Практика Shadowing: Did the AI bubble just pop? - Изучайте разговорный английский по видео

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just three weeks ago, it felt like nothing could go wrong.

SpaceX was up 7 % in a day,

every tech CEO in America was on stage explaining why they needed another $100 billion to decimate farmland in rural America,

and Jensen Wong was telling anyone who'd listen that demand for AI chips was insatiable.

But since then, the market took a dump.

Meta created an entirely new class of non -voting stock just to pay for GPUs,

while Microsoft offered a quarter of its employees money to leave so it can afford more of them.

Elon predicted that 200 NeoClouds are about to experience Guppy -level death, and CoreWeave, a former Ethereum mining operation

that became the poster boy of reckless AI spending after they pivoted into renting NVIDIA GPUs back to NVIDIA,

is now worth a third of what it was at the beginning of the month.

And then on Monday, Anthropic filed to go public, which showed that between January and when the government banned Fable back in June,

they lost more money than the annual GDP of over half the countries on Earth.

So naturally, the question on everyone's mind is, are we finally cooked?

In today's video, we'll break down the roughest three weeks in the history of AI,

find out what a neocloud is and why Elon wants them dead, and we'll analyze Anthropics financials in their Trust Me Bro S1.

It is October 28th, 2026, and you're watching the Code Report.

Before we can talk about the AI bubble, you need to understand how a GPU actually gets paid for.

And to do that, here's me in a bubble bath to explain.

First, NVIDIA makes a GPU that they need to sell.

The problem is the GPU is expensive and you don't have enough money to buy it.

So NVIDIA says, hey, we have money

and we'll give it to you as long as you give us a portion of your company

and use the money we give you to buy our GPUs.

But NVIDIA's money only covers a fraction of what you need.

So you go to Wall Street and borrow the rest by putting up the GPU you haven't bought yet as collateral.

Now normally, a bank wouldn't lend to you with a depreciating pile of chips as collateral,

but NVIDIA has promised that if nobody rents the GPUs they give you, they'll rent them themselves.

So NVIDIA's money gets used to buy NVIDIA GPUs that eventually get rented back to NVIDIA, which makes NVIDIA's stock go up,

which it uses to invest in more companies, which borrow more money to buy more NVIDIA GPUs, which keeps the good times going.

On Wall Street, they called this a circular financing arrangement, and back in college, we'd call it a s*.

The most popular company eating this forbidden fruit is CoreWeave, but NVIDIA has done it with a few other companies as well.

And to be honest, it works pretty well as long as the chips rent for more than they depreciate.

The labs keep buying, and someone keeps lending you money to buy more chips.

But three weeks ago, the third one stopped being true when it was discovered that CoreWeave, after it borrowed $52 billion to buy chips,

was now paying 15 % interest on that debt.

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,

and that he expects 200 plus of these neocloud type companies to die.

But conveniently, SpaceX is fine, because it also happens to sell rockets.

And right in the middle of all this, Anthropic decided to ask the public for $100 billion at a valuation

that would make it worth more than 492 out of the 500 companies in the S &P 500,

with 4 out of those 7 remaining companies being where they rent their compute from

and happen to owe $265 billion to through 2045.

The S1 itself is 330 pages long, with 90 of those being risk factors to the company, which is the fun part.

In it, Anthropic admits that everything we've already covered over the last few months is true, including Mythos being allergic to its sandbox,

Claude Haiku filing a fake homicide tip through the Philadelphia Police Department's website,

and a Chinese state -sponsored group using Claude code to attack banks and government agencies.

The filing also says that Claude now uses itself to improve itself,

and that they might not notice their models getting significantly smarter until after it's already happened.

Their guiding principle, according to the foreword, is to under -promise and over -deliver,

which is a little worrisome for a company whose head of alignment was quoted just last month,

saying he thinks there's a greater than 10 % chance that AI kills all humans within the next decade.

So are we cooked?

Well, as always, it depends.

It's not looking great

if your whole business model is borrowing money from one company just to give it right back to them.

But it's hard to call AI a bubble the day after

OpenAI claims one of its models disproved a 27 -year -old conjecture that half of complexity theory is built on.

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.

Akimi just dropped an open model within a point of Opus at half the price that we talked about yesterday,

and the GPU score we financed should be on eBay any week now.

And if you'd like to be one of the people profiting from the exit liquidity instead of providing it,

you can put those subsidized tokens to work with HyperAgent, the sponsor of today's video.

If you're already paying for ChatGPT, you can now use that plan to sign into HyperAgent

and hire a team of agents without setting up yet another AI subscription.

Right now, I'm using it to work on a v4 release of a date library I'm contributing to.

So I set up a HyperAgent room, which is basically a Slack channel where all my agents and human co -maintainers can work together.

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.

They all work in parallel and hand things off to each other, and only ping a human when something needs approval.

And anyone on a team can jump in to ask questions or make changes whenever they want, instead of routing everything through me.

This has been The Code Report, thanks for watching, and I will see you in the next one.

