Prosecution Insights
Last updated: April 17, 2026
Application No. 18/380,957

METHODS AND SYSTEMS FOR IMPLEMENTING AND UTILIZING INTERACTIVE NEURAL ENGINES IN INTERACTIVE PLATFORMS

Final Rejection §102
Filed
Oct 17, 2023
Examiner
IANNUZZI, PETER J
Art Unit
3715
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
unknown
OA Round
2 (Final)
67%
Grant Probability
Favorable
3-4
OA Rounds
2y 8m
To Grant
82%
With Interview

Examiner Intelligence

Grants 67% — above average
67%
Career Allow Rate
343 granted / 509 resolved
-2.6% vs TC avg
Moderate +15% lift
Without
With
+14.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
39 currently pending
Career history
548
Total Applications
across all art units

Statute-Specific Performance

§101
16.2%
-23.8% vs TC avg
§103
30.8%
-9.2% vs TC avg
§102
27.6%
-12.4% vs TC avg
§112
18.9%
-21.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 509 resolved cases

Office Action

§102
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 . Response to Arguments Applicant’s arguments, see remarks, filed December 15, 2025, with respect to 112b have been fully considered and are persuasive. The rejection of claims 5 and 15 with respect to section 112b has been withdrawn. Applicant's arguments filed December 15, 2025 with respect to 102 have been fully considered but they are not persuasive. Applicant argues that Examiner has not presented a rejection that allows for “counting the grounds of the rejection.” Applicant cites Chester v. Miller and fails to produce an articulable test or standard from that case and merely block quotes two of the many paragraphs cited from Dedonato. Examiner disagrees and notes that Chester v. Miller concerned a rejection without a statutory grounding, e.g. a single reference cited without notice if section 102 or 103 was invoked. This is not the case in this or the prior Office Action and Applicant’s arguments are not persuasive. Applicant makes a blanket assertion that the prior “Office Action fails to show that Dedonato teaches artificial intelligence (AI) component or elements that processes both of input data and interaction data (as distinct types of data), and then generates based on the processing of both of the input data and the interaction data, output data for a game playable via a user device.” Applicant does not cite any particular claim language and does not attempt to construe the claim limitations.1 Applicant’s citation insinuates that the phrase “artificial intelligence” does not appear in the prior art. Applicant appears to require and ipsissimis verbis test that is specifically excluded by MPEP§2131 and under the broadest reasonable interpretation of the claims, all of the cited techniques meet the broadest reasonable interpretation of the phrase “artificial intelligence”. As such, Applicant’s claims remain rejected as noted below. 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 person shall be entitled to a patent unless – (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by U.S. Pub. 2022/0343612 by Dedonato. Regarding claim 1, Dedonato discloses a system for gaming, the system comprising: a gaming platform that comprises (para. 115-116; fig. 2 and supporting paragraphs – see game system): a user device that comprises or is coupled to a display (fig. 2 and supporting paragraphs – see game system); and an interactive neural engine that comprises one or more circuits (para. 106-107 – see neural network); wherein the interactive neural engine is configured to: process, using artificial intelligence (AI), input data and interaction data (para. 106-107 – see AI processing of object processing); and generate, using the artificial intelligence (AI), based on the processing of the input data and the interaction data, output data for a game playable via the user device, for use during playing of the game via the user device (para. 106-107 – see AI processing of object processing; fig. 13A; para. 136-140 – see the displayed environment and objects); wherein the output data comprises data relating to one or both of: rendering of a game environment associated with the game and/or one or more game entities associated with the game, and rendering of interactions with the game environment and/or the one or more game entities; and wherein the gaming platform is configured to display the output data via the display during the playing of the game via the user device (para. 106-107 – see AI processing of object processing; fig. 13A; para. 136-140 – see the displayed environment and objects). Regarding claim 2, Dedonato discloses the system according to claim 1, wherein the interactive neural engine is configured to characterize each of the one or more game entities using a combination of position/location based information, time based information, and interactions based information (fig. 13A; para. 136-140 – see the displayed environment and objects at positions and times in the environment). Regarding claim 3, Dedonato discloses the system according to claim 1, wherein the interactive neural engine comprises a content component and an interaction component; wherein content component is configured to provide content for the game; and wherein the interaction component is configured to handle interactions by and/or with the one or more game entities, and/or interactions within the game environment as a whole (fig. 13A; para. 136-140 – see the generated interactive content.). Regarding claim 4, Dedonato discloses the system according to claim 3, wherein the content component is configured to provide the content of the game based on one or both of content generation and content synthesis (fig. 13A; para. 136-140 – see the provided content based on both content synthesis and generation). Regarding claim 5, Dedonato discloses the system according to claim 4, wherein the content component is configured to provide the content of the game based on combination of the content generation and the content synthesis across a continuum between a low limit for the content synthesis and a high limit for the content synthesis (fig. 13A; para. 136-140 – see the provided content based on both content synthesis and generation). Regarding claim 6, Dedonato discloses the system according to claim 5, wherein the low limit for the content synthesis is 0% and the high limit for the content synthesis is 100% (fig. 13A; para. 136-140 – see the elements that are fully rendered meeting the high limit and the elements that are fully reality meeting the low limit). Regarding claim 7, Dedonato discloses the system according to claim 4, wherein the content component is configured to provide the content generation using computer generated (CG) graphics (fig. 13A; para. 136-140 – see the CG content). Regarding claim 8, Dedonato discloses the system according to claim 4, wherein the content component is configured to provide the content synthesis using real content obtained via one or more capturing devices (fig. 13A; para. 136-140 – see the real content provided to the user from the environment). Regarding claim 9, Dedonato discloses the system according to claim 3, wherein the interaction component is configured to handle the interactions using one or both an internal state and an external state associated with one or more of the one or more game entities (fig. 13A; para. 136-140 – see the blending of the internal state and external state used in interactions in the AR world). Regarding claim 10, Dedonato discloses the system according to claim 1, wherein the interactive neural engine is configured to use one or more neural network for one or both of the processing of the input data and the interaction data, and the generating of the output data (para. 106-107 – see the use of the neural network for processing and generation). Claims 11-20 are rejected as noted above regarding claims 1-10. Conclusion THIS ACTION IS MADE FINAL. 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 PETER J IANNUZZI whose telephone number is (571)272-5793. The examiner can normally be reached M-F 9:30AM-5:30PM EST. 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, Kang Hu can be reached at 571-270-1344. 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. /PETER J IANNUZZI/ Primary Examiner, Art Unit 3715 1 Examiner notes that Applicant did not withhold claim construction when arguing section 112b and Examiner found those arguments persuasive.
Read full office action

