Artificial intelligence excels at complex tasks but struggles with generalization and adaptation, essential traits of human learning. The Abstraction and Reasoning Corpus (ARC) tests AI's ability to deduce rules and apply them in novel situations. Developed by Francois Chollet, the ARC became an industry standard for assessing AI models. The ARC Prize Foundation now administers multiple tests, including ARC-AGI-3, which evaluates AI agents by having them play video games. These assessments reveal the limitations of current AI, emphasizing the distinction between narrow AI and the goal of achieving artificial general intelligence (AGI).
One test designed to evaluate an AI's ability to generalize is the Abstraction and Reasoning Corpus, or ARC: a collection of tiny, colored-grid puzzles that ask a solver to deduce a hidden rule and then apply it to a new grid.
The ARC Prize Foundation has been routinely using two tests (ARC-AGI-1 and its successor ARC-AGI-2) and is launching ARC-AGI-3, which is specifically designed for testing AI agents with video games.
Collection
[
|
...
]