跟讀練習: Lisa Su on AMD’s Competition With Nvidia and Intel - 通過影片學習英語口語

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Lisa, thank you so much for being here tonight with your husband.

麗莎，非常感謝你今晚和丈夫一起來到這裡。

We're honored to have you here as Time's 2024 CEO of the Year.

I will start with an easy question.

President Trump takes office in a few weeks.

Will the new administration be good or bad for the chip industry?

Why don't we go back to the Kate and Clark -like numbers?

I like that.

That was a very nice introduction.

First of all, Sam, Jess, thank you so much.

This is such an honor to be here and such an honor to be amongst this company.

The truth is, we all think about what might happen.

But the most important thing for our business, and probably most businesses, is just having certainty on what's going to happen.

Since the election, I think all of us in business have been thinking about just what the next four years projects,

and I think we are optimistic.

about you know business we're optimistic about the opportunities Obviously, in the semiconductor world, for us and CHIPS,

we're a little bit of a sensitive topic.

We'll get into that.

我們稍後會詳細討論這個問題。

Yes, but overall, I think certainty is a good thing.

是的，但總的來說，我認為確定性是一件好事。

Good.

很好。

Um...

嗯……

You have in the past called AI the most transformational technology you've seen in your career.

您過去曾稱人工智慧是您職業生涯中見過的最具變革性的技術。

I'm curious for this crowd, What do most people get wrong about AI?

我很好奇，對於在座的各位來說，大多數人對人工智慧的誤解是什麼？

Well, let me ask, so how many people in the audience, like, use AI Every day.

好，我想問一下，在座有多少人每天都在使用AI？

That's pretty good.

那挺不錯的。

I think that is the most amazing thing.

我覺得那是最了不起的事。

That's why I believe AI is the most important technology that I've certainly seen in my career.

正因如此，我認為人工智慧是我職業生涯中所見過的最重要的技術。

And back to what you know, people may not quite understand is two things.

回到你所瞭解的內容，大家可能不太理解的有兩點。

One is we're at the very, very, very beginning of AI.

首先，我們現在正處於人工智慧發展的最早期階段。

So whatever you think you're doing today, that seems amazing, it's going to be 10 times more amazing,

所以，無論你今天覺得自己正在做什麼看起來很了不起的事，它都會比你想像的還要了不起十倍。

like even 12 months from now because we're at the very early part of the learning curve.

甚至從現在起的12個月後也是如此，因為我們正處於學習曲線的最早期階段。

And because we're learning, It's not always going to be right.

而且因為我們還在學習，所以不可能每次都做對。

And so, The fact that AI is not right today doesn't mean that it's not the most important technology ever.

因此，人工智慧如今還不夠完善這一事實，並不意味著它不是有史以來最重要的技術。

And Sarah is sitting right here at our table You know, the street always wants the answer today or tomorrow.

而莎拉就坐在我們這桌。你知道，市場總是希望今天或明天就得到答案。

It might take a little bit longer than that, but I think over the next-- this is a five to 10 year cycle that we're in.

可能需要比這更長一點的時間，但我認為我們現在正處於一個5到10年的週期中。

And we're at the very beginning of the cycle, and that's what's so exciting about it.

而我們正處於這個週期的最開端，這正是它如此令人興奮的地方。

I'd love to get into some of the geopolitical issues that you and your company sit across today.

我很想深入探討一下您和您的公司當前面臨的一些地緣政治問題。

AMD's most advanced chips are made outside the United States.

AMD最先進的晶片是在美國境外製造的。

When will they be made here?

它們什麼時候會在這裡生產？

So, I would maybe even take a step back and say, five years ago nobody thought about where chips were made.

所以，我甚至可能會退一步說，五年前根本沒人會去考慮晶片是哪裡製造的。

Nobody thought about where do you get your next chip.

沒人想過你從哪裡能拿到下一塊晶片。

And that is what has really changed for our industry is You know, chips are now at the backbone of everything,

而我們這個行業真正發生的變化是，晶片如今已成為一切事物的核心支柱。

like everything you do, whether it's something in your business or something.

