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.
Upcoming Events6
tinyML Talks: Unleashing the Power of the New XIAO ESP32S3 Sense: Tackling Anomaly Detection, Image Classification, and Keyword Spotting with TinyML
June 13, 2023
tinyML Talks: Standardized AI Architectures for Secure TinyML
June 20, 2023
tinyML Builds Series: tinyML Builds with Mahesh Chowdhary
June 21, 2023
News
tinyML Awards 2023
We are happy to congratulate these companies on earning Awards for their innovative tinyML products and solutions in the following categories:
tinyML EMEA Innovation Forum 2023 Sponsorship Opportunities
The tinyML EMEA Innovation Forum 2023 will continue the tradition of high-quality state-of-the-art presentations. Find out more about sponsoring and supporting the tinyML Foundation.
tinyML Deployment Working Group – White Paper
The tinyML Foundation Deployment Working Group is pleased to publish our first white paper exploring the challenges and solutions for deploying ultra-low power machine learning (ML) at the end of the cloud!
Industry News
TinyML unlocks new possibilities for sustainable development technologies
In this article, we take a look at two tinyML projects that have the potential to make contributions towards sustainable development goals. While the first project is about revolutionising precision farming, the second one aims to create a network of low-cost sensors for mapping carbon emissions.
TinyML is bringing deep learning models to microcontrollers
Deep learning models owe their initial success to large servers with large amounts of memory and clusters of GPUs. The promises of deep learning gave rise to an entire industry of cloud computing services for deep neural networks. Consequently, very large neural networks running on virtually unlimited cloud resources became very popular, especially among wealthy tech companies that can foot the bill…