Building AI by letting the computer learn rules from examples instead of being told.
Machine learning means you don't hand the computer the rules. You show it lots of examples and let it work the rules out. To catch spam, instead of listing "spammy" words one by one, you show it tens of thousands of spam and normal emails.
While looking at the examples, the computer keeps nudging the numbers inside it (its parameters) so it makes fewer mistakes. That process is called training. There are several styles: supervised learning gives it the right answers, reinforcement learning gives it rewards.
Think of it like this
Nobody learns to ride a bike by memorizing a manual. You wobble, fall, adjust and try again. Machine learning works the same way: practice and correction instead of a rulebook.
For example
A music app suggesting songs like the ones you keep replaying is machine learning.
Records about this
Source-checked moments from AI history.
The first learning procedure to update weights from errors. Psychological Review 65(6) 386–408