Shadowing Practice: AI for Everyone by Andrew Ng - Learn English Speaking with Video
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Welcome to AI for Everyone.
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AI is changing the way we work and live.
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This non-technical course will teach you how to navigate the rise of AI.
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Whether you want to know what's behind the buzzwords, or whether you want to perhaps use AI yourself,
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either in the personal context or in a corporation or other organization, this course will teach you how.
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And if you want to understand how AI is affecting society and how you can navigate that, you also learn that from this course.
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In this first week, we'll start by cutting through the hype and giving you a realistic view of what AI really is.
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Let's get started.
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You've probably seen news articles about how much value AI is creating.
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According to a study by McKinsey Global Institute,
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AI is estimated to create an additional 13 trillion US dollars of value annually by the year 2030.
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Even though AI is already creating tremendous amounts of value in the software industry,
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a lot of the value to be created in the future lies outside the software industry in sectors such as retail,
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travel, transportation, automotive, materials, manufacturing, and so on.
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I have a hard time thinking of an industry
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that I don't think AI will have a huge impact on in the next several years.
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My friends
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and I used to challenge each other to name an industry where we don't think AI will have a huge impact.
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And my best example was the hairdressing industry because you know how to use AI robotics to automate hairdressing.
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But I once said this on stage
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and one of my friends who is a robotics professor was in the audience
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that day that day and she actually stood up
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and she looked at me in the eye
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and she said you know Andrew most people's hairstyles I couldn't get a robot to cut their hair that way.
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But she looked at me and said, your hairstyle, Andrew, that a robot can do.
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There is a lot of excitement, but also a lot of unnecessary hype about AI.
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One of the reasons for this is because AI is actually two separate ideas.
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Almost all the progress we are seeing in AI today is artificial narrow intelligence.
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These are AIs that do one thing, such as a smart speaker or self-driving car
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or AI to do web search or AI applications in farming or in a factory.
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These types of AI are one-trick ponies, but when you find the appropriate trick, this can be incredibly valuable.
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Unfortunately, AI also refers to a second concept of AGI or artificial general intelligence.
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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.
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I'm seeing tons of progress in ANI, artificial narrow intelligence, and almost no progress toward AGI, or artificial general intelligence.
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Both of these are worthy goals, and unfortunately, the rapid progress in ANI, which is incredibly valuable.
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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
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that there might be a lot of progress in AGI as well,
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which is leading to some irrational fears about evil color robots coming over to take over humanity anytime now.
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I think AGI is an exciting goal for researchers to work on, but it'll take multiple technological breakthroughs before we get there.
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And it may be decades or hundreds of years or even even thousands of years away.
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Given how far away AGI is, I think there is no need to unduly worry about it.
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In this week, you will learn what ANI can do and how to apply them to your problems.
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Later in this course, you also see some case studies of how ANI,
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these one-trick ponies, can be used to build really valuable applications such as smart speakers and self-driving cars.
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In this week, you will learn what is AI.
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You may have heard of machine learning and the next video will teach you what is machine learning.
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You also learn what is data and what types of data are valuable, but also what types of data are not valuable.
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You learn what it is that makes a company an AI company or an AI first company,
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so that perhaps you can start thinking if there are ways to improve your company or other organization's ability to use AI.
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And importantly, you also learned this week what machine learning can and cannot do.
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In our society, newspapers as well as research papers tend to talk only about the success stories of machine learning and AI.
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And we hardly ever see any failure stories because they just aren't as interesting to report on.
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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
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so they can make more accurate judgments about what you may and maybe should not try to use these technologies for.
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Finally, a lot of the recent rise of machine learning has been driven through the rise of deep learning, sometimes also called neural networks.
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In the final two optional videos of this week,
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you can also see an intuitive explanation of deep learning so that you will better understand what they can do,
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particularly for a set of narrow ANI tasks.
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So that's what you learned this week.
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And by the end of this week, you have a sense of AI technologies and what they can and cannot do.
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In the second week, you learn how these AI technologies can be used to build valuable projects.
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You learn what it feels like to build an AI project
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as well as what you should do to make sure you select projects that are technically feasible
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as well as valuable to you or your business or other organization.
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After learning what it takes to build AI projects, in the third week, you learn how to build AI in your company.
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In particular, if you want to take a few steps toward making your company good at AI,
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you see the AI transformation playbook and learn how to build AI teams and also build complex AI products.
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Finally, AI is having a huge impact on society.
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In the fourth and final week, you learn about how AI systems can be biased and how to diminish or eliminate such biases.
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You also learn how AI is affecting developing economies and how AI is affecting jobs,
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and be better able to navigate this rise of AI for yourself and for your organization.
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By the end of this four-week course, you'll be more knowledgeable
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and better qualified than even the CEOs of most large companies in terms of your understanding of AI technology,
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as well as your ability to help yourself or help your company or other organization navigate the rise of AI.
