Machine Learning on Mobile and Edge Devices with TensorFlow Lite: Daniel Situnayake at QCon SF

At QCon SF, Daniel Situnayake presented "Machine learning on mobile and edge devices with TensorFlow Lite". TensorFlow Lite is a production-ready, cross-platform framework for deploying ML on mobile devices and embedded systems, and was the main topic of the presentation. The key takeaways from it included understanding and getting started with TensorFlow Lite, and on-device machine learning on various devices – specifically microcontrollers and optimizing the performance of machine learning models. Situnayake, developer advocate for TensorFlow Lite at Google, began the presentation by explaining what machine learning is. Traditionally a developer feeds rules and data into an application and output answers, while with machine learning the developer or data scientists' feeds in the answers and data and the output are rules, which can be applied in the future.