April 19, 2024, 4:43 a.m. | Dingzhu Wen, Xiaoyang Li, Yong Zhou, Yuanming Shi, Sheng Wu, Chunxiao Jiang

cs.LG updates on arXiv.org arxiv.org

arXiv:2306.01162v2 Announce Type: replace-cross
Abstract: Edge artificial intelligence (AI) has been a promising solution towards 6G to empower a series of advanced techniques such as digital twins, holographic projection, semantic communications, and auto-driving, for achieving intelligence of everything. The performance of edge AI tasks, including edge learning and edge AI inference, depends on the quality of three highly coupled processes, i.e., sensing for data acquisition, computation for information extraction, and communication for information transmission. However, these three modules need to …

abstract advanced and edge ai artificial artificial intelligence arxiv auto communication communications computation cs.ai cs.it cs.lg digital digital twins driving edge edge ai everything inference intelligence math.it performance projection semantic sensing series solution tasks twins type

Artificial Intelligence – Bioinformatic Expert

@ University of Texas Medical Branch | Galveston, TX

Lead Developer (AI)

@ Cere Network | San Francisco, US

Research Engineer

@ Allora Labs | Remote

Ecosystem Manager

@ Allora Labs | Remote

Founding AI Engineer, Agents

@ Occam AI | New York

AI Engineer Intern, Agents

@ Occam AI | US