Prosecution Insights
Last updated: October 02, 2026
Application No. 18/833,235

MODEL TRAINING METHODS AND APPARATUS

Non-Final OA §101
Filed
Jul 25, 2024
Priority
Jun 16, 2022 — CN 202210689425.2 +1 more
Examiner
MIAN, MUHAMMAD U
Art Unit
Tech Center
Assignee
Beijing Volcano Engine Technology Co., Ltd.
OA Round
1 (Non-Final)
67%
Grant Probability
Favorable
1-2
OA Rounds
7m
Est. Remaining
90%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allowance Rate
247 granted / 368 resolved
+7.1% vs TC avg
Strong +22% interview lift
Without
With
+22.4%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
19 currently pending
Career history
393
Total Applications
across all art units

Statute-Specific Performance

§101
23.3%
-16.7% vs TC avg
§103
47.9%
+7.9% vs TC avg
§102
8.5%
-31.5% vs TC avg
§112
15.3%
-24.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 368 resolved cases

Office Action

§101
DETAILED ACTION Remarks This Office Action is in response to the application 18/833235 filed on 25 July 2024. Claims 1-8, 10-11, and 13-22 have been examined. 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 § 101 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 1-8, 10-11, and 13-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. As to claims 1, 10, and 11, these claims recite segmenting task data to obtain a plurality of consecutive slice data. The claims do not specify nor place any limits upon the claimed “task data” and “slice data.” The broadest reasonable interpretation (BRI) of these limitations encompass a small amount of task data and slice data comprising just a few records/items each. Given that the BRI of the claims encompasses such a simple, a human could mentally perform the claimed segmenting with the aid of pencil and paper. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind (and/or with a pencil and paper) but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. These claims also recite generating a task to be processed based on slice data to be processed. The claims do not specify any details of the claimed “generating” or how it is performed, nor do they specify any details of the claimed “task.” Hence, the claims encompass any method for generating the task, and under the BRI, the claims encompass the simplest possible task. Given that the BRI of the claims encompasses such a simple case, a human could mentally perform the claimed generating of a task with the aid of pencil and paper. Hence, this limitation is also an abstract idea under the “Mental Processes” grouping. These claims also recite determining a target model trainer based on a task execution progress of each model trainer involved in model training. The claimed determination amounts to no more that a series of judgements/evaluations. Given that the BRI of the claims encompasses a simple case, as set forth above, a human could mentally perform the claimed determination with the aid of pencil and paper. Hence, this limitation is an abstract idea under the “Mental Processes” grouping. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. Other than the abstract idea, the claims recite the following: a) “sequentially caching the slice data in a slice data queue which is configured to dynamically maintain processing situations of the slice data;” b) “invoking a task distribution thread to read a slice data to be processed from the slice data queue;” c) “distributing the task to be processed to the target model trainer and instructing the target model trainer to execute the task to be processed;” d) a “task segmentation thread” and a “task distribution thread,” “wherein the task segmentation thread and the task distribution thread run in parallel;” e) an electronic device comprising a memory storing computer program instructions for a processor; f) a non-transitory readable storage medium storing computer program instructions. Limitations (a) and (b) amounts to no more than mere data gathering, which has been deemed by the courts to be insignificant extra-solution activity. See MPEP 2106.05(g). Limitations (c) and (d) are recited at a high level of generality and amount to mere instructions to apply the abstract idea on a general purpose computer, which cannot be deemed a practical application. See MPEP 2106.05(f). Limitations (e) and (f) are recited at a high level of generality, i.e. as generic computer components performing generic computing functions. 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. