Jerry Chen | The New Wave of Cloud Innovation
发布时间 2023-05-02 17:10:05 来源
Hi everyone, welcome to Gray Matter, the podcast from GrayLock where we share stories from company builders and business leaders. I'm Heather Mack, head of editorial at GrayLock. I'm joined today by Jerry Chen, who's a general partner here at GrayLock. Jerry works with starters building enterprise applications and infrastructure, particularly those purpose built for cloud-native ecosystems. Thanks for being here, Jerry.
大家好，欢迎来到GrayLock的播客Gray Matter，我们在这里分享企业创始人和商业领袖的故事。我是Heather Mack，GrayLock的编辑主管。今天我邀请到了Jerry Chen，他是GrayLock的一名常务合伙人。Jerry负责与初创企业合作，建立云本地生态系统特别设计的企业应用程序和基础设施。感谢你的到来，Jerry。
Hey, thanks for having me, Heather. Always fun, too. I chatted about cloud stuff. Always.
嘿，谢谢你邀请我来，Heather。也很有趣。我一直在聊云端的东西。一直都是这样。
Jerry's also the mastermind, if you will, behind GrayLock's Castles in the Cloud project, which is an interactive database that maps activity in the venture capital funding startup ecosystem without the big three cloud providers.
Jerry 也是灰锁公司云端城堡项目的首席策划，这个项目是一个交互式数据库，用于绘制创业投资生态系统中未使用三大云服务提供商的活动。
Jerry and fellow GrayLock investor Jason Reese just completed our analysis of the 2022 fundraising landscape. Then they spent the first few months of 2023 looking at a few trends and comparing them with what's playing out in the market right now. You can read Jason's essay on the findings on the content section of our website and you can see the full castles in the cloud project, the latest figures at GrayLock.com slash castles. Both of those are linked in the show notes.
Jerry和GrayLock的投资者Jason Reese刚刚完成了对2022年筹款市场的分析。接着，他们花费了2023年的前几个月，研究了一些趋势，并将其与目前市场上的情况进行了比较。您可以在我们网站的内容部分阅读Jason的研究结果，并可以在GrayLock.com/castles上查看完整的云城堡项目最新数据。这两个链接均在节目注释中提供。
So Jerry, let's talk about what's happening. Top line, what are the funding figures tell you?
杰瑞，让我们谈谈发生了什么。首先，这些资金数字告诉你什么？
Well, first, I don't know if I've ever been called a mastermind, at least not since my last art heist, but take what I can get, Heather. It's interesting, but remember, these numbers are about 222 trends and Jason I and his blog and in this podcast, we'll talk about what we're seeing since the end of 22, but in 2022, we saw about 17, half billion dollars invested across a little bit over 400 companies.
首先，我不知道我是否曾被称为天才，至少不是在我上一次艺术窃贼之后。但是，我很高兴，Heather。这很有趣，但是要记住，这些数字涉及到222种趋势、Jason I及其博客，以及在这个播客中，我们会谈论自2022年以来所看到的情况。在2022年，我们看到有超过400家公司获得了大约170亿美元的投资。
Now, to put that in context, that's a huge drop from 2021. So remember, 2021 was probably the peak of the pandemic years when we saw over $50 billion of VC financing. So 50 to 17 or 50 to 18, which is a huge drop. But to put in broader context, 17, half billion is kind of consistent with the 2020 cloud funding number, which are about 15 billion. So 15 billion invested in 2020, a huge spike or peak in 2021, a 50 billion. And in 2022, you say 17, half billion is returning more towards kind of normalize VC investment in the cloud. Right. So it's kind of to be expected.
现在，让我们把这个数据放在背景下来看，与2021年相比，它有了大大的下降。因为我们在2021年看到了超过500亿美元的风险投资，那可能是疫情年份的顶峰。所以从50亿到17亿或18亿，这是一个很大的下降。但是，从更宽广的角度来看，17.5亿美元差不多与2020年云基金数字的相符，约为150亿美元。因此，在2020年有150亿美元的投资，在2021年出现了一个巨大的峰值，达到了500亿美元。2022年，你说17.5亿美元的投资正回到云计算投资的正常水平。那么，这是可以预料的。
And do those lower figures translate to lower activity across the cloud ecosystem?
