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.
The tinyML Summit 2023 Program Committee invites contributions from experts in industry, academia, start-ups and government labs. This will be an IN-PERSON event (no streaming or pre-recorded presentations).
Women in tinyML (WitML) is an international non-profit organization on a mission to increase women representation in the field of tinyML.
We promote tinyML and women empowerment around the world with a focus on harnessing technology in sustainable, environment friendly and far-reaching areas/use cases.
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.
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…