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 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim 1 is directed to a “computing device” (i.e. a machine). Claim 6 is directed to “first features comprises applying a first machine learning model to the interactive content” (i.e. a process), and claim 20 is directed to a “non-transitory, computer-readable medium storing instructions” (i.e. a manufacture), hence the claims are directed to one of the four statutory categories (i.e. process, machine, manufacture, or composition of matter). In other words, Step 1 of the subject-matter eligibility analysis is “Yes.”
However, the claims are drawn to an abstract idea in the field of interactive digital media, content comprises various elements such as levels, maps, puzzles, scenarios, virtual environments, and dynamic narratives. These elements are integral to providing the interactive experience within digital platforms. The diversity of this content is evident across different genres and formats; for instance, strategy applications typically feature complex puzzles, whereas adventure experiences may offer extensive, exploratory worlds either in the form of certain methods of organizing
human activity, in terms of following and teaching interactive educational exercises or
reasonably in the form of “mental processes,” in terms of interactive storytelling which might involve branching narratives that change based on user choices. Claims that require a computer may also recite a mental process, as described in MPEP 2106.04(a)(2)(III)(C).
Regardless, the claims are reasonably understood as either “certain methods of organizing
human activity” or “mental processes,” which require the following limitations: generating, by a first computing device, interactive content using a procedural content generator;
extracting, by the first computing device, first features from the interactive content; determining, by the first computing device, a measure of the interactive content based at least in part on the first features;
and outputting, by the first computing device, the interactive content based at least in part on the measure.
These limitations simply describe a process conducted within various development platforms or engines. Through this manual methodology, creators craft each component of the experience, from designing levels to scripting interactions, thereby creating a cohesive and engaging environment. Hence, these limitations are akin to an abstract idea which has been
identified among non-limiting examples to be an abstract idea. In other words, step 2A, Prong 1 of the subject-matter eligibility analysis is “Yes.”
Furthermore, the claims do not include additional elements that either alone or in combination are sufficient to claim a practical application because to the extent that either alone or in combination are sufficient to amount to significantly more than the judicial exception
because to the extent that, e.g., a “processor,” “computing device,” “digital media,” “machine learning model,” “computer-readable medium,” and “virtual environment” are claimed as these are merely claimed to add insignificant extra-solution activity to the judicial exception (e.g., data gathering) and/or do no more than generally link the use of a judicial exception to a particular technological environment or field of use. In other words, in the field of interactive digital media, content comprises various elements such as levels, maps, puzzles, scenarios, virtual environments, and dynamic narratives. These elements are integral to providing the interactive experience within digital platforms. The diversity of this content is evident across different genres and formats; for instance, strategy applications typically feature complex puzzles, whereas adventure experiences may offer extensive, exploratory worlds is not providing a practical application, thus Step 2A, Prong 2 of the subject-matter eligibility analysis is “No.
Likewise, the claims do not include additional elements that either alone or in combination are sufficient to amount to significantly more than the judicial exception because to the extent that a “processor,” “computing device,” “digital media,” “machine learning model,” and “virtual environment” are claimed these are all generic, well-known, and conventional computing elements. As evidence that these are generic, well-known, and conventional computing elements. US 2021/0400142 A1 to Jorasch et al. discloses a processor [0091], a computing device [0069], a digital media [2398], a machine learning model [0188], and a virtual environment [2981]. Furthermore, Applicant’s specification discloses these elements in a manner that indicates that the additional elements are sufficiently well-known that the specification does
not need to describe the particulars of such additional elements to satisfy 35 U.S.C. § 112(a), per MPEP §2106.07(a) III (a), which satisfies the Examiner’s evidentiary burden requirement per the Berkheimer memo.
