Google's TensorFlow Lite Model Maker adapts state-of-the-art models for on-device AI

Google today announced TensorFlow Lite Model Maker, a tool that adapts state-of-the-art machine learning models to custom data sets using a technique known as transfer learning. It wraps machine learning concepts with an API that enables developers to train models in Google's TensorFlow AI framework with only a few lines of code, and to deploy those models for on-device AI applications. Tools like Model Maker could help companies incorporate AI into their workflows faster than before. According to a study conducted by Algorithmia, 50% of organizations spend between 8 and 90 days deploying a single machine learning model, with most blaming the duration on a failure to scale. Model Maker, which currently only supports image and text classification use cases, works with many of the models in TensorFlow Hub, Google's library for reusable machine learning modules.