Company Overview - WiMi Hologram Cloud Inc. is a leading global provider of Hologram Augmented Reality (AR) technology, focusing on various professional fields including in-vehicle AR holographic HUD, 3D holographic pulse LiDAR, and metaverse holographic AR/VR devices [1][15]. Technology Development - WiMi has proposed a new hybrid quantum-classical learning technology based on quantum convolutional neural networks (QCNN), which significantly improves performance in multi-class image classification tasks by recycling discarded qubit state information [2][3]. - This technology optimizes the efficiency of quantum networks under noisy intermediate-scale quantum (NISQ) devices and demonstrates the potential for quantum information reuse, paving a new path for hybrid quantum-classical models [3][12]. Quantum Computing Insights - Traditional QCNNs face challenges such as increased training time and energy consumption as model depth increases, necessitating a rethink of intelligent computing architectures [4][5]. - WiMi's architecture allows for the re-participation of discarded qubits in decision-making, enhancing the model's overall expressive ability and compensating for information loss during the pooling stage [6][10]. Architectural Innovation - The proposed architecture features a dual-channel structure that utilizes both retained and discarded qubit information, achieving maximum utilization of quantum information at the feature level [7][9]. - The training process employs a joint optimization mechanism based on classical cross-entropy loss, integrating outputs from both quantum and classical layers for improved performance [11][12]. Future Implications - WiMi's hybrid quantum-classical learning technology represents a significant advancement in quantum intelligence, exploring practical paths under current NISQ constraints and demonstrating the potential of quantum machine learning in various applications [13][14]. - As quantum computing progresses towards practical applications, hybrid models are expected to bridge the gap between theory and industry, driving innovation in fields such as intelligent vision and medical diagnosis [14].