쉐도잉 연습: China just dropped a new frontier model... and nobody can explain how - 영상으로 영어 말하기 배우기

연습 모드 선택

각 모드는 전체 화면 연습실로 열립니다.

82 문장

문장이 너무 짧거나 길면 Edit를 눌러 조정하세요.

Last week, an anonymous mystery model named Kibitz showed up randomly on Chatbot Arena, performing at the frontier level.

Kibitz is the Yiddish word for that guy standing behind you at a chess game, giving you tips on how to blunder your queen,

which to be honest is the perfect analogy for a coding agent.

But it was pretty obvious who was behind this mystery model from the beginning, because the first two letters of this word are a dead giveaway.

Everybody knew it was Kimmy, then right on cue last Friday, Moonshot dropped Kimmy K3 .1,

officially giving us a new 3 trillion parameter open weight model that will be fully downloadable on November 4th, or so they say.

And just when you thought the AI bubble was popping and the Trust Me Bro benchmarks could not possibly get any better, Kimmy made them better.

I can go lower.

In today's video, we'll find out why Kimmy K3 .1's performance should be impossible, and put it to the test on the only benchmark that matters,

building 3D horses with 3JS.

It is October 26, 2026, and you're watching the Code Report.

Earlier this year, Anthropic accused Moonshot AI, the company behind Kimi, alongside a bunch of other Chinese companies like DeepSeek and Minimax,

of running large -scale distillation attacks against Claude by sending swarms of fake users to steal Claude's output and reasoning tokens,

which could then be used to train these open models that they give to us for free.

Now, I believe distillation is a fundamental human right

because big AI companies have literally distilled the collective human brain by taking our internet weblogs, our githubs, our scientific papers,

and they even destructively scanned our books without asking.

Just google Project Panama.

But OpenAI and Anthropic don't really see distillation as a human right like I do.

To them, it's

Grand Theft Autocomplete, and they've invested millions and millions of dollars into stopping it.

And just a few weeks ago, Anthropic said it pretty much solved the distillation problem,

with 90 to 99 % of distillation attacks from China now being blocked.

And over at OpenAI, they've proved that their tech can even stop small -scale distilleries like PewDiePie.

But if that's true, that means an open Chinese model with Kimi's performance should not be possible,

because for years, Big AI has insinuated that the reason Chinese models get so good so fast is that they steal

Big AI's output.

But if we can trust this

Trust Me Bro distillation data from Anthropic, that would mean that these

Trust Me Bro benchmarks from Kimi should not be possible.

Like Kimi K3 .1 is within one point of Opus 5 .5 on Terminal Bench 4 .0.

That's pretty crazy, and no other open model is remotely close.

And we might even be able to actually trust these numbers because artificial analysis ran it independently and got 67%,

which is the highest score of any model they tested.

But one thing to keep in mind is that the harness plays a big role here.

Running different models with different harnesses will produce huge differences in benchmark results.

In addition, Kimmy also wins on SWE Marathon, which is a test for multi -hour software requirements,

or in other words, jobs that would take humans weeks of work to finish without AI assistance.

That's all pretty impressive, but there is one big caveat when it comes to coding, and specifically cybersecurity.

Moonshot deliberately ripped out a bunch of cybersecurity data from its training dataset,

where the goal was to make the model even worse at hacking than pirate software.

I'm a genius, dude.

And it worked, because internally at Moonshot, an unfiltered checkpoint solved 90 .5 % of their illegal exploit tests,

but the final release model only solves 81%, and that's a smart business move on their part, because just a few days ago, the US banned

China's DeepSeq model from government use, including all federal civilian agencies,

and they would just love a good reason to ban all Chinese models across the board, to hand OpenAI and Anthropic a huge win,

and make all the insiders even more unbelievably rich than they already are.

And that's why Moonshot really has no choice but to lobotomize its hacking capabilities.

But despite that, Kimmy still performed on top of all publicly available models on the new cyber index at Artificial Analysis,

although that's mostly because Claude and GPT -6 declined every prompt on safety grounds and just took the L.

But nowadays, the only AI capability that I really care about is how well it can generate a 3D horse with 3JS.

