Marina Rose Geldard, more commonly known as Mars, is a AI researcher from Down Under in Tasmania. Entering the world of technology relatively late as a mature-age student, she has found her place in the world: an industry where she can apply her lifelong love of mathematics and optimization. When she is not busy, she compulsively volunteers at industry events, dabbles in research, and serves on the executive committee for her state’s branch of the Australian Computer Society (ACS) as well as the AUC, where she helps run Australia’s longest-running Apple developer conference, /dev/world. She’s currently writing “Practical AI with Swift” for O’Reilly Media, and working on machine-learning and AI research projects for the University of Tasmania.
On-device Neural Style Transfer
Neural Style Transfer (NST) is a great machine learning technique for applying the style of one image to a separate, entirely different image. Using NST you can make pictures of your cat look like Van Gogh's 'The Starry Night', or snaps of your dinner look like da Vinci's 'Mona Lisa'.
This session demonstrates how easy it is to perform previously complex machine learning tasks, like NST, locally on an iOS device using CoreML. The future of personal machine learning features might be privacy-centric, on-device machine learning. There's no need to outsource your ML-features to the cloud.
In a world of increasing awareness of the value of privacy and security, on-device ML-features are an important component in any AI experts toolkit. We'll explain how they work, what they can be used for, and demonstrate their power. Come and learn just how powerful a portable device can be.