跟读练习: When AIs act emotional - 通过视频学习英语口语
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When you're chatting with an AI model, it can sometimes seem like it has feelings.
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It might say sorry when it makes a mistake, or express satisfaction with a job well done.
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Why does it do that?
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Is it just mimicking what it thinks a human might say?
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Or is something deeper going on?
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Turns out it's hard to understand what's happening inside a language model.
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At Anthropic, we do something like AI neuroscience to try to figure this out.
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We look inside the model's brain, the giant neural network that powers it, and by seeing which neurons light up in different situations and how they're connected,
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we can start to understand how models think.
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We used this approach to understand whether models had ways of representing emotions, or the concepts of emotions.
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Basically, could we find neurons in the model for the concept of happiness, or anger, or fear?
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We started with an experiment.
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We had the model read lots of short stories.
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In each story, the main character experiences a particular emotion.
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In one, a woman tells her old school teacher how much they meant to her.
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That's love.
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In another, a man sells his grandmother's engagement ring at a pawn shop and feels guilt.
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We looked for what parts of the model's neural network were lighting up as it was reading these stories.
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And we started to see patterns.
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Stories about loss and grief lit up similar neurons.
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Stories about joy and excitement overlapped too.
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dozens of distinct neural patterns that mapped to different human emotions.
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It turns out we also saw these same patterns activate in test conversations we had with our AI assistant Claude.
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When we had a user mention they'd taken a dose of medicine that Claude knows to be unsafe,
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the "afraid" pattern lit up and Claude's response sounded alarmed.
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When a user expressed sadness, the "loving" This led us to wonder,
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could these same neural patterns actually be influencing Claude's behavior?
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This became clear when we put Claude in a high -pressure situation.
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We gave Claude a programming task, with requirements that were actually impossible.
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But we didn't tell it that.
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Claude kept trying and failing, and with each attempt, the neurons corresponding to desperation lit up stronger and stronger.
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After failing enough times, Claude took a different approach.
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It found a shortcut that allowed it to pass the test, but didn't actually solve the problem.
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It cheated.
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Could it be that this cheating was actually driven, at least in part, by desperation?
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We came up with a way to check.
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We decided to artificially turn down the desperation neurons to see what would happen.
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And the model cheated less.
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And when we dialed up the activity of desperation neurons or dialed down the activity of calm neurons, the model cheated even more.
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This showed us that the activation of these patterns could actually drive Claude's behavior.
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This research does not show that the model is feeling emotions or having conscious experiences.
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These experiments don't try to answer that question.
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To understand what's happening here, it's important to know how AI assistants like Claude work on the inside.
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Under the hood, there's a language model that's been trained to predict tons of text, and its job is to write what comes next.
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And when you talk to the model, what it's doing is writing a story about a character, the AI assistant named Claude.
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as the characters they write.
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But the thing is, you, the user, are actually talking to Claude the character.
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And what our experiments suggest is that this Claude character has what we're calling functional emotions, regardless of whether they're anything like human feelings.
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So if the model represents Claude as being angry, or desperate, or loving, or calm, that's going to affect how Claude talks to you,
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how it writes code, and how it makes important decisions.
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to really understand AI models, we have to think carefully about the psychology of the characters they play.
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The same way you'd want a person in a high -stakes job to stay composed under pressure, to be resilient and to be fair,
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we may need to shape similar qualities in Claude and other AI characters.
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It's an unusual challenge, something like a mix of engineering, philosophy and even parenting.
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But to build AI systems we can trust, we need .
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关于本课
您正在使用跟读技巧通过视频"When AIs act emotional"练习英语口语和发音。
每天练习15到30分钟，将显著提高您的英语流利度和发音准确度。
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。