🔑Key Terms
English Term | Explanation | Chinese Term | Chinese Explanation |
---|---|---|---|
1. Generative AI | A subfield of artificial intelligence that focuses on creating new content, ideas, or solutions autonomously. | 生成式 AI | 一个人工智能子领域,专注于自主创建新的内容、想法或解决方案。 |
2. Deep Learning | A subfield of artificial intelligence that uses artificial neural networks to mimic human brain functions for learning. | 深度学习 | 一个人工智能子领域,使用人工神经网络模仿人脑功能以进行学习。 |
3. Neural Network | A computer model inspired by the human brain, consisting of interconnected nodes or neurons. | 神经网络 | 受人脑启发的计算机模型,由相互连接的节点或神经元组成。 |
4. GPT (Generative Pre-trained Transformer) | A type of generative AI model that can understand and generate human-like text based on given input. | GPT (生成预训练变换器) | 一种生成式AI模型,可以根据给定输入理解和生成类似人类的文本。 |
5. Training Data | The data used to teach a machine learning model how to perform a specific task. | 训练数据 | 用于教授机器学习模型如何执行特定任务的数据。 |
6. Fine-tuning | The process of refining a machine learning model's performance using additional data. | 微调 | 使用额外数据优化机器学习模型性能的过程。 |
7. Natural Language Processing (NLP) | A subfield of artificial intelligence that enables computers to understand, interpret, and generate human language. | 自然语言处理 (NLP) | 一个人工智能子领域,使计算机能够理解、解释和生成人类语言。 |
8. Model | A mathematical representation of a system or process that can be used to make predictions or decisions. | 模型 | 用于预测或决策的系统或过程的数学表示。 |
9. Bias | A systematic error in a machine learning model's predictions due to flawed assumptions or training data. | 偏差 | 由于错误的假设或训练数据导致的机器学习模型预测中的系统性错误。 |
10. Hallucination | An output generated by a machine learning model that is not grounded in reality or input data. | 幻觉 | 机器学习模型生成的与现实或输入数据无关的输出。 |
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