Shadowing Practice: Did the AI bubble just pop? - Learn English Speaking with Video
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just three weeks ago, it felt like nothing could go wrong.
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SpaceX was up 7 % in a day,
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every tech CEO in America was on stage explaining why they needed another $100 billion to decimate farmland in rural America,
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and Jensen Wong was telling anyone who'd listen that demand for AI chips was insatiable.
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But since then, the market took a dump.
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Meta created an entirely new class of non -voting stock just to pay for GPUs,
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while Microsoft offered a quarter of its employees money to leave so it can afford more of them.
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Elon predicted that 200 NeoClouds are about to experience Guppy -level death, and CoreWeave, a former Ethereum mining operation
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that became the poster boy of reckless AI spending after they pivoted into renting NVIDIA GPUs back to NVIDIA,
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is now worth a third of what it was at the beginning of the month.
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And then on Monday, Anthropic filed to go public, which showed that between January and when the government banned Fable back in June,
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they lost more money than the annual GDP of over half the countries on Earth.
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So naturally, the question on everyone's mind is, are we finally cooked?
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In today's video, we'll break down the roughest three weeks in the history of AI,
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find out what a neocloud is and why Elon wants them dead, and we'll analyze Anthropics financials in their Trust Me Bro S1.
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It is October 28th, 2026, and you're watching the Code Report.
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Before we can talk about the AI bubble, you need to understand how a GPU actually gets paid for.
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And to do that, here's me in a bubble bath to explain.
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First, NVIDIA makes a GPU that they need to sell.
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The problem is the GPU is expensive and you don't have enough money to buy it.
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So NVIDIA says, hey, we have money
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and we'll give it to you as long as you give us a portion of your company
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and use the money we give you to buy our GPUs.
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But NVIDIA's money only covers a fraction of what you need.
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So you go to Wall Street and borrow the rest by putting up the GPU you haven't bought yet as collateral.
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Now normally, a bank wouldn't lend to you with a depreciating pile of chips as collateral,
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but NVIDIA has promised that if nobody rents the GPUs they give you, they'll rent them themselves.
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So NVIDIA's money gets used to buy NVIDIA GPUs that eventually get rented back to NVIDIA, which makes NVIDIA's stock go up,
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which it uses to invest in more companies, which borrow more money to buy more NVIDIA GPUs, which keeps the good times going.
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On Wall Street, they called this a circular financing arrangement, and back in college, we'd call it a s*.
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The most popular company eating this forbidden fruit is CoreWeave, but NVIDIA has done it with a few other companies as well.
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And to be honest, it works pretty well as long as the chips rent for more than they depreciate.
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The labs keep buying, and someone keeps lending you money to buy more chips.
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But three weeks ago, the third one stopped being true when it was discovered that CoreWeave, after it borrowed $52 billion to buy chips,
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was now paying 15 % interest on that debt.
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Then on Sunday night, Elon chimed in, saying that debt markets have almost entirely shut off for any company whose only revenue is AI data centers,
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and that he expects 200 plus of these neocloud type companies to die.
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But conveniently, SpaceX is fine, because it also happens to sell rockets.
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And right in the middle of all this, Anthropic decided to ask the public for $100 billion at a valuation
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that would make it worth more than 492 out of the 500 companies in the S &P 500,
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with 4 out of those 7 remaining companies being where they rent their compute from
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and happen to owe $265 billion to through 2045.
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The S1 itself is 330 pages long, with 90 of those being risk factors to the company, which is the fun part.
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In it, Anthropic admits that everything we've already covered over the last few months is true, including Mythos being allergic to its sandbox,
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Claude Haiku filing a fake homicide tip through the Philadelphia Police Department's website,
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and a Chinese state -sponsored group using Claude code to attack banks and government agencies.
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The filing also says that Claude now uses itself to improve itself,
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and that they might not notice their models getting significantly smarter until after it's already happened.
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Their guiding principle, according to the foreword, is to under -promise and over -deliver,
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which is a little worrisome for a company whose head of alignment was quoted just last month,
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saying he thinks there's a greater than 10 % chance that AI kills all humans within the next decade.
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So are we cooked?
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Well, as always, it depends.
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It's not looking great
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if your whole business model is borrowing money from one company just to give it right back to them.
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But it's hard to call AI a bubble the day after
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OpenAI claims one of its models disproved a 27 -year -old conjecture that half of complexity theory is built on.
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But thankfully, as developers, things are actually looking pretty decent right now, since every one of these companies are fighting to sell us subsidized tokens.
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Akimi just dropped an open model within a point of Opus at half the price that we talked about yesterday,
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and the GPU score we financed should be on eBay any week now.
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And if you'd like to be one of the people profiting from the exit liquidity instead of providing it,
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you can put those subsidized tokens to work with HyperAgent, the sponsor of today's video.