这些低数字是否意味着云生态系统中的较低活动水平？
Not really. I think it's a combination that the bigger late stage checks or bigger late stage investments really have gone away. Right. So it's a because of the macro economy and the public markets, those big dollar amounts have slowed down. But the smaller early seed series A checks are as busy as ever. So I would say back half of 2022, the first quarter of 2023, graylock and a bunch of repairs, I think are as busy as ever looking at a cloud companies and other startups. And we'll talk about some of those trends. But I would say there's a lot of interesting things happening.
并不完全是这样。我认为，这主要是因为宏观经济和公共市场的原因，导致大额的后期融资或投资已经减少。但早期种子轮和A轮的小额支票仍然和以往一样繁忙。所以我认为，在2022年下半年和2023年第一季度，Graylock和其他一些机构仍然像以往一样繁忙地关注着云计算公司和其他创业公司。我们将探讨一些趋势，但我想说的是，目前有很多有趣的事情正在发生。
So the checks are smaller, which would be indicative of kind of a sea change, a lot more early early stage companies, but the number has increased dramatically. Right.
因此，这些支票的金额更小，这表明了一种海变的趋势，有更多的早期初创公司，但数量大幅增加。对的。
And what's fueling all that?
这一切是由什么推动的？意思是问这种情况的推动因素是什么。
Well, I think there's this thing you probably heard of called AI, our large language models in general, yeah, just a little bit of two vowels and a couple constants, AI and LLM, sort of, a, I mean, it's easy to say it's all caused by AI, but we'll talk about that. We'll talk about other trends, but I think it's simplistic to say it's just all AI. But it would say the past couple of years, probably Erison's Google published the attention is all you need paper. This whole concept of the transform models have created a sea change of or in the industry by this huge advantage, these large language models or foundation models. So we're seeing a foundation models appear and that's like open a eyes, chat GBT. There's a bunch of startups like inflection, anthropic, adept all building foundation models. Google and the big clouds have their own foundation models. Google releases barred their kind of version of chat GBT.
我认为你可能听说过AI，以及我们的大型语言模型（LLM），它们仅仅是一些元音和辅音的组合，AI和LLM。虽然AI可以解释一些事情，但我认为说所有的事情都是由AI引起的是过于简单化的。然而，近几年来，Google发布了“注意力机制”的论文，引发了“转换模型”的概念，这种模型为LLM打下了坚实的基础。现在，我们看到了很多基础模型的出现，如OpenAI的ChatGPT等。许多创业公司如inflection、anthropic和adept都在建立基础模型。Google和其他大云服务提供商也拥有自己的基础模型。Google发布了类似ChatGPT的版本。
So you will see there's a huge step function advancement in these foundation models, which leads to a downstream effect of thousands of thousands of startups building on top of these foundation models or exploring all the changes caused by foundation models, everything from management, security, explainability. So I think we're seeing kind of this bow wave of innovation right now and it's pretty exciting.
所以你会发现这些基础模型有了巨大的跃进，这导致了成千上万的初创企业在这些基础模型之上构建或探索因基础模型引起的所有变化，从管理、安全、可解释性等方面。因此，我认为我们目前正在看到一波创新的浪潮，这是非常令人兴奋的。
Break that down a little bit more. So it's happening both within the startup ecosystem and within the big three Amazon Google and Microsoft.
请再详细解释一下。这种情况正在创业生态系统内和亚马逊、谷歌和微软这三大巨头内部都出现。
Actually, it's pretty interesting because you see the big three players big cloud, we call it Amazon, Google, Microsoft, all fighting about AI now. I mean, if you look historically, it castles in the cloud, machine learning AI was always the largest funded category, both by VCs and the large number of cloud services offered by the big three.
实际上，这很有趣，因为你可以看到云计算三巨头——我们称之为亚马逊、谷歌和微软，现在都在争夺人工智能方面的市场份额。如果你回顾历史，云计算、机器学习和人工智能一直是投资最多的领域，不仅受到风险投资公司的大量投资，还受到三大云服务提供商的支持。
So AI machine learning has been the forefront of the background between the big three, but also you see competition between startups that are kind of either playing between these giants or enabling these giants are right in the wave. So you can argue that Amazon was early on the machine learning AI wave with salesmaker, but then Microsoft clearly with a part of the open AI really has disrupted both Google in terms of search as well as Amazon as a cloud platform with this tight coupling of Azure plus open AI.
