How AI Works

Understand AI process.

The Learning Process

1. Get Data: Collect examples
2. Train: AI learns patterns
3. Test: Check if AI learned correctly
4. Use: AI makes predictions

Example: Teaching AI to Recognize Cats

Step 1: Show 10,000 cat pictures
Step 2: AI finds patterns (fur, ears, whiskers)
Step 3: Test with new cat pictures
Step 4: AI can now identify cats!

Training vs Inference

Training: Teaching AI (takes time)
Inference: AI using what it learned (fast)

Like studying for exam (training) vs taking exam (inference).

Data is Key

More data = Better AI

If you show AI only 10 pictures, it won't learn well.
Show it 1 million pictures, it becomes very accurate!

AI Mistakes

AI can make mistakes, especially:

• With new types of data
• When training data was limited
• When data had errors

Remember

• AI learns from examples
• More data = better results
• Training takes time, using is fast