Future Of Machine Learning On Smartphones

Today, any typical modern-day smartphone is able to scan faces, documents, QR codes, capture super-resolution photos, recognise gestures, voice and perform multiple other tasks besides answering calls and texts. These handheld devices are the epitome of software and hardware engineering; and to do these tasks, they require state-of-the-art image recognition and NLP models running in the background. Image and language models are at the heart of many machine learning applications today and training these models is a computational nightmare with increasing data. Google has been using TensorFlow Lite for taking pictures on its flagship model Pixel. For Portrait mode on Pixel 3, Tensorflow Lite GPU inference accelerates the foreground-background segmentation model by over 4x and the new depth estimation model by over 10x vs CPU inference with floating-point precision.