Conscious AI at the Edge of Chaos

Abstract

The main problem for AI consciousness is to operate within the right kind of AI. We distinguish between the traditional computing (GOFAI), and the computing based on stochastic pattern optimization. The latter will be called here computing at the edge of chaos. Optimization of learning patterns, which is the gist of its success, often happens between the areas of too much repetitive order and those of hard to predict and control stochastic processes. This is to change the focus from the opposition of symbolic versus sub-symbolic computing; symbols can appear at different granularities and the hedge between The Physical Symbol System Hypothesis and neural nets seems no longer the most productive cut to make. Computing at the edge of chaos is promising for AGI, especially for AGI consciousness. The second problem for AI consciousness is to work with the right definitions of consciousness.