Quantum computers have potential to change future of Artificial Intelligence. Although, classical supercomputers have powerful processing efficiency that can be used for the Artificial Intelligence (AI) applications, but speed limitation is still a challenge for many. Nature exhibits quantum phenomena of Superposition and Entanglement; researchers adapted the same phenomena to design Quantum Computer (QC) hardware. Algorithms designed for QC have achieved polynomial speed-up over the classical supercomputers. With the high demand of fast and reliable AI applications, it is beneficial to develop AI algorithms suitable for QCs. As AI algorithms deal with processing data and signals (such as image and audio), signal processing techniques (such as digital filters or so-called convolutions) are at the heart of AI algorithm, e.g. Convolutional Neural Networks (CNNs).Contribution of this research will provide outstanding bases for future of AI applications.
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