Layered Cache Personalization Using LLM-Built User Objects

The system is divided into multiple cache layers (first cache layer near user interface, second cache layer for computationally intensive operations, third cache layer for long-term storage). Each layer handles specific types of personalization tasks, allowing the system to provide comprehensive personalization capability while distributing complexity across modular components rather than concentrating it in a single complex system.

The patent introduces a vertical dimension to cache architecture by stacking multiple cache layers at different proximity levels to the user interface. This dimensional organization allows the system to handle diverse personalization requirements efficiently - frequently accessed personalized data resides in the first cache layer, while less frequently accessed or computationally intensive personalization data resides in deeper layers, thus improving adaptability without proportionally increasing overall system complexity.

The system proactively generates and caches personalized objects before they are explicitly requested by users. The cache compute engine anticipates personalization needs by analyzing user interactions and pre-computing personalized content, storing it in appropriate cache layers. This preliminary action ensures high personalization accuracy is available when needed while avoiding the energy cost of real-time computation during user interactions.

Different cache layers are optimized for different types of personalization operations. The first cache layer is optimized for fast retrieval of frequently accessed personalized data, the second cache layer handles computationally intensive personalization tasks, and the third cache layer stores long-term personalization data. This local optimization allows the system to achieve high personalization accuracy for each specific use case while minimizing overall computing resource consumption by executing only the necessary computations in the appropriate layer.

The system pre-generates personalized objects and stores them in the cache layers before users request them. By anticipating personalization needs based on user interaction patterns and pre-computing personalized content, the system ensures high-quality user experience is delivered instantly when users interact with personalized content, while avoiding the energy waste of processing and transmitting unnecessary data in real-time.

The system creates cached copies of personalized objects and stores them in the cache layers for rapid retrieval. Instead of generating personalized content on-demand for each user interaction, the system produces copies of personalized objects in advance and stores them where they can be quickly accessed. This copying approach maintains high user experience quality while dramatically improving data flow efficiency by eliminating redundant real-time processing.

The caching system is segmented into multiple layers with different proximity to the user interface and different memory capacity characteristics. The first cache layer, positioned near the user interface, stores only the most frequently accessed personalized objects to ensure fast access speed. Less frequently accessed personalized objects are stored in the second and third cache layers with larger capacity but slower access. This segmentation allows the system to optimize for speed where it matters most while managing overall memory resource usage across the distributed cache structure.

The system dynamically adjusts caching parameters such as cache size, eviction policies, and data placement decisions based on access patterns and system conditions. By changing parameters like the amount of data stored in the first cache layer versus deeper layers, the system can optimize the balance between access speed and memory resource usage according to current workload demands and available memory capacity.