AI机器学习一直是大三之间的前沿，同时你也可以看到一些初创公司在这些巨头之间来回玩耍，或者是在这股浪潮中加入这些巨头。可以说Amazon早在Salesmaker机器学习AI浪潮方面走在了前面，但是微软在开放AI领域具有明显优势，在搜索和亚马逊的云平台方面都颠覆了谷歌，通过Azure和开放AI的紧密耦合。
So I think super interesting what's going on there. And you saw recently in early 2023, Amazon just released something called bedrock, right? It's kind of it's really to connect to different foundation models from a theropik, etc. So Amazon tried to marketize access to these foundation models like it did to different cloud services. So it's a the battle between all three of these players is super interesting.
我觉得那里正在发生的事情非常有趣。你最近看到了吗？早在2023年初，亚马逊刚刚发布了一种叫做Bedrock的东西，对吧？它的作用是将不同的基础模型与热带等进行连接。因此，亚马逊试图像它对不同的云服务那样市场化地访问这些基础模型。所以，这三个参与者之间的竞争非常有趣。
You know, Microsoft kind of did the parts of open AI, Google responded with Bard and then Amazon trying to play, hey, you come to Amazon for all things developer experience, come to Amazon for all things AI experience, right? But I'd say it's interesting. The big three are probably once a follow, but I would say recently we've heard a lot more about Oracle clouds, the OCI, both as a cloud platform like large startups like Uber, etc.
你知道吗，微软在开放式人工智能方面做了一些工作，谷歌回应了Bard，然后亚马逊也试图玩这个，嘿，你来到亚马逊体验所有开发者体验，来到亚马逊体验所有人工智能体验，对吧？但我认为这很有趣。这三个大家伙可能曾经是一家人，但我认为最近我们听到了更多关于Oracle云的事情，OCI，不仅仅是作为一家云平台，还有像优步等大型初创公司。
We're doing some capacity on Oracle. But in terms of training large language models, I hear from a lot of founders and engineers of OCI's actually a pretty amazing cloud to train these large models on.
我们正在对 Oracle 进行一些能力的测试。但就大型语言模型的培训而言，我从 OCI 的创始人和工程师那里听说，实际上是一个非常棒的云平台，可以用来训练这些大模型。
And then I would say the stock that I think we all wish we bought, you know, five years ago was Nvidia, right? These between the crypto boon a few years ago and the AI boom, the need for GPUs kind of drive all the training of these large models has never been greater. So it's a top of just the hardware, Nvidia's released their own cloud, DGX, they released more software on top of their own hardware.
然后我想说的是，我们都希望在五年前购买了Nvidia的股票，对吧？这几年来，由于加密货币的繁荣和人工智能的兴起，需要使用图形处理器（GPU）来训练大型模型的需求变得越来越大。因此，仅仅靠硬件本身，Nvidia还发布了自己的云平台DGX，并在其自有硬件之上发布了更多软件。
So I would say there are the big three Oracle making some headways into the cloud space both in just cloud platform as well as around AI. And then key parts of the ecosystem like Nvidia really kind of creating a beach headed and they're a part of every conversation right now.
因此，我可以说有三大巨头，Oracle正在云平台方面取得一些进展，同时也在AI领域大有作为。而像Nvidia这样的重要生态系统部分正在建立起一片领地，并且他们正在每一次的谈话中都扮演着重要角色。
We're talking about AI exists in multiple layers, kind of like the cloud. And so there's these different places for startups to play in like where are you seeing this happening on a startup level? But you know at the gray lock, you love layers and frameworks, obviously.
我们在谈论人工智能存在于多个层面，有点像云。因此，有不同的创业公司可以参与的领域，你在哪些地方看到它正在发生？但是，在灰色锁公司，你喜欢层次和框架显然。
But simplify down because this is a very complicated and evolving stack. We're looking at what we believe a new application stack evolving.
