Artificial General Intelligence (AGI)

Artificial General Intelligence is a system that matches or exceeds human-level performance across any intellectual task, not just one job. Narrow AI is strong at bounded tasks like chess or identifying images. AGI would learn, reason, and apply knowledge across domains without a new training run for each field.

It could move between physics, art, and engineering with the same kind of flexibility people have. Today's large language models are still narrow AI. They are strong at text generation, analysis, and reasoning inside text, but they cannot inherently understand physics equations or compose symphonies without explicit training. AGI would remove those walls.

It would reuse patterns across fields instead of starting from zero. Most AI researchers still think AGI is years away. Better scaling, architectures, and training methods close the gap a little at a time. The hard problem is whether we can make its goals compatible with human values before a system at that level exists.

OpenAI's charter defines AGI as systems that outperform humans at most economically valuable work. That is a company definition, not a scientific test that has been passed.