Specifically, the specification describes a “processor” in para. [0018], as follows: “[0018] In a fourteenth aspect, a system includes a processor and a memory storing instructions which, when executed by the processor, cause the processor to perform operations including generating interactive content using a procedural content generator; extracting first features from the interactive content; determining a measure of the interactive content based at least in part on the first features; and outputting the interactive content based at least in part on the measure.” A “computing device” in para [0005], as follows: “[0005] In a first aspect, a method includes generating, by a first computing device, interactive content using a procedural content generator; extracting, by the first computing device, first features from the interactive content; determining, by the first computing device, a measure of the interactive content based at least in part on the first features; and outputting, by the first computing device, the interactive content based at least in part on the measure. A “digital media” in para [0002], as follows: “[0002] In the field of interactive digital media, content comprises various elements such as levels, maps, puzzles, scenarios, virtual environments, and dynamic narratives.” A “machine learning” in para [0004], as follows: “[0004] By combining procedural content generation with machine learning predictions, these techniques may filter out unusable or unsolvable content, enhancing user engagement and satisfaction.” A “virtual environment” in para [0002], as follows: “[0002] In the field of interactive digital media, content comprises various elements such as levels, maps, puzzles, scenarios, virtual environments, and dynamic narratives.
These elements are reasonably considered generic and conventional computer components. As such, the claimed limitations do not provide anything significantly more than the judicial exception. Therefore, Step 2B, of the subject-matter eligibility analysis is “No.”
In addition, dependent claims 2-5 and 7-19 do not provide a practical application and
are insufficient to amount to significantly more than the judicial exception. As such,
dependent claims 2-5 and 7-19 are also rejected under 35 U.S.C. § 101.
Therefore, claims 1-20 are rejected under 35 U.S.C. § 101 as being directed to non-
statutory subject matter.
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)(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.
Claim(s) 1-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20210400142 A1 to Jorasch et al.
Regarding claim 1, Jorasch et al. teaches a method comprising: generating, by a first computing device, interactive content using a procedural content generator; (Jorasch et al. teaches Because the game controller has information about all player actions, as well as perfect information about procedurally generated aspects of the game such as resources, non-player characters, and loot boxes, an AI module could predict when something exciting or interesting is likely to happen [1476]).
extracting, by the first computing device, first features from the interactive content; (Jorasch et al. teaches in various embodiments, biometric data is used to establish features and/or combinations of features that can be uniquely linked or tied to an individual. The following discussion represents some methods of extracting and using features according to some embodiments [1230]).
determining, by the first computing device, a measure of the interactive content based at least in part on the first features; (Jorasch et al. teaches Score field 2812 may store an indication of the score achieved in a game. If there are multiple participants that were each scored separately, then a score may be recorded for each of the participants. Winner field 2814 may store an indication of the winner of the game, if applicable. This may be a team, a user, or even a side in a game (e.g., the Werewolves won against the Vampires [0176]).
and outputting, by the first computing device, the interactive content based at least in part on the measure. (Jorasch et al. teaches in various embodiments, outputs may be generated by various components, devices, technologies, etc. For example, outputs may be generated by output device 325 and/or by output device 425. Outputs may take various forms, such as lights, colored lights, images, graphics, sounds, laser pointers, melodies, music, tones, vibrations, jingles, spoken words, synthesized speech, sounds from games, sounds from video games, etc. [0113]).
Regarding claim 2, The method of claim 1, wherein the interactive content comprises digital media configured for user interaction. (Jorasch et al. teaches libraries for digital content, providers of shared workspaces, providers of collaborative workspaces, online gaming platforms, game servers, advertisement aggregation services, advertisement distribution services, facilitators of online meetings, email servers, messaging platforms, Wiki hosts, website hosts, providers of software, providers of software-as-a-service, providers of data, providers of user data, and/or any other data storage device and/or any other service provider [0080]).
Regarding claim 3, The method of claim 2, wherein the interactive content comprises gaming content, text content, virtual reality content, or any combination thereof. (Jorasch et al. teaches thus, in various embodiments, a highlight reel may contain not only visual content, but also tactile content, audio content, and/or content for any other sensory modality, modality, or any combination of modalities [0366]; see also [0198] showing displayed visual information can include game tips, game inventory contents, images or other game characters such as teammates or enemy characters, maps, game achievements, messages from one or more other game players, advertisements, promotions, coupons, codes, passwords, secondary messaging screens, presentation slides, data from a presentation, images of other callers on a virtual call, text transcriptions of another user, sports scores and/or highlights, stock quotes, news headlines, etc.).