但是要简化一下，因为这是一个非常复杂而不断发展的技术堆栈。我们正在研究我们认为是新兴的应用程序技术堆栈。
So gosh, how there are 30 years ago, almost we had the lamp stack was Linux Apache, my SQL PTP. That was kind of the default set of tools you built any web app. And then you had kind of the mean stack with Mongo, no JS, Angular JS, kind of these modern webb mobile apps. We had jam stack the past few years, kind of the nullify or sell kind of these JavaScript applications.
哇，回想在30年前，我们使用的几乎所有web应用的默认工具是Linux Apache, my SQL PTP。然后，就有了Mongo, Node JS, Angular JS等现代web和移动应用的MEAN stack。在过去的几年里，我们又出现了JAM stack，使用nullify或者sell等JavaScript应用程序。
I don't know what it's going to look like going forward. But for sure, we're seeing evolving stack or application architecture around these large Linux models apps out there. And so we're super excited about how this develops. But for sure, there's one layer that is the foundation models.
我不知道它将来会是什么样子。但是可以确定的是，我们正在看到围绕这些大型Linux模型应用程序的演变堆栈或应用程序架构。因此，我们非常兴奋地看待这一发展。但是可以确定的是，其中有一层是基础模型。
And AI, coherent and throttpix, stability AI, companies out there like adept and inflection I play in that space. But for sure, you can see startups and big companies play in the kind of the low level. We're going to see the top level application innovation. So Jasper, even up in legal, tome in presentations, Harvey and legal AI applications.
人工智能、连贯和稳定的AI，像Adept和Inflection这样的公司在这个领域扮演了重要角色。但肯定有一些初创公司和大公司在低级别领域打磨技术。我们将会看到最高级别的应用创新。比如Jasper等律师领域、演示文稿中的应用，Harvey和法律领域的AI应用。
Just so many companies out there taking advantage of these, you know, advances in AI to build applications, close to the gray lock portfolio is something called insubes that started document understanding and AI around there. They're really expanding on top of these foundation models.
目前有很多公司正在利用人工智能的进展来开发应用程序，与灰麒麟投资组合密切相关的一个名为insubes的公司开始应用文档理解和人工智能技术。他们正在基于这些基础模型进行扩展。
But this middle layer in between is kind of an evolving middleware stack. So we're seeing companies and technology like Lama index. That's really defining the category for data ingestion, data indexing for data querying.
但是这个中间层是一个不断发展的中间件堆栈。所以我们看到了像Lama Index这样的公司和技术，它真正定义了数据摄入、数据索引和数据查询的类别。
It's like this memory data layer around these AI apps because these these large Linux model apps need some level of data integration and memory.
就像这些AI应用程序周围的记忆数据层一样，因为这些大型Linux模型应用程序需要一定程度的数据集成和内存。简而言之，AI应用程序需要记忆数据层来存储和处理数据来进行计算。
You have technology like Lange chain and Fixie that are really pioneering how you think about building agents doing prop development and prop operations. And then vector databases, right? Vector databases have been around for a long time. But also the idea of storing and querying these vector embeddings is becoming a key piece of all these applications. So you're seeing comes like Pinecon, Weavey, Chroma, all kind of take hold in terms of this kind of embedding stores. And then when you have a new stack, right? Just like when you build mobile apps or cloud apps, you break a bunch of things, you got to fix these things, you got to monitor these things. We're seeing starts like Helicone and Honeyhive around LM monitoring, right? And it's thing there'd be there'd be more monitoring tools, security tools, management tools kind of all around this new application stack. So look, if we had kind of a lamp stack years and years ago, I don't know what the stack looks like next three or four years, but we're seeing evolving, you know, set up best practices and how to build these applications. Got it. That's a lot to keep track of.
