跟读练习: Cloud Providers are changing RAPIDLY [REUPLOAD] - 通过视频学习英语口语

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Cloud providers like Vercel, Cloudflare, but even AWS, to some extent, are changing rapidly, at least some of them, rapidly.
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And I think that's good for us developers.
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It's also worth a closer look. Now, cloud providers are changing because we are changing as developers because, of course, what's changing right now is what we're building and also how we're building. Both things are changing right now. What we're building is, of course, to some degree what we built before, software, web apps, and so on. So that, of course, to some degree has not changed, but we're building more because AI agents make it easier to build stuff. And let's be honest, there's a lot of stuff, a lot of applications and demos in there that will or at least should never see the light of day.
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But we're building more because AI agents make it easier.
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White coding, of course, is a thing.
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Maybe not the thing you wanna use primarily for serious projects, for serious software, which you plan on selling or distributing, but of course, white coding can be absolutely fine for your own little internal tools, some throw-away software that solves specific problems where you don't care about covering all niche cases or about security or anything like that. So we got that, and therefore, we are of course building more. And then, of course, we are building AI agents and agentic apps, whatever that means. But in the end, it means applications or tools, workflows, whatever you wanna call it that wrap large language models, that wrap AI and then do something potentially agentic where you potentially are building something where an AI can call tools, dispatch tasks, work with a file system and so on. So, that's the what part that is changing. But, of course, the how is also changing because we are, or at least many of us I guess, no longer are writing the code by hand. We're not doing that anymore, at least not 100% of the code. Instead, we are using AI agents like Claude or Codex or whatever you are using, and of course, we're letting those agents do more and more. So, you may use them to write code but maybe you also let them run all kinds of CLI commands and tools on your system, starting with Git for committing and pushing, which is relatively trivial and easy, all the way up to deployment maybe.
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You may not just be using those agents for generating the code.
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You may also be using them to generate docker images or to use CLI tools that push the code, that push the applications to some hosting provider. And that takes me back to the cloud and how cloud providers are changing.
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Vercel itself rebranded itself to be all about agentic infrastructure.
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If you visit vercel.com, that is the first thing you read right now. And on the right, you see "For coding agents, to ship apps and agents automated by agents." So (laughs) here we got the word "agents" in that box three times and they are clearly talking about being the platform for anything built by agents, including agents themselves. Now, it's pretty similar for Cloudflare.
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If I visit cloudflare.com right now, I see this message where I learn that "Cloudflare is one platform for my apps, agents and workforce." So, definitely a bit less agentic-first or AI-first, but we got the word "agents" right here in the main messaging as well. And we'll also see it when we take a look at the services offered by these cloud providers that they're changing quickly. Now, Netlify is also mentioning AI but not the word "agent" here.
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They are still mostly about serving your apps, your web apps, that may have been built with AI but not so much about running AI agents in the cloud and I'll get back to why that matters. And if we take a look at AWS as a last example here, I also right now when I visit this, have the word "agent" in the, in the main message I see, that I can "move at the speed of agents." Now, what is important here or what's interesting and what is of course related to what we're building and how we're building, is that all these cloud providers, I would say, nowadays have three main pillars.
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The, the first pillar is about apps and that is of course what they were always about. Now, a little side note, of course, AWS is a bit hard to compare to Vercel and so on because it's more complex. It's more about having tons of primitives and managed services. It's about all those enterprise customers, not to say that Vercel doesn't have enterprise customers, but AWS is all about giving you all the building blocks you could potentially ever want to build any kind of system in the cloud.
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And therefore, they were never primarily or only about running web apps or... ...
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other pieces of software in the cloud.
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They were about giving you the tools you need to do anything in the cloud, to store any kind of data there, run any kind of workflow. Vercel, Netlify, and also Cloudflare, of course, were more about, "Hey, you got a web application? Run it here." Not just about that, of course, but that was definitely more of their focus.
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So I'll primarily talk about apps here, and when I mean apps, I mean, of course, web apps, websites, whatever you wanna call it.
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So that is what we use these cloud providers for, and that, of course, has not really changed. You can and you will still use them for that, and it doesn't really matter how you built those apps, right?
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If you use Cloud Code or Codex, the thing that maybe is a bit easier now, and where I actually like AI a lot, is that deployment gets easier because you can point Cloud Code or whatever at the relevant documentation pages.
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You can install the CLIs. You can install the Vercel CLI, the Cloudflare Wrangler tool, and so on, and if you get that installed, if you give the agent some, some hints at where to search for, for deployment details and instructions, it can do the deployment for you, or at least it can prepare it for you.
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It can write configuration files.
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That all gets a bit simpler because, let's be honest, deployment can be a bit of a pain if it gets a bit more complex, and AI can definitely help a bit there. Now, just as with web coding, obviously, you still wanna understand what's going on, at least I want to understand what's going on, but it can help there. So that pillar, of course, still exists.
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Now, the second pillar, which we now have, however, which is new, is agents or AI agents, that you run those in the cloud because, of course, we're at this point in time where we're, for one, still trying to figure out how exactly we'll work with AI as developers.
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But we're also at this point where we're all, or where all the companies are, about building AI agents, and it's sometimes hard to grasp what exactly you wanna build and what exactly those agents should be doing for you.
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But at least from the perspective of a CEO, you might have an, a marketing agent. You might have an agent that, uh, does customer support, a finance agent that helps out in your finance department, and so on.
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And as a developer, you may have an agent that tackles open issues on your GitHub repository.
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You may have another agent that does research, and these agents need to run somewhere. Now, obviously, they can run on your system.
