Research on the optimization and performance evaluation of intelligent computing algorithms based on cloud computing
Intelligent Computing AI refers to the current era characterized by intelligent computation as its core feature,marked by significant improvement in computing power and rapid development of artificial intelligence technology.AI tools such as ChatGPT have rapidly spread worldwide with their powerful text processing capabilities,ushering in the era of intelligent computing.Against this backdrop,optimizing AI algorithms in cloud computing scenarios has become a key task in improving AI technology performance.This paper analyzes the transformer model self-attention mechanism algorithm used in ChatGPT,designs an algorithm optimization process aimed at enhancing model efficiency through reducing computational complexity.Experimental results demonstrate that the optimized model significantly improves computational efficiency while maintaining accuracy,aiming to enhance the performance of intelligent computing AI algorithms in cloud computing scenarios and provide insights for the development of artificial intelligence technology.
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