Shadowing-Übung: Did Anthropic just save its $1 trillion IPO? - Englisch Sprechen Lernen mit Video
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While Honeypot Wong was busy falling head over leather jacket for a succulent Chinese spy, These Chinese models are excellent.
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Dario was putting the final touches on his prep work for the Anthropic IPO roadshow that started yesterday.
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Unfortunately, it's coming at a pretty rough time for Dr. Doomsday.
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The U .S midterms turned into a referendum on data centers where voters made it clear they hate them,
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and Wall Street responded by panic selling every AI stock it could find.
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That dragged Anthropik's expected valuation down from $2 trillion in September to a mere $1 trillion today.
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So yesterday, Dollar Store Dario gave investors something else to look at by releasing Fable and Mythos 5 .2,
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which you'll never believe are faster and cheaper than the versions that just came out two months ago.
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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,
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and it even designed a working Tamagotchi.
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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.
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Can it create an interactive thoroughbred with an appropriate amount of realness?
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It is November 10th, 2026, and you're watching the Code Report.
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If you don't follow the Claude Cinematic Universe closely, Fable and Mythos are the same model,
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but Mythos is the unrestricted one reserved for large companies with budgets for cybersecurity insurance,
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and Fable is the one with guardrails that won't let you research how to cook up smallpox.
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Now, we'll get to the fun stuff in a second, but let's get the boring stuff out of the way first.
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The price is now $8 in and $40 out, which is down from $10 and $50 from $5 .1,
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but Anthropic suggests that you should stick with Opus 5 .5 for most work
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and only swap to Fable if you really need it.
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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.
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What comes out is a fairly legit OS that boots on a real laptop with its own kernel and drivers.
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And you may remember back in August
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when an unreleased Claude spent 11 days turning Fermat's last theorem into lean code that a computer could verify.
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This time, a swarm of 1 ,000 Fable agents did it in 30 hours, and the proof was 7 times shorter,
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while Opus 5 .5 crashed out at 26 % with the same setup.
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And apparently it's decent at hardware too.
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Working with a circuit board company called Diode, Fable took a one -paragraph prompt and used it to design a voice assistant hub,
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a USB speakerphone, and a handheld virtual pet.
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On the TMBBs, it beats GPT -6 Astra everywhere Anthropic listed an OpenAI score, it loses to Gemini 4
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Carbon on business automation, and it more than doubles Astra on a robotics benchmark that Anthropic ran itself.
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But enough glazing.
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As you know, there's only one benchmark I trust.
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A benchmark that's so good, it's become the industry standard by which humanity measures its new god -in -a -box toys, Thoroughbench.
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So I open Claudecode and type those five famous words create a realistic interactive 3D horse with 3JS.
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Make no mistakes.
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Fable cooked for 43 minutes, and instead of downloading a horse model like a normal developer,
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it sculpted the entire animal out of math using signed distance fields
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that get meshed up and rigged to a skeleton every time the page loads.
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It even screenshotted its own first attempt and roasted it.
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The mane is bluish, the tail is stick -like, and the neck and hind legs are thin.
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Then it went back and fixed every one of them.
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The end result is the most realistic horse Thoroughbench has ever seen.
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The skin texture and lighting look great, its head follows your mouse cursor,
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and you can steer it with the arrow keys or orbit around it in 3D.
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It's very cute and friendly, but gets extremely shy if you get too close.
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The transitions between gates are buttery smooth, from a standstill all the way to a gallop,
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although it's a little more awkward when coming to a full stop.
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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,
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and it plants each hoof with inverse kinematics, so unlike Kimmy, it's not just warping the mesh.
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Fable 5 .2 didn't hallucinate a giant low -poly phallus like Gemini, but it equipped our horse with those rear leg shock absorbers,
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which probably come in very handy when the horse decides to rear, as you can see here.
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And the mane is a little lopsided, unless this was a custom request for his barber.
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And even though I told it to make no mistakes, it admitted the horse is not photoreal, and the eyes are half -lidded.
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So the final score for Fable, 5 .2 on Thoroughbench, is a 7 .77, making it the new state -of -the -art in horse.
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And this really got me thinking, the models are starting to get so good
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that we should really be naming the horses they create to keep track of them.
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So we've decided to call this one TypeScript in honor of Secretariat, the greatest racehorse of all time,
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who I can only assume would have loved to type if it had fingers.
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And if you want to take him for a ride yourself, he now lives at typescript .dev, where you can walk, trot,
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and gallop them right in your browser.
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And if you ever need to run a video in your browser, you can do so with MUX, the sponsor of today's video.
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Their highly customizable API is by far the easiest way to add video features to your application.
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We've used it for years to host our courses, but it does a lot more than just infrastructure.
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When you upload a video to MUX, you automatically get transcripts, storyboards, thumbnails, and clips.
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From there, MUX Robots gives you AI workflows that can find key moments or pick the best thumbnail.
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without you needing to host a model or maintain a pipeline.
