微软首席技术官凯文·斯科特问答专场

欢迎来到《科技背后》。

Welcome to Behind the Tech.

我是你的联合主持人克里斯蒂娜·沃伦，GitHub的高级开发者倡导者。

I'm your cohost, Christina Warren, senior developer advocate at GitHub.

我是凯文·斯科特。

And I'm Kevin Scott.

现在到了我们的问答环节。

It is time now for our AMA episode.

在过去几个月里，听众们提交了一些非常精彩的问题。

And so for the past couple of months, listeners, have been sending in some really fantastic questions.

我们无法回答所有收到的问题，但非常感谢每一位提交问题的朋友。

And we cannot answer every single one that we got, but we are so appreciative of all of you who sent in your questions.

这将是一场非常有趣的对话。

And so this is gonna be a super interesting conversation.

这是来自拉文德的问题。

Here's our question from Ravender.

在人工智能时代，你的学习节奏发生了怎样的变化？

How has your pace of learning changed in the era of AI?

你个人用人工智能做过最酷的事情是什么？

What's been the coolest thing you've done with AI personally?

是的，我确实在工作之外的项目中大量使用了人工智能。

Yeah, I've definitely been using AI a ton for the projects that I'm doing outside of work even.

它在工作中被用于很多非常有用的事情。

So the bunch of things that it gets used for at work that are hugely useful.

但工作之外的那些应用，我觉得更有趣。

But the outside of work ones, I think, are fun.

也许我做过最酷的事情是，过去一年我在陶瓷工作室里迷上了制作日本茶碗。

Maybe the coolest thing that I've done is I have gotten really into making Japanese tea bowls in my ceramic studio this past year.

我一直研究如何复现传统日本乐烧茶碗的一些效果，这让我自己配制了窑炉、设计了釉料配方，甚至开发了一种方法，让制作茶碗的陶土变得更坚固，以应对这种疯狂烧制过程中剧烈的热循环。

And I have been researching how to replicate some of the results in traditional classic Japanese raku tea bowl making, which has involved me making my own kyun, devising my own glaze recipe, and even devising a way to take a clay body that you make the bowls out of and making it tougher so that it can handle all the thermal cycling in this crazy firing process.

我必须说，Copilot 在整个过程中都非常有用，尤其是在窑炉设计和帮助我获得灵感、推进釉料化学配方方面。

And I will tell you that Copilot was amazingly useful in all of that, particularly with the kiln design and with helping get some ideas and make progress on the glaze chemistry for this glaze.

这太有趣了。

That's so interesting.

那你用Copilot做些什么呢？

So what do you do with Copilot with that?

还是你只是和它聊天，来回提问，讨论如何设计东西？

Or do you just have a conversation and just ask questions back and forth about maybe how you want to design stuff?

是的。

Yeah.

基本上，在釉料设计方面，我告诉Copilot，或者说我问它：我有一套茶碗，以传统的乐烧方式在1100摄氏度下烧制，我会把上好釉的器物直接放进高温窑中，停留三分钟，直到釉面变成樱桃红色，然后取出进行空气淬冷。

Basically, the glaze design, told, I or I asked Copilot, I was like, I've got a, set of tea bowls that I, am firing in the classic Raku style at 1,100 degrees Celsius where, I'm going to, take the glazed vessel, put it directly in the at temperature kiln, leave it for three minutes until the glaze goes cherry red and then pull it out to air quench.

我给了它一些关于我想法的提示。

And I gave it a few hints about what I had been thinking about.

比如我知道的日本工艺的有趣之处。

Like what I know of the Japanese this is the interesting bit.

传统的日本乐烧釉料中含有铅，以使釉料成分在较低温度下熔化。

The traditional Japanese Raku glazes use lead in them to get the elements of the glaze to melt at a lower temperature.

哦，好的。

Oh, okay.

显然，我不希望在我的茶碗中使用铅。

And obviously, I don't want to be using lead in my tea bowls.

尽管有更安全的铅替代品可用于陶瓷，但我还是不想用。

Even though there are safer variants of lead that you can use that are safe in ceramics, but I didn't want to.

因此你需要使用其他东西，比如硼。

And so you need to use something else like boron.

所以，确定硼的用量、硼的存在形式以及釉料的配比有点复杂。

And so figuring out how much boron you use and in what form the boron comes in and the glaze is a little bit tricky.

这非常有帮助。

And it was super helpful.

这感觉就像我在和一个对釉料化学有不同了解的人进行真正的对话。

And it felt like a real conversation that I was having with someone who knew a little bit something different about glaze chemistry than I know.

真的，这太有趣了。

Genuinely, this is so fascinating.

而且，谢谢你与我们分享你这么多的兴趣，因为你真的非常有趣。

And also, thank you for sharing all of your many interests with us because you're such an interesting person.

我从未想过，从我所了解的来看，你竟然如此热衷于手工制作，比如自己建造窑炉、制作日本茶碗，还用人工智能来获取更多关于这方面的信息。

And I never would have thought that from all I know how much of the maker stuff you're into, but building your own kiln and making Japanese tea bowls and using AI to get more information about this.

我太喜欢了。

I love it.

这是人工智能的一个绝佳应用场景。

That's a great use case of AI.

我太喜欢了。

I love that.

很好。

Great.

很棒的东西。

Great stuff.

再次感谢你提出这个问题。

Thank you again for that question.

好的。

Alright.

这个问题来自拉斐尔，他问：你认为未来人工智能是否会彻底改变我们开发软件的方式？

This question is now from Rafael and he asks, do you believe that in the future, AI will completely reshape the way that we produce software?

