One example he cited is a manufacturing firm which is improving the yield and quality of its products, processing data on the millions of variables that can influence these factors.
"Using this deep learning technique to identify the opportunities for improving their manufacturing processes is absolutely huge," he explained, adding that using traditional 'brute force' computation would not be suitable.
Fraud detection, demand prediction and failure predictions are other clear areas for the technology, as they are not customer-facing.
"Granting a credit or not, or the particular procedure you use as a doctor is very consumer facing," he said, adding that "for internal improvement, you are probably okay in most cases."
"So pick your applications carefully."