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If you're already paying for ChatGPT, you can now use that plan to sign into HyperAgent
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and hire a team of agents without setting up yet another AI subscription.
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Right now, I'm using it to work on a v4 release of a date library I'm contributing to.
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So I set up a HyperAgent room, which is basically a Slack channel where all my agents and human co -maintainers can work together.
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I've got one agent triaging new issues as they come in another one drafting pull requests for new features, and a third one writing the changelog.
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They all work in parallel and hand things off to each other, and only ping a human when something needs approval.
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And anyone on a team can jump in to ask questions or make changes whenever they want, instead of routing everything through me.
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Sign in with your existing ChatGPT plan to try it out at the link below.
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This has been The Code Report, thanks for watching, and I will see you in the next one.
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Vocabulario y notas de pronunciación para esta lección
Esta lección de conversación se basa en el vídeo “Did the AI bubble just pop?”. Las palabras que más se repiten: Gpu, Nvidia, companies, chips. Este vídeo tiene 71 frases y 1128 palabras para practicar shadowing. La parte hablada dura 5:22. El hablante habla rápido, unas 210 palabras por minuto, así que espera sonidos enlazados y reducidos. Solo el 81 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es exigente.
Vocabulario clave de este vídeo
15 palabras del vídeo que vale la pena aprender, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| chip sustantivo | /t͡ʃɪp/ | astilla, cepa |
| bubble sustantivo | /ˈbʌbəl/ | burbuja, pompa |
| borrow verbo | /ˈbɑɹ.oʊ/ | pedir prestado, tomar prestado |
| sponsor sustantivo | /ˈspɒn.səː/ | patrocinador, patrocinadora |
| lend verbo | /ˈlɛnd/ | prestar, emprestar |
| token sustantivo | /ˈtoʊkən/ | seña |
| collateral sustantivo | /kəˈlætəɹəl/ | prenda, aval |
| naturally adverbio | /ˈnæt͡ʃ.(ə.)ɹə.li/ | naturalmente, a natura |
| bath sustantivo | /bɑːθ/ | bañera |
| decent adjetivo | /ˈdiː.sənt/ | decente |
| hire verbo | /ˈhaɪɹ/ | contratar, emplear |
| discover verbo | /dɪˈskʌvə/ | descubrir |
| exit sustantivo | /ˈɛɡzət/ | salida, partida |
| contribute verbo | /kənˈtɹɪb.jut/ | contribuir, aportar |
| principle sustantivo | /ˈpɹɪn.sɪ.pəl/ | principio |
Phrasal verbs que vas a escuchar
| Palabra | Significado |
|---|---|
| break down verbo | descomponerse, averiarse |
| find out verbo | averiguar, anoticiarse |
| go up verbo | subir |
| put up verbo | colgar |
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora | haven't bought · has promised · has done |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | was discovered · was quoted · is built |
| Oraciones de relativo who / which + oración — información extra sobre una persona o cosa | NVIDIA, which makes · company, which is · room, which is |
Pronunciación a tener en cuenta
El hablante usa 16 contracciones y formas reducidas, como we'll, I'm, you're. Dilas en su forma corta, tal como las oyes.
- Los sonidos de “sh” y “zh”: subscription /səbˈskɹɪpʃən/, fraction /ˈfɹæk.ʃən/, valuation /ˌvæ.ljuːˈeɪ.ʃən/, depreciate /dəˈpriʃiˌeɪt/, insatiable /ɪnˈseɪʃ(j)əbəl/
- Palabras largas — cuida el acento: collateral /kəˈlætəɹəl/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, developer /dɪˈvɛləpɚ/, complexity /kəmˈplɛk.sɪ.ti/, valuation /ˌvæ.ljuːˈeɪ.ʃən/
Sonidos difíciles para hispanohablantes:
- /v/ — no es /b/: los dientes tocan el labio inferior: discover /dɪˈskʌvə/, invest /ɪnˈvɛst/, developer /dɪˈvɛləpɚ/, valuation /ˌvæ.ljuːˈeɪ.ʃən/, conveniently /kənˈvinjəntli/
- /z/ — sonora, no /s/: exit /ˈɛɡzət/, analyze /ˈæn.əˌlaɪz/, subsidize /ˈsʌbsɪdaɪz/
- /dʒ/ — no es la “y” ni la “ch”: arrangement /əˈɹeɪnd͡ʒmənt/, allergic /əˈlɝ.d͡ʒɪk/, changelog /ˈtʃeɪndʒˌlɒɡ/, conjecture /kənˈd͡ʒɛkt͡ʃə/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Empieza a velocidad 0,75×, haz shadowing frase por frase y vuelve a la velocidad normal cuando te resulte fácil.
- Grábate y compara con el original, prestando atención a palabras como chip, bubble, borrow.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.