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A radical paradigm shift of wireless networks from ``connected things'' to``connected intelligence'' undergoes, which coincides with the Shanno andWeaver's envisions: Communications will transform from the technical level tothe semantic level. This article proposes a semantic communication method withartificial intelligence tasks (SC-AIT). First, the architecture of SC-AIT iselaborated. Then, based on the proposed architecture, we implement SC-AIT for aimage classifications task. A prototype of SC-AIT is also established forsurface defect detection, is conducted. Experimental results show that SC-AIThas much lower bandwidth requirements, and can achieve more than $40\%$classification accuracy gains compared with the communications at the technicallevel. Future trends and key challenges for semantic communications are alsoidentified.

Semantic Communications With AI Tasks