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 .
Response to Amendment
Examiner acknowledges receipt of Applicant’s amendments and arguments filed 09/20/2022. The arguments set forth are addressed herein below.
Claims 1-20 are now pending.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are provisionally rejected on the ground of nonstatutory obviousness type double patenting as being unpatentable over claims 1-20 of Application No. 18/194,425 (reference application (US 2024/0325923 A1) to Hill. This is a provisional rejection because the conflicting claims of Hill have not yet been issued.
Although the claims at issue are not identical, they are not patentably distinct. Hill claims a personalization system that determined a playstyle of a player from the player’s gameplay information and dynamically generates, based at least in part on the playstyle, personalized content (including animation) for the player, and transmits the content for presentation in a game associated with the player. The independent claims of the present application recite generating personalized gameplay content for a player by training/applying a gameplay generation model on that player’s gameplay/player data and outputting the generated content within the video game. The present claims and Hill’s claims both recite generating personalized in-game content from a player’s gameplay data via a model and presenting/transmitting it in/for the game; the present claims are an obvious variant of, or are anticipated in scope by, Hill’s claims (differing, at most, in the label of the content – “gameplay content” vs “personalized animation” – and in generic ML implementation details.) One of ordinary skill would have found the present claims obvious in view of Hill’s claims.
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 to 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claimed invention is directed to non-statutory subject matter because the claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. Each of Claims 1 to 20 has been analyzed to determine whether it is directed to any judicial exceptions.
The examiner follows the two step-analysis, as described in MPEP 2106 (available at https://www.uspto.gov/web/offices/pac/mpep/s2106.html). The following diagram is an overview of the steps involved.
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Step 1
Step 1 of the two step-analysis considers whether the claims fall into one of the four statutory categories of invention such as a process, machine, manufacture, or composition of matter. The instant invention claims a method, a computer system, and a non-transitory, computer-readable medium in claims 1-20. As such, the claimed invention falls into the broad statutory categories of invention. However, claims that fall within one of the four statutory categories may nevertheless be ineligible if they encompass laws of nature, physical phenomena, or abstract ideas.
Step 2A
Step 2A has been further divided into two prongs as shown in the following diagram.
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Step 2A, Prong 1
Under prong 1 of step 2A, the examiner considers whether the claim recites an abstract idea, law of nature or natural phenomenon. The term “abstract idea” is not interpreted as a layperson might. Instead, the term “abstract idea” is interpreted as described in legal opinions by courts.
According to MPEP 2106.04(a):
the Office has set forth an approach to identifying abstract ideas that distills the relevant case law into enumerated groupings of abstract ideas. The enumerated groupings are firmly rooted in Supreme Court precedent as well as Federal Circuit decisions interpreting that precedent, as is explained in MPEP § 2106.04(a)(2). This approach represents a shift from the former case-comparison approach that required examiners to rely on individual judicial cases when determining whether a claim recites an abstract idea. By grouping the abstract ideas, the examiners’ focus has been shifted from relying on individual cases to generally applying the wide body of case law spanning all technologies and claim types.
The enumerated groupings of abstract ideas are defined as:
1) Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations (see MPEP § 2106.04(a)(2), subsection I);
2) Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II); and
3) Mental processes – concepts performed in the human mind (including an observation, evaluation, judgment, opinion) (see MPEP § 2106.04(a)(2), subsection III).
Specifically, independent Claim 1 (and similarly recited Claims 10 and 19) recites “1. (Original) A computing system comprising:
one or more processors (additional element); and
one or more memory devices (additional element), wherein the one or more memory devices are communicatively coupled to the one or more processors, the one or more memory devices storing computer-executable instructions including at least a gameplay content generation system comprising base game data, global game data, a plurality of player accounts, and one or more gameplay generation models, wherein the base game data comprises one or more base game components, and wherein each of the plurality of player accounts is associated with a plurality of player data, wherein execution of the computer-executable instructions by the one or more processors causes, during runtime, at least one of the one or more processors to generate gameplay content within a virtual interactive environment of a video game by:
receiving first player data, wherein the first player data is associated with a first player account of the plurality of player accounts;
adding the first player data to a first plurality of player data associated with the first player account;
training a first gameplay generation model of the one or more gameplay generation models using at least one of the global game data and the first plurality of player data;
receiving a first request to generate gameplay content corresponding to a first base game component;
generating first gameplay content, wherein the first gameplay content corresponds to the first base game component;
adding the first gameplay content to the first plurality of player data and the global game data; and
outputting the first gameplay content within the virtual interactive environment of the video game.”
