How Artificial Intelligence Works

Data, training and neural networks in plain language — and where AI has limits

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How Artificial Intelligence Works

Data, training and neural networks in plain language — and where AI has limits

Artificial intelligence writes texts, recognizes faces and recommends what to watch next. It can feel like magic, but under the hood there is a surprisingly simple idea: learning patterns from examples. This explainer shows how that works — without formulas.

1

What AI is — and what it is not

— From hand-written rules to learning from data

For decades, programs followed rules written by people: if the email contains “win a prize”, mark it as spam. Modern AI works differently. Instead of rules, it gets thousands of examples — spam and normal emails — and finds the patterns itself. It does not understand the world the way people do; it calculates what is most likely given what it has seen.

Rules

People write the logic. Predictable, but breaks on cases nobody thought of.

Machine learning

The program learns patterns from labeled examples and applies them to new data.

Generative AI

Models trained on huge amounts of text or images create new content from a prompt.

We can only see a short distance ahead, but we can see plenty there that needs to be done.

— Alan Turing, Computing Machinery and Intelligence, 1950
2

How a model learns

— Data in, patterns out

Every AI system goes through the same stages. Click the markers to see what happens at each one.

Click a marker to see each stage
Click a marker to see each stage
  1. 1

    Collect data

    Gather examples and label them: “cat”, “dog”, “spam”, “not spam”.

  2. 2

    Train

    Show the examples to the model over and over until its guesses stop improving.

  3. 3

    Test

    Check the model on examples it has never seen to measure real accuracy.

  4. 4

    Use

    Put the model to work on new data in a product.

  5. 5

    Improve

    Collect mistakes, add new data and retrain.

Self-checkPut the stages of building an AI model in order.

Put the items in the correct order

  1. Test
  2. Train
  3. Collect data
  4. Use
  5. Improve
3

Inside a neural network

— Layers of simple calculations

A neural network: inputs on the left, hidden layers in the middle, answers on the right. The highlighted path is one signal.
Three columns of connected circles with one highlighted path from left to right

A neural network is a chain of layers. Each “neuron” takes numbers from the previous layer, weighs them and passes the result on. Training adjusts the weights so that the final answer matches the examples more and more often.

Receives raw data as numbers: pixels of a photo or words of a sentence turned into numbers.

What AI does in everyday products
TaskWhat it doesExample
ClassificationPuts input into categoriesSpam filter
PredictionEstimates a numberDelivery time forecast
RecommendationSuggests what you may likeNext video to watch
GenerationCreates new contentDrafting an email
Self-checkMatch each product feature with the type of AI task.

Match each item with its pair

Sorting support tickets by topic
Estimating next month’s sales
Suggesting courses to an employee
Writing a first draft of a summary

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