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 Amendments
This office action is in response to amendments filed on 03/23/2026.
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 1-11, 18-41, 47-60 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a mental process without significantly more. As per step 1 examiner recognizes the use of a processor, system, or steps stored on a non-transitory medium. As per step 2A the claim(s) recite(s) “obtain one or more media segments of gameplay of a game session of one or more users; provide input based on the one or more media segments of gameplay to one or more neural networks to identify, one or more scenes, actions, or objects in the one or more media segments based, at least in part, on one or more game interactions by the one or more users during the gameplay of the game session; and generate information about the identified one or more scenes, actions or objects; generate one or more game recommendations based, at least in part, on the generated information; and provide the one or more game recommendations via a user interface.” as being directed to a method and system comprising providing recommendations to a player based on observation of interactions by the player with scenes, actions, or objects during a game session. Specifically this is directed to the mental process of observing a player playing a first game in order to recommend, based on information in the observation, another game. For example if a player plays a first person shooter as a first game where they favor a certain type of weapon then a recommendation for a second title which focuses on that weapon would be a mental step that could be carried out by an individual outside of a computer. For example if a player prefers to use a sniper rifle, an object, then an observer could recommend a game that focuses on sniping to the player. These are mental steps which involve observation of data and applying the data to make a mental determination of a player’s preferences. Examiner notes the steps are performed by a “neural network” however insufficient information is provided regarding the function of the neural network to provide any more than a generic machine performing the mental steps above. Specifically neural network is generically recited as performing mental steps. Additional steps such as found in the dependents such as “the one or more recommendations based in part upon keywords inferred for the identified one or more scenes, actions, or objects in the one or more media segments” are steps regarding observing an environment, including media segments, to determine information about the environment which could be done as a mental step. For example, using the above example, an individual could determine, by watching a first game, that a genre of the first game is a first person shooter based on observing a scene in the game, such as players shooting at each other, and therefore base the recommendations on this. Therefore the dependent claims amount to no more than additional observation or learning steps which are mental steps for providing the recommendation. Therefore neural network at this time does not provide sufficient structure as to make the steps no more than mental steps performed on a generic machine. As per the media segments examiner recognizes that a media segment is a visual or audio representation of a game in the current invention and therefore observing information regarding a media segment involves observing the game. This would include steps performed by an individual such as watching the gameplay and therefore goes towards the mental step of observation. This judicial exception is not integrated into a practical application because series of mental steps regarding recommending games to a user based on observing previous gameplay history. Specifically a series of mental steps including observation, learning, and determining how to use the data. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the element of neural networks recited in the game lacks sufficient structure as to be no more than a generic computer element included, such as machine learning, without sufficient steps that amount to more than a generic machine performing a mental process. Specifically at this time neural network does not provide sufficient structure as to render the claims with a practical application significantly more than the recited exemption.
As per step 2B examiner recognize the processor, system, non-transitory medium, and network elements are all generic elements found in the gaming art. Therefore these elements do not provide significantly more than a generic machine. See for example Shen et al. (US Pub. No. 2016/0140408 A1) generally described neural network being used to determine information for images (paragraph [0001]) including the labeling of information related to the image (paragraph [0017]). Specifically the processing of images or other media by a neural network in a general fashion is conventional to the art and therefore the use of a neural network to perform a mental step function does not add significantly more under step 2B or provide a practical application.
