Towards efficient generative AI and beyond-AI computing:New trends on ISSCC 2024 machine learning accelerators  

作　　者：Bohan Yang Jia Chen Fengbin Tu 

机构地区：[1]Department of Electronic and Computer Engineering,The Hong Kong University of Science and Technology,Hong Kong,China [2]AI Chip Center for Emerging Smart Systems,The Hong Kong University of Science and Technology,Hong Kong,China [3]School of the Gifted Young,University of Science and Technology of China,Hefei 230026,Chin

出　　处：《Journal of Semiconductors》2024年第4期12-15,共4页半导体学报（英文版）

基　　金：This research was supported in part by ACCESS-AI Chip Center for Emerging Smart Systems,sponsored by InnoHK funding,Hong Kong SAR,and HKUST-HKUST(GZ)20 for 20 Cross-campus Collaborative Research Scheme C031.

摘　　要：Compared to the last decade when the convolution neu-ral network(CNN)dominated the research field,machine learn-ing(ML)algorithms have reached a pivotal moment called the generative artificial intelligence(AI)era.With the emer-gence of large-scale foundation models[1],such as large multi-modal model(LMM)GPT-4[2]and text-to-image generative model DALL·E[3].

关 键 词：ISSCC BEYOND AI 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]