Shadowing Practice: Did OpenAI actually build AGI? GPT-6 Astra first look - Learn English Speaking with Video
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The famous American philosopher Smashmouth once said, The years start coming and they don't stop coming,
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and I've never understood those words more deeply than I did this week after what felt like years in AI Bizarro land.
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First, on Tuesday, Anthropic released Fable and Mythos 5.1, which they're calling the world's most advanced models for coding and knowledge work.
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Then on Wednesday, Meta released Muse Spark 1.3, which Zuck says is a frontier model that's almost too cheap to meter.
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Then finally, on Thursday, OpenAI announced GPT-6 Astra, which President Greg Brockman says is AGI
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if you're one of the handful of lucky influencers or enterprise customers who got access to it.
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Unfortunately, I think I've made too many gay scam Altman jokes over the years to make the cut, but in this video, I'll do my best to break down the new models, see how the anointed are liking Astra,
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and look into the totally coincidental timing where the internet broke right as it was released.
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It is September 4th, 2026, and you're watching The Code Report.
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Normally, the first week of September is a quiet one, because all the rich VCs and poor project managers are busy appropriating schizophrenic culture in the Nevada desert.
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Because you did so well, you get to hear a magic tune on my ocarina.
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But apparently, AGI waits for no one, despite how dead your ego might be.
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On Tuesday, Anthropic got things rolling with the release of Fable and Mythos 5.1.
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Although they're the same model, Mythos is the one you can't use while Fable is the one you can.
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It just changes the subject when you ask about Anthrax.
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The TMBBs were fine, but the more interesting bits were in the case studies.
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A Backstreet Boys-inspired hedge fund named Millennium had a piece of code
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that for the last five years would crash about once in a million runs, and regardless of how much Adderall they took, they couldn't figure it out.
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So recently, they gave it to Fable 5.1, which took the memory snapshot the program leaves behind when it crashes,
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then found that the crash address pointed into a compiled vendor library they didn't have the source code for.
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They disassemble that library back into raw assembly and traced the crash to a bug in the vendor's code.
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And speaking of drugs, Mythos 5.1 is also pretty good at designing new ones.
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The first step in making most modern medicines is designing a protein that sticks to a specific target in your body.
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Typically AI gets this right about 10% of the time, but Mythos 5.1 was able to increase that number to about 50%.
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And for those of you who have the planet-flavored version of autism, it was able to train a neural network on 30-year-old NASA
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radar data to build a new elevation map for a part of Venus.
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Then on Wednesday, Meta dropped Muse Spark 1.3, which was the fourth release in five months from Meta Super Intelligence Labs.
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And what do you know, these TMBBs were also pretty good.
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But the more impressive part is in the price.
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The standard endpoint is $1.25 in and $4.25 out.
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But if you're the give up essential liberty to purchase a little temporary safety type, there's a contributor tier at 10 cents in
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and 20 cents out as long as you agree to let Meta train on everything you send it.
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Alexander Wang says a double-digit percentage of developers are choosing that option, which makes sense
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because a double-digit percentage of developers would also choose to eat the mystery beef from Argentina
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if you told them it was cheaper and open source.
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Which brings us to yesterday morning when right before the Astra released, ChatGPT, Claude, Grok, and Cursor all happened to go down at the same time.
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The Occam's Razor opinion is that it was most likely an Azure issue since they reported an outage around the same time,
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but the more entertaining theory is that Astra's first act as a public model was to literally kill its competition.
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But once the lights came back on, the launch itself was somehow even messier.
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OpenAI put up their launch page, and shortly after, Reuters, CNBC, and The Verge published their embargoed stories.
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Then for reasons no one really knows, OpenAI took down their announcement
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and the tech influencers got started on the modern status game of flexing how long they've secretly had access to Astra 4, and to be honest, I would have done the same thing
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if it wasn't for slippery scam Altman and his grubby little gang of misfits.
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Anyway, about 90 minutes later, when the post was back up, it turned out the model wasn't actually available to anyone publicly yet, and the rollout to Plus and Pro users would happen in the coming days.
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By the evening, Sam had posted an apology for the messy rollout, and when a Pro subscriber asked Sam if he should stay up and wait for it,
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Sam told him something we've all heard after making a desperate late-night plea, go to bed.
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Sam also told CNBC the model went through a formal review with the Trump administration before release, so even the government got to try AGI before we did.
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As far as Astra itself, it was pre-trained on more than 100,000 GPUs at the Stargate site in Texas,
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and it's the first model from OpenAI where previous models did a significant chunk of the supervising during training.
