シャドーイング練習: What Is AI? | Artificial Intelligence | What is Artificial Intelligence? | AI In 5 Mins |Simplilearn - 動画で英語スピーキングを学ぶ

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Picture this, a machine that could organize your cupboard just as you like it, or serve every member of the house a customized cup of coffee.
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Makes your day easier, doesn't it?
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These are the products of artificial intelligence.
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But why use the term artificial intelligence?
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Well, these machines are artificially incorporated with human -like intelligence to perform tasks as we do.
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This intelligence is built using complex algorithms and mathematical functions.
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But AI may not be as obvious as in the previous examples.
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In fact, AI is used in smartphones, cars, social media feeds, video games,
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banking, surveillance, and many other aspects of our daily life.
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The real question is, what does an AI do at its core?
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Here is a robot we built in our lab, which is now dropped onto a field.
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In spite of a variation in lighting, landscape, and dimensions of the field, the AI robot must perform as expected.
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This ability to react appropriately to a new situation is called generalized learning.
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The robot is now at a crossroad, one that is paved and the other rocky.
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The robot must determine which path to take based on the circumstances.
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This portrays the robot's reasoning ability.
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After a short stroll, the robot now encounters a stream that it cannot swim across.
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Using the plank provided as an input, the robot is able to cross this stream.
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So, our robot uses the given input and finds the solution for a problem.
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This is problem solving.
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These three capabilities make the robot artificially intelligent.
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In short, AI provides machines with the capability to adapt, reason, and provide solutions.
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Well, now that we know what AI is, let's have a look at the two broad categories an AI is classified into.
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Weak AI, also called narrow AI, focuses solely on one task.
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For example, AlphaGo is a maestro of the game
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Go, but you can't expect it to be even remotely good at chess.
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This makes AlphaGo a weak AI.
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You might say Alexa is definitely not a weak AI, since it can perform multiple tasks.
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Well, that's not really true.
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When you ask Alexa to play Despacito, it picks up the key words play and despacito, and runs a program it is trained to.
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Alexa cannot respond to a question it isn't trained to answer.
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For instance, try asking Alexa the status of traffic from work to home.
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Alexa cannot provide you this information, as she is not trained to.
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And that brings us to our second category of AI, Strong AI.
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Now, this is much like the robots that only exist in fiction as of now.
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Ultron from Avengers is an ideal example of a strong AI.
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That's because it's self -aware and eventually even develops emotions.
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This makes the AI's response unpredictable.
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You must be wondering, well, how is artificial intelligence different from machine learning and deep learning?
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We saw what AI is.
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Machine learning is a technique to achieve AI and deep learning, in turn, is a subset of machine learning.
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Machine learning provides a machine with the capability to learn from data and experience through algorithms.
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Deep learning does this learning through ways inspired by the human brain.
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This means through deep learning, data and patterns can be better perceived.
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Ray Kurzweil, a well -known futurist, predicts that by the year 2045, we would have robots as smart as humans.
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This is called the point of singularity.
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Well, that's not all.
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In fact, Elon Musk predicts that the human mind and body will be enhanced by AI implants, which would make us partly cyborgs.
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So, here's a question for you.
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Which of the below AI projects don't exist yet?
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A. An AI robot with citizenship.
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B. A robot with a muscular skeletal system.
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C. AI that can read its owner's emotions.
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D. AI that develops emotions over time
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Give it a thought and leave your answers in the comment section below.
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Three lucky winners will receive Amazon gift vouchers.
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Since the human brain is still a mystery, it's no surprise that AI too has a lot of unventured domains.
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For now, AI is built to work with humans and make our tasks easier.
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However, with the maturation of technology, we can only wait and watch what the future of AI holds for us.
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Well, that is artificial intelligence for you in short.
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Do not forget to leave your answer to the quiz in the comment section below.
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Also… Like, share and subscribe to our channel if you enjoyed this video.
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Stay tuned and keep learning!

