AI Abstract Series E11 – Omega: An Architecture for AI Unification

Welcome to the Technocracy A.I. Abstract Series for Published Scientific Work in the A.I. and Artificial General Intelligence field.

Todays paper is titled: Omega: An Architecture for AI Unification.

Authored By Eray Özkural.

Abstract: We introduce the open-ended, modular, self-improving Omega AI unification architecture which is a refinement of Solomonoff’s Alpha architecture, as considered from first principles. The architecture embodies several crucial principles of general intelligence including diversity of representations, diversity of data types, integrated memory, modularity, and higher-order cognition. We retain the basic design of a fundamental algorithmic substrate called an “AI kernel” for problem solving and basic cognitive functions like memory, and a larger, modular architecture that re-uses the kernel in many ways. Omega includes eight representation languages and six classes of neural networks, which are briefly introduced. The architecture is intended to initially address data science automation, hence it includes many problem solving methods for statistical tasks. We review the broad software architecture, higher-order cognition, self-improvement, modular neural architectures, intelligent agents, the process and memory hierarchy, hardware abstraction, peer-to-peer computing, and data abstraction facility.

As always thank you for listening to the Technocracy Abstract Series and a special thank you for our sponsors the Foundation, and the AGI Laboratory.


Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.