Comment by captainbland

I think after you factor it in being on the extreme end of slow but wide (like laptop GPUs) and being a native representation of the neural network rather than a computed silicon approximation, and being more similar to a recurrent/continuous learning model rather than a huge all at once back prop, are there more tricks required?

My thought is you could probably set up something similar with today's technological capabilities but it would probably take decades to train and be expensive to develop which is commercially unacceptable.