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このレッスンの語彙とスピーキングのポイント

繰り返し出てくる語は次のとおりです：robot, learning, machine, intelligence, Alexa。 この動画には、シャドーイング用の文が63文、単語が761語あります。 音声の長さは5:11です。 話す速さは1分あたり約147語で安定しており、シャドーイングしやすいペースです。 英語の頻出3,000語に含まれる単語は77%だけなので、語彙は難しめです。

この動画の重要語彙

動画に出てくる覚えておきたい単語15語を、発音と意味つきで紹介します。

単語発音意味
robot 名詞/ˈɹoʊ.bɑt/ロボット, 人造人間
artificial 形容詞/ˌɑː.tɪˈfɪʃ.əl/人工の
emotion 名詞/ɪˈməʊ.ʃən/感情, 心緒
capability 名詞/ˌkeɪ.pəˈbɪl.ɪ.ti/能力
predict 動詞/pɹɪˈdɪkt/予言する
algorithm 名詞/ˈælɡəɹɪðm̩/アルゴリズム, 演算手順
technique 名詞/tɛkˈniːk/技術
mystery 名詞/ˈmɪs.t(ə.)ɹi/ミステリー, 不思議
fiction 名詞/ˈfɪkʃən/フィクション, 小説
ideal 形容詞/aɪˈdi(ə)l/理想的な, 理想な
solve 動詞/sɒlv/解決する
aspect 名詞/ˈæspɛkt/様相
narrow 形容詞/ˈnæɹəʊ/狭い
landscape 名詞/ˈlan(d)skeɪp/景色, ランドスケープ
partly 副詞/ˈpɑɹtli/部分的に, 一部

動画に出てくる句動詞

単語意味
pick up 動詞拾う, 拾い上げる

注意したい発音

話し手はcan't, doesn't, don'tなど、短縮形や弱形を4回使っています。聞こえたとおりの短い形で発音しましょう。

  • 「th」の音: algorithm /ˈælɡəɹɪðm̩/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/
  • 「sh」と「zh」の音: artificial /ˌɑː.tɪˈfɪʃ.əl/, emotion /ɪˈməʊ.ʃən/, fiction /ˈfɪkʃən/, citizenship /ˈsɪtɪzənʃɪp/, variation /ˌvɛəɹiˈeɪʃn̩/
  • 長い単語（アクセントの位置に注意）: artificial /ˌɑː.tɪˈfɪʃ.əl/, capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, intelligent /ɪnˈtɛlɪd͡ʒənt/, citizenship /ˈsɪtɪzənʃɪp/, mathematical /ˌmæθ(.ə)ˈmæt.ɪ.kəl/

日本語話者が苦手な音：

  • /r/ と /l/ の区別 — /l/ は舌先を歯茎につけ、/r/ はどこにもつけない: algorithm /ˈælɡəɹɪðm̩/, partly /ˈpɑɹtli/, remotely /ɹɪˈmoʊtli/, stroll /stɹoʊl/, generalize /ˈd͡ʒɛn.(ə.)ɹə.laɪz/
  • /v/ — /b/ にならないように、上の歯を下唇に当てる: solve /sɒlv/, surveillance /sɚˈveɪ.ləns/, variation /ˌvɛəɹiˈeɪʃn̩/, perceive /pɚˈsiv/, pave /peɪv/
  • /f/ — 「フ」ではなく、上の歯と下唇で出す: artificial /ˌɑː.tɪˈfɪʃ.əl/, fiction /ˈfɪkʃən/, smartphone /ˈsmɑɹtfoʊn/, classify /ˈklæs.əˌfaɪ/

この動画での練習方法

  1. まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
  2. 通常の速度で一文ずつシャドーイングし、話し手のリズムに合うまで繰り返します。
  3. 自分の声を録音して元の音声と比べます。robot, artificial, emotionなどの単語に特に注意しましょう。

シャドーイングとは？英語上達に効果的な理由

シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

シャドーイングのやり方: ステップ別の完全ガイドを読む →