Artificial intelligence technology has long relied on powerful cloud computing. However, recently we have begun to raise the question: “Why has Edge AI only started to receive such attention now?” Upon careful consideration, the reasons are actually quite clear. For fields such as autonomous driving or smart factories that require immediate on-site decision-making, even a … Read more
The State Council has released opinions on the in-depth implementation of the “Artificial Intelligence +” initiative. The opinions propose to promote the “Internet of Everything” for smart terminals, cultivate an ecosystem of smart products, and vigorously develop new generation smart terminals such as smart connected vehicles, AI smartphones and computers, smart robots, smart homes, and … Read more
Edge AI: Reconstructing the underlying logic of intelligent terminals. Edge AI (Edge AI) achieves localized data processing by embedding the computing, reasoning, and decision-making capabilities of artificial intelligence directly into terminal devices (such as smartphones, smart cars, industrial robots, etc.). Compared to traditional architectures that rely on cloud services, its core advantages are: Low latency … Read more
CAA Intelligence Sets Sail for a Shared Future This is a gift from Jensen Huang to the robots. On Monday, NVIDIA officially launched its next-generation robotics-specific chip, Jetson Thor. Compared to the previous generation Jetson Orin, the new generation aims to significantly enhance computing power to accommodate embodied intelligence algorithms, supporting various forms such as … Read more
“ Compared to cloud AI, edge AI focuses on embedding AI capabilities into devices, enabling real-time data processing, privacy protection, and low-latency responses by running AI algorithms locally on the terminal. This approach is becoming the core carrier for the implementation of AI technology. According to the “2024-2030 China Edge AI Market Survey and Investment … Read more
Artificial Intelligence(AI) on edge devices is revolutionizing the field of embedded electronics by enabling advanced computing capabilities directly on low-power devices. Traditionally, neural networks required powerful hardware and abundant resources, but with the development of technologies like TinyML, inference can now be performed directly on devices even with limited computational resources. Deploying neural networks on … Read more
(By Richard Anslow, Senior Manager; Danail Baylov, Senior Engineer) Abstract There are various methods to enhance the intelligence of industrial systems, including the application of edge and cloud-based artificial intelligence (AI) technologies to sensors equipped with analog and digital devices. Given the diversity of AI approaches, sensor designers must consider several conflicting requirements, including decision … Read more
In industrial settings, motors, fans, compressors, and CNC machines operate day and night, with hidden dangers often lurking silently within vibration and noise. Without real-time monitoring, these “early signals” can be overlooked until equipment suddenly fails, leading to production stoppages or even safety incidents. Shenzhen Beirui Technology Co., Ltd. has launched the BL450 industrial embedded … Read more
Research Background and Core Issues The Rise of Edge AI: The Internet of Things (IoT) and AI applications (such as autonomous driving and smart industry) are driving data processing from the cloud to edge devices to reduce latency, enhance privacy, and alleviate bandwidth pressure. Key Challenges: Edge devices (such as Raspberry Pi and Jetson Nano) … Read more
🌐 Best Edge AI Development Boards for Summer 2025 Author: David Tischler Published 1 month ago • AI and Machine Learning As July reaches its peak, what better way to welcome the “Summer of Edge AI” than by reviewing the best edge AI hardware and devices of the season? Over the years, edge AI hardware … Read more