Source: Big Data Digest The length of this article is 5288 words, recommended reading time 10 minutes This article summarizes 10 deep learning methods suitable for four basic network architectures. Over the past decade, public interest in machine learning has grown significantly. Machine learning can be seen almost daily in computer science programs, industry conferences, … Read more
Citation format：[1] Xu Xinzhen, Wang Guanjun, Li Xiangqun, et al. “Exploration and Practice of AI Talent Cultivation System in the Context of New Engineering” [J]. Industrial and Information Education, 2024(05):1-4+14. Submission date: 2023-7-1 Author introduction: Xu Xinzhen (1980—), male, from Suzhou, Anhui, PhD, Professor, research direction in machine learning, embedded AI, and medical image processing; … Read more
The development of artificial intelligence has brought convenience and changes to people’s lives. However, a cloud-centric architecture is not always the ideal solution in every situation, such as concerns about information security and challenges in product design due to power consumption. As a result, embedded artificial intelligence technology, characterized by its distributed nature, has begun … Read more
Introduction The autonomous driving system is a comprehensive system integrating functions such as environmental perception, decision-making control, and action execution. It is a system that fully considers the coordination planning between vehicles and the traffic environment, and it is also an important component of future intelligent transportation systems. This article focuses on analyzing the relevant … Read more
The latest member of Nordic Semiconductor’s Thingy series, the Thingy 53, combines a flagship dual-core SoC, power management IC, PA/LNA range extender, and multiple sensors, along with embedded machine learning firmware, accelerating the realization of advanced wireless proofs-of-concept. Nordic Semiconductor has released the multi-sensor prototyping platform ‘Nordic Thingy:53’ (“Thingy:53”), which features multi-protocol short-range wireless connectivity … Read more
1. Why Use FPGA? As we all know, the Moore’s Law for general-purpose processors (CPU) has entered its twilight, while the scale of machine learning and web services is growing exponentially. People are using custom hardware to accelerate common computing tasks, but the rapidly changing industry demands that this custom hardware be reprogrammable to perform … Read more
Some time ago, I shared the “Research Report on China’s FPGA Chip Industry (Part 1)“. Today, I will continue discussing FPGA technology. CCI-Techat FPGAs can be used to handle various compute-intensive tasks. Relying on a pipelined parallel structure, FPGAs have a technical advantage over GPUs and CPUs in terms of latency for returning computation results. … Read more
Source: Chip Intelligence 1. Definition and Classification of FPGA Chips 1. Definition and Physical Structure of FPGA Chips FPGA (Field Programmable Gate Array) chips are developed based on programmable devices (PAL, GAL) and are semi-custom, programmable integrated circuits. Inventor: Ross Freeman, co-founder of Xilinx, invented the FPGA integrated circuit structure in 1984. The world’s first … Read more
(Source: techspot) Graphics Processing Units (GPUs) and Field Programmable Gate Arrays (FPGAs) are two of the three main types of processors used for imaging and other heavy computations. The Central Processing Unit (CPU) is the third type. Let’s delve into the main differences between GPUs and FPGAs, their advantages, common use cases, and when to … Read more
Imagine you have an electronic “Swiss Army knife” that can be sculpted into any shape, performing various complex computational tasks. Yes, this is FPGA! In simple terms, FPGA is a hardware chip that integrates a large number of programmable logic gates. Through programming, you can define the connections between these logic gates to achieve specific … Read more