Artificial General Intelligence (AGI) is a theoretical form of AI that can understand, learn, and apply its intelligence to solve any problem that a human being can. Unlike narrow AI, which is designed for specific tasks (e.g., playing chess or identifying images), AGI would possess cognitive abilities that are general and holistic. An AGI system could tackle novel tasks in unfamiliar domains, demonstrating a level of flexibility and adaptability that mirrors human intelligence.
The concept of AGI has its roots in the earliest days of AI research, dating back to the 1950s with pioneers like Alan Turing. However, the term 'Artificial General Intelligence' was popularized in the early 2000s by researchers like Shane Legg and Ben Goertzel to differentiate the goal of creating human-level intelligence from the more common, task-specific 'narrow AI' systems.
The pursuit of AGI is the ultimate objective for many of the world's leading AI research labs, including OpenAI, DeepMind, and Anthropic. The timeline for achieving AGI is a subject of intense debate, with predictions ranging from a few years to many decades. The potential development of AGI has also sparked significant discussions about its societal impact, ethical implications, and the safety protocols required to manage a technology that could surpass human intelligence.