Cognex：视觉探索——[商业剖析，重播]

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Portrait was built by former buy side investors, and they understand great investing isn't just about having more information from low quality sources.

关键在于以正确的方式组织正确的信息。

It's about having the right information organized the right way.

如果你听这个节目，你会明白尽职调查包含很多方面。

And if you listen to the show, you appreciate diligence consists of many things.

深入研究企业的历史，梳理细微的竞争动态，跟踪围绕你投资主题的关键指标。

Diving into the history of a business, framing the nuance competitive dynamics, tracking key signposts around your thesis.

而过去，这会占用你大量宝贵的时间。

And historically, that would take up material time that you do not have.

但Portrait基本上就像给你的团队增加了一支分析师大军。

But Portrait is basically like adding an army of analysts to your team.

它由专为投资研究工作流程设计的人工智能系统驱动。

It's powered by an AI system specifically designed for investment research workflows.

这样你就能获得细致的投资想法。

So you get nuanced idea generation.

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Portrait also customizes research report generation.

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And third, there's intelligent thesis monitoring, and that's where Portrait assesses thousands of data points across value chains each day, extracting the insights, driving the business.

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Again, all this work would typically take hours and hours and hours.

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It's at your fingertips now.

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我是Matt Russell。

This is Matt Russell.

这周我们还有一个重播，之后就会恢复正常节目。

We have another replay this week before we get back to regularly scheduled programming.

这一期是关于康耐视的。

And this one is on Cognex.

我记得和Brett Larson一起做这期节目时，结束后我就在想，这就是我想关注的人工智能和机器人故事，因为康耐视在机器视觉和所有与机器学习相关的算法工具方面，位置非常独特。

And I remember doing this episode with Brett Larson and leaving thinking to myself, this is the AI and robotics story that I want to monitor because Cognex has such an interesting position with machine vision, all of the algorithmic tools associated with machine learning.

自从这期节目发布以来，公司在多个不同场合谈到了他们利用人工智能扩大客户群、引入新用例所取得的进展，尤其是在物理AI方面。

Since this episode's been released, the company has talked in several different events about some of the progress that they've seen using AI to expand their customer base, introduce new use cases, particularly with physical AI.

所以这只是康耐视更宏大故事的一部分。

So it's only one piece of the broader Cognex story.

显然，这个业务涉及的内容远不止这些，包括各种终端市场和他们的天然客户群，但考虑到当前市场状况，特别是2026年，以及大家对AI在机器人领域应用的关注，我们想重播这一期。

Obviously there's much more that goes into this business with all of the different end markets and who their natural customer base is, but wanted to replay this one given where we are in the market, particularly in 2026 and so much focus on applying AI into the robotic space.

希望你们喜欢。

I hope you enjoy.

投资者和经营者们深入探讨一家企业。

With investors and operators diving deep into a single business.

对于每家企业，我们会探讨它的历史、商业模式、竞争优势，以及它运转的核心动力。

For each business, we explore its history, its business model, its competitive advantages, and what makes it tick.

我们相信每家企业都有值得投资者和经营者学习的经验与秘密，我们在这里为你呈现这些内容。

We believe every business has lessons and secrets that investors and operators can learn from, and we are here to bring them to you.

想收听更多《Business Breakdowns》的节目，请访问 colossus.com。

To find more episodes of breakdowns, check out colossus.com.

主持人和嘉宾在节目中表达的所有观点仅代表他们个人意见。

All opinions expressed by hosts and podcast guests are solely their own opinions.

主持人、嘉宾、他们的雇主或关联方可能持有本播客中讨论的证券头寸。

Hosts, podcast guests, their employers, or affiliates may maintain positions in the securities discussed in this podcast.

本播客仅供参考，不应作为投资决策的依据。

This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions.

今天，我们来深入分析机器视觉领域的领导者康耐视。

Today, we are breaking down machine vision leader Cognex.

今天的嘉宾是来自 NZS Capital 的 Brett Larson，他再次来到《Business Breakdowns》节目。

Our guest today is Brett Larson from NZS Capital, and Brett returns to Business Breakdowns.

去年我们聊过特灵科技，今天布雷特通过康耐视给我们带来了工业经济的另一个视角。

We covered Trane Technologies last year, and Brett gives us a different angle on the industrial economy with Cognex today.

我们深入探讨了机器视觉的历史，以及康耐视如何成为工厂领域的重要参与者。

We get into the history of machine vision and how Cognex is a factory player.

但我特别喜欢这次讨论中的战略角度。

But I particularly enjoyed the strategic angles of this discussion.

康耐视不是那种典型的经常性收入故事。

Cognex is not your typical reoccurring revenue story.

他们自称是周期性企业，长期以来一直专注于特定的客户群体，寻找可能触发下一轮增长期的S曲线。

They are a self proclaimed cyclical that has tended to focus on a specific customer segment over time, looking for s curves that might trigger their next growth era.

这个情况正在演变，我们在这次讨论中和布雷特深入聊了很多这方面内容。

This is evolving, and we get into a lot of that with Brett in this discussion.

我提到过，知名企业往往吸引最广泛的听众，但这些才是我最喜欢的节目。

I'd mentioned the big name businesses tend to attract the widest audience, but these are my favorite episodes.

所以请享受这期关于康耐视的商业解析。

So please enjoy this business breakdown on Cognex.

好的，Brett。

Alright, Brett.

很高兴你能再次来。

It is great to have you back.

我们上次聊Trane大概是一年前，可能还更早一点，但那个节目我在过去几个月里经常提到，也一直会回去听。

It was about a year ago that we covered Train, maybe a little bit more than a year ago, but it's an episode that I referenced quite a bit over the past few months and one that I consistently go back to.

我希望今天聊Cognex也能有同样的效果。

I'm hoping that we get the same thing today with Cognex.

我之前对这个名字不太熟悉，但在研究过程中发现它很有意思，而且似乎没有引起太多关注或讨论。

It was a name that I wasn't familiar with, and it's a very interesting name that seems to not get a ton of attention or conversation going as I was doing my research.

