Surface Problems in Information Science Keynote Address

Artificial intelligence (AI) and big data processing are extensively developed in recent information technologies. Deep learning in AI has been tried to apply to robotics, social activities and home appliances. Also, big data processing has been used in the networks and social services. There were fundamental problems in these recent technologies in AI and big data processing. One of these was “surface problems” in information technologies. The word “surface problem” is well known in physics, material sciences, and nanosciences as in the surface phenomena of the semiconductor, metals and crystal structures. As the surface problem in the information science, threshold element of neuron model is discussed, which are also fundamental elements used in deep learning neural networks. The surface is characterized by the surface extreme data, which discriminate classes of data. Threshold logic of their elements with much variables has not fully solved yet. We mention how to deal with such problem with much variables using surface data. As another problem of the surface problem, we have the reduction of higher dimensional data used in the big data processing. As the reduction method, reducts in the rough set are well known in the data processing. We mention how to generate reducts using the surface border data among classes.