他还进一步表示：我的意思是，我们最终能否摒弃今天使用的开发工具，从头开始重新思考整个流程，创造出一种全新的软件开发方法？

And he goes on to say, know, I mean, could we eventually get rid of the development tools that we use today and rethink the entire process from scratch, creating a completely new approach to software development?

看起来很有可能。

Seems likely.

是的。

Yeah.

我的意思是，我年纪够大了，这么说可能听起来有点令人不安，但我已经编程四十年了。

I mean, and I'm an old enough fart where I mean, this sounds disturbing to say, but, like, I I've been programming for forty years.

所以我52岁。

So I'm 52.

我12岁的时候就开始编程了。

I started when I was 12.

在过去的四十年里，尤其是软件开发，即使没有AI，也与1980年代的软件开发方式大不相同了。

And in in forty years, like, particularly the past forty years, like, it software development now, even without AI, doesn't really resemble much at all what software development looked like in the 1980s.

所以我认为，未来几年内，软件开发必然会自我重塑。

And so I think it's a safe bet that software development is going to reform itself over the next handful of years.

我认为很明显，AI将改变我们编写软件的方式。

And I think just super clear that AI is going to change the way that we write software.

没错。

Think, yeah.

它们只是以一些显而易见的方式，改变着一切。

They're they're just sort of all of the obvious ways, you know, that that it's gonna change things.

你知道，编程是一项复杂的活动，一直以来都是如此：你脑子里有个想法，需要把它提炼清晰，然后把这个清晰的想法转化为计算机能够执行的形式。

You know, coding is a complicated activity and like it always has been like this thing where you've got an idea in your head that needs to be sharpened and then you need to get the sharpened idea out into a form that the computer can go execute.

真正发生改变的是——我以前在公开场合也说过——我们构建软件的方式，自阿达·洛芙莱斯时代以来其实几乎没有变化。

The thing that's really changed, and I've said this before in public, think, is the way that we've been building software hasn't really changed since Ada Loveless.

整个算法思维的过程，理解机器的复杂性，直至其最底层的细节，然后利用对机器的这种理解，将你用算法构想出的想法转化为计算机能够执行的程序。

Whole process of algorithmic thinking and understanding the complexity of a machine all the way down to its atomic details and then using that understanding of the machine to transform this idea that you framed algorithmically into a program that the computer could write.

我们这样做了将近两个世纪，实际上一直没有什么替代方案。

We've been doing that for almost two centuries now, and there really hasn't been much of an alternative.

我们的工具变得越来越强大，但本质上，你只是希望计算设备为你做点什么。

Our tools have become increasingly more powerful, but it's like it's basically that you want a computing device to do something for you.

你要么自己弄清楚如何完成这个过程，要么只能指望有人写好了程序，你可以直接运行。

You either, like, figure out how to do that process yourself or you have to hope that someone who understands how to do that has written a program that you can run yourself.

我认为AI带来的巨大变化是，现在你可以描述你想要实现的目标，甚至不需要用算法术语来表达。

And I think the big thing that's changed with AI is now you have a thing where you can describe a thing that you want accomplished, not necessarily even in algorithmic terms.

然后AI可以完成其中一部分或全部映射工作，让计算机真正为你做事。

And then AI can do some or all of that mapping to get the computer to actually do the thing for you.

这极大地改变了我们对软件开发以及谁是开发者的理解。

And that really, really dramatically changes how we think about software development and who's a developer.

它改变了我们所构建事物的含义。

It changes what it means that we're building.

比如，我刚刚和一群工程师进行了这样的对话。

So for instance, I was just having this conversation with a bunch of engineers.

我不认为这个世界还需要应用程序。

I don't know that you need apps in this world.

应用程序是我刚才描述的早期模式的副产品，即有人必须理解一群人想要完成的一系列问题，然后将大量代码拼凑成一个被称为应用程序的东西，以足够通用的方式实现这些功能，让这些人能够从中获得价值并使用它。

An application is a byproduct of this early thing that I just described, that someone has to understand a set of problems that a group of people want to accomplish, and then they just edit a bunch of code together into this thing called an application that does those things in a general enough way that those people can get some value out of it and be able to use it.

我不认为在未来，人们还需要太多这样的应用程序。

And I don't know that you are gonna need that too much further in the future.

你仍然需要应用程序中所包含的功能，但用户界面——比如要求人们去学习某种软件的全部复杂性，因为他们必须 navigating 某些奇怪的用户界面信息架构才能完成一件事，而不是直接说出他们想要做什么——这种模式正在改变。

Like, you'll still need, like, the capabilities that are in the applications, but the user interface, like, telling someone they gotta go learn all of the complexity of some software because they gotta navigate some weird user interface information architecture to get a thing done versus just say what they want done.

这显然正在发生变化。

That's changing clearly.

这对软件开发也有影响。

That has an implication for the software development as well.

是的。

Yeah.

是的。

Yeah.

确实如此。

It does.

我的意思是，这正是我一直在想的，对吧？

I mean, that's what I kind of think about, right?

因为显然，你说得对。

Because obviously, think you're right.

它可能会彻底改变我们对开发者的定义，而我们长期以来一直在以各种方式尝试这样做。

Like, it could change completely how we define a developer, which is something that we've been trying to do in various ways for a long time.

但现在，我们终于感觉可能正站在真正拓宽这一概念的边缘。

But now we finally feel like we're maybe on the cusp of really broadening that concept.

这真的感觉可能成为现实。

It really feels like that could be a reality.

但它确实让我想到其他层面的问题：那么，你该如何设计编程语言，或者你真的需要设计吗？

But it does make me think about on other levels, okay, so how do you design programming languages or do you?

