Pinaki Laskar on LinkedIn: #machinelearning #artificialintelligence #CausalAI

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 It is a common knowledge that current ML technology fails when applied to dynamic, complex systems. It produces static models that overfit to yesterday's world. The models are data-hungry and unintelligible to humans, as listed below, Static models Historic correlations Black box Observational data only Predictions only And Causal AI comes with the competitive features, Dynamic models Causal drivers Explainable Understands business context Predictions, interventions & counterfactuals Causal AI is a new category of intelligent machines that understand cause and effect ― a major step towards true AI. It is widely recognized that Understanding Causality Is the Next Challenge for Machine Learning. Deep neural nets do not interpret cause-and effect, or why the associations and correlations exist.