シャドーイング練習: Did Anthropic just save its $1 trillion IPO? - 動画で英語スピーキングを学ぶ

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While Honeypot Wong was busy falling head over leather jacket for a succulent Chinese spy, These Chinese models are excellent.

Dario was putting the final touches on his prep work for the Anthropic IPO roadshow that started yesterday.

Unfortunately, it's coming at a pretty rough time for Dr. Doomsday.

The U .S midterms turned into a referendum on data centers where voters made it clear they hate them,

and Wall Street responded by panic selling every AI stock it could find.

That dragged Anthropik's expected valuation down from $2 trillion in September to a mere $1 trillion today.

So yesterday, Dollar Store Dario gave investors something else to look at by releasing Fable and Mythos 5 .2,

which you'll never believe are faster and cheaper than the versions that just came out two months ago.

During testing, it built an entire operating system starting from an empty folder, it finished a math project in 30 hours that Opus failed to finish,

and it even designed a working Tamagotchi.

In today's video, we'll look at everything these new models can do and answer the question I know you've all been wondering.

Can it create an interactive thoroughbred with an appropriate amount of realness?

It is November 10th, 2026, and you're watching the Code Report.

If you don't follow the Claude Cinematic Universe closely, Fable and Mythos are the same model,

but Mythos is the unrestricted one reserved for large companies with budgets for cybersecurity insurance,

and Fable is the one with guardrails that won't let you research how to cook up smallpox.

Now, we'll get to the fun stuff in a second, but let's get the boring stuff out of the way first.

The price is now $8 in and $40 out, which is down from $10 and $50 from $5 .1,

but Anthropic suggests that you should stick with Opus 5 .5 for most work

and only swap to Fable if you really need it.

For the operating system demo, an engineer pointed Fable at an empty folder and let 1 ,000 subagents have a Jensen -inspired freakfest for 8 days.

What comes out is a fairly legit OS that boots on a real laptop with its own kernel and drivers.

And you may remember back in August

when an unreleased Claude spent 11 days turning Fermat's last theorem into lean code that a computer could verify.

This time, a swarm of 1 ,000 Fable agents did it in 30 hours, and the proof was 7 times shorter,

while Opus 5 .5 crashed out at 26 % with the same setup.

And apparently it's decent at hardware too.

Working with a circuit board company called Diode, Fable took a one -paragraph prompt and used it to design a voice assistant hub,

a USB speakerphone, and a handheld virtual pet.

On the TMBBs, it beats GPT -6 Astra everywhere Anthropic listed an OpenAI score, it loses to Gemini 4

Carbon on business automation, and it more than doubles Astra on a robotics benchmark that Anthropic ran itself.

But enough glazing.

As you know, there's only one benchmark I trust.

A benchmark that's so good, it's become the industry standard by which humanity measures its new god -in -a -box toys, Thoroughbench.

So I open Claudecode and type those five famous words create a realistic interactive 3D horse with 3JS.

Make no mistakes.

Fable cooked for 43 minutes, and instead of downloading a horse model like a normal developer,

it sculpted the entire animal out of math using signed distance fields

that get meshed up and rigged to a skeleton every time the page loads.

It even screenshotted its own first attempt and roasted it.

The mane is bluish, the tail is stick -like, and the neck and hind legs are thin.

Then it went back and fixed every one of them.

The end result is the most realistic horse Thoroughbench has ever seen.

The skin texture and lighting look great, its head follows your mouse cursor,

and you can steer it with the arrow keys or orbit around it in 3D.

It's very cute and friendly, but gets extremely shy if you get too close.

The transitions between gates are buttery smooth, from a standstill all the way to a gallop,

although it's a little more awkward when coming to a full stop.

Under the hood, Opus 5 .5's horse had 95 ,000 vertices and 35 bones, while Fables has over 120 ,000 vertices and 38 bones,

and it plants each hoof with inverse kinematics, so unlike Kimmy, it's not just warping the mesh.

Fable 5 .2 didn't hallucinate a giant low -poly phallus like Gemini, but it equipped our horse with those rear leg shock absorbers,

which probably come in very handy when the horse decides to rear, as you can see here.

And the mane is a little lopsided, unless this was a custom request for his barber.

And even though I told it to make no mistakes, it admitted the horse is not photoreal, and the eyes are half -lidded.

So the final score for Fable, 5 .2 on Thoroughbench, is a 7 .77, making it the new state -of -the -art in horse.

