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We at NTT laboratories are focusing on the research and development of zero-touch operations using artificial intelligence (AI) for early recovery from network failures, which requires learning a large amount of network failure data. We have established a framework that allows AI to learn autonomously by artificially generating a large amount of network failures in a simulated environment and learning how to respond to them. This article describes the concept of this framework and how AI learns in the framework. [ABSTRACT FROM AUTHOR]

We are studying the use of digital twins to optimize traffic flow so that traffic congestion will not occur. To reproduce current real-world traffic flow and predict future traffic flow using digital twins requires traffic-demand data with fine granularity in time and space. Due to recent increasing activity to create smart cities, we can now obtain cross-sectional traffic-volume data for short time intervals of five minutes, but such measurements are still only being taken at a relatively small number of locations, so spatial granularity is large. In this article, we introduce our OD (origin-destination)-estimation technology that uses cross-sectional traffic volume on arterial roads to interpolate such fragmented cross-sectional traffic data to generate realistic traffic-demand data. [ABSTRACT FROM AUTHOR]

This article introduces the following four technologies we are developing that apply neuroscience for creating a world in which people with different sensibilities can understand and respect one another: (i) technology for decoding the sense of discomfort or satisfaction from electroencephalogram data, (ii) technology for making brain states containing sensory information perceptible as representations in the brain, (iii) neural-coupling technology for enhancing mutual understanding, and (iv) mental-imagereconstruction technology for reproducing the images in the mind. [ABSTRACT FROM AUTHOR]

NTT is researching digital twin technology that reproduces not only the outer states, such as appearance, voice, and movement, but also the inner states, such as values and thoughts, of humans. To actualize a future in which human digital twin technology contributes to the well-being of people and society, it is necessary to examine the ideal path of technology evolution from a broad interdisciplinary perspective. This article introduces research activities to pursue well-being as the Grand Challenges of Digital Twin Computing, i.e., Another Me and Mind-to-Mind Communication. [ABSTRACT FROM AUTHOR]