Pathways to AGI

A Dual LLM Framework for Multi-Modal Processing, Continuous Adaptation, and Ethical Evolution

Abstract

Artificial General Intelligence (AGI) represents an aspiration to achieve a flexible, human-like intelligence capable of interpreting and reasoning across diverse domains. This paper presents a dual LLM (Language Learning Model) framework designed to approach AGI through continuous learning, multi-modal sensory integration, and collaboration among specialized LLMs. Central to this architecture is the interaction between a primary, real-time processing LLM and a secondary, continuously learning model. Together, they facilitate adaptive knowledge acquisition, managing inputs ranging from sensory streams to scientific literature, building a progressively complex understanding. Future directions explore AGI’s evolution, ensuring scalability, ethical alignment, and efficient resource usage. This research highlights a pathway for responsible AGI development, bridging narrow AI with AGI’s broad cognitive goals.

Introduction

Artificial Intelligence has seen significant developments, yet the pursuit of Artificial General Intelligence (AGI) — a system with human-like adaptability — remains a frontier challenge. Unlike specialized AI systems, AGI demands an architecture…