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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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Vocabolario e note di pronuncia per questa lezione
Questo video contiene 78 frasi e 1231 parole da ripetere con lo shadowing. Il parlato dura 7:35. Chi parla ha un ritmo naturale di circa 162 parole al minuto, vicino a una conversazione quotidiana. Il 85% delle parole rientra nelle 3.000 più comuni dell’inglese; conviene studiare le altre prima di iniziare.
Vocaboli chiave di questo video
15 parole meno comuni del video, con pronuncia e significato:
- navigate /ˈnæv.ɪ.ɡeɪt/ (verbo) — seguire, dirigere. 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/ (aggettivo) — artificiale, artificioso. Man-made; made by humans; of artifice.
- trick /ˈtɹɪk/ (sostantivo) — inbroglio. Something designed to fool, dupe, outsmart, mislead or swindle.
- narrow /ˈnæɹəʊ/ (aggettivo) — stretto, angusto. Having a small width; not wide; having opposite edges or sides that are close, especially by comparison to length or depth.
- robot /ˈɹoʊ.bɑt/ (sostantivo) — robot. An intelligent mechanical being designed to look like a human or other creature, and usually made from metal.
- incredibly /ɪŋˈkɹɛdɪbli/ (avverbio) — incredibilmente. In an incredible manner; not to be believed.
- bias /ˈbaɪ.əs/ (sostantivo) — pregiudizio, predisposizione. Inclination towards something.
- realistic /ˌɹɪəˈlɪs.tɪk/ (aggettivo) — realistico. Expressed or represented as being accurate, practicable, or not idealistic.
- pony /ˈpoʊni/ (sostantivo) — pony. A small horse; specifically, any of several small breeds of horse under 14.2 hands at the withers.
- robotics /ɹoʊˈbɑ.tɪks/ (sostantivo) — robotica. The science and technology of robots, their design, manufacture, and application
- refer /ɹɪˈfɜː/ (verbo) — riferire. To direct the attention of (someone toward something).
- select /sɪˈlɛkt/ (verbo) — scegliere, selezionare. To choose one or more elements of a set, especially a set of options.
- explanation /ˌɛkspləˈneɪʃən/ (sostantivo) — spiegazione, esplicazione. The act or process of explaining.
- rapid /ˈɹæp.ɪd/ (aggettivo) — rapido, deciso. Very swift or quick.
- humanity /hjuˈmænɪti/ (sostantivo) — umanità. Humankind; human beings as a group.
I phrasal verb che sentirai
- look at (verbo) — guardare. To observe or watch.
- stand up (verbo) — alzarsi in piedi. To rise from a lying or sitting position.
- take over (verbo) — usurpare. To assume control of something, such as a business or enterprise, and sometimes by force.
Pronuncia a cui fare attenzione
Chi parla usa 10 contrazioni e forme ridotte, come don't, you'll, aren't. Pronunciale nella forma breve, così come le senti.
- I suoni “th”: worthy /ˈwɝ.ði/, breakthrough /ˈbɹeɪk.θɹuː/
- I suoni “sh” e “zh”: artificial /ˌɑː.tɪˈfɪʃ.əl/, explanation /ˌɛkspləˈneɪʃən/, transformation /ˌtɹæns.fɔɹˈmeɪ.ʃən/, optional /ˈɑp.ʃə.nəl/, irrational /ɪˈɹæʃ.(ə.)nəl/
- Parole lunghe — attenzione all’accento: artificial /ˌɑː.tɪˈfɪʃ.əl/, incredibly /ɪŋˈkɹɛdɪbli/, explanation /ˌɛkspləˈneɪʃən/, humanity /hjuˈmænɪti/, intelligent /ɪnˈtɛlɪd͡ʒənt/
Come esercitarsi con questo video
- Ascolta tutto il video una volta senza parlare e annota le parole che non conosci.
- Inizia a velocità 0,75×, fai shadowing frase per frase e torna alla velocità normale quando diventa facile.
- Registrati e confronta con l’originale, facendo attenzione a parole come navigate, artificial, trick.
La grammatica di questo video
Le strutture che chi parla usa di più, con le parole esatte del video:
| Struttura | Nel video |
|---|---|
| Forma passiva be + participio passato — conta ciò che accade, non chi lo fa | is estimated · be created · has been driven |
| Present perfect have/has + participio passato — un’azione passata che conta ancora adesso | You've probably seen · has caused · has been driven |
| Frasi relative who / which + frase — un’informazione in più su una persona o una cosa | friends who is · ANI, which is |
Cos'è la tecnica dello Shadowing?
Shadowing è una tecnica di apprendimento delle lingue supportata da studi scientifici, originariamente sviluppata per la formazione dei traduttori professionisti e resa popolare dal poliglotta Dr. Alexander Arguelles. Il metodo è semplice ma potente: ascolti un audio in inglese di madrelingua e lo ripeti immediatamente ad alta voce — come un'ombra che segue il parlante con un ritardo di solo 1–2 secondi. A differenza dell'ascolto passivo o degli esercizi di grammatica, lo shadowing costringe il tuo cervello e i muscoli della bocca a elaborare e riprodurre simultaneamente i modelli di discorso reale. La ricerca dimostra che migliora significativamente la precisione della pronuncia, l'intonazione, il ritmo, il discorso connesso, la comprensione dell'ascolto e la fluidità del parlato — rendendolo uno dei metodi più efficaci per la preparazione alla prova di speaking dell'IELTS e per la comunicazione reale in inglese.