USPTO Patent Grant for Data Generation Device and Learning Method
Summary
The USPTO has granted a patent (US12582959B2) to FUJIFILM Corporation for a data generation device and learning method. This patent covers a system designed to create datasets for training neural networks used in product manufacturing processes.
What changed
The United States Patent and Trademark Office (USPTO) has issued patent US12582959B2 to FUJIFILM Corporation for a novel data generation device and associated learning method. The patent describes a system that creates a dataset comprising multiple pieces of learning data for training neural networks. These networks are intended to predict production results based on input process conditions in a manufacturing context. The method involves setting a large number of process conditions (at least 2xM0, where M0 is the total number of connection weights in the neural network), acquiring production results for each condition, and generating a dataset from this information.
This patent grant is primarily of interest to entities involved in AI development, machine learning, and manufacturing technology. While it does not impose new regulatory obligations on businesses, it represents a significant intellectual property asset for FUJIFILM Corporation in the field of AI-driven manufacturing. Compliance officers should note this as a development in the IP landscape related to AI and data generation technologies, particularly for companies operating in or licensing technology within the advanced manufacturing sector.
Source document (simplified)
Data generation device and method, and learning device and method
Grant US12582959B2 Kind: B2 Mar 24, 2026
Assignee
FUJIFILM Corporation
Inventors
Masataka Hasegawa
Abstract
A data generation device generates a data set consisting of a plurality of pieces of learning data for training a neural network in which a plurality of layers are connected by a plurality of connection weights, the neural network outputting a production result corresponding to a process condition in a case where the process condition is input in a process for producing a product. At this time, assuming that a total number of the connection weights of the neural network is M0, a plurality of the process conditions of 2×M0 or more are set. In addition, a production result corresponding to each of the plurality of process conditions is acquired, which is derived by producing the product under each of the plurality of process conditions. The plurality of pieces of learning data consisting of the plurality of process conditions and the production result are generated as the data set.
CPC Classifications
G06N 3/04
Filing Date
2021-08-20
Application No.
17407770
Claims
4
Named provisions
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