或者这会如何改变，对吧？

Or how does that change, right?

那么，除了这些之外，底层代码还有什么重要的地方？

What Like what matters then about the the underlying code beyond that?

如果我们能够仅凭自然语言和我们的需求来创建东西，并且让多人同时进行迭代更新。

If we are able to just create things based on our natural language and based on what we want and and make updates iteratively with multiple people at once.

这会如何改变我们设计这些底层系统的方式？

How does that change how we design those underlying systems?

我觉得这也是非常值得思考的。

I think that's really interesting to think about too.

是的。

Yeah.

完全同意。

100%.

这些都是非常值得思考的有用内容。

And super useful stuff to think about.

关键在于，这在软件开发中一直如此：你希望东西能够组合在一起。

And the trick is, and this has been true about software development forever, is you want things to compose.

所以，AI 距离实现我刚刚描述的这一宏大愿景还很遥远。

So AI is still a pretty far ways away from doing this grand vision that I just articulated.

因此，在当下到那个愿景实现（如果真的能实现的话）之间的这段时间里，我们真正需要思考的是：如何将那些处于从传统软件开发工具到全新 AI 未来这一连续谱系上的工具，以合理的方式整合起来，让开发者能够充分利用他们工具箱中的所有资源，最终构建出他们想要的东西。

And so what we really need to be thinking about between now and, like, whenever that happens, if it actually happens, way that I imagine, is, like, how do you take tools that are on some spectrum of, you know, classical software development tools to, you know, this new AI future and make sure that all of the things compose together in reasonable ways so that developers can then take all of this stuff that's in their toolkit and get the thing built that they're hoping to be able to build.

是的。

Yeah.

没错，完全同意。

Yeah, totally.

我的意思是，还有很多值得思考的问题，我完全赞同你的观点。

I mean, lots of things to think about and I totally agree with you on that.

好的。

All right.

我们收到了维罗妮卡的一个问题，虽然稍微转向了另一个话题，但仍然围绕着 AI。

We've got this question from Veronica, shifting topics just a little bit still around AI.

她想知道，你建议我们如何监管 AI？

And she wants to know, how do you suggest we regulate AI?

这应该由联邦层面还是州层面来实施？

Should this be done at the federal or state level?

我们如何确保AI在公共和私人层面都安全可靠？

And how can we ensure that AI is safe and secure both from a public and private standpoint?

很好的问题。

Great question.

是的，我觉得这是个非常棒的问题。

Yeah, I think it's a super great question.

我也说过这一点，而且我想我在我的书里也提到过。

Again, I've said this as well, and, like, I think I talked about it even some in my book.

当然，任何像AI这样强大的技术都需要监管，如果如此强大的技术却未被监管，那在人类历史上将是极其反常的。

Like, of course, any technology as powerful as AI needs to be regulated, and it would be just an odd thing in the course of human history if you had something this powerful and it wasn't regulated.

不过，监管时你想要做的是，我认为一致性很有帮助。

You know, the thing that you wanna do though with regulation is I think consistency is helpful.

也就是说，像联邦层面的统一监管，能在各州乃至国际上保持一致的标准，将会非常非常有用。

Like, that's where, you know, sort of, you know, federal federal regulation that is, you know, consistent across all the states and even, you know, sort of international standards would be super, super useful.

是的。

Yeah.

因为监管的良好意图是让有益的技术尽可能快速且安全地部署给那些能够从中受益的人。

Because regulation regulation like, good regulations intent is to, like, get beneficial technologies deployed to those who will benefit from it as quickly and safely as humanly possible.

所以你不希望监管本身变得不必要的复杂，因为那样会阻碍有益技术到达真正需要它的人手中。

And so you you don't want unnecessary complexity in the in the regulation itself, because, like, that prevents, you know, the the whole, you know, beneficial technologies getting to whom it benefits.

但确实，我认为总体上，我们的监管机构需要非常灵活，制定出既能鼓励最有益的技术尽快进入市场，同时又能谨慎应对各种潜在风险的法规。

But, yeah, I mean, I I I think in general, we will need our regulators to be pretty agile, in making regulation that can encourage the most beneficial things for the broadest number of people to get to the market as quickly as possible while at the same time being careful about, you know, what the downside risks are to a bunch of things.

在很多地方，最大的潜在风险实际上是部署速度不够快。

And in in a bunch of places, like, the biggest downside risk honestly, is failure to deploy quickly enough.

嗯。

Mhmm.

比如，现在有很多医疗领域的应用，其模型表现已经远远超越了人类水平。

Like, there there are, for instance, like, whole bunch of medical things right now where the models are strongly superhuman.

是的。

Yeah.

在过去一年里，我亲自经历过母亲在医疗系统中的遭遇，如果她能使用最先进的AI工具，本可以减少大量痛苦。

And I I've, you know, had some experience with my own, you know, mother in the past year with the health care system where, you know, if she had had access to the most advanced AI tools, a whole lot of suffering could have been reduced.

是的。

Yeah.

有大量的人正处在类似的情况中，这并不是某种理论上的未来可能性，而是现在就能带来益处。

It's lots and lots and lots and lots of people are in similar situations where it's not some theoretical future where stuff could be beneficial.

现在就能带来益处。

It's now that it could be beneficial.

你觉得我们该如何教育或确保立法者了解这一领域潜在的机遇与风险呢？

How do you think we go about, I guess, educating or ensuring that our legislators are aware of what the potential, I guess, both opportunities and risks are in this area, right?

因为这是我经常思考的问题。

Because this is something I think about a lot.

我同意你的观点。

I agree with you.

