As AI applications migrate to edge devices, AI chips specifically designed for edge computing are becoming the new focal point of competition. This chip revolution is pushing intelligent computing from the cloud to the network edge, ushering in a new era of ubiquitous intelligence. Core Directions of Architectural Innovation Storage-Compute Integration: Breaking the von Neumann … Read more
Gongbang·New Ecology of Industrial Interconnection Bangxun 01 Introduction Edge Artificial Intelligence (Edge AI) refers to the development and deployment of artificial intelligence (AI) algorithms and programs on edge devices. It is a form of edge computing characterized by analyzing and processing data near the location where it is generated or collected. In contrast to Edge … Read more
Must-read for business owners: How to use cost-effective and responsive edge intelligence to solve long-standing pain points in quality inspection, security, and data privacy. A manufacturing business owner calculated that a high-end quality inspection line in his factory processes dozens of high-definition images every second. If the image data is sent to the cloud for … Read more
On November 13, 2025, Arm Technology (China) Co., Ltd. (hereinafter referred to as “Arm Technology”) held a product launch conference in Shanghai, officially introducing the next-generation NPU IP – “Zhouyi” X3. This product features the latest DSP+DSA architecture specifically designed for large models, balancing CNN and Transformer architectures, and is complemented by the user-friendly “Zhouyi” … Read more
With the explosive growth of IoT devices, traditional pure cloud or pure edge architectures can no longer meet the balance of real-time performance, privacy security, and computational cost. This article proposes an edge-cloud collaborative architecture based on popular open-source large models, achieving millisecond-level environmental perception and autonomous decision-making through model hierarchical deployment, dynamic task offloading, … Read more
Introduction With the deep integration of edge computing and AI technology, developers have an increasing demand for AI tools that can be deployed quickly, at low cost, and with high performance. For instance, in the past, if you wanted to deploy DeepSeek, you had to have a server to host it, whether it was a … Read more
MCUs (Microcontrollers) and DSPs (Digital Signal Processors) are commonly used hardware components in edge AI devices. This article provides a brief analysis of the characteristics of these two types of devices, in conjunction with the book “AI at the Edge“. A microcontroller is a small, inexpensive computer that is involved in the manufacturing of almost … Read more
The recent fluctuations in the global storage market have provided a vivid lesson on “supply chain security” for the rapidly developing edge AI industry. The transition of DDR4 chips from shortage to skyrocketing prices reflects the risk resistance capabilities of different technological paths. In this test, Rockchip’s flagship chip RK3588 and its platform-oriented thinking not … Read more
Edge AI and TinyML: Empowering Intelligent Connectivity In response to the four major challenges of cloud AI regarding latency, bandwidth, power consumption, and privacy, the AI field is undergoing a profound transformation from “cloud” to “edge”. Edge AI and TinyML, as the core driving forces of this transformation, are liberating intelligence from data centers and … Read more
Development and Value Evolution of the Global Edge AI Industry Edge AI refers to deploying AI models at the edge nodes close to the data generation sources, especially in AI consumer electronics and automotive fields, ensuring localized completion of data collection, processing, inference, and decision-making. Through a collaborative model of cloud training and edge deployment, … Read more