- February 13, 2021
TinyML Could Democratize AI Programming for IoT
Upgrading microcontrollers with small, essentially self-contained neural networks enables organizations to deploy efficient AI capabilities for IoT without waiting for specialized AI chips.
- November 03, 2020
How TinyML Makes Artificial Intelligence Ubiquitous
TinyML is the latest from the world of deep learning and artificial intelligence. It brings the capability to run machine learning models in a ubiquitous microcontroller – the smallest electronic chip present almost everywhere.
- October 30, 2020
Can artificial intelligence give elephants a winning edge?
Open-source developers and tech giants created the world’s most advanced elephant tracking collars.
“Sara Olsson, a Swedish software engineer who has a passion for the natural world created a tinyML and IoT monitoring dashboard”.
- January 11, 2020
Why tinyML is a giant opportunity right now
The world is about to get a whole lot smarter. As the new decade begins, we’re hearing predictions on everything from fully remote workforces to quantum computing. However, one emerging trend is scarcely mentioned on tech blogs – one that may be small in form but has the potential to be massive in implication. We’re talking about microcontrollers.
- December 01, 2019
tinyML book written by Pete Warden and Daniel Situnayake of Google
Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size—small enough to work on the digital signal processor in an Android phone. With this practical book, you’ll learn about TensorFlow Lite for Microcontrollers, a miniscule machine learning library that allows you to run machine learning algorithms on tiny hardware.
- October 31, 2019
Stanford University Seminar
Evgeni Gousev of Qualcomm and Pete Warden of Google participated in a panel at Stanford University seminar “Current Status of tinyML and the Enormous Opportunities Ahead”.
- July 12, 2019
AI at the Very, Very Edge (EE Times)
When the TinyML group recently convened its inaugural meeting, members had to tackle a number of fundamental questions, starting with: What is TinyML? TinyML is a community of engineers focused on how best to implement machine learning (ML) in ultra-low power systems. The first of their monthly meetings was dedicated to defining the issue.
- March 28, 2019
TinyML Sees Big Hopes for Small AI (EE Times)
SUNNYVALE, Calif. – A group of nearly 200 engineers and researchers gathered here to discuss forming a community to cultivate deep learning in ultra-low power systems, a field they call TinyML. In presentations and dialogs, they openly struggled to get a handle on a still immature branch of tech’s fastest-moving area in hopes of enabling a new class of systems.