Artificial General Intelligence: Definition and Examples

Artificial General Intelligence, or general artificial intelligence, represents the theoretical stage where a machine would be capable of understanding, learning, and applying its knowledge to any intellectual domain, exactly as a human would. Unlike current so-called "narrow AI" systems, which excel at specific tasks like translation or image recognition, an AGI could transfer its skills from one domain to another without reprogramming.

The concept of AGI is at the heart of debates in the scientific and technological community. Some researchers believe that current large language models (LLMs) represent significant steps toward AGI, while others argue that fundamental abilities like deep causal reasoning, self-awareness, or true understanding of the physical world are still lacking. The boundary between advanced AI and AGI remains blurry and is subject to competing definitions.

In prompt engineering, understanding the distinction between current AI and AGI is essential for calibrating expectations. Today's language models simulate certain aspects of general intelligence—reasoning, creativity, analysis—but remain fundamentally statistical systems trained on data. Knowing how to leverage their strengths while circumventing their limitations is precisely the art of prompt engineering.

The societal implications of a potential AGI are considerable: ethical questions about machine autonomy, impact on employment, safety and alignment issues (ensuring AGI acts according to human values). These reflections currently fuel AI regulation policies worldwide.