18038211. PROCESSING METHOD, PROCESSING SYSTEM, AND PROCESSING PROGRAM simplified abstract (NIPPON TELEGRAPH AND TELEPHONE CORPORATION)

PROCESSING METHOD, PROCESSING SYSTEM, AND PROCESSING PROGRAM

Organization Name

NIPPON TELEGRAPH AND TELEPHONE CORPORATION

Inventor(s)

Kyoku Shi of Musashino-shi, Tokyo (JP)

Shohei Enomoto of Musashino-shi, Tokyo (JP)

Takeharu Eda of Musashino-shi, Tokyo (JP)

Akira Sakamoto of Musashino-shi, Tokyo (JP)

PROCESSING METHOD, PROCESSING SYSTEM, AND PROCESSING PROGRAM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18038211 titled 'PROCESSING METHOD, PROCESSING SYSTEM, AND PROCESSING PROGRAM

Simplified Explanation

The processing method described in the abstract involves performing first inference in an edge device and second inference in a server device, determining changes in the target data group, and executing relearning of models based on these changes.

• The method involves determining if there is a change in the tendency of the target data group based on variations in load or decrease in inference accuracy in either the edge device or the server device.
• If a change is detected, relearning of the models that perform the inference is executed to adapt to the new tendencies.

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 addresses the following issues:

• Adapting to changes in data patterns
• Maintaining inference accuracy in dynamic environments

Benefits

The benefits of this technology include:

• Improved inference accuracy
• Adaptability to changing data patterns
• Enhanced performance in edge and server devices

Potential Commercial Applications

Optimized for SEO: "Inference Relearning Technology for Edge and Server Devices in IoT Applications"

• Smart home devices
• Industrial automation systems
• Surveillance and security systems

Possible Prior Art

There may be prior art related to:

• Adaptive machine learning models
• Dynamic inference systems

What are the potential security implications of implementing this technology?

Implementing this technology could raise concerns about data privacy and security, especially if the relearning process involves sensitive information. Companies using this technology must ensure robust security measures to protect data during the inference and relearning processes.

How does this technology compare to traditional inference methods in terms of efficiency and accuracy?

Traditional inference methods may not be able to adapt to changing data patterns as effectively as the proposed technology. By relearning models based on variations in load or accuracy, this technology can potentially offer higher efficiency and accuracy in inference tasks.

Original Abstract Submitted

A processing method executed by a processing system that performs first inference in an edge device and performs second inference in a server device, the processing method includes determining whether or not a tendency of a target data group on which inference is performed is changed in at least one of the edge device or the server device on a basis of a variation in load or a decrease in inference accuracy in at least one of the edge device or the server device, and executing relearning of at least one of a first model that performs the first inference or a second model that performs the second inference in a case where it is determined that the tendency of the target data group is changed.