odds of success are going to be significantly higher at the application layer because the diversity of needs there is greater. You manage to kind of enterprise usage that.
如果将此类比应用于投资者，那么在应用层面上，成功的几率会显著提高，因为在那里的需求多样性更大。您可以管理这种企业使用。

The thing I can get my head around is like some of the biggest companies in the world will not allow the majority of their data to be put through a different solution stored in some cloud infrastructure they've got no idea about. This is some of the most sensitive data they have. If they want to run any form of queries or models on it, it will need to be on-prem in their HQ under lock and key.
我能理解的是世界上一些最大的公司不允许大部分数据通过别的解决方案存储在一些云基础设施中，而他们对此毫不知情。这些是他们最敏感的数据。如果他们想对此运行任何形式的查询或模型，就需要将其放置在总部内保密的内部服务器上。

How do we think about enterprise access when data access is so cool to their needs? So the first generation of software, all the software was run on and enterprises machines. And Salesforce said let's move it to the cloud and we convinced as an ecosystem everyone that the cloud was safe. And the cloud is also expensive, starting to realize.
当数据访问对于企业来说如此重要时，我们如何考虑企业的访问方式？因此，在第一代软件中，所有的软件都是在企业的机器上运行的。Salesforce说让我们将它搬到云端，并且我们作为生态系统的一部分，说服大家云是安全的。 但目前我们开始意识到，云也很昂贵。

And so now there's a bifurcation where data remains in the customer's account. The application is being run by the software company. So they have a separation of the application from the application plane from the control from the data plane. I think we'll see a very similar architecture where the model actually goes to the data and then comes back out with the result.
所以现在存在一种数据分离，即数据保留在客户账户中，应用程序由软件公司运行。因此，控制业务与数据业务被分离开来。我认为我们将看到一种非常相似的架构，其中模型实际上会访问数据，然后再带着结果返回。

So the data is actually within the customer's account. There's some compute that's input next to the data. The model is executed and then it goes away. And that way whoever's managing the model can update the model, modify it, do whatever they need to. And then at the time the model is needed to send the point and pull back. So I think that's probably a dominant architecture.
因此，数据实际上存储在客户的账户中，与数据一起输入一些计算。执行模型后，计算就会消失。这样，管理模型的人就可以更新、修改或者进行其他必要的操作。然后当需要执行模型时，就可以发送点并返回结果。这可能是主要的架构方式。

I think if you're in like finance or healthcare, it'll probably be completely on-prem for the foreseeable future. There are other kinds of issues like if co-pilot produces a bunch of code, any year of global 2000 and that code is actually copyrighted by somebody else, what do you do? If a model produces a bunch of PII that's like quasi-related to somebody else, I put together this presentation on the opportunities for AI startups and one of them is this whole bucket of enterprise readiness, like SOC2 compliance, legal shielding, data security, there are all these kinds of deployment models, there are all these kinds of challenges and issues that are associated with them and there's a big business there.
我认为如果你从事的是金融或者医疗领域，未来它们很可能会完全采用本地部署。还有其他一些问题，比如如果合作伙伴生成了一堆代码，并且这些代码在全球2000强企业的某一年中被其他人版权所有，你该怎么办？如果模型生成了一大堆几乎与其他人相关的个人身份信息，我也整理了一个关于AI初创公司的机遇的演示文稿，其中一个机会就是企业准备就绪的整个领域，包括SOC2合规性、法律保护、数据安全等方面。这里有各种各样的部署模型，以及与之相关的各种挑战和问题，这是一个巨大的商机。

Many big businesses to be built there. That's a question. Do you think this is a bundled environment? I always think about the quotes Jim Bostel, bundling or unbundling. As you said that, there's many different big businesses to be built at but they could also be bundled into an enterprise software suite. Do you think it's a bundle or an unbundled world in that envisioning?
在那里将建造许多大型企业。这是一个问题。您认为这是一种捆绑环境吗？我一直在思考吉姆·博斯特尔的名言，即捆绑或分拆。就像您所说的，有许多不同的大型企业可以建立，但它们也可以被捆绑成一个企业软件套件。您认为这是一个捆绑还是分拆的世界？

My learning has been that in early markets people want bundling and they want bundling because they don't yet understand the technology moving so fast that most people don't really understand it end to end but they want the technology to solve a problem. For your global 2000 you want a generative model, you're not yet in the place where you can, most people aren't, say that these are the five different layers, these are the best of breed across the five different layers and these are the parameters upon which I'm going to choose best of breed. So the embedding layer, the two most important things are X and Y, right? And at the model serving layer that latency versus cost, most people aren't there yet in their level of sophistication because they don't have enough experience with it.
我的学习经验是，在早期市场上，人们想要一揽子的服务，这是因为他们还不了解科技的快速发展，大多数人并不完全理解科技的始终。但他们想要科技来解决问题。对于全球2000强企业来说，他们需要一个生成模型，大多数人还不具备足够的经验，无法在各个层面上评估不同的选择。例如，针对嵌入层，最重要的两个因素是X和Y。在模型服务层，大多数人还缺乏足够的专业知识，无法找到平衡延迟和成本的最佳方法。

So my sense is in the beginning people want an end-to-end solution, just give me a thing that works that's simple and then as I learn what my needs are and what my customer needs are and what I need the software to do, I will break it in a particular way, then I will go and look for a best of breed in the market and I will swap out that layer. My question to you is I'm worried about this asymmetry of knowledge. We mentioned kind of enterprise, but I was there and then the providers told me I'm European, I know how some of these large enterprises think, especially in Europe. Hey, I, it's kind of like you need to remind them it's artificial intelligence. Al Alams is your gone. You've lost me already.
我的理解是，在开始，人们希望得到一个端到端的解决方案，只要给我一个能工作的简单的东西，当我了解我的需求、客户的需求以及我需要软件做什么时，我会以特定的方式来打破它，然后我会去寻找市场上最好的解决方案并替换掉那个层。我的问题是，我担心这种知识的不对称性。我们谈到了企业，但我在那里，供应商告诉我我是欧洲人，我知道一些大型企业的想法，尤其是在欧洲。嘿，我觉得你需要提醒他们这是人工智能。 Al Alams 是你失去的了。你已经失去了我。

