Luyện nói tiếng Anh bằng Shadowing qua video: The AI Bubble… We Need to Talk

Đang tạo bài học...
1
Right now, half of the internet's screaming that AI is the biggest bubble in history.
2
The other half's screaming that it's the biggest breakthrough since sliced bread.
3
And honestly, I avoided making this video for a long time, mostly because AI is the only thing anyone talks about anymore.
4
But the longer this debate spiraled, the clearer it got to me that both sides were arguing about the wrong thing entirely.
5
It's reached a point where I felt like I couldn't just sit back and watch anymore, so here we are.
6
right.
7
Both of them are watching the wrong thing entirely.
8
They're missing what's hiding in plain sight.
9
Everyone in this fight is arguing about the same thing: user growth, adoption, revenue, how many people are using this stuff.
10
They're all just arguing about demand.
11
But demand is also the side of the coin that can lie to you.
12
It's noisy, it's narrative driven, and it's a story that changes depending on who's telling it and what they're trying to sell you.
13
But every coin has two sides.
14
And the other side, the one nobody's talking about, is the side that paints a much better picture of what's actually unfolding.
15
It's what the world's best investors have quietly used to track financial bubbles for more than 200 years.
16
And it starts by looking at the other side of the coin: supply.
17
Because demand can be faked, and we'll get more into exactly how that happens a bit later.
18
But you can't fake supply.
19
Supply takes real capital, committed up front, and it tells the real story of what's happening.
20
This year alone, the biggest tech companies in the world are on track to spend around $725 billion on artificial intelligence.
21
And when most people hear a number like that, they usually just scroll right past it, without ever stopping to picture how much money that actually is.
22
Because $725 billion isn't just a big number, it's an almost incomprehensible amount of money.
23
To put it into perspective, if you spent $1 million every single day starting from the day Jesus was born, all the way through the fall of the Roman Empire,
24
the Middle Ages, the Renaissance, both world wars, and all the way up to today, you still wouldn't have spent as much as Big Tech is projected to spend in AI in just this year.
25
It breaks down to roughly $2 billion a day,
26
$83 million an hour, or about $23 ,000 every second. on artificial intelligence.
27
We've never seen a bubble of this size before.
28
But as Mark Twain put it, "History doesn't repeat itself, but it often rhymes.
29
And what we're seeing right now is very familiar." The real
30
question isn't whether AI is going to change the world or not.
31
That part doesn't actually really matter.
32
Financial bubbles aren't required to be built on bad technology.
33
In fact, most of the time, it's the opposite.
34
ResearchGate looked at 175 years of major breakthroughs, from 1825 to 2000, that included innovations like the television, the automobile, and the internet.
35
And they found that 37 of the 51 major breakthroughs in technology triggered a massive speculative financial bubble.
36
As billionaire investor George Soros said, "Stock market bubbles don't grow out of thin air.
37
They have a solid basis in reality, but reality is distorted by a misconception." If you look throughout history, it's the same pattern repeating itself over and over,
38
and it always ends the same way.
39
Which is why the best investors have stopped watching the demand side and started watching the supply side.
40
Because when you follow the paper trail, you get to the truth.
41
It starts with a framework that is rooted in some of the oldest ideas in economics, going all the way back to Adam Smith's in the 1700s.
42
The increase of stock, which raises wages, tends to lower profit.
43
When the stocks of many rich merchants are turned into the same trade, their mutual competition naturally tends to lower its profit.
44
And when there is a like increase of stock in all the different trades carried on in the same society, the same competition must produce the same effect in them all.
45
When Adam Smith says "stock," he is referring to capital and productive assets.
46
So translate this out of 1700's powdered wig talk, and what Adam Smith is really saying is that money naturally flows into industries where there are perceived high returns,
47
which means more competition enters, which ultimately drives returns down for everyone in the industry.
48
And this idea has been modernized and expanded upon into a framework with a new name, the capital cycle theory.
49
It ignores the noise involved with demand
50
and just focuses on what actually matters: the capital cycle theory flowing through the supply side of an industry.
51
