On September 10, Apple and Huawei held their product launch events simultaneously, inviting scrutiny from the market. The two tech giants—Huawei and Apple—unexpectedly chose this day to unveil their new products, undoubtedly bringing double anticipation to tech enthusiasts. This face-off has been humorously dubbed by many netizens as “mutual face-to-face grand opening”. So, when we … Read more
MLNLP community is a well-known machine learning and natural language processing community, with an audience covering NLP master’s and doctoral students, university professors, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, especially for beginners. Reprinted from … Read more
Originally from PaperWeekly Author: Dan Jiang Affiliation: National University of Singapore Generally speaking, the deployment of large language models follows the “pre-training – then fine-tuning” model. However, when fine-tuning a base model for numerous tasks (such as personalized assistants), the training and service costs can become very high. Low-Rank Adaptation (LoRA) is a parameter-efficient fine-tuning … Read more
Recently, NVIDIA’s market value increased by 5.2%, closing at $3.019 trillion, surpassing Apple to become the second largest company by market value in the US stock market, second only to Microsoft. In today’s technology landscape, GPUs have become one of the most important infrastructures driving the development of artificial intelligence, deep learning, and high-performance computing. … Read more
X-Silicon Inc. (XSi) has created a new RISC-V microprocessor architecture that combines RISC-V CPU cores with vector capabilities and GPU acceleration into a single chip. According to Jon Peddie Research, the CPU/GPU hybrid chip is open-source and is designed to handle a variety of functions typically managed by dedicated CPUs and GPUs, aiming to do … Read more
1. Overview With the surge of artificial intelligence and the widespread application of AI algorithms, deep learning has become a key focus of current AI research. In the field of autonomous driving, environmental perception, sensor fusion, and control decision-making all involve deep learning to some extent. The performance of autonomous driving is directly related to … Read more
Source: Semiconductor Industry Review Original Author: Feng Ning In the layout of artificial intelligence computing architecture, the collaborative working model of CPUs and acceleration chips has become a typical AI deployment solution. The CPU plays the role of providing basic computing power, while the acceleration chips are responsible for enhancing computing performance to assist algorithms … Read more
In recent years, the concept of FPGA has become increasingly prevalent. For example, in Bitcoin mining, there are miners based on FPGA. Additionally, Microsoft previously stated that it would use FPGA to “replace” CPU in data centers, among other things. In fact, for professionals, FPGA is not unfamiliar; it has been widely used. However, most … Read more
The following content is organized from Zhihu: Author: Wang Peng Link:https://www.zhihu.com/question/285202403/answer/444253962First, let me answer the question, (1) There is a significant difference in performance compared to traditional chips, such as CPUs and GPUs. When executing AI algorithms, they are faster and more energy-efficient. (2) There is no difference in manufacturing processes; everyone is the same. … Read more
Source: Software and Hardware Integration Original Author: Chaobowx Editor’s Note Reviewing the history of computer development, from serial to parallel, from homogeneous to heterogeneous, it will continue to evolve to ultra-heterogeneous: First Stage: Serial Computing. Single-core CPUs and ASICs belong to serial computing. Second Stage: Homogeneous Parallel Computing. Multi-core CPUs and GPUs with thousands of … Read more