DETAILED ACTION
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 Objections
Claim13 is objected to because of the following informalities: “to arrive an optimal state” (lines 7-8) should presumably read “to arrive at an optimal state” or something similar. Appropriate correction is required.
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 1-19 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.
Claim 1 recites "GM input" (line 6) and “GM output” (line 6). It is unclear what “GM” refers to. Independent claims 18-19 recite similar language and are similarly rejected. Dependent claims 2-17 inherit these discrepancies by nature of their dependencies. Appropriate correction is required.
Claim 3 recites “gameplay” (line 2). Claim 1, upon which claim 3 depends, recites “gameplay” (line 2) and “the gameplay” (lines 3, 5, 8, and 9-10). The first instance of a claim element should generally subsequently be followed by referring to the element using “the” or “said”. Reciting “gameplay” a second time makes it unclear whether the two instances of “gameplay” refer to the same claim element or different claim elements. Dependent claims 4 and 14 recites similar language and is similarly rejected. Appropriate correction is required.
Claim 3 recites “gameplay of the user” (line 2). Claim 1, upon which claim 3 depends, recites “gameplay of a video game” (line 2) and “the gameplay of the video game” (lines 3, 5, 8, and 9-10). It is unclear what the difference is between “gameplay of the user” and “gameplay of the video game”. Dependent claims 4 and 14 recites similar language and is similarly rejected. Appropriate correction is required.
In claims 10 and 11, applicant refers to "user’s gameplay” and “the additional user’s gameplay”, respectively. The examiner discourages the use of possessive nouns because they combine two separate claim elements (e.g., “user”, “additional user”, and “gameplay”) and recite them in a way not previously disclosed. An alternate way of reciting “the gameplay of the user” or “the gameplay of the additional user”, which keeps the claim elements separate from each other as they were originally recited. Appropriate correction is required.
Claim 10 recites "the user’s game play of the video game" (lines 1-2). Claim 1, upon which claim 10 ultimately depends, recites “gameplay of a video game” (line 2) and “the gameplay of the video game” (lines 3, 5, 8, and 9-10). There is insufficient antecedent basis for this limitation in the claim. Consistent usage of the same terms is much preferred over creatively describing the same elements using different language. Using similar, yet slightly different claim language creates confusion. It is unclear whether "the user’s game play of the video game" is intended to refer to “the gameplay of the video game” or whether each term refers to a new claim element. Claim 11 recites similar language and is similarly rejected. Appropriate correction is required.
Claim 10 recites the limitation "the user’s gameplay" (line 1). There is insufficient antecedent basis for this limitation in the claim. Appropriate correction is required.
Claim 11 recites the limitation "the additional user’s gameplay" (line 2). There is insufficient antecedent basis for this limitation in the claim. Appropriate correction is required.
Claim 13 recites "the GM" (lines 4 and 15). It is unclear what “GM” refers to. Independent claims 18-19 recite similar language and are similarly rejected. Dependent claims 2-17 inherit these discrepancies by nature of their dependencies. Appropriate correction is required.
Claim 13 recites the limitation "the GM" (line 4) and “the losses” (line 15). There is insufficient antecedent basis for these limitations in the claim. Appropriate correction is required.
Claim 13 recites “SFT training instances” (line 5). It is unclear what “SFT” stands for. Appropriate correction is required.
Claim 13 recites “one or more losses” (lines 13-14) and “one of more of the losses” (line 15). The initial recitation of “one or more losses” allows for a single or a plurality of losses, whereas subsequently the limitation refers to one or more of the plurality of losses (excluding the a singular loss). It is believed that applicant may have intended the limitation to recite “the one or more losses” instead of “one of more of the losses”. Appropriate correction is required.
Claim 15 recites “a plurality of possible actions” (line 4) and “the plurality of the possible actions” (line 6). It appears the “plurality of possible actions” is a single claim element, making it appropriate to recite “the plurality of possible actions” instead of “the plurality of the possible actions”. Appropriate correction is required.
Claim 16 recites “reinforcement learning from human feedback (RLHF)” (line 3) and “RLHF” (line 4). The first instance of a claim element should generally subsequently be followed by referring to the element using “the” or “said”. Reciting the same claim element a second time makes it unclear whether the two instances refer to the same claim element or different claim elements. Dependent claim 17 inherits this discrepancy by nature of its dependency. Appropriate correction is required.
Claim 16 recites the limitation "the GM" (line 7). There is insufficient antecedent basis for this limitation in the claim. Dependent claim 17 inherits this discrepancy by nature of its dependency. Dependent claim 17 inherits this discrepancy by nature of its dependency. Appropriate correction is required.
Prior Art
There are currently no prior art rejections against claims 1-20.