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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.
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Now, one of the major technologies driving the recent rise of AI is machine learning.
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But what is machine learning?
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Let's take a look in the next video.
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Vocabulary and speaking notes for this lesson
This video has 78 sentences and 1231 words to shadow. The speech runs for 7:35. The speaker talks at a natural 162 words per minute, close to everyday conversation. 85% of the words are among the 3,000 most common in English; the rest is worth studying before you start.
Key vocabulary in this video
15 less common words from the video, with pronunciation and meaning:
- navigate /ˈnæv.ɪ.ɡeɪt/ (verb) — To plan, control and record the position and course of a vehicle, ship, aircraft, etc., on a journey; to follow a planned course.
- artificial /ˌɑː.tɪˈfɪʃ.əl/ (adjective) — Man-made; made by humans; of artifice.
- trick /ˈtɹɪk/ (noun) — Something designed to fool, dupe, outsmart, mislead or swindle.
- narrow /ˈnæɹəʊ/ (adjective) — Having a small width; not wide; having opposite edges or sides that are close, especially by comparison to length or depth.
- robot /ˈɹoʊ.bɑt/ (noun) — An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
- incredibly /ɪŋˈkɹɛdɪbli/ (adverb) — In an incredible manner; not to be believed.
- bias /ˈbaɪ.əs/ (noun) — Inclination towards something.
- realistic /ˌɹɪəˈlɪs.tɪk/ (adjective) — Expressed or represented as being accurate, practicable, or not idealistic.
- hype /haɪp/ (noun) — Promotion or propaganda, especially exaggerated claims.
- pony /ˈpoʊni/ (noun) — A small horse; specifically, any of several small breeds of horse under 14.2 hands at the withers.
- robotics /ɹoʊˈbɑ.tɪks/ (noun) — The science and technology of robots, their design, manufacture, and application
- refer /ɹɪˈfɜː/ (verb) — To direct the attention of (someone toward something).
- select /sɪˈlɛkt/ (verb) — To choose one or more elements of a set, especially a set of options.
- explanation /ˌɛkspləˈneɪʃən/ (noun) — The act or process of explaining.
- rapid /ˈɹæp.ɪd/ (adjective) — Very swift or quick.
Phrasal verbs you will hear
- look at (verb) — To observe or watch.
- cut through (verb) — To take a shortcut through.
- look in (verb) — To visit a place or person briefly and casually.
- see in (verb) — To show (someone) in: to introduce (someone) to the inside of a place.
- stand up (verb) — To rise from a lying or sitting position.
- take over (verb) — To assume control of something, such as a business or enterprise, and sometimes by force.
- work on (verb) — To apply mental or physical effort to (something) in order to shape, form, improve, investigate, solve it, etc.
Pronunciation to watch
The speaker uses 10 contractions and reduced forms, such as don't, you'll, aren't. Say them the short way, as you hear them.
- The “th” sounds: worthy /ˈwɝ.ði/, breakthrough /ˈbɹeɪk.θɹuː/
- The “sh” and “zh” sounds: artificial /ˌɑː.tɪˈfɪʃ.əl/, explanation /ˌɛkspləˈneɪʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, optional /ˈɑp.ʃə.nəl/, irrational /ɪˈɹæʃ.(ə.)nəl/
- Long words — get the stress right: artificial /ˌɑː.tɪˈfɪʃ.əl/, incredibly /ɪŋˈkɹɛdɪbli/, explanation /ˌɛkspləˈneɪʃən/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/
How to practise with this video
- Listen to the whole video once without speaking and note the words you do not know.
- Start at 0.75× speed, shadow it sentence by sentence, then go back to normal speed once it feels easy.
- Record yourself and compare with the original, paying attention to words like navigate, artificial, trick.
Grammar in this video
The structures the speaker uses most, with the exact words from the video:
| Structure | In the video |
|---|---|
| Passive voice be + past participle — the focus is on what happens, not who does it | is estimated · be created · has been driven |
| Present perfect have/has + past participle — a past action that still matters now | You've probably seen · has caused · has been driven |
| Relative clauses who / which + clause — extra information about a person or thing | friends who is · ANI, which is |
What is the Shadowing Technique?
Shadowing is a science-backed language learning technique originally developed for professional interpreter training and popularized by polyglot Dr. Alexander Arguelles. The method is simple but powerful: you listen to native English audio and immediately repeat it out loud — like a shadow following the speaker with just a 1–2 second delay. Unlike passive listening or grammar drills, shadowing forces your brain and mouth muscles to simultaneously process and reproduce real speech patterns. Research shows it significantly improves pronunciation accuracy, intonation, rhythm, connected speech, listening comprehension, and speaking fluency — making it one of the most effective methods for IELTS Speaking preparation and real-world English communication.