Cognitive Singularity Horizons: Predictive Models and Safety in Artificial General Intelligence

Abstract

Cognitive singularity, the threshold at which Artificial General Intelligence (AGI) exceeds human cognitive abilities, represents a paradigm shift in technology and society. This paper analyzes predictive modeling approaches to AGI, including reinforcement learning, neural scaling laws, and emergent intelligence in large language models. The study evaluates methods for ensuring AGI safety, such as value alignment, corrigibility, and containment strategies. Additionally, it examines possible scenarios following singularity, including accelerated innovation, ethical dilemmas, and socio-economic disruptions. By integrating technical, theoretical, and ethical perspectives, the paper outlines a roadmap for preparing society and technology for the eventual realization of cognitive singularity.

KEYWORDS: Cognitive Singularity, Artificial General Intelligence, Predictive Modeling, AGI Safety, Reinforcement Learning