跟读练习: AI for Everyone by Andrew Ng - 通过视频学习英语口语

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Welcome to AI for Everyone.

欢迎来到《AI for Everyone》课程。

AI is changing the way we work and live.

This non-technical 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 the personal context or in a corporation or other organization, this course will teach you how.

And 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 in the software industry,

a lot of the value to be created in the future lies outside the software industry in sectors such as retail,

travel, transportation, automotive, materials, manufacturing, and so on.

I 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 to challenge each other to name an industry where we don't think AI will have a huge impact.

And my best example was the hairdressing industry because you 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 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 AI today is artificial narrow intelligence.

These are AIs that do one thing, such as a smart speaker or 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 that can do anything a human can do, or maybe even be super intelligent and do even more things than any human can.

I'm seeing tons of progress in ANI, artificial narrow intelligence, and almost no progress toward 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 color 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 multiple technological breakthroughs before we get there.

And it may be decades or hundreds of years or even 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 also see some case studies of how ANI,

these 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 what is 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 types of 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 organization's 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 and cannot do, I think it's important that you see examples of both

so they can make more accurate judgments 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 learned 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 learn how these AI technologies can be used to build valuable projects.

You learn what it feels like to build an AI project

as well 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 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 build complex AI products.

Finally, AI is having a huge impact on society.

In the fourth and final week, you learn about how AI systems can be biased 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-week course, 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 help your company or other organization navigate the rise of AI.

And so 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.

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音标练习掌握每个音

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FOR YOU

本课的词汇与口语要点

这段视频共有 78 个句子、1231 个单词可供跟读。讲话部分时长为 7:35。说话人语速自然，每分钟约 162 个词，接近日常对话。 85% 的单词属于英语最常用的 3,000 词，其余的词建议在练习前先学一下。

视频中的重点词汇

视频中 15 个不太常见的单词，附发音和释义：

artificial /ˌɑː.tɪˈfɪʃ.əl/ (形容词) — 人造的. Man-made; made by humans; of artifice.
trick /ˈtɹɪk/ (名词) — 詭計 /诡计, 騙術 /骗术. Something designed to fool, dupe, outsmart, mislead or swindle.
narrow /ˈnæɹəʊ/ (形容词) — 窄. Having a small width; not wide; having opposite edges or sides that are close, especially by comparison to length or depth.
robot /ˈɹoʊ.bɑt/ (名词) — 機器人 /机器人, 機械人 /机械人. An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
bias /ˈbaɪ.əs/ (名词) — 偏見 /偏见. Inclination towards something.
realistic /ˌɹɪəˈlɪs.tɪk/ (形容词) — 現實 /现实, 栩栩如生. Expressed or represented as being accurate, practicable, or not idealistic.
hype /haɪp/ (名词) — 炒作. Promotion or propaganda, especially exaggerated claims.
pony /ˈpoʊni/ (名词) — 矮種馬 /矮种马, 小馬 /小马. A small horse; specifically, any of several small breeds of horse under 14.2 hands at the withers.
robotics /ɹoʊˈbɑ.tɪks/ (名词) — 機器人學 /机器人学. The science and technology of robots, their design, manufacture, and application
refer /ɹɪˈfɜː/ (动词) — 談到 /谈到. To direct the attention of (someone toward something).
select /sɪˈlɛkt/ (动词) — 選 /选, 挑選 /挑选. To choose one or more elements of a set, especially a set of options.
explanation /ˌɛkspləˈneɪʃən/ (名词) — 解釋 /解释, 說明 /说明. The act or process of explaining.
rapid /ˈɹæp.ɪd/ (形容词) — 快, 迅速. Very swift or quick.
humanity /hjuˈmænɪti/ (名词) — 人類 /人类. Humankind; human beings as a group.
estimate /ˈɛs.tɪ.mət/ (名词) — 估計 /估计. A rough calculation or assessment of the value, size, or cost of something.

视频中出现的短语动词

look at (动词) — 觀察 /观察, 看. To observe or watch.
stand up (动词) — 站起來 /站起来, 起來 /起来. To rise from a lying or sitting position.
take over (动词) — 接管, 接手. To assume control of something, such as a business or enterprise, and sometimes by force.

需要注意的发音

说话人用了 10 次缩略和弱读形式，例如 don't, you'll, aren't。请按听到的简短形式来说。

“th” 音: worthy /ˈwɝ.ði/, breakthrough /ˈbɹeɪk.θɹuː/
“sh” 和 “zh” 音: artificial /ˌɑː.tɪˈfɪʃ.əl/, explanation /ˌɛkspləˈneɪʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, optional /ˈɑp.ʃə.nəl/, irrational /ɪˈɹæʃ.(ə.)nəl/
长单词——注意重音位置: artificial /ˌɑː.tɪˈfɪʃ.əl/, incredibly /ɪŋˈkɹɛdɪbli/, explanation /ˌɛkspləˈneɪʃən/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/

如何用这段视频练习

先完整听一遍视频，不要开口，记下不认识的单词。
先用 0.75 倍速逐句跟读，熟练之后再回到正常速度。
录下自己的声音并与原声对比，特别注意 artificial, trick, narrow 这类单词。

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
被动语态 be + 过去分词 — 强调发生了什么，而不是谁做的	is estimated · be created · has been driven
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	You've probably seen · has caused · has been driven
定语从句 who / which + 从句 — 补充说明人或事物	friends who is · ANI, which is

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 →

跟读练习: AI for Everyone by Andrew Ng - 通过视频学习英语口语

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