What is Artificial Intelligence?

AI in plain language

Artificial intelligence (AI) is a broad name for computer systems that do things we normally associate with human thinking: recognizing faces in photos, understanding speech, recommending a movie, translating a sentence, or writing a paragraph.

You already use AI every day, often without noticing it:

• Your email's spam filter decides which messages are junk.
• Your phone's keyboard suggests the next word as you type.
• A streaming service recommends a show based on what you watched last week.
• A map app predicts how long your drive will take given current traffic.

None of these systems "think" the way you do. They are very good at spotting patterns in data and using those patterns to make a useful guess.

From rules to learning

Early software was built on rules. A programmer wrote every instruction by hand: "If the email contains the phrase you have won, mark it as spam." Rules work well when the world is predictable, but they break quickly. Spammers just change the wording.

Machine learning flipped the approach. Instead of writing the rules, people show the computer thousands or millions of examples ("this email is spam, this one isn't") and let it learn the patterns itself. The result is a model: a large mathematical structure that captures what it learned from the examples.

Here is how the common terms nest inside each other:

Where AI assistants fit

The tools most people mean when they say "AI" today, such as ChatGPT, Claude, or Gemini, are generative AI assistants built on large language models (LLMs). A language model learned from an enormous amount of text and can produce new text that fits what you asked for. You'll see how that works in a later lesson.

What makes these assistants different from older AI is that they are general-purpose. The same assistant can draft an email, explain photosynthesis, suggest a recipe for what's in your fridge, and help debug a spreadsheet formula. You steer it entirely with words.

That's the key idea of this whole course: with an AI assistant, your words are the controls. There are no menus for "make it shorter" or "write for a ten-year-old." You just say so.

A real-world example

Imagine you want help planning a weekend trip. Many people's first instinct is to treat the assistant like a search engine and type a few keywords:

The first version gives the assistant almost nothing to work with, so you'll get a generic list. The second version uses what an AI assistant is actually good at: taking your specific situation and shaping an answer around it. A search engine finds pages that already exist; an AI assistant generates a response for you.

What AI is good at, and what it isn't

AI assistants are genuinely strong at:

• Drafting and rewriting text (emails, summaries, outlines)
• Explaining concepts at different levels
• Brainstorming lots of options quickly
• Reformatting information (notes into a table, a paragraph into bullet points)
• Helping with code and formulas

They are weaker at, or can be unreliable for:

• Guaranteeing that facts, quotes, or references are correct
• Knowing about very recent events (unless connected to a search tool)
• Precise counting and some kinds of arithmetic
• Knowing anything about you that you haven't told them

Why this matters for prompting

Because an AI assistant learned from patterns rather than following fixed rules, the way you ask shapes what you get. A vague request matches vague, average patterns. A clear, specific request gives the model much more to work with. That skill of asking well is called prompting, and it's what the rest of this course is about.

Quick recap

AI is a broad field; machine learning lets computers learn from examples; generative AI creates new content; and the AI assistants you use today are general-purpose tools you control with ordinary language. Next up: what exactly a prompt is.