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 .
DETAILED ACTION
2. This action is in response to the Amendment filed July 31, 2026.
3. Claims 21, 26, 31, and 36 have been amended.
4. Claims 21-40 have been examined and are pending with this action.
Response to Arguments
5. Applicant's arguments filed July 31, 2026 with respect to the rejection of claims 21-40, have been fully considered but are moot because the arguments do not apply to any of the references being used in the current rejection.
After further searching and consideration, Fidaleo (US 2022/0398395 A1), herein referenced Fidaleo, has been cited to better teaches the steps of independent claims 21, 26, 31, and 36, as newly amended. Please see rejections set forth below.
For the reasons above and the rejections set forth below, claims 21-40 have been rejected and remain pending.
Claim Rejections - 35 USC § 102
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 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.
6. Claims 21-22, 24-27, 29-32, 34-37, and 39-40-40 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Fidaleo (US 2022/0398395 A1).
INDEPENDENT:
As per claim 21, Fidaleo teaches a first user device, comprising:
first circuitry configured to execute a first artificial intelligence topology partition defining an operational role within a distributed artificial intelligence topology (see Fidaleo, Fig. 2; [0031]: “It is noted that, in some implementations, one or both of social agent software code 110/210 and social agent client application 266 may include one or more machine learning models, such as NNs, for example. Social agent client application 266 is configured to create personalized dialogue 148/248 for user 118 by filling one or more placeholder fields included in selected dialogue template 122/222, selected by social agent software code 110/210, utilizing user data obtained from user database 264.”; [0039]: “Referring to FIG. 4 in combination with FIGS. 1 and 2, flowchart 470 begins with receiving, from client system 150/250, input data 128/228 provided by user 118 of client system 150/250 when user 118 is interacting with social agent system 100/200 using client system 150/250 (action 471).”; and [0043]: “based on a verbal expression, a non-verbal expression, or a combination of verbal and non-verbal expressions described by input data 128/228, processing hardware 104/204 may execute social agent software code 110/220 to determine a goal of user 118, for example, using a machine learning predictive model included in social agent software code 110/210.”); and
the first circuitry being configured to carry out the operational role by selectively applying personal data stored locally at the first user device to population-ready generated output received from a remote artificial intelligence topology partition associated with a second user device, wherein the personal data remains stored locally at the first user device and is not transmitted to the remote artificial intelligence topology partition (see Fidaleo, [0010]: “As stated above, a characteristic feature of human social interaction is personalization”; [0031]: “Social agent client application 266 is configured to create personalized dialogue 148/248 for user 118 by filling one or more placeholder fields included in selected dialogue template 122/222, selected by social agent software code 110/210, utilizing user data obtained from user database 264. According to various implementations of the present disclosure, social agent client application 266 enables user 118 to selectively restrict access to the user data stored locally on client system 150/250 by social agent system 100/200, while advantageously enabling use of that restricted user data to create personalized dialogue 148/248 from selected dialogue template 122/222.”; [0047]: “As a result, that user data may be sequestered on client system 150/250 and may be used locally on client system 150/250 by social agent client application 266 in action 474 to create personalized dialogue 148/248, using selected dialogue template 122/222, for responding to user 118.”; and [0051]: “Flowchart 580 further includes receiving, from social agent system 100/200, dialogue template 122/222 for responding to user 118, dialogue template 122/222 including at least one placeholder field configured to be filled by client system 150/250 (action 582). As noted above, dialogue template 122/222 is selected in action 473 described above by social agent software code 110/210 of social agent system 100/200 from among multiple predetermined dialogue templates 122a-122c/222a-222c. Selected dialogue template 122/222 may be received in action 582 by social agent client application 266, executed by hardware processor 254 of client system 150/250, via communication network 112 and network communication links 114/214.”), wherein:
the population-ready generated output comprises at least one population-ready portion having a tag identifying a category of replaceable content and default content associated with the tag, (see Fidaleo, Abstract: “The processing hardware is further configured to execute the social agent software code to deliver, to the client system, the dialogue template including the one or more placeholder fields to be filled by the client system to create the personalized dialogue for responding to the user.”; [0023]: “Selected dialogue template 122, as well as dialogue templates 122a-122c, each includes one or more placeholder fields to be filled by client system 150 using user data stored on client system 150 and inaccessible to social agent system 100, to create a personalized dialogue for responding to user 118. Social agent system 100 may then deliver, to client system 150, selected dialogue template 122 including the one or more placeholder fields to be filled by client system 150 to create personalized dialogue 148, using selected dialogue template 122.”; and [0024]: “Client system 150 may receive selected dialogue template 122 from social agent system 100, and may identify user data stored locally on client system 150 for filling the one or more placeholder fields included in selected dialogue template 122. Client system may then fill the one or more placeholder fields using the user data to create personalized dialogue 148 for responding to user 118, and may execute the personalized dialogue, using one or more output devices of client system 150, such as display 158, or using wireless communication link 115 to control output devices of social agent 116b”) and
the first circuitry is configured to identify, from the personal data, replacement content corresponding to the category and locally replace the default content with the replacement content after receipt of the population-ready generated output (see Fidaleo, [0048]: “In some implementations, the privacy level restricting access to the user data stored in user database 264 of client system 150/250 may be predetermined and fixed. For example, in some of those implementations, the user data stored in user database 264 may include personally identifiable information (PII) of user 118, and social agent client application 266 may be configured to make all PII unavailable to social agent system 100/200. However, in other implementations, it may be advantageous or desirable to enable user 118 to control their preferred level of privacy by selecting that privacy level from multiple predetermined alternative privacy levels using social agent client application 266.”; [0051]: “Flowchart 580 further includes receiving, from social agent system 100/200, dialogue template 122/222 for responding to user 118, dialogue template 122/222 including at least one placeholder field configured to be filled by client system 150/250 (action 582).”; and [0052]: “For example, the user data for filling the one or more placeholder fields included in selected dialogue template 122/222 may be identified by searching user database 264 on client system 150/250. That user data may be identified and obtained from user database 264 in action 583 by social agent client application 266, executed by hardware processor 254 of client system 150/250.”).
