18060122. SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS simplified abstract (Dell Products L.P.)
Contents
- 1 SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS - 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 Original Abstract Submitted
SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS
Organization Name
Inventor(s)
OFIR Ezrielev of Beer Sheva (IL)
JEHUDA Shemer of Kfar Saba (IL)
SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18060122 titled 'SYSTEM AND METHOD FOR MANAGING INFERENCE MODEL PERFORMANCE THROUGH PROACTIVE COMMUNICATION SYSTEM ANALYSIS
Simplified Explanation
The abstract describes methods and systems for managing the execution of inference models hosted by data processing systems. The system includes an inference model manager and multiple data processing systems. The manager communicates system data to link the data processing systems and uses this data to determine if the communication system meets the inference generation requirements of the downstream consumer. If not, the manager obtains an inference generation plan to return to compliance.
- Inference model manager coordinates communication and data processing systems
- Determines if communication system meets inference generation requirements
- Obtains inference generation plan if requirements are not met
Potential Applications
This technology could be applied in various industries such as healthcare, finance, and manufacturing to optimize data processing and inference model execution.
Problems Solved
This technology solves the problem of ensuring that communication systems meet the inference generation requirements of downstream consumers, improving overall system efficiency.
Benefits
The benefits of this technology include improved data processing efficiency, better compliance with inference generation requirements, and enhanced communication between systems.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of data processing systems for large organizations looking to streamline their operations and improve decision-making processes.
Possible Prior Art
One possible prior art could be the use of communication systems in data processing to optimize system performance and ensure compliance with consumer requirements.
Unanswered Questions
How does this technology handle real-time data processing requirements?
This article does not specifically address how the system manages real-time data processing needs and if it can adapt to changing requirements on the fly.
What security measures are in place to protect the communication system data?
The article does not mention the security protocols or measures implemented to safeguard the communication system data from potential threats or breaches.
Original Abstract Submitted
Methods and systems for managing execution of inference models hosted by data processing systems are disclosed. To manage execution of inference models hosted by data processing systems, a system may include an inference model manager and any number of data processing systems. The inference model manager may communication system data for the communication system linking the data processing systems. The inference model manager may use the communication system data to determine whether the communication system meets inference generation requirements of the downstream consumer. If the communication system does not meet inference generation requirements of the downstream consumer, the inference model manager may obtain an inference generation plan to return to compliance with the inference generation requirements of the downstream consumer.
