The AI field has a history of over confidence; just look up Marvin Minsky's predications in the 1950's and 1960's.
This had been repeated throughout AI history - a new approach is found, it has some promising initial results, and then progress gets stuck and the approach is basically halted for decades.
Machine learning and neural networks have prospered due to massive increases in computing speed and data, but I suspect it will also be a dead end in general AI. There will be some niche wins, some quite impressive, but the machine won't have the properties of an intelligent child or even a rat.
There seems to be a big difference in how actual neurons work - I think neural networks are misnamed. The brain is not a big matrix, biology does not appear to reinforce behavior using gradient operations. I think increased research into neuroscience and biomimicry is the most likely approach for general AI, but I think we are still far away and the current hype will just be one more dead end.
Machine learning and neural networks have prospered due to massive increases in computing speed and data, but I suspect it will also be a dead end in general AI. There will be some niche wins, some quite impressive, but the machine won't have the properties of an intelligent child or even a rat.
There seems to be a big difference in how actual neurons work - I think neural networks are misnamed. The brain is not a big matrix, biology does not appear to reinforce behavior using gradient operations. I think increased research into neuroscience and biomimicry is the most likely approach for general AI, but I think we are still far away and the current hype will just be one more dead end.