Research work · 2025
Understanding Artificial General Intelligence: Defining Characteristics and Benchmarks
Journal of Artificial Intelligence & Control Systems
Abstract
Artificial General Intelligence (AGI) is an advanced form of Artificial Intelligence (AI) that aims to perform any intellectual task that a human can, surpassing the narrow scope of Artificial Narrow Intelligence (ANI). Unlike ANI, which is designed to handle specific, well-defined tasks, AGI has the potential to generalize knowledge and adapt across a variety of domains. This research examines AGI's learning and adaptability, common-sense thinking, autonomous decision-making, transfer learning, creativity, and problem-solving. It examines AGI history using cognitive science, neuroscience, machine learning, and other disciplines. This topic requires trustworthy criteria to measure AGI research progress. This research paper serves as a review of AGI, summarizing its defining traits, challenges, and evaluation benchmarks. It also surveys key recent advancements in AGI systems, integrating perspectives from cognitive science, machine learning, and neuroscience. Evaluation methods such as the Turing Test, Winograd Schema Challenge, Coffee Test, and Lovelace 2.0 Test are assessed for their relevance to AGI.