Tips for Optimizing AI Models for Tiny Devices
Tips for Optimizing AI Models for Tiny Devices And the hidden cost of not getting it right! What happens when […]
TinyML
Optimizing TinyML with Neural Architecture Search: A Practical Guide for Edge AI
Deploying AI onto microcontrollers—known as TinyML—is akin to packing a symphony orchestra inside a wristwatch. Could Neural Architecture Search be the key to achieving this mammoth feat?
Facial Recognition at the Edge is Hard! Imagine it Done with embedUR
Facial recognition is exploding across devices—but deploying it to the edge is brutally hard. Learn why open-source fails, and how embedUR is the closest thing to plug-and-play!
How Neuromorphic Chips Could Redefine Edge AI Devices
Designed to replicate the structure and functionality of the human brain, we take a look at this groundbreaking advancement in computing – Neuromorphic chips
Reducing Energy Demand of AI with Edge Computing
We explore how industries are using energy efficient edge computing to scale AI, improve products and services as well as reduce operational costs.
Intelligent Edge: A New Era of Network Evolution
The race is on to push machine learning intelligence into small devices, creating the Intelligent Edge. What’s involved?