最简单的开始方式就是介绍一下Cognex是谁，以及他们是做什么的。

Easiest place to start is just with an introduction to who Cognex is and what they do.

谢谢邀请我，Pat。

Thanks for having me, Pat.

上次很有趣，所以我很高兴能再次加入你。

It was fun, so I was excited to be able to join you again.

Cognex 代表的是认知专家，他们是机器视觉领域的领导者。

Cognex stands for Cognition Experts, and they are leaders in machine vision.

具体来说，他们销售带有嵌入式处理的加固相机，以及软件，这才是真正的增值部分，软件负责捕捉图像并进行分析，以便在制造和物流环境中高速自动化决策。

What that means specifically is they sell ruggedized cameras with embedded processing and then software, which is the real value add, which captures images and analyzes them in order to automate decisions at high speeds in manufacturing and logistics environments.

所以，产品看起来可能像两个手机叠在一起，带有 Cognex 黄色，就放在工厂车间里。

So, the product might look like two cell phones stacked together with the Cognex Yellow that sits right out there on the factory floor.

应用通常分为四类。

And the applications generally fall into four categories.

分别是引导、测量、检测和识别。

So, there's guide, gauge, inspect, and ID.

识别是 DataMan 产品系列，利用视觉读取条形码和进行光学字符识别，也就是读取印在或刻在物体上的字母和数字。

ID is the DataMan family of products, and that's using vision for reading barcodes and for optical character recognition, which is reading letters and numbers that are printed or etched on something.

最容易想象的例子是亚马逊的分拣设施，每天以极高的速度处理数万或数十万个包裹。

So, the easiest example to picture for somebody would be an Amazon sorting facility that's moving tens or hundreds of thousands of packages per day at extremely high speeds.

Cognex 的视觉产品扫描所有这些条形码，然后执行自动化操作，执行所需的动作。

And Cognex's vision products scan all those barcodes and then perform the automation, then performs the actions that are required.

Insight是另一个主要产品类别，涵盖引导、测量和检测。

Insight is the other main product category, and that covers guide, gauge, and inspect.

检测就是质量检测，用二维和三维视觉系统来检查产品。

Inspect would be quality inspection, so two d and three d vision systems that are used to inspect something.

一个常见的例子是印刷电路板。

A common example would be a printed circuit board.

系统会确保各种元件的数量、尺寸和位置正确，焊接质量也过关。

The system would make sure that it has the correct number, size, and placement of different components and quality soldering.

另一个经典例子是确保灌装线上的瓶子都有瓶盖和标签。

Another classic example would be making sure bottles in a bottling machine have the lids on and labels.

引导就是用视觉系统来引导机械臂，而测量则是测量物体的尺寸。

Guide would be vision systems, which are used to guide robotic arms, and then gauge would be measuring the dimensions of something.

最终，他们想提供的价值是提高质量、提升产量、降低成本、减少浪费，而且越来越常见的是解决劳动力短缺问题。

And, ultimately, you can think of the value prop that they're trying to deliver as improving quality, throughput, reducing costs and waste, and then a more and more common one is just addressing labor constraints.

这类产品的投资回报期通常很短。

And the payback period is usually quite quick for these types of products.

你提到了硬件部分，我能想象你们在传送带上安装这些摄像头。

You mentioned there's the hardware, which I can imagine you have these cameras on a conveyor belt.

软件方面，它们必须与你正在处理的东西连接起来。

The software aspect to them, they have to link into whatever you are working on.

在某种程度上，这种软件就是机器对机器的执行。

In some ways, that software is machine to machine execution.

是不是也有很多东西需要回到人类那里，或者需要人类与软件互动？

Is there a lot that's also going back to humans or human interaction with the software?

理想情况下，人类真正与软件互动的主要时间是在前期编程应用的时候。

Ideally, the only time the human's really interacting with the software primarily would be upfront when you're programming the application.

之后，摄像头就放在工厂车间里，捕捉数据、分析数据，然后这些数据会传送到罗克韦尔可能销售的可编程逻辑控制器，由它来执行需要完成的操作。

And then, after that, the camera is really sitting out on their factory floor, capturing the data, analyzing it, and then that data will be communicated to more like the programmable logic controller that Rockwell might sell, which is then performing whatever action needs to be done.

理想情况下，一旦部署到工厂车间，人类基本上就退出了操作环节，只需要监督就行。

Ideally, once it's out on the factory floor, the human's kind of out of the loop other than overseeing it.

我觉得你提到了一个很好的例子，就是亚马逊的分拣设施，现在那里有多少环节已经自动化了。

I think you brought up a great visual in terms of an Amazon sorting facility and how much of that is now automated.

现在不需要人工去搬大包裹或小包裹了。

You don't have the humans involved moving the big packages here, the smaller packages there.

所以技术已经进步了很多。

So it's gotten more advanced.

那现在机器视觉这个市场有多大呢？

But how big of a market is this machine vision world today?

我还挺好奇最近增长了多少，是不是有那种跳跃式的增长。

And I'd also just be curious how much that has grown recently, if there's been a step change in terms of the growth of the market.

关于机器视觉，市场上有各种不同的TAM估算，但康耐视并不是所有细分领域都参与的。

There's a lot of different TAM estimates out there for machine vision, but Cognex doesn't play in all the different niches within it that get captured usually.

康耐视最近估计其可服务市场为65亿美元，比2017年的29亿美元有所增长。

Cognex last estimated their serviceable addressable market at $6,500,000,000 which was up from $2,900,000,000 in 2017.

他们可能会在投资者日再次更新这个数字，根据他们进入的新产品类别，可能会达到80亿到90亿美元。

And they'll probably update their SAM again at their Investor Day, and it'll probably be something like 8,000,000,000 to $9,000,000,000 based on new product categories they've entered.

过去十年，这个行业大概以每年10%的复合增长率增长。

Industry's probably grown at a 10% type of CAGR the past decade.

