WiMi Developed a Blockchain Empowered Asynchronous Federated Learning for Optimizing Model Training

Core Viewpoint - WiMi Hologram Cloud Inc. has developed a blockchain-based asynchronous federated learning (BAFL) framework that enhances the efficiency and security of federated learning systems by integrating blockchain technology with asynchronous learning mechanisms [1][3]. Group 1: Technology and Innovation - The BAFL framework combines blockchain's decentralization, immutability, and transparency to ensure the integrity and traceability of model data, preventing malicious tampering [1][3]. - Asynchronous learning allows devices to upload model updates flexibly, improving the efficiency of the learning process, especially in high-latency environments [2][3]. - The framework addresses data silos and enhances model training efficiency while safeguarding data security and privacy, paving the way for distributed AI model training [3]. Group 2: Applications and Market Potential - BAFL has broad application prospects in various fields, including healthcare, finance, and smart manufacturing [3]. - In healthcare, BAFL can facilitate the sharing of medical record data for joint training of disease prediction models while protecting patient privacy [3]. - In finance, it can be used to train credit risk assessment models, improving risk identification accuracy while complying with data protection regulations [3]. - In smart manufacturing, BAFL enables optimization of production processes and predictive maintenance by analyzing data from different factories without risking data leakage [3]. Group 3: Company Overview - WiMi Hologram Cloud, Inc. is a comprehensive technical solution provider focusing on holographic AR technologies, including automotive HUD software, 3D holographic pulse LiDAR, and holographic cloud software [4].