跟读练习: Top five moments from CNBC's interview with OpenAI CEO Sam Altman - 通过视频学习英语口语
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People are really saying, you know, the future of my company, the future of my scientific research program, it is going to depend on this.
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Can you promise me compute long into the future?
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The coding models have so transformed how companies are doing their work
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and the efficiency and the speed of which they're able to build products.
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The coding models got really good late last year, early this year, and then another step forward in recent months.
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So I think you're right that that's the single biggest driver.
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But we are now seeing scientists really use these models and a much broader application of knowledge work beyond coding.
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The companies that I know that have adopted AI the most are also the ones hiring the most.
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And the companies, as a general rule, that are talking about doing layoffs because of AI are the ones adopting AI the least.
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But it's a convenient way to explain it.
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I think I underestimated how jagged these models are going to be.
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They do some things incredibly well, but they don't do kind of the long-term complex task supervision well at all.
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And so watching people who are really good at using these models, they can do an amazing amount of work,
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create way more economic value than people without models could or certainly the models could on their own.
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But I think people are right to be anxious and I understand it.
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This is not even a technological shift that happens every generation.
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This is one of the big ones.
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If not one of the biggest.
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And so it would be imprudent not to have some real caution around.
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I think there is a race to deliver the best technology and build the best business,
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but Going public is a financing event and I don't think that's one that we're focused on the timing of.
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We'll do it when we think it makes sense.
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But you will do it as well, I would assume.
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I assume we'll do it someday.
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So I think this is the most fair criticism right now of AI, which is you hear companies saying, I am spending a ton of money on AI.
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And I know some great stuff is happening, but I know there's a ton of waste.
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And how long do I have to wait for it to really show up in revenue
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and how long do I have to wait to really get the costs under control?
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I assume that the industry will figure that out pretty quickly, but I think that is a fair issue.
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You do.
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Yeah.
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Quickly being?
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I would bet that by another year
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or two from now there is a much better rationalization of companies' spend relative to outcomes.
为何通过这个视频练习口语？
在当前快速发展的科技背景下，了解人工智能的应用及其对商业和科学研究的影响至关重要。这段采访中，OpenAI的CEO Sam Altman分享了许多关于如何利用AI提高工作效率和经济价值的见解。这些见解不仅适用于科技行业，还适用于各个领域的职场人士。通过与该视频进行口语练习，学习者能够在真实的对话环境中练习表达观点，并熟悉行业相关的英语词汇。
上下文中的语法与表达
- 句子结构：在视频中，Altman使用了许多复合句来表达复杂的思想，例如“我认为这是一个严重的问题，但我也相信行业会迅速找到解决办法。”这样的句型在职业对话中非常常见，学习者可以通过模仿来提高英语口语练习。
- 条件句：比如“如果我们能更好地控制成本，公司的收入将会迅速增长。”这种条件句的使用，可以帮助学习者理解如何在谈论未来可能性时构建句子。
- 情态动词：Altman多次使用如“可以”、“应该”和“会”等情态动词，以表达建议和预期。这在日常对话和正式演讲中都非常重要，能帮助你自然地表达意图。
常见发音陷阱
视频中有一些难以发音的词汇，比如“AI”（人工智能）和“technology”（技术）。这些词汇的发音需要特别注意。在快速发言时，分清音节和语调是很有帮助的。此外，Altman的口音也渗透着硅谷的特色，学习者在模仿时可以体验不同的发音方式，打造出更自然的口语。
如果你渴望提高英语发音，不妨尝试“shadow speech”技巧，跟随视频进行“shadowing”，这样不仅可以改善发音，还能提高理解能力。通过“看YouTube学英语”，学习者可以轻松接触到许多真实的英语对话，提高英语口语练习的有效性。
什么是跟读法？
跟读法 (Shadowing) 是一种有科学依据的语言学习技巧，最初开发用于专业口译员的培训，并由多语言者Alexander Arguelles博士普及。这个方法简单而强大：您在听英语母语原声的同时立即大声重复——就像是一个延迟1-2秒紧跟说话者的影子。与被动听力或语法练习不同，跟读法强迫您的大脑和口腔肌肉同时处理并模仿真实的讲话模式。研究表明它能显着提高发音准确性，语调，节奏，连读，听力理解和口语流利度——使其成为雅思口语备考和真实英语交流最有效的方法之一。