The closest prior art of record includes Chaput et al., US 11,724,201 B1 (hereinafter Chaput); Vange et al., US 2022/0274023 A1 (hereinafter Vange); Yilmazcoban et al., US 2020/0324206 A1 (hereinafter Yilmazcoban); AI Coach for Battle Royale Games by Nina Zhou, Matt Doerner, Lisa Ryna, and Christopher Pierse (hereinafter Zhou); and MarioQA: Answering Questions by Watching Gameplay Videos by Johgwhan Mun, Paul Hongsuck Seo, Ilchae Jung, Byhyung Han (hereinafter Mun).
Chaput discloses systems, methods, and machine-readable media for generating insights for video games (Chaput [Abstract]). The method includes gathering information regarding a player for a plurality of video games, the information comprising at least one of in-world state data, player action data, player progression data, and/or real-world events relevant to each video game (Chaput [Abstract]). The method also includes tracking events in at least one video game of the plurality of video games, the events comprising an action event or a standby event (Chaput [Abstract]). The method also includes determining that an event of the tracked events is an action event (Chaput [Abstract]). The method also includes generating insights regarding the action event based on the information gathered regarding the player, the insights for improving the player's performance in the video game (Chaput [Abstract]). The method also includes relaying the insights to the player to improve the player's performance in the video game (Chaput [Abstract]). Chaput fails to explicitly disclose, at least, receiving a natural language prompt that is associated with a client device of a user, a generative model, a chain of thought, and multimedia content including at least one image.
Vange discloses systems and methods for an artificial intelligence powered user interface according to various aspects of the present technology include a game engine that is powered by an artificial intelligence system that is able to receive minimal platform specific discrete user inputs and infer optimal in-game action (Vange [Abstract]). The game engine may be trained to generate a set of known, expected, or predicted behaviors for both non-player characters and actual players (Vange [Abstract]). The game engine may then present one or more events to players and then infer a player response based upon a received user input (Vange [Abstract]). The game engine may also be configured to measure success of each inference based on a comparison of a player's response to a set of predetermined goals (Vange [Abstract]). Vange fails to explicitly disclose, at least, receiving a natural language prompt that is associated with a client device of a user, a generative model, a chain of thought, and multimedia content including at least one image.
Yilmazcoban discloses a method and system for assisting game-play of a user (Yilmazcoban [Abstract]). The method and system includes a training module to train an Artificial Intelligence (AI)-based learning model based on a plurality of offline features and a plurality of online features (Yilmazcoban [Abstract]). The plurality of offline features are extracted from one or more of data collected by one or more game developers, a plurality of Application Programming Interfaces (APIs) and a plurality of replay files associated with game-play (Yilmazcoban [Abstract]). On the other hand, the plurality of online features are extracted from a screen state of the user (Yilmazcoban [Abstract]). Further, the method and system includes a coaching module to coach the user in game-play utilizing the AI-based learning model using techniques such as, but not limited to, statistics, post-game analysis and progress tracking of game-play for optimizing the performance of the user, and generates one or more game-play suggestions for the user (Yilmazcoban [Abstract]). Yilmazcoban fails to explicitly disclose, at least, receiving a natural language prompt that is associated with a client device of a user, a generative model, and a chain of thought.
Zhou discloses an AI Coach algorithm to provide personalized and adaptive coaching suggestions to Apex Legends players (Zhou [p. 1]). The proposed algorithm first models player game skills with a comprehensive set of in-game attributes using a random forest (Zhou [p. 1]). Then, it artificially perturbs individual player data to search for impactful candidate attributes and the associated actions that an individual player can use to improve their game skill (Zhou [p. 1]). The AI Coach technique provides automated and objective suggestions based on players’ recent gameplay data, optimizing expected game outcomes (Zhou [p. 1]). Zhou fails to explicitly disclose, at least, receiving a natural language prompt that is associated with a client device of a user, a generative model, a chain of thought, and multimedia content including at least one image.
Mun discloses a framework to analyze various aspects of models for video question answering (VideoQA) using customizable synthetic datasets, which are constructed automatically from gameplay videos automatically generated from a customized synthetic VideoQA dataset using Super Mario Bros. gameplay videos so that it contains events with different levels of reasoning complexity (Mun [Abstract]). Using the dataset, Mun shows that properly constructed datasets with events in various complexity levels are critical to learn effective models and improve overall performance (Mun [Abstract]). Mun fails to explicitly disclose, at least, receiving a natural language prompt that is associated with a client device of a user, a generative model, and determining a chain of thought to improve the gameplay of the video game.
The prior art, alone or in combination, absent hindsight, does not fairly teach or suggest the claimed invention for at least the reasons stated above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WERNER G GARNER whose telephone number is (571)270-7147. The examiner can normally be reached M-F 7:30-15:30 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, DAVID LEWIS can be reached at (571) 272-7673. 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.
/WERNER G GARNER/Primary Examiner, Art Unit 3715
Prosecution Insights