就像你做的每一件事，無論是工作上的事務還是其他方面的事情。

in your home or something in your community goes through, probably thousands of trips a day, and that's what makes it so important.

無論是在你家裡還是社群裡，這類設施每天可能要經歷數千次使用，這正是它如此重要的原因。

And I think the turning point was actually during the pandemic, when people couldn't get enough chips.

我覺得轉折點其實是在疫情期間，當時晶片供不應求。

Like if you remember, you know, people were wondering, like, why were why were the, you know, the cars You know?

就好比你還記得嗎，大家當時都在納悶，那些車到底是怎麼回事，你懂吧？

constrained because you didn't have enough chips, why couldn't you get your computers when you needed it?

由於晶片不足而受到限制，為什麼你們在需要的時候無法獲取到計算機呢？

And that's when it became important as to where you can actually manufacture chips.

就在那時，晶片的實際製造地點變得至關重要。

So yes, from a political standpoint, geopolitical standpoint, It wasn't that important.

是的，從政治和地緣政治的角度來看，這件事並沒有那麼重要。

five or ten years ago, so it wasn't something the United States focused on.

五年或十年前，這還不是美國關注的重點。

And since then, it's become super important.

從那以後，它就變得至關重要了。

It's become, you know, with the CHIPS Act and everything else,

你知道，隨著《晶片與科學法案》以及其他各項政策的出臺，情況已經發生了變化。

And actually, what that has done is it's put so much more investment into this area over the last few years.

實際上，這帶來的影響是，過去幾年裡該領域獲得了大量新增投資。

So, you know, I think it will take us probably the next five plus years to rebuild manufacturing in the United States.

所以，我認為我們可能需要未來五年以上的時間來重建美國的製造業。

But it's going, and it's actually going faster than some might have thought.

但它確實在推進，而且實際進展速度比一些人預想的還要快。

To go back to my question, will you be able to make your most advanced chips in the United States?

回到我的問題，你們能否在美國生產最先進的晶片？

We will.

我們會的。

and that will be in five years?

那會是五年之後的事嗎？

I would say in the next three to five years, you'll start seeing the most advanced chips.

我認為在未來三到五年內，你將開始看到最先進的晶片。

You move that forward, three years, I like that.

把時間往前推三年，我覺得這個想法不錯。

Yes.

是的。

Well, in Arizona right now, I mean, Arizona is like the center of some of the most advanced chips in the country, and we're getting our first chips off the line,

嗯，現在在亞利桑那州，我是說，亞利桑那州就像是美國一些最先進晶片的中心，我們的第一批晶片已經下線了。

and they're looking quite good.

它們看起來相當不錯。

You talked about being at the beginning of this cycle.

你之前提到過，我們正處於這個週期的開端。

There are some reports that AI is actually plateauing.

有一些報道稱人工智慧實際上正進入平臺期。

Isn't that bad news for AMD?

這對AMD來說難道不是壞訊息嗎？

I...

我……

First of all, I don't agree with them.

首先，我並不同意他們的觀點。

Why not?

為什麼不呢？

Because, again, this is the view of whenever we see technology cycles, there are actually arcs.

因為話說回來，這就是我們觀察技術週期時會發現的規律——它們實際上是呈弧線發展的。

So you get a new innovation and it takes you so far.

所以當你獲得一項新創新時，它能帶你走這麼遠。

And then you need the next new innovation and it takes you the next you know, five plus years, and then you see the next.

然後你需要下一項新的創新，這又要花上五年甚至更久，之後你才能看到下一個成果。

And I think we're just at the initial waves of AI.

我認為我們才剛剛處於人工智慧發展的最初幾波浪潮之中。

So today what people want is larger and larger computers.

所以如今人們想要的是越來越大的計算機。

Like you talk about supercomputers.

就像你談到超級計算機那樣。

We just had Every six months they talk about,

我們剛剛才聊過，他們每六個月就會提一次這事。

they rank actually the fastest supercomputers and we just had a couple of supercomputers that were just built.