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity and/or generic computer implementation. Hence, the claim as a whole, looking at the additional elements individually and in combination, does not integrate the abstract idea into a practical application. The claim is directed to an abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Limitations (a) and (b) amount to no more than mere data gathering, which has been deemed by the courts to be insignificant extra-solution activity. See MPEP 2106.05(g). In addition, the courts have deemed receiving data to be well-understood, routine, and conventional activity, as in the following cases: Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015) (storing and retrieving information in memory). See MPEP 2106.05(d)(II). Limitations (c) and (d) are recited at a high level of generality and amount to mere instructions to apply the abstract idea on a general purpose computer, which cannot be deemed a practical application. See MPEP 2106.05(f). As discussed above with respect to integration of the abstract idea into a practical application, additional elements (e) and (f) amount to no more than mere field of use limitations and instructions to apply the exception using generic computer components. Mere instructions to apply an exception using conventional computer components and functions cannot provide an inventive concept. Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity; well-understood, routine, and conventional subject matter; and/or generic computer implementation. Hence, the claim as a whole, looking at the additional elements individually and in combination, does not amount to significantly more than the abstract idea. These claims are not patent eligible. As to dependent claims 2, 13, and 18, these claims recite certain details about how determining the target model trainer is performed. However, given that the BRI of the claims encompasses a simple case, as set forth above, nothing in these claims goes beyond what a human could mentally perform with the aid of pencil and paper. Hence, these claims recite an abstract idea under the “Mental Processes” grouping. As to dependent claims 3-8, 14-17, and 19-22, these claims recite limitations that amount to merely reading and writing data, which is insignificant extra solution activity in the form of mere data gathering. As set forth above in the parent claims, mere data gathering that is well-understood, routine, and conventional cannot deemed a practical application nor an inventive concept. See MPEP 2106.05(g) and the cases cited at MPEP 2106.05(d)(II). Looking at the additional elements as a whole adds nothing beyond the additional elements considered individually—they still represent insignificant extra-solution activity; well-understood, routine, and conventional subject matter; and/or generic computer implementation. Hence, the claim as a whole, looking at the additional elements individually and in combination, does not amount to a practical application nor significantly more than the abstract idea. These claims are not patent eligible. Additional Art Considered The prior art made of record and not relied upon is considered pertinent to the Applicants’ disclosure. The following patents and papers are cited to further show the state of the art at the time of Applicants’ invention with respect to distributed machine learning model training. a. Wu et al.; “METHOD AND APPARATUS FOR PERFORMING DISTRIBUTED TRAINING ON DEEP LEARNING MODEL, DEVICE AND STORAGE MEDIUM”; U.S. PGPub. No. 20220374713 A1. Teaches distributed training of a deep learning model including a target segmentation strategy of a distributed training task based on the distributed computation view and the cluster resource view (see abstract and para. 0005-0008). b. Wang et al.; “DISTRIBUTED TRAINING METHOD BASED ON END-TO-END ADAPTION, AND DEVICE”; U.S. PGPub. No. 20230169351 A1. Teaches a distributed machine learning training method that involves slicing a model to be trained, determining a distribution strategy, and performing distributed training based on the distribution strategy (see abstract and para. 0004-0008). c. Yang et al.; “GLOBAL FEDERATED TRAINING FOR NEURAL NETWORKS”; U.S. PGPub. No. 20220076133 A1. Teaches distributed training framework for a neural network including performing image segmentation (see abstract and para. 0078 and 0120) and parallel multi-threaded operation (see para. 0177 and 0370-0373). Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to UMAR MIAN whose telephone number is (571)270-3970. The examiner can normally be reached Monday to Friday, 10 am to 6:30 pm. 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, Tony Mahmoudi can be reached on (571) 272-4078. 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. /Umar Mian/ Primary Examiner, Art Unit 2163
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Prosecution Timeline

Jul 25, 2024
Application Filed
Sep 10, 2026
Non-Final Rejection mailed — §101 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
67%
Grant Probability
90%
With Interview (+22.4%)
2y 10m (~7m remaining)
Median Time to Grant
Low
PTA Risk
Based on 368 resolved cases by this examiner. Grant probability derived from career allowance rate.

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