你们拥有像Lange链和Fixie这样的技术，它们正在开创建立代理人进行属性开发和属性运营的思维方式。然后是向量数据库，对吧？向量数据库已经存在很长时间了。但是存储和查询这些向量嵌入的想法也正在成为所有这些应用程序的关键部分。因此，你会看到类似于Pinecon、Weavey和Chroma这样的嵌入式存储正在成为主流。当你拥有新的堆栈时，就像构建移动应用程序或云应用程序一样，你需要解决一堆问题，要修复这些问题，要监控这些问题。我们看到像Helicone和Honeyhive这样的LM监控起步，对吧？这意味着会有更多的监控工具、安全工具、管理工具等等，围绕这个新的应用程序堆栈展开。所以，看吧，如果几年前我们有一个lamp堆栈，我不知道下三四年堆栈看起来像什么，但是我们正在看到一个演变，建立这些应用程序的最佳实践。明白了。这是很多需要跟踪的东西。
And then outside of AI, there's some other things that are fueling more of these trends. What are you seeing? For sure Heather, we're seeing a lot of more innovation, but let's just take a step back and we're still in the early early innings of cloud migration and companies going cloud data, right? So for us in my scene like cloud has been around for the beginning since like pretty much all the founders we deal with are born in the cloud and known as been building their own data centers for years, but just remember in terms of the total compute storage application used out there, were still early, early days cloud.
除了人工智能以外，还有一些其他因素推动更多这些趋势。您看到了什么？当然，希瑟，我们看到了更多的创新，但让我们退一步，我们仍然处于云迁移的早期，公司正在进行云数据转换，对吧？所以对于我们来说，像云这样的看起来是从一开始就存在的东西，因为我们处理的所有创始人几乎都是在云中出生并建立了自己的数据中心，但请记住，就总的计算存储应用程序使用量而言，我们仍然处于云的早期阶段。
But within cloud development, we're seeing a lot more evolution and specialization and we're calling industry clouds or vertical clouds. So you're seeing different industries from healthcare, government, transportation. They have either a their own needs, right? Like application needs or they have their own kind of compliance, security needs or data sharing needs. So you think about vertical SaaS companies around healthcare, government or solution products around productivity around developer tools around security. So you can see some specialization and what's happening is is both the needs are evolving and how to build these applications. But also the cloud providers themselves can now cost effectively build specialized services around these different verticals, different industries. And so Jason, who's one of the Vesar teams wrote a lot about industry clouds and how they're evolving as well on our blogs and podcasts. So it's super interesting to see how this is going to be probably the next evolution of cloud is these verticals and these specializations.
在云开发领域中，我们看到了更多的演进和专业化，这就是所谓的行业云或垂直云。因此，您可以看到不同的行业，例如医疗保健、政府、交通等等，它们都有自己的需求，例如应用需求、合规和安全需求以及数据共享需求。因此，您可以想象到围绕医疗保健、政府、开发人员工具和安全的垂直SaaS公司或解决方案产品。因此，您可以看到一些专业化，正在发生的是这些应用程序如何发展的需求。而且，云提供商现在可以以成本效益的方式构建围绕不同行业的专业化服务。所以，我们的Vesar团队之一Jason在博客和播客中详细介绍了行业云及其演变。因此，看到这些垂直和专业化可能会成为云的下一个演变非常有趣。
Right, specialization sounds like a good place for startups. It's a great place for startups, right? If you think about how you build sustainable modes, for example, and defend against your competitors, is you have to either a own kind of a domain or you have to own a set of data, this proprietary. So I think different verticals are different solutions and a vertical could be like a market like healthcare, government or financial services or it could be a vertical solution like around CRM, customer support or BTC support or only one problem. So the own a data set or one workflow around an industry or one problem, you can actually kind of build an end to end solution and in the cloud that becomes a very viable, very attractive business model. And sometimes it's getting more complex, more security needs. Obviously, it's like an ongoing trend we see across every industry.
专业化听起来像是创业公司的好去处。是的，对于创业公司来说，这是一个很棒的地方。如果你考虑如何建立可持续的模式，并防范竞争对手，你就必须拥有一种领域或一组专有数据。因此，我认为不同的垂直领域需要不同的解决方案，一个垂直领域可能是一个市场，比如医疗、政府或金融服务，或者可能是一个垂直解决方案，比如围绕CRM、客户支持或BTC支持的解决方案，或者仅仅是解决一个问题。因为拥有一个数据集或一个工作流程，围绕一个行业或一个问题，你实际上可以构建一个端到端的解决方案，在云中这成为一个非常可行、非常具有吸引力的商业模式。有时，这变得更加复杂，安全性需求也越来越高。显然，这是我们在每个行业看到的一个持续趋势。
So what does that mean for a cloud? What security is great is, is it evergreen market? Like I said before, typically what happens when you have a new technology, a new platform like moving to mobile, moving to cloud. First thing first is you enable new applications to be built, but also you break a bunch of stuff, right? And so cloud really enabled a bunch of new stuff, but a broke a bunch of stuff. And the first thing you try to do is try to fix what's broken with the tools you have. Security is an evergreen need because when you go cloud, you create a bunch of new security vulnerabilities or security needs. First thing you do is try to fix these security needs with existing security tools, but largely when we see these platform shifts like going cloud, the old stuff you have, especially when security isn't good enough and you see this explosion in these security companies.
