Dell products l.p. (20240103991). HCI PERFORMANCE CAPABILITY EVALUATION simplified abstract
Contents
- 1 HCI PERFORMANCE CAPABILITY EVALUATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 HCI PERFORMANCE CAPABILITY EVALUATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Unanswered Questions
- 1.11 Original Abstract Submitted
HCI PERFORMANCE CAPABILITY EVALUATION
Organization Name
Inventor(s)
HCI PERFORMANCE CAPABILITY EVALUATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240103991 titled 'HCI PERFORMANCE CAPABILITY EVALUATION
Simplified Explanation
The abstract describes a patent application for an information handling system that uses artificial intelligence to predict whether a target system can handle a desired workload.
- The information handling system includes at least one processor and memory.
- It receives configuration data and evaluation data for the target system to train an AI model.
- The system also receives information about the desired workload for the target system.
- Based on the AI model, it predicts whether the target system can satisfy the desired workload.
Potential Applications
This technology could be applied in various industries such as IT, cloud computing, and data centers to optimize system performance and resource allocation.
Problems Solved
This technology helps in predicting system performance and capacity, allowing for better planning and resource management.
Benefits
The benefits of this technology include improved efficiency, reduced downtime, and better utilization of resources.
Potential Commercial Applications
Optimizing system performance and predicting workload capacity can have commercial applications in cloud service providers, data centers, and IT consulting firms.
Possible Prior Art
One possible prior art could be predictive analytics software used in IT systems to forecast performance and capacity.
Unanswered Questions
How accurate are the predictions made by the AI model?
The accuracy of the predictions made by the AI model is crucial for the success of this technology. Further research and testing may be needed to determine the reliability of the predictions.
What are the limitations of the information handling system in terms of scalability?
Understanding the scalability limitations of the information handling system is essential for deploying this technology in large-scale environments. Further analysis and testing may be required to assess the system's scalability.
Original Abstract Submitted
an information handling system may include at least one processor and a memory. the information handling system may be configured to: receive configuration data and evaluation data regarding a target information handling system; train an artificial intelligence (ai) model based on the configuration data and evaluation data; receive information regarding a desired workload for the target information handling system; and predict, based on the ai model, whether or not the target information handling system will be able to satisfy the desired workload.