监管非常重要，而且必须保持一致。

Regulation is super important and it needs to be consistent.

但我有时会想，作为技术人员，我们要跟上所有这些进展已经够难了。

But I do sometimes wonder, I mean, it's hard enough for us as technologists to keep up with all of these things.

我们该如何做好确保立法者得到充分信息的工作呢？

How can we do a good job of making sure that the legislators are informed?

是的。

Yeah.

就这一点而言，我对人工智能感到最鼓舞的，是超过我所知的任何以往技术。

I will say the thing that I'm most encouraged by on this front with AI is more so than any previous technology that I'm aware of.

你看到这个领域的从业者花了大量时间与学术界和政府人士交流，以确保他们获得做出明智决策所需的信息。

You have practitioners in the field spending a whole bunch of time talking with people in the academy and people in government trying to make sure that they have the information that they need in order to make good decisions.

而且我看到人们是以非常尊重的方式在做这件事。

And I see people doing it in very respectful ways.

当然，无论你是来自政府、学术界还是产业界，每个人在看待这个问题时显然都带有某种偏见。

Now, you know, obviously, everybody who's coming at it, like, whether you're in the government or you're in the academy or you're in the industry, you're obviously biased in some way.

我们都必须尽可能清晰地阐明自己的偏见，并把它们摆到桌面上来。

We all need to be as clear as we possibly can about our biases and sort of lay them on the table.

但仅仅因为你有偏见，并不意味着你不能把信息传递出去，然后让别人去调整这些偏见，找出其中的主线，等等，从而做出良好的政策决策。

But, like, just because you're biased, like, doesn't mean that you can't get information out there and then have someone, you know, adjust for the biases, look for, you know, what the through line is and everything, and then make good policy policy decisions.

这比不透明地对待正在发生的事情，或者因为‘这不归我管’就决定不与人交流要好得多。

Like, that's a way better way to be than to, like, not be transparent about what's going on or, you know, decide that you're not gonna talk to somebody because it's not your job.

我认为，目前在科技领域，任何从事人工智能工作的人，一旦被要求，都有责任耐心地解释你正在做什么、为什么做，以及它是如何运作的。

Like, I think right now in in tech, anybody who's working on AI, part of your job is to, when required, patiently explain what it is you're doing, why you're doing it, and how it works.

很棒的内容。

Great stuff.

好的。

Alright.

这是一个来自Mooey Gary的问题，非常好。

So this is a question from Mooey Gary, and this is really good.

如何在技术基础设施有限的地区有效扩展大型语言模型？

How can large language models be scaled effectively across regions with limited technological infrastructure?

想想非洲国家这样的地方。

So think about places like, African nations.

在科技基础设施有限的欠发达地区，AI驱动的教育解决方案要超越原型阶段并实现大规模部署，面临哪些主要障碍？

What are some of the biggest hurdles for AI powered educational solutions to move beyond prototyping and into full scale deployments in underserved regions?

如何克服这些挑战？

How can these challenges be overcome?

我认为，这方面的情况可能相当乐观。

Well, I think the news there is probably pretty good.

如果你想要构建一个AI应用，现在比以往任何时候都更容易实现。

So if what you want to do is to build an AI application, it has never been easier than it is right now to go build one.

你可以选择更多强大的模型来使用。

You have more choices about very powerful models to access.

你有通过API提供的模型，只需注册开发者密钥，就能开始发送请求。

You have models that are available behind APIs that are hosted where, you know, you sign up for a developer key and, you know, just start making requests.

你还可以获得大量开源模型，这些模型覆盖了从通用型到特定任务设计的广泛范围。

You have, like, a huge catalog of open source models that are, you know, on on a spectrum from, you know, general purpose to, like, very specific tasks, design things.

因此，你不需要一开始就想着必须从零开始训练一个模型。

And so, like, you just have a lot of choice where you don't have to start by saying, I've gotta train a model from scratch.

对。

Right.

对。

Right.

所以我认为这是一个巨大的优势。

And so I I think that is a huge advantage.

这和二十年前我写第一个机器学习程序时的情况完全不同。

Like, it's definitely not the way things were twenty years ago when I wrote my first machine learning programs.

甚至和三四年前的情况也不一样。

It isn't even how things were three or four years ago.

对。

Right.

即使那时也大不相同。

Say it's was a lot different even then then.

正如你所说，现在人们比三四年前更容易构建出优秀的东西。

It's much easier for people to build really good things now versus three or four years ago to your point.

是的。

Yeah.

我的老板萨提亚·纳德拉最近讲过一些关于他访问印度的故事，他看到人工智能应用在那里的普及速度之快，是他前所未见的。

I mean, my boss Satya Nadella tells stories about his visits to India recently where he has seen the just rapid diffusion of AI applications at a pace that he's never seen before.

他提到的一点我觉得非常好：在印度一些农村地区，工业革命至今仍未到来，已经250年了，但那里的人们却已经开始接触人工智能——农民通过手机就能访问一个强大的AI系统，帮助他们了解自己有权享受哪些政府项目，并协助他们注册申请，从而获得政府原本打算给予他们的福利。

The thing that he says, which I think is really good, is there are parts of rural India where the industrial revolution still hasn't shown up after two fifty years, where they already are seeing the diffusion of AI, where a farmer through their mobile device can access a powerful AI system that will help them understand how they are entitled to government programs and then go sign them up for them so that they get these benefits that their government intended them to have.

这种普及速度真是令人震惊。

And that's just shocking rate of diffusion.

但这也并非全是好消息。

But it's also not all good news.