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You can automate all of this with directives where you define a workflow once and it runs on every new upload.
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And robots keep up with new AI models automatically
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so you can safely ignore the next video about whichever model just changed everything.
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Perplexity, Patreon, and many other prestigious companies all trust MUX, and you can try robots on your own video in the dashboard.
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The free plan includes 100 ,000 robots units and delivery minutes every month,
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and you get an extra $50 credit at mux .com slash fireship or 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 „Did Anthropic just save its $1 trillion IPO?“. Diese Wörter kommen am häufigsten vor: Fable, horse, model, mux. Dieses Video enthält 74 Sätze und 1127 Wörter zum Nachsprechen. Der gesprochene Teil dauert 5:31. Der Sprecher spricht schnell, etwa 204 Wörter pro Minute – rechne mit verbundenen und verkürzten Lauten. Nur 74 % 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:
| Wort | Aussprache | Bedeutung |
|---|---|---|
| robot Substantiv | /ˈɹoʊ.bɑt/ | Roboter |
| benchmark Substantiv | /ˈbɛn(t)ʃmɑːk/ | Maßstab, Höhenfestpunkt |
| bone Substantiv | /boʊn/ | Knochen, Gebeine |
| math Substantiv | /mæθ/ | Mathe |
| realistic Adjektiv | /ˌɹɪəˈlɪs.tɪk/ | realistisch |
| interactive Adjektiv | /ˌɪn.tɚˈæk.tɪv/ | interaktiv, wechselwirkend |
| upload Verb | /ˈʌpˌloʊd/ | hochladen, uploaden |
| mesh Substantiv | /mɛʃ/ | Netz, Gitter |
| folder Substantiv | /ˈfoʊldɚ/ | Ordner, Mappe |
| finger Substantiv | /ˈfɪŋɡɚ/ | Finger |
| ignore Verb | /ɪɡˈnɔː/ | ignorieren, missachten |
| circuit Substantiv | /ˈsɝ.kɪt/ | Umlauf |
| gate Substantiv | /ˈɡeɪ̯t/ | Tor |
| thin Adjektiv | /ˈθɪn/ | dünn, tünn |
| infrastructure Substantiv | /ˈɪnfɹəˌstɹʌkt͡ʃə/ | Infrastruktur |
Phrasal Verbs, die du hören wirst
| Wort | Aussprache | Bedeutung |
|---|---|---|
| come out Verb | /ˌkʌm ˈaʊt/ | herauskommen |
| go back Verb | zurückgehen, zurückfahren | |
| keep up with Verb | mithalten, mit etwas Schritt halten |
Aussprache, auf die du achten solltest
Der Sprecher verwendet 10 Kurzformen und abgeschwächte Formen, zum Beispiel we'll, we've, didn't. Sprich sie in der kurzen Form, so wie du sie hörst.
- Die „th“-Laute: math /mæθ/, thin /ˈθɪn/, smooth /smuːð/, leather /ˈlɛðɚ/, theorem /ˈθiərəm/
- Die Laute „sh“ und „zh“: benchmark /ˈbɛn(t)ʃmɑːk/, mesh /mɛʃ/, shock /ʃɔk/, transition /tɹænˈzɪʃ.ən/, automation /ˌɔ.təˈmeɪ.ʃən/
- Lange Wörter – auf die Betonung achten: interactive /ˌɪn.tɚˈæk.tɪv/, infrastructure /ˈɪnfɹəˌstɹʌkt͡ʃə/, humanity /hjuˈmænɪti/, developer /dɪˈvɛləpɚ/, referendum /ˌɹɛfəˈɹɛndəm/
Laute, die Deutschsprachigen schwerfallen:
- /w/ — mit runden Lippen, nicht wie das deutsche „w“ (/v/): hardware /ˈhɑɹdˌwɛɹ/, awkward /ˈɔk.wɚd/, swap /ˈswɑp/, whichever /wɪt͡ʃˈɛvɚ/, warp /ˈwɔːp/
- Stimmhafter Auslaut — /b/, /d/, /g/, /z/, /v/ am Wortende nicht verhärten: interactive /ˌɪn.tɚˈæk.tɪv/, upload /ˈʌpˌloʊd/, awkward /ˈɔk.wɚd/, drag /dɹæɡ/, hood /hʊd/
- /æ/ — offener als „ä“: math /mæθ/, interactive /ˌɪn.tɚˈæk.tɪv/, transition /tɹænˈzɪʃ.ən/, humanity /hjuˈmænɪti/, jacket /ˈd͡ʒæk.ɪt/
So übst du mit diesem Video
- Höre dir das ganze Video einmal an, ohne zu sprechen, und notiere die Wörter, die du nicht kennst.
- Beginne mit 0,75-facher Geschwindigkeit, sprich Satz für Satz nach und wechsle zur normalen Geschwindigkeit, sobald es leichtfällt.
- Nimm dich auf und vergleiche mit dem Original; achte dabei auf Wörter wie robot, benchmark, 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.