How does Artificial General Intelligence (AGI) differ from Narrow AI?

Artificial General Intelligence (AGI) is characterized by its ability to learn, understand, and apply intelligence across a diverse set of tasks, similar to human cognitive abilities. Unlike Narrow AI, which is designed to perform specific tasks or solve particular problems, AGI has the potential to integrate knowledge and skills from various domains, enabling it to solve new and complex problems it has not encountered before.

The defining feature of AGI is its versatility and adaptability. That means, if an AGI system is trained in one context, it can leverage that knowledge and apply it to different fields or situations. This learning competency suggests that AGI could replicate human-like reasoning and adaptability, leading to a more generalized form of intelligence capable of tackling a breadth of tasks beyond its initial programming.

In contrast, Narrow AI, which includes applications like speech recognition or image classification, excels at specific functions but lacks the ability to transfer knowledge or skills between different domains. Therefore, the ability of AGI to learn across a wide range of tasks fundamentally distinguishes it from Narrow AI.