The underlined portions of representative claim 1 generally encompass the abstract idea, with substantially similar features in claims 10 and 19. The dependent claims further define the abstract idea by introducing player data, further generating and retraining by the gameplay content, comparisons, and judgments, etc. The abstract idea may be viewed, for example, as:
at least one step or instruction or rule for: (i) an observation, judgement or evaluation, which is a mental process under the 2019 PEG (i.e., conceiving/selecting content based on collected information about a player);
a method of managing a game similar to that of managing a game of bingo in Planet Bingo, LLC v. VKGS LLC, 576 F. App'x 1005 (Fed. Cir. 2014) (non-precedential);
a set of game rules similar to increasing or decreasing the risk-to-reward ratio of a game, as discussed in Bot M8 LLC v. Sony Corp. of Am., 4 F.4th 1342 (Fed. Cir. 2021);
use of machine learning in a given environment (e.g., for generating gameplay) as discussed in Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025); and/or
a method of organizing human activities (e.g., allowing a human player to play an award-providing game according to rules of the game method) as discussed in Bilski v. Kappos, 561 U.S. 593 (2010) and Alice Corp. v. CLS Bank.
The abstract idea is also similar to that of Planet Bingo, in which a method of managing a bingo game was found to be an abstract idea. Though the instant claims are not limited to bingo games, they encompass the management of similar games. The abstract idea is also comparable to the game rules presented on gaming machines in Bot M8 LLC v. Sony Corp. of America, in which a reward probability could be increased or decreased based on aggregating previous game outcomes placed on the gaming machines. Like the claims in Recentive, the instant claims merely recite the use of generic machine learning applied to a given data environment. The Recentive court determined that claimed methods are not rendered patent eligible by the fact that using existing machine learning technology they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. The courts have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. Therefore, under prong 1, the above analysis demonstrates that the claimed invention encompasses an abstract idea in the form of mental processes and/or certain methods of organizing human activity.
Step 2A, Prong 2
Under prong 2 of step 2A, the examiner considers whether the additional elements in the claims integrate the abstract idea into a practical application. Here, the abstract idea is not integrated into a practical application. According to 2019 PEG, a consideration indicative of integration into a practical application includes improvements to the functioning of a computer or to any other technology or technical field (MPEP 2106.05(a)) or adding a specific limitation other than what is well-understood, routine, conventional activity, or adding unconventional steps that confine the claim to a particular application (a non-conventional and non-generic arrangement of various computer components for filtering Internet content, as discussed in BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350-51, 119 USPQ2d 1236, 1243 (Fed. Cir. 2016) (MPEP § 2106.05(d)). Conversely, considerations not indicative of integration include adding words “apply it” (or equivalent) with the judicial exception or mere instructions to implement the abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. (MPEP 2106.05(f)); adding insignificant extra-solution activity (MPEP 2106.05(g)), or generally linking the use of the abstract idea to a particular technological environment or field of use (MPEP 2106.05(h)).
Claims 1, 10, and 19 further recite one or more processors and one or more memory devices, yet these are recited so generically (no details whatsoever are provided other than in name only) that they represent no more than mere instructions to apply the judicial exception on a computer. These limitations can also be viewed as nothing more than an attempt to generally link the use of the judicial exception to the technological environment of a computer. It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the physical nature of these computer components does not affect this analysis. See MPEP 2106.05(I) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224-26 (2014).
The receiving, adding, training, generating and outputting steps are deemed to be data gathering and data presentation for the use of the judicial exception and similarly are recited at a high level of generality. Thus, these limitations are a form of insignificant extra-solution activity (See MPEP 2106.05(g), See also selecting a particular source and type of data to be manipulated where “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)).
Even when the limitations are viewed in combination, the additional elements in this claim do no more than automate the organizing activities needed to be performed, using the one of more computer components as tools. While this type of automation is an improvement in a general sense as opposed to performance manually, there is no change to the computers and other technology that are recited in the claim as automating the abstract ideas, and thus this claim cannot improve computer functionality or other technology. See, e.g., Trading Technologies Int’l v. IBG, Inc., 921 F.3d 1084, 1093 (Fed. Cir. 2019) (using a computer to provide a trader with more information to facilitate market trades improved the business process of market trading, but not the computer) and the cases discussed in MPEP 2106.05(a)(I), particularly FairWarning IP, LLC v. Latric Sys., 839 F.3d 1089, 1095 (Fed. Cir. 2016) (accelerating a process of analyzing audit log data is not an improvement when the increased speed comes solely from the capabilities of a general-purpose computer) and Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055 (Fed. Cir. 2017) (using a generic computer to automate a process of applying to finance a purchase is not an improvement to the computer’s functionality). Furthermore, the additional elements do not serve to apply the above-identified abstract idea with, or by use of, a particular machine, effect a transformation or apply or use the above-identified abstract idea in some other meaningful way beyond generally linking the use thereof to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception. Accordingly, Claims 1, 10, and 19 as a whole does not integrate the recited judicial exception into a practical application and these claims are directed to the judicial exception. Thus, Claims 1, 10, and 19 lack the eligibility requirements of Step 2 Prong II.