How ready do you think enterprise buyers actually are? Do you think the hype cycle is ahead of the enterprise propensity to buy? This is a technology that most buyers won't need to understand how it works. It's like a database. How does Snowflake work? I bet most people who buy Snowflake don't know.
你认为企业买家实际上准备好了吗？你认为炒作周期是否超前于企业购买意向？这是一项大多数买家不需要理解如何运作的技术。它就像一个数据库。雪花是如何工作的？我敢打赌，购买雪花的大多数人不知道。

I don't know if you ever have seen the story, but there's this Italian artist and he was exploring this idea. It's called the illusion of explanatory depth. So he found 100 people in Milan and he asked them to draw a bicycle and then he 3D printed all those bicycles. And out of the 100 bicycles, how many did you think worked? 10. 2. So just because we're very familiar with the technology or an innovation doesn't necessarily mean that we understand how it works. And so I think in the case for most enterprise buyers, like I said before, I think they want an end-to-end solution that will just work and what work in 85 to 90% of the time and that'll be good enough. And if in those 80 to 95% of the time, I can save you half of your times, co-bile it does, then that's good enough. And as long as it checks all the boxes for my security team, my IT team and my compliance team, then that's good enough.
我不知道你是否看过这个故事，有位意大利艺术家探讨了一个想法，叫做解释深度的幻觉。他在米兰找到了100个人，让他们画一辆自行车，然后把这100辆自行车都进行了3D打印，其中有多少辆自行车能够正常工作呢？只有10辆，还是2辆。这说明我们只是对某项技术或创新非常熟悉，并不意味着我们了解其原理。因此，对于大多数企业买家而言，像我之前所说的，他们想要的是一个端到端的解决方案，能够正常工作，并且在85%到90%的时间内都能够正常工作，这就足够了。如果在这80%到95%的时间内，我可以像Co-Bile一样为你节省一半的时间，那就足够了。只要它符合我安全团队、IT团队和合规团队的所有需求，那就够了。

Imagine that co-pilot, and you mentioned it quite a few times. Today, I think it's co-generation. 40% of new co-generation is artificially intelligent co-generation. What do you think that will be in 10 years' time? I think it'll probably be 70 to 80%. And reason I say that, I bet that 40% a lot of it is what's called boilerplate code. A lot of it is standard code or code that's been slightly modified. I'm creating an HTML page. I need the HTML header and the title. And so that's probably 40% of the content of an HTML page. It's probably the same for a Ruby file or Python environment. And so we're at 40% today, and I bet we're at 75 to 80%. Most of the code that's written is slight modifications of existing code. And Pepsi's website is not that different to Coca-Cola except for the underlying assets in the text. And so we'll get there.
想象一下，你一直提到副驾驶员。今天，我认为是共发电。新的40%的共发电是人工智能共发电。你认为在10年后会是什么样子？我认为可能会达到70%至80%。我说这个的原因是，我打赌其中40%是所谓的"样板代码"。很多都是标准代码或略微修改过的代码。我正在创建一个HTML页面。我需要HTML头和标题。因此这可能是HTML页面内容的40%。对于Ruby文件或Python环境，情况可能相同。所以今天我们占40%，而我敢打赌我们会达到75%至80%。大部分编写的代码都是现有代码的轻微修改。百事可乐的网站与可口可乐的网站只有文本和底层资源不同。所以我们会到达那里。

And so then the question is, OK, Goldman projects a 7% reduction in the labor population as a result of artificial intelligence. But overall, a 2.5% increase in GDP. And so that's massive. The US GDP is growing at about 2.5%. Over the last 20 years grew at about 2.5% a year. And so you have this impact where you can literally double the GDP growth of the US as a result of AI. And so the reason I think a lot of people are super excited about it. The reason I'm so excited about it is the macroeconomically for the US. We're in a hole where we've printed way too many dollars for the GDP that we're producing. But now we face with a technology that could replicate the postwar surplus out of World War II that drove the next 40 to 60 years of prosperity. But you've got a technology that's not really a wartime technology that could do it. That's the reason I think so many people are so excited about it. And the evaluations are as astronomical as they are.
所以问题来了，高盛预测由于人工智能的影响，劳动人口将减少7%，但总体上GDP将增长2.5%。这是一个巨大的变化。美国GDP增长约为2.5%，在过去20年里年均增长率达到了2.5%。因此，在人工智能的帮助下，美国的GDP增长率可以翻倍。这是许多人对人工智能感到非常兴奋的原因，也是我对此如此兴奋的原因之一。从宏观经济角度来看，我们已经为我们所生产的GDP印刷了太多的美元。但现在我们面临的是一种技术，可以再现出二战后的经济盈余，推动未来40至60年的繁荣。但这项技术不是一种战时技术，这就是为什么我认为许多人对此如此激动并估值如此高的原因。

The one concern I have is when you look at it, it does bring about a concern about distribution of wealth and the concentration of income. How do you think about wealth inequality over the next few years? And the dangers of it actually concentrating wealth further into the hands of fewer?
我唯一的担忧是，当你看到这个问题时，就会担心财富的分配和收入的集中。你如何看待未来几年的财富不平等？以及它将进一步将财富集中到更少的人手中的危险？

Getting into politics. I think it's the role of the private markets in order to drive innovation forward. And it's the role of government in order to encode the values of the population into its loss. So I think those are the forces that exist in tension and the network effects and the power laws that we're all chasing definitely create those dynamics when it comes to wealth. But it's not a new problem. You look at railroads or telecommunications or wailing that's been around for forever.
“进入政治领域。我认为，推动创新的作用是私有市场的角色；而将人民价值观编入其法律体系的作用则是政府的角色。因此，我认为这些力量之间存在着紧张关系，我们追求的网络效应和权力法则肯定会在财富方面产生动态作用。但这并不是一个新问题。你可以看看铁路、电信或捕鲸业，这些问题一直存在。”