Regarding claim 4, The method of claim 1, wherein generating the interactive content comprises generating the interactive content based on predefined parameters and introducing randomness via a random seed or entropy source. (Jorasch et al. teaches furthermore, if a presenter needs to practice a presentation remotely in advance of the live presentation, the central controller can present a random set of emojis and images for the presenter to practice. In various embodiments, a real-time emoji dashboard is displayed to the presenter for selected reactions. The central controller should allow the meeting participants to provide emoji style feedback to the presenter in real time [1104]).
Regarding claim 5, the method of claim 1, wherein the first features comprise at least one of: structural features comprising sizes, shapes, connectivity graphs, or spatial arrangements; (Jorasch et al. teaches in various embodiments, a mouse may cause a pointer to rapidly trace and retrace the same path, thereby creating the illusion of a continuous line, ark, or other shape. I.e., the mouse may cause the mouse pointer to move so quickly that the human eye is unable to discern the mouse pointer as its own distinct object, and sees instead the path traced out by the mouse pointer. In this way, a mouse may output text, stylized text, shapes (e.g., a heart shape), images, cartoons, animations, or any other output [01347]. It further teaches If there are groups of different sizes, then the regions containing the groups may also be of different sizes. For example, suppose there are groups of sizes six, four, and two [3200].
content-specific metrics comprising a number of obstacles, available resources, paths to completion, or difficulty ratings; (Jorasch et al. teaches at step 8633, the user makes an in-game purchase, according to some embodiments. The user may purchase a game resource (e.g., a weapon, vehicle, treasure, etc.), an avatar, an aesthetic (e.g., a background image; e.g., a dwelling; e.g., a landscape), a game shortcut (e.g., a quick way to a higher-level or to a different screen; e.g., a quick way to bypass an obstacle) [0351]. It further teaches The user may identify a game title, a time to play, a game level, a league or other desired level of competition (e.g., an amateur league), a mission, a starting point, a stadium or arena (e.g., for a sports game), a time limit on the game, one or more peripheral devices he will be using (e.g., mouse and keyboard; e.g., game console controller), a user device he will be using (e.g., a personal computer; e.g., a game console; e.g., an Xbox), a character, a set of resources [0331]. It also teaches For example, central controller 110 may wish to estimate a user's skill level at a video game based on just a few minutes of play (this may allow the central controller, for example, to adjust the difficulty of the game) [0189]).
statistical features comprising distributions of elements, frequencies of certain patterns, randomness indicators; or semantic features comprising narrative arcs, character interactions, emotional tones, pacing; or a combination thereof. (Jorasch et al. teaches An AI module could then predict how the player would respond to different variations of in-game content, difficulty level, in-game loot, resource levels or other aspects of gameplay in order to elicit particular emotional responses, such as excitement or fear. Likewise, an AI module could predict how a player would respond to variation in game play to increase engagement, game play time, amount of money spent-in game, levels of social interaction among players, or another goal of the game controller [1473]).
Regarding claim 6, The method of claim 5, wherein extracting the first features comprises applying a first machine learning model to the interactive content. (Jorasch et al. teaches Referring to FIG. 35, a diagram of an example of ‘AI models’ Table 3500 according to some embodiments is shown. As used herein, “AI” stands for artificial intelligence. An AI model may include any machine learning model, any computer model, or any other model that is used to make one or more predictions, classifications, groupings, visualizations, or other interpretations from input data [0188]).
Regarding claim 7, The method of claim 1, wherein determining the measure comprises determining the measure using a second machine learning model, wherein the measure indicates a likelihood that the interactive content is solvable by a user. (Jorasch et al. teaches For example, synchronizing lights on a keyboard or mouse with combinations of lights in a game could solve a puzzle or be used as a key to open a door [1479]).
