쉐도잉 연습: AI for Everyone by Andrew Ng - 영상으로 영어 말하기 배우기

연습 모드 선택

각 모드는 전체 화면 연습실로 열립니다.

78 문장

문장이 너무 짧거나 길면 Edit를 눌러 조정하세요.

Welcome to AI for Everyone.

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.

앱 다운로드

유창하게 말하는 데 필요한 모든 것

AI 발음 평가문장마다 점수 확인

IPA 발음 연습모든 소리 마스터

단어 학습나만의 단어장 만들기

단어 게임놀면서 외우기

QR 스캔

Download on theApp Store Get it onGoogle Play

같은 채널

FOR YOU

이 레슨의 어휘와 말하기 포인트

이 영상에는 섀도잉할 문장 78개와 단어 1231개가 있습니다. 말하는 구간의 길이는 7:35입니다. 화자는 분당 약 162단어로, 일상 대화에 가까운 자연스러운 속도로 말합니다. 단어의 85%가 영어에서 가장 많이 쓰이는 3,000단어에 속합니다. 나머지는 연습 전에 미리 확인해 두세요.

이 영상의 핵심 어휘

영상에 나오는 덜 흔한 단어 15개를 발음, 뜻과 함께 정리했습니다.

artificial /ˌɑː.tɪˈfɪʃ.əl/ (형용사) — 인공, 인조. Man-made; made by humans; of artifice.
narrow /ˈnæɹəʊ/ (형용사) — 좁은, 좁다. Having a small width; not wide; having opposite edges or sides that are close, especially by comparison to length or depth.
robot /ˈɹoʊ.bɑt/ (명사) — 로봇, 인조인간. An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
bias /ˈbaɪ.əs/ (명사) — 편견. Inclination towards something.
realistic /ˌɹɪəˈlɪs.tɪk/ (형용사) — 현실적. Expressed or represented as being accurate, practicable, or not idealistic.
pony /ˈpoʊni/ (명사) — 조랑말. A small horse; specifically, any of several small breeds of horse under 14.2 hands at the withers.
robotics /ɹoʊˈbɑ.tɪks/ (명사) — 로봇공학, 로봇학. The science and technology of robots, their design, manufacture, and application
refer /ɹɪˈfɜː/ (동사) — 언급하다. To direct the attention of (someone toward something).
select /sɪˈlɛkt/ (동사) — 고르다. To choose one or more elements of a set, especially a set of options.
explanation /ˌɛkspləˈneɪʃən/ (명사) — 설명. The act or process of explaining.
rapid /ˈɹæp.ɪd/ (형용사) — 빠르다. Very swift or quick.
humanity /hjuˈmænɪti/ (명사) — 인류, 인간. Humankind; human beings as a group.
intelligent /ɪnˈtɛlɪd͡ʒənt/ (형용사) — 똑똑하다, 똑똑한. Of high or especially quick cognitive capacity, bright.
ton /tʌn/ (명사) — 톤. The short ton of 2000 pounds (about 907 kg), 20 hundredweights of 100 pounds avoirdupois each.
transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/ (명사) — 변형, 변환. The act of transforming or the state of being transformed.

영상에 나오는 구동사

stand up (동사) — 일어서다. To rise from a lying or sitting position.

주의할 발음

화자는 don't, you'll, aren't 같은 축약형과 약화된 형태를 10번 사용합니다. 들리는 대로 짧게 발음하세요.

“th” 소리: worthy /ˈwɝ.ði/, breakthrough /ˈbɹeɪk.θɹuː/
“sh”와 “zh” 소리: artificial /ˌɑː.tɪˈfɪʃ.əl/, explanation /ˌɛkspləˈneɪʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, optional /ˈɑp.ʃə.nəl/, irrational /ɪˈɹæʃ.(ə.)nəl/
긴 단어 — 강세 위치에 주의: artificial /ˌɑː.tɪˈfɪʃ.əl/, incredibly /ɪŋˈkɹɛdɪbli/, explanation /ˌɛkspləˈneɪʃən/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
자신의 목소리를 녹음해 원본과 비교하고, artificial, narrow, robot 같은 단어에 특히 주의합니다.

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	is estimated · be created · has been driven
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	You've probably seen · has caused · has been driven
관계절 who / which + 절 — 사람이나 사물에 대한 추가 정보	friends who is · ANI, which is

쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법

쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.

섀도잉 방법: 단계별 전체 가이드 읽기 →

쉐도잉 연습: AI for Everyone by Andrew Ng - 영상으로 영어 말하기 배우기

연습 모드 선택

앱 다운로드

같은 채널

#1 Machine Learning Specialization [Course 1, Week 1, Lesson 1]

The Ultimate Transformer Course for Working Engineers

C4W1L01 Computer Vision

추천 영상

Everyone Is Wrong About AI Coding

P1 机器学习的应用【2024公认最好的 | 吴恩达机器学习 | 教程 | Machine Learning Specialization(超爽中英!)】

Ray Dalio on the AI Bubble

Andrew Ng: The Biggest Opportunities in AI Aren't Where You Think

Neurosymbolic AI Explained

How AI is Changing Data Scientist's Workflow

The Human Economy in the Age of AI | Ben Pascut | TEDx

AI & Education: Generative AI & the Future of Critical Thinking

AI Concepts Every Product Manager Should Know in 25 Minutes | Crash Course

Did Google just kickstart the intelligence explosion?

Don’t Start with AI, Start with the Problem

Cần cập nhật gì về AI - Ali Abdaal #AI #Update #ielts