BEIJING, Oct. 23, 2025 (GLOBE NEWSWIRE) -- BEIJING, Oct. 23, 2025––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, today announced that they are actively exploring a shallow hybrid quantum-classical convolutional neural network (SHQCNN) model, bringing innovative breakthroughs to the field of image classification.Variational quantum methods, as an important technical means in the field of quantum computing, provide ef ...

Core Viewpoint - WiMi Hologram Cloud Inc. has developed a Quantum Computing-Based Feedforward Neural Network (QFNN) algorithm that addresses computational bottlenecks in traditional neural network training, utilizing Quantum Random Access Memory (QRAM) for efficient data processing [1][10]. Quantum Algorithm Development - The QFNN algorithm incorporates key quantum computing subroutines, particularly in the feedforward and backpropagation processes, providing exponential speedup in both stages of neural network training [2][4]. - Classical feedforward propagation, which involves multiple matrix-vector multiplications, is enhanced by the quantum algorithm through the use of quantum state superposition and coherence, allowing computations to be performed in logarithmic time [3][6]. Computational Efficiency - The quantum algorithm significantly reduces computational complexity, shifting from a dependency on the number of connections (O(M)) in classical networks to a dependency solely on the number of neurons (O(N)) in the quantum framework [6][7]. - This reduction in complexity leads to at least a quadratic speedup in training large-scale neural networks, making it particularly advantageous for ultra-large-scale datasets [7]. Overfitting Mitigation - WiMi's quantum algorithm demonstrates inherent resilience to overfitting, a common issue in deep learning, due to the intrinsic uncertainty of quantum computing, which acts similarly to regularization techniques [8][9]. Application Prospects - The QFNN algorithm has broad application potential in fields requiring high computational speed and data scale, such as financial market analysis, autonomous driving, biomedical research, and quantum computer vision [10][11]. - Additionally, the research lays the groundwork for quantum-inspired classical algorithms that can optimize computational complexity on traditional computers, providing a transitional solution until quantum computers become widely available [10]. Future Implications - The advancement of WiMi's QFNN algorithm marks a significant milestone in the intersection of quantum computing and machine learning, suggesting that quantum neural networks will play a crucial role in the future of artificial intelligence [11][12].

Core Insights - WiMi Hologram Cloud Inc. has reported a significant financial turnaround, moving from a net loss of approximately RMB 510.4 million in 2023 to a net income of around RMB 103.3 million (USD 14.4 million) in 2024, indicating effective operational strategies and strong management [2] - The company experienced a substantial increase in cash and cash equivalents and short-term investments, rising by approximately RMB 1.14 billion, or 148.0%, from about RMB 773.9 million in 2023 to approximately RMB 1.92 billion (USD 266.9 million) in 2024, enhancing its financial position for future growth [3] Company Overview - WiMi Hologram Cloud Inc. is a leading provider of hologram augmented reality technology, focusing on various professional areas including automotive HUD software, 3D holographic pulse LiDAR, and holographic cloud software, among others [6]