它們實際上是對最快的超級計算機進行排名，而我們剛剛有幾臺超級計算機建成。

We'll have a faster one.

我們會有一個更快的。

like a year from now.

大概一年後吧。

And the innovation that happens when you have all of this engineering talent come together There are lots of new ideas,

當所有這些工程人才匯聚在一起時，就會產生創新。會湧現出許多新想法。

lots of new algorithms out there.

市面上有很多新的演算法。

Probably what I find most exciting about AI is that you can think about AI solving a broad set of issues.

我覺得人工智慧最讓人興奮的一點，大概是你可以設想它能解決各種各樣的問題。

Like you think about ChatGPT today, you can ask it questions, you can We're talking about some of the things that you might do.

就像大家現在想到 ChatGPT 時，會向它提問，我們現在討論的就是你可能會做的一些事情。

with time you can see the ability to transfer lots of general information.

隨著時間的推移，你可以看到傳輸大量通用資訊的能力。

But there's also a really interesting part of AI, that how you can go really deep and solve some of the world's hardest problems,

但人工智慧還有一個非常有趣的方面，那就是你可以深入鑽研，解決一些世界上最棘手的問題。

This idea that you know, you can accelerate the rate and pace of medical discovery.

這種理念認為，你可以加快醫學發現的速度和步伐。

Like I'm really interested in how AI and healthcare come together because, you know, healthcare is so personal to all of us, right?

我對人工智慧與醫療健康的融合非常感興趣，因為你知道，醫療健康對我們每個人來說都非常私人化，不是嗎？

We all have a family, friends that have been impacted by various diseases.

我們每個人身邊都有家人或朋友受到各種疾病的影響。

If we can accelerate drug discovery, if we can accelerate finding some of these the next wave, I believe you can do that with the next set of AI.

如果我們能夠加快藥物研發的速度，如果我們能夠加快找到下一波候選藥物的程序，我相信新一代人工智慧就能幫我們實現這一目標。

So I don't think we're anywhere near plateauing.

所以我認為我們遠未達到停滯狀態。

I think you might need to do it a different way.

我覺得你可能需要換一種方式來做這件事。

And we've always had this notion as engineers that when you reach a roadblock,

作為工程師，我們一直有這樣一個觀念：當你遇到阻礙時，

you find your next set of ideas to go forward.

你會找到接下來可以推進的新思路。

Well, speaking of doing it a different way, AI requires a massive amount of energy.

說到換一種方式來做，人工智慧需要消耗大量能源。

Is it making our climate worse?

它是否正在讓我們的氣候變得更糟？

Is it harming our planet?

它正在危害我們的星球嗎？

- Thank you.

- 謝謝。

I think we are all in this place where you know, power, is one of the key things that we think about.

我覺得我們現在都處在這樣一個階段，效能是我們考慮的關鍵因素之一。

How do we get enough energy for what we want to do?

我們如何才能獲得足夠的能量來完成我們想做的事情？

You do need a lot of energy to run these massively powerful systems.

執行這些功能極其強大的系統確實需要大量能源。

100

I think AI can also help us conserve, actually, energy in the sense

我認為人工智慧實際上也能在這個意義上幫助我們節約能源。

101

that it'll help us solve problems in a different way so that you won't have to necessarily take as long.

它將幫助我們以不同的方式解決問題，這樣你就不一定需要花那麼長的時間了。

102

Like one of the most interesting parts of AI

就像是人工智慧最有意思的一個方面

103

is It should be able to kind of help us get to the answer, some problems that might have taken Um,

它應該能在一定程度上幫助我們找到答案，解決一些原本可能需要花費很長時間的問題。

104

months or even years to simulate.

需要數月甚至數年才能完成模擬。

105

Like if you think about some of the latest discoveries, latest drug discoveries and how long things take, you can imagine a time when that might be done in days or weeks.

