쉐도잉 연습: Did Anthropic just save its $1 trillion IPO? - 영상으로 영어 말하기 배우기

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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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이 레슨의 어휘와 말하기 포인트

이 말하기 레슨은 영상 “Did Anthropic just save its $1 trillion IPO?”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: Fable, horse, model, mux. 이 영상에는 섀도잉할 문장 74개와 단어 1127개가 있습니다. 말하는 구간의 길이는 5:31입니다. 화자는 분당 약 204단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 영어에서 가장 많이 쓰이는 3,000단어에 속하는 단어가 74%뿐이라 어휘가 어려운 편입니다.

이 영상의 핵심 어휘

영상에 나오는 익혀 둘 만한 단어 15개를 발음, 뜻과 함께 정리했습니다.

단어	발음	뜻
robot 명사	/ˈɹoʊ.bɑt/	로봇, 인조인간
bone 명사	/boʊn/	뼈
realistic 형용사	/ˌɹɪəˈlɪs.tɪk/	현실적
interactive 형용사	/ˌɪn.tɚˈæk.tɪv/	인터랙티브
upload 동사	/ˈʌpˌloʊd/	업로드하다, 올리다
mesh 명사	/mɛʃ/	그물
folder 명사	/ˈfoʊldɚ/	서류철, 폴더
finger 명사	/ˈfɪŋɡɚ/	손가락
ignore 동사	/ɪɡˈnɔː/	무시하다
gate 명사	/ˈɡeɪ̯t/	문, 대문
thin 형용사	/ˈθɪn/	가늘다, 얇다
infrastructure 명사	/ˈɪnfɹəˌstɹʌkt͡ʃə/	기반시설, 기간시설
shock 명사	/ʃɔk/	충격, 쇼크
transition 명사	/tɹænˈzɪʃ.ən/	전이, 변화
custom 명사	/ˈkʌstəm/	습관, 풍속

영상에 나오는 구동사

단어	발음	뜻
come out 동사	/ˌkʌm ˈaʊt/	나오다
go back 동사		돌아가다

주의할 발음

화자는 we'll, we've, didn't 같은 축약형과 약화된 형태를 10번 사용합니다. 들리는 대로 짧게 발음하세요.

“th” 소리: math /mæθ/, thin /ˈθɪn/, smooth /smuːð/, leather /ˈlɛðɚ/, theorem /ˈθiərəm/
“sh”와 “zh” 소리: benchmark /ˈbɛn(t)ʃmɑːk/, mesh /mɛʃ/, shock /ʃɔk/, transition /tɹænˈzɪʃ.ən/, automation /ˌɔ.təˈmeɪ.ʃən/
긴 단어 — 강세 위치에 주의: interactive /ˌɪn.tɚˈæk.tɪv/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, humanity /hjuˈmænɪti/, developer /dɪˈvɛləpɚ/, referendum /ˌɹɛfəˈɹɛndəm/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: folder /ˈfoʊldɚ/, finger /ˈfɪŋɡɚ/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, define /dɪˈfaɪn/, safely /ˈseɪfli/
/v/ — ㅂ(/b/)과 구별하기: interactive /ˌɪn.tɚˈæk.tɪv/, virtual /ˈvɜɹt͡ʃuəl/, developer /dɪˈvɛləpɚ/, voter /ˈvoʊtɚ/, investor /ɪnˈvɛs.tə(ɹ)/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: browser /ˈbɹaʊ.zəɹ/, transition /tɹænˈzɪʃ.ən/, glaze /ɡleɪz/

이 영상으로 연습하는 방법

먼저 말하지 않고 영상을 끝까지 듣고 모르는 단어를 적어 둡니다.
0.75배속으로 한 문장씩 섀도잉을 시작하고, 익숙해지면 보통 속도로 돌아갑니다.
자신의 목소리를 녹음해 원본과 비교하고, robot, bone, realistic 같은 단어에 특히 주의합니다.

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.

섀도잉 방법: 단계별 전체 가이드 읽기 →

쉐도잉 연습: Did Anthropic just save its $1 trillion IPO? - 영상으로 영어 말하기 배우기

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