Regarding claim 8, The method of claim 7, wherein the second machine learning model is trained on historical data comprising examples of solvable and unsolvable interactive content. (Jorasch et al. teaches In one example, a user's FIDE chess rating could be stored for use on a chess playing website. Last login field 2720 may store an indication of the time when a user last logged into a game, game environment, game server, or the like. In some embodiments, table 2700 may store a user's login name, which may differ from their screen name. The login name may be used to identify the user when the user first logs in [0175]).
Regarding claim 9, The method of claim 1, further comprising: determining that the measure satisfies a first predefined threshold; and outputting the interactive content in response to determining that the measure satisfies the first predefined threshold (Jorasch et al. teaches At block 10103, the values for variables M, C, and H are determined. Exemplary values might be 5, 11, and 77, respectively. The variable M is then compared to the predefined threshold of zero. If M is equal to zero, then it is inferred that the user is not present (block 10106) [1505]).
Regarding claim 10, The method of claim 9, further comprising: determining a difficulty level based on user interaction data associated with a user; and adjusting the first predefined threshold based on the difficulty level. (Jorasch et al. teaches the difficulty of the achievement, the level of the achievement, or any other aspect of the achievement. Examples of achievement types may include ‘professional’, ‘gaming’, ‘educational’, or any other achievement type. Achievement field 1710 may store an indication of the actual achievement. Example achievements may include: the user got through all three out of three meeting agenda items; the user received 10 positive tags relating to the quality of their ideas; the user provided additional insights regarding the tags of 25 other users, the user learned pivot tables in Excel®; or any other achievement [0156]. It also further teaches If the player falls below a threshold amount, such as a reaction time of 90% or less of normal, then the mouse could be instructed to end current game play for a predetermined period of time, such as one hour. After that hour is up, the user would again have access to the mouse, but further checks of reaction time would be made. The mouse could also end game play if the user appeared to not be playing their best game [1367]).
Regarding claim 11, The method of claim 1, further comprising: determining that the measure does not satisfy the first predefined threshold; and refraining from outputting the interactive content in response to determining that the measure does not satisfy the first predefined threshold. (Jorasch et al. teaches when in a restricted setting, a user may be required to re-authenticate to maintain access if any of their credentials expire and their authentication score dips below the necessary level. They must regain the needed score within a threshold timeframe or have their access revoked [1836]).
Regarding claim 12, The method of claim 1, wherein outputting the interactive content comprises transmitting the interactive content to a second computing device associated with a user. (Jorasch et al. teaches In various embodiments, a control signal received from user 2 can be used directly (e.g., can be directly transmitted to the user device of user 1; e.g., can be directly used for controlling a game character of user 1), without modification. The peripheral device of user 1 would then be simply relaying the control signal received from user 2 [0359]).
Regarding claim 13, the method of claim 1, further comprising: receiving, by the first computing device, user interaction data associated with the interactive content. (Jorasch et al. teaches asset library table 1900 may store records of digital assets, such as music, movies, TV shows, videos, games, books, e-books, textbooks, presentations, spreadsheets, newspapers, blogs, graphic novels, comic books, lectures, classes, interactive courses, exercises, cooking recipes, podcasts, software, avatars, etc. These assets may be available for purchase, license, giving out as rewards, etc. For example, a user may be able to purchase a music file from the central controller 110. As another example, a user who has achieved a certain number of five star tags for excellence in meeting facilitation may have the opportunity to download a free electronic book [0160]).
and updating the first machine learning model, the second machine learning model, or a combination thereof, based on the user interaction data. (Jorasch et al. teaches The peripheral device may, in turn, process any received inputs before interpreting such inputs or converting such inputs into an output or result. For example, a mouse may detect a raw motion (i.e., a change in position of the mouse itself), but may then multiply the detected motion by some constant factor in order to determine a corresponding motion of the cursor. [0141}
Regarding claim 14, A system comprising: a processor; and a memory storing instructions which, when executed by the processor, cause the processor to perform operations including: generating interactive content using a procedural content generator; (Jorasch et al. teaches Because the game controller has information about all player actions, as well as perfect information about procedurally generated aspects of the game such as resources, non-player characters, and loot boxes, an AI module could predict when something exciting or interesting is likely to happen [1476]).