比如，如果你想想一些最新的發現、最新的藥物研發，以及這些過程需要多長時間，你就可以想像有一天這些工作可能只需要幾天或幾週就能完成。

106

And so that's how you see the trade -off between energy and and more computing power.

這樣你就能看到能耗與更強計算能力之間的權衡關係了。

107

China just opened an antitrust investigation into NVIDIA.

中國剛剛對NVIDIA啟動了一項反壟斷調查。

108

Are you worried that a geopolitical fight between China and the U .S will harm your business?

您是否擔心中美之間的地緣政治鬥爭會對您的業務造成不利影響？

109

So, There's a lot of discussion about the US and China.

關於美國和中國，目前有很多討論。

110

and what that means.

以及這意味著什麼。

111

I'm sorry.

對不起。

112

Clearly, chips have become something that are so important from a national security standpoint.

113

And we recognize that.

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There are some chips, for example, that are so special that we can't ship to China, that we can't ship to certain other restricted countries.

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I I think balance is always important in these things.

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Look, China's also an important market for us.

117

you know, China as there are lots and lots of uses of semiconductors, and we like to have balance in this.

118

It's so important, you know, we talked about the new administration at the top.

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Uh, What's really important is for there to be a good dialogue between sort of the public sector and the private sector.

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I think there's a lot of partnerships that are necessary.

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That's true in most industries.

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That's certainly very true in our industry.

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And the key is that we want to have the ability to protect national security,

124

while also ensuring that we have access to the Chinese market.

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Those who work with you say you're a competitive person.

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Is that okay?

127

It's fantastic.

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Is there a day when AMD will be bigger than NVIDIA?

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AMANDA SCHADE: You know-- Competition is a good thing,

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but one doesn't-- I believe that there are multiple winners in this market.

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And the key for us is-- Are we putting out new technology?

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Are we putting out technology that is changing the world?

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Are we helping solve some of the world's most important problems?

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Those are really, really important.

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And at the end of the day, you know, who's bigger, who's smaller, we'll see.

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We'll see how that plays out.

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I think the challenge is on.

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Speaking of competition, there's an opening in the CEO's office at Intel. Who should take it?

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You know Sam, this was supposed to be a pleasant dinner, wasn't it?

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I mean like… I think they're having a great time.

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Look, I have a lot of respect for Pat as a colleague.

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So I've known him for many, many years.

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It is hard to turn around a semiconductor company.

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But let me start with that.

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There are, the thing about our

146

industry is that the decisions that you make today you actually won't see the fruits of that labor for like, five years.

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I mean that's the case.

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It's like a five year cycle.

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It takes that long to design products, to think about technology, to think about markets going forward.

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So I would say it's a tough job.

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It's a tough job.

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Has the Biden administration encouraged you to merge with Intel?

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Yeah.

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I think the answer to that question is no. So I can answer that question.

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I think what we're all looking for is how do we make the U .S industry stronger.

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All right.

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The US leads in semiconductors today, in semiconductor design.

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We have been fortunate enough with Silicon Valley,

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with all of the intellectual property that we've developed over the last many years for

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um just the innovation in our culture you know that's

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that goes with startups but also with larger more advanced companies um you know we've actually

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acquired a number of companies over the last few years, and it's added a lot to the equation.

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We're going to continue to do that.

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As an industry, we're going to continue to push the envelope on technology.

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I think that's something that we should be really proud of.

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We want to have the best chips.

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We want to have the best computers.

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We want to use those computers to solve the most difficult problems.

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How we do that as an industry? is partnering.

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Like actually, you know, we are partnering, you know, with Intel on a number of things.

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We're partnering with many of the companies in the semiconductor industry

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Because there's no one company that has all of the good ideas.

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It is a place where

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We absolutely have to come together and there are places where we're going to compete

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and there are places where we're going to collaborate.

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I think one of the things that stands out in reading

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and listening to people talk about your journey as a leader is the points in time where

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you decided not to do something when people were encouraging you to do that.

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We often talk about leadership as what you do, but it's just as frequently what you choose not to do.

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Is there a moment in time, a decision that sticks out for you where you said everyone was telling you to go this way and you said, no, we have to go that way?

