Prosecution Insights
Last updated: May 29, 2026
Application No. 17/957,889

METHOD, APPARATUS, AND DEVICE FOR OBTAINING ARTIFICIAL INTELLIGENCE MODEL, AND STORAGE MEDIUM

Final Rejection §112
Filed
Sep 30, 2022
Priority
Mar 31, 2020 — CN 202010246686.8 +1 more
Examiner
SANKS, SCHYLER S
Art Unit
2129
Tech Center
2100 — Computer Architecture & Software
Assignee
Huawei Technologies Co., Ltd.
OA Round
2 (Final)
72%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
88%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allowance Rate
367 granted / 507 resolved
+17.4% vs TC avg
Strong +16% interview lift
Without
With
+16.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
24 currently pending
Career history
542
Total Applications
across all art units

Statute-Specific Performance

§101
0.6%
-39.4% vs TC avg
§103
75.3%
+35.3% vs TC avg
§102
6.4%
-33.6% vs TC avg
§112
17.2%
-22.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 507 resolved cases

Office Action

§112
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1-8, 13-19, and 21-22 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Regarding claims 1 and 13, “the at least one target neuron” lacks antecedent basis in the claims. Regarding claims 1 and 13, “a group of client devices” renders the claim indefinite because it is unclear if “client devices” indicates a group of client devices as describe in the claim or if the client device is in a group of client devices where the other client devices in the group are not necessarily the same as the previously defined client devices. Regarding claims 2, 4, 6, 8, and 21, “the at least one target neuron” lacks antecedent basis in the claims. Claims 2-8, 14-19, and 21-22 are indefinite by virtue of dependency on claims 1 or 13, accordingly. Allowable Subject Matter Claims 1 and 13 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action. Claims 2, 4, 6, 8, and 21 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims. Notwithstanding the above in ¶9, claims 2-8, 14-19, and 21-22 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: Independent claims 1 and 13 each recite locally training a model based on an active flag bit associated with at least one target neuron. The parameter data for the at least one target neuron, after local training, is then transferred to the global model to train a global model to convergence, where each of a plurality of client devices send their parameters. The above scheme is a specific form of federated learning. Federated learning is well known in the prior art. Furthermore, as noted in the previous rejection, it is known to utilize active-flag bits in neural networks to indicate where training should occur. The prior art does not anticipate or render obvious the claimed combination of the federated learning and active-flag bit training as claimed in claims 1 and 13. While each methodology is known in its own right, there is insufficient nexus between them in the prior art to lead one of ordinary skill in the art to arrive at the claimed invention without impermissible hindsight. Response to Arguments Applicant’s arguments filed 12/26/2025 have been fully considered. Applicant’s arguments are generally persuasive but specific reasons for indicating allowable subject matter are given above. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SCHYLER S SANKS whose telephone number is (571)272-6125. The examiner can normally be reached 06:30 - 15:30 Central Time, M-F. 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, Michael Huntley can be reached at (303) 297-4307. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /SCHYLER S SANKS/Primary Examiner, Art Unit 2129
Read full office action

Prosecution Timeline

Sep 30, 2022
Application Filed
Jan 24, 2023
Response after Non-Final Action
Sep 26, 2025
Non-Final Rejection mailed — §112
Dec 26, 2025
Response Filed
Mar 26, 2026
Final Rejection mailed — §112 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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AUTOMATED FEATURE ENGINEERING FOR MACHINE LEARNING MODELS
4y 8m to grant Granted May 19, 2026
Patent 12632787
SYSTEMS AND METHODS FOR TRAINING MACHINE LEARNING MODELS USING GENERATED FACETED MODELS
3y 5m to grant Granted May 19, 2026
Patent 12619896
Bayesian Optimal Model System (BOMS) for Predicting Equilibrium Ripple Geometry and Evolution
3y 10m to grant Granted May 05, 2026
Patent 12614114
INTERNET-OF-THINGS-ORIENTED MACHINE LEARNING CONTAINER IMAGE DOWNLOAD METHOD AND SYSTEM
3y 3m to grant Granted Apr 28, 2026
Patent 12602588
NEURAL NETWORK MODEL OPTIMIZATION METHOD BASED ON ANNEALING PROCESS FOR STAINLESS STEEL ULTRA-THIN STRIP
3y 2m to grant Granted Apr 14, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
72%
Grant Probability
88%
With Interview (+16.0%)
2y 10m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 507 resolved cases by this examiner. Grant probability derived from career allowance rate.

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