WiMi Hologram Cloud Inc. (“WiMi” or the “Company”), a leading global Hologram Augmented Reality (“AR”) Technology provider, announced that WiMi researched on AIGC intelligent interactive interface generation system based on big data. This is a system that utilizes large-scale datasets and artificial intelligence algorithms to automatically generate intelligent interactive interfaces.
Big data plays a crucial role in the AIGC intelligent interactive interface generation system based on big data researched by WiMi. Big data does not only refer to a large amount of data, but more importantly, it contains multiple types of data and needs to be processed and analyzed by complex algorithms. First, the system collects a large amount of user data, including but not limited to user usage, search history, preferences and so on. Then, the system gives these data to AI models for training, from which it learns the user’s favorite elements and design styles, and the system automatically generates the corresponding code and design according to the needs and ideas provided by the user, in order to quickly build a high-quality intelligent interactive interface. Finally, the system will continuously improve the algorithm and enhance the quality of the generated content based on the user’s feedback information and behavioral data, and optimize the generated content and update the algorithm model to better meet the user’s needs.
This system is a complex system whose core modules include a data collection and processing module, AI model training module, code generation and design module, optimization and update module, and interface display and testing module. These modules cooperate with each other to complete the function of the whole system, which can help designers and developers quickly build high-quality intelligent interactive interfaces and improve work efficiency and productivity.
Data collection and processing
Collect user data from various data sources and process and filter this data. The data sources can include websites, applications, social media, etc. Through data collection and processing, the system can better understand the user’s preferences and needs, and provide a basis for the subsequent generation of intelligent interactive interfaces.
AI model training
Machine learning algorithms are used to analyze and model previously collected and processed user data to train an AI model. During the training process, the system learns the user’s preferred elements, design styles and interaction methods. After training, the AI model can automatically generate the appropriate code and design based on the requirements and ideas provided by the user.
SOURCE: PRNewswire