Started efforts to provide AI cloud to improve productivity in manufacturing industry

SoftBank Technology Corp. (Headquarters: Shinjuku-ku, Tokyo, Representative Director: Shinichi Ata, hereinafter referred to as SBT) and artificial intelligence venture Cross Compass Co., Ltd. (Headquarters: Chiyoda-ku, Tokyo, Representative Director: Satoshi Sato, hereinafter referred to as Cross) Compass) has recently announced that it will use the deep learning provided by Cross Compass to easily generate artificial intelligence (AI) for the manufacturing industry using Manufacturing-IX (M-IX), which will be used on Microsoft Azure. We are pleased to announce that we have started a joint effort to provide an AI module from.

■Background
Recently, manufacturing industries and IoT device manufacturers are developing concepts to improve productivity by incorporating AI into edge devices that aggregate information from sensors (or provide instructions to devices at the end of the network or exchange data with the cloud). Many demonstration experiments are being conducted to confirm whether the concept can be realized. Specifically, by utilizing cutting-edge technologies such as edge AI and IoT, it is expected that manufacturers will be able to improve the accuracy of abnormality detection and predictive maintenance at their production bases, and IoT device manufacturers will be able to perform maintenance on installed machinery before it breaks down. It has been.

In order to realize such a concept, it is important to have a system that collects information from sensors, accumulates it as big data, and analyzes and learns from it. Utilization of the cloud will also be necessary to deal with changes in the amount of data acquired and the number of IoT devices.

This time, SBT which specializes in cloud development and operations such as the use of Microsoft Azure, and Cross Compass, which provides M-IX, a development environment that can easily generate AI for the manufacturing industry, will provide AI modules from the cloud by the end of 2018. We will start working towards this goal. By providing M-IX from Microsoft Azure, we plan to reduce implementation costs and enable deep learning of sensor data across locations.

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