The core of blockchain is its chain-like data structure, where each block contains three components: transaction data, a timestamp, and the hash of the previous block. This design ensures data integrity and immutability because any modification to the data would change its hash, thereby breaking the continuity of the chain. In blockchain, asymmetric encryption algorithms (such as RSA and ECC) are widely used for data encryption and digital signatures. These algorithms are based on complex mathematical probl ...

Core Insights - WiMi Hologram Cloud Inc. has announced the development of a Scalable Quantum Neural Network (SQNN) technology [1] Company Overview - WiMi is recognized as a leading global provider of Hologram Augmented Reality (AR) technology [1]

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].

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