International business machines corporation (20240104368). REDUCTION OF DATA TRANSMISSION AND DATA STORAGE USING NEURAL NETWORK TECHNOLOGY simplified abstract
Contents
- 1 REDUCTION OF DATA TRANSMISSION AND DATA STORAGE USING NEURAL NETWORK TECHNOLOGY
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 REDUCTION OF DATA TRANSMISSION AND DATA STORAGE USING NEURAL NETWORK TECHNOLOGY - 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
REDUCTION OF DATA TRANSMISSION AND DATA STORAGE USING NEURAL NETWORK TECHNOLOGY
Organization Name
international business machines corporation
Inventor(s)
Paula Kim Ta-shma of Tel Aviv-Jaffa (IL)
REDUCTION OF DATA TRANSMISSION AND DATA STORAGE USING NEURAL NETWORK TECHNOLOGY - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240104368 titled 'REDUCTION OF DATA TRANSMISSION AND DATA STORAGE USING NEURAL NETWORK TECHNOLOGY
Simplified Explanation
The abstract describes a system where a hub in a computing environment receives a training set from an edge of the environment, which includes data used to train a neural network at the hub. The training results in a detector and a generator at the hub, and once training is complete, the detector is sent to the edge to suppress additional edge data based on similarity to the training data.
- The system involves a hub in a computing environment receiving a training set from an edge.
- The training set is used to train a neural network at the hub, resulting in a detector and a generator.
- Once training is complete, the detector is sent to the edge to suppress additional edge data based on similarity to the training data.
Potential Applications
This technology could be applied in various fields such as:
- Internet of Things (IoT) devices
- Autonomous vehicles
- Healthcare monitoring systems
Problems Solved
This technology helps in:
- Reducing unnecessary data transmission
- Improving efficiency in data processing
- Enhancing data security and privacy
Benefits
The benefits of this technology include:
- Optimizing network bandwidth usage
- Enhancing real-time data analysis
- Improving overall system performance
Potential Commercial Applications
A potential commercial application for this technology could be in:
- Smart home devices
- Industrial automation systems
- Telecommunication networks
Possible Prior Art
One possible prior art for this technology could be:
- Edge computing systems that optimize data processing and transmission.
Unanswered Questions
How does the system handle edge data that is not similar to the training data?
The abstract does not provide information on how the system deals with edge data that is not statistically similar to the training data.
What criteria are used to determine the similarity between edge data and training data?
The abstract does not specify the criteria used to determine the statistical similarity between edge data and training data.
Original Abstract Submitted
a hub of a computing environment obtains a training set from an edge of the computing environment. the training set that is obtained includes data from the edge and is used to train a neural network at the hub. the training of the neural network provides a detector and a generator at the hub. a determination is made as to whether the training of the neural network is complete. based on determining that the training of the neural network is complete, the detector is sent to the edge. the detector at the edge is to facilitate suppression of additional edge data to the hub based on the detector at the edge determining that the additional edge data is statistically similar, based on one or more selected criteria, to data used to train the neural network.