AI vs Machine Learning
AI is the broader field of intelligent software; Machine Learning is one way to build it.
Artificial Intelligence describes any software that behaves intelligently. Machine Learning is one of the main techniques used to build AI systems — models learn patterns from data instead of following rules.
| Dimension | Artificial Intelligence | Machine Learning |
|---|---|---|
| Definition | The field of intelligent software. | A technique where models learn from data. |
| Scope | Broad — includes rules, search, planning and ML. | A subset of AI. |
| Approach | Any method that produces intelligent behaviour. | Statistical learning from examples. |
| Example | A voice assistant. | The speech-to-text model inside that assistant. |
Key differences
- Every ML system is AI, but not every AI system is ML.
- AI can be rule-based; ML is always data-driven.
- ML depends on data quality; classical AI depends on hand-written logic.
When to reach for each
Use the term AI when discussing intelligent behaviour overall.
Use ML when the emphasis is on learning from data.
Is ChatGPT AI or ML?
Both — ChatGPT is an AI product built on machine-learning models.
Do I need ML to work with AI?
Not always — using AI tools like ChatGPT doesn't require ML expertise, but building AI does.
Glossary
Artificial Intelligence
Artificial Intelligence is the field of building software systems that can perceive, reason, learn and generate content.
Machine Learning
Machine Learning is a branch of AI where systems learn patterns from data instead of following fixed rules.
Deep Learning
Deep Learning is a type of machine learning that uses many-layered neural networks to learn complex patterns.