Part 4/16:

Thoren underscores the importance of causal understanding, noting that most regularities in the world stem from causal relations—though he acknowledges the philosophical debate on whether causality is fundamental or if the universe is purely statistical. Practical AI systems, he states, should model these causal relations to generalize effectively and make informed predictions or diagnostics.

Reasoning, Generalization, and Analogy

He emphasizes that reasoning involves multiple processes—prediction, cause inference (abduction), generalization, and analogy—that must operate systematically for true intelligence. These processes enable the system to model rule-based systems, zoom into details or zoom out to broader perspectives, and extract signals amidst noise.