シャドーイング練習: Did the AI bubble just pop? - 動画で英語スピーキングを学ぶ

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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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このレッスンの語彙とスピーキングのポイント

このスピーキングレッスンは、動画「Did the AI bubble just pop?」を教材にしています。繰り返し出てくる語は次のとおりです：Gpu, Nvidia, companies, chips。この動画には、シャドーイング用の文が71文、単語が1128語あります。音声の長さは5:22です。話す速さは速く、1分あたり約210語です。音のつながりや弱く発音される音が多くなります。英語の頻出3,000語に含まれる単語は81%だけなので、語彙は難しめです。

この動画の重要語彙

動画に出てくる覚えておきたい単語15語を、発音と意味つきで紹介します。

単語	発音	意味
bubble 名詞	/ˈbʌbəl/	泡
borrow 動詞	/ˈbɑɹ.oʊ/	借りる
sponsor 名詞	/ˈspɒn.səː/	スポンサー
lend 動詞	/ˈlɛnd/	貸す
token 名詞	/ˈtoʊkən/	トークン
collateral 名詞	/kəˈlætəɹəl/	担保, 抵当
naturally 副詞	/ˈnæt͡ʃ.(ə.)ɹə.li/	勿論
bath 名詞	/bɑːθ/	湯船, 風呂
hire 動詞	/ˈhaɪɹ/	借りる
discover 動詞	/dɪˈskʌvə/	発見する, 見つける
exit 名詞	/ˈɛɡzət/	出口
contribute 動詞	/kənˈtɹɪb.jut/	貢献する
principle 名詞	/ˈpɹɪn.sɪ.pəl/	原理, 原則
invest 動詞	/ɪnˈvɛst/	投入する
rocket 名詞	/ˈɹɑk.ɪt/	ロケット, 噴進弾

動画に出てくる句動詞

単語	意味
find out 動詞	見出す, 調べる
go up 動詞	上がる, 登る

この動画の文法

話し手がよく使っている文型を、動画の実際の表現とともに紹介します。

文型	動画での表現
現在完了形 have/has + 過去分詞 — 過去の出来事が今も関係している	haven't bought · has promised · has done
受動態 be + 過去分詞 — 誰がするかより、何が起きるかに焦点を当てる	was discovered · was quoted · is built
関係詞節 who / which + 節 — 人や物について情報を加える	NVIDIA, which makes · company, which is · room, which is

注意したい発音

話し手はwe'll, I'm, you'reなど、短縮形や弱形を16回使っています。聞こえたとおりの短い形で発音しましょう。

「sh」と「zh」の音: subscription /səbˈskɹɪpʃən/, fraction /ˈfɹæk.ʃən/, valuation /ˌvæ.ljuːˈeɪ.ʃən/, depreciate /dəˈpriʃiˌeɪt/, insatiable /ɪnˈseɪʃ(j)əbəl/
長い単語（アクセントの位置に注意）: collateral /kəˈlætəɹəl/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, developer /dɪˈvɛləpɚ/, complexity /kəmˈplɛk.sɪ.ti/, valuation /ˌvæ.ljuːˈeɪ.ʃən/

日本語話者が苦手な音：

/r/ と /l/ の区別 — /l/ は舌先を歯茎につけ、/r/ はどこにもつけない: collateral /kəˈlætəɹəl/, naturally /ˈnæt͡ʃ.(ə.)ɹə.li/, principle /ˈpɹɪn.sɪ.pəl/, parallel /ˈpæ.ɹəˌlɛl/, circular /ˈsɜɹ.kjə.ləɹ/
/v/ — /b/ にならないように、上の歯を下唇に当てる: discover /dɪˈskʌvə/, invest /ɪnˈvɛst/, developer /dɪˈvɛləpɚ/, valuation /ˌvæ.ljuːˈeɪ.ʃən/, conveniently /kənˈvinjəntli/
/f/ — 「フ」ではなく、上の歯と下唇で出す: fraction /ˈfɹæk.ʃən/, forbid /fɚˈbɪd/, farmland /ˈfɑːɹmlænd/, foreword /ˈfɔːwɜːd/

この動画での練習方法

まず声を出さずに動画を最後まで聞き、知らない単語をメモします。
まず0.75倍速で一文ずつシャドーイングし、慣れてきたら通常の速度に戻します。
自分の声を録音して元の音声と比べます。bubble, borrow, sponsorなどの単語に特に注意しましょう。

シャドーイングとは？英語上達に効果的な理由

シャドーイング（Shadowing）は、もともとプロの通訳者養成プログラムで開発された言語学習法で、多言語習得者として知られるDr. Alexander Arguelles によって広く普及されました。方法はシンプルですが非常に効果的：ネイティブスピーカーの英語を聞きながら、1〜2秒の遅延で声に出してすぐに繰り返す——まるで「影（shadow）」のように話者を追いかけます。文法ドリルや受動的なリスニングと異なり、シャドーイングは脳と口の筋肉が同時にリアルタイムで英語を処理・再現することを強制します。研究により、発音精度、抑揚、リズム、連音、リスニング力、そして会話の流暢さが大幅に向上することが確認されています。IELTSスピーキング対策や自然な英語コミュニケーションを目指す方に特におすすめです。

シャドーイングのやり方: ステップ別の完全ガイドを読む →

シャドーイング練習: Did the AI bubble just pop? - 動画で英語スピーキングを学ぶ

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