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
Claim 15 is objected to because of the following informalities:
Claim 15, Line 2: Change “indicative of of” to – indicative of --.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
3. 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.
4. Claims 13-32 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
5. Step 1
Claims 13-32 are directed to an apparatus or method meeting the requirements for Step 1.
6. Step 2A Prong 1
In independent Claim 13 (and similarly for Claims 23 and 32), the following bolded steps recite determining a likelihood which is a mathematical concept and identifying other assets which is a mental process, for the purposes of analysis these abstract ideas are merged into a single abstract mathematical concept:
13. A method of memory management for a video game, the method comprising:
loading a first asset into a memory;
determining a likelihood that a respective other asset from a plurality of other assets will be used within a predetermined period of time after the first asset is loaded into the memory;
identifying one or more of the plurality of other assets based on the determined likelihood of a respective other asset; and
preloading the one or more identified assets into the memory in response to the first asset being loaded into the memory.
In Claims 23 and 32, directed to computer readable media and processor where:
23. One or more non-transitory machine-readable storage media storing instructions which, when executed by one or more computers, cause the one or more computers to perform operations for managing memory for a video game, the operations comprising:
loading a first asset into a memory;
determining a likelihood that a respective other asset from a plurality of other assets will be used within a predetermined period of time after the first asset is loaded into the memory;
identifying one or more of the plurality of other assets based on the determined likelihood of a respective other asset; and
preloading the one or more identified assets into the memory in response to the first asset being loaded into the memory.
32. A processing device for memory management for a video game, the processing device comprising: at least one memory; and
one or more processors configured to:
loading a first asset into the at least one memory;
determining a likelihood that a respective other asset from a plurality of other assets will be used within a predetermined period of time after the first asset is loaded into the at least one memory;
identifying one or more of the plurality of other assets based on the determined likelihood of a respective other asset; and
preloading the one or more identified assets into the memory in response to the first asset being loaded into the at least one memory.
7. Step 2A Prong II
The abstract idea is not integrated into a practical application because Applicant has not added a specific limitation other than what is well-known, routine, or conventional activity which is discussed under Step 2B (below).
According to MPEP 2106, 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)).
Here, as pertaining to the determination of a likelihood, and of computers, memory, and processor of Claims 13, 23 and 32, Applicant discloses that he has a technological solution to a technical problem, where:
“As processing speeds and display technologies have improved, users' expectations of rendering capabilities have likewise increased. Meanwhile, as rendering capabilities increase, some hardware requirements may not be able to keep up with the increased capabilities, which may result in a bottleneck in rendering capabilities.” [0003, 0020].
“The method further comprises a step of identifying 230 one or more of the other assets in dependence upon the determined likelihood of a respective other asset; and a step of preloading 240 the one or more identified assets into the memory in response to the first asset being loaded into the memory. Each of these steps will now be discussed in turn.” [0027].
“In some embodiments of the present disclosure, the first asset is loaded into a first portion of the memory and the one or more identified assets are preloaded into a second portion of the memory. Optionally, the second portion of the memory may be adjacent to the first portion of the memory, which may improve memory latency when the processor reads the data from the portion of the memory and then reads the data from the second portion of the memory.” [0058]
Yet, the independent claims do not express elements that are other than what is already well-known, routine, or conventional amounting to providing a practical application.
According to Applicant, the likelihood can be based on a period of time [0032]; as a proportion of activity [0033]; as a function of a proportion or threshold [0036, 0040]; or a current game state [0060] and can be produced with the aid of a trained machine learning model [0066]. Applicant discloses:
“It will be appreciated that the above methods may be carried out on conventional hardware suitably adapted as applicable by software instruction or by the inclusion or substitution of dedicated hardware.” [0094], and
“Thus the required adaptation to existing parts of a conventional equivalent device may be implemented in the form of a computer program product comprising processor implementable instructions stored on a non-transitory machine-readable medium such as a floppy disk, optical disk, hard disk, solid state disk, PROM, RAM, flash memory or any combination of these or other storage media, or realised in hardware as an ASIC (application specific integrated circuit) or an FPGA (field programmable gate array) or other configurable circuit suitable to use in adapting the conventional equivalent device. Separately, such a computer program may be transmitted via data signals on a network such as an Ethernet, a wireless network, the Internet, or any combination of these or other networks.” [0095].
