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SoftBank Looking to Bring AI to Shared IoT Services

The sharing economy is something of a disruptive trend that’s reshaping the way people purchase goods and services—with access to bike sharing, ride hailing apps and shared vehicle services like Zipcar, owning a vehicle isn’t really necessary or, depending on a number of variables, the best economic option. From bikes, cars and office spaces, SoftBank has invested in a number of shared service firms, and now the Japanese conglomerate is using artificial intelligence (AI) to enhance its shared services.

SoftBank is working with Tupl to use data analysis of shared service usage “to predict demand as well as revenue generation for sharing services all within an accessible user interface.”

For ride-sharing, SoftBank is financially backing both Uber and Didi Chuxing, a Chinese ride-sharing company. For bicycles, SoftBank has invested more than $1 billion in Chinese firm Ofo. And the company is invested in WeWork, which essentially provides commercial office space as a service. Ancillary to its investments in ride-sharing, SoftBank has also put money into the development of autonomous driving with a two-part, $2.25 billion boost to GM subsidiary Cruise.

According to Tupl, Softbank will use the TuplOS, an AI engine, to develop a proof of concept based on analysis of SoftBank shared services data. Tupl CEO Petri Hautakangas said the combination of the AI engine and SoftBank’s IoT platform will help the company better address the “potentially significant market segment within the sharing economy.”

Earlier this year SoftBank partnered with Israeli firm Vayyar Imaging to collaborateon IoT proof of concept projects. Major applications for Vayyar’s products include the detection of displacement and degradation in structures, analyzing people flow, identifying human postures and seeing through solid objects. By combining Vayyar’s products with SoftBank’s IoT platform, AI and big data capabilities, both companies believe they can provide IoT solutions that are not possible with conventional technologies. – Enterprise IoT Insights

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