Prosecution Insights
Last updated: August 17, 2026
Application No. 18/975,308

AI GENERATED GAME SUMMARY

Non-Final OA §101§102§103
Filed
Dec 10, 2024
Examiner
ROWLAND, STEVE
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Sony Group Corporation
OA Round
1 (Non-Final)
78%
Grant Probability
Favorable
1-2
OA Rounds
11m
Est. Remaining
95%
With Interview

Examiner Intelligence

Grants 78% — above average
78%
Career Allowance Rate
837 granted / 1077 resolved
+7.7% vs TC avg
Strong +18% interview lift
Without
With
+17.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 7m
Avg Prosecution
33 currently pending
Career history
1098
Total Applications
across all art units

Statute-Specific Performance

§101
14.6%
-25.4% vs TC avg
§103
33.7%
-6.3% vs TC avg
§102
29.0%
-11.0% vs TC avg
§112
14.7%
-25.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1077 resolved cases

Office Action

§101 §102 §103
Detailed Action 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a sequence of calculations which are analogous to a series of steps performable by a human mind. The claim(s) recite(s), inter alia, input to one or more machine learning (ML) models information related to play of a computer game execute the one or more ML models to generate a report identifying at least a first portion of the computer game having a first quality and at least a second portion of the computer game having a second quality identify text related to play of a computer game input the text to one or more machine learning (ML) models use output of the one or more ML models to change the computer game inputting information related to plural game play sessions of a computer game to one or more ML models executing the ML models to output indication of game play Under the broadest reasonable interpretation, claims 1 and 10 recite limitations performable in the human mind. Regarding claims 1, 10 and 17, a human—using their mind, pen, and paper—is capable of synthesizing textual information, analyzing the information using a model, identifying a plurality of qualities regarding the information to create model output, and using the output to modify a game. The abstract idea is not integrated into a practical application. The claims recite the additional elements of a processor, a memory, a computer game, and a machine learning model. Processor and memory: are depicted in Fig. 1 with a high degree of generality. Specific features are not claimed. Therefore, it would be reasonable to interpret these as routine and conventional computing components. Computer game: is recited with a high degree of generality and is nothing is claimed that limits the game as requiring a computer to run. Therefore, the feature can be regarded as a conventional game that can be performed using a human mind, pen and paper. Using a machine-learning model: Under the broadest reasonable interpretation of the claims, simply declaring that certain functions are performed by artificial intelligence per se amounts to an abstract human-performable mental step. If the claims were amended to specify the types of AI or machine learning algorithms used, and how they are applied to produce the given result, they could then meet the eligibility under the requirements of this section as non-practicably human-performable steps. The additional elements, when considered individually and in combination are not enough to qualify as significantly more than the abstract idea. The additional elements which were interpreted under step 2A prong 2 are re-evaluated in step 2B, and evidence is known that they are nothing more than what is well-understood, routine, and conventional at the time of filing. Using a machine-learning model: These steps are analogous to step (d) of claim 2 in Example 47 of the July 2024 Subject Matter Eligibility Examples.1 The example employs using a type of AI to search for anomalies in a data set, which resembles the recited “execute the one or more ML models to generate a report identifying at least a first portion of the computer game.” The analysis of Example 47 states: Step (d) recites detecting one or more anomalies in a data set using the trained ANN. Under its broadest reasonable interpretation when read in light of the specification, the “detecting” encompasses mental observations or evaluations that are practically performed in the human mind. For example, the claimed detecting of anomalies in a data set encompasses observing data in a data set and performing an evaluation by comparing anomalous and non-anomalous data … Under its broadest reasonable interpretation when read in light of the specification, the “analyzing” encompasses mental processes practically performed in the human mind by observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III. Claims 2-9, 11-16 and 18-20 are similarly human-performable to claims 1 and 10, and are thus also held as ineligible subject matter under 101/Alice for the reasons given supra. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: (a) A person shall be entitled to a patent unless— (1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention Claims 1, 2, 5-7, 17, 18 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Mattar et al (US 2022/0032202 A1). Regarding claim 1, Mattar discloses an apparatus comprising at least one processor system (Fig. 4C) configured to input to one or more machine learning (ML) models, information related to play of a computer game (506: provide gameplay session data), and execute the one or more ML models to generate a report identifying at least a first portion of the computer game having a first quality and at least a second portion of the computer game having a second quality (506: identify game events). Regarding claim 2, Mattar discloses wherein the information comprises captured clips of the computer game (¶ [0112]: visual images of game play). Regarding claim 5, Mattar discloses wherein the information comprises captured comments of gamers playing the computer game (¶ [0051]: player commentary). Regarding claim 6, Mattar discloses wherein the information comprises text related to the captured clips (Fig. 4C: Comments). Regarding claim 7, Mattar discloses wherein the information comprises internet comments related to the computer game (Fig. 4C: Comments). Regarding claim 17, Mattar discloses inputting information related to plural game play sessions of a computer game to one or more ML models (506: provide gameplay session data), and executing the ML models to output indication of game play (506: identify game events). Regarding claim 18, Mattar discloses wherein the information comprises output of one or more ML models (508). Regarding claim 20, Mattar discloses wherein the information comprises captured clips of the computer game and/or number of views of the captured clips and/or number of views of clips similar to the captured clips and/or comments of gamers playing the computer game (¶ [0112]: visual images of game play). . Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. If this application names joint inventors, Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claims 8, 10, 11, 14-16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Mattar in view of Keilwert et al (US 2021/0043031 A1). Regarding claim 8, Keilwert suggests—where Mattar does not disclose—wherein the processor system is configured to change the computer game using output of the one or more ML models (¶ [0072]: AI implementation may modify or alternate presentations and animations to emphasize or reduce game impact It would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the invention to combine the disclosures of Mattar and Keilwert in order to increase player satisfaction. Regarding claim 10, Mattar discloses an apparatus comprising computer memory that is not a transitory signal (Fig. 4C) and that comprises instructions executable by at least one processor system to identify text related to play of a computer game (¶ [0051]: player commentary) and input the text to one or more machine learning (ML) models (506: provide gameplay session data). Keilwert suggests—where Mattar does not disclose—using the output of the one or more ML models to change the computer game (¶ [0072]: AI implementation may modify or alternate presentations and animations to emphasize or reduce game impact). It would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the invention to combine the disclosures of Mattar and Keilwert in order to increase player satisfaction. Regarding claim 11, Mattar discloses wherein the instructions are executable to input captured clips of the computer game to the one or more ML models (¶ [0112]: visual images of game play). Regarding claim 14, Mattar discloses wherein the information comprises captured comments of gamers playing the computer game (¶ [0051]: player commentary). Regarding claim 15, Mattar discloses wherein the information comprises internet comments related to the computer game (Fig. 4C: Comments). Regarding claim 16, Mattar discloses wherein the text comprises output of the one or more ML models (¶ [0051]: player commentary). Regarding claim 19, Keilwert suggests—where Mattar does not disclose—changing the computer game using output of the one or more ML models (¶ [0072]: AI implementation may modify or alternate presentations and animations to emphasize or reduce game impact). It would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the invention to combine the disclosures of Mattar and Keilwert in order to increase player satisfaction. Claims 3, 4, 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Mattar in view of Keilwert and Coppola (US 2021/ 0027580 A1). Regarding claims 3 and 12, Coppola suggests—where Mattar does not disclose—wherein the information comprises number of views of the captured clips (¶ [0110]: number of views or replays of a particular game event may be tracked). It would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the invention to combine the disclosures of Mattar, Keilwert and Coppola in order to gauge the popularity of a specific game feature. Regarding claims 4 and 13, Coppola suggests—where Mattar does not disclose— wherein the information comprises number of views of clips similar to the captured clips (¶ [0110]: number of views or replays of a particular game event may be tracked). It would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the invention to combine the disclosures of Mattar, Keilwert and Coppola in order to gauge the popularity of a specific game feature. Conclusion Claim 9 is not subject herein to a rejection under 35 USC §§ 102 or 103, but stands rejected under § 101 as ineligible subject matter. The prior art considered pertinent to applicant's disclosure and not relied upon is made of record on the attached PTO-892 form. Dutilly et al (US 20100190555 A1) discloses dynamic video game recapping. Shen et al (US 20210117691 A1) discloses automatic video content summarizing. Kanshik et al (US 20220067385 A1) discloses multimodal game video summarization. Dubey et al (S 12167108 B1) discloses on-demand video content summarization. Any inquiry concerning this communication or earlier communications from the examiner should be directed to STEVE ROWLAND whose telephone number is (469) 295-9129. The examiner can normally be reached on M-Th 10-8. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor Dmitry Suhol can be reached at (571) 272-4430. The fax number for the organization where this application or proceeding is assigned is (571) 273-8300. 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. Applicant may choose, at his or her discretion, to correspond with Examiner via Internet e-mail. A paper copy of any and all email correspondence will be placed in the appropriate patent application file. Email communication must be authorized in advance. Without a written authorization by applicant in place, the USPTO will not respond via e-mail to any correspondence which contains information subject to the confidentiality requirement as set forth in 35 U.S.C. 122. Authorization may be perfected by submitting, on a separate paper, the following (or similar) disclaimer: PNG media_image1.png 18 19 media_image1.png Greyscale Recognizing that Internet communications are not secure, I hereby authorize the USPTO to communicate with me concerning any subject matter of this application by electronic mail. I understand that a copy of these communications will be made of record in the application file. PNG media_image1.png 18 19 media_image1.png Greyscale See MPEP 502.03 for more information. 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. /STEVE ROWLAND/Primary Examiner, Art Unit 3715 1 See https://www.uspto.gov/sites/default/files/documents/2024-AI-SMEUpdateExamples47-49.pdf
Read full office action

Prosecution Timeline

Dec 10, 2024
Application Filed
Aug 04, 2026
Non-Final Rejection mailed — §101, §102, §103 (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
78%
Grant Probability
95%
With Interview (+17.7%)
2y 7m (~11m remaining)
Median Time to Grant
Low
PTA Risk
Based on 1077 resolved cases by this examiner. Grant probability derived from career allowance rate.

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