The remaining limitations in Claim 13, and similarly in Claims 23 and 32, comprise extra-solution data gathering (“loading a first asset into a memory”); a separate mental process (“identifying one or more of the plurality of other assets based on the determined likelihood of a respective other asset”), and extra-solution data gathering (“preloading the one or more identified assets into the memory in response to the first asset being loaded into the memory”).
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 2104(d)(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, 110 USPQ2d 1976, 1983-84 (2014).
Even when the limitations are viewed in combination, the elements do no more than automate the steps 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).
Accordingly, each independent claim, as a whole and expressing conventional and extra-solution activity, does not integrate the recited judicial exception into a practical application. Thus, Claim 13, and similarly Claims 23 and 32, lack the eligibility requirements of Step 2 Prong II.
8. Step 2B
According to MPEP 2106, in addition to the considerations discussed in Step 2A, an additional consideration indicative of an inventive concept (aka “significantly more”) is the addition of a specific limitation other than what is well-understood, routine, conventional activity in the field (MPEP 2106.05(d)). Conversely, an additional consideration not indicative of an inventive concept is simply appending well-understood, conventional activities previously known to the industry, specified at a high level of generality, to the abstract idea (MPEP 2106.05(d) and Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 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.
Here, according to Applicant’s specification, Applicant expressly admits that conventional elements are employed where:
“[0094] It will be appreciated that the above methods may be carried out on conventional hardware suitably adapted as applicable by software instruction or by the inclusion or substitution of dedicated hardware” and
“[0095] Thus the required adaptation to existing parts of a conventional equivalent device may be implemented in the form of a computer program product comprising processor implementable instructions stored on a non-transitory machine-readable medium such as a floppy disk, optical disk, hard disk, solid state disk, PROM, RAM, flash memory or any combination of these or other storage media, or realised in hardware as an ASIC (application specific integrated circuit) or an FPGA (field programmable gate array) or other configurable circuit suitable to use in adapting the conventional equivalent device. Separately, such a computer program may be transmitted via data signals on a network such as an Ethernet, a wireless network, the Internet, or any combination of these or other networks.”
Applicant’s disclosure satisfies the criteria for what Examiner’s must rely upon for a conclusion that the steps are well-understood, routine, conventional activity supported under Berkheimer. Additionally, Examiner has determined that the elements are used as tools to carry out the claimed steps and viewing the claim as a whole, in light of Applicant’s specification and despite the use of conventional elements, does not conclude that the claims rise to the level of eligibility on par with a) the self-referential table in the case of Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339, 118 USPQ2d 1684, 1691-92 (Fed. Cir. 2016); b) the unique rule sets improving lip synchronization and facial expression animation of McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1315, 120 USPQ2d 1091, 1102-03 (Fed. Cir. 2016); or c) the non-conventional and non-generic arrangement of various computer components for filtering Internet content at a remote location while maintaining local security protocols, 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)).
As to the extra-solution data gathering discussed under above, Court decisions cited in MPEP 2106.05(d)(II) indicate that it is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here for data gathering assets to load them into memory).See storing and retrieving information in memory (MPEP 2106.05(d)(II)(iv).
Therefore, these limitations remain insignificant extra-solution activity even upon reconsideration, and do not amount to significantly more. Thus, Claim 13, and similarly Claims 23 and 32, do not recite additional elements, individually or in combination, that amount to significantly more than the abstract idea. Thus, Claims 13, 23 and 32 are ineligible.
