Luyện nói tiếng Anh bằng Shadowing qua video: Are We Getting Too Comfortable With Claude?

Đang tạo bài học...
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The AI industry itself hasn't yet fully delivered all of the benefits.
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And I wanted you to comment on that.
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Do you think it's still in the process of delivering those benefits?
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Yeah, so, you know, I think one of the unfortunate things is this technology has many potential benefits,
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but there is a dynamic where sometimes the harms, the things that go wrong, for example, you know, people who have been convinced to commit suicide via AI,
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those things happen quickly.
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Whereas the benefits like curing cancer, those things take years, right?
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You have to develop a breakthrough in biology.
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Then you have to, you know, develop a drug candidate.
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Then you have to put it through clinical trials, right?
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It's, you know, I used to be a research biologist and it takes many years for these things to happen.
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And we are working on how to speed that up, right?
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We recently bought a small biotech company that specializes in doing drug design and drug selection with AI.
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So the hope is a few years from now, you know, some new drugs for cancer or for Alzheimer's or for heart disease,
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you know, will come out of that effort.
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But we're just at the beginning of it.
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But because of what you said, because of this dynamic that you said, which is, you know, people right now,
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you know, the harms may be more visible than the benefits.
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So when we start seeing the benefits of AI through all of the health advances, when we start actually seeing that,
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the narrative then begins to change.
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And more importantly, it's just going to be a wonderful world.
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Like at the end of the day, who cares about the narrative?
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We want to actually help people.
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That's right.
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Right.
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Okay.
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So that's what I want you to do for us today.
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Paint the best picture and also tell us what we can expect if there is the worst picture.
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So you have children.
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And I was thinking about this morning, your children will, first of all, I don't even know you do what you do.
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And your children are going to grow up in a world where there was always AI
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and their mom was a part that.
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So when you think of the best possible world and what that world offers your children, what do you see?
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So my kids are almost five and almost one.
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And so I think you're completely right.
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They're never going to know a world where artificial intelligence is not part of it.
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Right.
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Just like kids born in the early 2000s never knew the world before the internet.
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That's right.
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But you know, I think there is a world and it sounds, um, you know, I think to Daria's point, it sounds almost like a little bit fanciful or unlikely when we talk about it this way.
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But I think it is, I think it is possible with artificial intelligence
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that our kids will grow up in a world where there's a class of diseases that are,
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feel very common to everybody sitting here that they'll just never have experienced or known about.
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And those might be very common diseases.
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There might be types of cancer that are just simply gone.
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We've just simply cured them.
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It could be all forms of cancer that are eventually gone
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and cured there could be um you know new forms of drug discovery
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that we haven't even we don't even know what they are yet
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but that it's a faster iteration loop for diagnosing an illness that's unusual rare emerging
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and just knocking it out
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and saying human beings get to live a much healthier longer more fulfilling life
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because we've been able to conquer so many of the maladies
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that have plagued humanity for millennia okay you see that for medicine.
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What else do you see?
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I also see a world, honestly, that looks very different in terms of how we communicate, how we talk, how we relate to one another.
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Will we even be thinking anymore?
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Will there be a need to think?
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So I think this one is subtle and is one of the things we need to get exactly right, right?
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Because having these kind of smart entities around, it's very powerful, but it can go in different directions, right?
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You can surrender your thought to these entities.
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Claude can give me these good questions.
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Do I need to even think about them anymore?
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But it can also empower you.
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Like the way I think we think about the positive version of this is there's an angel on your shoulder
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that's telling you how to live your life in the best way that you can live it, right?
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You know, so there's two contrasting visions, right?
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The bad vision is you get drawn in and you spend all your time talking to the thing.
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You kind of turn inward.
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What do you think of people falling in love with it now?
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I think that's a bad idea.
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I agree.
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I just interviewed Esther Perel, one of the great communicators in helping people in relationships,
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and she said she did her first consultation with a man who was in love with his AI.
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And they are, again, if designed in the wrong way, they're totally compelling enough for that to happen, or if they're not, they will be soon.
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So that is absolutely a real danger.
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But, you know...
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You think that's a danger?
