Baidu launches a $1.5B autonomous vehicle fund

Pic Reuters

Pic ReutersBEIJING

This should allow Baidu to take the lead over competitors in the self-driving vehicle market.

Online search leader Baidu Inc. unveiled plans for a 10 billion yuan ($1.52 billion) fund to support its Apollo project for autonomous-car development - part of its recent drive to transform into an artificial intelligence (AI) specialist. The company also expanded by investing in AI technology recently, with autonomous vehicles as their next goal.

According to a statement from the firm, newly joined members include Hyundai Motor, ROS, ESD electronics, Neousys Technology, and autonomous driving start-ups such as Momenta and iDriver+ Technologies. The Apollo Fund, as it's called, appears meant to place a particular focus on backing firms that use Baidu's driverless navigation software of the same name.

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Baidu opened the platform to third parties hoping it would quicken its technology development and enable the company to compete with U.S. rivals such as Tesla and Google's Waymo project that have already heavily invested in the area.

Project Apollo now has 70 partners with the source code in the hands of more than 1,300 companies. The company has even signed more than 50 cooperation agreements with Apollo partners on mass production or joint product development plans.

Now Baidu - which is testing autonomous vehicles in both China and the USA - is doubling down with capital via this new fund, which it said will aim to support around 100 companies over the next three years.

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Baidu has announced a huge investment into autonomous driving, launching a $1.5bn investment fund which will enable the firm to compete with big U.S. rivals in the market.

But he said his company remains "neutral" on Baidu's stock as its analysts are "cautious on the core search business, and believe it could take years for the AI-driven business models to evolve". The software offers five new capabilities to the Apollo platform including high definition maps, obstacle perception, planning, cloud stimulation and end-to-end deep learning.

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