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Microsoft joins Baidu’s “Android for autonomous driving”
Shortly after revealing a partnership with Baidu’s Apollo Project, Microsoft announced Tuesday further details of the tie-up. The US internet behemoth will provide cloud infrastructure services via Azure to Apollo’s partners outside of China.
As part of the partnership, Baidu and Microsoft plan to explore opportunities to deliver connected vehicle solutions and unique customer experiences that aim to digitally transform the autonomous driving industry, according to the statement.
“We’re excited to partner with Baidu to take a giant step in helping automotive manufacturers and suppliers fully realize the promise of autonomous driving,” said Kevin Dallas, corporate vice president, Microsoft. “Today’s vehicles already have an impressive level of sophistication when it comes to their ability to capture data. By applying our global cloud AI, machine learning, and deep neural network capabilities to that data, we can accelerate the work already being done to make autonomous vehicles safer.”
As of July, Baidu has forged partnerships with approximately 50 companies composed of mapping company TomTom, IT firms like Microsoft, Nvidia, tier-one suppliers Bosch and Continental, auto manufacturers like Chery and BAIC Motor, and Uber competitor Grab.
Processing power is a crucial factor for crunching the huge amount of data produced by Apollo system. While Baidu can ensure that power within China, it would be a problem when operating in countries where it doesn’t have much presence, therefore, could be a speed bump for the global adoption of this system.
If Apollo is to become “Android for autonomous cars” in a real sense, stable processing power around the globe is a must, especially when competing with rivals like Alphabet’s Waymo.
On the other hand, Microsoft has already been dipping their toes into the automotive industry through partnerships with BMW, Ford, Renault-Nissan, Toyota and Volvo in a bid to ingest huge volumes of sensor and usage data from connected vehicles and apply that data to deliver actionable intelligence.