And to analyze the skill objectively and scientifically, I use a formal benchmark.

It's a state -of -the -art eval I've developed after thousands of hours of research, which I call Thoroughbench.

The way it works is I literally just go into the chat window

and type create a realistic interactive 3D horse with 3JS and then press enter.

From there, I rank them from 0 to 10 based on a proprietary loss function I keep in my brain.

Using this technique, Google Argon achieved a 0 .69, GPT -6 Astra achieved a 5 .21, and Opus achieved a 6 .39.

But now it's time to try Kimi K 3 .1.

I tried to be cheap and use the free tier,

but got denied, so now I'm paying 250 yuan per month to show you guys this demo.

It was worth it though, because Kimi produced what is easily the most beautiful horse in this sample.

Its coloring is spot on, it looks realistic, and most importantly, its copulatory organ is a reasonable size.

I was blown away by its beauty at first glance, but then I pushed play on the animation and found a problem.

The animations are absolutely terrible.

If we look closely, you can see it achieves the animation by simply warping the original mesh

which is a very unsophisticated and half -assed way to animate a 3D object.

If we compare that to Claude, the horse itself may not look as beautiful,

but it actually built a mesh with 95 ,000 vertices with each shape tied to one of 35 bones, and all those bones are animated independently.

Even Gemini Argon used bones, but for some reason it added an extra one.

Skeletal animation is more difficult, but it's why the horse doesn't look like it's being torn apart by a black hole when it walks.

So the final score for KimiK 3 .1 on Thoroughbench is a 4 .20, which is pretty dang impressive, but still behind the other Frontier models.

But if you really want to build an amazing 3D horse or user interface, you need to check out Mobbin, the sponsor of today's video.

I've been using Mobbin for over five years,

and its MCP server now lets your coding agent study its library of 600 ,000 real UI screens before it designs anything.

So instead of asking for a login page and getting the same purple gradient vibe slop, you start by telling ClaudeCode,

Cursor, or Codex to study how the best apps built that complete user flow.

It'll use Mobbin to gather references and build a visual report of the patterns they all share.

Then it'll recreate that flow and adapt it to your app.

Every result points back to the original screen, so you can check the source, and after you connect Mobbin,

everything your agent designs will feel like it has actual taste.

But try Mobbin for free today and get a 20 % discount at the link below.

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

앱 다운로드

유창하게 말하는 데 필요한 모든 것

AI 발음 평가문장마다 점수 확인

IPA 발음 연습모든 소리 마스터

단어 학습나만의 단어장 만들기

단어 게임놀면서 외우기

QR 스캔

Download on theApp Store Get it onGoogle Play

같은 채널

FOR YOU

이 레슨의 어휘와 말하기 포인트

이 말하기 레슨은 영상 “China just dropped a new frontier model... and nobody can explain how”을(를) 바탕으로 합니다. 가장 자주 반복되는 단어는 다음과 같습니다: model, horse, distillation, Kimmy, Anthropic. 이 영상에는 섀도잉할 문장 82개와 단어 1258개가 있습니다. 말하는 구간의 길이는 6:21입니다. 화자는 분당 약 198단어로 빠르게 말하므로 연음과 약하게 발음되는 소리가 많습니다. 영어에서 가장 많이 쓰이는 3,000단어에 속하는 단어가 76%뿐이라 어휘가 어려운 편입니다.

이 영상의 핵심 어휘

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

단어	발음	뜻
animation 명사	/ˌæn.ɪˈmeɪ.ʃən/	애니메이션, 아니메
bone 명사	/boʊn/	뼈
solve 동사	/sɒlv/	해결하다
impressive 형용사	/ɪmˈpɹɛsɪv/	인상적
mystery 명사	/ˈmɪs.t(ə.)ɹi/	신비, 미스터리
output 명사	/ˈaʊtpʊt/	출력
steal 동사	/stiːl/	훔치다
artificial 형용사	/ˌɑː.tɪˈfɪʃ.əl/	인공, 인조
realistic 형용사	/ˌɹɪəˈlɪs.tɪk/	현실적
independently 부사	/ˌɪndɪˈpɛndəntli/	독립하여, 자주적으로
frontier 명사	/ˈfɹʌntɪə/	경계, 국경
mesh 명사	/mɛʃ/	그물
technique 명사	/tɛkˈniːk/	기술
server 명사	/ˈsɝvɚ/	서버, 봉사기
compare 동사	/kəmˈpɛɚ/	비교하다, 비유하다

이 영상의 문법

화자가 가장 많이 쓰는 문형을 영상 속 실제 표현과 함께 정리했습니다.

