About us
tinyML
Tiny machine learning is broadly defined as a fast growing field of machine learning technologies and applications including hardware, algorithms and software capable of performing on-device sensor data analytics at extremely low power, typically in the mW range and below, and hence enabling a variety of always-on use-cases and targeting battery operated devices.
News
Summit 2022 Call for Posters
The tinyML Summit 2022 Technical Program Committee invites contributions from experts from industry, academia, start-ups and government labs to submit abstracts for posters in the areas of tinyML for audio, vision, sensors, hardware and software and tools.
tinyML Vision Challenge – Winners
We are very excited to announce the winners of Eyes on Edge: tinyML Vision Challenge! First we would like to thank the 485 people/teams that participated in our inaugural challenge we held with Hackster.io.
Industry News
Meet TinyML: The Latest Machine Learning Tech Having An Outsize Business Impact
As device sensors proliferate across every company’s value chain – from new product development through inspection, tracking, and delivery – tinyML is surfacing to provide actionable insights, transforming business as we know it. There are sound economic reasons for all this interest and activity. McKinsey researchers predict IoT will have a potential economic impact of US $4-11 trillion by 2025, identifying manufacturing as the largest vertical (US $1.2-3.7 trillion).
Why tinyML is such a big deal
While machine-learning (ML) development activity most visibly focuses on high-power solutions in the cloud or medium-powered solutions at the edge, there is another collection of activity aimed at implementing machine learning on severely resource-constrained systems.
Known as TinyML, it’s both a concept and an organization — and it has acquired significant momentum over the last year or two.
“TinyML deployments are powering a huge growth in ML deployment,…