Shadowing-Übung: China just dropped a new frontier model... and nobody can explain how - Englisch Sprechen Lernen mit Video

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Last week, an anonymous mystery model named Kibitz showed up randomly on Chatbot Arena, performing at the frontier level.
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Kibitz is the Yiddish word for that guy standing behind you at a chess game, giving you tips on how to blunder your queen,
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which to be honest is the perfect analogy for a coding agent.
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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.
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Everybody knew it was Kimmy, then right on cue last Friday, Moonshot dropped Kimmy K3 .1,
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officially giving us a new 3 trillion parameter open weight model that will be fully downloadable on November 4th, or so they say.
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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.
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I can go lower.
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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,
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building 3D horses with 3JS.
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It is October 26, 2026, and you're watching the Code Report.
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Earlier this year, Anthropic accused Moonshot AI, the company behind Kimi, alongside a bunch of other Chinese companies like DeepSeek and Minimax,
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of running large -scale distillation attacks against Claude by sending swarms of fake users to steal Claude's output and reasoning tokens,
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which could then be used to train these open models that they give to us for free.
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Now, I believe distillation is a fundamental human right
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because big AI companies have literally distilled the collective human brain by taking our internet weblogs, our githubs, our scientific papers,
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and they even destructively scanned our books without asking.
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Just google Project Panama.
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But OpenAI and Anthropic don't really see distillation as a human right like I do.
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To them, it's
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Grand Theft Autocomplete, and they've invested millions and millions of dollars into stopping it.
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And just a few weeks ago, Anthropic said it pretty much solved the distillation problem,
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with 90 to 99 % of distillation attacks from China now being blocked.
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And over at OpenAI, they've proved that their tech can even stop small -scale distilleries like PewDiePie.
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But if that's true, that means an open Chinese model with Kimi's performance should not be possible,
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because for years, Big AI has insinuated that the reason Chinese models get so good so fast is that they steal
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Big AI's output.
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But if we can trust this
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Trust Me Bro distillation data from Anthropic, that would mean that these
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Trust Me Bro benchmarks from Kimi should not be possible.
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Like Kimi K3 .1 is within one point of Opus 5 .5 on Terminal Bench 4 .0.
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That's pretty crazy, and no other open model is remotely close.
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And we might even be able to actually trust these numbers because artificial analysis ran it independently and got 67%,
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which is the highest score of any model they tested.
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But one thing to keep in mind is that the harness plays a big role here.
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Running different models with different harnesses will produce huge differences in benchmark results.
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In addition, Kimmy also wins on SWE Marathon, which is a test for multi -hour software requirements,
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or in other words, jobs that would take humans weeks of work to finish without AI assistance.
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That's all pretty impressive, but there is one big caveat when it comes to coding, and specifically cybersecurity.
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Moonshot deliberately ripped out a bunch of cybersecurity data from its training dataset,
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where the goal was to make the model even worse at hacking than pirate software.
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I'm a genius, dude.
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And it worked, because internally at Moonshot, an unfiltered checkpoint solved 90 .5 % of their illegal exploit tests,
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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
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China's DeepSeq model from government use, including all federal civilian agencies,
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and they would just love a good reason to ban all Chinese models across the board, to hand OpenAI and Anthropic a huge win,
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and make all the insiders even more unbelievably rich than they already are.
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And that's why Moonshot really has no choice but to lobotomize its hacking capabilities.
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But despite that, Kimmy still performed on top of all publicly available models on the new cyber index at Artificial Analysis,
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although that's mostly because Claude and GPT -6 declined every prompt on safety grounds and just took the L.
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But nowadays, the only AI capability that I really care about is how well it can generate a 3D horse with 3JS.
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And to analyze the skill objectively and scientifically, I use a formal benchmark.
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It's a state -of -the -art eval I've developed after thousands of hours of research, which I call Thoroughbench.
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The way it works is I literally just go into the chat window
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and type create a realistic interactive 3D horse with 3JS and then press enter.
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From there, I rank them from 0 to 10 based on a proprietary loss function I keep in my brain.
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Using this technique, Google Argon achieved a 0 .69, GPT -6 Astra achieved a 5 .21, and Opus achieved a 6 .39.
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But now it's time to try Kimi K 3 .1.
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I tried to be cheap and use the free tier,
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but got denied, so now I'm paying 250 yuan per month to show you guys this demo.
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It was worth it though, because Kimi produced what is easily the most beautiful horse in this sample.
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Its coloring is spot on, it looks realistic, and most importantly, its copulatory organ is a reasonable size.
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I was blown away by its beauty at first glance, but then I pushed play on the animation and found a problem.
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The animations are absolutely terrible.
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If we look closely, you can see it achieves the animation by simply warping the original mesh
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which is a very unsophisticated and half -assed way to animate a 3D object.
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If we compare that to Claude, the horse itself may not look as beautiful,
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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.
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Even Gemini Argon used bones, but for some reason it added an extra one.
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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.
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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.
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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.
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I've been using Mobbin for over five years,
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and its MCP server now lets your coding agent study its library of 600 ,000 real UI screens before it designs anything.
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So instead of asking for a login page and getting the same purple gradient vibe slop, you start by telling ClaudeCode,
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Cursor, or Codex to study how the best apps built that complete user flow.
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It'll use Mobbin to gather references and build a visual report of the patterns they all share.
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Then it'll recreate that flow and adapt it to your app.
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Every result points back to the original screen, so you can check the source, and after you connect Mobbin,
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everything your agent designs will feel like it has actual taste.
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But try Mobbin for free today and get a 20 % discount at the link below.
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This has been The Code Report, thanks for watching, and I will see you in the next one.

