Copyright Bloomberg
In the three years since ChatGPT’s release, tech companies in the US and China have invested hundreds of billions of dollars in data centers, chips and talent to outdo each other in building more sophisticated artificial intelligence models. Increasingly, the stated goal is not just better AI, but a more powerful technology often referred to as AGI. Once regarded as a fringe idea, AGI, or artificial general intelligence, has become a rallying cry for leading AI labs. It guides research roadmaps, marketing materials and policy debates, with some US lawmakers and AI leaders worrying about the national security implications if other countries (for which read China) reach the milestone first. But for all the fuss, the matter of what AGI even is remains riddled with confusion. Academics and tech industry executives disagree on how to define it, including how much to focus on economic value and whether AGI will exceed human capabilities. There’s also disagreement about when it might be achieved and whether it’s even possible to build, at least with AI as currently designed. There’s no single definition of artificial general intelligence. ChatGPT developer OpenAI Inc. defines AGI as systems that outperform humans at most economically useful tasks. A 2023 paper from Google DeepMind focuses less on economic value. It outlines benchmarks that focus on versatility, such as surpassing humans at useful work or learning new skills with scarce data. The ARC Prize Foundation, the nonprofit behind a popular AGI benchmark, goes a step further and says economic value “is an incorrect measure of intelligence.” Instead, the organization offers a different definition: “AGI is a system that can efficiently acquire new skills outside of its training data.”
