generative AI

Welcome to generative AI for everyone. Since the release of ChatGPT, AI specifically, generative AI has caught the attention of many individuals, corporations, and governments. It is a very disruptive technology that's already changing how many people learn and work. Many developers think that generative AI will empower many people and lead to productivity gains, and also make a significant contribution to global economic growth. But there could be downsides as well, since it's job loss or worse that some people worry about. In this course, you learn what generative AI is. What it can and cannot do, and also how to use it in your own work or business. Because generative AI is so new, there is still a lot of misinformation out there, and so in this course, I hope to convey an accurate non-technical understanding of what it really is. It also work of you to think through how you can best make use of this technology. This course does not assume any technical or AI background and is designed to be useful to anyone in business, science, engineering, the humanities, arts, or other sectors so that, let's dive in.

欢迎来到全民生成AI。自OpenAI发布ChatGPT以来，AI特别是生成AI已经引起了许多个人、企业和政府的关注。它是一项非常具有破坏性的技术，已经改变了很多人的学习和工作方式。许多开发者认为，生成AI将赋予许多人力量，带来生产力的提升，并对全球经济增长做出重大贡献。但也可能会带来一些不利因素，例如失业或更糟糕的后果，这让一些人感到担忧。在这门课程中，您将学习生成AI是什么，它能做什么，不能做什么，以及如何在自己的工作或业务中使用它。由于生成AI是如此新颖，仍然存在许多错误信息，因此在本课程中，我希望传达一个准确的非技术性理解。它也能帮助您思考如何最好地利用这项技术。本课程不需要任何技术或AI背景，旨在对商业、科学、工程、人文、艺术或其他行业的任何人都有用，那么，让我们开始吧。

Generative AI had caught the mainstream attention starting around November 2022 when OpenAI released ChatGPT and its momentum has continued unabated according to McKinsey, it could add $2.6 to $4.4 trillion annually to the economy. Goldman Sachs estimates it could raise global GDP by 7% in the next decade, and a study by OpenAI and UPenn estimates that it could impact 10% of the work or tasks carried out daily by over 80% of workers in the United States. The same study also estimates that there is a 20% of workers whose work or task is more than 50% impacted by generative AI, and so studies like these lead to hope for a tremendous productivity gain, as well as worries about job loss through automation.

从2022年11月左右开始，ChatGPT就引起了主流关注，其势头仍在不减。据麦肯锡公司估计，它每年可以为经济增加2.6至4.4万亿美元的贡献。高盛估计，在未来十年内，它可以提高全球GDP 7%，而OpenAI和宾夕法尼亚大学的一项研究估计，它可能影响80%以上美国工人每天进行的10%的工作或任务。同样的研究还估计，有20%的工人的工作或任务受到50%以上的生成AI的影响，因此像这样的研究带来了巨大的生产力提升的希望，也让人们担心自动化带来的失业问题。

What is generative AI? This term refers to AI, or artificial intelligence systems that can produce high-quality content, specifically text, images and audio. One of the best-known generative AI or GenAI systems is OpenAI's ChatGPT, which can follow instructions to carry out tasks like write three captions for a social media posts about our new line of sunglasses for robots, and have a generate a variety of creative outputs. Many users are familiar with websites or direct consumer applications that can generate texts like this. Other examples include Bard, which is offered by Google, as well as Bing Chat offered by Microsoft. But there are now many companies that are offering user interfaces that let you type in some texts called a prompt and will generate a response. But beyond these consumer applications, there's one other application of generative AI that I think may turn out to be even more impactful in the long term, which is the use of generative AI as a developer tool. AI is already pervasive in our lives and many of us use it dozens of times a day or more without even thinking about it. Every time you do a web search on Google or Bing, that's AI. Every time you use your credit card, there's probably an AI checking if it really is you using your credit cards or every time you go to a website like Amazon or Netflix and it recommends products of movies to you, that's AI. But many AI systems have been complex and expensive to build, and generative AI is making many AI applications much easier to build. This means that the number and variety of AI product offerings is blossoming because it's becoming much cheaper to build certain AI applications compared to before. In this course, one of the things we'll touch on a few times as well will be how generative AI may allow your business to much more inexpensively build very valuable AI applications, and you learn best practices for identifying and exploring whether or not such applications might be useful for a given business.
什么是生成AI？这个术语指的是能够生成高质量内容的AI，特别是文本、图像和音频。最知名的生成AI系统之一是OpenAI的ChatGPT，它可以根据指示执行任务，例如为我们新款机器人太阳镜写三个社交媒体帖子的标题，并生成各种创意输出。许多用户熟悉网站或直接消费者应用程序可以生成这样的文本。其他例子包括Google提供的Bard以及Microsoft提供的Bing Chat。但现在有许多公司提供用户界面，让您输入一些文本称为提示，并生成一个响应。但除了这些消费者应用程序之外，我认为可能更具长期影响力的生成AI应用是作为开发工具使用。AI已经普及到我们的生活中，我们中的许多人每天使用它几十次甚至更多，甚至不用考虑它。每次在Google或Bing上进行网络搜索时，都是AI。每次使用信用卡时，可能会有AI检查是否真的是您在使用信用卡。每次访问像亚马逊或Netflix这样的网站时，它会向您推荐产品或电影，这就是AI。但是，许多AI系统建立起来很复杂，成本也很高，而生成AI正在使许多AI应用程序更容易构建。这意味着构建某些AI应用程序的数量和种类正在蓬勃发展，因为与以前相比，构建某些AI应用程序变得更加便宜。在本课程中，我们将多次触及生成AI如何允许您的企业以更低的成本构建非常有价值的AI应用程序的最佳实践，并学习识别和探索这些应用程序是否对特定业务有用。

