AGI Essentials by Peter, August 22,2002
General intelligence comprises the essential, domain-independent skills necessary for acquiring a wide range of domain-specific knowledge — the ability to learn anything. Achieving this with “artificial general intelligence” (AGI) requires a highly adaptive, general-purpose system that can autonomously acquire an extremely wide range of specific knowledge and skills and can improve its own cognitive ability through self-directed learning. This chapter in the forthcoming book, Real AI: New Approaches to Artificial General Intelligence, describes the requirements and conceptual design of a prototype AGI system.
Towards Incremental Learning: A Critical Review
Incremental learning is the ability of systems to acquire knowledge over time, enabling their adaptation and generalization to novel tasks. It is a critical ability for intelligent, real-world systems, especially when data changes frequently or is limited. This review provides a comprehensive analysis of incremental learning in Large Language Models. It synthesizes the state-of-the-art incremental […]
Concepts is All You Need: A More Direct Path to AGI
Little demonstrable progress has been made toward AGI (Artificial General Intelligence) since the term was coined some 20 years ago. In spite of the fantastic breakthroughs in Statistical AI such as AlphaZero, ChatGPT, and Stable Diffusion none of these projects have, or claim to have, a clear path to AGI. In order to expedite the […]
Why We Don’t Have AGI Yet
The original vision of AI was re-articulated in 2002 via the term ‘Artificial General Intelligence’ or AGI. This vision is to build ‘Thinking Machines’ – computer systems that can learn, reason, and solve problems similar to the way humans do. This is in stark contrast to the ‘Narrow AI’ approach practiced by almost everyone in […]
