Edge AI: Three Memory Compression Techniques for Deploying TinyML with MicroPython

Edge AI: Three Memory Compression Techniques for Deploying TinyML with MicroPython

Edge AI: Three Memory Compression Techniques for Deploying TinyML with MicroPython To be honest, when I first tried to run a neural network on the ESP32, I was almost driven to madness. 256KB of RAM? Are you serious? That 5MB model I trained on Colab was completely out of the question. However, after experimenting over … Read more

New Breakthrough in TinyML! Efficient Indoor Localization Using Transformers and Mamba

New Breakthrough in TinyML! Efficient Indoor Localization Using Transformers and Mamba

Paper Title: Optimising TinyML with Quantization and Distillation of Transformer and Mamba Models for Indoor Localisation on Edge DevicesPublication Date: December 2024Authors: Thanaphon Suwannaphong, Ferdian Jovan, Ian Craddock, Ryan McConvilleAffiliations: University of Bristol, University of AberdeenOriginal Link: https://arxiv.org/pdf/2412.09289Open Source Code and Dataset Link: https://github.com/AloeUoB/tinyML_indoor_localisation Introduction Typically, accurate indoor localization systems rely on large machine learning … Read more