Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
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 an abstract idea specifically parental control based on criteria (ratings) without significantly more. The independent claims describe receiving user inputs, using artificial intelligence to analyze each media content member to assign ratings for each of the plurality of content categories for each media content member of a library of media content; analyzing the library comprises using artificial intelligence to review each media content member and identify content portions corresponding to the content ratings; identifying objectionable portions of content; and generating a dynamic library of content and altering content during playback. Nothing in the claim elements preclude the steps from practically being performed in the human mind. This feature is a mental process.
This judicial exception is not integrated into a practical application because the additional elements link to generic components like “digital content controller”, “user interface” or “user interface device”. The claims emphasis on the functional result of altering media rather than a technical improvement to computer functionality. The additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, when considered separately and in combination, they do not add significantly more to the exception. The additional limitations such as “receiving user inputs via a user interface of a digital content controller” or “receive user inputs via a user interface of a digital content controller”, “using artificial intelligence to analyze each of a plurality of media content members …to review each media content member to identify content ratings…and identify portion of content…automatically building a dynamic library…configured to be altered during playback by removing or replacing or more objectionable portions of content” encompass: a generic input step using conventional computer performing its standard function, a generic tool (AI) of automatic function, data classification using conventional machine routines, creating/updating of data repository in conventional computing system, and the functional result of the process. The combination of these additional elements in claims is not indicative of integration into a practical application and the claims do not provide an invention concept. The claims fail to include additional elements that are sufficient to amount to significantly more than the judicial exception because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are ineligible.
Claims 2-10 and 12-20 are directed to an abstract idea and ineligible as addressed above. The combination of the additional elements in claims 2-10 and 12-20 is not indicative of integration into a practical application and the claims do not provide an invention concept. The claims fail to include additional elements that are sufficient to amount to significantly more than the judicial exception because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are ineligible.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 10, 11, 12, 15, 16, 18 and 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 10 recite the limitation "wherein AI media agent” in line 1. It is unclear whether it is different from “an artificial intelligence (AI) media agent” previously defined in claim 1.
Claim 11 recites the limitation "the AI agent” in lines 2, 6, 13 and 15. There is insufficient antecedent basis for this limitation in the claim. Also, it is unclear whether the preamble “a media artificial (AI) agent” referring to a media artificial intelligence agent
Claims 12, 15, 16 and 18 recite the limitation "the AI media agent” in line 1. There is insufficient antecedent basis for this limitation in the claims.
Regarding claim 20 recites “wherein AI media agent” in line 1. It is unclear whether it is different from “a media artificial (AI) agent” previously defined in claim 11.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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.
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-9 and 11-19 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Cobb (US 20190387275 A1) in view of Dhiman et al. (US 20220312075 A1).
Regarding claim 1, Cobb teaches a method for a digital content controller comprising:
receiving user inputs via a user interface of a digital content controller (e.g., use interface 100 – FIG. 1) comprising respective levels of user-defined content filters for a plurality of content categories (receiving user input via, parental controls user interface 100, comprising a list of the multiple rating categories with a range from low to high, which could correlate to a mature to family-friendly scale. See FIG. 1, 0057, 0065, 0104);
using artificial intelligence to analyze each of a plurality of media content members of
a library of media content to assign ratings for each of the plurality of content categories for
each media content member of the library (the rating system provides for all media entities loaded into the master database 50 (see FIG. 11) can have a rating assigned to it. If a media entity doesn't have one, it is unrated, which is treated as the highest possible rating. (when a media entry is added to the database, ratings are assigned to it both programmatically (from external rating sources like MPAA, IMDB, and Dove) and edited and reviewed by a system administrator editor. The ratings are organized into multiple categories, e.g., sex, violence, drugs, etc, and entered using artificial intelligence. See 0071, 0072), wherein the operation of analyzing the library comprises using artificial intelligence to review each media content member to identify content ratings for each of the plurality of content categories (artificial intelligence reviews and rates content. See 0106);
identifying objectionable portions of content based on the plurality of content ratings
compared to the respective levels of user-defined content filters (monitoring media content portions according appropriate and inappropriate content, and associating alphabetic, numeric and/or alphanumeric ratings for objectionable content, e.g., in the categories of sex, language, violence, drugs, nudity, media rating systems and other inappropriate elements – see 0049); and
automatically building a dynamic library of content appropriate for respective levels
of user-defined content filters, wherein the dynamic library comprises media content meeting
the respective levels of user-defined content filters (the system 10 can access in order to help build a library of content ratings 302 within server 30. See FIG. 11. This process could be done automatically by the system 10 by pulling the information from other sources and propagating the fields 308 that are seen in the interface 300. The library 302 may collect ratings from an existing provider 304 and build the library from pre-existing information. The system 10 could also produce an edit list or a library of content that has been edited for inappropriate material. See 0060, 0086) and media content configured to be altered during playback by removing or replacing one or more objectionable portions of content (the library 204 of media content can be built within the system 10 and saved on the server 30. If the content is segmented into rated content chunks, the system may only block the chunks of content that are offensive. See 0059, 0078, 0103).