我认为，虽然构建人工智能应用所需的专业知识正在以极快的速度普及，人们可以轻松访问API和构建这些应用所需的基本基础设施，但你仍然必须有网络连接。

I think while expertise required to build an AI application is democratizing super fast and you've got, like, high levels of accessibility to the APIs and, you know, basic infrastructure required to go build them, you still have to be connected.

有网络连接。

Connected.

你仍然需要具备一定的技术基本素养，才能使用这些系统。

Still have to, like, have some baseline level of technology fluency in order to be able to use the systems.

事实上，世界上还有很多地区尚未实现充分的网络连接，技术素养也远未达到应有的水平。

And, like, the reality is there are large parts of the world that are not yet sufficiently connected and where, like, that technology fluency isn't as good as it should be.

因此，我认为，眼下还有很多非常枯燥但至关重要的工作需要我们优先推进，比如专注于农村宽带建设。

And so, you know, I think, yeah, there there's a bunch of, at this point, deeply unsexy work that we still need to prioritize and and make sure that we're focusing on things like just rural broadband.

嗯。

Mhmm.

我以前 definitely 讲过这个故事，但确实，我妈妈和弟弟住在弗吉尼亚州中部的一个小镇，他们很幸运，住得离当地电信交换站不到一百码，所以网络很好。

You know, like, I've definitely told this story before, but, yeah, my mom and brother have good Internet in this rural town that they live in in Central Virginia because they're lucky enough to live within a 100 yards of the local telco exchange.

而我叔叔住的地方离他们只有几英里远，却还在用那种糟糕的300K DSL网络，他的网速几乎没法用。

My uncle who lives just a few miles away from them is still on some kinda, like, crazy 300 k DSL connection, and, you know, his Internet is barely usable.

所以他不得不去我妈妈家上网办事。

And so, yeah, he has to come to my mom's house to do things on the Internet.

真是荒唐。

So nuts.

所以，我认为我们必须高度重视这类问题，因为随着网络连接所能提供的功能和能力越来越强大，缺乏网络连接的劣势也会变得越来越严重。

And so, like, that that's the sort of thing that I think we really have to pay attention to because as the things that you can do and the capabilities you can access with that connectivity become more powerful, like absence of connectivity, like, becomes a bigger and bigger disadvantage.

不。

No.

我的意思是，你说得完全对。

I mean, think you're exactly right.

这是一场我觉得我们在这个播客里确实讨论过的话题，但我觉得，作为整个行业和社会，我们至少已经谈论了二十年了。

And this is a conversation I feel like, you know, we've definitely talked about this on this podcast, but I feel like, we collectively as, you know, an industry and society have been talking about this for at least twenty years.

而且，这变得越来越重要，我们必须真正投资于克服这些基础设施挑战，因为连接性只会变得更加重要。

And and it's only becoming more and more important, right, to start to really invest in in overcoming these these infrastructure challenges just because connectivity is only going to be more important.

对吧？

Right?

我认为这是一个很好的区分：用这些工具来构建应用程序和相关东西比以往任何时候都更容易，但真正把它们带给用户，让他们能够使用，可能是不太有趣的部分，但 arguably 更加重要，因为没有它，我们所做的一切都变得毫无意义。

I think that's a a great distinction that it's easier than ever to, you know, build, you know, applications and and things with these tools, but actually getting it to people and and making it so that they can interact with them, is is the maybe the less, fun part, but but arguably even more important because without that, we've, you know, all of this is is moot.

是的。

Yeah.

没错。

Yep.

好吧。

Alright.

彼得的问题。

Question from Peter.

他问：我很想知道微软是如何对其自身基础设施、LinkedIn、Xbox、Office 365 等系统进行技术测试的。

He asks, I'm curious about how Microsoft approaches running technical tests against its own infrastructure, LinkedIn, Xbox, Office three sixty five, and others.

考虑到这些系统的规模和复杂性，多年来在管理这些基础设施的过程中，你们学到了多少经验教训？

Given the scale and complexity of these systems, how many lessons have you learned over the years while managing that infrastructure?

他还进一步问：对于从事 DevOps 的我们来说，你们遇到的最令人惊讶的教训是什么，可能会让我们措手不及？

And he goes on to ask, and for those of us in DevOps, what is the most surprising lesson that, you've encountered that might catch us off guard?

天啊。

Oh, god.

这是个非常好的问题。

That's a super good question.

这个问题非常复杂，我不确定自己能否完整回答。

Very complicated, so I don't know whether I'm going to be able to answer the whole thing.

本来想说，如果你把这个问题分成几部分来看，就这么做。

Was going say, if think this in parts, do that.

就这么做。

Do that.

没关系。

That's okay.

是的。

Yeah.

听我说，我曾经有个老板，可能是我职业生涯中遇到过的最出色的DevOps领导者。

Look, so I had a boss who was, like, maybe the best DevOps leader I've ever worked, for or with in my career.

他有一些非常简单的话，用来阐述如何从哲学层面看待DevOps。

And he had a bunch of very simple things that he would say about philosophically how you should approach DevOps.

他曾经说过，如果你不进行测量，就无法修复或改进任何东西。

One of the things he says is or said is you can't fix something or improve it if you're not measuring it.

所以，对这个问题的大部分回答归根结底就是：你的指标够好吗？

So a lot of the answer to the question just boils down to like, are your metrics good?

你正在监控系统中发生的所有事情吗？

Are you measuring everything that's happening in your system?

你是否基于这些指标建立了良好的监控系统？

Do you have good monitoring built on top of the metrics?

你是否能清晰地了解所有系统的内部状态？

Do you have good visibility into the internal state of all of the systems?

这是非常重要的一点。

That's one thing that's super important.