Step 2B
Finally, under step 2B, the examiner evaluates whether the additional elements:
add a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present (MPEP 2106.05(d)); or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present (MPEP 2106.05(d) and Berkheimer Memo, April 20, 2018). Thus, the additional elements evaluated under Step 2A are re-evaluated in Step 2B to determine if they are more than what is well-understood, routine, conventional activity in the field.
Claims 1, 10, and 19 do not recite additional elements, individually or in combination, that amount to significantly more than the abstract idea. As discussed above with respect to the lack of a practical application, the additional elements in the claim (i.e. one or more processors, one or more memory devices, etc.) amount to no more than mere instructions to apply the exception using generic computer components used as tools. These additional elements are generically claimed computer components which enable a game to be conducted by performing the basic functions of: (i) receiving, processing, and storing data, (ii) automating mental tasks and (iii) receiving or transmitting data over a network, e.g., using the Internet to gather data. The courts have recognized such computer functions as well understood, routine, and conventional functions when claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. See, Versata Dev. Group, Inc. v. SAP Am., Inc. , 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93. See storing and retrieving information in memory (MPEP 2106.05(d)(II)(iv) and then to present or display said information is well known as in presenting offers and gathering statistics (MPEP 2106.05(d)(II)(iii).
The specification describes the relevant computer systems in generic, functional, and conventional terms. For example, the specification simply refers to one or more processors in generic and functional terms, without any specificity as to the type or capabilities of such processor(s). See, e.g., Spec. ¶ 44. Moreover, the specification admits that the “computing device might be a video game console device, a general-purpose laptop or desktop computer, a smart phone, a tablet, a server, or other suitable system..” Spec. ¶ 139. Such features are considered well-understood, routine, and conventional because they merely require generic and conventional computer components described at a high level of generality. Additionally, while the specification discusses the use of machine learning, it does not provide any indication that the machine learning themselves are improved in any way. See, e.g., Spec. ¶¶ 85-90. Instead, the machine learning appear to be pre-existing, off-the-shelf computer components arranged in conventional ways. Nothing in the claims provides detail about specific or improved machine learning. In light of the court decision in Recentive, this is not sufficient to save a claim from abstraction.
Furthermore, taking the claimed elements individually yields no difference from taking them in combination because each element simply performs its respective function as discussed above. The claims do not purport to improve the functioning of a computer itself, nor do they effect an improvement in any other technology or technical field. Instead, the additional features merely amount to an instruction to apply the abstract idea using generic, functional, and conventional components well-known in the art. Viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that the claims amount to significantly more than the abstract idea itself.
Therefore, for at least the above reasons, Claims 1 to 20 are directed to applying an abstract idea (e.g., rules for conducting a game and/or mental process) on a general purpose computer without (i) improving the performance of the computer itself (as in McRO, Bascom and Enfish), or (ii) providing a technical solution to a problem in a technical field (as in DDR). In other words, none of Claims 1 to 20 provides meaningful limitations to transform the abstract idea into a patent eligible application of the abstract idea such that these claims amount to significantly more than the abstract idea itself. See Alice Corporation Pty. Ltd. v. CLS Bank International, et al., 573 U.S. 208 (2014).
The dependent claims recite further extra-solution activities and further define the abstract idea of the independent claims. Dependent Claims are ineligible and lack a practical application. Claims 2-9 inherit the same abstract idea as Claim 1. Claims 11-18 inherit the same abstract idea as Claim 10. Claim 20 inherit the same abstract idea as Claim 19.
AIA Notice
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 of this title, 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.
Claims 1-3, 5-6, 9-12, 14-15, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication 2020/0197811 At to Eatedali et al. in view of U.S. patent Application Publication 2019/0060759 A1 to Krishnamurthy.
