How to train AI models with synthetic data

But while there are quite a few tools out there to create virtual environments, there aren’t a lot of tools for creating virtual objects. It takes massive amounts of data to train AI models. But sometimes, that data simply isn’t available from real-world sources, so data scientists use synthetic data to make up for that. At its re:Mars conference, Amazon today announced synthetics in Sagemaker Ground Truth, a new feature for creating a virtually unlimited number of images of a given object in different positions and under different lighting conditions, as well as different proportions and other variations. In machine vision applications, that means creating different environments and objects to train robots or self-driving cars, for example. “What Ground Truth Synthetics does is you start with the 3D model in a number of different formats that you can pull it in and it’ll synthetically generate photorealistic images that match the resolution of the sensors you have,” he explained. With WorldForge, the company already offers a tool to create synthetic scenes. Vass noted that Amazon is also partnering with 3D artists to help companies that may not have access to that kind of in-house talent to get started with this service, which uses the Unreal Engine by default, though it also supports Unity and the open source Open 3D Engine. (TechCrunch). Continue reading.



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