吴恩达教授《AI for everyone》课程第一周—

本文主要是介绍吴恩达教授《AI for everyone》课程第一周——介绍，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

视频地址：https://www.coursera.org/learn/ai-for-everyone/lecture/SRwLN/week-1-introduction

英文字幕：

Welcome to AI for everyone. AI is changing the way we work and live and this nontechnical course will teach you how to navigate the rise of AI. Whether you want to know what's behind the buzzwords or whether you want to perhaps use AI yourself either in a personal context or in a corporation or other organization, this course will teach you how. If you want to understand how AI is affecting society, and how you can navigate that, you also learn that from this course. In this first week, we'll start by cutting through the hype and giving you a realistic view of what AI really is. Let's get started. You've probably seen news articles about how much value AI is creating. According to a study by McKinsey Global Institute, AI is estimated to create an additional 13 trillion US dollars of value annually by the year 2030. Even though AI is already creating tremendous amounts of value into software industry, a lot of the value to be created in a future lies outside the software industry. In sectors such as retail, travel, transportation, automotive, materials, manufacturing and so on. I should have a hard time thinking of an industry that I don't think AI will have a huge impact on in the next several years. My friends and I used a challenge each other to name and industry where we don't think AI will have a huge impact. My best example was the hairdressing industry because we know how to use AI robotics to automate hairdressing. But, I once said this on stage and one of my friends who is a robotics professor was in the audience that day, and she actually stood up and she looked at me in the eye and she said, "You know Andrew, most people's hairstyles, I couldn't get a robot to cut their hair that way." But she looked at me and said, "Your hairstyle Andrew, that a robot can do." There is a lot of excitement but also a lot of unnecessary hype about AI. One of the reasons for this is because AI is actually two separate ideas. Almost all the progress we are seeing in the AI today is artificial narrow intelligence. These are AIs that do one thing such as a smart speaker or a self-driving car or AI to do web search or AI applications in farming or in a factory. These types of AI are one trick ponies but when you find the appropriate trick, this can be incredibly valuable. Unfortunately, AI also refers to a second concept of AGI or artificial general intelligence. That is the goal to build AI. They can do anything a human can do or maybe even be superintelligence and do even more things than any human can. I'm seeing tons of progress in ANI, artificial narrow intelligence and almost no progress to what AGI or artificial general intelligence. Both of these are worthy goals and unfortunately the rapid progress in ANI which is incredibly valuable, that has caused people to conclude that there's a lot of progress in AI, which is true. But that has caused people to falsely think that there might be a lot of progress in AGI as well which is leading to some irrational fears about evil clever robots coming over to take over humanity anytime now. I think AGI is an exciting goal for researchers to work on, but it'll take most for technological breakthroughs before we get there and it may be decades or hundreds of years or even thousands of years away. Given how far away AGI is, I think there is no need to unduly worry about it. In this week, you will learn what ANI can do and how to apply them to your problems. Later in this, course you'll also see some case studies of how ANI, this one trick ponies can be used to build really valuable applications such as smart speakers and self-driving cars. In this week, you will learn why this AI. You may have heard of machine learning and the next video will teach you what is machine learning. You also learn what is data and what types of data are valuable but also what does the data are not valuable. You learn what it is that makes a company an AI company or an AI first company so that perhaps you can start thinking if there are ways to improve your company or other organizations ability to use AI and importantly, you also learned this week what machine learning can and cannot do. In our society, newspapers as well as research papers tend to talk only about the success stories of machine learning and AI and we hardly ever see any failure stories because they just aren't as interesting to report on. But for you to have a realistic view of what AI and what machine learning can or cannot do, I think is important that you see examples of both so that you can make more accurate judgements about what you may and maybe should not try to use these technologies for. Finally, a lot of the recent rise of, machine learning has been driven through the rise of Deep Learning. Sometimes also called Neural Networks. In the final two optional videos of this week, you can also see an intuitive explanation of deep learning so that you will better understand what they can do particularly for a set of narrow ANI tasks. So, that's what you learn this week and by the end of this week, you have a sense of AI technologies and what they can and cannot do. In the second week, you'll learn how these AI technologies can be used to build valuable projects. You learn what it feels like to build an AI project as what as what you should do to make sure you select projects that are technically feasible as well as valuable to you or your business or other organization. After learning what it takes to build AI projects, in the third week you'll learn how to build AI in your company. In particular, if you want to take a few steps toward making your company good at AI, you see the AI transformation playbook and learn how to build AI teams and also built complex AI products. Finally, AI is having a huge impact on society. In a fourth and final week, you'll learn about how AI systems can be bias and how to diminish or eliminate such biases. You also learn how AI is affecting developing economies and how AI is affecting jobs and be better able to navigate this rise of AI for yourself and for your organization. By the end of this four recourse, you'll be more knowledgeable and better qualified than even the CEOs of most large companies in terms of your understanding of AI technology as well as your ability to help yourself or your company or other organization navigate the rise of AI as I hope that after this course, you'll be in a position to provide leadership to others as well as they navigate these issues. Now, one of the major technologies driving the recent rise of AI is Machine Learning. But what is Machine Learning? Let's take a look in the next video.

