AI Fundamentals
20 min read
How AI Learns
The simple truth about how machines learn patterns
How does a computer learn to write like a human? The answer is surprisingly simple: it sees a lot of examples, makes predictions, checks if it was right, and adjusts. Repeat billions of times, and you get ChatGPT.
Learning From Examples
Imagine you're learning a new language. At first, you memorize phrases. Then you start noticing patterns. Eventually, you can construct sentences you've never heard. AI learning works similarly, but at massive scale.
The Training Loop
All AI training follows the same basic loop: Show input → Make prediction → Check answer → Adjust model. Repeat billions of times, and the model transforms from random noise to something that can write poetry or debug code.
Generalization
The remarkable thing about neural networks isn't that they memorize—it's that they generalize. After seeing enough examples, AI can solve problems it's never seen before.
💡 Key Takeaways
- AI learns through predict-check-adjust cycles
- More data = more nuanced understanding
- Neural networks generalize from patterns
Ready for the full curriculum?
This is just one chapter. Get all 9+ chapters, practice problems, and bonuses.
30-day money-back guarantee • Instant access • Lifetime updates