쉐도잉 연습: Introducing GPT-6 Astra for developers - 영상으로 영어 말하기 배우기
레슨 만드는 중...
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GPT-6 Astra is here.
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It's our latest frontier model and the best model in the world for tasks where raw intelligence matters.
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For my own projects, Astra feels like working with an experienced collaborator.
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I'm able to hand it bigger, less well-defined tasks with minimal handholding.
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And whether you're coding, writing, designing, or just working on things that require a little bit more intellectual horsepower, you'll find that Astra delivers great results,
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often on the first attempt.
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So let's talk about the model's new capabilities, starting with computer use.
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You might already be familiar with computer use.
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It's a capability that lets a model use a computer or browser like you or I would.
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With Astra, the model is more accurate and more efficient when using a computer.
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It's easiest to show this in the ChatGPT app, but Astra's improved skills are also available in the API.
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I'm going to have it illustrate where where I'm standing.
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I'll take a photo, then send it to Codex to paint.
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Use Krita to paint this picture in the style of Van Gogh and add the Golden Gate Bridge in the background.
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Astra has to keep track of the picture I asked for while working through the app's controls.
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It's using screenshots to see what's happening while keeping the app in the background, meaning I can stay focused on other work.
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The model is able to paint a hopefully recognizable picture far faster and far better than I could have done.
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The same ability can help with the workflows developers use every day, whether you're filling out forms for an API key or performing QA on a mobile app.
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When it comes to creativity and knowledge work, we've also seen Astra produce significantly better outputs than previous models.
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We took several prompts of demos, games, and tools we've built with previous models and rebuilt them at different reasoning levels.
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Across the board, Astra has more attention to detail, better understanding of the user's prompt, and can build more sophisticated outputs.
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In particular, it excels at building 3D models.
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I've seen it make incredible renderings of gardens, shipyards, animals, cityscapes, even Dyson spheres.
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In my own experience, I've found Astra's outputs, from slideshows to essays, significantly easier to read and work with than other models I've tried.
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Its personality feels more natural to me, especially in the back and forth when I'm giving it feedback.
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As you might expect, Astra excels at long-running tasks.
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And as you give models longer, more involved pieces of work, you need better ways to work with them.
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That's why we're bringing asynchronous tool calling and steering to the Responses API.
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First, async tools.
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With asynchronous tool calling, the model can keep working on other parts of a task while a tool call runs.
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When the results are available, it can use that information to continue.
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Steering lets you give the model new context or change its direction while a response is still in progress.
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If you view steering in codecs, this should feel familiar.
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Let's go ahead and give the model a task and then change what we're asking for while it's working.
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You can see it pick up my new instruction and adjust its next steps while the tool it already started continues running.
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I can change the direction without having to cancel the running tool or start the task over.
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And I get the final result with the new context incorporated.
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Astra is now available in ChatGPT, Codex, and the API.
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Try it on your most challenging tasks and take a close look at the results.
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Happy building.
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이 영상에서 배울 말하기 실력
이 영상은 기술 제품을 소개하는 전문적이고 논리적인 발화 스타일을 연습할 수 있는 기회를 제공합니다. 특히, 복잡한 기능을 간결하게 설명하는 방법과 자신의 경험을 결합해 설득력 있는 이야기를 전달하는 법을 배울 수 있습니다. 또한, "비동기 도구 호출"과 같은 전문 용어를 자연스럽게 사용하면서 청자에게 명확히 전달하는 용어 구사 능력도 향상시킬 수 있습니다.
들어야 할 연속 발음 현상
영어의 자연스러운 발음을 배우기 위해서는 연결 발음(linking)과 축약 발음(reductions)에 주목해야 합니다. 이 영상에서는 "it's our"가 /ɪts aʊər/가 아닌 /ɪts aʊər/로 연결되거나, "you'll find that"에서 "that"이 /ðæt/가 아닌 /ðət/로 축약되는 것을 들을 수 있습니다. 이러한 현상은 말하기 속도를 높이고 자연스러운 리듬을 만들어 주므로, 쉐도잉(shadowspeak) 연습 시 반드시 따라해 보세요.
원어민처럼 말하는 법: 리듬과 강세
원어민의 발음을 흉내내기 위해서는 리듬과 강세를 중점적으로 연습해야 합니다. 이 영상의 화자는 "GPT-6 Astra is here"에서 "Astra"를 강조하고, "the model is more accurate and more efficient"에서 "accurate"와 "efficient"에 강세를 두어 중요한 정보를 강조합니다. 또한, 긴 문장에서 쉼표나 마침표 없이 자연스럽게 흐르는 리듬을 가지고 있는데, 이는 영상 영어 공부 시 쉐도잉을 반복함으로써 익힐 수 있습니다. 특히, "Happy building"과 같은 짧은 문장에서는 높은 톤으로 끝내어 긍정적인 느낌을 전달하는 방법도 관찰해 보세요. 이렇게 리듬과 강세를 맞추면, 영어 발음 교정뿐만 아니라 의사 전달력도 크게 향상됩니다.
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.