And after I explain how it works, you'll start to notice the same patterns repeating across stock market bubbles throughout history.
52
The capital cycle moves through an industry in four steps.
53
First, the flood.
54
A new technology shows up, the returns look sexy, and capital comes pouring in to chase them.
55
Step two is the boom.
56
Money keeps pouring in, competitors pile in faster than the demand can grow, and the more everyone builds, the more the returns start to slip.
57
Step three: the collapse.
58
All that new supply finally crushes the very returns that attracted it in the first place.
59
Prices fall, companies fail, the industry consolidates, and a lot of people lose a lot of money.
60
And finally, the inheritance.
61
This is where the real money gets made.
62
Capital flees the industry, the builders go bankrupt, and somebody walks into the wreckage, buys the assets for pennies on the dollar,
63
and collects the value the original builders in the industry paid for.
64
That's the capital cycle The best opportunities show up where capital is fleeing, the worst where it's flooding in.
65
And if you go back through history, you'll see the capital cycle showing up again and again.
66
But before I show you, here's Oaktree Capital co -founder and billionaire investor Howard Marks, breaking down how history repeats itself in the markets.
67
Most people ignore history.
68
Most booms, and I, you know, I've probably lived through about half a dozen real booms in my 50 years in the business.
69
um...
70
are usually about something new.
71
And The Internet in '99, the Nifty Fifty, Xerox in '69, whatever it might be, subprime mortgage securities.
72
The people who get excited about it,
73
who caught into it, who are intoxicated by the positives and willing to ignore the negatives um If you say to them,
74
"Well, that happened 20 and 40 years ago
75
and it ended badly," what they say is they use the four worst words in the world.
76
It's different this time.
77
The rules of the past don't apply.
78
Yes, the average P -E ratio historically has been 16, but now it's 32, and that's okay, because the Internet has changed the world.
79
So let's rewind to one of the earliest examples of the capital cycle theory playing out from start to finish.
80
Take yourself back to the 1830s.
81
The first industrial revolution is in full swing in Britain.
82
Mines and factories need to move coal and iron faster than horse -drawn wagons allow them to.
83
Then new railway technology shows up and changes everything.
84
And where excitement is, the money follows.
85
This is the flood.
86
Capital poured into anything with the word "railway" attached to it.
87
And not just from bankers, shopkeepers, clergymen women, widows, all of them piled into railway stocks, because nobody wanted to be the one who missed out on getting rich.
88
At its peak, railway investment hit around 7 % of the entire British economy.
89
In a single year, parliament passed 272 separate acts just to authorize new lines.
90
Then came the boom.
91
Companies stopped building the railways the country needed and started building whatever they thought would push their share price up.
92
Routes got duplicated, lines got run out to villages that would never fill a single train.
93
Then a reality check came
94
when the new lines were bringing in only about a quarter of the revenue investors had been promised.
95
And once that was undeniable, the math caught up all at once.
96
By 1850 the collapse was in full effect, and the British Railway Index saw its shares being worth less than half their peak.
97
Fortunes that had felt permanent were simply gone.
98
And then the last step: the inheritance.
99
The original investors got wiped out, themselves laying were still sitting in the ground.
100
Over the following decades, that network became the backbone of the entire British industrial economy.
101
And the people who got rich were the ones who scooped those assets up for pennies after the bubble burst.
102
That's the capital cycle from start to finish: flood, boom, collapse, inheritance.
103
Money flooded toward the shiniest new industry, certain that's where the best returns were, until all the competition led to oversupply,
104
returns getting crushed, and the people who supplied the boom were destroyed by the very supply they created
105
while the value they paid for was left for whoever showed up after the crash to snag for a great price.
106
But while the top hats and mutton chops make it easy to dismiss all this as a Victorian problem, we would never fall victim to now.
107
That couldn't be farther from the truth.
108
Jump all the way to the late 90s, and we can see the same cycle play out again.
109
After the US rewrote its telecom laws in 1996,
110
the flood poured into fiber optic cable. and under the oceans.
111
But then the hype started to fade, and reality caught up.
112
Around 85 % of all that fiber sat in the ground completely unused.
