On the Emergence of Autonomous Systems towards Deep Thinking Machines and General AI Driven by Abstract Intelligence Theories and Intelligent Mathematics

Thinking and inference are key essences of human intelligence as René Descartes stated that "I think therefore I am (1637)." The ultimate goal of General AI (GAI) [1], [2], [3], [4] is to enable machine thinking and inference [5], [6], [7], [8], [9] beyond data-based learning [10], [11] towards run-time intelligence generation [9], [12] driven by Autonomous Systems (AS) [13], [14] and cognitive robots [15]. Basic research on machine thinking is powered by Abstract Intelligence theories [16], [17], [18], [19], [20], [21] and Intelligent Mathematics (IM) [22], [23], [24], [25], [26], [27], [28], [29], [30], [31], [32] towards enabling symbiotic and collective intelligence [13], [33] and cognitive systems [34], [35], [36], [37], [38], [39].This keynote lecture presents theoretical foundations of and latest advances in machine thinking and inference driven by AS, GAI, and cognitive robots. Latest breakthroughs in IMs and run-time behavior generation by cognitive systems and AS are elaborated. Emerging paradigms of machine thinking autonomies are introduced to demonstrate the next generation of general AI and symbiotic intelligent systems. The advances in AS are expected to lead to a wide range of novel applications in deep machine thinking, machine knowledge learning, cognitive robots, inference computers, brain-inspired systems, and mission-critical intelligent systems.