Regarding Claim 1, and similarly recited Claims 10 and 19, Eatedali discloses a computing system comprising:
one or more processors (fig. 1, ¶¶ [0050], [0058] discloses computer system 110 may include one or more processors 112); and
one or more memory devices (fig. 1), wherein the one or more memory devices are communicatively coupled to the one or more processors, the one or more memory devices storing computer-executable instructions including at least a gameplay content generation system comprising base game data, global game data, a plurality of player accounts, and one or more gameplay generation models, wherein the base game data comprises one or more base game components (fig. 1, ¶ [0062], [0064] discloses one or more memory devices), and wherein each of the plurality of player accounts is associated with a plurality of player data, wherein execution of the computer-executable instructions by the one or more processors causes (fig. 1, ¶ [0062], [0064] discloses one or more memory devices), during runtime, at least one of the one or more processors to generate gameplay content within a virtual interactive environment of a video game by:
receiving first player data, wherein the first player data is associated with a first player account of the plurality of player accounts (¶¶ [0010], [0065]-[0067] discloses one or more profiles of human players to generate human player data);
adding the first player data to a first plurality of player data associated with the first player account (¶¶ [0010], [0033], [0070] discloses game data representative of one or more game events or game outcomes);
training a first gameplay generation model of the one or more gameplay generation models using at least one of the global game data and the first plurality of player data (¶¶ [0010], [0020], [0070] discloses data representative of the behavior of non-player characters by applying a neural network or machine learning process to the human player data and the game data);
receiving a first request to generate gameplay content corresponding to a first base game component;
generating first gameplay content, wherein the first gameplay content corresponds to the first base game component (¶¶ [0010], [0020], [0070] discloses generating of NPC behaviour data (i.e., gameplay content) for use in the game);
adding the first gameplay content to the first plurality of player data and the global game data; and
outputting the first gameplay content within the virtual interactive environment of the video game (¶¶ [0010], [0020], [0070] discloses transmitting generated data representative of the NPC behavior to one or more servers hosting the multiplayer video games for use/presentation of the game).
Eatedali, however, does not explicitly disclose receiving a first request to generate gameplay content corresponding to a first base game component.
In a related invention, Krishnamurthy discloses generating personalized gameplay content via a trained model. Krishnamurthy discloses receiving a first request to generate gameplay content corresponding to a first base game component (figs. 5-6, ¶¶ [0026], [0051]-[0056] discloses a video game system that implements a deep learning neural network to train one or more content generators – expressly including a level generator and context generator – each being a model trained on a player’s game-session data, and that generates personalized in-game content for the player based on that player’s data (for e.g., generating a particular level/context responsive to the player’s game-session data) and adapts/presents it within the game).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Eatedali with the gaming system of Krishnamurthy as both systems are directed to applying machine-learning models to a player’s gameplay/player data together with game data in order to produce content that enhances and personalizes the player’s experience. The combination is the predictable use of known machine-learning game personalization techniques to generate gameplay content tailored to the player, yielding no more than the expected result of personalized generated content.
Regarding Claim 2, and similarly recited Claim 11, Eatedali in view of Krishnamurthy discloses the computing system of claim 1, wherein player data comprises at least one of:
an amount of time a player has spent playing the video game, an amount of progress a player has made in completing a storyline of the video game, objects a player has previously interacted with in the video game, characters a player has previously interacted with in the video game, types of interactions the player has had within the video game, a percentage corresponding to how much of the virtual interactive environment the player has interacted with (Eatedali, ¶¶ [0010], [0020], [0070]; Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056] discloses the level generator 512 makes use of a deep learning network to extract features from the game session training dataset 530. The features can then be used to develop a deep learning model that can classify a player at a particular experience level. These features can include, for example, the speed and types of actions performed (e.g., the combination of buttons on a joystick), the progress in a video game, the accomplishments achieved, the trophies earned, the number of attempts per accomplishment, the score. The features can also relate to a player profile, such as the history of playing games, genres of played game, and other profile information).
Regarding Claim 3, and similarly recited Claim 12, Eatedali in view of Krishnamurthy discloses the computing system of claim 1, wherein execution of the computer-executable instructions further causes at least one of the one or more processors to generate gameplay content by:
retraining, by the gameplay content generation system, the first gameplay generation model using at least one of the global game data and first plurality of player data (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]);
receiving, at the gameplay content generation system, a second request to generate gameplay content corresponding to the first gameplay content (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]); and
generating, by the first gameplay generation model, second gameplay content, wherein the second gameplay content corresponds to the first gameplay content (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]).
Regarding Claim 5, and similarly recited Claim 14, Eatedali in view of Krishnamurthy discloses the computing system of claim 1, wherein at least one of the one or more gameplay generation models is a machine-learning model (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]; Eatedali, ¶¶ [0010]).