Final one on this. How do you think about regulation? I'm concerned about the asymmetry of knowledge between private and public. We're very fortunate to spend time with someone most brilliant entrepreneur in the world. And then you go and speak to regulatory bodies which, Bloney just don't have the same level of information and knowledge. And they're setting the regulation. It's concerning.
把最后一部分也翻译了。你对监管有什么看法？我担心私人和公众之间的知识不对称问题。我们非常幸运能够与全球最为杰出的企业家共度时光。但是，当你去与监管机构对话时，你会发现，他们缺乏相同的信息和知识水平。而他们却制定着法规。这令人担忧。

How do you think about that chasm of knowledge between those two bodies? And why it means we'll shake out from a regulatory standpoint. It's a lower conversation. I think regulation on the whole, one, it benefits incumbents because the cost of adhering to regulations are significant. You take a look at in the mid-90s you could have 25 million in revenue and go public. Today, if you have 100 million in revenue, it costs you $15 million in your first year to go public. And that's just a byproduct of regulation. So regulation benefits the winners or the bigger companies.
你认为那两个领域之间的巨大知识鸿沟如何？为什么这意味着我们从监管角度来说会动荡不安？这是一个较低级别的讨论。我认为，整体上监管有利于现有老牌企业，因为遵守监管规定的成本很高。回顾上世纪90年代，你可以有2500万美元的收入并上市。而今天，如果你有1亿美元的收入，在第一年上市就需要花费1500万美元。这仅仅是监管的副作用。因此，监管有利于赢家或更大的公司。

I think the second thing is a lot of the times when regulation is imposed, people don't anticipate the second order effects. You look at real estate prices in California as there are three to four times what they are in the rest of the country because of the law that was passed in the 1970s called Prop 13. They're all these sort of like second and third order effects that a lot of regulation doesn't anticipate. And the legal process doesn't move fast enough. You look at crypto, right? It's taken the US government 10 years to catch up to what's going on and now with Operation Choke Point starting to really regulate that ecosystem and they finally gotten around to it.
我认为第二个问题往往在于当规定被实施时，人们并没有预料到二级效应。例如，你看看加利福尼亚州的房地产价格，比国家其他地方高三到四倍，这是由于在20世纪70年代通过的“Prop 13”法律导致的。很多规定并没有预料到这些二次和三次效应，而且法律程序也不够迅速。你看看加密货币，对于美国政府来说，花了10年时间才追赶到发展潮流，现在的“封喉行动”开始真正监管这个生态系统，终于找到机会了。

So I think the system, maybe a dollar and another example, if you think about airplanes, it post world war two airplanes. We were just invented the jet engine and the commercial airlining business was growing. But it was still really risky. The FAA put a bunch of regulations around planes and we kept flying planes. And then one day we realized that planes will square windows crash more because they create stress fractures along the points of the squares. And so we regulated that out. What does that teach you? We don't know what we don't know. And so the best path to regulation is incremental when we identify that there's something wrong. Will bad things happen long way? Yes, there's no doubt. I mean, this is my town, Calis, but that's the path of the price of progress.
我认为这个系统，就像一个美元和另一个例子，如果你想想飞机，它是二战后的飞机。我们刚刚发明了喷气发动机和商业航空业正在增长。但这仍然是非常高风险的。FAA在飞机周围制定了一堆规定，但我们仍然继续飞行。然后有一天，我们意识到有方形窗户的飞机更容易坠毁，因为它们在方形点周围会产生应力裂纹。因此我们对此进行了规定。这告诉我们什么？我们不知道我们不知道的东西。因此，最好的规定途径是逐步地在我们发现有问题时进行。长期会发生糟糕的事情吗？是的，毫无疑问。这是进步的代价。

Final one, you mentioned it, sometimes benefiting larger companies and incumbents. This is my also big question, which is like startups first incumbents, Alex Rampeller-Landryson says a brilliant one, which is, will the incumbent acquired innovation before the startup acquires distribution? When we look at the two-ensilist spectrum for the next generation of AI and LLM, which is will existing incumbents integrate it well enough into their distribution channels to be highly effective and continue their dominance. Or actually a startup with agility, flexible code bases, much better place to win in this next generation.
最后一个问题，你提到的，有时会让大公司和现有企业受益。这也是我的一个大问题，这就像初创企业面对现有企业，亚历克斯·兰佐瑟森提出了一个很棒的问题，那就是，现有企业是否能够在初创企业获得分销之前获得创新？ 当我们看下一代人工智能和法律语言模型的双重分布谱时，现有企业能够将其充分整合到其分销渠道中以实现高度有效性并继续主导地位，还是敏捷、灵活的基础代码的初创企业更有优势赢得下一代市场。

How do you think that that kind of startup versus incumbent megawatt? My thinking is evolved here. In the beginning of the 13 comments, we're going to win the whole thing. And I thought that because the incumbents have far greater distribution, Microsoft has an incredible channel, Microsoft has a special relationship with OpenAI, the pace with which Microsoft is injecting its products with LLMs is astounding. And so startups are in this unusual position where they have negative time to launch. They're actually behind the market, which is unusual. Think about mobile apps and the launch of the Apple Store. Startups for the first ones to understand how to write mobile apps with objective scene.
你怎么看待这种初创公司与现有龙头企业的竞争？我的想法在这里有所改变。在开头的13个评论中，我们会赢得整件事。我之所以这样想是因为龙头企业具有更广泛的分销渠道，微软拥有不可思议的渠道，微软与OpenAI有特殊的关系，微软注入其产品的LLMs的速度也令人惊叹。因此，初创公司处于一种不寻常的位置，他们没有足够的时间去推出自己的产品。他们实际上落后于市场，这是不寻常的。想想移动应用程序和Apple Store的推出。初创公司是第一个理解如何编写具有客观场景的移动应用程序的人。