当然，这里面肯定有周期波动，而且不同公司之间的表现也有差异，像Cognex就增长得比这个范围高，有些则低于这个水平。

And, obviously, there's cycles in there, and then there's dispersion between some that are growing above that range, like Cognex, and some that have been below.

我喜欢SAM这个术语。

I like the SAM terminology.

以后我可能得把TAM和SAM混着用了。

I might have to mix that in with Tam in the future.

在市场份额方面，Cognex在市场上排名如何？

Where does Cognex rank in terms of market share within the market?

他们的定位有什么特点？整个市场的情况又是怎样的？

What are some of the characteristics about their positioning and then just the market overall?

Cognex排在第二位，仅次于基恩士，那是一家日本公司。

Cognex is number two behind Keyence, which is a company based in Japan.

这两家公司显然有竞争，但有趣的是，它们历来侧重的领域略有不同。

The two companies do obviously compete, but they've also historically focused in slightly different areas, which is interesting.

Cognex历来专注于金字塔顶端，也就是那些客户技术能力很强的，通常他们会雇佣训练有素的工程师，与客户合作，为特定任务定制系统。

So Cognex, they historically have focused on the top of the pyramid when you think about the sophistication of the customer, typically, they're hiring very trained engineers who are working with customers to spec systems for specific tasks.

所以，这基本上是一种技术性更强的销售，客户非常专业，他们正在自动化非常复杂的任务。

So, it's a more technical sale with very sophisticated customers that are automating very complex tasks, basically.

他们不是靠价格取胜的。

They're not winning on price.

他们是机器视觉领域更昂贵的供应商。

They're a more expensive vendor of machine vision.

但他们以拥有非常优秀的应用工程师而闻名，他们能在规格层面提供最好的技术，从而脱颖而出。

But they have a reputation for having really good application engineers, the best tech that they can differentiate at the spec level.

比如，在物流设施中，假设你每天扫描10万个包裹，康耐视通常能提供比同行高出100个基点甚至两三百个基点的读取率。

So, for example, that logistics facility where, let's say, you're scanning 100,000 packages a day, Cognex usually can deliver read rates that are 100 basis points or even two or 300 basis points better than a peer.

所以，即使只算一天，也有成千上万的包裹不需要人工去查看。

So, over even just a day, that's thousands of packages that don't have to have a human there to look at something.

他们通常就是这样竞争的。

That's usually how they go about competing.

而且他们的品牌声誉也非常强。

And there's a really strong brand reputation as well.

所以，如果一家公司新来的首席运营官第一次走进工厂，看到黄色的康耐视摄像头，这对他们来说就说明了一些问题。

So, if a new COO of a company walks into a factory for the first time and sees the yellow Cognex cameras, that says something to them.

对于所有供应商来说，已安装的客户基础也非常稳固。

The installed base is very sticky as well for all of the vendors.

我先稍微透露一下，他们专注于金字塔的顶端。

I'll foreshadow a bit, but they're focused on the top of the pyramid.

目前，他们也在向更低端的市场拓展，这很有意思。

Currently, they're also broadening out a little bit lower as well, which is interesting.

正如我提到的，基恩士是第一名。

Keyence, as I mentioned, is number one.

他们总部在日本。

They're based in Japan.

这是一家非常成功的公司，但同时也非常神秘。

It's been a really successful company, it's also very much an enigma.

它是一家上市公司，但关于它的信息并不多。

It's a public company, but there's just not a lot of intel out there on it.

我猜，根据我收集到的信息，他们的销售额大概只有康耐视的20%左右。

My best guess, what I've gathered, is maybe 20% or so of their sales are comparable to Cognex.

他们还做科学显微镜、PLC，还有直接营销之类的业务。

They also do things like scientific microscopes and PLCs and direct marketing and stuff like that.

但更有意思的是，他们研发投入只占销售额的2%或者低个位数，而毛利率却能达到85%左右。

But what's also quite interesting is they spend 2% of sales or low single digits on R and D and have mid-80s gross margins.

相比之下，康耐视的研发投入占销售额的15%左右，毛利率大概在70%。

That compares to Cognex, which spends more like mid teens on R and D and has more like 70% gross margins.

其他机器视觉厂商的研发投入和毛利率都比康耐视要低一些。

The other machine vendor peers spend a little bit less and have even a little bit lower gross margins than Cognex.

这真的取决于基恩士的市场策略和他们的专注点。

It really comes down to the way Keyence goes to market and how they focus.

他们通常只关注中低端客户，然后努力开发更标准化的产品，针对高频应用。

They generally focus just on the middle to lower tiers of customers, and then they're really trying to develop more standardized products that are going after the very high frequency applications.

他们的销售非常注重流程，所以会招聘更多大学毕业生，然后培训他们熟悉产品，再派到现场去。

It's a very process oriented sale, so they'll hire more college graduates compared to Cognex, and then they'll train them with the products, put them out in the field.

而且他们的销售流程更像是有固定套路的，会在CRM里记录更多像活动量这样的关键指标。

And it's more of a scripted sales process where they're keeping track of more of those activity like KPIs in the CRM.

所以，就是看你打了多少电话、拜访了多少客户、做了多少次演示。

So, it's how many calls are you making, how many shop visits, how many demos.

他们的覆盖真的很到位，而且非常执着。

It's really good coverage and really relentless.

如果你深入了解，这已经成了圈子里一个梗了。

If you get down the rabbit hole, it's become a meme in the community.

网上有一些挺搞笑的梗图。

There are some pretty funny memes out there.

如果你要从网站上下载产品规格书，最好用你朋友的邮箱和电话，别用自己的。

If you're going to download a product spec sheet up the website, you should use your buddy's email and phone number, not your own.

不然你会被烦死的。

You'll never hear the end of it.

这就是两大主要玩家。

That's the two main players.

既然聊到这里，我顺便简单提一下其他几个竞争对手。

Maybe I'll briefly mention a couple of other competitors while we're here.