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Probably the most striking moment in time is Whenever you think about technology,

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people always are most interested in what you're doing today.

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Like, what's the fad of today?

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So when I first took over as CEO, it was 2014 and 2015 time frame.

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And the fad was-- not fad is not the right word-- but the more interesting thing was, you're so excited about your next Apple iPhone.

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You're so excited about the next tablet that you're going to buy.

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And people were asking-- my board was asking me Lisa, why are we not like doing that.

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Like why are we not in phones?

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Why are we not in tablets?

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And the truth was, you know, those are fine businesses to be in, but they're not AMD.

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Like AMD, we build big computers.

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That's what we do.

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We build big computers.

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And many of you may not have heard about AMD, certainly 10 years ago, maybe five years ago.

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Hopefully in the last year you've heard us from time to time.

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We build big computers, and big computers were not sexy.

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Um...

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10 years ago, but they're kind of sexy now.

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Right?

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I mean, you're talking to me about AI.

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I'm lucky enough to sit amongst this audience.

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And Um, I think that's the key.

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The key is to be very clear on what you want to be best at.

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And it doesn't have to be the most popular thing.

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but it has to be something that you know will make a difference.

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Well, Lisa Su, thank you for making supercomputer sexy.

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We're so glad to have you here.

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Thank you.

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FOR YOU

對話背景與核心內容

這段影片是AMD執行長Lisa Su的訪談，她分享了對AI、晶片產業及地緣政治的看法。對話圍繞科技趨勢、行業挑戰展開，語言口語化且資訊密度高，非常適合作為看YouTube學英語的素材，既能瞭解行業動態，又能提升聽力和口語。

日常交流必備的5個實用表達

certainty：確定性。例：商業運營中，certainty比猜測更重要。
transformational technology：變革性技術。AI被稱為transformational technology，影響深遠。
backbone：支柱。晶片是現代科技的backbone，支撐著各類應用。
turning point：轉折點。疫情是晶片產業的turning point，改變了人們對製造地的關注。
constrained：受限制的。汽車生產因晶片短缺而constrained。

跟著影片練口語：Shadow Speak分步指南

想通過這段影片練shadowspeak？只需3步：
1. 先盲聽1遍，抓整體大意，注意Lisa Su的語速和語調；
2. 逐句暫停，模仿發音和重音（比如"transformational"的重音在第4個音節），尤其練習連讀（如"a little bit longer"），提升英語發音；
3. 完整跟說3遍，錄音對比，重點糾正"certainty"、"constrained"等難詞的發音。
這段對話話題正式但表達自然，適合雅思口語練習，能幫助你掌握職場和科技類話題的用詞。堅持用shadow speak法練習，口語流暢度會明顯提升！

影片中的語法

說話人最常用的結構，並附上影片中的原話：

結構	影片中的用法
現在完成時 have/has + 過去分詞 — 過去發生但與現在仍有關聯的事	you've seen · I've certainly seen · has really changed
被動語態 be + 過去分詞 — 強調發生了什麼，而不是誰做的	are made · be made · were made

什麼是跟讀法？

跟讀法 (Shadowing) 是一種有科學依據的語言學習技巧，最初開發用於專業口譯員的培訓，並由多語言者Alexander Arguelles博士普及。這個方法簡單而強大：您在聽英語母語原聲的同時立即大聲重複——就像是一個延遲1-2秒緊跟說話者的影子。與被動聽力或語法練習不同，跟讀法強迫您的大腦和口腔肌肉同時處理並模模擬實的講話模式。研究表明它能顯著提高發音準確性，語調，節奏，連讀，聽力理解和口語流利度——使其成為雅思口語備考和真實英語交流最有效的方法之一。

影子跟讀法: 閱讀完整分步指南 →

跟讀練習: Lisa Su on AMD’s Competition With Nvidia and Intel - 通過影片學習英語口語

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跟著影片練口語：Shadow Speak分步指南

影片中的語法

什麼是跟讀法？