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AI and AGI Past Present and Future - Ben Goertzel
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Nothing close to a consensus on the right path to human-level Artificial General Intelligence (AGI)
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Today, Narrow AI Dominates the Artificial Intelligence (AI) Field (in both academia and applications)
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Will narrow-AI Natural language processing (NLP) software ever correctly interpet this paragraph?
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2008 The technological and scientific context leaves us poised for dramatic AGI progress.
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What We Have Now - four preconditions for Artificial General Intelligence (AGI)
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1. What’s a Workable Cognitive Cycle?
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2. Can abstract knowledge representation serve as an adequate foundation for the adaptive creation of context-specific knowledge representations?
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3. Must an AGI wholly learn language, or can linguistic resources, statistical NLP, and Commonsense KB’s help?
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4. What must a world be that AGI can develop in it?
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5. Can Logic Serve a Scalable Fundation for Sensorimotor Learning?
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6. How does neural learning relate to abstract formal models of learning?
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7.Can integrative design allow multiple AI Algorithms to quell each others’ combinatorial explosions
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Integrated Representation - Joscha Bach
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Seven Principles of Synthetic Intelligence - Joscha Bach
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Four Paths to AI - How to Achieve AI? Jonathan Connell
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Four Paths to AI - Final Thoughts from Jonathan Connell
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Real AGI? (Artificial General Intelligence) Wlodzislaw Duch
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Why not all together? Pei Wang
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Panel Discussion Technical Session I: Overview of AGI Research
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Speakers view at The First Conference on Artificial General Intelligence (AGI-08)
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Reasons for Ethical Autonomy [ in Robots]
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LIDA and a Theory of Mind
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Learning from Inconsistencies in an Integrated Cognitive Architecture
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Extending the Soar Cognitive Architecture
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Upcoming Challenges [Extending the Soar Cognitive Architecture]
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Sparse Knowledge
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Computing Plans
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Computational consciousness
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Conclusions for Linguistic Study of Cognitive Constructor