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Лексика и советы по произношению к этому уроку

Этот урок разговорной практики построен на видео «Did the AI bubble just pop?». Чаще всего повторяются слова: Gpu, Nvidia, companies, chips. В этом видео 71 предложений и 1128 слов для шедоуинга. Речь длится 5:22. Говорящий говорит быстро, около 210 слов в минуту, поэтому звуки часто сливаются и сокращаются. Только 81% слов входят в 3000 самых частых слов английского языка, поэтому лексика сложная.

Ключевая лексика этого видео

15 слов из видео, которые стоит выучить, с произношением и значением:

Слово	Произношение	Значение
chip существительное	/t͡ʃɪp/	ще́пка, лучи́на
bubble существительное	/ˈbʌbəl/	пузы́рь
borrow глагол	/ˈbɑɹ.oʊ/	занима́ть, заня́ть
sponsor существительное	/ˈspɒn.səː/	поручи́тель, поручи́тельница
lend глагол	/ˈlɛnd/	ода́лживать, одолжи́ть
token существительное	/ˈtoʊkən/	знак, си́мвол
collateral существительное	/kəˈlætəɹəl/	поручи́тельство, зало́г
naturally наречие	/ˈnæt͡ʃ.(ə.)ɹə.li/	есте́ственно
bath существительное	/bɑːθ/	ва́нна
decent прилагательное	/ˈdiː.sənt/	подходя́щий, прие́млемый
hire глагол	/ˈhaɪɹ/	брать напрока́т, взять напрока́т
discover глагол	/dɪˈskʌvə/	открыва́ть, откры́ть
exit существительное	/ˈɛɡzət/	вы́ход
contribute глагол	/kənˈtɹɪb.jut/	де́лать поже́ртвования, де́лать взно́сы
principle существительное	/ˈpɹɪn.sɪ.pəl/	при́нцип

Фразовые глаголы, которые вы услышите

Слово	Произношение	Значение
set up глагол	/ˌsɛt ˈʌp/	устана́вливать, установи́ть
break down глагол		ломаться, сломаться
find out глагол		узнава́ть, узна́ть
go up глагол		поднима́ться, подня́ться
put up глагол		ста́вить

Грамматика в этом видео

Конструкции, которые говорящий использует чаще всего, с точными словами из видео:

Конструкция	В видео
Present Perfect have/has + причастие прошедшего времени — прошлое действие, важное сейчас	haven't bought · has promised · has done
Пассивный залог be + причастие прошедшего времени — важно, что происходит, а не кто это делает	was discovered · was quoted · is built
Придаточные определительные who / which + предложение — уточнение о человеке или предмете	NVIDIA, which makes · company, which is · room, which is

Произношение, на которое стоит обратить внимание

Говорящий использует 16 сокращённых и редуцированных форм, например we'll, I'm, you're. Произносите их коротко, так, как слышите.

Звуки «sh» и «zh»: subscription /səbˈskɹɪpʃən/, fraction /ˈfɹæk.ʃən/, valuation /ˌvæ.ljuːˈeɪ.ʃən/, depreciate /dəˈpriʃiˌeɪt/, insatiable /ɪnˈseɪʃ(j)əbəl/
Длинные слова — следите за ударением: collateral /kəˈlætəɹəl/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, developer /dɪˈvɛləpɚ/, complexity /kəmˈplɛk.sɪ.ti/, valuation /ˌvæ.ljuːˈeɪ.ʃən/

Звуки, трудные для русскоязычных:

/w/ — губы округлены, это не /v/: borrowing /ˈbɔrəwɪŋ/, foreword /ˈfɔːwɜːd/, liquidity /lɪkˈwɪdəti/, worrisome /ˈwʌɹisəm/
/h/ — лёгкий выдох, а не русское «х»: hire /ˈhaɪɹ/, homicide /ˈhɑ.məˌsaɪ̯d/
Звонкие согласные в конце слова — не оглушайте их: lend /ˈlɛnd/, lab /læːb/, depend /dɪˈpɛnd/, analyze /ˈæn.əˌlaɪz/, homicide /ˈhɑ.məˌsaɪ̯d/

Как заниматься с этим видео

Прослушайте всё видео один раз молча и выпишите незнакомые слова.
Начните со скорости 0,75×, повторяйте предложение за предложением и вернитесь к обычной скорости, когда станет легко.
Запишите себя и сравните с оригиналом, обращая внимание на такие слова, как chip, bubble, borrow.

Что такое техника Shadowing?

Shadowing — это научно обоснованная техника изучения языка, изначально разработанная для подготовки профессиональных переводчиков и популяризированная полиглотом доктором Александром Аргуэльесом. Метод прост, но эффективен: вы слушаете аудио на английском от носителей языка и немедленно повторяете вслух — как тень, следующая за говорящим с задержкой в 1–2 секунды. В отличие от пассивного прослушивания или грамматических упражнений, Shadowing заставляет мозг и мышцы рта одновременно обрабатывать и воспроизводить реальные речевые паттерны. Исследования показывают, что это значительно улучшает точность произношения, интонацию, ритм, связную речь, понимание на слух и беглость речи — что делает его одним из самых эффективных методов для подготовки к IELTS Speaking и реального общения на английском.

Техника шедоуинга: читать полное пошаговое руководство →

Практика Shadowing: Did the AI bubble just pop? - Изучайте разговорный английский по видео

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