쉐도잉 연습: Is the AI Boom Just Another Bubble? - 영상으로 영어 말하기 배우기
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Hey there! I believe most of you here have heard of AI or even used it, like ChatGPT, Gemini, and others. Maybe you use it to help with your tasks, ask questions, make pictures, create videos, and some people are even getting married to it. Everything feels AI-hyped right now. Many companies are starting to build their own AI too. Google, Microsoft, Elon, and many others are making it, using it, and pouring billions of dollars into it. You might also see AI-related stocks like Nvidia going crazy over the past few years. Investors are happy, so they pour in even more money. And then, suddenly, you stop and think… wait, hold on. Isn’t this starting to feel like a bubble? Everyone seems way too excited and is throwing billions into AI almost blindly. People have been saying this for a long time, and now you’re probably wondering, is it really a bubble? Well, in this video, we’re going to talk about how bubbles really happen, why so many people say AI is a bubble, the infinite circular money glitch, whether this is the dot-com bubble 2.0, and finally, whether AI will really burst and crash. Alright, let’s get started.
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Section 1. How bubbles really happen. So, when everyone says AI is in a bubble, some of you might ask, what is a bubble? A bubble is like this. Everyone starts buying the same thing because they think it will be super valuable later. At first, only a few people buy it. Then more people copy. Soon, everyone is buying it just because everyone else is buying it. Nobody really stops to ask if it’s actually worth that much right now. So, the price goes higher and higher, even though the real value hasn’t changed much yet. And when people finally realize it’s not as amazing as they imagined, they stop buying. That’s when the bubble pops.
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And bubbles have happened many times before. In fact, many major economic crises were also linked to bubbles. For example, the 2008 housing bubble, when everyone rushed to buy houses and it eventually popped, played a major role in causing a global crisis. There was also Japan’s economic bubble, which is one reason its economy stayed weak for decades. And of course, the dot-com bubble in the early 2000s, which was driven by internet hype. So, bubbles have happened many times, in many countries, and with many different technologies.
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Section 2. Why so many people say AI is a bubble? Mostly because it feels very familiar. People remember what happened during the dot-com era, when the internet was new and exciting. Back then, prices went up fast, excitement went crazy, and everyone believed the future had already arrived. That memory never really disappeared. And because both are transformative technologies with similar hype stories, people connect AI to the dot-com bubble. For example, ChatGPT needed only 2 months to reach 100 million users, much faster than platforms like TikTok, which needed about 9 months, or Instagram, which needed 2.5 years, or Facebook, which needed more than 4 years. AI tools are being used by professionals and regular people across many industries. So, you might think, if platforms like Facebook, Instagram, and Google made tons of money, then AI tools like ChatGPT should make even more money, right?
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Well, that’s the problem. Many AI companies are still not clearly profitable, especially OpenAI, the company behind ChatGPT. AI is extremely expensive to run. Training models, buying chips, running servers, paying engineers, and doing constant research all cost huge amounts of money. AI needs GPUs, which are special machines that handle the heavy calculations, and that is super expensive. Some estimates suggest training GPT-4 may have cost tens of millions of dollars, and possibly over $100 million. And that’s not even the end of the cost. Every time you use ChatGPT online, all the calculations happen on OpenAI’s servers.
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That means electricity, cooling systems (often water-based), and maintenance all add to costs.
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At the same time, users expect AI to be cheap or even free. For example. When many people saying something simple in ChatGPT like “thank you” actually cost millions for OpenAI. Of course, one “thank you” costs almost nothing, but billions of them add up to millions of dollars. Some reports and estimates suggest OpenAI may have lost around $11.5 billion in a single quarter in 2025! With this situation, it starts to make sense why so many people call this an AI bubble.
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Section 3. The infinite circular money glitch. One of the biggest reasons people worry about an AI bubble is something called circular investment. The idea is simple. Big AI companies invest in each other, then buy from each other, which makes growth look much bigger than it really is.