那么对于云计算意味着什么呢？优秀的安全性是否是一个长盛不衰的市场？就像我之前说的，通常当您拥有一种新技术、一种新平台，比如转向移动、转向云，首要的是让新应用程序得到开发，但同时也会破坏一些东西，对吧？因此，云计算真正实现了许多新功能，但同时也破坏了许多功能。您首先要尝试做的是尽可能地利用现有工具修复破裂的功能。安全性是一项长期需要，因为当您转向云计算时，会产生许多新的安全漏洞或安全需求。首先要做的就是使用现有的安全工具来修复这些安全需求，但是通常当我们看到这些平台转变，比如转向云计算时，您拥有的旧东西，尤其是安全性不够好的东西，就会看到这些安全公司的爆炸增长。
So last year we saw that over $3 billion from vested into security startups in the cloud. So they put over $3 billion into the security subsector, which is huge, but that's only half what they put in 2021. So that's a huge number, but they put between the last two, three years, north of over $10 billion in security startups because that is going to be an evergreen need as you go cloud, as you build AI to applications, as you go to different verticals, you're going to need to build these security solutions.
去年我们看到，超过30亿美元被投入云安全初创公司。这意味着他们投入了超过30亿美元用于安全子领域，这是一个巨大的数字，但是与2021年相比，仅相当于一半。过去两三年，他们将超过100亿美元投入了安全初创企业，因为云计算、人工智能应用程序和不同的垂直领域需要构建这些安全解决方案，所以这将是一个永恒的需求。
So should startups just always expect that enterprise organizations are going to have limitless budgets for security. It's always going to be something they're going to invest in and these are just ample opportunity for everybody. I would say it's not ample opportunity for everybody because a lot of great markets, there's always replacing the old stuff. So there's definitely security budget because security and compliance is a top three priority for every CEO is a top three priority for every public company board, and you're going to see dollar shift from old technology and platforms and new ones.
那么，初创企业应该总是期望企业组织拥有无限的安全预算吗？这总是他们要投资的方面，对于所有人来说都是充足的机会。我认为这并不是所有人都有充足的机会，因为很多伟大的市场总是在替换旧的东西。所以，肯定会有安全预算，因为安全和合规是每位首席执行官的头三大优先事项，也是每个上市公司董事会的头三大优先事项。你会看到资金从旧的技术和平台转向新的技术和平台。
So you see companies like the cloud security vendors like Wiz growing faster in security companies seen a long time. Companies like an art portfolio like abnormal around email security that's growing super fast as you think about how email and identity changes when you go to the cloud. There's a whole bunch of other companies that were seeing around AI security that are kind of being born in the cloud now born in this AI generation.
所以，你会发现像Wiz这样的云安全供应商在安全公司中增长得更快，这是很长时间以来的趋势。像abnormal这样的邮件安全艺术品公司也在以惊人的速度增长，因为当你进入云时，邮件和身份发生了变化。我们还发现了一大批AI安全公司在云中诞生，这是在这个AI时代诞生的。
Increasingly as you build more and more application in the cloud, you carry about what we call S bomb, your software bill materials, story, more than gradients, where the open source project is actually built your application out of to try and understand the proveness of all this code. So I think it's exciting for me as an investor because we see huge opportunity, but because there's new challenges. And also the old technology, the old companies often cannot make that transition.
随着您在云中构建越来越多的应用程序，您所关注的逐渐渐变为我们所说的“S炸弹”，即您的软件账单材料、故事和更多梯度，其中开源项目实际上是构建您的应用程序以尝试理解所有这些代码的可证明性。因此，作为一名投资者，我认为这令人兴奋，因为我们看到了巨大的机会，但也面临新的挑战。此外，旧技术、旧公司通常无法完成这种转变。
So it's a really attractive area for great founders to have some deep IP to attack. And I think securities one that we're constantly looking at because we think there's always going to be innovation. And so what are you expecting throughout the next year like a generative AI to build its own cloud and then its own security company? So yeah, if the AI companies could build their own stuff and we're kind of getting there with projects like like AGI and Auto GBT, right, kind of this AI building AI or their coding themselves and proving themselves, I think we're still luckily for me.