另一个大类，我觉得就是中国市场。

The other bucket, I would say, is China.

这些主要是面向中国的制造商。

And these are primarily for manufacturers in China.

海康机器人，是海康威视的一个部门，大概是整个行业里第三大的玩家。

Hik Robotics, which is a division of Hikvision, is probably the third largest player in the industry overall.

他们发展得很快，主要靠国内市场和国内制造商带动。

And they've grown quite quickly driven by that domestic market with the domestic manufacturers.

他们的销售额大概是康耐视的一半左右。

They're probably about half the size of Cognex in terms of sales.

还有其他一些规模较小的中国厂商。

There are a number of other smaller Chinese players as well.

除了这些，还有一些更老牌的厂商。

Outside of there, there are more legacy players.

Teledyne旗下有Dalsa和Point Grey，德国有SICK和Basler，还有Datalogic。

With Teledyne, there's Dulsa and Point Grey, There's SICK and Basler in Germany, Datalogic.

Matrix是被Zebra收购的一家公司。

Matrix was a company acquired by Zebra.

甚至还有像NZS Tech这样的公司，只卖软件，然后你可以自己去买硬件。

And there's even companies like NZS Tech that just sell the software, then you can go get your own hardware.

所以这就是行业结构的大致情况。

So that's kind of a lay of the land in terms of the industry structure.

我确实读了不少关于基恩士的销售流程以及他们建立的销售组织有多高效的内容。

I did read quite a bit about Keyence and their sales process and how effective of a sales organization they built.

但对于像康耐视这样的公司，听起来他们的销售更偏技术性，按需定制，可能更先进，而不是现成的产品。

But in the sale for someone like Cognex, where it sounds like it's much more technical, built to spec, perhaps advanced and not so much off the shelf.

他们是卖给像亚马逊这样的客户，然后亚马逊再把它集成到他们使用的其他硬件和设备中吗？

Are they selling to an Amazon who then works to integrate it into the other hardware and equipment that they're using?

还是卖给设备制造商，比如制造传送带的公司？康耐视的客户到底是谁？

Or are they selling into the equipment manufacturers, whoever builds the conveyor belt, who is the customer for Cognex?

答案是肯定的。

The answer is yes.

如果你想想他们怎么进入市场，70%的销售是直销，要么直接卖给工厂，康耐视和客户的自动化工程师一起实施系统。

If you think about how they're going to market, 70% of sales are direct, and that would be direct either to the factory floor where Cognex and the automation engineers at the customer are working to implement the system.

直销也包括卖给机器制造商或原始设备制造商，他们再把系统集成到机器里，然后把机器带到最终工厂。

Direct also includes selling to a machine builder or an OEM who would then integrate it into the machine, and then they take that machine to the end factory floor.

剩下的30%中，大约一半通过系统集成商销售，目前主要是物流领域。

Then, the remaining 30%, about half of that, is going to be through systems integrators, and that's primarily logistics at this point.

那30%的另一半则通过分销商，主要针对像柬埔寨这样的终端市场，因为那里他们完全没有存在感。

And then the other half of that 30% would be distribution, and that's primarily just for end markets like Cambodia or something where they just don't have any presence.

这就是我大致区分客户的方式。

That's kind of how I would separate the customer.

有道理。

That makes sense.

在整个行业结构的讨论中，这是一个有趣的动态。

It's an interesting dynamic within the overall industry structure conversation.

在我们继续深入之前，我确实想了解一下历史背景。根据我做的研究，这家公司有很强的技术专长，而且非常注重技术专长。

Before we move on too far, I do wanna get into a bit of the history and what came across through the work that I was doing is that there is technical expertise here and there's a focus on that technical expertise.

那你能带我们回到最初，讲讲他们的起源故事吗？他们是什么时候进入市场的，以及随着时间推移是如何演变的？

So can you bring us back to the beginning and the origin story here, when they got into the market and some of the evolution over time?

要理解康耐视，关键是要明白他们本质上是在四五十年里不断叠加S曲线的DNA。

It's really important to understand for Cognex the DNA of them stacking S curves essentially over forty to fifty years.

公司成立于1981年，他们带着世界上第一套工业光学字符识别系统进入市场，也就是用来读取数字和字母的。

The company was founded in 1981, and they came to market with what was the world's first industrial optical character recognition system, so again, reading numbers and letters.

当时，这套系统看起来更像是一个带外部处理的大型摄像机。

And at the time, the system looked more like a big video camera with external processing.

第一个应用实际上是为IBM读取半导体晶圆上的序列号。

And the first application was actually to read serial numbers on semiconductor wafers for IBM.

那就是Dataman产品系列，至今仍然存在。

That was the Dataman product family that still exists.

从那时起，他们接到了强生公司的电话，要求做标签的光学字符识别。

From there, they got a call from Johnson and Johnson to do optical character recognition for labels.

他们做了那个应用，但后来强生又问他们，嘿，你们能不能做一些当时算是新颖的应用，比如检查瓶盖有没有盖好、标签有没有贴好之类的。

They did that application, but then J and J asked them, Hey, can you do some of these other, at the time, what would have been novel applications like verifying the caps were on the bottles and the labels were present and the like.

所以那时候康耐视就增加了更多这类检查应用。

So that's when Cognex added more of these inspection type of applications.

公司前二十年左右主要是在为各种应用开拓机器视觉，但主要还是集中在半导体和电子资本设备行业。

The first twenty years or so of the business was pioneering machine vision for all these different applications, but it was very much for semiconductors and the electronics capital equipment industries primarily.

在互联网泡沫时期，这些行业的销售额占比高达80%，后来经历了一段艰难时期，降到了54%。

It was as high as 80% of sales going into the dot com bubble to those industries, and that went to 54% following the hard way.

大约在2000年，智能相机开始崭露头角，就是把处理功能直接集成到相机里。

Around 2000 was when we saw smart cameras really come onto the scene, so where you embedded the processing directly into the camera.

