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
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
📢 Breaking News:Only 4 days left until the deadline for the 2025 China Edge Computing Top 20 Company list registration! If you miss this moment, your company may miss the biggest exposure opportunity in edge computing this year!🚀 The edge computing community has learned that Qualcomm has recently acquired the edge AI startup Edge Impulse. … Read more
Author: Zach Shelby (Founder of Edge Impulse, Co-founder of Yunhe Capital)IoT Think Tank Original This is my 364th column article. Recently, the field of Tiny Machine Learning (TinyML) has made milestone progress, crossing an important watershed. The maturity and development potential of this technology will reach a new level. The most representative event was Qualcomm’s … Read more
Author: Peng Zhao (Founder of Zhici Fang, Co-Founder of Yunhe Capital)IoT Think Tank Original This is my 365th column article. In the previous article “Tech Giants Enter TinyML, Edge AI Reaches a New Turning Point,” I mentioned that the TinyML Foundation has undergone a rebranding and is now known as the Edge AI Foundation. Recently, … Read more
The 41st ICCAD (International Conference on Computer Aided Design) was grandly held from October 30 to November 4 in San Diego, California, USA. This conference, co-sponsored by ACM and IEEE, is an annual event that explores new challenges, proposes cutting-edge innovative solutions, and identifies emerging technologies in the field of Electronic Design Automation (EDA). S … Read more
When Smartwatches Can Translate Sign Language in Real Time Have you ever thought that a chip the size of a fingernail could run face recognition? MIT Han Lab’s open-source TinyML technology is making these sci-fi scenarios a reality. This groundbreaking technology has been successfully deployed in over 100,000 IoT devices, with WIRED and MIT News … Read more
Deep learning dominates various fields and fundamentally changes human society. Efficiency is a key factor in democratizing deep learning and expanding its application scope. This has become increasingly important as Moore’s Law slows down and the pace of model size expansion accelerates. We need efficient algorithms and systems to help bridge this gap. In this … Read more
Click the card below to follow the “LiteAI” public account Hi, everyone, I am Lite. Recently, I shared the Efficient Large Model Full-Stack Technology from Article One to Nineteen, which includes content on large model quantization and fine-tuning, efficient inference for LLMs, quantum computing, generative AI acceleration, etc. The content links are as follows: Efficient … Read more
Are you eager to master the future of artificial intelligence? Are you curious about how to embed powerful machine learning algorithms into a tiny Arduino board? Then, you definitely cannot miss the exciting TinyML theme at the 2AI/ML DevFest workshop! This article will take you deep into this event, review its highlights, and let you … Read more