这是非常吸引杰出创始人攻击深度知识产权的地区。我认为证券是我们不断关注的领域，因为我们认为创新总是不断的。你预计在接下来的一年中会出现什么样的生成AI来建立自己的云和安全公司？如果AI公司能够建立自己的东西，我们实际上正在通过像AGI和Auto GBT这样的项目，即AI构建AI或他们自己编码并证明自己，来到达这个目标。对我来说，我觉得我们还很幸运。
I saw a job because we're still a little bit away from that. But we're definitely seeing advances around developer productivity, right? So some of these AI things can make your developers more productive. So you're going to see actually an interesting phenomenon where startups can actually probably develop farther and faster on the funding they have in different markets.
我看到了一份工作，因为我们距离那还有一段距离。但是我们绝对可以看到开发者生产力方面的进步，对吗？因此，一些人工智能技术可以提高开发者的生产力。因此，你将会看到一个有趣的现象，即在不同市场上，初创企业可以用他们拥有的资金更快地更远地发展。
So one, exciting two, we're still in a business investing because we still need to pick the best founders, the best opportunities in front of us. But I think we're excited because I think 2021 is all huge spike in venture investing. 2022 kind of a lower level but returned to kind of normal levels historically. And I think 2023, we're probably about the same pace as 2022. I mean, check back with me in a year, Heather will you do the cast on the cloud looking back in 2023. But so far, I think 2023 will probably be close to where we were last year.
首先，我们依然在进行商业投资，因为我们需要挑选最优秀的创始人和最好的机遇。但是我认为我们感到兴奋，因为我认为2021年风险投资将有巨大的增长。2022年可能会稍微降低，但是历史上会恢复到正常水平。我认为到了2023年，我们的速度可能和2022年差不多。明年再回来看看，Heather，你能回顾一下2023年的情况吗？但目前为止，我认为2023年可能会接近去年的水平。
But we're going to see a bunch of new companies be the activity we're seeing just in the first three, four months of this year around the AI stuff, around security companies, around some of these vertical clouds has been pretty interesting. So we're super busy, I know my peers and other firms are super busy. And so I think it'll be fun to see kind of how those bubbles on our castle cloud chart have changed.
但是，我们将看到一大批新公司在人工智能、安全公司以及一些垂直云领域的活动方面展现出来，我们在今年头3、4个月看到的这种活动非常有趣。因此，我们非常忙碌，我知道我的同行和其他公司也非常忙碌。因此，我认为看到我们的城堡云图表中的气泡如何变化将是有趣的。
I mean, my early prediction is the AI and the one is still going to be the biggest circle on our two by two. For those listening, check out Castle and the cloud on gray lock. We have kind of a great visualization of where the money is going to. So I think security and AI will still be to the biggest bubbles. I think you can see a lot of activity at the seed and series a activity level for all the V season startups.
我的预测是，人工智能和云计算仍将成为我们的二次创业圈中最大的领域。对于在听的人们，请去Graylock的Castle和Cloud了解一下资金流向的清晰可见图。因此，我认为安全和人工智能仍将是最大的创业领域。在所有V季初创公司的种子轮和A轮阶段，您都可以看到很多活动。
And then you're going to see a lot more coming from the big three, right? I think Google, Amazon, Microsoft are going to double trouble down on their efforts in AI. Google for example, it's reorganized or Google brain in their deep mind research teams to one org. So you can see, I think those big players come out. I think you haven't heard a lot yet from other companies like an Apple or a Facebook meta or Salesforce, which has their Einstein team.