But I think any time we talk about machine learning, there's always this question around what is the mode? And I have this as a reaction, which is like to data mode to data mode. And I think the answer is the one that it's always been, which is better execution is the mode.
但我认为每次我们谈论机器学习时，总会有一个问题：“什么是模式？”我有一种反应，就是“数据模式到数据模式”。而我认为答案始终都是相同的，那就是更好的执行是模式。

If you can build a better CRM and get it into the market, you can win. You take a look at what notion has done with documents. Or what Snowflank did with databases facing too big incumbents. There are these stories. They're all over. They create this beautiful constellation within startup land of the David versus Kaliah story.
如果你能建立一个更好的客户关系管理系统并把它推向市场，你就能获胜。你可以看看Notion是如何处理文档的，以及Snowflank是如何面对庞大的竞争者处理数据库的。这些故事随处可见，在初创企业中形成了一个美丽的星座，David与Kaliah的故事。

I think if you're a venture capitalist or if you're a startup founder, you have to believe. I think it's in your fabric that no matter how big the incumbent is or the advantages that they have, that if you have really great execution, you can still win and you can win big. And tell you, Lager, I always say the speed of execution is the biggest determinant that I see and the differences between achieving and not achieving product market fit.
我认为，如果你是一位风险投资家或者创业公司创始人，你必须要相信。我认为，这已经融入到你的本质中，无论现有公司的规模大小或者他们所拥有的优势有多大，只要你有非常出色的执行力，你仍然能够赢得并且赢得更大。而我告诉你，拉格，我总是说，执行速度是我看到的最大决定因素，以及实现和未实现产品市场适配之间的差异。

Tom, I think we both agree that Microsoft's absolutely killed it in terms of their embracing and approach to this netting generation who's done really badly at which one of them is, ah, you really missed the beat on this one, guys. How it's got to be Google. It's my former employer, so it pains me to say it. And I didn't believe that chat would replace search, but I think for many use cases it will.
汤姆，我认为我们都同意，微软在接纳和处理这一网络世代方面做得非常好，而这一代人在其中表现得非常糟糕，其中一个原因是，啊，你们真的在这件事上错过了机会，伙计们。现在必须是谷歌。它是我之前的雇主，所以说这让我很痛苦。我之前认为聊天不会取代搜索，但我认为对于许多使用场景来说它都会。

And I think Google had a root awakening where I don't know, for 20, 25 years, they were uncontested. And now all of a sudden, there's disruptive technology. For some extent, they developed in-house, but ignored. So it's a classic innovator's dilemma. And so this technology went to other places and now is challenging the hegemony, the monopoly power.
我认为谷歌最近有了一个根本性的觉醒，因为在过去的20到25年里，他们一直处于无人能敌的地位。现在突然出现了颠覆性技术。在某种程度上，这些技术是谷歌自己开发出来的，但他们没有加以利用。所以这是一个典型的创新者困境。这些技术现在已经流向其他地方，正在挑战谷歌的霸权和垄断权。

And that is so exciting. If you think about like the ads ecosystem, like the BDC ecosystem has been relatively quiet over the last 10 years because of that dominance of Facebook and Google. And now all of a sudden, you have a technology and a replatforming where all that market share is conceivably up for grabs. You couldn't create a new travel agency. You could create a new shopping experience. You could create a new stack overflow. You could create a new social experience based on chat. And so it's wide open.
这是非常令人兴奋的事情。如果你考虑广告生态系统，由于Facebook和Google的主导，BDC生态系统在过去的十年中相对安静。现在，你突然拥有了一种技术和重新平台化，所有的市场份额都有可能被争夺。你可以创建一个新的旅行社，也可以创建一个新的购物体验，或者是一个基于聊天的新社交体验。所以这个领域是完全开放的。

They were so strategically ahead of the game acquiring DeepMind, an amazing team there. What went wrong with that? I think it's a classic thing that when you have a golden goose, when you have an incredible business model, you're always faced with the choice of disrupting yourself and destabilizing the ship or waiting until somebody destabilizes it for you. I think as a leadership team, it is so difficult to have the discipline to say, we are going to destabilize this ourselves.
他们在收购DeepMind方面非常具有战略优势，那里有一个非常出色的团队。但是出了什么问题呢？我认为这是一个经典问题，当你拥有一个金鹅，一个令人难以置信的商业模式时，你总是面临一个选择：是破坏它并破坏整艘船，还是等着别人为你破坏它。作为领导团队，要做到有纪律地说：“我们要自己破坏这个机构”，这是非常困难的。

That's what happened. I think they knew. And what I mean by that is that Netflix did destabilize the golden goose. They took their mail all the business and put it online because it was obvious. It would lose revenue in a short time, but it would be obvious. The move from search to chat still isn't actually obvious. It's potential, but it's not obvious. Do you think that's why? I think it's part of it.
这就是发生的事情。我觉得他们知道。我的意思是Netflix破坏了那只金鹅。他们把所有的邮寄业务都放到了网上，因为这是显而易见的。虽然短期内会损失收入，但这一点是显而易见的。而从搜索到聊天的转变，现在仍然不是显然的。它有潜力，但不是显而易见的。你认为这是为什么吗？我觉得这是它的一部分。

So you think about the cost that produces a GPT-4 query versus the cost that produces a Google query. I bet it's like 100 or a thousand or 10,000 times different. And Chris Dixon had this post every major innovation starts out looking like a toy about the chat, the Google, or anybody working in search is looking at those tech. And then we had conversations with friends talking about the cost for query on the stuff. You just can't get the economics.
所以你应该思考一下，制造GPT-4查询的成本和制造Google查询的成本之间的差距。我敢打赌，它们之间的差距可能是100倍、1000倍或者1万倍不止。克里斯·迪克森在他的博客上提到，每一项重大创新都开始像一件玩具一样，这适用于聊天机器人、Google或任何从事搜索领域的人。我们和朋友聊天时谈到了搜索技术的查询成本。你就是琢磨不透这些经济规律。