Regarding Claim 6, and similarly recited Claim 15, Eatedali in view of Krishnamurthy discloses the computing system of claim 1, wherein execution of the computer-executable instructions further causes at least one of the one or more processors to generate gameplay content by:
transmitting the first gameplay content to a user platform, wherein the user platform is configured to communicate with one or more user computing devices (Eatedali, ¶¶ [0010], [0020], [0070] discloses transmitting generated data representative of the NPC behavior to one or more servers hosting the multiplayer video games for use/presentation of the game).
Regarding Claim 9, and similarly recited Claim 18, Eatedali in view of Krishnamurthy discloses the computing system of claim 1, wherein execution of the computer-executable instructions further causes at least one of the one or more processors to generate gameplay content by:
receiving, at the gameplay content generation system, second player data, wherein the second player data is associated with a second player account of the plurality of player accounts (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]);
adding the second player data to a second plurality of player data associated with the second player account (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]);
training, by the gameplay content generation system, a second gameplay generation model of the one or more gameplay generation models using at least one of the global game data and the second plurality of player data (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]);
receiving, at the gameplay content generation system, a third request to generate gameplay content corresponding to the first base game component (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]); and
generating, by the first gameplay generation model, third gameplay content, wherein the third gameplay content corresponds to the first base game component, and wherein the third gameplay content is different from the first gameplay content (Krishnamurthy, figs. 5-6, ¶¶ [0026], [0051]-[0056]).
Potentially Allowable Subject Matter
Claims 4, 7-8, 13, 16-17, and 20 are not rejected under prior art, i.e. could be objected to as being dependent upon a rejected base claim. These claims remain rejected under § 101, but could be allowable, if applicant can successfully overcome the 101 rejection.
Response to Arguments/Remarks
Applicant’s arguments filed 04/02/2026 have been fully considered but they are not persuasive.
As an initial matter, consistent with the interview discussion, the Hill reference (2024/0325923) does not qualify as prior art under 35 USC § 102(a)(2). Therefore, the § 102(a)(2) rejection is therefore withdrawn. Note, however, that the common ownership exception of § 102(b)(2)(C) removes Hill only as prior art under § 102(a)(2)/ § 103; it does not preclude an obviousness-type double patenting rejection under Hill’s claims, which is entered below.
On pages 3-7 of the Remarks in which Applicant argues the claims are broadly overgeneralized and fails to establish a prima facie case, the Examiner respectfully disagrees. The rejection identifies the specific limitations that recites the abstract idea and the enumerated groupings (i.e. mental processes) as required by the 2019 PEG. Reciting the abstract idea at a high level of generality is a function of the breadth of Applicant’s independent claims, which recite “generating … content” and “training a … model” without reciting any specific technical means; this does not defeat the prima facie case.
On pages 5-6, in Applicant argues the judicial exception is integrated into a practical application/specific video-game architecture. The recited “gameplay content generation system” comprising base/global game data, player accounts, and generation models is a generic data-and-model arrangement; it does not impose a meaningful limit beyond applying the abstract idea in the field of video games. The argument that “current technology fails to provide a solution as claimed” is directed to novelty, not to the 101 integration. Additionally, the specification’s asserted benefits as described in ¶¶ [0033]-[0036], i.e. increased engagement, content tailored to a player’s culture, etc., are desired results and not a specific technical improvement to the functioning of a computer or a technical field. The claims do not recite how the model is trained or how the generation id performed in a manner that improves computer technology; they recite the result (generated content) and generic ML mechanism.
On pages 7-8, Applicant asserts that after considering the claim recitations as amended, individually and in combination, the claim recitations transform the nature of the claims into a patent-eligible concept and compares it to DDR Holdings. DDR Holdings is distinguishable from the present application as the claims there were necessarily rooted in computer network/technology to overcome a problem specifically arising in that technology (i.e. retaining website visitors). Here, generating personalized or localized game content is not a problem rooted in computer technology beyond the generic use of machine learning; the claims recite the desired result and a conventional ML mechanism, not a specific technical solution to a technical problem. The additional elements remain well-understood, routine, and conventional; no inventive concept is present.
As to Applicant’s request that the Office Action provide §§ 102/103 documentation, while the prior art and eligibility inquiries are distinct, newly cited prior art is applied in the § 103 rejection above and further confirms that the generic recitations of training/applying a model on a player and game data to generate and output in-game content were known in the art. The Step 2B “well-understood, routine, and conventional” determination is independently supported by the generic recitation of the additional elements and by the Specification’s description of conventional computing and ML components.
Therefore, the § 101 rejection is hereby maintained.
Conclusion
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/XUAN M THAI/Supervisory Patent Examiner, Art Unit 3715
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