Achieving AGI within My Lifetime: Some Progress and Some Observations

The development of artificial intelligence (AI) systems has to date taken largely a constructionist approach, with manual programming playing a central role. After half a century of AI research, enormous gaps persist between artificial and natural intelligence. The differences in capabilities are readily apparent on virtually every scale we might want to compare them on, from adaptability to resilience, flexibility to robustness, to applicability. We believe the blame lies with a blind application of various constructionist methodologies building AI systems by hand. Taking a fundamentally different approach based on new constructivist principles we have developed a system that goes well beyond many of the limitations of present AI systems. Our system can automatically acquire complex skills through observation and imitation. Based on new programming principles supporting deep reflection and auto-catalytic principles for maintenance and self-construction of architectural operation, the system is domain-dependent and can be applied to a vast array of problem areas. We have tested the system on a challenging task: Learning a subset of socio-communicative skills by observing humans engaged in a simulated TV interview. This presentation introduces the core methodological ideas, architectural principles, and shows early test scenarios of the system in action.