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Here’s an over-simplified example with numbers so it’s easy to see. Remember, this is an over-simplified version. So, a chip company like Nvidia designs the most important chips for AI. An AI company like OpenAI needs those chips to run ChatGPT and train new models.
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So, let’s say Nvidia invests $10 billion into OpenAI, either directly or through long-term deals and partnerships. OpenAI now has more money and more computing power, so it spends a large part of it on cloud computing for more powerful AI.
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Now look at where that money goes. OpenAI spends $8 billion on cloud services from companies like Oracle or other AI cloud providers. Those cloud companies use that $8 billion to buy GPUs and hardware, mostly from Nvidia. So, a big part of the original $10 billion flows back to Nvidia as chip sales. So, Nvidia sees higher revenue. OpenAI shows growth. Cloud companies see higher sales. On paper, everyone looks like they’re winning.
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And again, this is an over-simplified version, because the real scenario looks like this. Yeah, quite different and more complicated but the idea is same.
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From the outside, valuations go up and revenues look strong. But the uncomfortable question is this: how much of this money comes from real users and businesses paying from outside the system, and how much is just the same tens of billions of dollars moving in a circle? If one part of that loop slows down or stops, the pressure spreads quickly to everyone else. Even though big companies like Nvidia, Oracle, and Microsoft are quite diversified beyond AI, the idea of money just moving around still makes people worry. Section 4. Is this dot-com bubble 2.0? So, as I mentioned before, in the early 2000s there was a bubble called the dot-com bubble. The internet was the new hype, and investors threw money at almost any company with “.com” in its name, even if it had no profits and no real business model. At its peak, over 400 internet companies went public, and the Nasdaq, which is heavily focused on technology stocks, jumped by over 600% in total.
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So, is this just the same scenario, with a different mask? The short answer is, there are indeed similarities. Because of that history, people today look at AI and feel uneasy.
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Like the internet in the past, AI is also a new technology. AI-related stocks have pushed tech markets sharply higher again in recent years. Excitement is high, investment is massive, and expectations are huge. While many AI-leading companies like Nvidia, Microsoft, and Google are making huge profits and are strong, cash-rich businesses, very different from dot-com companies, where many didn’t even make a single penny, but other companies like OpenAI are still burning tons of money with unclear profit potential. This makes people wonder: how long will this trend survive?
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Section 5. Will the AI bubble burst, and what happens next? So, the big question is, will the AI bubble actually burst? The honest answer is, it might. There’s a real possibility it will happen.
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But that doesn’t mean AI will suddenly disappear. When bubbles burst, what usually breaks first is not the technology itself, but the hype around it. If AI does burst, the first thing that happens is that money slows down. Investors become more careful. Companies stop throwing money at every AI project just because it sounds cool. AI companies that don’t make real profit will struggle, while the ones that survive will rise again. But here’s the important part. AI itself doesn’t go away. Just like after the dot-com bubble, the internet didn’t disappear. I mean, you’re literally watching this video on the internet right now. What disappeared were unrealistic business models, like Pets.com, a company selling pet products that earned hundreds of thousands but spent millions. That didn’t last. But companies that proved their businesses could survive didn’t die. Many people forgot that Amazon, eBay, and Cisco are all dot-com bubble survivors.
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Are they dead today? No. They’re giants. And if you’re investing in tech stocks, this is why it’s important to understand what you’re actually investing in. Always do your own research. If you want to learn more about market crashes, you can check out my other video on what happens when the stock market crashes. The link is in the description.
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So, in conclusion. AI is a real and revolutionary technology that’s already changing how we work and live. But when a powerful new technology shows up, money often moves faster than reality.
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Some AI companies may fail and some hype may disappear, but AI itself won’t vanish. Just like after the dot-com bubble, the companies that actually make sense are the ones that survive. So, don’t panic, and don’t blindly hype it either. If you want to invest in tech, always do your own research and don’t just follow the crowd or FOMO. Help us keep making videos like this by becoming a member and unlock some exclusive perks too. If you want me to make other videos explaining these topics, please like and subscribe. Thanks for watching.