Response to Arguments
Applicant's arguments filed 03/23/2026 have been fully considered but they are not persuasive. As per the 101 rejection applicant argues that language overcomes the rejection by reciting a specific neural network performing a computer related function that goes beyond a mental step. Examiner notes that the limitation has the neural network “identify, using one or more media segments of gameplay of a game session...one or more scenes, actions, or objects in the one or more media segment” without indicating the steps on how the identification occurs. Specifically the neural network performs the task of observation without including the computer steps involved and therefore performs a task that an individual can perform mentally. An individual can observe a game and note information regarding the game including scenes, action, or object. Without further clarification this is broadly claiming a step that is already performed by individuals and therefore the neural network portion does not overcome the rejection under step 2A or 2B since the network is additionally recited in a generic fashion. For example examiner looks to example 39 regarding a neural network for facial detection wherein limitations such as “applying one or more transformations to each digital facial image including mirroring, rotating, smoothing, or contrast reduction to create a modified set of digital facial images; creating a first training set comprising the collected set of digital facial images, the modified set of digital facial images, and a set of digital non-facial images;” were found not to recite a judicial exception. Specifically a mental step since a user cannot reasonably perform the steps recited. Examiner however finds that applicant’s limitation does not include computer specific steps (e.g. transformation of visual images using mirroring, rotating, smoothing, contrasting, or other graphic steps) which cannot be performed in the mind but are instead directed towards broadly identifying elements or keywords in an image. For example, as shown by Figs. 1A-1C and 3, looking at an image to identify that a player, for example, is playing a golfing game and therefore to recommend other golfing games. These are steps that an individual performs mentally. For example a person can view that an individual is playing a golfing game by observing that a character is carrying out the action of golfing. An individual also identifies elements in the image such as the character, golf club, and golf ball among others to determine that the action of golfing occurs. Therefore as broadly written the claims do not meet the elements of example 39 wherein an individual cannot perform the task mentally. Without additional computer steps the action of identifying features in an image or video is a mental step.
Applicant makes reference to Ex Parte Desjardins et al. as support for overcoming 101 since both cases are directed to AI aspects. Examiner reviewing Desjardins finds that the features that appear to overcome the 101 are related to hardware and software methods that improve the machine learning. For example reducing the forgetfulness of the model. Examiner does not find similar hardware or software features that improves the neural network of applicant’s claims. Instead a neural network is directed towards the mental step of game recommendation. Applicant should cite to a technical improvement as found similarly in Desjardins.
As per arguments that claims overcome 101 by providing an inventive concept “[g]roundbreaking, innovative, or even brilliant,” but that is not enough for eligibility. Ass’n for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1352 (Fed. Cir. 2014). Nor is it enough for subject-matter eligibility that claimed techniques be novel and nonobvious in light of prior art, passing muster under 35 U.S.C. §§ 102 and 103. See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 89–90 (2012); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (“[A] claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating § 102 novelty.”); Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1315 (Fed. Cir. 2016) (same for obviousness) (Symantec). The claims here are ineligible because their innovation is an innovation in ineligible subject matter.
Applicant argues that the recommendation system improves upon existing recommendation systems and therefore is a practical application. First examiner notes the method of training is a generic recitation of a neural network and therefore is a broad recitation of a process which is a mental process being performed by a machine. Specifically the act of identifying and recommendation which is a mental process and without additional steps an abstract idea. Specific limitations regarding how the neural training occurs would be required to lend specific weight to an improvement in the computing art. Therefore the action of performing the recommendation on a computer via the neural network would not provide a practical application since it still directed to an abstract idea. Recommending games or other media to individuals based on observing their preferences or interaction with media is a well-known process outside of computers. Having a computer perform these steps without specific additional steps tied to a computer based solution does not provide a practical application. Additionally the act of recommendation is a known process that pre-exist computer technology and the purpose of providing good recommendations is known as well. The general argued improvement of having a computer preform this step still reads on a computer performing a mental step. Applicant should indicate a technological function performed by the machine that goes beyond conventional actions and which can be argued to provide an improvement to the action of recommendation. A general recitation of neural networks is merely claiming a machine that perform a mental process of an individual. How the machine neural network functions may differ from this as it goes towards technological steps.
Applicant argues that step 2B is overcome based on the order of operations. Examiner notes that in order to provide a recommendation based on game play that a system or individual would be required to receive game play to observe. For example an individual would need to first watch a player play a game to note what the player prefers to play. A computer performing this function is mimicking what an individual performs as well. The actual steps are mental steps as indicated above and therefore do not overcome the rejection under step 2B. Therefore it is unclear how the order is significantly more than the exception. As per the claims they read as broadly claiming a neural network performing a mental function without steps that cannot be performed by an individual as indicated above. Therefore the claims do not overcome step 2B.
Based on the reasons above the 101 rejection is maintained.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUSTIN L MYHR whose telephone number is (571)270-7847. The examiner can normally be reached 10AM-6PM.
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/JUSTIN L MYHR/Primary Examiner, Art Unit 3715 4/24/2026
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