课程概述
📚 课程概述
本课程为人工智能与机器人技术提供基础入门，引导学生了解使机器能够学习和与世界互动 Thus core concepts。我们将从定义人工智能以及探索其基础工具开始，例如用于感知Thus sensors 和用于指令遵循Thus algorithms。课程Then 深入探讨机器如何通过数据（机器学习）获取 intelligence，并考察生成式AIThus creative potential。最后，课程将Thus mechanical hardware（机器人技术）与Thus smart brain 结合起来，并以必要Thus ethical guidelines 结尾，确保强大Thus AI Technologies 的负责任和有益Thus use。
🎯 学习目标
完成本课程后，您将能够：
- 定义人工智能，并将“智能”机器系统与传统Thus automated toys 区分开来。
- 解释传感器、算法和数据训练在实现机器感知和学习中的作用。
- 分析AI软件（“大脑”）与机器人硬件（“身体”）之间的联系，并应用基本的道德规则与这些技术安全互动。
🔹 Lesson 1: Awakening the Sleeping Robot (Hello AI)
Overview: Understanding what Artificial Intelligence is and how a machine with a 'smart brain' is different from simple, remote-controlled toys.
Learning Outcomes:
- Define AI as a machine that can think, learn, and respond independently.
- Distinguish between AI-driven robots and non-AI toys (cause and effect).
- Understand that AI listens and processes information (voice commands).
- Identify real-world AI relatives, such as smart home assistants.
🔹 第1课：唤醒沉睡的机器人（你好，人工智能）
概述： 了解什么是人工智能，以及拥有“智能大脑”的机器与简单的遥控玩具有什么不同。
学习成果：
- 将人工智能定义为能够独立思考、学习和响应的机器。
- 区分由人工智能驱动的机器人和非人工智能玩具（原因和结果）。
- 理解人工智能能够收听并处理信息（语音命令）。
- 识别现实世界中的人工智能“亲戚”，例如智能家居助手。
🔹 Lesson 2: Eyes and Ears for Machines (Sensors)
Overview: Exploring how machines sense and perceive the world using specialized sensors, which act as the robot's eyes and ears.
Learning Outcomes:
- Introduce sensors (cameras, microphones) as the machine's 'five senses'.
- Understand that machines interpret sensory input as 'numbers' or data, not images/sounds directly.
- Practice using machine vision to identify objects or faces in an interactive game.
- Recognize sensor technology in everyday tools like barcode scanners.
🔹 第2课：机器的眼睛和耳朵（传感器）
概述： 探索机器如何使用专用传感器来感知和识别世界，这些传感器充当机器人的眼睛和耳朵。
学习成果：
- 将传感器（摄像头、麦克风）介绍为机器的“五官”。
- 理解机器将感官输入解释为“数字”或数据，而不是直接的图像/声音。
- 在交互式游戏中练习使用机器视觉来识别物体或人脸。
- 识别日常工具中的传感器技术，例如条形码扫描仪。
🔹 Lesson 3: The Robot's Recipe Book (Algorithms)
Overview: Learning why machines follow instructions in a specific order. Algorithms are the detailed, step-by-step recipes machines use to solve problems.
Learning Outcomes:
- Define an algorithm as the ordered steps or 'recipe' for completing a task.
- Understand that the order of steps is crucial for machines to succeed.
- Participate in a pathfinding game to provide sequential instructions to a robot.
- Identify real-world applications of algorithms, such as GPS navigation.
🔹 第3课：机器人的食谱（算法）
概述： 学习机器为何要按特定顺序执行指令。算法是机器用来解决问题的详细、分步的“食谱”。
学习成果：
- 将算法定义为完成任务的有序步骤或“食谱”。
- 理解步骤顺序对于机器的成功至关重要。
- 参与寻路游戏，为机器人提供连续的指令。
- 识别算法的现实世界应用，例如 GPS 导航。
🔹 Lesson 4: How Machines Get Smart (Data & Training)
Overview: Discovering the concept of Machine Learning. Machines are not born smart; they need 'training' by looking at lots of examples (data) to find patterns.