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이 클립이 좋은 말하기 연습 자료인 이유
이 비디오는 AI 붐과 버블에 관한 논평으로, 일상적인 대화체와 분석적인 표현이 적절히 섞여 있어 영어 말하기 실력 향상에 탁월합니다. 특히 자연스러운 흐름과 논리적인 구조가 뚜렷해, 쉐도잉 연습 시 발음 뿐만 아니라 말의 흐름과 강조점을 익힐 수 있습니다. 또한 "bubble", "circular investment"와 같은 전문 용어도 포함되어 있어 실용적인 어휘력 향상에도 도움이 됩니다.
자연스러운 표현 분석
다음은 비디오에서 자연스러운 표현 몇 가지를 분석한 것입니다.
- "Hey there! I believe most of you here have heard of AI..." : "Hey there"는 친근한 인사말로, 청자를 쉽게 끌어당깁니다. "I believe most of you here"는 주관적인 의견을 표현하면서도 청자와의 공감대를 형성하는 표현입니다.
- "So, the price goes higher and higher, even though the real value hasn't changed much yet." : "goes higher and higher"는 반복을 사용해 강조하며, "even though"로 대조관계를 명확히 하여 논리적 흐름을 이어갑니다.
- "But that doesn't mean AI will suddenly disappear." : "But that doesn't mean"은 전술한 내용을 부정하면서 새로운 관점을 제시하는 자연스러운 전환 표현입니다.
쉐도잉 연습 루틴
이 비디오를 활용한 쉐도잉 연습은 다음과 같이 진행할 수 있습니다.
- 듣고 따라하기 : 비디오를 5초씩 재생하며 즉시 따라합니다. 이때 영어 발음 교정에 주의하여, "bubble"의 [bʌbl] 발음이나 "circular"의 [ˈsɜːrkjələr] 발음을 정확히 따라합니다.
- 녹음하고 비교하기 : 자신의 목소리를 녹음한 후 원본과 비교합니다. 발음 뿐만 아니라 억양과 강조점이 일치하는지 확인하며, shadow speech 기술을 연습합니다.
- 속도 조절하기 : 처음에는 느린 속도로 연습하다가 점차 원본 속도에 맞춥니다. 영어 쉐도잉을 통해 자연스러운 말하기 속도를 익힐 수 있습니다.
- 전문 용어 암기하기 : "circular investment", "valuation" 등의 용어를 메모하고, 문장 속에서 어떻게 사용되는지 분석합니다. 이는 실제 의사소통에서도 유용하게 활용됩니다.
연습에 필요하다면 shadowing site를 활용하여 더 체계적으로 연습할 수 있습니다. 규칙적으로 10분씩 연습하면 2주 내에 발음과 말의 흐름이 눈에 띄게 개선될 것입니다.
이 영상의 문법
화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.
| 문형 | 영상 속 표현 |
|---|---|
| 현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때 | have heard · hasn't changed · have happened |
| 관계절 who / which + 절 — 사람이나 사물에 대한 추가 정보 | bubble, which is · GPUs, which are · other, which makes |
| 수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점 | were also linked · are indeed |
쉐도잉이란? 영어 실력을 빠르게 키우는 과학적 방법
쉐도잉(Shadowing)은 원래 전문 통역사 훈련을 위해 개발된 언어 학습 기법으로, 다언어 학자인 Dr. Alexander Arguelles에 의해 대중화된 방법입니다. 핵심 원리는 간단하지만 매우 강력합니다: 원어민의 영어를 들으면서 1~2초의 짧은 지연으로 즉시 소리 내어 따라 말하는 것——마치 '그림자(shadow)'처럼 화자를 따라가는 것입니다. 문법 공부나 수동적인 청취와 달리, 쉐도잉은 뇌와 입 근육이 동시에 실시간으로 영어를 처리하고 재현하도록 훈련합니다. 연구에 따르면 이 방법은 발음 정확도, 억양, 리듬, 연음, 청취력, 말하기 유창성을 크게 향상시킵니다. IELTS 스피킹 준비와 자연스러운 영어 소통을 원하는 분들에게 특히 효과적입니다.