Microsoft is teaming with London-based Wayve for a collaboration that will see the company invest in the development of deep learning technologies for autonomous vehicles (AVs). In return, Wayve will use Microsoft Azure across its services.
By partnering with Microsoft, Wayve will use Microsoft cloud technologies to propel its supercomputing that powers its AI models. Microsoft is investing as part of Wayve's $200 million Series B round. However, the companies have been working together since 2020 when Wayve first selected Azure as its preferred cloud platform.
Now, the companies plan to leverage Wayve's AI expertise and deep learning models to train Microsoft's AI. As for Azure, it will provide Microsoft's resources and engineering experience across large-scale projects.
Mark Russinovich, CTO, Azure at Microsoft said: “Supercomputing capabilities are key to processing the immense amount of data required for the simulation, validation, and training of AI models that enable safe and secure autonomous driving. Wayve is combining its expertise in deep learning-based autonomous vehicle systems with Microsoft Azure computing power to bring self-driving transportation experiences to more people and organizations faster.”
Wayve is going to commercialize its product at some point. The company says it will continue to use Azure as its chosen cloud platform. During commercial piloting of its technology, supercomputers will take the deep learning models necessary for commercialization to the next level.
Microsoft Azure will underpin the cloud infrastructure needed to power these supercomputers.
Alex Kendall, CEO of Wayve said: “Joining forces with Microsoft to design the supercomputing infrastructure needed to accelerate deep learning for autonomous mobility is an opportunity that we are honoured to lead. Deep learning systems thrive on data, and we've put an immense amount of effort into understanding what it takes to get these systems on the road. We are excited by the opportunities that this collaboration will create as we push deep learning to new levels of scale.”
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