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# AI 专业术语概念 | ||
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## Generative Al(Gen AI) | ||
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生成型人工智能,是人工智能领域的一个分支,专注于创造新的内容,如图像、音乐、文本等。这些内容可以与人类创作的内容相媲美,甚至无法区分。 | ||
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## Prompt | ||
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提示词,是指输入到模型的初始信息或指令,用于引导模型生成特定的输出内容。 | ||
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## Prompt Engineering | ||
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提示工程,是指设计和调整提示,以引导模型生成特定的输出内容。 | ||
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## Prompt Injection | ||
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提示词注入攻击,是一种针对生成型人工智能模型的攻击方式,通过在输入中注入提示词,使模型生成特定的输出内容。 | ||
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## Agent | ||
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Agent 是一种以人工智能技术为基础的软件程序,可以代表用户执行特定的任务。 | ||
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## AI hallucination | ||
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AI 幻觉,是指人工智能模型生成的内容与现实世界不符,或者没有实际意义。 | ||
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## Chain of Thought (CoT) | ||
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思维链,是一种基于提示工程的人工智能模型,可以生成连贯的文本内容。 | ||
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## Context Window | ||
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上下文窗口,是指模型在生成文本时考虑的上下文范围。 | ||
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## Embedding | ||
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嵌入,是指将文本、图像等数据映射到低维空间的过程。 | ||
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## Retrieval | ||
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检索,是指从数据库中检索相关信息的过程。 | ||
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## Inference | ||
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推理,是指从已知事实推导出新的结论的过程。 | ||
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## Fine-Tuning | ||
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微调,是指在预训练模型的基础上,通过少量数据进行训练,以适应特定任务。 | ||
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## LangChain | ||
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LangChain 是一种基于提示工程的人工智能模型,可以生成连贯的文本内容。 | ||
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## Large Language Model(LLM) | ||
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大型语言模型,是指参数量较大的语言模型,通常具有更好的生成能力。 | ||
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## Multimodal Model | ||
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多模态模型,是指可以处理多种数据类型(如文本、图像、音频等)的人工智能模型。 | ||
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## zero-shot | ||
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zere-shot 是指训练模型在没有直接接触到某些特定任务或类别的样板的情况下,依然能够识别和处理这些新任务的能力。 | ||
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## few-shot | ||
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few-shot 是指只有在少量样本的情况下,模型就能够学习到新任务的能力。 |
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# children | ||
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## 什么是 children | ||
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`children` 是一个特殊的 prop,它允许将组件作为数据传递到其他组件。 | ||
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## 基本用法 | ||
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`props.children`可以是任意的 JSX 元素,包括原始值、React 元素、函数、组件等。 | ||
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::: code-group | ||
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<<< @/../projects/react-sandbox/src/pages/children-demo/ChildrenOriginalValue.tsx [原始值] | ||
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<<< @/../projects/react-sandbox/src/pages/children-demo/ChildrenReactElement.tsx [React 元素] | ||
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<<< @/../projects/react-sandbox/src/pages/children-demo/ChildrenFunction.tsx [函数] | ||
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<<< @/../projects/react-sandbox/src/pages/children-demo/ChildrenComponent.tsx [组件] | ||
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::: | ||
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## 传递多个具名的子组件 | ||
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<<< @/../projects/react-sandbox/src/pages/children-demo/ChildrenMultiple.tsx |
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