Cobb teaches the process of automatic filtering and trigger generation in use with at least a community source, a user interface, and artificial intelligence 2010. See FIG. 31 and 0129. Cobb does not explicitly disclose using artificial intelligence to identify portions of content corresponding to the content ratings for each of the plurality of content categories. Dhiman discloses identifying segments of media assets corresponding to parental ratings and categories using machine learning and artificial intelligence techniques. See 0065-0066. It would have been obvious to one of ordinary skill in the art at the time invention was made to modify to modify Cobb by using artificial intelligence to identify portions of content corresponding to the content ratings for each of the plurality of content categories as disclosed or taught by Dhiman to efficiently detect parental ratings and categories of segments of media assets in an automated manner.
Regarding claim 2, Cobb further discloses that a user interface for the user to define a block list of media content (blocklist 2018 – see FIG. 31, 0132).
Regarding claim 3, Cobb in combination with Dhiman teaches that the block list includes a sub-genre identification of content (Cobb: blocklist - see FIG. 31; Dhiman: user preferences for restricted viewing content indicate combination of parental rating and category of content or ratings with sub-ratings for classification of media content, e.g., “PG and abuse”, “18-violence” – see 0063, 0066).
Regarding claim 4, Cobb in view of Dhiman teaches that the sub-genre identification of content is determined via artificial intelligence review of at least one of the media content and metadata associated with the media content (the content analyzer and classifier 310 uses machine learning and artificial intelligence techniques in order to identify parental ratings and categories for classifications of media content – see Dhiman: 0066).
Regarding claim 5, Cobb teaches that the AI media agent provides curated media content based at least in part on the block list (e.g., media content with all or any undesirable portions blocked. The process of automatic comparing the media content to blocklist 2018 and filtering in use with at least a community source, a user interface, and artificial intelligence 2010, where the blocklist indicates listing of media content with all or any undesirable portions blocked according to according to one or more predefined ratings. See FIG. 31, 0129, 0132, 0133).
Regarding claim 6, Cobb teaches that the AI media agent provides a user interface for the user to define a whitelist of media content (the process of comparing the media content to a whitelist 2022 in use with at least user interface 100, user interface 200, server 30, and artificial intelligence. The whitelist is defined by the user, using the user interface – see 0129, 0132).
Regarding claim 7, the combination of Cobb and Dhiman teaches that wherein the whitelist includes a sub-genre identification of content determined via artificial intelligence review of at least one of the media content and metadata associated with the media content (the content analyzer and classifier 310 uses machine learning and artificial intelligence techniques in order to identify parental ratings and categories for classifications of media content – see Dhiman: 0066; the whitelist indicates listing of media desired portions identified according to one or more predefined ratings – see Cobb: 0106, 0132).
Regarding claim 8, Cobb teaches that wherein the AI media agent provides curated media content based at least in part on the whitelist (e.g., appropriate, desirable portions or non-offensive media content. The process of automatic comparing the media content to whitelist 2022 and filtering in use with at least a community source, a user interface, and artificial intelligence 2010, where the whitelist indicates listing of media desired portions identified according to one or more predefined ratings. See FIG. 31, 0106, 0132, 0133).
Regarding claim 9, Cobb teaches that the media content configured to be altered is altered during playback on a local network or cloud network under the control of the user (the media player is modified to replace the offensive content with transition content or no content that would offer a safe user experience without too much disruption to the consumption media. See 0056).
Regarding claims 11-19, see rejection of claims 1-9, respectively.
Claims 10 and 20 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Cobb (US 20190387275 A1) in view of Dhiman et al. (US 20220312075 A1) and further in view of Hermoni et al. (US 11568280 B1).
Regarding claim 10, the combination of Cobb and Dhiman does not teach that wherein AI media agent is instantiated on an edge AI processing network located within a local network or cloud network under control of the user. Hermoni teaches a system for parental controls based on artificial intelligence comprising an artificial intelligence (AI) server coupled to a network. Based on the explicit user input, the AI server may create implicit filters to more accurately present content that is of interest to the user. The media presented may include media on a home media server (e.g., owned locally) or on a cloud based system. See abstract; FIG. 4; col. 3, lines 2-7; col. 4, lines 59-67; col. 5, lines 5-10. It would have been obvious to one of ordinary skill in the art at the time invention was made to modify the combination of Cobb and Dhiman by including AI media agent is instantiated on an edge AI processing network located within a local network or cloud network under control of the user as taught or suggested by Hermoni to increase effectiveness of providing parental controls using AI trained based on the user input in order to present content to the user more accurately and appropriately.
Regarding claim 20, see rejection of claim 10.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Asarikuniyil et al. (US 20220368985 A1) teach methods, computer-readable media, and systems for filtering content based on improved content classification.
Dhiman et al. (US 20220248089 A1) teach systems and methods are described to selectively stream content based on parental control ratings.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NGOC K VU whose telephone number is (571)272-7306. The examiner can normally be reached Monday & Thursday: 10AM-6:30PM EST; Tuesday, Wednesday & Friday: out of office.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, NATHAN FLYNN can be reached at 571-272-1915. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/NGOC K VU/Primary Examiner, Art Unit 2421
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