But you can't look at it at a point in time. You've got to look at it on some geometric curve or some logarithmic curve where you've got effectively a Moore's Law happening for you. So I think that was definitely a mistake that I made in anticipating the technology.
但你不能只看它的某一时刻。你必须将它放在某个几何曲线或某个对数曲线上，这样你才能有效地看到一个摩尔定律正在发生。所以我认为在预测技术发展方面，我犯了一个错误。

I think the other thing that I didn't really appreciate until some of the later models came out was just how sophisticated the emergent behavior can. So there's this paper that talks about how these LLMs learn. And the analogy is like humans.
直到一些较晚的模型问世，我才真正意识到另一个事情，即紧急行为可以有多复杂。有一篇论文探讨了这些LM（语言模型）如何学习，类比于人类。

So I can learn math by reading a book. I can learn addition. I can learn division. In that way, the next time I see 4 plus 4, I know what the answer is. Or what a cube root of 27. I also learn how to swim. And in order to learn how to swim, I can read a book about the physics, fluid dynamics, and I can understand what's happening with the vortices and where my arms need to be and what my legs need to do. But after reading that book, you throw me in the pool I will drown.
我能通过读书学习数学。我可以学习加法。我可以学习除法。这样，下次当我看到4加4时，我知道答案是多少。或者一个27的立方根。我也能学会游泳。为了学会游泳，我可以读一本关于物理学和流体动力学的书，我可以理解涡流的发生及我的手臂和腿应该做什么。但是，读完那本书后，如果你把我扔进游泳池，我会淹死。

Paragraph 1: I'm just going to question. I can read all the theory in the world. And so there's two different ways that we learn. We learn by effectively memorization and we learn by doing. And what we thought at the beginning with these LLMs was that they're primarily memorization systems. And that's why there's improvements in the GMATs and the LSATs and the AP tests, because they have more and more exposure to those questions. But we're starting to realize that they learn also by doing.
第一段： 我只是要质疑一下。阅读再多的理论都没有用。我们学习有两种不同的方式。我们通过有效的记忆和实践来学习。起初我们认为这些硕士学位主要是背诵系统。这就是为什么他们在GMAT、LSAT和AP考试中有更多的暴露，因为他们接触到更多的这些问题。但我们开始意识到，他们也通过实践学习。

Paragraph 2: And so there are these sort of what they're called emergent properties where the more questions that they're asked, the more they figure out how to answer those questions in a better way. And so the feedback loop that exists that only happens when they swim more. They swim more. They learn how to swim faster. They ask more questions. They learn how to answer questions better, just like a human would. And not to say that they're humans, said that whole thing aside, but that I think has a compounding benefit that is really difficult to appreciate.
因此，这些被称为“新兴性质”的特征随着提出的问题越来越多，它们会更好地思考如何回答这些问题。只有当它们游得更多，存在这种反馈循环。它们游得更多，学会了更快地游泳。它们提出更多的问题，学会了更好地回答问题，就像人类一样。不是说它们是人类，放下这一切不谈，但我认为这具有复合效益，非常难以欣赏。

Paragraph 3: Humans are very good at linear stuff and they're terrible at geometric stuff. And I think what happened is that the quality of the answers and the breadth of the knowledge and some of these emergent behaviors, like the models learning how to swim, all of a sudden snuck up on everybody and now the pace of innovation in space is so fast you wake up every morning and there's a new model, there's a new way of putting it together, there's a new application. It's just it's really hard to stay on top and that's because we're on the steep part of this geometric curve for the sophistication of these models. And at some point it will make the shelf of an S, but it doesn't feel like we're going to be close.
人类在线性方面非常擅长，但在几何方面却很差。我认为发生的事情是，模型的答案质量和知识广度以及一些新兴行为，比如模型学会游泳，突然间悄无声息地发生了，现在太空领域的创新速度如此之快，每天早上都会有一个新的模型，有一种新的组合方式，或有一种新的应用。保持领先非常困难，这是因为我们处于这些模型复杂程度的几何曲线的陡峭部分。在某些时候，它会变成S形曲线，但感觉我们离这个状态还很远。

Paragraph 4: The final one I promise. The one thing that is a European, I'm not a short learner, no one else is thinking about or seems to be knowing anything about it, is like the data or content ownership. And what I mean by that is Google will redirect you to a newspaper website where the cool pages, where the original post is. ChaoGBT will leverage the internet and the world's content base and retain you on their website and simply scrape the information to theirs.
我承诺这是最后一个话题了。我要谈的是一个欧洲独有的问题，其他人好像都没有注意到或不太懂得 —— 数据或内容所有权。我的意思是，谷歌会将你重定向到报纸网站的炫酷页面，即原始帖子所在的地方。而ChaoGBT会利用互联网和全球的内容库，并将你留在他们的网站上，并将信息转移到他们的服务器上。

Paragraph 5: Content providers will not be able to build a business when ChaoGBT just scrapes all of their content and they have no way to monetize in any way. But how do we think about the future of data attribution and content attribution in that model? So Google has had this problem for forever with snippets. You ask it, like who is Harry Stubbix and it puts the three paragraphs about how amazing you are on the search results page, right? And that could come from the New York Times and the publishers and Google have been fighting back and forth in Europe and other geographies.
当超高速下载技术（ChaoGBT）抓取所有的内容，并且内容提供商无法以任何方式进行货币化时，他们将无法建立业务。但是，在这种模式下，我们如何考虑数据和内容的归属问题？因此，Google一直存在缩略语的这个问题。例如，当你查询“Harry Stubbix是谁”时，它会在搜索结果页上放置三段关于你有多么惊人的内容。这可能来自《纽约时报》等出版商，而Google与出版商之间一直在欧洲和其他地区进行争论。

