Technological Breakthroughs in Dynamic Memory Management
MemOS uses a patent-level MemScheduler component to realize intelligent allocation of memory resources. The mechanism's task type-based adaptive allocation strategy contains three major innovations:
- Attention weight-based hotspot memory prediction algorithm
- Hierarchical memory elimination (eviction) strategies
- Real-time Load Balancing Optimizer
Experiments on a standardized review set show that the technique reduces the latency of long text processing over 512k by 731 TP3T, while maintaining an accuracy improvement of 38.981 TP3T. Typical examples include:
- Legal Contract Analysis Scenarios Achieve 98% Clause Correlation Accuracy
- Medical Records Traceability Task Reduces Retrieval Time for 60%
The system supports policy fine-tuning through the scheduler.yaml file to meet the QoS requirements of different business scenarios.
This answer comes from the articleMemOS: An Open Source System for Enhancing the Memory Capacity of Large Language ModelsThe
May not be reproduced without permission:AI productivity tools " MemOS's Memory Scheduling Mechanism Significantly Improves Long-Context Task Performance
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