Lesson 04 — What Are AI Models?

We have seen that AI systems learn patterns from data. But what exactly is doing the learning?

The answer is an AI model.

Understanding what a model is will make many other AI concepts much easier to understand.

What Is an AI Model?

An AI model is a system that has learned patterns from data and can use those patterns to produce a result.

Think of it as the part of an AI system that contains what it has learned.

For example, a model trained to recognize cats can look at a new image and estimate whether it contains a cat.

How Does a Model Learn?

During training, the model is exposed to many examples.

It looks for patterns in those examples and gradually adjusts itself to become better at its task.

For example, imagine training a model to recognize handwritten numbers.

You could show it thousands of examples of the numbers 0 to 9. Over time, the model learns patterns that help it distinguish one number from another.

Models Learn Different Things

Not every AI model is designed for the same purpose.

Some models are designed to:

• Understand or generate text
• Recognize images
• Generate images
• Understand speech
• Translate languages
• Write or analyze code
• Make predictions from data

This is why the AI tool you choose matters. Different models can have very different abilities.

What Is a Large Language Model?

You may have heard the term LLM.

LLM stands for Large Language Model.

These models are trained on large amounts of text and are designed to understand and generate human language.

ChatGPT, Claude, Gemini, and many other AI assistants use large language models.

What Makes a Model “Large”?

The word “large” generally refers to the enormous amount of data and computing resources involved in training these models, as well as the number of internal parameters they contain.

You do not need to understand the mathematics behind parameters yet.

For now, think of parameters as adjustable values that help the model recognize patterns and produce useful results.

One Model Can Power Many Tools

An AI model and an AI application are not always the same thing.

A company can build an application around a model and add features such as a chat interface, file uploads, web search, image generation, or other tools.

This means that two different AI applications can sometimes use similar underlying models while offering very different experiences.

A Simple Analogy

Think of an AI model as the brain behind a tool.

The model provides the ability to process information, while the application provides the interface and features that allow you to interact with it.

This is not a perfect comparison, but it is a useful way to understand the difference between an AI model and an AI application.

Why Do AI Models Matter?

The model behind an AI tool can strongly influence what the tool is capable of doing.

A model designed for coding may perform better at programming tasks than a model designed primarily for image generation.

Understanding models will therefore help you make better choices when selecting AI tools.

Key Takeaways

• An AI model learns patterns from data.
• Different models are designed for different tasks.
• LLM means Large Language Model.
• Many AI assistants are built using language models.
• An AI model and an AI application are not necessarily the same thing.
• The model behind a tool can strongly influence its capabilities.

What’s Next?

Now that you understand what an AI model is, we can look at one of the most important ideas behind modern AI: machine learning.

In the next lesson, we will explain what machine learning means and how it allows computers to learn from data.