Nature International Weekly Journal of Science, 10/5/2016
Scientists attempt to understand how computers think and learn in order to verify the reliability of large scale data analysis. This article covers several efforts in the last few years to understand how deep neural nets work. If scientists can understand how computers gather and interpret data in deep learning, these techniques can be used with more confidence, in day to day applications as well as in cutting edge scientific research.
[See the full post at: Can We Open the Black Box of AI?]