Paragraph 6: It definitely exists here. Who owns that content? The notion of fair use. If I take two music tracks and put them together, that's a new product. And so I have that copyright. If I take the New York Times article about the events in Taiwan and I mix it with a CNN article and it produces a new article, is that a new thing? Where I should have copyright. And so basically the internet becomes one huge wall garden that's just summarized by ChaoGBT.
这种情况在这里确实存在。但是谁拥有那些内容呢？关键在于公平使用的概念。如果我把两首音乐混合在一起，那就是一个新作品，我就会拥有版权。如果我把纽约时报关于台湾事件的文章和CNN的一篇文章混合起来，产生了一个新的文章，那这是一个新的东西吗？在这里，我应该拥有版权。因此，互联网成为了一个由ChaoGBT总结的巨大的围墙花园。

Paragraph 7: I don't think any large language model operator wants to see that world because the reality is you need CNN and New York Times or any of the content producers to have a viable business model in order to put into this system. And the large language model company is probably not going to get into that business. And so what does the revenue share look like and what those arrangements and features TBD? I wonder if you can look at the Mozilla Google deal or the Google Apple deal or some of the publisher contracts or even distribution agreements across media companies today. We'll probably get to something like that, be my guest.
我认为大型语言模型运营商都不希望看到这样的世界，因为事实上你需要CNN、纽约时报或其他内容生产者拥有可行的商业模式，才能将其纳入这个系统中。而大型语言模型公司可能不会涉足这个业务。那么收入分成是什么样子的，这些安排和特征还有待确定。我想知道是否可以参考Mozilla与谷歌的协议、谷歌与苹果的协议或者其他媒体公司的分销协议。我们可能会达成类似的协议，敬请期待。

Paragraph 8: I could clearly talk to you all day, but I want to move into a quick fire. I say short statement and then you give me your immediate thoughts. So will we be in a better or worse place macro wise by the end of 2023? I think we will probably be in a worse place by the end of the 23. I think the Fed is over corrected on rates, the rate of money production M1 and M2 is decreasing faster than anyone expected. I think there's just like a human psychology to want to over rotate on things and be slow. And then I think the risk of conflict in Taiwan is significant. So the combination of those four risk factors, I think puts the odds of a US recession meaningfully higher than I think a lot of people appreciate.
我很愿意和你谈上整整一天，但是我想进入一个快速反应的环节。我会说一个简短的陈述，然后你会立刻给我你的想法。那么到2023年末，宏观经济形势会更好还是更糟？我认为到2023年末，我们可能会处于一个更糟的境地。我认为美联储对利率进行了过度纠正，M1和M2的货币生产速度正在比任何人预期的要快。我认为人类心理倾向于过度反应和缓慢。而且，我认为台湾冲突的风险非常大。所以，这四个风险因素的结合，我认为美国经济衰退的可能性较多人所认为的要高。

Paragraph 9: We mentioned Microsoft is like the leader and Google is bluntly behind. Who's like second to be chasing Microsoft? Who are you like they have a short at chasing? Adobe doesn't have the recognition it deserves when it comes to using generative. I think about the applications in Photoshop, the launch of the product called Firefly. I think they're right there.
我们提到Microsoft就像领导者，而Google却直截了当地落后。那么谁是第二个追逐Microsoft的人呢？谁可能有追赶Microsoft的机会？Adobe在使用生成式方面没有得到应有的认可。我想到了Photoshop中的应用程序，以及叫做Firefly的产品的发布。我觉得他们就在那里。

Paragraph 1: What trend in AI and that generation of AI do you see that you don't think others are spending enough time on?
你认为人工智能领域的哪种趋势或是一个生产的人工智能，其他人可能没有足够的时间去关注它？

Paragraph 2: Enterprise readiness. I think if there's one big market opportunity that people haven't focused on, it's how do you bring this to the global 2000 in a way that they will accept it by? That's consistent with ways that they've bought software in the past.
企业就绪性。我认为如果有一个市场机会还没有被人们关注，那就是如何以全球2000大企业已经购买软件的方式推广这种技术，使其符合企业接受标准。

Paragraph 3: You can invest in and you can short one multi stage fund, which fund you invest in and which do you short? I would invest in founders fund and I don't want to say on the shorting side.
你可以投资一支多阶段基金，也可以做空一支，你会选择投资哪支基金？你会做空哪一支？我会选择投资创始人基金，至于做空，我不想透露。

Paragraph 4: Okay, on the seed fund, be teased side pure play seed fund. You can invest in one fund and I guess you don't want to short one. So we can just say invest in which one would you invest in on that side?
好的，关于种子基金，我们考虑纯种子基金投资。你可以在一个基金上进行投资，我猜你不想做空一个基金。那么我们来选择在哪个基金上进行投资，你会选择哪一个呢？

Paragraph 5: On the seed stage, I'd invest in good water. I'd invest in good water because it's completely worth organelle to B2B. I really respect what she was building with his huge, pretty significant engineering team down in the five B2C opportunities all over the world. The opportunity for LLMs to destabilize the existing B2C internet is really huge. That's what I think has got a nice market opportunity in front of them.
在种子阶段，我会投资于水资源领域。因为良好的水资源在B2B市场中具备非常高的价值。我非常尊重投资者正在和他庞大的工程团队在全球各地发展五种B2C机会所做的努力。LLMs为颠覆现有的B2C互联网提供了极大的机会。我认为他们面前有着非常好的市场机遇。

