Journal of Artificial Intelligence, Machine Learning and Soft Computing

Authors: Geeta Gupta, Rohini Rathore

Abstract: Artificial General Intelligence (AGI) represents a leap in AI research, aiming to create machines with cognitive abilities comparable to humans. Unlike narrow AI, which excels in specific tasks, AGI seeks to understand, learn, and apply knowledge across a broad range of domains. This paper explores the evolution of AGI, from early concepts to the current state of research, highlighting key advancements, challenges, and future directions. It discusses interdisciplinary approaches, the importance of scalability and generalization, ethical considerations, and the potential societal impacts of AGI. The paper concludes by emphasizing the need for continued research, ethical frameworks, and collaboration to realize the promise of AGI.

Keywords: Artificial General Intelligence, AGI, machine learning, cognitive architectures, neural-symbolic systems, scalability, transfer learning, ethics, neuromorphic computing