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The main pitch today seems to be computer use, where Astra can fill out forms, crunch spreadsheets, and operate engineering tools like KiCat and Blender.
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On OSworld, which is a benchmark that drops a model into a real desktop
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and makes it do office work with a mouse and keyboard, just like a human meatbag does until it begs for Xanax, it scored 73% while taking about 40 minutes for each task,
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compared to Sol's 65% at 75 minutes.
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And of course, the agents on the Trust Me Bro benchmarks are the best to ever do it.
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It got 100% on ExploitBench and 65% on TerminalBenchScience, which beats the numbers Anthropic was bragging about on Tuesday.
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It also got 99% on ARC-AGI3, which is the benchmark that's supposed to prove your model actually generalizes instead of memorizing, which is kind of the definition of AGI,
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depending on who you ask.
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And according to OpenAI, Astra is the first model to hit the critical cyber threshold in its preparedness framework, which is just a fancy way of saying it can find
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and exploit zero days on its own without a human telling it what to do.
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Pricing is the same as Fable 5.1 at $10 per million input tokens and $50 out.
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But what do the anointed humans think about it?
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The early access reviews are positive in the way early access reviews typically are from people who don't publicly slander Sham Altman,
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but the demos, specifically the ones that require spatial awareness, are impressive.
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Sharif Shamim had it recreate the Palace of Fine Arts in San Francisco, and it did so almost perfectly in Blender.
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And Thomas Ricard from OpenAI posted a walkthrough of the demo house from the launch post, which Astra first modeled in Blender and then turned into a fully walkable Unreal 5 scene.
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But the most interesting was Matt Schumers, who asked Astra to build a world in Unreal Engine and fill it with a dozen Astra-powered agents.
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A day later, he heard voices coming from his living room
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and walked out to a bunch of agents talking about what
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I can only assume was a plan to create a dating app for horses.
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With all that said, when artificial analysis ran Astra through their independent intelligence index,
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it scored a 61, which is exactly the same as GPT 5.6 SOL, and 5 points behind Fable 5.1.
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Something doesn't add up here, but one thing that does add up is CodeRabbit, the sponsor of today's video.
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They got tired of seeing me make new videos about new exploits hitting the timeline every week,
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so they just launched CodeRabbit Security to provide continuous code security that's powered by actual reasoning instead of brittle regex rules.
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Their security agents are designed to think like an attacker in order to hunt for real vulnerabilities across your entire codebase.
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Then it prioritizes actual risks based on reachability, exploitability, and blast radius.
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And it explains the problem to you in plain English and suggests a fix you can approve and merge from the diff.
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CodeRabbit Security reviews every PR before merge, and you can also schedule deep scans across your full codebase to protect your backdoor 24-7.
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Get 10 free code scans to try it out for free today 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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Vocabulario y notas de pronunciación para esta lección
Esta lección de conversación de nivel C1 se basa en el vídeo “Did OpenAI actually build AGI? GPT-6 Astra first look”. Las palabras que más se repiten: model, Astra, code, Fable, Openai. Este vídeo tiene 80 frases y 1466 palabras para practicar shadowing. La parte hablada dura 7:25. El hablante habla rápido, unas 198 palabras por minuto, así que espera sonidos enlazados y reducidos. Solo el 78 % de las palabras está entre las 3.000 más comunes del inglés, por lo que el vocabulario es exigente.
