What is artificial intelligence?
Artificial intelligence (AI) is the branch of computer science dedicated to building systems that can perform tasks normally requiring human intelligence. That includes recognizing images and speech, understanding and producing language, making decisions, and learning from experience.
The term was first proposed in 1956, but AI as we know it today took off once two things became available in abundance: large datasets and cheap computing power. Together they made practical machine learning possible, where a model improves at a task by being shown examples rather than being explicitly programmed.
The main types of AI
AI is usually split into three categories by capability:
- Narrow AI (or weak AI) — systems built for one specific task, like transcribing audio or recommending products. Every AI in use today is narrow AI.
- General AI (AGI) — a hypothetical system as capable as a human across any task. It does not exist yet.
- Super AI — a speculative system surpassing human intelligence. Also theoretical.
How AI relates to machine learning and deep learning
These terms are nested, not interchangeable:
- AI is the broad goal — machines doing intelligent things.
- Machine learning is one approach to AI — systems that learn patterns from data.
- Deep learning is a subset of machine learning using multi-layered neural networks.
Why it matters
Artificial intelligence is already embedded in search engines, smartphones, healthcare diagnostics, fraud detection, and the generative tools reshaping creative work. Understanding what AI is — and what it isn't — is the foundation for evaluating any individual AI product.