Finding patterns
A pattern is something that repeats or happens in a regular way. AI is very good at finding patterns in large amounts of data and using them to make predictions.
📌 Key points
- A pattern is something that repeats or follows a rule, like 2, 4, 6, 8 or day and night.
- People find patterns all the time: dark clouds often mean rain is coming.
- AI looks for patterns in data, often in far more data than a person could ever check.
- Once AI finds a pattern, it can use it to make a prediction about new data.
- A prediction is a good guess, not a certainty. Patterns have exceptions, so AI can be wrong.
- Sometimes AI finds a pattern that is just a coincidence and is not really useful. People need to check.
- Examples: a shop sells more ice cream on hot days; a map app learns that some roads are busy at 8 o'clock in the morning.
📖 Key words
- Pattern
- Something that repeats or happens in a regular way.
- Prediction
- A good guess about what will happen, based on patterns.
- Exception
- Something that does not follow the usual pattern.
- Coincidence
- When two things happen together by chance, not because they are linked.
- Trend
- The general direction data is going in, such as getting warmer each year.
✏️ Worked example
A shop records the temperature and how many ice creams it sells each day. What pattern might an AI find, and how could the shop use it?
- The data shows: 20 °C → 30 ice creams, 25 °C → 45 ice creams, 30 °C → 60 ice creams.
- Pattern: the hotter the day, the more ice creams are sold.
- Prediction: tomorrow will be 32 °C, so the shop should expect to sell more than 60 and order extra.
- It is only a prediction. If it rains or there is a holiday, the pattern may not hold.
- Answer: hotter days → more ice creams. The shop uses this to plan, but watches for exceptions.
Try this at home: write down something every day for a week, such as the weather or when the bus comes. Can you find a pattern and predict tomorrow?
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