Vocabulario clave de este vídeo
Las 15 palabras más avanzadas del vídeo, con su pronunciación y significado:
| Palabra | Pronunciación | Significado |
|---|---|---|
| benchmark sustantivo | /ˈbɛn(t)ʃmɑːk/ | cota de referencia, estándar de comparación |
| anoint verbo | /əˈnɔɪnt/ | ungir |
| influencer sustantivo | /ˈɪnflu.ənsə(ɹ)/ | influidor, influidora |
| merge verbo | /mɝd͡ʒ/ | mergear |
| digit sustantivo | /ˈdɪd͡ʒɪt/ | dígito, cifra |
| exploit sustantivo | /ˈɛksplɔɪt/ | hazaña, proeza |
| messy adjetivo | /ˈmɛsi/ | desordenado, desprolijo |
| scam sustantivo | /ˈskæm/ | estafa, timo |
| scan verbo | /skæn/ | escrutar |
| brittle adjetivo | /ˈbɹɪtəl/ | frágil, quebradizo |
| compile verbo | /kəmˈpaɪl/ | copilar, recopilar |
| disassemble verbo | /dɪs.əˈsɛm.bəl/ | desmontar, desensamblar |
| embargo sustantivo | /ɪmˈbɑɹɡoʊ/ | embargo |
| endpoint sustantivo | punto extremo, extremo | |
| generalize verbo | /ˈd͡ʒɛn.(ə.)ɹə.laɪz/ | generalizar |
Phrasal verbs que vas a escuchar
| Palabra | Pronunciación | Significado |
|---|---|---|
| add up verbo | adicionar | |
| back up verbo | retroceder, ciar | |
| break down verbo | descomponerse, averiarse | |
| fill out verbo | /fɪl ˈaʊt/ | rellenar, cumplimentar |
| give up verbo | rendirse, entregar | |
| go through verbo | atravesar | |
| put up verbo | colgar | |
| stay up verbo | quedarse despierto, empalmar |
Gramática en este vídeo
Las estructuras que más usa el hablante, con las palabras exactas del vídeo:
| Estructura | En el vídeo |
|---|---|
| Oraciones de relativo who / which + oración — información extra sobre una persona o cosa | option, which makes · OSworld, which is · memorizing, which is |
| Present perfect have/has + participio pasado — una acción pasada que sigue importando ahora | I've never understood · I've made · has been |
| Voz pasiva be + participio pasado — importa lo que ocurre, no quién lo hace | was released · are designed |
Pronunciación a tener en cuenta
El hablante usa 18 contracciones y formas reducidas, como you're, don't, I've. Dilas en su forma corta, tal como las oyes.
- Los sonidos de “th”: walkthrough /ˈwɔːk.θɹuː/, threshold /ˈθɹɛʃ(h)oʊld/
- Los sonidos de “sh” y “zh”: benchmark /ˈbɛn(t)ʃmɑːk/, snapshot /ˈsnæpʃɒt/, spreadsheet /ˈspɹɛd.ʃit/, spatial /ˈspeɪ.ʃəl/, elevation /ˌɛlɪˈveɪʃn̩/
- Palabras largas — cuida el acento: influencer /ˈɪnflu.ənsə(ɹ)/, coincidental /ˈkəʊ.ɪn.sɪˌdɛn.tl̩/, disassemble /dɪs.əˈsɛm.bəl/, generalize /ˈd͡ʒɛn.(ə.)ɹə.laɪz/, ocarina /ɑkəˈɹinə/
Sonidos difíciles para hispanohablantes:
- s + consonante al inicio — sin añadir una “e” delante: scam /ˈskæm/, scan /skæn/, schizophrenic /ˌskɪtsəˈfɹɛnɪk/, slander /ˈslændɚ/, snapshot /ˈsnæpʃɒt/
- /v/ — no es /b/: los dientes tocan el labio inferior: supervise /ˈsuː.pə.vaɪz/, vulnerability /ˌvʌln(ə)ɹəˈbɪlɪti/, vendor /ˈvɛn.dɚ/, elevation /ˌɛlɪˈveɪʃn̩/, flavor /ˈfleɪvə/
- /z/ — sonora, no /s/: generalize /ˈd͡ʒɛn.(ə.)ɹə.laɪz/, memorize /ˈmɛm.əˌɹaɪ̯z/, prioritize /pɹaɪˈɒɹ.ə.taɪz/, supervise /ˈsuː.pə.vaɪz/, autism /ˈɔːtɪzəm/
Cómo practicar con este vídeo
- Escucha el vídeo entero una vez sin hablar y anota las palabras que no conoces.
- Empieza a velocidad 0,75×, haz shadowing frase por frase y vuelve a la velocidad normal cuando te resulte fácil.
- Grábate y compara con el original, prestando atención a palabras como benchmark, anoint, influencer.
¿Qué es la Técnica de Shadowing?
Shadowing es una técnica de aprendizaje de idiomas respaldada por la ciencia, desarrollada originalmente para la formación de intérpretes profesionales y popularizada por el políglota Dr. Alexander Arguelles. El método es simple pero poderoso: escuchas audio en inglés nativo y lo repites en voz alta de inmediato, como una sombra que sigue al hablante con solo 1-2 segundos de retraso. A diferencia de la escucha pasiva o los ejercicios de gramática, el shadowing obliga a tu cerebro y músculos de la boca a procesar y reproducir simultáneamente patrones de habla reales. Las investigaciones muestran que mejora significativamente la precisión de la pronunciación, la entonación, el ritmo, el habla conectada, la comprensión auditiva y la fluidez al hablar, convirtiéndola en una de las metodologías más efectivas para la preparación del IELTS Speaking y la comunicación en inglés en el mundo real.