Evolution of Artificial Intelligence from Traditional to Super Intelligence

Evolution of artificial intelligence from traditional to super intelligence takes the attention of not only the scientific community but also societies. There is a remarkable transformation from narrowly defined, rule-based systems to ever increasingly autonomous and generative machine cognition leading to general and responsible intelligence. The progress of AI is indicating not only from technical aspects but also some philosophical transformation. Traditional knowledge processing systems are leaving their place to data-driven intelligence sustaining deep intelligence and responsibility to some degree. This transformation ensures that early AI methodologies with symbolic reasoning and explicit human knowledge evolving into a more rationalist and human-centered modelling of intelligence. Today, data-driven and generative approaches focus more on deep learning and predictive performance with some degree of transparency and interpretability. This chapter provides a systematic analysis and overview of the evolution of AI paradigms, focusing on shifting respective capabilities from traditional approaches to machine learning, from generative AI to explainable AI, and artificial general intelligence. First, traditional AI and machine learning approaches are discussed, and then the respective AI transformations are summarized. While highlighting paradigm shifts, attention of the reader will also be taken to capacity changes and philosophical shifts experienced. It is intended that this chapter offers a conceptual foundation for future development of artificial intelligence systems in alignment with human intelligence.