문형	영상 속 표현
현재완료 have/has + 과거분사 — 과거의 일이 지금도 관련이 있을 때	they've invested · they've proved · has insinuated
수동태 be + 과거분사 — 누가 하는지보다 무슨 일이 일어나는지에 초점	being blocked · was blown · are animated

주의할 발음

화자는 I'm, I've, it'll 같은 축약형과 약화된 형태를 12번 사용합니다. 들리는 대로 짧게 발음하세요.

“sh”와 “zh” 소리: benchmark /ˈbɛn(t)ʃmɑːk/, animation /ˌæn.ɪˈmeɪ.ʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, mesh /mɛʃ/, evaluation /ɪˌvæljuˈeɪʃn̩/
긴 단어 — 강세 위치에 주의: animation /ˌæn.ɪˈmeɪ.ʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, independently /ˌɪndɪˈpɛndəntli/, fundamental /ˌfʌn.dəˈmɛn.təl/

한국어 화자가 어려워하는 소리:

/f/ — ㅍ(/p/)으로 바꾸지 말고 윗니를 아랫입술에 대기: artificial /ˌɑː.tɪˈfɪʃ.əl/, frontier /ˈfɹʌntɪə/, formal /ˈfɔɹməl/, fundamental /ˌfʌn.dəˈmɛn.təl/, interface /ˈɪn(t)ɚˌfeɪs/
/v/ — ㅂ(/b/)과 구별하기: solve /sɒlv/, impressive /ɪmˈpɹɛsɪv/, server /ˈsɝvɚ/, invest /ɪnˈvɛst/, collective /kəˈlɛktɪv/
/z/ — ㅈ이 아니라 성대를 울리는 /s/: nowadays /ˈnaʊ.ə.deɪz/, analyze /ˈæn.əˌlaɪz/, accuse /əˈkjuz/

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, animation, bone, solve 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: China just dropped a new frontier model... and nobody can explain how - 영상으로 영어 말하기 배우기

연습 모드 선택

앱 다운로드

PostgreSQL in 100 Seconds

React Native in 100 Seconds

Did Google just dethrone OpenAI and Anthropic?

Every app on Earth is now open source... whether it likes it or not

Brainf**k in 100 Seconds

OpenAI’s lead engineer was secretly a spy...

The most interesting "hack" in history...

Mind-bending new programming language for GPUs just dropped...

The last real programmers are dying out...

Did the AI bubble just pop?

Intel chips can’t possibly be this bad… 100% crash rate?

OpenAI’s new browser feels familiar…

Docker in 100 Seconds

Firefox and Tor hit with 9.8 critical level exploit

5 open source tools that replaced my $320/mo AI stack...

C++ in 100 Seconds

Linux in 100 Seconds

Meta is pivoting again... everything you missed from Connect 2026

VS Code in 100 Seconds

7 Programming myths that waste your time

A $6.3 billion open-weight model just got embarrassed by the French...

Did Anthropic Kill Git?

The REAL reason China built so much

9 Insane Claude Mods I Already Can't live Without

AI Governance Explained: Ethical, Transparent & Accountable AI for the Future

Naomi Klein: The AI Bubble Is Going To Burst. This Is How We Prepare.

Jack Dorsey’s New Dessa AI Voice Sounds Scary Human

We Let $200 GPT-Pro Think for 7 Days on Unsolved Math

Why AI Tokens are so Expensive - Computerphile

Expensive RTX 5090 for LLMs? NO. Use This Instead. (Tesla V100 SXM2 + Z8 G4, #RACERRRZ)

Mark Zuckerberg: “Alex, are you sure this is going to work?”