I haven't read the article but wanted to comment on specifically for your question. As a person working on neuromorphic computing, I would like to make somethin

I haven't read the article but wanted to comment on specifically for your question. As a person working on neuromorphic computing, I would like to make something clear: Most of frontier neuromorphic research of today, neither focus on creating an "general artificial intelligence" by copying human brain nor think that neuromorphic computing is the most probable discipline to achieve it. Instead, optimizing hardware for neural networks is the focus. If we want to achieve high number of (>10^14) weights, low energy consumption and spatial shrinkage we would like to give up running 1000 GPU clusters which only a handful of companies have. Neuromorphic computing only suggests that we need a better hardware (which may or may not require working with spiking neural nets as a consequence) in order to make AI hardware scalable, nothing more.