I've described generative AI as generating text, images and audio, and of these three types of contents, the biggest impact so far has been on text generation. But it can also generate images where given instructions, a different type of prompt. It can generate beautiful images like this one, or even a photo-realistic image like this. Generative AI can also generate audio. For example, here is a voice clone of me. Hi, I'm an AI-generated voice clone of Andrew. Andrew never actually said these words. Isn't that cool? You can also put audio together with image or even video generation to create a video clone of me like this. Hi, I'm a video clone of Andrew, it's nice to meet you. There's a lot going on in generative AI, and this is an exciting and disruptive technology that I'm confident you will find useful in your work. In this course, during the first week, we'll go through how generative AI technology actually works and specifically what it can and cannot do, and you also see a variety of common use cases that I hope will help spark your creativity to how you may use it to create value in your life on your work. In the second week, we'll discuss generative AI projects. Specifically how to identify useful generative AI applications, as well as best practices for how to go about building them, and we'll take a deeper dive into the range of technology options for building a variety of valuable projects. In the final week, we will zoom out beyond a single project to look at how generative AI will impact businesses as well as society at large. We'll look at some best practices for how teams where a company can take advantage of generative AI and also take a look at AI risks and how to make sure that what we do with AI is responsible and benefits people. I'm excited to dive into this material with you. Until that let's go on to the next video where we'll go through a non-technical description of how generative AI technology actually works. I'll see you in the next video.

我将生成AI描述为生成文本、图像和音频，在这三种内容中，到目前为止，对文本生成的影响最大。但它也可以生成图像，其中在给定指令的情况下，它可以生成像这样的漂亮图像，甚至是像这样的照片般逼真的图像。生成AI还可以生成音频。例如，这里是我的语音克隆。嗨，我是安德鲁的AI生成语音克隆。安德鲁实际上从未说过这些话。很酷吧？您还可以将音频与图像甚至视频生成组合在一起，以创建像这样的视频克隆。嗨，我是安德鲁的视频克隆，很高兴认识您。生成AI中有很多事情正在发生，这是一项令人兴奋和具有破坏性的技术，我相信您会发现它在工作中非常有用。在本课程中，在第一周，我们将介绍生成AI技术的实际工作原理，特别是它能做什么，不能做什么，并展示一些常见的使用案例，希望这将激发您的创造力，使您在工作或生活中使用它来创造价值。在第二周，我们将讨论生成AI项目，特别是如何识别有用的生成AI应用程序，以及构建它们的最佳实践，我们将更深入地了解构建各种有价值项目的技术选择范围。在最后一周，我们将超越单个项目，看看生成AI如何影响企业以及整个社会。我们将研究一些团队或公司利用生成AI的最佳实践，并审视AI风险以确保我们所做的是负责任的，并使人们受益。我很兴奋能和您一起深入研究这门课程。在这之前，请继续观看下一个视频，其中我们将介绍生成AI技术的非技术性描述。