As per claim 26, Fidaleo teaches a user device within an artificial intelligence infrastructure, the user device comprising:
first circuitry configured to carry out defined operations corresponding to a local topology partition of an artificial intelligence based topology (see Claim 21 rejection above); and
the first circuitry being configured to select at least one node of the artificial intelligence based topology from a plurality of personalized nodes associated with a respective third parties based on the personal data locally at the user device, wherein the personal data is not transmitted to the selected node (see Claim 21 rejection above), wherein:
the defined operations generate an outcome based on the personal data locally at the user device (see Claim 21 rejection above), and
the first circuitry selects the at least one node based on the outcome without transmitting the personal data used to generate the outcome to the selected node (see Claim 21 rejection above).
As per claim 31, Fidaleo teaches a user device, comprising:
processing circuitry configured to receive generated output from a remote artificial intelligence node (see Fidaleo, Fig. 1-Fig. 3B; [0018]: “More generally, system 100 may include one or more computing platforms 102, such as computer servers for example, which may be co-located, or may form an interactively linked but distributed system, such as a cloud-based system, for instance. As a result, processing hardware 104 and system memory 106 may correspond to distributed processor and memory resources within system 100”; and Claim 21 rejection above);
memory circuitry configured to store personal data (see Fidaleo, [0015]: “As shown in FIG. 1, social agent system 100 (hereinafter “system 100”) includes computing platform 102 having processing hardware 104 and system memory 106 implemented as a non-transitory storage medium”; [0048]: “in some of those implementations, the user data stored in user database 264 may include personally identifiable information (PII) of user 118, and social agent client application 266 may be configured to make all PII unavailable to social agent system 100/200. However, in other implementations, it may be advantageous or desirable to enable user 118 to control their preferred level of privacy by selecting that privacy level from multiple predetermined alternative privacy levels using social agent client application 266.”; and Claim 21 rejection above); and
the processing circuitry being configured to selectively apply at least a portion of the personal data locally at the user device within a secure local topology partition to personalize the generated output after generation by the remote artificial intelligence node without transmitting the personal data to the remote artificial intelligence node (see Claim 21 rejection above), wherein:
the generated output comprises at least one population-ready portion having a tag identifying a category of replaceable content and default content associated with the tag (see Claim 21 rejection above), and
the processing circuitry is configured to identify, from the personal data, replacement content corresponding to the category and locally replace the default content with the replacement content (see Claim 21 rejection above).
As per claim 36, Fidaleo teaches a user device, comprising:
processing circuitry configured to receive generated image output from a remote artificial intelligence node, the generated image output being personalizable (see Fig. 1-Fig. 3B; [0055]: “In some implementations, personalized dialogue 148/248 may take the form of language based verbal communication by social agent 116a. Moreover, in some implementations, output unit 240/340 may include display 158/358. In those implementations, personalized dialogue 148/248 may be executed by being rendered as text on display 158/358 of client system 150/250.”; and Claims 21 & 31 rejections above);
memory circuitry configured to store personal image data (see Claims 21 & 31 rejections above); and
the processing circuitry being configured to selectively apply at least a portion of the personal image data locally at the user device within a secure local topology partition to personalize the generated output without transmitting the personal image data to the remote artificial intelligence node (see Claims 21 & 31 rejections above), wherein:
the generated image output comprises a plurality of separately personalizable image portions, at least one of the separately personalizable image portions being associated with a population tag (see Claim 21 rejection above), and
the processing circuitry is configured to select, based on the population tag, a corresponding personalized image element derived from the personal image data and locally replace or modify the at least one separately personalizable image portion using the corresponding personalized image element (see Claim 21 rejection above).
