The main difference is the range of tasks an AI system is designed and capable of handling.
- Narrow AI: Also called weak or specialized AI, it is built to perform specific tasks or a limited range of related tasks. Examples include spam filters, recommendation systems, image-recognition software, and voice assistants. A narrow AI can perform its intended task extremely well without having general human-like intelligence.
- Artificial General Intelligence (AGI): AGI refers to a hypothetical type of AI that could learn, reason, adapt, and apply knowledge across a broad range of tasks, rather than being limited to one specific application. An AGI system would be expected to transfer knowledge between different domains and handle unfamiliar problems with much greater generality.
| Feature | Narrow AI | AGI |
|---|
| Scope | Specific tasks or domains | Broad range of intellectual tasks |
| Adaptability | Limited to its designed capabilities | Expected to adapt across domains |
| Knowledge transfer | Usually constrained | Expected to transfer skills and knowledge |
| Status | Widely deployed today | Not yet established as a demonstrated general system |
For example, a chess-playing AI can become exceptionally good at chess but does not automatically know how to diagnose a machine fault or write a business plan. An AGI, by definition, would aim to handle many such different tasks using general-purpose reasoning and learning.
In simple terms, narrow AI is specialized intelligence for particular tasks, while AGI refers to a still-hypothetical form of broadly capable, general-purpose intelligence.
