— Ch. 1 · Defining Artificial General Intelligence —
Artificial general intelligence.
~7 min read · Ch. 1 of 7
Artificial general intelligence is a hypothetical type of artificial intelligence that would match or surpass human capabilities across virtually all cognitive tasks. Unlike narrow AI systems confined to well-defined tasks, an AGI system can generalize knowledge and transfer skills between domains without task-specific reprogramming. The concept does not require the system to be an autonomous agent; a static model like a highly capable large language model could satisfy the definition so long as human-level breadth and proficiency are achieved. Some academic sources reserve the term strong AI for computer programs that will experience sentience or consciousness. In contrast, weak AI can solve one specific problem but lacks general cognitive abilities. A framework for classifying AGI was proposed in 2023 by Google DeepMind researchers who define five performance levels: emerging, competent, expert, virtuoso, and superhuman. They consider large language models like ChatGPT or LLaMA 2 to be instances of emerging AGI comparable to unskilled humans.
Historical Development And Cycles
Modern AI research began in the mid-1950s when the first generation of researchers were convinced that artificial general intelligence was possible within just a few decades. AI pioneer Herbert A. Simon wrote in 1965 that machines would be capable of doing any work a man could do within twenty years. Their predictions inspired Stanley Kubrick and Arthur C. Clarke's fictional character HAL 9000 who embodied what AI researchers believed they could create by the year 2001. Marvin Minsky served as a consultant on the project making HAL 9000 as realistic as possible according to the consensus predictions of the time. He said in 1967 that within a generation the problem of creating artificial intelligence would substantially be solved. However in the early 1970s it became obvious that researchers had grossly underestimated the difficulty of the project. Funding agencies became skeptical and put researchers under increasing pressure to produce useful applied AI. In the early 1980s Japan's Fifth Generation Computer Project revived interest in AGI setting out a ten-year timeline that included goals like carrying on a casual conversation. Confidence in AI spectacularly collapsed in the late 1980s and the goals of the Fifth Generation Computer Project were never fulfilled.