中文翻译：

欢迎大家参加AI。人工智能正在改变我们的工作和生活方式，这个非技术课程将教你如何驾驭人工智能的兴起。无论您是想知道流行语背后的内容，还是想在个人环境或公司或其他组织中自己使用AI，本课程都将教您如何操作。如果您想了解AI如何影响社会，以及如何进行导航，您还可以从本课程中学习。在第一周，我们将首先通过大肆宣传，让您真实地了解AI的真实情况。让我们开始吧。您可能已经看过有关AI正在创造多少价值的新闻文章。根据麦肯锡全球研究所的一项研究，人工智能估计到2030年每年将创造额外的13万亿美元的价值。尽管人工智能已经为软件行业创造了巨大的价值，但还是要创造很多价值。在未来，软件行业之外。在零售，旅游，运输，汽车，材料，制造等行业。我应该很难想到一个我不认为人工智能将在未来几年内产生巨大影响的行业。我和我的朋友们互相挑战名称和行业，我们认为人工智能不会产生巨大的影响。我最好的例子是美发行业，因为我们知道如何使用AI机器人来自动化美发。但是，我曾经在舞台上说过这一天，我的一位机器人教授的朋友当天在观众席上，她实际上站起来，看着我的眼睛，她说，“你知道安德鲁，大多数人的发型，我无法让机器人那样剪头发。“但她看着我说，“你的发型安德鲁，一个机器人可以做的。”有很多令人兴奋的事情，但也有很多关于AI的不必要的炒作。其中一个原因是因为AI实际上是两个独立的想法。我们今天在AI中看到的几乎所有进展都是人为的狭隘智能。这些是能够做一件事的AI，例如智能扬声器或自动驾驶汽车或AI，用于在农业或工厂中进行网络搜索或AI应用。这些类型的AI是一个小技巧，但是当你找到合适的技巧时，这可能是非常有价值的。不幸的是，AI也提到了AGI或人工一般智能的第二个概念。这是构建AI的目标。他们可以做人类可以做的任何事情，甚至可以做超级智能，甚至可以做任何比人类更多的事情。我在ANI中看到了很多进步，人工狭隘的情报以及几乎没有进展到AGI或人工智能。这两个都是有价值的目标，不幸的是ANI的快速进展非常有价值，这使得人们得出结论认为人工智能有很多进步，这是事实。但这导致人们错误地认为AGI可能会有很多进展，这导致人们对邪恶聪明的机器人现在随时接管人类的一些非理性担忧。我认为AGI对于研究人员而言是一个令人兴奋的目标，但在我们到达之前它将需要大部分技术突破，它可能需要数十年，数百年甚至数千年才能实现。鉴于AGI有多远，我认为没有必要过分担心它。在本周，您将了解ANI可以做什么以及如何将它们应用到您的问题中。在后面的课程中，您还将看到一些案例研究，了解ANI，这一招小马可用于构建真正有价值的应用，如智能扬声器和自动驾驶汽车。在这个星期，你将了解为什么这个AI。您可能听说过机器学习，下一个视频将教您什么是机器学习。您还可以了解什么是数据以及哪些类型的数据有价值，但也了解数据没有价值。你了解到什么使公司成为人工智能公司或人工智能第一公司，这样你或许可以开始思考是否有办法改善你的公司或其他组织使用人工智能的能力，重要的是，你本周也学到了什么机器学习可以也可以做不到。在我们的社会中，报纸和研究论文往往只谈论机器学习和人工智能的成功故事，我们几乎看不到任何失败的故事，因为它们报告的内容并不那么有趣。但是为了让你对人工智能和机器学习能做什么或不做什么有一个现实的看法，我认为重要的是你看到两者的例子，这样你就可以做出更准确的判断，你可能不应该尝试使用这些技术。最后，很多最近兴起的机器学习都是通过深度学习的兴起来推动的。有时也称为神经网络。在本周的最后两个可选视频中，您还可以看到深度学习的直观解释，以便您更好地了解他们可以做些什么，特别是对于一组狭窄的ANI任务。所以，这就是你在本周所学到的知识，到本周末，你对AI技术以及它们能做什么和不能做什么都有所了解。在第二周，您将学习如何使用这些AI技术来构建有价值的项目。您将了解构建AI项目的感受，以及确保您选择技术上可行且对您或您的企业或其他组织有价值的项目。在了解了构建AI项目所需的内容之后，在第三周，您将学习如何在公司中构建AI。特别是，如果您想采取一些措施使您的公司擅长AI，您可以看到AI转换手册，并学习如何构建AI团队以及构建复杂的AI产品。最后，人工智能正在对社会产生巨大影响。在第四周也是最后一周，您将了解AI系统如何偏向以及如何减少或消除此类偏差。您还将了解AI如何影响发展中经济体以及AI如何影响工作，并且能够更好地为您自己和您的组织引导AI的这种崛起。在这四种资源的最后阶段，您对大多数大型公司的首席执行官在理解人工智能技术方面以及帮助自己或公司或其他组织提升自身能力方面的能力方面，知识渊博，资质更高。因为我希望在这个课程结束后，你能够为他人提供领导以及他们解决这些问题。现在，推动人工智能近期兴起的主要技术之一是机器学习。但什么是机器学习？我们来看看下一个视频。