Project eve announcement12/31/2023 This library would be able to pull up specific locations, like New York City or London, or generic spaces, like an airport. Using data from Bing Maps and other providers, Microsoft is curating a ready-to-use library of simulated 3D environments of both urban and rural landscapes under Project AirSim. Read: Tiny planes, big planes – Wing unveils new drones for different delivery markets Project AirSim is a critical tool that lets us bridge the world of bits and the world of atoms, and it shows the power of the industrial metaverse – the virtual worlds where businesses will build, test, and hone solutions and then bring them into the real world. But first, we must safely train these systems in a realistic, virtualized world. Gurdeep Pall, Microsoft’s corporate VP for business incubations in technology and research, explained:Īutonomous systems will transform many industries and enable many aerial scenarios, from the last-mile delivery of goods in congested cities to the inspection of downed power lines from 1,000 miles away. How would the drone fly in rain, sleet, or snow? How would strong winds or high temperatures affect battery life? Can the drone’s camera see a turbine’s arms on an overcast day just as well as on a clear one? Using Project AirSim’s high-fidelity simulations, drone AI models can run through millions of flights in seconds, learning how to react to countless variables much as they would in the physical world: Massive amounts of data are required for training drone AI models on exactly which actions to take at each phase of flight, right from takeoff to cruising and landing. Read: Skydio’s secret sauce for making drones smarter, faster is now public While the earlier open-source research project is being retired, Microsoft said learnings from the same have inspired the launch of this new end-to-end platform that would allow AAM customers to test and train AI-powered aircraft in simulated 3D environments more easily. Project AirSim is a result of five years of research and experimentation into deep learning and AI.
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