另一个要点是，复杂性必须有其理由。

Another thing is complexity needs to have a reason.

很多时候，复杂性只是自然而然地出现，因为从架构上讲，最方便的做法往往是把新东西直接叠加到旧系统上，而不是去做更困难的工作——比如，我们现在的系统需求已经发生了变化。

And so a lot of times, complexity just emerges because the most convenient thing to do to systems architecturally is often to just append new stuff onto old rather than to do the harder work of, okay, we've got some evolved requirements here.

现在的情况和我们最初设计这个系统时已经不同了。

Things are different from when we originally designed this system.

现在我们需要暂停一下，重新梳理整个系统，确保它以最简单的方式设计，以满足我们现在所理解的新需求。

Now we need to push pause and go refactor the whole system and make sure that it's designed in the simplest possible way to meet the new set of requirements that we now understand.

因此，我一直努力在我所领导的组织中确保为处理技术债务预留一部分工程能力，让团队专注于构建共享基础设施，他们的职责不仅是为所有人提供一系列服务，更要以架构上极其简洁的方式构建系统，确保系统具备稳健性、可维护性、可扩展性、安全性以及容错性等你希望系统具备的特性。

And so one of the things that I've always tried to do in the organizations that I've led is to make sure that you are reserving some amount of your engineering capacity to go deal with tech debt, that you've got teams who are building shared infrastructure, whose job it is not just to provide a set of services to everyone, but to like be building things in a really architecturally simple way and to make sure that things are robust, maintainable, scalable, secure, fault tolerant, of the things that you want out of your systems.

你必须时不时地重新构建一些东西。

You just got to rebuild stuff every now and again.

尽管听起来很痛苦，但当你面对产品经理催促你赶紧上线新功能，或者盯着短期收入时，你仍得告诉所有利益相关者：嘿。

Like it it's painful as it may sound, you know, when you've got product managers screaming at you that you like, you need to go ship, you know, this new feature or, you know, you're eyeballing, you know, short term revenue or something like that to, like, go tell all of your stakeholders, hey.

我们需要暂停一下，重新架构这个系统。

We gotta go push pause on this for a little while while we, like, rearchitect this thing.

你必须这么做，因为复杂性才是真正的问题所在。

You just have to you have to do it because complexity really is the it's the killer.

是的。

Yeah.

不过，我们现在正用人工智能处理一些复杂性问题。

There's a bunch of stuff that we're doing with AI right now, though, to deal with some of the complexity.

当系统中存在复杂性时，它是无法消除的。

So it can when you have complexity in systems, it's irreducible.

你根本无法通过设计来规避它。

You just can't figure out how to design away from it.

AI 可以帮助管理一些复杂性。

AI can help manage some of the complexity.

它并不是让你把 AI 当作一个抽象层，躲在后面而不理解你的系统，而是帮助你快速地进行问题分类，或者找出操作问题的根本原因之类的事情。

And it's not in a way where you're you know, letting this AI be an abstraction layer that sits between you and your understanding of your system, but to like help you just very quickly, like, you know, triage things or, you know, figure out like how to, you know, root cause, operational issues or whatnot.

在这方面，它非常有帮助。

It can be super helpful with stuff like that.

是的。

Yeah.

我的意思是，我光是谈这一堆问题就能说上一整天。

I mean, like, I I look, I I could go on all day about this particular bag of bag of issues.

但没错。

But yeah.

我的意思是，你就是得不停地测试，测试，再测试。

I mean, like, you you just gotta you just gotta test, test, test.

而且，你看，这里有个问题。

And, like, you know, here here's a, you know, a thing.

也许我以前遇到过这种情况，人们构建了某些系统或功能，专门应对罕见情况，比如数据中心级别的容错能力。

Maybe this is I I have gone into situations before where people have built systems or built functionality that are designed to do a thing, in rare circumstances, like, you know, sort of data center level fault tolerance, for instance.

所以，如果整个数据中心宕机了，断电了，或者光纤被切断了，团队测试一次后就假设这个功能会永远可用，仅仅因为它曾经成功过一次。

So, like, what happens if this whole data center goes down, if it loses power or if, like, there's a fiber cut or something where the team tests the functionality once and then assumes that it's going to be available forever and ever just because it worked one time.

对。

Right.

对。

Right.

所以，你真的必须测试那些不常发生的情况，确保当这些罕见情况真的发生时，你已经做好了准备，这意味着你需要比自然发生频率更频繁地模拟这些罕见事件。

And so yeah, you you just gotta you you gotta test for infrequently occurring things and make sure that when the infrequently occurring thing happens, that you are ready to go, which basically means you need to simulate the infrequent thing more frequently than it will naturally happen.

我觉得对一些人来说，这有点反直觉。

That's like a counterintuitive thing, I think, for some folks.

是的。

Yeah.

不，就是这样。

No, that is.

但我喜欢这一点。

But I like that.

我认为这很好地回答了这个问题，因为这确实看似反直觉，但很有道理。

I think it probably answers this question really well because that does seem counterintuitive, but it makes sense.

你需要确保当这种情况真正发生时，系统能够正常运行。

You need to make sure that when this actually occurs, that it's going to work.

但要做到这一点，就像消防演习一样。

But to do that, it's like fire drills.

你们会尽可能比实际情况更频繁地进行演练，以防万一，确保随时做好准备。

You do them hopefully much more frequently than they actually occur just in case, just if you need to be ready.

是的。

Yeah.

我只想说，在领英，我们过去每周都会在随机时间点直接关闭整个数据中心，以确保所有容错系统都能正常工作。

I just gonna say like at LinkedIn, we used to, at random points every week, just take a whole data center offline to make sure that all the fault tolerance systems would work.