体积更小，更坚固耐用。

Smaller footprint, more ruggedized.

这样一来，产品就更能适应工厂车间的环境，就像我们通常想象的那样。

Now, that enabled the product to be ready for the factory floor as we more often think about it.

所以我们看到机器视觉在更多重工业领域得到应用，比如汽车、消费电子、食品饮料和包装行业。

So we saw machine vision get adopted in more heavy manufacturing industries like automotive, consumer electronics, food and beverage, packaging.

所以到2010年底，半导体和电子资本设备只占销售额的15%，因为他们真正开拓了那些能服务所有新增长曲线的终端市场。

So by the end of twenty ten, that semiconductor and electronics capital equipment was down to 15% of sales as they really brought in the end markets that they could serve all those new S curves.

大约在2010年，康耐视推出了他们的第一款用于读取条形码的ID产品。

Around 2010 was when Cognex came out with their first ID product for reading barcodes.

它主要是为了在物流设施中取代激光扫描仪，因为它的速度更快，读取率也高得多。

It was primarily aimed at displacing laser based scanners in logistics facilities because they could do it faster and then with much higher read rates.

回顾2010年，他们曾表示，如果有一天这个业务线的长期目标销售额能达到7500万美元，他们就很满意了。

If you go back in 2010, they were talking about they'd be happy if one day long term target is $75,000,000 in sales from this line of business.

然后，他们与亚马逊紧密合作，共同开发这项技术。

And then, they worked very closely with Amazon to develop the technology.

到了2021年，也就是高峰期，销售额大约为3亿美元，占康耐视整体业务的30%。

And in 2021, the peak, it was about $300,000,000 in sales and 30% of Cognex's overall business.

结果证明，这真是一个巨大的U。

It turned out to be just an enormous U.

S。

S.

对他们来说，这是一条巨大的增长曲线。

Curve for them.

目前，我们实际上正处于行业下一轮技术变革的早期阶段。

At present, we're really in the early innings of the next tech evolution for the industry.

这始于2017年，当时康耐视收购了Viti，然后在2019年，他们收购了一家名为Sualab的公司。

It began in 2017 when Cognex acquired Viti, and then in 2019, they acquired a company called Sualab.

这两笔收购本质上都是知识产权和人才收购，专注于深度学习领域，也就是将人工智能应用于机器视觉。

And those were both essentially IP and acqui hires in the field of deep learning or the application of AI into machine vision.

Viti的联合创始人兼首席技术官现在是康耐视现任人工智能技术副总裁。

Viti's co founder and CTO is Cognex's current VP of AI technology.

因此，在这些收购之后，他们进行了大量的研发工作，并推出了这些新的深度学习和边缘学习产品。

So, after those acquisitions, there was a big development effort and they came to market with these new deep learning and edge learning products.

我的理解是，这标志着从基于规则的视觉系统编程转向了通过示例进行教学，这具有深远的影响。

And the way I conceptualize this is moving from rules based programming of vision systems to teaching by example, which has large implications.

我认为，在长期周期性下行周期的背景下，我们可能正处于这一新篇章的第一阶段。

I think we're probably in the first inning of this next chapter behind the scenes of a long cyclical down cycle.

你能举个例子来说明一下吗？

Could you paint that picture in terms of an example?

比如说，基于规则的话，包裹超过100磅，尺寸是这些。

Rules based, let's say, package is over 100 pounds with these dimensions.

就送到左边那条道。

Send it in the left lane.

如果低于这个标准，就送到中间那条道。

If it's under that, send it through the middle.

如果特别小，就送到右边那条道。

If it's super small, send it to the right.

这就是一个很标准的逻辑和决策树。

And it's a pretty standard tree of logic and decisioning.

那这种新的示例或新的训练会在哪里发挥作用呢？

Where would this new example or this new training come into play?

你有没有一些实际应用案例能说明一下？

Do you have any real world applications that would paint the picture?

我之前提到过，有深度学习和边缘学习。

There's deep learning and edge learning, as I mentioned.

先讲深度学习。

Deep learning first.

基于规则的视觉系统在很多方面都很好，但对于那些非常细微或复杂、变化多端的任务就不太行了。

So, rules based vision is great for a lot of things, but not for things very subtle or nuanced tasks with a great deal of variation.

这类任务通常还是由人来完成，因为说实话，很难把它们量化，然后编程实现。

Those sorts of tasks, you still usually have a human performing them because, frankly, it's just hard to quantify them to then program them.

举个例子，检查手机壳上的细微缺陷。

Maybe an example of that would be inspecting a phone case for very subtle defects.

显然，手机壳颜色多样，潜在缺陷也数不胜数，比如划痕、凹痕、漆面瑕疵。

There's obviously a wide variety of colors and there's just an endless list of potential defects, so scratches, dents, blemishes in the paint.

这些缺陷非常小，非常细微。

They're very small, very nuanced.

而且通常还有一个可接受和不可接受的标准，人一眼就能看出来，很快就能判断。

And then, there's also usually a scale of what's acceptable and what's not, where a human would be able to look at it and pretty quickly discern that.

但要让机器做到这一点非常困难，尤其是在高速运转的情况下。

But it's very hard to program a machine to be able to do that, especially at high speeds.

但通过深度学习，不是编程，而是用大量的数据集和图像集来训练它。

But with deep learning, instead of programming it, you teach it with very large data sets and very large image sets.

这些是好的手机图片。

These are good phone images.

这些是缺陷。

These are defects.

这些是可接受的缺陷。

These are acceptable defects.

机器学会了什么是可接受的，什么不是，并且能够完成这项任务。

And the machine learns what is acceptable and what is not and is able to accomplish that task.

稍微量化一下，目前全球仍有3000万人在做视觉检测，而人类其实并不擅长这个。

Just to quantify this a little bit, there are currently still 30,000,000 people in the world doing visual inspection, and that's something that humans actually aren't great at.

他们能快速完成，但容易疲劳，会漏掉一些东西。

They can do it quickly, but they get fatigued and they miss things.

