TY - JOUR
T1 - Enabling Design Methodologies and Future Trends for Edge AI
T2 - Specialization and Codesign
AU - Hao, Cong
AU - Dotzel, Jordan
AU - Xiong, Jinjun
AU - Benini, Luca
AU - Zhang, Zhiru
AU - Chen, Deming
N1 - Funding Information:
This work was supported in part by the IBM-Illinois Center for Cognitive Computing System Research (C3SR)—a research collaboration as part of IBM AI Horizons Network, by the Semiconductor Research Corporation (SRC) program under Grant 2803.001/2804.001, and in part by NSF under Award 2007832.
PY - 2021/8
Y1 - 2021/8
N2 - Significant growth is seen in artificial intelligence (AI), in particular deep learning (DL), which has made remarkable progress in various areas such as computer vision, natural language processing, health care, autonomous driving, and surveillance. To accomplish this, AI technologies have broadened from a centralized fashion to mobile or distributed fashion, opening a new era called edge AI, with dramatic advancements that are substantially changing everyday technology, social behavior, and lifestyles. Edge AI couples intelligence and analysis to a broad collection of connected devices and systems for data collection, caching, and processing. It enables a wide variety of new promising applications where data collection and analysis are combined. Billions of mobile users are exploiting various smartphone applications such as translation services, digital assistants, and health monitoring services.
AB - Significant growth is seen in artificial intelligence (AI), in particular deep learning (DL), which has made remarkable progress in various areas such as computer vision, natural language processing, health care, autonomous driving, and surveillance. To accomplish this, AI technologies have broadened from a centralized fashion to mobile or distributed fashion, opening a new era called edge AI, with dramatic advancements that are substantially changing everyday technology, social behavior, and lifestyles. Edge AI couples intelligence and analysis to a broad collection of connected devices and systems for data collection, caching, and processing. It enables a wide variety of new promising applications where data collection and analysis are combined. Billions of mobile users are exploiting various smartphone applications such as translation services, digital assistants, and health monitoring services.
KW - Edge AI
KW - IoT
KW - co-design
KW - design methodology
KW - edge device
KW - machine learning
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U2 - 10.1109/MDAT.2021.3069952
DO - 10.1109/MDAT.2021.3069952
M3 - Review article
AN - SCOPUS:85103758914
SN - 2168-2356
VL - 38
SP - 7
EP - 26
JO - IEEE Design and Test
JF - IEEE Design and Test
IS - 4
M1 - 9391712
ER -