Learning Outcomes:
- Explain that machines learn through 'training,' similar to how humans learn to ride a bike.
- Understand the role of data (pictures, examples) in helping AI classify objects.
- Practice being a 'coach' by training a robot to recognize different items.
- Discuss the importance of feeding AI positive and accurate training information.
🔹 第4课：机器如何变聪明（数据与训练）
概述： 探索机器学习的概念。机器并非天生就聪明；它们需要通过观察大量示例（数据）来“训练”，以发现模式。
学习成果：
- 解释机器通过“训练”来学习，就像人类学习骑自行车一样。
- 理解数据（图片、示例）在帮助人工智能对物体进行分类中的作用。
- 通过训练机器人识别不同物品来练习充当“教练”。
- 讨论向人工智能提供积极和准确训练信息的重要性。
🔹 Lesson 5: The Magic Sketchpad (Generative AI)
Overview: Exploring the creative power of Generative AI, which allows machines to draw pictures, write stories, and create things that never existed before.
Learning Outcomes:
- Define Generative AI as the ability of a machine to create novel content.
- Distinguish generated content from simple collages or copying.
- Use interactive prompts to witness AI transforming simple ideas into detailed artwork.
- Recognize the limitless imaginative potential of AI (e.g., drawing winged elephants).
🔹 第5课：魔法画板（生成式人工智能）
概述： 探索生成式人工智能的创造力，它能让机器绘画、写作和创造前所未有的事物。
学习成果：
- 将生成式人工智能定义为机器创造新颖内容的能力。
- 区分生成内容与简单的拼贴或复制。
- 使用交互式提示，见证人工智能将简单的想法转化为精美的艺术品。
- 认识到人工智能无限的想象潜力（例如，画出有翅膀的大象）。
🔹 Lesson 6: The Iron Super-Body (Robotics)
Overview: Understanding the physical side of AI. The mechanical body (robotics) carries out the commands given by the AI brain using joints, motors, and batteries.
Learning Outcomes:
- Differentiate between AI (the intelligence/brain) and Robotics (the physical body).
- Understand the role of physical components like motors and actuators in movement.
- Practice controlling a simulated robotic arm to perform a precise physical task.
- Identify everyday household robots (e.g., vacuum cleaners) as integrated AI systems.
🔹 第6课：钢铁超体（机器人技术）
概述： 理解人工智能的物理层面。机械身体（机器人技术）利用关节、马达和电池执行人工智能大脑发出的命令。
学习成果：
- 区分人工智能（智能/大脑）和机器人技术（物理身体）。
- 理解马达和执行器等物理组件在运动中的作用。
- 练习控制模拟机械臂来执行精确的物理任务。
- 将日常家用机器人（例如吸尘器）识别为集成的人工智能系统。
🔹 Lesson 7: Rules for Good Friends (Ethics)
Overview: Establishing ethical guidelines and 'Good Friend Rules' for interacting with powerful AI, ensuring machines are used as helpful assistants.
Learning Outcomes:
- Understand that AI must follow rules and listen to good human commands.
- Establish AI's primary role as a helpful assistant, not a bad influence.
- Practice ethical decision-making when presented with scenario choices for the robot.
- Recognize human responsibility in commanding and training AI systems kindly and fairly.
🔹 第7课：好朋友的规则（伦理）
概述： 建立与强大人工智能互动的伦理准则和“好朋友规则”，确保机器被用作有益的助手。
学习成果：
- 理解人工智能必须遵守规则并听从人类的良好指令。
- 确立人工智能的主要作用是有益的助手，而不是不良影响。
- 在面对机器人场景选择时，练习道德决策。
- 认识到人类在友善、公平地指挥和训练人工智能系统方面的责任。