Prosecution Insights
Last updated: April 19, 2026
Application No. 17/832,733

NEURAL NETWORK SYSTEM, NEURAL NETWORK LEARNING METHOD, AND NEURAL NETWORK LEARNING PROGRAM

Final Rejection §101
Filed
Jun 06, 2022
Examiner
TRAN, TAN H
Art Unit
2141
Tech Center
2100 — Computer Architecture & Software
Assignee
Fujitsu Limited
OA Round
2 (Final)
60%
Grant Probability
Moderate
3-4
OA Rounds
3y 6m
To Grant
92%
With Interview

Examiner Intelligence

Grants 60% of resolved cases
60%
Career Allow Rate
184 granted / 307 resolved
+4.9% vs TC avg
Strong +32% interview lift
Without
With
+31.8%
Interview Lift
resolved cases with interview
Typical timeline
3y 6m
Avg Prosecution
60 currently pending
Career history
367
Total Applications
across all art units

Statute-Specific Performance

§101
14.4%
-25.6% vs TC avg
§103
55.3%
+15.3% vs TC avg
§102
19.2%
-20.8% vs TC avg
§112
6.1%
-33.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 307 resolved cases

Office Action

§101
Notice of Pre-AIA or AIA Status 1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . DETAILED ACTION 2. This Office Action is sent in response to Applicant’s Communication received on 08/06/2025 for application number 17/832,733. Response to Amendments 3. The Amendment filed 08/06/2025 has been entered. Claims 1-10 have been amended. Claims 1-10 remain pending in the application. Response to Arguments Applicant argues that Claim 1 includes technical features such as, for example, "in a second case in which it is true that the plurality of the cumulative amounts of the gradient or update amount is less than the threshold value, the plurality of processors executes a second update processing for updating the respective parameters with the gradient or update amount (not the aggregated cumulative amount of the gradient or update amount as the first update processing) which the plurality of processors respectively calculates, without aggregating the plurality of the cumulative amounts of the gradient or update amount through transmission." Therefore, the claim 1 recites a technical feature of reducing the learning time of a computer that performs federated learning, in which a plurality of processors transmits the gradients or update amounts calculated by each processor among the plurality of processors and aggregate them in every learning steps. Claim 1 integrates an abstract idea into a practical application and is not directed to an abstract idea as a judicial exception (NO in Prong 2 of Step 2A), and is patent eligible. Examiner respectfully disagrees and notes that claim 1 recites mathematical operations, including: executing neural network computations, calculating gradients and update amounts, accumulating values, comparing cumulative amounts to a threshold, and branching between aggregation or local update. These limitations are mathematical concepts. Furthermore, the claim recites only a “memory” and “plurality of processors configured to access the memory and communicate with each other.” These generic computer elements that merely execute the mathematical steps. The USPTO guidance makes clear that merely applying an abstract idea using generic computer components does not constitute integration into a practical application. Claim Rejections - 35 USC § 101 4. 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the abstract idea without significantly more. Step 1, the claims are directed to the statutory categories of a method, system and medium. Step 2A Prong 1, Claims 1, 9, and 10 recite, in part, calculate at least one output of the neural network, calculates a gradient to the parameter of a difference between the calculated output and supervised data of the training data or an update amount based on the gradient, and calculates a cumulative amount of the gradient or update amount, in a first case in which it is false that a plurality of cumulative amounts of the gradient or update amount respectively calculated is less than a threshold value, the plurality of cumulative amounts of the gradient or update amount respectively calculated to aggregate the plurality of the cumulative amounts of the gradient or update amount, receiving the aggregated cumulative amount of the gradient or update amount, updating the parameter with the aggregated cumulative amount of the gradient or update amount, and resetting the cumulative amount of the gradient or update amount, and in a second case in which it is true that the plurality of the cumulative amounts of the gradient or update amount is less than the threshold value, a second update processing for updating the respective parameters with the gradient or update amount which calculates, without aggregating the plurality of the cumulative amounts of the gradient or update amount. These operations (e.g. gradient computation, threshold comparison, aggregation) are directed to “Mathematical Concept” grouping of abstract ideas. Accordingly, the claims recite an abstract idea. Step 2A Prong 2, this judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of “plurality of processors” and “memory”. The computer components in the claim are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Please see MPEP §2106.04.