Artificial intelligence consists of three elements: algorithms, computation, and data. Algorithms are the core of AI implementation, while computation and data serve as the foundation. In terms of algorithms, they can mainly be divided into engineering methods and simulation methods. The engineering method employs traditional programming techniques to improve algorithm performance using extensive data processing … Read more
The current mainstream AI chips can be mainly divided into three categories: GPU, FPGA, and ASIC. Both GPU and FPGA are relatively mature chip architectures and belong to general-purpose chips. ASIC is a chip customized for specific AI scenarios. The industry has confirmed that CPU is not suitable for AI computing, but is still indispensable … Read more
Banner Promotion Writtenby Research Team Introduction Recently, Professor Yi Lilin’s team from the Key Laboratory of Regional Optical Fiber Communication Networks and New Optical Communication Systems at Shanghai Jiao Tong University proposed a Learnable Digital Signal Processing (LDSP) technology for high-speed optical fiber communication systems. This technology treats traditional Digital Signal Processing (DSP) modules as … Read more
As part of the “2022 Research and Analysis Report on 45 Domestic AI Chip Manufacturers”, the AspenCore analyst team compiled a list of 10 domestic AI chips and 10 international AI chips to showcase the latest technological developments in global AI chips. The top 10 domestic AI chips come from the following manufacturers: Cambricon, Horizon … Read more
Click the blue text Follow us Shen Xiangyang Chairman of the Board of Hong Kong University of Science and Technology, Foreign Member of the National Academy of Engineering, USA On September 5, 2024, the internationally renowned Inclusion Bund Conference was grandly held in Shanghai. In the keynote speech at this conference, Shen Xiangyang, Chairman of … Read more
01 Reinforcement Learning (RL), also known as evaluative learning or enhanced learning, is one of the paradigms and methodologies in machine learning used to describe and solve the problem of agents learning strategies to maximize rewards or achieve specific goals through interactions with the environment. It is inspired by the behaviorist theory in psychology, which … Read more
Imagine if Alan Turing and John McCarthy had Instagram; their posts might crash the servers! The history of artificial intelligence in the tech world has been like a roller coaster, experiencing thrilling highs and frustrating lows. In 1950, Turing proposed the “Turing Test,” which was like dropping a depth charge in the tech community. Then, … Read more
1. Machine Vision Hardware Can Collect Environmental Information The commonly used visual sensors include: cameras, ToF lenses, and LiDAR technology. Machine vision cameras. The purpose of machine vision cameras is to transmit images projected onto sensors through lenses to machines that can store, analyze, and/or display them. A simple terminal can be used to display … Read more
Source: MedRobot ; Editor: Mint Reprint Requirements: Please indicate the source at the beginning of the article, and it can be reprinted directly. From selecting navigation paths on maps to ChatGPT drafting emails, artificial intelligence has made everyday life easier and reduced the difficulty of various tasks. Similarly, in the healthcare field, AI plays a … Read more
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