9. Dependent Claims 14-18 and 24-28
Claims 14 and 24, and by their dependencies, Claims 15-18 and 25-28, pertain to the recitation of inputting asset information into a machine learning model as a means to determine the likelihood. Claims 19-22 and 29-31 recite additional details of the abstract mathematical concept. None of the claims supply a practical application or inventive concept sufficient to transform the nature of the claim into a patent-eligible application.
Claims 14 and 24 recite the use of artificial intelligence. Examiner finds that Applicant’s disclosure and recitation in the claims are different than those which led to the eligibility decision in Ex Pate Desjardins due to Berkheimer discussed above. (In Ex Parte Desjardins, the decision analyzed eligibility in terms of whether the claims were directed to an improvement in the functioning of a computer, or an improvement to other technology or technical field under longstanding Federal Circuit precedent in Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) and McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299 (Fed. Cir. 2016). See also MPEP §§ 2106.04(d)(l) and 2106.05(a).) Specifically, Ex Pate Desjardins reduced storage, reduced system complexity and streamlining, and preservation of performance attributes associated with earlier tasks during subsequent computational tasks as technological improvement to overcome “catastrophic forgetting” encountered in continual learning systems (See Advance notice of change to the MPE in light of Ex Parte Desjardins, December 5, 2025)).
Lastly, the combination of additional elements adds nothing that is not already present when considered individually where the additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which cannot provide an inventive concept. Thus, Claims 14-18 and 24-28 are ineligible.
Claim Rejections - 35 USC § 102
10. 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)(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.
(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.
11. Claims 13-18, 20-28, and 30-32 are rejected under 35 U.S.C. § 102 (a1, a2) as being anticipated by U.S. Pat. Pub. No. 2020/0391118 to Kerr.
In Reference to Claims 13, 23, and 32
Kerr discloses a system, computer-readable media, and method of memory management for a video game (Abstr., Fig. 1 100, [0001]), the system including processor 604, computing device memory 604, computer-readable medium and instructions [0090-0091], the method comprising:
loading a first asset into a memory (Fig. 5 504 wherein player data is obtained and loaded into memory [0079] which results in available game options such as items, movements, and actions in 506 [0080], see also game-related data assets [0068. 0069, 0070, 0074, 0077]);
determining a likelihood that a respective other asset from a plurality of other assets will
be used within a predetermined period of time after the first asset is loaded into the memory (Fig. 5 508 the loaded options are provided to a prediction model [0081], see also Kerr’s gameplay examples wherein other asset accessories as expressed: “[t]he training of the model 104 can include player-specific (or user-specific) training of the neural network(s) based on past game choices (e.g., this user usually chooses the most popular game from the search results) or based on past game play (e.g., this user, upon entering a room, usually navigates left). The training can also include cohort-based training such as users in a particular demographic group, upon starting a game, choose accessories of this type (e.g., 21 year-old males typically choose a leather jacket and baseball hat; 30 year old females typically choose red hair, and a hair band). Also “players choose x and then choose y” [0065]. Training can also include prior-data training without demographic data (e.g., users choose accessories related to hair first then accessories for footwear).” [0070] such that the navigation left, leather jacket, baseball hat, red hair, hair band, footwear are other assets. These are used within a predetermined period of time after the first asset is loaded where “Thus, during the time period when the user is viewing available game selections, one or more available game options can begin to be preloaded based on predictions from the machine learning model.” [0029]);
identifying one or more of the plurality of other assets based on the determined likelihood of a respective other asset (Fig.5 510 one or more game options are available [0082]); and
preloading the one or more identified assets into the memory in response to the first asset being loaded into the memory (Fig. 5 512 preloading one or more game options received in 510 is started [0083]).
In Reference to Claims 14 and 24
Kerr discloses inputting data representative of the first asset into a machine learning model trained to determine the likelihood based on the input data (Fig. 4 in predicting game data assets [0076] real-world data input can refer to data obtained by a gaming platform during gameplay [0076], See also, Fig. 5 508, [0006, ]).