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Wortschatz und Sprechhinweise zu dieser Lektion

Diese Sprechübung basiert auf dem Video „China just dropped a new frontier model... and nobody can explain how“. Diese Wörter kommen am häufigsten vor: model, horse, distillation, Kimmy, Anthropic. Dieses Video enthält 82 Sätze und 1258 Wörter zum Nachsprechen. Der gesprochene Teil dauert 6:21. Der Sprecher spricht schnell, etwa 198 Wörter pro Minute – rechne mit verbundenen und verkürzten Lauten. Nur 76 % der Wörter gehören zu den 3.000 häufigsten im Englischen, der Wortschatz ist also anspruchsvoll.

Wichtiger Wortschatz in diesem Video

15 lernenswerte Wörter aus dem Video, mit Aussprache und Bedeutung:

WortAusspracheBedeutung
benchmark Substantiv/ˈbɛn(t)ʃmɑːk/Maßstab, Höhenfestpunkt
animation Substantiv/ˌæn.ɪˈmeɪ.ʃən/Belebung, Vitalisierung
bone Substantiv/boʊn/Knochen, Gebeine
solve Verb/sɒlv/lösen
impressive Adjektiv/ɪmˈpɹɛsɪv/beeindruckend, eindrucksvoll
mystery Substantiv/ˈmɪs.t(ə.)ɹi/Geheimnis, Rätsel
output Substantiv/ˈaʊtpʊt/Output
steal Verb/stiːl/stehlen, entwenden
artificial Adjektiv/ˌɑː.tɪˈfɪʃ.əl/künstlich
realistic Adjektiv/ˌɹɪəˈlɪs.tɪk/realistisch
capability Substantiv/ˌkeɪ.pəˈbɪl.ɪ.ti/Fähigkeit, Fertigkeit
independently Adverb/ˌɪndɪˈpɛndəntli/unabhängig, selbstständig
frontier Substantiv/ˈfɹʌntɪə/Grenzland, Grenzgebiet
mesh Substantiv/mɛʃ/Netz, Gitter
harness Verb/ˈhɑɹ.nəs/vorspannen, aufzäumen