DEPENDENT:
As per claims 22, 27, 32 and 37, which respectively depend on claims 21, 26, 31, and 36, Fidaleo further teaches wherein: the first user device is operable to allow recipients to personalize shared content (see Fidaleo, [0010]: “As stated above, a characteristic feature of human social interaction is personalization”; [0027]: “Thus, social agent system 200 may share any of the characteristics attributed to social agent system 100 by the present disclosure, and vice versa. That is to say, although not shown in FIG. 1, like social agent system 200, social agent system 100 may include transceiver 208.”; and [0036]: “Output unit 340 corresponds in general to output unit 240, in FIG. 2. Thus, output unit 240 may share any of the characteristics attributed to output unit 340 by the present disclosure, and vice versa.”).
As per claims 24, 29, 34, and 39, which respectively depend on claims 21, 26, 31, and 36, Cummings further teaches wherein: the first user device is operable to support secure output personalization (see Fidaleo, [0023]: “Processing hardware 104 of computing platform 102 may execute social agent software code 110 to select, using input data 128, one of dialogue templates 122a-122b (i.e., selected dialogue template 122) for responding to user 118. Selected dialogue template 122, as well as dialogue templates 122a-122c, each includes one or more placeholder fields to be filled by client system 150 using user data stored on client system 150 and inaccessible to social agent system 100,”; [0031]: “According to various implementations of the present disclosure, social agent client application 266 enables user 118 to selectively restrict access to the user data stored locally on client system 150/250 by social agent system 100/200”; and [0047]: “”According to various implementations of the present disclosure, social agent client application 266 enables user 118 to selectively restrict access to the user data stored locally on client system 150/250 by social agent system 100/200).
As per claims 25, 30, 35, and 40, which respectively depend on claims 21, 26, 31, and 36, Cummings further teaches wherein: the first user device is operable to use public and private data for secure communication and anonymous advertising (see Fidaleo, [0002]: “concerns regarding personal privacy, data security, and liability for data breaches make it increasingly advantageous, for users and system administrators alike, to provide users with the ability to restrict access to their personal user data while continuing to enable use of such data to personalize their interactions with a social agent” [0048]: “One or more user selectable intermediate privacy levels may partially anonymize the user data made available to social agent system 100/200.”; and [0049]: “In some implementations, social agent client application 266 may be configured to partially anonymize user data other than PII, using a proto-object as a proxy for a famous or otherwise identifiable object favored by user 118.”).
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 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.
7. Claims 23, 28, 33, and 38 are rejected under 35 U.S.C. 103 as being unpatentable over Fidaleo (US 2022/0398395 A1) in view of Rouhani et al. (US 2021/0019605 A1).
As per claims, which respectively depend on claims 23, 28, 33, and 38, although Fidaleo further teaches wherein: the first user device is operable to ensure data flow security, digital rights management, and malware prevention (see Fidaleo, [0023]: “Processing hardware 104 of computing platform 102 may execute social agent software code 110 to select, using input data 128, one of dialogue templates 122a-122b (i.e., selected dialogue template 122) for responding to user 118. Selected dialogue template 122, as well as dialogue templates 122a-122c, each includes one or more placeholder fields to be filled by client system 150 using user data stored on client system 150 and inaccessible to social agent system 100,”; [0031]: “According to various implementations of the present disclosure, social agent client application 266 enables user 118 to selectively restrict access to the user data stored locally on client system 150/250 by social agent system 100/200”; and [0047]: “”According to various implementations of the present disclosure, social agent client application 266 enables user 118 to selectively restrict access to the user data stored locally on client system 150/250 by social agent system 100/200), Fidaleo does not explicitly teach operable to ensure watermarking.
Rouhani teaches a device operable to ensure watermarking (see Rouhani, [0004]: “Systems, methods, and articles of manufacture, including computer program products, are provided for embedding a digital watermark in a machine learning model”; and [0012]: “In some variations, the first digital watermark may be embedded in a first copy of the first machine learning model distributed to a first client. A third digital watermark may be embedded in a second copy of the first machine learning model distributed to a second client. The first client may be determined to be a source of the second machine learning model based at least on the second digital watermark extracted from the second machine learning model matching first digital watermark embedded in the first copy of the first machine learning model.”).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the invention to modify the system of Fidaleo in view of Rouhani by implementing a device operable to ensure watermarking. One would be motivated to do so because digital watermarking is well known routine and conventional for embedding, identifying or verification information into a digital content for ownership/copyright/authenticity identification/verification, tamper detection, content tracking, and also enables users to know content was created by AI.
Conclusion
8. For the reasons above, claims 21-40 have been rejected and remain pending.
9. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
10. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL Y WON whose telephone number is (571)272-3993. The examiner can normally be reached on Wk.1: M-F: 8-5 PST & Wk.2: M-Th: 8-7 PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nicholas R Taylor can be reached on 571-272-3889. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Michael Won/Primary Examiner, Art Unit 2443
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