From Data-Aggregative Learning to Cognitive Knowledge Learning

Explore a groundbreaking keynote lecture on Autonomous Machine Learning (AML) and the HMML framework, delivered by Dr. Yingxu Wang from the University of Calgary. Delve into the fundamental AI theory that proposes binary relations as the basic unit of knowledge for AML, challenging traditional data-aggregation neural network technologies. Discover why high-level intelligence, including inductive knowledge acquisition, causal reasoning, and robust decision-making, is cognitively independent from data magnitude. Learn about the emerging AML technology for knowledge acquisition and its potential to revolutionize AI systems beyond current data-driven approaches. Gain insights from Dr. Wang, a distinguished professor of cognitive systems, brain science, software science, and intelligent mathematics, whose extensive research spans multiple scientific disciplines and has earned him recognition as a top scholar in various fields of artificial intelligence and cognitive computing.