Prosecution Insights
Last updated: April 19, 2026
Application No. 18/331,765

PREDICTING ELECTRICAL COMPONENT FAILURE

Final Rejection §101
Filed
Jun 08, 2023
Examiner
YANCHUS III, PAUL B
Art Unit
2115
Tech Center
2100 — Computer Architecture & Software
Assignee
X Development LLC
OA Round
2 (Final)
83%
Grant Probability
Favorable
3-4
OA Rounds
2y 11m
To Grant
97%
With Interview

Examiner Intelligence

Grants 83% — above average
83%
Career Allow Rate
685 granted / 827 resolved
+27.8% vs TC avg
Moderate +14% lift
Without
With
+14.2%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
29 currently pending
Career history
856
Total Applications
across all art units

Statute-Specific Performance

§101
7.3%
-32.7% vs TC avg
§103
51.5%
+11.5% vs TC avg
§102
24.6%
-15.4% vs TC avg
§112
5.1%
-34.9% vs TC avg
Black line = Tech Center average estimate • Based on career data from 827 resolved cases

Office Action

§101
DETAILED ACTION This final office action is in response to amendments filed on 12/15/25. 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, 5-13, 16 and 20-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Below is an analysis in accordance with the Subject Matter Eligibility Test for Products and Process found in MPEP 2106(III). Claim 1: An electrical grid asset failure prediction method comprising: obtaining a first image that depicts a component of an electrical grid within a portion of the first image at a first time; identifying a set of second images that each depict the same of the component of the electrical grid within the images and each image represents the component of the electrical grid at a time prior to the first time; processing the first image and the set of images as first input to a first machine learning model that is configured to detect electrical component defects within images and to generate image encodings that indicate the presence and the type of any detected defects, the first machine learning model output including a set of image encodings indicating a particular defect in each of the first image and the second images; processing the set of image encodings as second input to a second machine learning model that is configured to determine a likelihood that the component of the electric grid will fail based on a type of the particular defect and a rate of change of the particular defect as identified in each of the first image and the second images; and providing, for presentation by a display, the likelihood that the component of the electric grid will fail. Step 1: The claim recites a method. Thus, the claim is to a process, which is a statutory category of invention. Step 2A Prong One: Limitation (c) in claim 1 recites “processing the first image and the set of images…to generate image encodings that indicate the presence and the type of any detected defects”. Limitation (d) in claim 1 recites “processing the set of image encodings to determine a likelihood that the component of the electric grid will fail based on a type of the particular defect and a rate of change of the particular defect as identified in each of the first image and the second images”. As is evident from applicant’s disclosure, the claimed processing falls into the “Mental Processes” group of abstract ideas because the recited determinations are simple enough that they can be practically performed in the human mind. Note that even if most humans would use a physical aid to help them complete the recited calculation or observation, the use of such physical aid does not negate the mental nature of these limitations because the claim here merely uses general purpose computer as a tool to perform the otherwise mental process. Step 2A Prong Two: Besides the abstract idea, the claim recites additional elements (a) obtaining a first image that depicts a component of an electrical grid within a portion of the first image at a first time, (b) identifying a set of second images that each depict the same of the component of the electrical grid within the images and each image represents the component of the electrical grid at a time prior to the first time, and (e) providing, for presentation by a display, the likelihood that the component of the electric grid will fail. These additional elements represent mere data gathering (obtaining images) and data display (presentation by a display) that is necessary for the use of the recited judicial exception. Accordingly, elements (a), (b) and (e) are insignificant extra-solution activity. The claim also recites in elements (c) and (d) processing using a machine learning model. The processing using a machine learning model is merely recitation of a generic processor which is recited at a high level of generality. Furthermore, the processor is recited so generically that it represents no more than mere instructions to apply the judicial exceptions on a computer. Therefore, the processing using a machine learning model in elements (c) and (d) does not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application. Step 2B: The claim as a whole does not amount to significantly more than the recited exception. The claim has additional elements: (a) obtaining a first image that depicts a component of an electrical grid within a portion of the first image at a first time, (b) identifying a set of second images that each depict the same of the component of the electrical grid within the images and each image represents the component of the electrical grid at a time prior to the first time and (e) providing, for presentation by a display, the likelihood that the component of the electric grid will fail. Additional elements (a), (b) and (e), as explained previously, are mere data gathering and data display, which is extra-solution activity and for purposes of Step 2A Prong Two was considered insignificant. Thus, limitations (a), (b) and (d) do not amount to significantly more. As explained previously, the processing using a machine learning model is at best the equivalent of merely adding the words “apply it” to the judicial exception. Mere instructions to apply an exception cannot provide an inventive concept. Examiner takes official notice that processing data using a machine learning model was well-known and conventionally used before the effective filing date of the claimed invention to analyze input data and generate output data based on the input data. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept. The claim is not eligible. Claims 5-13, 16 and 20-22 are merely just extensions or variations of the judicial exception, generally linking the use of the judicial exception to the technological environment, or insignificant extra-solution activity. Allowable Subject Matter Claims 1, 5-13, 16 and 20-22 would allowable upon resolution of the 35 USC 101 rejections. The following is an examiner’s statement of reasons for allowance: The prior art of record does not teach or suggest the combination of: obtaining a first image that depicts a component of an electrical grid within a portion of the first image at a first time, identifying a set of second images that each depict the same of the component of the electrical grid within the images and each image represents the component of the electrical grid at a time prior to the first time, processing the first image and the set of images as first input to a first machine learning model that is configured to detect electrical component defects within images and to generate image encodings that indicate the presence and the type of any detected defects, the first machine learning model output including a set of image encodings indicating a particular defect in each of the first image and the second images, and processing the set of image encodings as second input to a second machine learning model that is configured to determine a likelihood that the component of the electric grid will fail based on a type of the particular defect and a rate of change of the particular defect as identified in each of the first image and the second images. Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.” Response to Arguments Applicant’s arguments with respect to the claims have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. 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 PAUL B YANCHUS III whose telephone number is (571)272-3678. The examiner can normally be reached Monday-Friday 9am-5pm. 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, Kamini Shah can be reached at (571) 272-2279. 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. /PAUL B YANCHUS III/Primary Examiner, Art Unit 2115 March 21, 2026
Read full office action

Prosecution Timeline

Jun 08, 2023
Application Filed
Sep 30, 2025
Non-Final Rejection — §101
Dec 15, 2025
Response Filed
Mar 21, 2026
Final Rejection — §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

3-4
Expected OA Rounds
83%
Grant Probability
97%
With Interview (+14.2%)
2y 11m
Median Time to Grant
Moderate
PTA Risk
Based on 827 resolved cases by this examiner. Grant probability derived from career allow rate.

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