In Reference to Claims 15 and 25
Kerr discloses a trained model using training data indicative of historical loading times for respective assets (the model utilizes player data and historical game options indicating that they may be selected again such that the list is a prediction of past choices and as such is indicative of historical loading times) (Fig. 5 508, [0007, 0062]).
In Reference to Claims 16 and 26
Kerr discloses a trained model for a given user using training data recorded during gameplay of the given user (“player experience of gaming platform” which Examiner interprets as including game play [0009], see also real-world data input can refer to data obtained by a gaming platform during gameplay [0076]).
In Reference to Claims 17-18 and 27-28
Kerr discloses wherein the likelihood is determined based on data representative of a current gameplay state and entry into a machine learning model (within the player data 304 and player actions 306 can lead to training data 302 based on game level [0069] – game level is construed reasonably broadly to be equivalent in light of Applicant’s description of current gameplay state describing location in a virtual environment as in Spec. [0061]). See also in Kerr, “choices or options within a particular game” [0076] and “stage of game play, game type or game instance” [0069] which are used in a predictive model 104 of Fig. 4).
In Reference to Claims 20 and 30
Kerr discloses wherein the predetermined period of time for the respective other asset is
determined based on a size of the respective other asset (“preloading a threshold number of asserts or consuming a certain amount of memory resource” [0063]).
In Reference to Claims 21 and 31
Kerr discloses wherein identifying the one or more other assets comprises identifying a respective one of the other assets responsive to the determined likelihood exceeding a threshold likelihood (“include preloading a threshold number of games/assets” [0063]).
In Reference to Claim 22
Kerr discloses wherein the threshold likelihood is determined based on a size of the respective other asset (“preloading a threshold number of asserts or consuming a certain amount of memory resource” [0063]).
Claim Rejections - 35 USC § 103
12. 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.
13. 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.
14. 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.
15. Claims 19 and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Kerr in view of U.S. Pat. Pub. No. 2021/0329089 to Yellin.
Kerr discloses the invention substantially as claimed. However, the reference does not explicitly disclose the likelihood is determined based on a proportion calculated by dividing a number of times the respective other asset has previously been used within the predetermined period of time by a total number of times the first asset was loaded into memory. One of skill in the art would be aware of the teachings of Yellin.
Yellin teaches of pre-loading user applications (Titl.) to include type of content items that are games [0177] wherein examples of metrics that can be use are “a percentage of prefetched content items that are eventually accessed. This can also be provided in terms of a percentage of total prefetched content size. [0524]. Percentage of all content access requests that are being satisfied by prefetched content. This can also be provided in terms of a percentage of total accessed content size. [0525]. Yellin invents these metrics as part of his system to help access content in a timely way [0040] through the use of prefetching to reduce latency [0041].
The Supreme Court in KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 415-421, 82 USPQ2d 1385, 1395-97 (2007) identified a number of rationales to support a conclusion of obviousness of which one is:
(E) “Obvious to try” – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success;
Here, it would have been obvious to one skilled in the art at the time of the invention to modify the prediction approach of Kerr with the percentages of Yellin. This would entail considering the simple use of using proportions or percentages as a means of calculating a likelihood of occurrences over the total number of opportunities. Given the scope of the claim which can be as few as a small number of other assets to a small number of first assets, one of skill in the art would determine that given the finite number of permutations that it would have been obvious to try to formulate the claimed proportion of variables and have a reasonable expectation of success. Thus, given the use of percentages of Yellin to modify the prediction learning of Kerr, it would have been obvious to try because
Conclusion
16. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure is in the Notice of References Cited.
17. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Paul A. D’Agostino whose telephone number is (571) 270-1992.
18. 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.
19. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kang Hu can be reached on (571) 270-1344. The fax phone number for the organization where this application or proceeding is assigned is 571-270-2992.
/PAUL A D'AGOSTINO/Primary Examiner, Art Unit 3715
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