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They may on the right track to say:

"Part of this difficulty comes from the very nature of the human mind, evolved over billions of years as a complex mix of different functions and systems. “The pieces are very disparate; they’re not necessarily built in a compatible way,” Gershenfeld says. “There’s a similar pattern in AI research. There are lots of pieces that work well to solve some particular problem, and people have tried to fit everything into one of these.” Instead, he says, what’s needed are ways to “make systems made up of lots of pieces” that work together like the different elements of the mind. “Instead of searching for silver bullets, we’re looking at a range of models, trying to integrate them and aggregate them,” he says."

It makes sense to create a single intelligent entity by combining different types of technology that works well on specific topic. We have many good techniques that do things better than human being, why try to mimic ourselves in general (the neuron way) rather than utilize a better solution to each problem?




The problem is that all of our successes combined in AI (even including neural networks) don't add up to something even remotely resembling general intelligence. It's not simply a matter of connecting the output of a DSP to the input of an edge detector, etc.




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