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
▲ For more exciting content, please click the blue text above and follow us! Last November, a piece of AI hardware called “AI Pin” took the tech world by storm. This device breaks away from tradition, eliminating the screen interface and relying entirely on voice and projection technology to interact with users, responding to short … Read more
The functionality of artificial intelligence (AI) has become crucial in various mobile devices. Particularly in 2024, AI PCs are being launched, marking it as the “Edge Device AI Era.” This article reviews the main AI PCs and processors released in the second half of 2024. The semiconductor industry in 2024 is expected to be fully … Read more
AI chips can be categorized based on their application scenarios into cloud AI training and inference, edge AI inference, and terminal AI inference. In our article on the Top 10 Domestic AI Chips, we listed the cloud AI training and inference chips from 10 domestic AI chip companies. This article will focus on edge and … Read more
This article is sourced from: Smart Car Technology Recently, there has been news online about LeddarTech partnering with Hailo to create solutions for ADAS (Advanced Driver Assistance Systems) customers that are higher in performance, more affordable, more scalable, more flexible, and lower in power consumption. We can’t help but ask, what kind of companies are … Read more
Ms. Chloe Ma, Vice President of Business Development at Arm’s IoT Division Recently, Ms. Chloe Ma, Vice President of Business Development at Arm’s IoT Division, conducted an online interview with industry media, introducing the evolution of edge artificial intelligence (AI) and Arm’s new generation Ethos-U85 AI accelerator and the new IoT reference design platform Arm … Read more
According to reports from Electronic Enthusiasts (Written by Li Wanwan), in the era of artificial intelligence, more and more AI applications need to extend from the cloud to the edge, such as smart headphones, smart cameras, smart bracelets, logistics robots, etc. Deploying AI at the edge has become a trend. With the rapid development of … Read more