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That will be a bit harder if you're working in some bigger company where you don't have unlimited privilege and can't install everything you want on your system. But even as a small developer, running everything on your system has, of course, some security implications.
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If you have an AI agent roam around on your system, it can potentially do damage accidentally or because of prompt injections and so on. So you may want an environment where it can safely operate or where it can't do as much damage. Now, there are loads of different solutions out there. You could look into tooling like Just Bash, which is, interestingly enough, also by Vercel, by the way.
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They are releasing many tools, uh, that aim to make development with AI easier. And Just Bash essentially is a, a sandboxing solution, which you can run on your system to run an agent inside of a virtual bash with limited privilege and so on.
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So you could use tools like that, but, of course, you could also run those agents in the cloud, or you could have a combination and have an agent that runs locally offload certain tasks to the cloud. So the Cloudflare Sandbox SDK, for example, aims to simplify the process of running tasks, agentic tasks, with an AI agent doing its thing in the cloud, where you can then potentially expose R2, Cloudflare R2, which is their S3 equivalent, as a file system and so on, so that you have a throwaway environment where an agent can do whatever you wanna do.
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If it breaks stuff, it doesn't matter because you can just restart the Sandbox and you don't expose your entire system.
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And that, of course, therefore is a brand-new category of things you wanna deploy to the cloud or you wanna run in the cloud, and that is definitely where Vercel and Sandbox are moving towards. They want to not just make it easy for you and your agents to push web apps and apps to the cloud. That's also something they wanna do, but not just. But instead, they also wanna make it easy for you to run AI agents you may have built in the cloud.
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And then there is a third pillar, I think, and that's the AI gateway pillar, or however you wanna call it.
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You know, we got all these AI providers.
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We got proprietary providers, obviously, like OpenAI, Anthropic, Google, and then we got some open-source models, which may be open source or open weight, but running them on your system can be tricky depending on the size.
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Now, I do have various courses, obviously, including on ChatGPT, uh, the advanced guide, Cloud Code, but I also have a course about running local large-language models because I'm a big fan of those open-weight models where you can really just run them with Ollama or LM Studio or other tools on your system. But, of course, for most systems at least, you are limited to the smaller models, which can still be helpful as I show in this course.
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But if we're talking about bigger models, you will still likely want some provider that hosts them for you so that you can access them through the cloud.
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And no matter if we're talking about those open models, which you can't or don't want to run on your system, or if we're talking about many of the proprietary models, these providers, like Cloudflare, but also Vercel and also AWS, they offer services...
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That could be called AI Gateway in the case of Cloudflare or for AWS, it's Amazon Bedrock. But these are simply services that are all about accessing AI through one uniform API where you can basically just switch one value and switch to a different provider, where billing is done through Cloudflare or AWS. And where it's, therefore, easier to access a broad variety of AI models which are easy to monitor, easy to switch, where you don't need to create, uh, tons of accounts with OpenAI, with Anthropic, with Google, with whatever other provider you want.
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Think of it as OpenRouter!, essentially.
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OpenRouter!, of course, is a service that makes it easy to switch between different models and Cloudflare, Vercel, AWS, they essentially have their own OpenRouter!-like solution, you could say. There are some differences because OpenRouter!
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is really just a router, which is about funneling your request to different providers. Whereas, Cloudflare and AWS, for example, they also provide hosting for these models. So with Amazon Bedrock, for example, you can access Anthropic models that are hosted on AWS infrastructure, whereas a customer you can control in which region it should be hosted, where you have greater, uh, control over where your data gets stored or who gets access to your data.
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And that, of course, can matter to enterprise customers.
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So it's actually a combination of things here.
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It's convenience, obviously, because it's easier to switch between different models. You can even set up routing rules where different requests may get different models automatically.
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You have a, a unified billing experience.
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But besides the convenience, it's also about more control over where the model is hosted and so on, at least for some of these providers. And I think, therefore, these are the main pillars we see right now for these major cloud providers, and I find it quite interesting that, for example, Netlify is still mostly about that first pillar here. It's their decision, their strategy, whereas Cloudflare and Vercel and AWS and many others, by the way, are, of course, branching out and are trying to cover all three pillars.
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Now, I think, as a developer, no matter if you're building AI agents or not or... and, and no matter if you're working with AI or not, these are great developments. Because one s- nice side effect is that these cloud providers, in their effort to make it easier for AI agents to use them, are giving us more ways of accessing their services. They are improving their CLI tools, their documentation to provide (laughs) all that information to agents, which, spoiler, you as a human can also read.
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So that's pretty nice. And they're building more useful primitives. I mean, Cloudflare alone...
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And just to be super clear, this is not some paid advertisement or anything like that. These are really just services I'm using.
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But Cloudflare alone, they released so many new nice services, like dynamic workers, where one worker, which is like a, a serverless solution provided by them, where you can execute code in the cloud, where one worker can spin up more workers to offload certain tasks. No matter if you're building AI agents or not, this can be a useful feature. If you're building any kind of service or tooling where your customers can maybe share some data or code with you or where you wanna execute some code that involves customer data or customer code, it's nice to have primitives where you can securely do so in throwaway environments. And therefore, these new capabilities are pretty nice to have, even if you don't care about AI at all, even if you're not building AI agents.
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And that's why I'm pretty excited about these changes in cloud providers and why I think it's more interesting than ever to play around with different providers.
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If you've used Netlify forever, maybe give Vercel or Cloudflare a try and dive back into their docs, maybe together with AI to understand what they offer and how you can build on top of them.
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Anyways, that's just something I'm observing, something I'm pretty excited about. And as always, I'm interested in hearing your perspective on that and what I maybe missed or what you think about this transformation of cloud providers and where we're heading to.

