The panelists in this video discuss various ways of representing information for cognitive AI systems. They argue that deep learning is not reliable or trustworthy, and discuss the idea of adaptive resonance theory. They also discuss the importance of memory and representation, and how these concepts can be used to build neural architectures that can control movement and decision-making.
The panelists discuss different representational paradigms for cognitive AI. They suggest that consciousness is only possible with the use of certain representational paradigms, and that humans are losing control over the knowledge that is being created by machines. The panelists also discuss the need for new representations for cognitive AI, and present three perspectives on this issue.