这是个很大的机会。

That's a big opportunity.

另一个例子是给鸡去骨，每只鸡都不一样。

Another example would be something like deboning chickens, where every chicken is different.

鸡从流水线上下来，方向各不相同。

It comes down the line in a different orientation.

鸡翅的位置也都不一样。

The wings are somewhere different.

要量化并编程让机器人抓对位置是不可能的。

It'd be impossible to quantify and program a robot to be able to grab the right places.

但有了深度学习，现在就能做到这一点。

But with deep learning, that's an application that they can now do.

深度学习意味着机器视觉可能会有新的应用。

Deep learning, the implication would be potentially new applications for machine vision.

边缘学习则是另一个极端，对投资者来说，现在可能更实在一些。

Edge learning is the other end of the spectrum, and it's probably more financially tangible for the investor community right now.

这些产品针对特定应用预编程，但只需五到十张图片就能完成训练。

These products come preprogrammed for specific applications, but then they're trained with just as few as five to 10 images.

所以，相比传统的基于规则的视觉系统，部署起来非常容易。

So, it's essentially very easy to deploy relative to traditional rules based vision.

通常几个小时内就能让一个应用运行起来。

You can usually get an application up and running in a few hours.

所以这里的主要影响是，康耐视现在可以卖给不太专业的客户了。

So the major implication here is that Cognex can now sell to less sophisticated customers.

再想想他们历史上一直专注于金字塔顶端。

Again, thinking about where they've historically focused on the top of the pyramid.

而且他们可以用技术含量低得多的销售团队来做到这一点，从而在传统服务范围之外扩大客户群。

And they can do it with a much less technical sales force, so broadening their customer base below where they've typically served.

现在他们有了产品，康耐视正在投资建设销售团队，称为“新兴客户计划”。

So now they have the product and Cognex is currently making a sales force investment called the Emerging Customer Initiative.

这实际上是在借鉴基恩士的做法。

And it's really taking the Keyence playbook.

这些新兴客户销售员，他们把自己的员工叫做Cognoids，销售人员叫做salesnoids。

These emerging customer salesnoids, they call their employees Cognoids, their salespeople salesnoids.

他们招聘的是年轻销售人员，而不是技术应用工程师。

They're hiring young salespeople instead of technical applications and engineers.

他们用这些新的边缘学习产品来武装他们，这些产品非常容易实施。

They're arming them with these new edge learning products that are really easy to implement.

他们瞄准的是那些不太成熟的客户，更多是中小企业类型，甚至包括现有客户中那些不太复杂的任务。

And they're going after these less sophisticated customers, more SMB types, and even less sophisticated tasks within existing customers where those exist.

而且，他们有一套更加正式的销售流程，跟踪关键绩效指标，就像基恩士一样。

And then, it's a much more formalized selling playbook that tracks the KPIs, just like Keyence.

他们的薪酬既基于销售活动，也基于佣金。

They're getting compensated on both their selling activity as well as their commission.

去年，第一批销售员进入市场，他们进行了8万次客户拜访，新增了3000个客户，而之前客户总数是3万，毛利率还有增长，年底时这批销售员每周带来约100万美元的销售额。

Last year, Cohort one of these sales noise hit the field, they did 80,000 customer visits, added 3,000 new customers to a base of what was previously 30,000 at accretive gross margins, and they exited the year at about $1,000,000 a week in sales from that first cohort.

第二批销售员在2025年进入市场，希望从经验中吸取教训，能做得更好一些。

The second cohort entered this year in 2025, and hopefully will do a bit better just from lessons learned.

显然，他们现在正在和基恩士争夺核心目标客户，所以有时候会遇到这些客户被抢走的情况。

Obviously, they're now competing in Keyence's bread and butter target customer set, so they are running into them sometimes with these customers being vended.

但大多数情况下，这些客户之前根本没用过机器视觉。

But the majority of the time, these customers have never used machine vision at all.

我觉得大概有60%到70%的销售是来自那些工厂里从未装过摄像头的客户。

Think it's more like 60 to 70% of their sales have been people that have never had a camera in their factory.

显然，从财务角度看，他们是想把客户群从3万扩展到几十万，这显然是个收入机会，同时还能提高毛利率，并降低客户集中度。

Obviously, the financial implications here are they're trying to grow their customer base from 30,000 to hundreds of thousands over time, which could be obviously revenue opportunity and then add accretive gross margins and reduce the customer concentration as well over time.

关于客户群，我觉得你刚才已经描绘了一幅图景，涵盖了各种应用和潜在用户。

The customer base, I think you painted a picture just in terms of the various applications and who might use them.

但从客户的角度来看，具体是什么样呢？比如合同、销售，以及合同或销售的推进过程，还有一旦你构建了解决方案，客户的粘性如何？

But what does it look like in terms of a customer, whether it's a contract, whether it's a sale, the ramping of that contract or sale, and then what the stickiness is once you build something out?

客户的粘性非常高。

The stickiness of a customer is quite high.

一旦你进入工厂，负责管理车间的人熟悉了用于编程摄像头的软件，而且这种软件通常或多或少是标准化的，尤其对一些客户来说，为了简化，他们不希望有多个机器视觉供应商和相关的软件。

Once you're on the factory floor and the people that are managing the floor are familiar with the software used to program the cameras, and it's usually more or less standardized, especially for some customers where, for the sake of simplification, they don't want a bunch of different machine vision vendors out there and the associated software.

这是一笔资本支出销售，而且正如我提到的，他们历史上一直专注于金字塔顶端的客户。

It's a CapEx sale, and they have, as I mentioned, historically been focused on the top of the pyramid customers.

所以他们一直与苹果和亚马逊这样的大公司的资本支出建设紧密相连。

So they've been tied to the large CapEx build outs of companies like Apple and Amazon.

这显然是波浪式的，然后更多的问题是叠加U。

And that obviously comes in a wave, and then it's more of a question of stacking U.

S。

S.