然后你将会看到来自三大巨头的更多内容，对吧？ 我认为谷歌、亚马逊和微软将会加倍努力在人工智能方面。比如说，谷歌已经将他们的Google Brain和DeepMind研究团队整合成了一个组织。因此，我们可以看到这些大公司在人工智能领域发挥出更强的影响力。我认为，像苹果、Facebook Meta或Salesforce的爱因斯坦团队这些其他公司，你还没有听到他们的很多声音。
So I think a lot of tensions around open AI around Google. But I think there are a whole bunch of other large companies out there that have great, great resources around AI that will be making big moves this year. That's awesome to call as waves. But on those waves will be great momentum for these startups to serve.
我觉得谷歌周围的开放人工智能产生了很多紧张情绪。但是我认为还有很多其他大公司拥有丰富的人工智能资源，他们将在今年推出重大举措。这就像是在喊着“浪来了”，而这些初创公司将乘着这些浪潮获得巨大的推动力。
You know, as we're talking, obviously, this is all a reminder of your very popular essay, the new moats from a few years back in that essay. In that essay, you talked about why systems of intelligence are the next offensive business model. You made pretty prescient observations at the time, was it six years ago, which is like a million years ago in technology. But you said startups using AI would be the ones to build the next business vote.
你知道的，当我们谈论这些时，很明显，这都是你发布数年前非常受欢迎的文章《新的护城河》的提示。在那篇文章中，你谈到为什么智能系统是下一代的攻势商业模式。当时你做出了非常准确的判断，那时是六年前，时间在技术领域看来仿佛过去了数百年。但你说，使用人工智能的初创公司将是建立下一个商业竞争壁垒的人。
It all seems to be coming true with the developments in the past year. I'd love to hear if you're going to dive into that further.
在过去的一年里，所有的一切似乎都在变得真实起来。我很想知道你是否会进一步深入探讨这个问题。
Yeah, I think six years is two lifetimes in technology. But for sure, I was talking to you a few other day about what we got right with the new moats and what we got wrong with the new moats and how we have this framework of the system of record, which is your big ERP CRM. So you had a system engagement, which is like your user experience chat or browser or the mobile app store and had what we call system intelligence using AI to power these applications.
是的，我认为在技术行业，六年就相当于两个生命周期。但我跟你在前几天聊天时，确实谈到了我们对新壕堑的正确和错误之处，以及我们有一个框架叫作系统记录，对于你们大型企业资源规划（ERP）和客户关系管理（CRM）来说，这是非常关键的。所以，你们有一个系统参与，类似于用户体验的聊天框或浏览器或移动应用商店，并且我们使用人工智能来支持这些应用程序，从而实现系统智能。
But I think it's worth revisiting. We got a lot right. Think about this business models. I think you're seeing a bunch of new companies building system intelligence. We obviously got a lot wrong in terms of who would have predicted these large foundation models, who would have predicted chat GBT as the system engagement, for example. We mentioned chat slack as a system engagement for some applications. But now chat GBT really made a legitimate system engagement for your data interactions. And that plus these plugins that OpenEyes releasing have really created a new kind of stack for applications.
我认为重新审视这个问题很值得。我们做得很好，特别是在商业模式方面。我认为你会看到许多新公司正在构建系统智能。但是在预测这些大型基础模型和系统参与方式上，我们还是做错了很多。例如，谁会预测到聊天GBT会成为系统参与方式？我们曾经提到，聊天slack可以成为某些应用程序的系统参与方式。但是现在，聊天GBT真正成为了您的数据交互的合法系统参与方式。加上OpenEyes发布的这些插件，真的为应用程序创建了一种全新的技术堆栈。
So I think it's probably worth while rethinking what we got right and wrong. But I still believe system intelligence, these AI powered applications really are core to building what we call the new moats.
因此，我认为重新考虑我们所做的正确与错误是值得的。但我仍然相信，系统智能，即由人工智能驱动的应用程序，是构建我们所谓的新筑垒核心所必需的。
Very cool. Well, I'm excited to hear the next wave of the new new moats. So I look forward to that. Jerry, thanks so much for being here with me today. And again, for our listeners, if you want to visit our castles in the cloud projects at relog.com slash castles, Jerry, thanks so much. Thanks a lot, Heather.
非常酷。我很期待听到新的新雄堡的下一波。因此我非常期待。杰里，非常感谢你今天在这里和我一起。再次感谢我们的听众，如果你想访问我们在云端的城堡项目，请访问relog.com/castles。杰里，非常感谢。非常感谢，希瑟。