Kristinn R. Thórisson & Eric Nivel. Center for Analysis and Design of Intelligent Agents / School of Computer Science Reykjavik University.
Certain necessary features of general intelligence are more system-wide than others; features such as attention, learning and temporal grounding are transversal in that they seem to affect a significant subset of all mental operation. We argue that such transversal features unavoidably impose fundamental constraints on the kinds of architectures and methodologies required for building artificially intelligent systems. Current component-based software practices fall short for building systems with transversal features: Artificial general intelligence efforts call for new system architectures and new methodologies, where transversal features must be taken into account from the very outset.