Prosecution Timeline

Oct 17, 2023
Application Filed
Aug 11, 2025
Non-Final Rejection — §102
Dec 15, 2025
Response Filed
Jan 09, 2026
Final Rejection — §102 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

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SYSTEMS AND METHODS OF ELECTRONIC GAMING INCLUDING GESTURE-BASED PLAYER CONSTRUCTED SYMBOL COMBINATIONS
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METHOD AND AR GLASSES FOR AR GLASSES INTERACTIVE DISPLAY
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Patent 12589311
PERFORMANCE PREDICTION FOR VIRTUALIZED GAMING APPLICATIONS
2y 5m to grant Granted Mar 31, 2026
Patent 12589290
FUNCTION BUTTON MODULE WITH VARIABLE FUNCTION LAYOUT AND GAME CONTROLLER
2y 5m to grant Granted Mar 31, 2026
Patent 12586442
SYSTEM AND METHOD FOR IMPLEMENTING SINGLE ACCOUNT AND SINGLE WALLET FOR DISTRIBUTED GAMING SYSTEM ACROSS JURISDICTIONS
2y 5m to grant Granted Mar 24, 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
67%
Grant Probability
82%
With Interview (+14.6%)
2y 8m
Median Time to Grant
Moderate
PTA Risk
Based on 509 resolved cases by this examiner. Grant probability derived from career allow rate.

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