The biggest problem with neural networks is that they are not that accurate, mostly because they have a relatively slow learning curve. And the problem isn't just with accuracy, but also with efficiency. Neural networks can be extremely slow to operate, because many times they rely on feedback from previous computations to the next one. A simple way to solve this will be taking out one of the many layers of the network to avoid such feedback, but this might actually damage the accuracy of the network. Another solution could be to use parallel computers, which can be used to divide the workload and eliminate problems of speed.