113
Bandwidth prices fell about 90%.
114
The Nasdaq fell more than 70%.
115
And Corning, one of the largest fiber makers in the world, watched its stock go from over $100 a share to about a dollar.
116
And funny enough, Corning over the past year has become one of the hottest names in AI right now, and their stock chart looks awfully similar today, as it did back in the early 2000s.
117
If we fast forward another decade, we see the pattern play out again in oil.
118
Innovations in fracking unlocked massive, previously inaccessible reserves.
119
Capital flooded in, drillers came chasing all at once, US oil production roughly doubled, and the US became the largest oil producer on earth.
120
the price of oil collapsed from over $100 a barrel to about $30.
121
More than 200 North American oil and gas companies went bankrupt, the borrowers drowned, and the cheap energy they left behind got picked up at a steep discount.
122
So railway mania in the 1840s, fiber optic cable in the late 90s, and shale just over a decade ago.
123
Three different centuries, three different technologies, three completely different industries, nothing in common except one thing: the exact same cycle playing out underneath all of it.
124
Which brings us to the biggest one yet, the one our entire economy is currently clinging onto for dear life: artificial intelligence.
125
This is the one that matters the most, because when the other three collapsed, they took down some investors and a couple of industries.
126
But artificial intelligence right now is holding up the entire economy.
127
Before we get into just how big this AI thing has actually become, a quick pause.
128
Because a lot of what I've covered so far comes down to one pattern: the people building countries,
129
the infrastructure, the capital, they spend first, and hope demand shows up later.
130
Which brings us to the sponsor of today's video, Printful.
131
They do the opposite.
132
Printful is print -on -demand.
133
You make a design, put it on a product, and nothing gets made until someone's already bought it.
134
Meaning no upfront inventory costs, no stacks of boxes taking over your garage, and no risk of being stuck with products nobody wants.
135
The order comes first.
136
Printful handles everything after that.
137
Here's what it looks like.
138
I just take whatever design I choose.
139
Upload it to a product inside Printful, like this coffee mug.
140
Connect to a store like Shopify or Etsy.
141
Publish it.
142
Set up billing.
143
And that's it.
144
The whole process takes less than an hour, and I'm ready to start selling.
145
With 508 customizable products to choose from, more than a million items fulfilled each month, and a 99 % + order approval rate,
146
Printful is the fastest, most reliable way to turn an idea into a product you can sell online.
147
If you're interested, you can check out Printful using the link below or in the pinned comment.
148
Thank you to Printful for sponsoring this video.
149
And now back to how the entire United States economy has quietly become dependent on one massive bet.
150
A Harvard economist named Jason Furman ran the numbers, and in the first half of 2025, he found that investment in information processing equipment and software,
151
which is the AI build -out, was only about 4 % of GDP, but it accounted for roughly 92 % of all the growth in the US economy.
152
So if you strip the AI build -out from the equation, the US economy only grew at about 1 /10th of 1%.
153
So where does AI sit inside the capital cycle?
154
Well, the money is still pouring in, but if you look closely, There are cracks starting to show.
155
Remember when I said you can fake demand and that we'd come back to it?
156
This is us coming back to it.
157
In the 90s, they faked demand with a story.
158
WorldCom stood up and said internet traffic was doubling every hundred days
159
and the whole industry ran with a number that was never real.
160
This time, they're not faking it with a story.
161
They're faking it with money.
162
You've probably seen this chart that looks like a circuit board.
163
Every name on it is one of the biggest companies in AI.
164
And every arrow is money moving between them.
165
A purchase here, an investment there, a loan over there.
166
And if you follow almost any arrow, it loops back to one place.
167
NVIDIA funds OpenAI.
168
OpenAI pays Oracle.
169
Oracle buys NVIDIA chips.
170
The money makes its rounds throughout the industry and eventually comes home to NVIDIA.
171
And every time it passes a hand, it gets counted again as somebody's brand new demand.
172
market is really just the same money going around in a circle.
173
If this sounds familiar, it should.
174
The fiber bubble ran the same trick.
175
Equipment makers like Lucent and Nortel lent their own customers the money to buy their gear, then booked it as revenue.
176
