These libraries use the onboard hardware to accelerate operations such as inference and decision making by trained neural networks. It basically provides the same Python interfaces you'd expected on a Jetson system, specifically the Inference and Utilities API, meaning it's possible to prototype applications in Python and run and test them with the emulator, and once it all works out or you get used to the interfaces, you can perhaps buy a Jetson and run your code on that system, where it will talk to Nvidia's libraries. It's the Jetson AI-Computer Emulator, an open-source project created by machine-learning software engineer Tea Vui Huang. If you’ve been thinking about playing with an Nvidia single-board computer for an AI task, but you’re not quite ready to part with your cash for something like the Jetson Nano just yet, here’s an application-level emulator of the hardware you can tinker with.