What is AI?
Overview
In this lesson, you will learn:
- What Artificial Intelligence (AI) is and how it works.
- Key components of AI systems, including agents and environments.
- Differences between AI, Machine Learning (ML), and LLMs.
- Practical examples of AI in daily life.
By the end, you will understand the core concept of AI and how it interacts with real-world tasks.
Key Concepts
- Artificial Intelligence (AI): Machines performing tasks that normally require human intelligence.
- Machine Learning (ML): A subset of AI where machines learn patterns from data.
- Large Language Models (LLMs): AI models trained on text to generate or understand language.
- Agent: An AI entity that perceives input and takes actions to achieve goals.
- Environment: The world in which the AI agent operates.
Concept Explanation
1. What is AI?
AI enables machines to perform tasks like:
- Understanding and generating text or speech
- Recognizing images or patterns
- Solving problems and making decisions
Examples in daily life:
- Chatbots (ChatGPT, Google Bard)
- Recommendation systems (Netflix, YouTube, Spotify)
- Smart assistants (Siri, Alexa)
- Navigation apps (Google Maps, Waze)
2. AI vs ML vs LLMs
- AI: Broad concept – machines performing intelligent tasks.
- ML: AI that learns from data to improve performance automatically.
- LLMs: Specialized AI models trained to understand and generate natural language.
Example:
- AI: A self-driving car.
- ML: Car learns from driving data to improve braking and lane control.
- LLM: ChatGPT generating step-by-step instructions for a task.
3. Agents and Environments
- Agent: Reads input (percepts) and acts (actions).
- Environment: Everything outside the agent, including humans, objects, and rules.
Example – Thermostat Agent:
- Percepts: Current room temperature
- Actions: Turn heater on/off
- Environment: Room, weather, user preferences
Example – Chatbot Agent:
- Percepts: User messages
- Actions: Generate responses
- Environment: Chat interface, user context
Practical Examples
Example 1 – Chatbot Interaction
- Input: “Explain photosynthesis.”
- AI Agent generates a step-by-step explanation.
Example 2 – Recommendation System
- Input: User watched “Movie A”
- Action: AI suggests “Movie B”
- Environment: Streaming platform user history and preferences
Example 3 – Smart Assistant
- Input: “Remind me to call John at 5 PM.”
- Action: Schedule reminder
- Environment: Phone calendar and notifications
Tools for Hands-On Practice
- ChatGPT / OpenAI Playground: Interact with AI agents via text.
- Google Bard / Gemini: Explore LLM outputs.
- Replit / Jupyter Notebook: Experiment with AI APIs and small ML tasks.
Step-by-Step Beginner Activity
- Identify one AI agent in your daily life (chatbot, recommendation system, or smart assistant).
- List its percepts, actions, and environment.
- Determine if it behaves rationally to achieve its goal.
- Record findings in a table:
| Agent | Percepts | Actions | Environment | Rational? |
Exercises
- Give 3 examples of AI agents you interact with daily.
- Describe their percepts, actions, and environment.
- Identify one ML application and one LLM application.
- Explain how an AI agent achieves its goal in one of your examples.
Summary & Key Takeaways
- AI allows machines to perform tasks requiring human-like intelligence.
- ML enables AI to learn from data, improving performance.
- LLMs specialize in language understanding and generation.
- Agents perceive inputs, act on them, and operate in an environment.
- Understanding AI fundamentals prepares learners to use and design effective prompts in LLMs.