All fundamental unsolved problems of AGI are concentrated in two elements of the scheme: 'Concept Formation' and 'Pattern Learning'.
For both, 'neuro-components' involvement in the design does not promise anything new. The search for patterns (and, in particular, the search for cause-and-effect relationships), essentially a combinatorial task, requires the generation of hypotheses with their subsequent testing. Finding a niche here for the useful use of a neural network is at least difficult.
In the task of forming concepts, neural networks can be used as a detector of those predetermined primitive basic features of the observed reality - but this is quite feasible in other ("classical") ways.
All fundamental unsolved problems of AGI are concentrated in two elements of the scheme: 'Concept Formation' and 'Pattern Learning'.
For both, 'neuro-components' involvement in the design does not promise anything new. The search for patterns (and, in particular, the search for cause-and-effect relationships), essentially a combinatorial task, requires the generation of hypotheses with their subsequent testing. Finding a niche here for the useful use of a neural network is at least difficult.
In the task of forming concepts, neural networks can be used as a detector of those predetermined primitive basic features of the observed reality - but this is quite feasible in other ("classical") ways.