Core Viewpoint - WiMi Hologram Cloud Inc. is exploring an innovative solution called Synergic Quantum Generative Network (SQGEN), which utilizes a parallel quantum learning framework to enhance the efficiency of generative learning in quantum computing [1][4]. Group 1: SQGEN Overview - SQGEN features a parallel quantum learning framework where the generator and discriminator operate simultaneously, improving training speed and efficiency [1][3]. - The architecture employs the Nelder-Mead optimization algorithm, which is effective in quantum computing environments where gradient calculations are challenging [2]. - SQGEN introduces a cost function that relaxes the reversibility condition, enhancing stability and reducing quantum resource consumption during training [2][3]. Group 2: Technological Advantages - The collaborative quantum generative network architecture significantly improves training efficiency and reduces the time to reach a converged state compared to traditional methods [3][4]. - By optimizing quantum communication mechanisms and reducing cost function evaluations, SQGEN makes quantum generative learning more economically feasible [3][4]. - The synchronization mechanism within SQGEN ensures that the generator and discriminator remain in sync, addressing training instability and enhancing model robustness [2][3]. Group 3: Future Implications - With ongoing advancements in quantum computing technology, SQGEN has the potential for broader applications in machine learning and artificial intelligence [4]. - The improvements in training speed and data quality achieved by SQGEN validate its effectiveness and suggest new methodologies for quantum generative learning [3][4]. Group 4: Company Background - WiMi Hologram Cloud, Inc. specializes in holographic AR technologies, including automotive applications, 3D holographic pulse LiDAR, and holographic software development [5]. - The company is positioned as a leading provider in the global Hologram Augmented Reality technology sector, focusing on innovative solutions and applications [5].