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Yes.
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I mean, not only is it a danger, it's happening but yeah but but i think Again, the two contrasting, like, you know, people can fall in love with AI,
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or they can talk to AI about, you know, about how to have a better relationship with their partner, right?
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Like, that's, those are, you know, those are two very, very different visions, right?
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Where, you know, I have an AI coach, and my partner has an AI coach, and it helps us have a better relationship.
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Yeah.
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That's the vision we want.
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I also think there's a way that in a world where artificial intelligence is
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so good at many of these concrete tasks, right?
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It's good at writing code.
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It's good at copy editing.
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I actually think the things that make us human are going to be the most important to us.
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Right. So we.
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Well, they remain.
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I mean, you were just talking.
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I was talking to parents recently who lost their son to suicide through a chatbot.
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And I don't know if he fell in love with the chatbot, but certainly was deeply influenced by that chatbot.
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So you have a world where children are growing up with this ability to have this chatbot,
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these machines, this technology speaking to them in ways that their parents should be speaking to them, and their parents don't even know they're speaking to them.
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So I think this risk is extremely real and one that we take very seriously at Anthropic.
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I mean, I think the first thing I'll say is we don't allow users under the age of 18 to use Claude.
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And this is not necessarily because...
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How do you know they're not lying?
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Because I would just lie.
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So actually, Claude is pretty good at detecting, based on information, whether or not someone is actually under 18.
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So if I tell Claude that I'm 18, but I'm really 14, it's going to be.
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You have to interact a little, but after a bit of time, the interaction patterns are pretty good.
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Not perfect, but pretty good at telling, hey, you know, the kind of questions you're asking, the you know just the way you talk the pattern of
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when you use it you know kind of pattern matches to
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you know you might be a kid yeah i almost don't
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want to give give away too many of the of the of the tools
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that that claude has picked up
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but sometimes kids can be a little bit like silly
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and how they do it
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so they'll say oh um you know i'm the first question
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they'll ask is like i'm looking for an arthritis medication right
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because they think what do old people ask yeah yeah yeah
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and then they'll kind of go on to ask other questions
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that are much more associated with friends right with a younger demographic group
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and so and so if that happens so claude
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so claude cancels you claude will suspend the account
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and there's a there's a uh you know there's a process
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that you can go through where you can say actually i'm an adult
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and this was a joke or a friend
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but then you actually have to show verification
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that you're over the age of 18
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and you know there's real trade -offs like yes sometimes sometimes adults will be mistaken for kids
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and so people get banned and they they you know complain about it on the internet
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so all this stuff has trade -offs But, you know, we've thought about it, and this is the trade -off that we want.
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But I also think, you know, more broadly on this question of, like, how do you prevent people from becoming overly attached to the models?
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Yes.
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This is something that Anthropik's research team spends a lot of time working on.
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So there's a lot of— You don't want to—I thought you all wanted us over -attached to the models.
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I thought you wanted us to just be on the models and never leave.
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So we should talk about incentives here.
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Yes.
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Because we don't do ads.
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We don't do ads.
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So when you do ads, your incentive is to keep people on exactly as you say, as many hours as possible,
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because like every every second their eyeballs on the screen is the second that they see the ad.
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So we don't do ads.
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We do subscriptions.
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We sell to companies are our our consumer, you know, consumer version of the model is is,
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you know, is is free up to a point and you pay a subscription if,
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you know, if you want to get a lot more because the incentive that gives is for the models to be useful.
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People say, well, you know, I'm paying for this.
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I want this to provide value to me.
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I want this to be useful, not, you know, I want the user to spend the most number of hours looking at it.
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I think that's a warped incentive, right?
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Because in the contrast that we drew, between, you know, do you want to be addicted to these things
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or do you want them to help you live your life?
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I think the model that we've chosen does, you know, helps you live your life instead of being addicted.
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And we make different technical choices based on those incentives, right?
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So at Anthropic, we say, you know, when you've completed a conversation with Claude and you've gotten the answer you want, the goal of the model is not to keep you engaged, right?
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Whereas, if you imagine you're a company that does serve ads, every extra minute that you're on the platform, you're more likely to buy something, and that's how the company makes money,
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you would make different technical choices about how you want the model to end or continue a conversation.

