Schedule
Timezone: PDT
TinyML: Enabling Low Power at the Edge – Lagos, Nigeria
Daniel SITUNAYAKE, Founding tinyML Engineer
Edge Impulse
TinyML is a fast-growing and exciting field of Machine Learning that enables edge computing and data analytics at extremely low power, typically in the mW range and below. This allows for a variety of always-on use-cases and targeting battery-operated devices. It has the potential to be transformational for Africa in spaces/areas such as agriculture, wildlife conservation, transportation, manufacturing etc.
Edge Impulse is building tools for easier machine learning integration at the edge. These tools are free and easy to use for developers.
Daniel SITUNAYAKE, Founding tinyML Engineer
Edge Impulse
Daniel Situnayake leads embedded machine learning engineering at Edge Impulse, a platform that allows developers to train machine learning models that run on tiny, low-power devices. He’s co-author of the book TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers, published by O’Reilly, and sits on the tinyML Foundation’s community organizing committee. He has previously worked on the TensorFlow team at Google, as CEO of Tiny Farms Inc., and as a lecturer in Automatic Identification and Data Capture at Birmingham City University.
Schedule subject to change without notice.