Reflections on the Promoting Effect of Quantum Machine Learning on the Development of Artificial Intelligence in the Iteration Process of Machine Learning Technology
DOI:
https://doi.org/10.54097/bzp2nb70Keywords:
Quantum Machine Learning, Artificial Intelligence, Computational Complexity, Algorithm Iteration, Quantum Computing, Neural NetworksAbstract
With the rapid development of artificial intelligence technology, some shortcomings in the traditional machine learning model have begun to show. With the growth of the quantity of data, too many parameters have become a problem and traditional silicon-based computers are near their physical limits. Quantum machine learning is a new way that will be able to advance the development of artificial intelligence significantly in the future. This paper will introduce and investigate the promoting effect of quantum machine learning on the overall development process of artificial intelligence. By learning about the differences between traditional neural networks and quantum-enhanced algorithms, this paper will show that superposition and entanglement in quantum mechanics can solve computational problems that have been very difficult to solve for a long time. Also, based on the above, it will be explored how quantum feature spaces and quantum neural networks can significantly boost the speed of data processing and pattern recognition. Based on the above results, it is hoped that quantum machine learning will be able to provide a new computing system with enhanced capabilities compared with the current model and thus advance the continuous development of artificial intelligence.
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