Baidu Inc, a Chinese technology company, has recently announced plans to develop an EV company and partner with Zhejiang Geely Holding Group, a car manufacturer. The technology company has been focusing on launching smart electric vehicles to contribute to the rapidly evolving sector.
Over the past years, Baidu has been developing internet connectivity infrastructure and autonomous driving technology. The company is expected to reach this target by leveraging its intelligent driving capabilities and the car manufacturing expertise of Geely. Following the deal, Geely will serve as a strategic investor in the new smart EV company, which will function as Baidu’s independent subsidiary.
Sources familiar with the matter have cited that Baidu is likely to hold an absolute voting power and majority stake, with Geely to hold a minority stake in the new firm. The collaboration is also reportedly based on SEA (Sustainable Experience Architecture), an EV-focused platform of Geely.
The recent move comes amid the robust focus of the global tech companies to develop smart cars, following the success of Tesla in commercializing EVs. For example, Apple is targeting to unveil an EV, as well as batteries by 2024. In addition, Alibaba also has inked an EV joint venture deal with SAIC Motor Corp.
In 2017, Baidu established Apollo, an autonomous driving unit that mainly supplies AI-powered technology. The unit functions in collaboration with automakers such as Ford Motor Co, Toyota Motor Corp, Volkswagen AG, and Geely.
Baidu operates Go Robotaxi, an autonomous taxi service with safety drivers in Cangzhou, Changsha, and Beijing. The company plans to expand this service to 30 cities in 3 years to eventually commercialize its autonomous driving technologies. It has also gained the approval to test 5 cars without safety drivers in Beijing.
People with knowledge of the matter have reported that Baidu’s smart car manufacturing plan will strengthen software-defined vehicles. Despite this, the success of its smart EV business will depend on factors such as user demand, low equipment cost, and government policies.
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