Excellent large-scale processing capabilities
OxyGent's distributed architecture excels at handling large-scale real-time decisions.
Its key technical features include:
- Linear Scaling: Distributed scheduler ensures that system resource usage grows linearly with task size
- Efficient scheduling: supports concurrent operation of thousands of intelligences to meet the real-time optimization needs of finance, logistics and other fields
- Performance guarantee: system response latency is controlled in milliseconds in official benchmarks
In practice, logistics companies can use this feature to dynamically adjust distribution routes, and financial institutions can realize real-time risk monitoring. All these scenarios require the system to have strong real-time processing capabilities, and OxyGent is designed to meet these needs.
This answer comes from the articleOxyGent: Python open source framework for rapidly building intelligent systemsThe
May not be reproduced without permission:AI productivity tools " OxyGent's Distributed Scheduling Supports Large-Scale Real-Time Decision-Making at Industry-Leading Levels
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