Larger datasets require more extensive training time to reach a predictive solution, and there is the possibility of overtraining, in which there was low training error but high actual testing error. Unknown data necessary for the solution will also cause a high error rate, sometimes by affecting the weighted values used in determining a solution.
Simple systems which have learned to recognize simple entities (e.g. walls looming, or simple commands like Go, or Stop) may have neural network chips implanted to help in decision-making. Japanese are already using fuzzy logic for this purpose.
Use of neural networks to put labels on what is determined to be in the pictures, for use in medical searches
User-specific systems for education and entertainment based on readings taken of the user.