(a)(2).III.C. The claims also recite the additional element of “a plurality of processors configured to access the memory and communicate with each other, in each of a plurality of iterations of learning, the plurality of processors each, by using training data for each of the plurality pf processors, and in parallel, executes a computational operation of a neural network based on a plurality of input of the training data, transmitting, among the plurality of processors” and “neural network”. This limitation is recited at a high level of generality and provide no details on how this process is performed. The additional elements in the claims merely used as a tool to implement the abstract idea. Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, either alone or in combination. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “plurality of processors”, “memory”, “a plurality of processors configured to access the memory and communicate with each other, in each of a plurality of iterations of learning, the plurality of processors each, by using training data for each of the plurality pf processors, and in parallel, executes a computational operation of a neural network based on a plurality of input of the training data, transmitting, among the plurality of processors” and “neural network” to perform the steps of the claims amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Please see MPEP §2106.05(b) and (g). The claim is not patent eligible. Claim 2 provides further limitations of “executes the second update processing, if, in the first case, a number of iterations of learning in which the second update processing was successively performed is less than a first reference number”. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea (adding insignificant extra-solution activity to the judicial exception). Claim 3 provides further limitations of “executes the first update processing and reset the number of iteration of learning, if, in the second case, the number of iterations of learning is not less than a second reference number greater than the first reference number”. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea (adding insignificant extra-solution activity to the judicial exception). Claim 4 provides further limitations of “executes the second update processing in the second case, if the number of iterations of learning is not less than the first reference number and is less than the second reference number”. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea (adding insignificant extra-solution activity to the judicial exception). Claim 5 provides further limitations of “executes the first update processing, if, in the second case, the number of iterations of learning is not less than the second reference number”. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea (adding insignificant extra-solution activity to the judicial exception). Claim 6 provides further limitations “wherein, in the first case, at least one of the cumulative amounts of the gradients gradient or update amounts amount among the plurality of the cumulative amounts of the gradient or update amount respectively calculated is not less than the threshold value” to the abstract idea (Mathematical concepts, including relationships, formulas, equations, or calculations) as rejected above. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea. Claim 7 provides further limitations “wherein aggregation of the plurality of the cumulative amounts of the gradient or update amount is performed by one of adding the plurality of the cumulative amounts of the gradient or update amount, or obtaining a maximum value of the plurality of the cumulative amounts of the gradient or update amount” to the abstract idea (Mathematical concepts, including relationships, formulas, equations, or calculations) as rejected above. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea. Claim 8 provides further limitations “wherein the aggregated cumulative amounts of the gradient or update amount is a value obtained by accumulating the plurality of cumulative amounts of the gradient or update amount over the iterations of second update processing, and averaging the cumulative amount of the gradient or update amount” to the abstract idea (Mathematical concepts, including relationships, formulas, equations, or calculations) as rejected above. However, they do not disclose any additional elements that would amount to a practical application or significantly more than an abstract idea. Allowable Subject Matter Claims 1-10 would be allowable if the 35 U.S.C. § 101 for being directed to an abstract idea is successfully addressed. Conclusion THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action. It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)). Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAN TRAN whose telephone number is (303)297-4266. The examiner can normally be reached on Monday - Thursday - 8:00 am - 5:00 pm MT. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kieu Vu can be reached on 571-272-4057. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /TAN H TRAN/Primary Examiner, Art Unit 2141
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Prosecution Timeline

Jun 06, 2022
Application Filed
May 05, 2025
Non-Final Rejection — §101
Aug 06, 2025
Response Filed
Sep 18, 2025
Final Rejection — §101 (current)

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Prosecution Projections

3-4
Expected OA Rounds
60%
Grant Probability
92%
With Interview (+31.8%)
3y 6m
Median Time to Grant
Moderate
PTA Risk
Based on 307 resolved cases by this examiner. Grant probability derived from career allow rate.

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