为何这个视频是绝佳的口语练习素材?

这个视频讨论云计算提供商的变革,内容贴近科技前沿,对话自然流畅,充满真实的口语表达(比如笑声、重复强调),非常适合用来练习英语影子跟读。它的语速适中,逻辑清晰,既有专业术语(如AI agents、CLI commands),也有日常表达(如“let's be honest”),能帮助学习者兼顾词汇积累和口语流畅度。对于准备雅思口语练习的同学,这种兼具信息密度和口语化的内容,还能锻炼描述趋势、分析现象的能力,一举多得。

拆解自然表达,学习地道口语

我们来看看视频里的几个精彩表达:

  • “Cloud providers like Vercel, Cloudflare, but even AWS, to some extent, are changing rapidly, at least some of them, rapidly.” 这里重复“rapidly”并加入“at least some of them”,是典型的口语修正,让表达更准确,也更符合日常说话习惯。练习时注意这种自然的重复和补充,避免过于生硬。
  • “So (laughs) here we got the word 'agents' in that box three times...” 笑声和“so”的使用让对话更生动,体现说话人的思考过程。影子跟读后要模仿这种语气,让口语更有感染力。
  • “But we're also at this point where we're all, or where all the companies are, about building AI agents...” 这里的停顿和“or”的替换,是口语中常见的表达调整。学习这种灵活的句式变化,能让你的口语更接近母语者水平。

简单高效的影子跟读练习法

利用这个视频做shadow speech,只需三步:

  1. 先完整听一遍视频,理解内容大意,标记出生词和难句。
  2. 逐句跟读:播放一句,暂停,立即重复,注意模仿语调、语速和停顿。重点练习带笑声、重复的句子,感受口语的自然感。
  3. 录音对比:用手机录下自己的跟读,和原视频对比,找出发音、节奏的差异,针对性改进。每天练习10分钟,一周就能明显感受到流畅度提升。

如果觉得逐句困难,可以先用shadowing site调整播放速度,从0.75倍速开始,逐渐过渡到原速。坚持练习,你会发现不仅口语变好了,听力和理解能力也同步提升,轻松应对各种英语交流场景!

视频中的语法

说话人最常用的结构,并附上视频中的原话:

结构视频中的用法
定语从句 who / which + 从句 — 补充说明人或事物pushing, which is · however, which is · Bash, which is
被动语态 be + 过去分词 — 强调发生了什么,而不是谁做的have been built · are limited · could be called
现在完成时 have/has + 过去分词 — 过去发生但与现在仍有关联的事has not changed · has not really changed · have unlimited

什么是跟读法?

跟读法 (Shadowing) 是一种有科学依据的语言学习技巧,最初开发用于专业口译员的培训,并由多语言者Alexander Arguelles博士普及。这个方法简单而强大:您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同,跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性,语调,节奏,连读,听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。

影子跟读法: 阅读完整分步指南 →