Activist hedge fund and alternative asset manager Buxton Helmsley clocked this immediately.
177
They noted that: "Vendor financing did not merely add risk at the margin.
178
It manufactured the appearance of end demand.
179
Equipment sold to customers who could pay only because the seller had financed them was recognized as revenue, validated growth narratives, and supported valuations,
180
until the moment the sellers could no longer extend credit." So that circle can do a lot.
181
It can manufacture demand, prop up revenue, and keep the chips moving.
182
But there's one thing it can't do: it can't escape the ideas Adam Smith laid out about money chasing high returns, competition entering, and returns getting compressed for everyone.
183
And the best place to look for returns slipping is in the eye of the storm: OpenAI.
184
Two years ago, OpenAI basically was AI.
185
ChatGPT had no real competition.
186
Then everyone showed up: Google, Anthropic, Meta, XAI, a dozen others, all selling more or less the same thing.
187
It's the boom arriving, right on schedule.
188
AI's financials leaked, for the first time we could see what that competition did to the hottest company in the world.
189
And it's ugly.
190
OpenAI lost $38 .5 billion in 2025, nearly eight times its loss the year before.
191
But the real story for OpenAI isn't just in the headline number, it's buried a few lines down.
192
When you look at what OpenAI had to spend on sales and marketing, it jumped more than 400 % in a single year to $5 .7 billion.
193
That's using the product.
194
That's the cost of the boom.
195
The returns are falling, exactly the way they fell for railways, for fiber, and for shale,
196
which means you already know what comes next and we're already seeing early signals of it throughout the industry.
197
In early June, a chipmaker called Broadcom beat its earnings, but guided its AI sales for the next quarter a few hundred million dollars light.
198
For a company worth nearly $2 trillion, that should barely move the needle.
199
But following that news, about $300 billion of its market value vanished in a single session.
200
One of the biggest single -day losses in Wall Street history
201
over what amounts to a rounding error for a company of Broadcom's size.
202
and soft guidance can erase $300 billion in a day, you're not looking at a healthy market.
203
You're looking at one priced for perfection, where being even slightly less than perfect costs you more than a quarter of a trillion dollars.
204
There's an old line in business: the pioneers get the arrows, and the settlers get the land.
205
It means the first companies into a new market take the hits: the risk, the losses, and the resistance.
206
Then the later arrivals walk in after everything has stabilized, the dust has settled, and quietly take the prize without ever
207
You've watched this happen in front of your eyes for your whole life, whether you realize it or not.
208
Take search.
209
In the mid -90s, AltaVista, Lycos, and Excite were the pioneers.
210
They spent millions building the first web crawlers and teaching the world what a search engine even was.
211
Then they buried their pages in news, email, and banner ads chasing revenue to pay for it all and let the actual search product decay.
212
Then Google walked in, didn't repeat their mistakes, and took the land or rideshare.
213
Before Uber and Lyft, a company called Sidecar spent its life getting sued by cities and blocked by taxi commissions, fighting the legal battles that made the model possible.
214
And while it was stuck in court bleeding cash, Uber and Lyft copied the model, raised billions, and took over the world on the foundation Sidecar had built.
215
There's countless other examples of this, it's the Capital Cycle Theory.
216
The first movers flood in, prove the market, and pay for it with everything they have, then eventually get taken down by the arrows.
217
The supply they built gets left behind for the settlers, where the second movers walk in and inherit it for pennies on the dollar.
218
Which brings us all the way back to where we started.
219
Everyone is staring at one side of the coin, the demand side, screaming about whether it's real.
220
And it's easy to see why.
221
The demand side is loud, it's a story, and a story is what gets clicked.
222
But in finance, the side that actually decides what happens is never the loud one.
223
It's the quiet mechanics underneath that drive everything.
224
If you want to track that side instead of just following the noise in traditional media, hit subscribe.
225
Once you understand the cycle of how capital flows through industries, the whole fight everyone is having online looks like the wrong fight.
226
Bubble or not was never the right question.
227
The question was always who floods in, who drowns, and who inherits.
228
Once you start asking the real questions, you start getting to the real answers.