And this really got me thinking, the models are starting to get so good

that we should really be naming the horses they create to keep track of them.

So we've decided to call this one TypeScript in honor of Secretariat, the greatest racehorse of all time,

who I can only assume would have loved to type if it had fingers.

And if you want to take him for a ride yourself, he now lives at typescript .dev, where you can walk, trot,

and gallop them right in your browser.

And if you ever need to run a video in your browser, you can do so with MUX, the sponsor of today's video.

Their highly customizable API is by far the easiest way to add video features to your application.

We've used it for years to host our courses, but it does a lot more than just infrastructure.

When you upload a video to MUX, you automatically get transcripts, storyboards, thumbnails, and clips.

From there, MUX Robots gives you AI workflows that can find key moments or pick the best thumbnail.

without you needing to host a model or maintain a pipeline.

You can automate all of this with directives where you define a workflow once and it runs on every new upload.

And robots keep up with new AI models automatically

so you can safely ignore the next video about whichever model just changed everything.

Perplexity, Patreon, and many other prestigious companies all trust MUX, and you can try robots on your own video in the dashboard.

The free plan includes 100 ,000 robots units and delivery minutes every month,

and you get an extra $50 credit at mux .com slash fireship or at the link below.

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 Anthropic just save its $1 trillion IPO?」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：Fable, horse, model, mux。この動画には、シャドーイング用の文が74文、単語が1127語あります。音声の長さは5:31です。話す速さは速く、1分あたり約204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74%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
robot 名詞	/ˈɹoʊ.bɑt/	ロボット, 人造人間
benchmark 名詞	/ˈbɛn(t)ʃmɑːk/	水準点
bone 名詞	/boʊn/	骨
realistic 形容詞	/ˌɹɪəˈlɪs.tɪk/	現実的
upload 動詞	/ˈʌpˌloʊd/	アップロードする
mesh 名詞	/mɛʃ/	網
folder 名詞	/ˈfoʊldɚ/	フォルダ
finger 名詞	/ˈfɪŋɡɚ/	指
ignore 動詞	/ɪɡˈnɔː/	無視する, 忽略する
gate 名詞	/ˈɡeɪ̯t/	門, 大門
thin 形容詞	/ˈθɪn/	薄い, 細い
infrastructure 名詞	/ˈɪnfɹəˌstɹʌkt͡ʃə/	インフラストラクチャ, インフラ
shock 名詞	/ʃɔk/	衝撃, ショック
transition 名詞	/tɹænˈzɪʃ.ən/	遷移, 推移
custom 名詞	/ˈkʌstəm/	習慣, 風俗

動画に出てくる句動詞

単語	発音	意味
come out 動詞	/ˌkʌm ˈaʊt/	出る
go back 動詞		戻る, 帰る

注意したい発音

話し手はwe'll, we've, didn'tなど、短縮形や弱形を10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。

「th」の音: math /mæθ/, thin /ˈθɪn/, smooth /smuːð/, leather /ˈlɛðɚ/, theorem /ˈθiərəm/
「sh」と「zh」の音: benchmark /ˈbɛn(t)ʃmɑːk/, mesh /mɛʃ/, shock /ʃɔk/, transition /tɹænˈzɪʃ.ən/, automation /ˌɔ.təˈmeɪ.ʃən/
長い単語（アクセントの位置に注意）: interactive /ˌɪn.tɚˈæk.tɪv/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, humanity /hjuˈmænɪti/, developer /dɪˈvɛləpɚ/, referendum /ˌɹɛfəˈɹɛndəm/

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: realistic /ˌɹɪəˈlɪs.tɪk/, virtual /ˈvɜɹt͡ʃuəl/, guardrail /ˈɡɑɹdˌɹeɪl/, perplexity /pəɹˈplɛksəti/
/v/ — /b/ にならないように、上の歯を下唇に当てる: interactive /ˌɪn.tɚˈæk.tɪv/, virtual /ˈvɜɹt͡ʃuəl/, developer /dɪˈvɛləpɚ/, voter /ˈvoʊtɚ/, investor /ɪnˈvɛs.tə(ɹ)/
/f/ — 「フ」ではなく、上の歯と下唇で出す: folder /ˈfoʊldɚ/, finger /ˈfɪŋɡɚ/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, define /dɪˈfaɪn/, safely /ˈseɪfli/

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。robot, benchmark, bone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 Anthropic just save its $1 trillion IPO? - 動画で英語スピーキングを学ぶ

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