曲线，以及下一波资本支出何时到来。

Curves and when the next waves in CapEx is going to come.

但客户本身通常非常忠诚。

But the customers themselves are generally quite sticky.

也许这是一个很好的过渡，来讨论不同的终端市场，我们可以从消费电子开始。

Maybe this is a good segue into the different end markets, and we can start with consumer electronics.

有趣的是，这个终端市场与围绕新消费电子或功能的资本支出相关。

It's interesting because that end market is tied to the CapEx spending around new consumer electronics or features.

手机普及带来了一个顺风，然后苹果建设iPhone生产线又带来了一个顺风。

There was a tailwind from the adoption of cell phones, then there was the tailwind from Apple building out the iPhone manufacturing.

曾经有一段时间，苹果占了康耐视销售额的20%，这相当惊人。

At one point, Apple was as high as 20% of Cognex's sales, which is pretty incredible.

现在可能已经降到了中高个位数百分比的范围。

It's now probably down to more mid to high single digits range.

OLED出现时又有一个大的顺风，那是跟三星合作的。

There was another big tailwind when OLED came on the scene, and that was with Samsung.

所以，展望未来，想想会不会有新的形态或者现有形态的变化，跟大语言模型相关，或者AR/VR会不会终于起飞，或者人形机器人会不会火起来，这些都挺有意思的。

So, forward, it's interesting to think about if there will be new form factors or changes to the existing ones for consumer electronics tied to things like LLMs or if AR or VR is going to take off ever or if humanoid robots are going to take off.

基本上，如果这些产品要大规模生产，那正好是康耐视的强项——客户成熟，制造能力强大。

Basically, if any of those things were to be manufactured at high volumes, that would fall right into Cognex's sweet spot sophisticated customers, big manufacturing capability.

在消费电子领域，2024年占了销售额的17%。

In consumer electronics, in 2024, 17% of sales.

长期来看，他们期望这个市场能有中双位数的增长，这是他们的目标。

Longer term, they expect that market to grow mid teens is their target.

物流是最大的终端市场。

Logistics is the largest end market.

它占销售额的23%。

It's 23% of sales.

在高峰期，它占销售额的30%，而亚马逊曾占康耐视销售额的17%。

At peak, it was 30% of sales and Amazon was up to 17% of Cognex's sales.

显然，这个终端市场经历了一个广为人知的低迷周期。

Obviously, there was a well publicized down cycle in that end market.

他们在2024年恢复了增长。

They did return to growth in 2024.

他们增长了20%，这也是该终端市场的长期目标，即能够增长20%。

They grew 20%, and that's the long term target for that end market, is that they can grow 20%.

亚马逊作为客户，可能又回到了高个位数到10%的范围。

Amazon probably is back around that high single digits to 10% range in terms of a customer.

按照康耐视的风格，他们在物流领域不断叠加新的S曲线，这真的很有意思。

In Cognex fashion, they're stacking new S curves in logistics, which is really interesting.

所以他们正在把视觉隧道技术——这项技术他们是在亚马逊那里打磨成熟的——推广到新客户和新地区。

So they're taking the vision tunnels, which they've really honed with Amazon, to new customers and new geographies.

那些非亚马逊的客户增长非常快。

Those non Amazon customers are growing very quickly.

然后，他们还在识别条码读取之外的其他应用，比如视觉检测，用来检查流水线上是否有损坏的箱子或标签，确保标签完好。

And then, they're also identifying other applications outside of barcode reading, things like vision inspection to see damaged boxes coming down the line or damaged labels, make sure there are labels.

甚至还有像尺寸测量这样的应用，用来估算运费等等。

Even things like dimensioning to do estimating of your shipping costs and things like that.

所以，他们先打入市场，然后在这个终端市场里寻找更多的应用场景。

So, they get their foot in the door and then they find additional applications within the end market.

这就是目前物流领域的情况。

That's the story of logistics at the moment.

汽车是第二大市场，占销售额的22%。

Automotive is the second largest market at 22% of sales.

理论上，电动汽车电池应该会给他们带来有利的推动。

In theory, EV battery should be a good tailwind for them.

康耐视有解决方案。

Cognex has solutions.

坦白说，这个转型确实需要大量资本支出，无论是新的汽车生产线还是电池工厂，如果只是新车型、内燃机车型的话，这些投入本来是不需要的。

The transition just, frankly, necessitates a bunch of CapEx, whether it be new automotive lines but also battery facilities that otherwise would not have been the case if it was just new models, internal combustion engine models.

但坦白说，去年增长并没有像人们预期的那样实现。

But frankly, the growth just didn't come through last year as people had expected it to.

2024年汽车销售额下降了百分之十几。

Automotive sales were down mid teens in 2024.

2025年预计不会是好年景，但至少不会像2024年那样大幅下滑。

It's not expected to be a good year in 2025, but it shouldn't be a deep decline like 2024 at least.

长期来看，这个终端市场的目标是康耐视实现10%的增长。

And long term, the target for this end market is 10% growth for Cognex.

还有两个简短的点。

Two other quick ones.

半导体现在大约占销售额的10%到15%。

Semiconductor is probably about 10% or 15% of sales now.

他们主要卖给半导体设备制造商，目前那里的增长前景是积极的。

They're selling primarily to the semiconductor capital equipment manufacturers, and the growth outlook there is positive at this point in time.

然后，另外20%到25%是通用工厂自动化，主要关注PMI。

And then, the other 20% to 25% is general factory automation and keeping an eye on PMI there primarily.

工业制造业历史上经历了很长的下行周期，Cognex在那一部分客户群中感受到了这一点。

It's been historically long down cycle for industrial manufacturing, and that's been felt by Cognex in that part of their customer base.

他们安装的设备有没有平均使用寿命？

Is there an average useful life in terms of the equipment that they're installing?

设备也有更换周期吗？

Are there replacement cycles for the equipment as well?

理想情况下，当客户在工厂安装摄像头时，他们希望它能用十到二十年。

Ideally, when a customer puts the camera in the factory, they're hoping it's gonna last for ten to twenty years.