Từ vựng và ghi chú luyện nói cho bài học này

Bài luyện nói trình độ C1 này dựa trên video “The AI Bubble… We Need to Talk”. Video này có 228 câu và 3237 từ để luyện shadowing. Phần lời nói dài 17:56. Người nói nói nhanh, khoảng 181 từ mỗi phút, nên sẽ có nhiều chỗ nối âm và nuốt âm. 83% số từ nằm trong 3.000 từ tiếng Anh thông dụng nhất; phần còn lại nên xem trước khi luyện.

Từ vựng quan trọng trong video

15 từ khó nhất trong video, kèm phiên âm và nghĩa:

TừPhiên âmNghĩa
investor danh từ/ɪnˈvɛs.tə(ɹ)/người đầu tư
bankrupt tính từ/ˈbæŋk.ɹəpt/phá sản
billionaire danh từ/ˌbɪl.jəˈnɛɚ/tỉ phú
builder danh từ/ˈbɪl.dəɹ/chủ thầu
bury động từ/ˈbɛɹi/chôn, mai táng
cellar danh từ/ˈsɛləɹ/hầm chứa, hầm rượu
bleed động từ/ˈbliːd/chảy máu, xuất huyết
mechanic danh từ/mɪˈkænɪk/thợ máy
competitor danh từ/kəmˈpɛt.ɪ.tɚ/đối thủ
dismiss động từ/dɪsˈmɪs/đuổi, thải hồi
scroll danh từ/skɹoʊl/cuộn, cuốn
fade động từ/feɪd/nhòa
economist danh từ/iˈkɑ.nə.mɪst/nhà kinh tế học
translate động từ/tɹænzˈleɪt/dịch, phiên dịch
automobile danh từ/ˈɔː.tə.məˌbil/xe hơi, ô tô

Cụm động từ bạn sẽ nghe

TừNghĩa
break down động từhỏng, hỏng hóc
check out động từtính tiền, trả phòng
go back động từtrở lại
stand up động từđứng dậy

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 tạiWe've never seen · have stopped · has been modernized
Câu bị động be + quá khứ phân từ — nhấn vào việc xảy ra, không phải người làmcan be faked · was born · is projected
Mệnh đề quan hệ who / which + mệnh đề — thêm thông tin về người hoặc vậtpeople who get · one who missed · people who got

Phát âm cần chú ý

Người nói dùng 35 dạng rút gọn, ví dụ they're, can't, isn't. Hãy nói theo dạng ngắn đúng như bạn nghe.

  • Âm “th”: breakthrough /ˈbɹeɪk.θɹuː/, underneath /ˌʌndɚˈniθ/
  • Âm “sh” và “zh”: shale /ʃeɪl/, perfection /pɚˈfɛk.ʃən/, equation /ɪˈkweɪ.ʒən/
  • Từ dài — đặt trọng âm cho đúng: inheritance /ɪnˈhɛɹɪtəns/, competitor /kəmˈpɛt.ɪ.tɚ/, economist /iˈkɑ.nə.mɪst/, automobile /ˈɔː.tə.məˌbil/, historically /hɪˈstɔɹɪkli/

Những âm người Việt thường gặp khó:

  • Cụm phụ âm cuối — đọc đủ từng âm, đừng nuốt âm cuối: inheritance /ɪnˈhɛɹɪtəns/, bankrupt /ˈbæŋk.ɹəpt/, economist /iˈkɑ.nə.mɪst/, merchant /ˈmɝt͡ʃənt/
  • Âm /tʃ/, /dʒ/ và /ʒ/ — tiếng Việt không có, đừng đọc thành “ch” hay “gi”: equation /ɪˈkweɪ.ʒən/, merchant /ˈmɝt͡ʃənt/
  • Âm /æ/ — mở miệng rộng hơn âm “e”: bankrupt /ˈbæŋk.ɹəpt/, mechanic /mɪˈkænɪk/, translate /tɹænzˈleɪt/

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 investor, bankrupt, billionaire.

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 →