好吧，太棒了。

Okay, that's awesome.

这太疯狂了。

That's wild.

这个流程是在你加入之前就有的，还是你要求他们这么做的？

And was that a process that started before you joined or was that something that you asked them to do?

我只是很好奇。

I'm just curious.

这是我要求他们做的。

That was a thing I asked them to do.

太棒了。

Amazing.

太棒了。

Amazing.

是因为这个原因吗，只是因为你希望确保

And was it for that reason just because you wanted to ensure that

是的。

Yeah.

是正确的。

Was correct.

这是因为实现起来非常困难。

It was because is a super hard thing to achieve.

所以这不是一种你可以随便注册就能获得弹性的服务。

So it is not a service that you can just sign up for and get resilience.

这意味着数据中心中运行的每一件事都必须具备弹性。

It basically means that every single thing that's running in the data center has to be resilient.

它必须能够应对最糟糕的故障情况，这包括数据库、网络和存储系统等明显需要处理的方面，还有许多经典的计算机科学和工程方法可以用来使这些系统具有容错能力。

It has to be prepared to deal for things to fail in the worst possible way, which means obvious things for things like databases and networks and storage systems and whatnot, and there's a bunch of super classic computer science and engineering stuff that you can go do to make those things fault tolerant.

但你还需要让你的应用程序具备容错能力。

But you also have to make your applications fault tolerant.

如果用于向用户呈现体验的应用服务器突然失去所有网络连接，会发生什么？

What happens if an application server that's rendering the user experience to a user, what happens if it loses all network connectivity?

会发生什么？是否在最终用户使用的应用程序中存在某个路由层，能够察觉到它与应用服务器的连接已无响应，并将请求转向服务目录中另一个数据中心的另一台服务器？

What happens Is there some routing layer somewhere maybe in the end user application that the user is using that will notice that its connection back to its application server is no longer responsive and it routes it sideways to another server somewhere in the service catalog in another data center.

所以你必须仔细思考所有这些情况。

So you just have to think through all of this stuff.

这个系统的每一个组成部分都要考虑到，而且必须让每个服务的所有者对其完成这项工作负责。

How is every single piece of this system and you have to have every single service owner accountable for having done that work.

确保他们完成工作的绝佳方法是，不提前告知他们，直接直接关停整个系统，这样你就能立刻知道他们的应用程序是否足够健壮。

A real good way to make sure that they've done the work is without telling them, you just kill the whole system and you'll know real quick whether their application is robust or not.

我喜欢这个。

I love it.

我喜欢这个。

I love it.

很高兴你实施了这一点。

I'm glad you implemented that.

我的意思是，我认为这证明了领英在许多需要高在线时间的服务和公司中，已经很好地覆盖了这些服务，而这些公司过去并不总是拥有良好的正常运行时间。

I mean, I think it is a testament to LinkedIn that it is one of covered many of these services and worked on companies that need to be online a lot that have not always had great uptime.

LinkedIn 是我所经历过的、拥有非常非常良好正常运行时间的公司之一。

LinkedIn is one of the ones that has, at least in my experience, had very, very good, uptime and those sorts of things.

我认为这很可能归功于这些演练。

And I think that's probably a testament to the to the drills

但现在并不总是如此。

Now, but not not always.

是的。

Yeah.

但这就是你达到这种状态的方式。

Well, but but that's how you get there.

对吧？

Right?

我想，就是得时刻做好最坏的打算，系统随时可能崩溃。

I guess is by having to just at the top of hat, it could be gone.

你打算怎么恢复？

How are you gonna recover?

嗯。

Yep.

我喜欢这个。

I love that.

我喜欢这个。

I love that.

好的。

Alright.

这个问题来自萨曼莎，她问：我注意到你最近邀请了几个非典型技术人士作为嘉宾，比如本·拉登和拉菲克·安达尔。

This question is from Samantha and she asks, I've noticed you've had a few recent guests that aren't typical technologists like Bin Laden and Rafiq Andal.

你能分享一下你对创意型领导者在科技和人工智能时代如何工作的想法和观点吗？

Could you share more about your thinking and perspective on how more creative leaders are working in the era of tech and AI?

嗯。

Yeah.

说实话，部分原因是，这些人是我很想和他们交谈的人。

Like, part of it is, like, just to be perfectly honest, like, these are people that I wanna talk to.

嗯。

Yeah.

我觉得这些对话很有趣，我想分享它们。

And I think the conversations are interesting and I wanna share them.

但我觉得，我们一直在谈论一件事，那就是在人工智能时代，技术专家和非技术专家之间的界限正在以一种深刻的方式模糊化。

But I I think, you know, there there is this thing that we have been talking about which in the era of AI, this distinction between, you know, like, who's a technologist and who isn't is, like, blurring in a really profound way.

所以我觉得与更多样化的人交谈是很好的，比如拉菲克，他是一位受过训练的艺术家，但他正以极其复杂的方式运用技术来实现他的艺术愿景。

And so I I I think it's good to be talking to a broader variety of people because you have, like, Rafiq, for instance, is a trained artist, but he's using technology in incredibly sophisticated ways to realize this artistic vision that he has.

我认为随着时间的推移，这样的情况会越来越多，因为过去令人望而生畏、难以接触的技术正变得不那么可怕、更加易用，这意味着更多人会用它来做更广泛的事情。

And I think there's just gonna be more and more and more of that over time because this previously, you know, daunting and inaccessible technology is becoming less daunting and more accessible and which means that more people are gonna be using it to do a broader swath of things.

