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Machine learning on embedded hardware is a new field that's only beginning to be used in the developed world, but it has some characteristics that may make it particularly appropriate for developing countries. The hardware and software required to train students, advance research, and build products is much cheaper than the equivalents for Cloud ML, and since the devices don't need reliable network or even mains power connections, they can be deployed almost anywhere. Pete Warden is the Technical Lead of the TensorFlow Micro open source project from Google, and has previously helped projects like Plant Village use on-device deep learning in West Africa. In this talk he'll introduce some of the possibilities that edge compute opens up for the world outside the West, and will be looking to learn from the audience what problems in their domains it might be applicable to.