Pinaki Laskar on LinkedIn: #AI #ml #robotics

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner How to Create Causality of Machine Intelligence and Learning? Causation, and its powers and forces, processes and mechanisms, physical and mental, social and technological, is the engine of the world (as the positive and negative gravity, or dark energy, for the oscillating universe). Causal reasoning is the driving force of human mind/intelligence/intellect; for real causal mechanisms defines all the world's knowledge. The two opposing types of theories of causation, The Humean idealist theory (causation as regularities & invariants & patterns) the causal realist theory (causation as causal mechanism, causal processes, causal interactions, and causal laws, providing the mechanisms by which the world changes and machine works and human acts; to understand why something ever changes or events happen, we need to see how they are produced by these mechanisms). The Hume's theory holds that causation is entirely constituted by facts about empirical regularities among observable variables; there is no underlying causal nature, causal power, or causal necessity.