所以实际上没有固定的更换周期。

So there's not really a a regular replacement cadence.

更重要的是，你让客户进入你的安装基础，然后他们会在现有生产线上进行棕地资本支出，这将为Cognex创造收入机会。

It's more about you get the customer in your installed base, and then they'll be doing brownfield CapEx on existing lines, and that'll create revenue opportunities for Cognex.

时不时地，会有这些新项目的机会，或者就是新的终端市场和新客户。

Every now and then, there'll be these greenfield opportunities with those customers or just new end markets and new customers.

这就是推动行业长期增长的动力。

And that's what drives the growth of the industry over time.

在软件业务方面，当我想到他们从设备销售中能赚多少钱时，软件真的是他们的收入驱动力吗？

On the software side of the business, is that an actual revenue driver for them when I think about how much they will make from the sale of equipment?

这笔收入是在第一年全部确认，还是随着某种软件组件分摊到多年？

Is it all recognized in year one or is it spread out with some type of software component?

我开玩笑说，Cognex 不调整他们的股票补偿支出，这对一家本质上是软件公司的企业来说很棒，但代价是你得承受工业公司的周期性波动。

The joke I say is that Cognex doesn't adjust out their stock based comp, which is great for a company that's essentially a software company, but you get stuck with the cyclicality of an industrial company as a trade off.

所以这都是一次性的销售。

So it's all an upfront sale.

软件是和硬件资本支出绑定的。

The software is tied to the hardware CapEx.

听起来，当行业出现范式转变或引入新的产品形态，需要工厂或生产线进行新的资本支出，从而必须引入新的 Cognex 设备时，你就会看到 S 曲线。

It sounds like you get the S curves when there is a paradigm shift or a new form factor introduced into an industry that would require new CapEx spent on a factory or a production line where new Cognex equipment would have to come in.

但如果只是生产同样的手机或汽车，没有新增功能，你就不会看到收入大幅增长，因为不需要对工厂进行调整，对吧？

But if it's just producing the same phones or the same cars without added features, you're not gonna see a big step up in revenue because you don't have to make adjustments to the factory?

我觉得你说得对。

I think that's right.

你可以把核心业务看作是支持客户进行大额资本支出。

You can think of the core business as supporting customers as they're doing their big CapEx spends.

这些业务都跟资本支出挂钩。

They're tied to that.

所以目前，比如在消费电子领域，我们正在留意可能的新机会，但还没有什么能推动苹果进行大规模资本支出。

So at the moment, in consumer electronics, for example, we're keeping an eye out what it could be, but there's not something that's driving a big CapEx spend to Apple, for example.

这个终端市场目前处于一种比较稳定的维护水平。

That end market's kind of at a more steady state maintenance type of level.

你描述得很准确。

You characterized it correctly.

在这种背景下，半导体业务听起来占了相当大的比重，但可能并没有像半导体市场本身那样享受到同样的增长动力。

Within that context on semiconductors, it sounds like it's a meaningful chunk of the business, but not something that maybe has captured the same tailwind of the actual market itself with semiconductors.

那这种脱节是什么原因造成的？

What drives the disconnect there?

你会把它归因于什么，让它现在不只是业务的一大块，因为我们正在经历这个周期？

What would you tie that to where it's not just this massive chunk of the business right now as we're seeing this cycle play out?

他们实际上在2023年底对一家叫Moritex的公司进行了一次补强收购。

They actually did a bolt on acquisition of a company called Moritex in late twenty twenty three.

Moritex销售光学和照明产品。

Moritex sells optics and lighting.

其中很多都进入了半导体终端市场。

A lot of that goes into the semiconductor's end market.

在那之前，Cognex在半导体领域的业务占比非常小，可能不到5%。

Prior to that, Cognex's semiconductor exposure was quite small, probably sub-five percent.

而在那次收购之后，比如在2024年，它增长得非常快。

And then after that acquisition, it grew quite quickly in 2024, for example.

预计在2025年，它还会再次强劲增长。

The expectation is it's going to grow very strongly again in 2025 at this point in time.

所以我觉得这大概解释了为什么它的规模会这么大。

So I think that kind of explains why it's the size that it is.

你刚才提到的那些大客户，还有汽车市场目前不温不火，这些都吻合。

Everything you mentioned just in terms of the various big customers, the auto market being tepid or modest at best at the moment, all align.

我们之前聊历史的时候，没怎么谈到文化，尤其是领导层。

One thing we didn't get into when we talked about the history was the culture, more so the leadership.

你觉得文化和团队管理方面是怎么演变的？

What would you point to just in terms of the evolution of the culture and then management team?

我觉得在讨论康耐视的时候，很少能聊到这么深入才谈到文化。

I think it's rare that you get to this point in the discussion before you talk about the culture at Cognex.

它的文化确实非常独特。

It really is very unique.

就像我说的，他们的员工被称为Cognoids，而且在过去四十五年里，他们只有过两位CEO。

As I mentioned, their employees are called Cognoids, and they've had two CEOs in the past four and a half decades.

所以，创始人，博士。

So, the founder, Doctor.

罗伯特·希尔曼，真是独一无二。

Robert Schillman, is one of a kind.

大家都叫他博士。

He goes by Doctor.

鲍勃。

Bob.

我在想怎么在播客里快速描述他。

I was thinking about how to describe him quickly for a podcast.

我觉得他半开玩笑说过的一个理论，挺能概括他的。

I think there's one theory that he says tongue in cheek that I think captures him quite well.

他虽然是开玩笑说的，但他说他不相信锻炼，因为身体就是一堆机械关节，任何机械的东西都有使用寿命。

He says it tongue in cheek, but he says that he doesn't believe in exercise because basically your body is a bunch of mechanical joints and anything mechanical has a finite amount of use.

光从这一点就能看出，他绝对是个工程师。

Just from that, you can see that he's clearly an engineer.

他非常聪明。

He's really smart.