Практика Shadowing: AI for Everyone by Andrew Ng - Изучайте разговорный английский по видео

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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.

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FOR YOU

Лексика и советы по произношению к этому уроку

В этом видео 78 предложений и 1231 слов для шедоуинга. Речь длится 7:35. Говорящий говорит в естественном темпе, около 162 слов в минуту, близком к повседневной речи. 85% слов входят в 3000 самых частых слов английского языка; остальные стоит разобрать перед занятием.

Ключевая лексика этого видео

15 менее частых слов из видео с произношением и значением:

artificial /ˌɑː.tɪˈfɪʃ.əl/ (прилагательное) — иску́сственный. Man-made; made by humans; of artifice.
trick /ˈtɹɪk/ (существительное) — обма́н, трюк. Something designed to fool, dupe, outsmart, mislead or swindle.
narrow /ˈnæɹəʊ/ (прилагательное) — у́зкий, те́сный. Having a small width; not wide; having opposite edges or sides that are close, especially by comparison to length or depth.
robot /ˈɹoʊ.bɑt/ (существительное) — ро́бот. An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
incredibly /ɪŋˈkɹɛdɪbli/ (наречие) — невероя́тно. In an incredible manner; not to be believed.
bias /ˈbaɪ.əs/ (существительное) — предубежде́ние, предвзя́тость. Inclination towards something.
realistic /ˌɹɪəˈlɪs.tɪk/ (прилагательное) — реалисти́чный. Expressed or represented as being accurate, practicable, or not idealistic.
hype /haɪp/ (существительное) — шуми́ха, хайп. Promotion or propaganda, especially exaggerated claims.
pony /ˈpoʊni/ (существительное) — по́ни. A small horse; specifically, any of several small breeds of horse under 14.2 hands at the withers.
robotics /ɹoʊˈbɑ.tɪks/ (существительное) — робототе́хника. The science and technology of robots, their design, manufacture, and application
refer /ɹɪˈfɜː/ (глагол) — ссыла́ться, сосла́ться. To direct the attention of (someone toward something).
select /sɪˈlɛkt/ (глагол) — отбира́ть. To choose one or more elements of a set, especially a set of options.
explanation /ˌɛkspləˈneɪʃən/ (существительное) — объясне́ние, разъясне́ние. The act or process of explaining.
rapid /ˈɹæp.ɪd/ (прилагательное) — бы́стрый, ско́рый. Very swift or quick.
humanity /hjuˈmænɪti/ (существительное) — челове́чество. Humankind; human beings as a group.

Фразовые глаголы, которые вы услышите

stand up (глагол) — встава́ть, встать. To rise from a lying or sitting position.
take over (глагол) — брать на себя́, взять на себя́. To assume control of something, such as a business or enterprise, and sometimes by force.

Произношение, на которое стоит обратить внимание

Говорящий использует 10 сокращённых и редуцированных форм, например don't, you'll, aren't. Произносите их коротко, так, как слышите.

Звуки «th»: worthy /ˈwɝ.ði/, breakthrough /ˈbɹeɪk.θɹuː/
Звуки «sh» и «zh»: artificial /ˌɑː.tɪˈfɪʃ.əl/, explanation /ˌɛkspləˈneɪʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, optional /ˈɑp.ʃə.nəl/, irrational /ɪˈɹæʃ.(ə.)nəl/
Длинные слова — следите за ударением: artificial /ˌɑː.tɪˈfɪʃ.əl/, incredibly /ɪŋˈkɹɛdɪbli/, explanation /ˌɛkspləˈneɪʃən/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/

Как заниматься с этим видео

Прослушайте всё видео один раз молча и выпишите незнакомые слова.
Начните со скорости 0,75×, повторяйте предложение за предложением и вернитесь к обычной скорости, когда станет легко.
Запишите себя и сравните с оригиналом, обращая внимание на такие слова, как artificial, trick, narrow.

Грамматика в этом видео

Конструкции, которые говорящий использует чаще всего, с точными словами из видео:

Конструкция	В видео
Пассивный залог be + причастие прошедшего времени — важно, что происходит, а не кто это делает	is estimated · be created · has been driven
Present Perfect have/has + причастие прошедшего времени — прошлое действие, важное сейчас	You've probably seen · has caused · has been driven
Придаточные определительные who / which + предложение — уточнение о человеке или предмете	friends who is · ANI, which is

Что такое техника Shadowing?

Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.

Техника шедоуинга: читать полное пошаговое руководство →

Практика Shadowing: AI for Everyone by Andrew Ng - Изучайте разговорный английский по видео

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