Microsoft and Grab come together for on-demand AI Services

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Grab and Microsoft
Grab and Microsoft are on- board for something exciting.

 Microsoft signed off a contract with Singapore ride-hailing company ‘Grab’ to access the on-demand AI and Big data services.

Microsoft is known for collaborating with organizations from a multitude of niches. This time Microsoft’s strategic management chose a transportation company to achieve its goal. Recently, Microsoft has signed a contract with the famous riding company of Singapore, known as Grab to access on-demand AI and Big data services. The news proved to be of sheer joy for Singaporean riders as they can now get secure, hassle-free rides to anywhere in Singapore.

According to the agreement, Grab is going to implement Microsoft Azure for cloud computing services. Grab also wanted to use Microsoft’s cloud computing service to digitize their transportation services along with food and payment delivery services.

Peggy Johnson, executive vice president at Microsoft, said in a statement:

“Our partnership with Grab opens up new opportunities to innovate in both a rapidly evolving industry and growth region”

Both companies showed an inclination to work on deep innovative technology projects in the future. The companies have decided to implement facial recognition to identify registered drivers and riders.

Both companies consented on proceeding with the natural language processing, machine learning and AI on Grab’s platform to build maps and detect frauds. Also, the companies plan to provide address translation facility at passenger’s end.

Grab and Microsoft has decided to make their end-to-end support via Toyota.

Toyota has already made an investment of $1 billion dollars in Grab and is working with Microsoft too. In 2017, Toyota signed off a contract with Microsoft to launch Internet-connected cars. To achieve this Milestone, Toyota utilized Microsoft Azure to access data for the development of more precise software products for drivers.

No doubt, it is a great initiative in the transportation services industry. But to deal with data as big as this is a bit challenging.

Stay tuned for more!

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