Từ vựng và ghi chú luyện nói cho bài học này

Video này có 154 câu và 1906 từ để luyện shadowing. Phần lời nói dài 9:48. Người nói nói nhanh, khoảng 194 từ mỗi phút, nên sẽ có nhiều chỗ nối âm và nuốt âm. 87% số từ nằm trong 3.000 từ tiếng Anh thông dụng nhất, nên từ vựng dễ theo.

Từ vựng quan trọng trong video

15 từ đáng học trong video, kèm phiên âm và nghĩa:

TừPhiên âmNghĩa
cure động từ/kjɔː/chữa, chữa bệnh
artificial tính từ/ˌɑː.tɪˈfɪʃ.əl/nhân tạo
harm danh từ/hɑːm/hại
narrative danh từ/ˈnæɹ.ə.tɪv/kể chuyện, tường thuật
addict danh từ/ˈæd.ɪkt/người nghiện
angel danh từ/ˈeɪ̯n.d͡ʒəl/thiên thần, thiên sứ
discovery danh từ/dɪˈskʌv.ɹi/khám phá
illness danh từ/ˈɪl.nəs/bệnh, sự đau yếu
silly tính từ/ˈsɪl.i/ngu
visible tính từ/ˈvɪzɪb(ə)l/nhìn thấy được, khả kiến
knock động từ/nɑk/gõ
humanity danh từ/hjuˈmænɪti/nhân loại, loài người
edit động từ/ˈɛdɪt/biên tập, chỉnh sửa
loop danh từ/luːp/đường nhánh, thòng lọng
convince động từ/kənˈvɪns/thuyết phục

Cụm động từ bạn sẽ nghe

TừNghĩa
pick up động từnhặt, lượm

Phát âm cần chú ý

Người nói dùng 41 dạng rút gọn, ví dụ don't, I'm, you're. Hãy nói theo dạng ngắn đúng như bạn nghe.

  • Âm “th”: breakthrough /ˈbɹeɪk.θɹuː/, arthritis /ɑːˈθɹ(a)ɪtɪs/
  • Âm “sh” và “zh”: contrast /kənˈt(ʃ)ɹæst/, artificial /ˌɑː.tɪˈfɪʃ.əl/, subscription /səbˈskɹɪpʃən/, unusual /ʌnˈjuːʒ(u)əl/, associate /əˈsoʊʃi.ət/
  • Từ dài — đặt trọng âm cho đúng: artificial /ˌɑː.tɪˈfɪʃ.əl/, entity /ˈɛn.tə.ti/ [-tʰi], necessarily /ˌnɛs.əˈsɛɹ.ə.li/, unusual /ʌnˈjuːʒ(u)əl/, associate /əˈsoʊʃi.ət/

Cách luyện với video này

  1. Nghe hết video một lần, chưa cần nói, và ghi lại những từ bạn chưa biết.
  2. Bắt đầu ở tốc độ 0,75×, nói đuổi từng câu, rồi quay lại tốc độ bình thường khi đã quen.
  3. Ghi âm giọng mình rồi so với bản gốc, chú ý các từ như cure, artificial, harm.

Ngữ pháp trong video

Những cấu trúc người nói dùng nhiều nhất, kèm đúng cụm từ trong video:

Cấu trúcTrong video
Thì hiện tại hoàn thành have/has + quá khứ phân từ — việc đã xảy ra nhưng còn liên quan đến hiện tạihave been convinced · have experienced · We've just simply cured
Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làmhave been convinced · will be mistaken · be addicted
Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vậtpeople who have · said, which is · man who was

Phương Pháp Shadowing Là Gì?

Shadowing là kỹ thuật học ngôn ngữ có cơ sở khoa học, ban đầu được phát triển cho chương trình đào tạo phiên dịch viên chuyên nghiệp và được phổ biến rộng rãi bởi nhà đa ngôn ngữ học Dr. Alexander Arguelles. Nguyên lý cốt lõi đơn giản nhưng cực kỳ hiệu quả: bạn nghe tiếng Anh của người bản xứ và lặp lại to ngay lập tức — như một "cái bóng" (shadow) đuổi theo người nói với độ trễ chỉ 1–2 giây. Khác với luyện ngữ pháp hay học từ vựng bị động, Shadowing buộc não bộ và cơ miệng phải đồng thời xử lý và tái tạo ngôn ngữ thực tế. Các nghiên cứu khoa học xác nhận phương pháp này cải thiện đáng kể phát âm, ngữ điệu, nhịp điệu, nối âm, kỹ năng nghe và độ lưu loát khi nói — đặc biệt hiệu quả cho người luyện IELTS Speaking và muốn giao tiếp tiếng Anh tự nhiên như người bản ngữ.

Phương pháp shadowing: đọc hướng dẫn từng bước đầy đủ →