Phrasal Verbs, die du hören wirst

WortBedeutung
check out Verbüberprüfen
find out Verbherausfinden, erfahren
rip out Verbabreißen, wegreißen
show up Verbauftauchen, erscheinen

Grammatik in diesem Video

Die Strukturen, die der Sprecher am häufigsten verwendet, mit den genauen Worten aus dem Video:

StrukturIm Video
Present Perfect have/has + Partizip Perfekt – eine vergangene Handlung, die jetzt noch wichtig istthey've invested · they've proved · has insinuated
Passiv be + Partizip Perfekt – wichtig ist, was geschieht, nicht wer es tutbeing blocked · was blown · are animated

Aussprache, auf die du achten solltest

Der Sprecher verwendet 12 Kurzformen und abgeschwächte Formen, zum Beispiel I'm, I've, it'll. Sprich sie in der kurzen Form, so wie du sie hörst.

  • Die Laute „sh“ und „zh“: benchmark /ˈbɛn(t)ʃmɑːk/, animation /ˌæn.ɪˈmeɪ.ʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, mesh /mɛʃ/, evaluation /ɪˌvæljuˈeɪʃn̩/
  • Lange Wörter – auf die Betonung achten: animation /ˌæn.ɪˈmeɪ.ʃən/, artificial /ˌɑː.tɪˈfɪʃ.əl/, capability /ˌkeɪ.pəˈbɪl.ɪ.ti/, independently /ˌɪndɪˈpɛndəntli/, fundamental /ˌfʌn.dəˈmɛn.təl/

Laute, die Deutschsprachigen schwerfallen:

  • /w/ — mit runden Lippen, nicht wie das deutsche „w“ (/v/): requirement /ɹɪˈkwaɪɹmənt/, warp /ˈwɔːp/, swarm /swɔɹm/
  • Stimmhafter Auslaut — /b/, /d/, /g/, /z/, /v/ am Wortende nicht verhärten: solve /sɒlv/, impressive /ɪmˈpɹɛsɪv/, alongside /əˌlɔŋˈsaɪd/, collective /kəˈlɛktɪv/, nowadays /ˈnaʊ.ə.deɪz/
  • /æ/ — offener als „ä“: animation /ˌæn.ɪˈmeɪ.ʃən/, rank /ˈɹæŋk/, gather /ˈɡæðɚ/, evaluation /ɪˌvæljuˈeɪʃn̩/, scan /skæn/

So übst du mit diesem Video

  1. Höre dir das ganze Video einmal an, ohne zu sprechen, und notiere die Wörter, die du nicht kennst.
  2. Beginne mit 0,75-facher Geschwindigkeit, sprich Satz für Satz nach und wechsle zur normalen Geschwindigkeit, sobald es leichtfällt.
  3. Nimm dich auf und vergleiche mit dem Original; achte dabei auf Wörter wie benchmark, animation, bone.

Was ist die Shadowing-Technik?

Shadowing ist eine wissenschaftlich fundierte Sprachlerntechnik, die ursprünglich für die professionelle Dolmetscherausbildung entwickelt und durch den Polyglotten Dr. Alexander Arguelles populär gemacht wurde. Die Methode ist einfach aber wirkungsvoll: Du hörst englisches Audio von Muttersprachlern und wiederholst es sofort laut — wie ein Schatten, der dem Sprecher mit nur 1–2 Sekunden Verzögerung folgt. Anders als passives Hören oder Grammatikübungen zwingt Shadowing dein Gehirn und deine Mundmuskulatur, gleichzeitig echte Sprachmuster zu verarbeiten und zu reproduzieren. Studien zeigen, dass es Aussprachegenauigkeit, Intonation, Rhythmus, verbundene Sprache, Hörverständnis und Sprechflüssigkeit signifikant verbessert — was es zu einer der effektivsten Methoden für die IELTS Speaking-Vorbereitung und reale englische Kommunikation macht.

Shadowing-Technik: die vollständige Schritt-für-Schritt-Anleitung lesen →