Model Training & Adaptation
Supervised learning
Machine learning that learns from examples paired with known answers.
Example
An AI system learns to distinguish spam from messages labeled legitimate.
Why people use it
It teaches AI from examples where the desired answer is already known.
What you'll hear
“We showed it examples marked right or wrong.”
What this means for you
Ask how performance was checked on unseen, relevant examples.
Can you control it?
Developer-only
The people building or running the AI choose this setup. An everyday user generally needs their help to change how this part works.
Common questions
- Can accurate training answers guarantee good future predictions?
- No. New cases may differ from the examples used for learning.
- What happens if the teaching examples are wrong?
- The AI may learn those mistakes and repeat them when it encounters new cases.
- Does it need a person watching every lesson?
- No. People prepare or check the examples, but computers usually carry out the learning process automatically.