Project AirSim is a new platform running on Microsoft Azure to safely build, train and test autonomous aircraft through high-fidelity simulation.
Project AirSim uses the power of Azure to generate massive amounts of data for training AI models on exactly which actions to take at each phase of flight, from takeoff to cruising to landing. It will also offer libraries of simulated 3D environments representing diverse urban and rural landscapes as well as a suite of sophisticated pretrained AI models to help accelerate autonomy in aerial infrastructure inspection, last-mile delivery and urban air mobility.
It arrives as advances in AI, computing and sensor technology are beginning to transform how we move people and goods, said Gurdeep Pall, Microsoft corporate vice president for Business Incubations in Technology & Research. And this isn’t just happening in remote areas home to wind farms; with urban density on the rise, gridlocked roads and highways simply can’t cut it as the quickest way to get from Point A to Point B. Instead, businesses will look to the skies and autonomous aircraft.
High-fidelity simulation was at the heart of AirSim, an earlier open-source project from Microsoft Research that is being retired but inspired today’s launch. AirSim was a popular research tool, but it required deep expertise in coding and machine learning.
Now, Microsoft has transformed that open-source tool into an end-to-end platform that allows Advanced Aerial Mobility (AAM) customers to more easily test and train AI-powered aircraft in simulated 3D environments.
“Everyone talks about AI, but very few companies are capable of building it at scale,” said Balinder Malhi, engineering lead for Project AirSim. “We created Project AirSim with the key capabilities we believe will help democratize and accelerate aerial autonomy – namely, the ability to accurately simulate the real world, capture and process massive amounts of data and encode autonomy without the need for deep expertise in AI.”
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