Shadowing-Übung: AI for Everyone by Andrew Ng - Englisch Sprechen Lernen mit 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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Wortschatz und Sprechhinweise zu dieser Lektion
Dieses Video enthält 78 Sätze und 1231 Wörter zum Nachsprechen. Der gesprochene Teil dauert 7:35. Der Sprecher spricht in natürlichem Tempo, etwa 162 Wörter pro Minute, ähnlich wie im Alltagsgespräch. 85 % der Wörter gehören zu den 3.000 häufigsten im Englischen; den Rest solltest du dir vor dem Üben ansehen.
Wichtiger Wortschatz in diesem Video
15 weniger häufige Wörter aus dem Video, mit Aussprache und Bedeutung:
- navigate /ˈnæv.ɪ.ɡeɪt/ (Verb) — die Richtung vorgeben, steuern. 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/ (Adjektiv) — künstlich. Man-made; made by humans; of artifice.
- trick /ˈtɹɪk/ (Substantiv) — List, Falle. Something designed to fool, dupe, outsmart, mislead or swindle.
- narrow /ˈnæɹəʊ/ (Adjektiv) — eng, begrenzt. Having a small width; not wide; having opposite edges or sides that are close, especially by comparison to length or depth.
- robot /ˈɹoʊ.bɑt/ (Substantiv) — Roboter. An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
- incredibly /ɪŋˈkɹɛdɪbli/ (Adverb) — unglaublich. In an incredible manner; not to be believed.
- bias /ˈbaɪ.əs/ (Substantiv) — Voreingenommenheit, Neigung. Inclination towards something.
- realistic /ˌɹɪəˈlɪs.tɪk/ (Adjektiv) — realistisch. Expressed or represented as being accurate, practicable, or not idealistic.
- hype /haɪp/ (Substantiv) — Hype. Promotion or propaganda, especially exaggerated claims.
- pony /ˈpoʊni/ (Substantiv) — Pony, Kleinpferd. A small horse; specifically, any of several small breeds of horse under 14.2 hands at the withers.
- robotics /ɹoʊˈbɑ.tɪks/ (Substantiv) — Robotik. The science and technology of robots, their design, manufacture, and application
- refer /ɹɪˈfɜː/ (Verb) — verweisen. To direct the attention of (someone toward something).
- select /sɪˈlɛkt/ (Verb) — auswählen. To choose one or more elements of a set, especially a set of options.
- explanation /ˌɛkspləˈneɪʃən/ (Substantiv) — Erläuterung, Erklärung. The act or process of explaining.
- rapid /ˈɹæp.ɪd/ (Adjektiv) — schnell. Very swift or quick.
Phrasal Verbs, die du hören wirst
- look at (Verb) — schauen. To observe or watch.
- stand up (Verb) — aufstehen. To rise from a lying or sitting position.
- take over (Verb) — übernehmen. To assume control of something, such as a business or enterprise, and sometimes by force.
Aussprache, auf die du achten solltest
Der Sprecher verwendet 10 Kurzformen und abgeschwächte Formen, zum Beispiel don't, you'll, aren't. Sprich sie in der kurzen Form, so wie du sie hörst.
- Die „th“-Laute: worthy /ˈwɝ.ði/, breakthrough /ˈbɹeɪk.θɹuː/
- Die Laute „sh“ und „zh“: artificial /ˌɑː.tɪˈfɪʃ.əl/, explanation /ˌɛkspləˈneɪʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, optional /ˈɑp.ʃə.nəl/, irrational /ɪˈɹæʃ.(ə.)nəl/
- Lange Wörter – auf die Betonung achten: artificial /ˌɑː.tɪˈfɪʃ.əl/, incredibly /ɪŋˈkɹɛdɪbli/, explanation /ˌɛkspləˈneɪʃən/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/
So übst du mit diesem Video
- Höre dir das ganze Video einmal an, ohne zu sprechen, und notiere die Wörter, die du nicht kennst.
- Beginne mit 0,75-facher Geschwindigkeit, sprich Satz für Satz nach und wechsle zur normalen Geschwindigkeit, sobald es leichtfällt.
- Nimm dich auf und vergleiche mit dem Original; achte dabei auf Wörter wie navigate, artificial, trick.
Grammatik in diesem Video
Die Strukturen, die der Sprecher am häufigsten verwendet, mit den genauen Worten aus dem Video:
| Struktur | Im Video |
|---|---|
| Passiv be + Partizip Perfekt – wichtig ist, was geschieht, nicht wer es tut | is estimated · be created · has been driven |
| Present Perfect have/has + Partizip Perfekt – eine vergangene Handlung, die jetzt noch wichtig ist | You've probably seen · has caused · has been driven |
| Relativsätze who / which + Satz – eine Zusatzinformation über eine Person oder Sache | friends who is · ANI, which is |
Was ist die Shadowing-Technik?
Shadowing ist eine wissenschaftlich fundierte Sprachlerntechnik, die ursprünglich für die professionelle Dolmetscherausbildung entwickelt und durch den Polyglotten Dr. Alexander Arguelles populär gemacht wurde. Die Methode ist einfach aber wirkungsvoll: Du hörst englisches Audio von Muttersprachlern und wiederholst es sofort laut — wie ein Schatten, der dem Sprecher mit nur 1–2 Sekunden Verzögerung folgt. Anders als passives Hören oder Grammatikübungen zwingt Shadowing dein Gehirn und deine Mundmuskulatur, gleichzeitig echte Sprachmuster zu verarbeiten und zu reproduzieren. Studien zeigen, dass es Aussprachegenauigkeit, Intonation, Rhythmus, verbundene Sprache, Hörverständnis und Sprechflüssigkeit signifikant verbessert — was es zu einer der effektivsten Methoden für die IELTS Speaking-Vorbereitung und reale englische Kommunikation macht.