extracting, by the first computing device, first features from the interactive content; (Jorasch et al. teaches in various embodiments, biometric data is used to establish features and/or combinations of features that can be uniquely linked or tied to an individual. The following discussion represents some methods of extracting and using features according to some embodiments [1230]).
determining, by the first computing device, a measure of the interactive content based at least in part on the first features; (Jorasch et al. teaches Score field 2812 may store an indication of the score achieved in a game. If there are multiple participants that were each scored separately, then a score may be recorded for each of the participants. Winner field 2814 may store an indication of the winner of the game, if applicable. This may be a team, a user, or even a side in a game (e.g., the Werewolves won against the Vampires [0176]).
and outputting, by the first computing device, the interactive content based at least in part on the measure. (Jorasch et al. teaches in various embodiments, outputs may be generated by various components, devices, technologies, etc. For example, outputs may be generated by output device 325 and/or by output device 425. Outputs may take various forms, such as lights, colored lights, images, graphics, sounds, laser pointers, melodies, music, tones, vibrations, jingles, spoken words, synthesized speech, sounds from games, sounds from video games, etc. [0113]).
Regarding claim 15, The system of claim 14, wherein the interactive content comprises digital media configured for user interaction. (Jorasch et al. teaches in some embodiments, displayed visual information can include game tips, game inventory contents, images or other game characters such as teammates or enemy characters, maps, game achievements, messages from one or more other game players, advertisements, promotions, coupons, codes, passwords, secondary messaging screens, presentation slides, data from a presentation, images of other callers on a virtual call, text transcriptions of another user, sports scores and/or highlights, stock quotes, news headlines, etc. [0198]).
Regarding claim 16, The system of claim 15, wherein the interactive content comprises gaming content, text content, virtual reality content, or any combination thereof. (Jorasch et al. teaches thus, in various embodiments, a highlight reel may contain not only visual content, but also tactile content, audio content, and/or content for any other sensory modality, modality, or any combination of modalities [0366]).
Regarding claim 17, The system of claim 14, wherein generating the interactive content comprises generating the interactive content based on predefined parameters and introducing randomness via a random seed or entropy source. (Jorasch et al. teaches furthermore, if a presenter needs to practice a presentation remotely in advance of the live presentation, the central controller can present a random set of emojis and images for the presenter to practice. In various embodiments, a real-time emoji dashboard is displayed to the presenter for selected reactions. The central controller should allow the meeting participants to provide emoji style feedback to the presenter in real time [1104]).
Regarding claim 18, the method of claim 14, wherein the first features comprise at least one of: structural features comprising sizes, shapes, connectivity graphs, or spatial arrangements; (Jorasch et al. teaches in various embodiments, a mouse may cause a pointer to rapidly trace and retrace the same path, thereby creating the illusion of a continuous line, ark, or other shape. I.e., the mouse may cause the mouse pointer to move so quickly that the human eye is unable to discern the mouse pointer as its own distinct object, and sees instead the path traced out by the mouse pointer. In this way, a mouse may output text, stylized text, shapes (e.g., a heart shape), images, cartoons, animations, or any other output [01347]. It further teaches If there are groups of different sizes, then the regions containing the groups may also be of different sizes. For example, suppose there are groups of sizes six, four, and two [3200]).
content-specific metrics comprising a number of obstacles, available resources, paths to completion, or difficulty ratings; (Jorasch et al. teaches at step 8633, the user makes an in-game purchase, according to some embodiments. The user may purchase a game resource (e.g., a weapon, vehicle, treasure, etc.), an avatar, an aesthetic (e.g., a background image; e.g., a dwelling; e.g., a landscape), a game shortcut (e.g., a quick way to a higher-level or to a different screen; e.g., a quick way to bypass an obstacle) [0351]. It further teaches The user may identify a game title, a time to play, a game level, a league or other desired level of competition (e.g., an amateur league), a mission, a starting point, a stadium or arena (e.g., for a sports game), a time limit on the game, one or more peripheral devices he will be using (e.g., mouse and keyboard; e.g., game console controller), a user device he will be using (e.g., a personal computer; e.g., a game console; e.g., an Xbox), a character, a set of resources [0331]. It also teaches For example, central controller 110 may wish to estimate a user's skill level at a video game based on just a few minutes of play (this may allow the central controller, for example, to adjust the difficulty of the game) [0189]).
