一、基础概念
– 人工智能:Artificial Intelligence (AI)
– 大模型:Large Language Model (LLM)
– 机器学习:Machine Learning (ML)
– 深度学习:Deep Learning
– 算法:Algorithm
– 数据:Data
– 训练:Train / Training
– 学习:Learn / Learning
– 推理:Inference
– 生成:Generate / Generation
二、模型与技术
– 自然语言处理:Natural Language Processing (NLP)
– 计算机视觉:Computer Vision (CV)
– 语音识别:Speech Recognition
– 图像生成:Image Generation
– 文本生成:Text Generation
– 预训练:Pre-training
– 微调:Fine-tuning
– 提示词:Prompt
– 对话模型:Conversational Model
– 多模态:Multimodal
三、功能与能力
– 回答:Answer / Response
– 总结:Summarize / Summary
– 翻译:Translate / Translation
– 创作:Create / Creation
– 理解:Understand / Understanding
– 交互:Interact / Interaction
– 推荐:Recommend / Recommendation
– 识别:Recognize / Recognition
– 分析:Analyze / Analysis
– 优化:Optimize / Optimization
四、应用场景
– 智能助手:AI Assistant
– 聊天机器人:Chatbot
– 智能写作:AI Writing
– 智能教育:AI Education
– 自动驾驶:Autonomous Driving
– 人脸识别:Face Recognition
– 智能推荐:Smart Recommendation
– 内容创作:Content Creation
五、安全与伦理
– 隐私:Privacy
– 安全:Security
– 合规:Compliance
– 公平:Fairness
– 透明:Transparency
– 负责任AI:Responsible AI
六、常用句子
– 人工智能正在改变世界:AI is changing the world.
– 大模型能理解和生成语言:Large models understand and generate language.
– 我是AI助手:I am an AI assistant.
– 提示词很重大:Prompts are very important.