那么，拉菲克到底是一位艺术家，还是一位技术专家呢？

And so, you know, like, is is Rafiq an artist or a technologist?

你知道，也许这并不重要。

Like, you know, maybe it doesn't matter.

他只是在做令人惊叹的事情。

He's just doing amazing stuff.

你知道吗，我和本·劳蒂的这次对话，让我一直思考艺术的本质，以及艺术和工具之间究竟有什么区别。

You know, and, like, this conversation I had with Ben Lauti is, like, I I think all the time about what the nature of art is and, like, what what are the, you know, what are the things what's the difference between, you know, art and instrument?

那么，表演者和工具之间的界限又在哪里呢？

And, like, what's the boundary between performer and instrument?

所以我觉得，让艺术家来谈谈他们长期以来在艺术和技艺中对这些关系的思考，以及在人工智能时代这些思考如何发生变化，这非常有趣。

And so I think it's interesting to have artists come in and talk about how they're thinking about those relationships, you know, that they have had in their art and in their craft for a very long while, and then, you know, how that thinking is changing in an era of AI.

因此，我觉得现在进行这些对话至关重要。

So I just feel like they're super important conversations to have right now.

不，你说得对。

No, think you're right.

我认为，或许打破这些界限是有意义的，我不知道这是否重要，对吧？

And I think that breaking down maybe this demarcation in places, I don't know if it matters with yes, Right?

这可能就是这两个问题的答案。

That that could be the the the answer to to both questions.

因为这些界限，当技术真正变得普及，成为我们每个人自然而然融入的一部分时，它就不再是什么外在的东西了。

And because the these lines, I mean, when technology truly becomes accessible and and kind of, something that that we all sort of kind of imbibe, it's it's not it becomes just a part of us.

对吧？

Right?

就像，我们常常设立的人为界限会消失，你就是一个创作者，就是一个普通人，你知道的，没错。

Like, it we the and I think that the oftentimes artificial barriers that we put into place disappear and it's just like you're a creator, you're a person, you know Yeah.

无论你如何到达那里，无论你做什么。

Regardless of of how how you get there and and what you do.

你不需要非得被困在某个框框里，或者那个框框里。

You know, it doesn't have to be, oh, I have to be in this box or this box.

不，不是这样的。

It's like, no.

我只是，嗯。

I'm just Yeah.

我只是在创作。

You know, I'm just creating.

我还想说的是，我对一些事情有着非常强烈的观点。

The thing that the thing that I will also say is, like, I I have super strong opinions about some things.

例如，如果没有人运用人工智能去做一些有趣的事情，我对人工智能完全不感兴趣。

For instance, I'm not interested in AI at all absent a human wielding the AI to do something interesting.

我并不是在声称每个人都必须和我想法一致，但让我觉得有趣的是，这个观点并不是我经过深思熟虑后才形成的。

Now, I'm not claiming that everybody needs to be my way, but it's just interesting to me that this isn't a point of view that I came to through some huge process of deliberation.

我只是觉得，如果没有任何人类创作者的参与，仅仅由一个自主的AI生成艺术、音乐之类的东西，我根本提不起兴趣，因为我发现，我之所以能与艺术体验产生连接，部分原因在于我喜欢知道：这是一个人的作品，他是如何创作的，他在创作时可能在想什么，我们是否相似，又是否不同？

It's just like I am not interested in the idea of some autonomous AI spitting out art or music or whatnot absent the hand of a human creator because I've discovered part of my connection to the experience of experiencing art in the first place is I like to know, this is the human and this is how they made it and this is imagining what they must have been thinking and are we alike, are we different?

你喜欢这个故事吗？

You like the story?

我喜欢这个故事。

I like the story.

机器人创作的？谁在乎呢？

The story of the robot made this, who cares?

对。

Right.

不。

No.

而且我觉得这是一个很好的观点。

And I and I think that's a great point.

对吧？

Right?

这是一个非常有趣的视角，因为显然，有人可能会说，如果完全由人工智能自主生成，也可能产生某种艺术性的东西。

And that's a really interesting perspective because obviously, I I mean, I think there's an argument to be made that there is something artistic that could be made if it were completely, you know, autonomously generated.

拥有这样的东西确实很有趣，但我倾向于同意你的看法。

And that's an interesting thing to have, but I I tend to agree with you.

比如，我最感兴趣的、超越抽象层面的那些内容，绝对是那些有人类引导的作品。

Like, the stuff that I'm interested in consuming the most outside of kind of like an abstract level is definitely the stuff that has been guided by a human.

但如果这项技术能让事物更独特、更有效，或者为某事物增添不同的细微差别，那可能会带来很棒的结果。

But if the technology if the AI can make things more unique or effective or just add a different nuance to something, that can lead to a great, you know, outcome.

所以，或者至少是有趣的。

So or interesting anyway.

所以，是的。

So yeah.

是的。

Yeah.

这是一个有趣的争论，因为我不知道是我对还是你对，实际上我确实和一些人争论过，他们会说，‘你疯了。’

It's an interesting debate because I I don't know whether I'm right or you're right or, you know, I I do actually have this argument with people who, like, will say, like, hey, you're crazy.

就像，你知道的，是的。

Like, you know, the the yeah.

你可能会拥有某些有趣、有艺术性且值得称赞的东西，而它们并不需要……嗯，好吧。

You you could have something that's interesting and artistic and merit worthy that doesn't have and it's like, okay.

很好。

Great.

这个争论很有趣，对吧？

The argument is interesting, right?

确实如此。

It is.

它让我们思考这些事物的本质是什么。

It tells us something about what are the nature of these things.