The controller is one of the three core components of industrial robots and acts as the brain of the robot. Its quality directly determines the performance of the robot. Therefore, whether it is ABB, KUKA, or domestic suppliers like Siasun and Estun, all major industrial robot suppliers have taken control of the controller technology into … Read more
Hello everyone, today I’m going to take you to explore a super interesting field – TinyML! Are you still worried about insufficient computing power of devices? Or are you concerned that AI models are too large to run? TinyML was born to solve these problems. It can make AI models lightweight, make smart devices smarter, … Read more
Are you curious about Artificial Intelligence (AI) and Machine Learning (ML)? Do you want to know how to use it on the MCU you have already worked with? In this article, we will introduce you to Machine Learning on MCUs. This topic is also known as Tiny Machine Learning (TinyML). Get ready to lose to … Read more
TinyML is a miniature or small-scale artificial intelligence technology that can run on resource-constrained microcontrollers (MCUs) with features such as low latency, low power consumption, and low cost. It can perform inference tasks in AI such as keyword detection, anomaly detection, and object recognition. MCU Manufacturers Merging with AI Companies to Layout TinyML In May … Read more
Industry Insights and News Sharing Invites You to Submit/Recommend Articles Electric Family Supply and Demand Information Platform www.dd1j.com www.ev108.com Author | Matthew Stewart Translator | Gai Lei Planning | Chen Si A trend in artificial intelligence is rapidly shifting from the “cloud” to the “edge”. TinyML is the implementation of AI on microcontrollers at the … Read more
Click the card below to follow the “LiteAI” public account Hi, everyone, I am Lite. A while ago, I shared the Efficient Large Model Full-Stack Technology from Part 1 to Part 19, which includes content on large model quantization and fine-tuning, efficient LLM inference, quantum computing, generative AI acceleration, etc. The content links are as … Read more
Tiny Machine Learning (TinyML) is the new frontier of machine learning. By compressing deep learning models into billions of Internet of Things (IoT) devices and microcontrollers (MCUs), we expand the scope of AI applications and achieve ubiquitous intelligence. However, due to hardware limitations, TinyML faces challenges: the tiny memory resources make it difficult to accommodate … Read more
We previously published an article titled “TinyML: The Next Wave of Artificial Intelligence Revolution“, and held several events related to machine learning. We believe everyone has a certain understanding of TinyML, so why did we choose TinyML? Why Choose TinyML? ✦ Artificial Intelligence (AI) is rapidly transitioning from the cloud to the edge, entering increasingly … Read more
Author: Wu Nü Wang (Peng Zhao) IoT Think Tank Original Reprint must indicate the source and origin Introduction The most widely distributed IoT devices are often very small and have limited power. They serve as terminal hardware, collecting various data through embedded sensors; their computing power is limited and extremely sensitive to power consumption. Can … Read more
Computer vision is often seen as an important development direction for AI. With the continuous maturation of the AI industry and the expansion of application scenarios, the advantages of computer vision have gradually emerged, leading to an increase in market demand. Because computer vision is an indispensable and important sector for giants to layout AI, … Read more