Paragraph 6: What's your biggest investing miss and how did that impact your mindset? Yeah, I've missed so many companies, data dog and Twilio, many others. The thing that I've learned is that the startups are the ones who create the markets. And so if you have a rabid user base in a really early market, it will most of the time surprise you on the upside.
你最大的投资失误是什么，它对你的心态产生了什么影响？是的，我错过了很多公司，比如 DataDog 和 Twilio，还有很多其他的。我从中学到的是创业公司是创造市场的那些公司。如果你在一个非常早期的市场拥有狂热的用户群体，它在大多数情况下会向上超过你的预期。

Paragraph 7: What would you mind to change about the world of LPs? I think the thing that I'd love to see happen in the LP base is LPs educating VCs on their goals. This sort of happened in venture where venture capitalists explain their business models in really clear ways about like fund construction. And I think the most impenetrable part about the LP in a lot of cases is just understanding what drives them, what's the portfolio construction, and then figuring out how to map that to a fund. A theft in the hardest part for me. And he's really hard also for me, I agree with you and I ask many LPs to come on the show, but a lot of them really don't like to be public. About 10 years ago, venture was not nearly as transparent, and I hope we bring a level of transparency to the LP market that we haven't had before.
你希望LP这个世界发生什么改变？我认为我希望看到的是LP向风险投资家（VC）介绍他们的目标。在风投行业，投资者非常清楚地解释了他们的商业模式，如基金构建等等。而在很多情况下，LP中最难理解的部分就是了解是什么驱动他们，什么是组合构建，以及如何将其映射到基金中。这对我来说非常困难。对于其他人来说也很困难。我同意你的看法，我也邀请了许多LP参加节目，但很多人真的不想公开。大约10年前，风投行业不像现在这么透明，我希望我们能为LP市场带来前所未有的透明度。

Paragraph 8: Will Trump win the election? I don't think so. I bet the Santas wins. I think it will be tough for him to circumnavigate all the legal troubles, and I wonder if the RNC doesn't get involved. Would this sound to be good for all business? He's a very complicated person. I think the Republican Party is still the party of business and capitalism. And so I would say yes, put it a different way, which is the entitlement spending in the US over the next 10 years is projected to consume something like 95% of tax receipts.
特朗普能否赢得选举？我不这么认为。我认为桑塔斯会胜出。我觉得他难以解决所有法律问题，而且我不知道共和党全国委员会是否会介入。这对所有企业听起来好吗？他是一个非常复杂的人。我认为共和党仍然是商业和资本主义的党派。因此，我会说是的，换句话说，美国未来10年的福利支出预计将占税收的95％左右。

Paragraph 9: And so we need, and I don't know who it will be, but we need some reform on the entitlements. And France is going through this now, and it's you can see it's extremely painful. And the strikes in the US and the strikes in France. I think we're looking at a long period of time where the relationship between government and people are going to change over the next 10 years pretty meaningfully. And so we need a leader who can guide us through all that.
因此，我们需要改革社会保障，但我不知道这个改革领导者是谁。法国正在经历这个过程，可以看到这是非常痛苦的。美国和法国的罢工。我认为在未来的十年中，政府与人民之间的关系将发生重大变化。因此，我们需要一位领导人来引导我们应对这一切。

Paragraph 10: Tom, but not so at one. Who's your favorite angel to work with? The more than? So I love to work with Guy Pajone. He's the founder of Sneak. Just fantastically insightful, really helpful, very granular advice. It can be a founder that you bring in. One of the angels I really like to work with is his name Alan Black.
汤姆，并非如此。你最喜欢和哪位天使一起工作？更多的是？我喜欢和盖伊·帕乔恩一起工作。他是Sneak公司的创始人。他非常有见解，给出的建议非常具体，帮助很多。当你成为创始人时，你会找到像艾伦·布莱克这样的天使投资人来合作。

Paragraph 11: And Alan was a CFO at Zendesk, and he was on the board with me at Looker. And he took Zendesk public during the crash of 08. And so his experience going through financial carnage is just awesome. Just to have that story to have lived yet, I really respected it. I think he's got a really great world view as a result of that.
阿兰是Zendesk的CFO，他曾经和我一起在Looker的董事会上任职。他在08年市场崩溃期间将Zendesk上市。他在财务瓦解中的经历非常了不起。我尊重他拥有这样的故事和经历。我认为，这让他的世界观更加优秀。

Paragraph 12: Tom, final one, my friend. Well, it's been the biggest home run cash-generative investment that you've made from a DPI perspective. And how do we come to be? It was Looker. The story there was in 2012, Rich Shift with the fast-screwing product inside of AWS and Tableau was the dominant B.I. product. And there was a thesis that there would be a new B.I. product that would be architecture for the cloud. And the front of mind from Google, I introduced me to Lloyd, the founder. And we clicked and I love the technology we had built. And there was a post that I think it was Josh Coppeman, a Finn Barnes, wrote, and the question was, who took a bet on you when you were young in your career? And Lloyd took a bet on me and brought me in at DA and very grateful for it.
汤姆，最后一个了，我的朋友。从 DPI角度来看，这是你进行的最大的净现金投资。我们是如何做到的呢？那就是看涨者。在2012年，里奇·希夫特在AWS内部推出了快速升级的产品，而Tableau则是占主导地位的B.I.产品。于是，有一个理论认为，云端将会产生一种新的B.I.产品。在我与Google了解情况后，我认识了创建者洛伊德，并且我们一拍即合。我喜欢他们所构建的技术，也有一篇文章的问答环节，我想是乔希·科珀曼和芬恩·巴恩斯写的，问题是：谁在你职业生涯早期就愿意投入赌注？洛伊德在我身上下了赌注，并让我在DA里开始工作。我非常感激。

Paragraph 1: Tom, listen, I love doing this. I hope my interviewing style has changed a little bit over the years. It's so much fun. Thank you so much for doing it, my man.
汤姆，听着，我喜欢这个。希望我的采访风格在这些年里有所改变。这太有趣了。非常感谢你参与采访，我的朋友。

Paragraph 2: Thank you so much, Harry. I really appreciate it. Congratulations on all your success, too.
非常感谢你，哈利。我真的很感激。祝贺你取得的所有成功，太棒了。

