Comprehensive Portfolio Propels Qualcomm to Market Leadership in TinyML-Based Machine Vision

Subscribe To Read This Insight

By Lian Jye Su | 4Q 2020 | IN-5988


TinyML-Based Machine Vision Has Large Commercial Potential


Bringing machine learning (ML) to all forms of devices has been the key in enabling distributed intelligence. This vision is shared by many Artificial Intelligence (AI) vendors, including Arm, Qualcomm, and Google. As such, these companies have been championing the development of the Tiny Machine Learning (TinyML) ecosystem. TinyML is broadly defined as an ML technology that enables the performance of data analytics on hardware and software dedicated for low-powered systems, typically in the mW range, using algorithms, networks, and models down to 100 Kilobytes (kB) and below. TinyML applications range from the detection of ambient temperature, vibration, and voltage to identification of images, voice, and video.

Among these applications, TinyML-based machine vision is expected to play key roles both in consumer devices, such as wearables and smart glasses, and enterprise equipment such as security cameras and ambient sensors. Some of the key use cases include facial recognition-based auto-wake and auto-sleep function, gaze tracking for advertising, and occ…

You must be a subscriber to view this ABI Insight.
To find out more about subscribing contact a representative about purchasing options.