statistical features comprising distributions of elements, frequencies of certain patterns, randomness indicators; or semantic features comprising narrative arcs, character interactions, emotional tones, pacing; or a combination thereof. (Jorasch et al. teaches An AI module could then predict how the player would respond to different variations of in-game content, difficulty level, in-game loot, resource levels or other aspects of gameplay in order to elicit particular emotional responses, such as excitement or fear. Likewise, an AI module could predict how a player would respond to variation in game play to increase engagement, game play time, amount of money spent-in game, levels of social interaction among players, or another goal of the game controller [1473]).
Regarding claim 19, the system of claim 18, wherein extracting the first features comprises applying a first machine learning model to the interactive content (Jorasch et al. teaches Referring to FIG. 35, a diagram of an example of ‘AI models’ Table 3500 according to some embodiments is shown. As used herein, “AI” stands for artificial intelligence. An AI model may include any machine learning model, any computer model, or any other model that is used to make one or more predictions, classifications, groupings, visualizations, or other interpretations from input data [0188]).
Regarding claim 20, A non-transitory, computer-readable medium storing instructions which, when executed by a processor, cause the processor to perform operations comprising: generating interactive content using a procedural content generator; (Jorasch et al. teaches Because the game controller has information about all player actions, as well as perfect information about procedurally generated aspects of the game such as resources, non-player characters, and loot boxes, an AI module could predict when something exciting or interesting is likely to happen [1476]).
extracting, by the first computing device, first features from the interactive content; (Jorasch et al. teaches in various embodiments, biometric data is used to establish features and/or combinations of features that can be uniquely linked or tied to an individual. The following discussion represents some methods of extracting and using features according to some embodiments [1230]).
determining, by the first computing device, a measure of the interactive content based at least in part on the first features; (Jorasch et al. teaches Score field 2812 may store an indication of the score achieved in a game. If there are multiple participants that were each scored separately, then a score may be recorded for each of the participants. Winner field 2814 may store an indication of the winner of the game, if applicable. This may be a team, a user, or even a side in a game (e.g., the Werewolves won against the Vampires [0176]).
and outputting, by the first computing device, the interactive content based at least in part on the measure. (Jorasch et al. teaches in various embodiments, outputs may be generated by various components, devices, technologies, etc. For example, outputs may be generated by output device 325 and/or by output device 425. Outputs may take various forms, such as lights, colored lights, images, graphics, sounds, laser pointers, melodies, music, tones, vibrations, jingles, spoken words, synthesized speech, sounds from games, sounds from video games, etc. [0113]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 20250050221 A1 teaches Presently available game titles and other interactive titles may allow a user to customize objects or characters for use during gameplay sessions and other interactive virtual sessions. The system includes interactive gameplay that comprises of customization allows, for example, objects or characters to match or otherwise reflect a particular user's personality, likes/dislikes, preferences, mannerisms, looks, etc. US 20250041717 A1 teaches For example, gameplay objectives may correspond to reaching certain levels within the virtual environment of the game title, achieving a certain number of points or other recognition, performing better in relation to other players or characters (e.g., winning a race, fight), and other metrics or statuses under the rules of the game title. The system includes virtual reality content which is included in the gameplay where users can explore and interact.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SENIYA BAIG whose telephone number is (571)270-0447. The examiner can normally be reached Monday-Thursday 7:30am-5:00pm, Friday 7:30am-4:00pm.
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, Xuan Thai can be reached at (571) 272-7147. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/S.B./Examiner, Art Unit 3715
/WILLIAM H MCCULLOCH JR/Primary Examiner, Art Unit 3715
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