Paragraph 3: I just love doing that episode with Tom and I implore you to check out his writing. It is fantastic. Find about TomTongers.com. You can also find us on YouTube by searching for 20VC, where you can watch the full interview to stay in full.
我非常喜欢和汤姆一起录制这一集，我敦促你去看他的文章。它很棒。了解一下TomTongers.com。你也可以在YouTube上搜索20VC找到我们，观看完整访谈并保持更新。

Paragraph 4: But before we leave you to stay, leave, let me talk about Coda. Coda is the doc that brings it all together and how it can help your team run smoother and be more efficient. I know this because Coda helps me.
在我们让你留下或离开之前，让我谈谈Coda。Coda是一种文档，它将一切结合起来，并帮助您的团队更顺畅地运行，更高效。我知道这是因为Coda帮助了我。

Paragraph 5: At 20VC, we use Coda for all of our research for every episode. So all team members essentially can work on the schedule all in one doc, seamlessly built by Coda.
在20VC中，我们使用Coda对每一集节目进行所有研究。因此，所有团队成员都可以在一个文档中无缝地工作，这个文档是由Coda构建的。

Paragraph 6: And here's how Coda can help your team run smoother and be more efficient. Coda allows you team to operate on the same information and collaborate like my team does all in one Coda place.
这里，我们来看看Coda如何帮助您的团队更加顺畅高效地运营。Coda让您的团队在同一处操作信息，并像我的团队一样协作，所有工作都可以在Coda中完成。

Paragraph 7: By putting data in one centralized location, regardless of format, it eliminates so many road blocks that can just stop your team in their tracks. This is really what slows down productivity and collaboration.
把数据放在一个集中的地方，无论格式如何，都能消除很多可能妨碍团队进展的障碍。这就是拖慢生产力和协作的原因。

Paragraph 8: With Coda, your team can operate on the same information and collaborate in one place to get projects across the finish line faster. Help your team run more smoothly, more efficiently with Coda.
通过Coda，你的团队可以在同一个地方操作相同的信息并协作，更快地完成项目。使用Coda，帮助你的团队更顺畅、更高效地运作。

Paragraph 9: Get started, stay for free. Head over to coder.io slash 20VC. That's coder.io and get started, stay for free. Coda.io slash 20VC.
开始使用吧，免费留下。前往 coder.io/20VC ，这是 coder.io 的网址，开始使用吧，免费留下。也可以前往 coda.io/20VC。

Paragraph 10: And some EU tools we cannot live without. Angelist is fast becoming the center of the venture ecosystem. So for startups, Angelist reduces the friction of capital management, banking and fundraising all in one place.
有些欧盟的工具对我们来说是无法离开的。Angelist正在迅速成为风险投资生态系统的中心。所以对于初创企业来说，Angelist在一个平台上降低了资本管理、银行业务和筹款的摩擦度。

Paragraph 11: Teams can focus on scaling and let Angelist handle the rest. Thousands of startups have moved their cap tables to Angelist in the past year. Angelist also supports large venture funds and their teams with an automated software first approach and the best customer service in the industry.
团队可以专注于规模化，让Angelist处理其余的事务。过去一年中，成千上万的初创企业已将其股本清单移至Angelist。Angelist还通过自动化软件为先的方法支持大型风险基金及其团队，并提供行业最佳的客户服务。

Paragraph 12: Fun managers can focus on making great deals, while Angelist handles reporting, taxes, compliance and more. What's more, with the recent release of Angelist Network banking for fun managers and investors, your deposits are secure with the most trusted banks for maximized FDIC coverage and mitigated single-bank risk.
有趣的经理人可以专注于达成出色的交易，而Angelist则处理报告、税收、合规等事务。更重要的是，随着Angelist Network为有趣的经理人和投资者提供银行服务，你的存款将通过最值得信赖的银行来保障最大化的FDIC覆盖面和降低单一银行风险。

Paragraph 13: If you're ready to scale your startup or fund with the platform of the center of it, visit angelist.com forward slash 20VC to get started. And finally, Brexit. Since its founding, Brexit has been committed to helping startups launch and scale faster at every stage of growth, from MVP to IPO.
如果您准备通过平台来扩大创业公司或融资，请访问angellist.com/20VC开始操作。最后，谈到 Brexit。自成立以来，Brexit一直致力于帮助创业公司在从MVP到IPO的各个增长阶段更快地推出和扩大规模。

Paragraph 14: Today, Brexit's all-in-one financial stack is used by one in four US startups and counting. I get to speak to founders all day, and I know how crucial it is for them to have the right financial stack. Brexit gives you fast access to a high-eal business account where you can safely store and move your cash while getting up to 6 million in FDIC protection.
如今，Brexit 的一站式金融平台正在被四分之一的美国初创企业所使用，而这个数字还在不断增加。我每天都在和创始人进行交流，而我知道他们拥有适合自己的金融平台是多么重要。Brexit 提供了快速获得高质量商业账户的途径，您可以在这里安全地存储和转移现金，并获得高达 600 万美元的 FDIC 保障。

Paragraph 15: Lately, it's been all too clear how important that is. Plus, you get high-limited corporate cards, easy-espans tracking, and automated bill pay. To learn more about the all-in-one financial stack for startups, visit Brexit.com forward slash 20VC.
最近，这一点变得越来越重要。此外，您可以获得高限额的企业信用卡、易于扩展的跟踪和自动化账单支付。要了解更多关于初创企业的全方位金融技术堆栈，请访问Brexit.com/20VC。

Paragraph 16: That's B-R-E-X.com slash 20VC. As always, I so appreciate all your support. It really does mean the world to me and a calm-wage-breathing, an incredible set of episodes next week.
这是B-R-E-X.com/20VC。像往常一样，我非常感激你们的支持。这真的对我来说意义非凡，下周我们还将播出一系列令人难以置信的剧集。