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 .
This Office Action is responsive to: RCEX filed 01 Jan. 2026
Claims 1-20 are pending in this case. Claims 1, 8 and 16 are independent claims
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 01 Jan. 2026 has been entered.
Applicant’s Response
In Applicant’s Response dated 01 Jan. 2026, Applicant amended claims 1, 8 and 16; argued against all rejections previously set forth in the Office Action dated 07 Oct. 2025.
Claim Rejections - 35 USC § 103
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.
Claims 1-3, 7- 11 and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Setlur et al. (Pat. No.: US 12,217,000 B1; Filed: Sep. 10, 2021)(hereinafter “Setlur”) in view of Mishchenko et al. (Pat. No.: US 11,922,144 B1; Filed: Mar. 20, 2023)(hereinafter “Mishchenko”).
Regarding independent claims 1, 8 and 16, Setlur disclose a computing system, comprising:
one or more processors (col 2 lines 23-25); and
one or more non-transitory computer-readable media storing instructions that are executable to cause the one or more processors to perform operations, the operations comprising (col 5 lines 62-65):
obtaining, via a conversational campaign assistant interface, by a custom language model, natural language input (col 3 line 59-col 4 line 11);
generating, by the custom language model, an output comprising a predicted user intent (col 3 lines 28-35; col 7 line 44-col 8 line 2);
determining one or more actions associated with a content creation structured interface to perform by:
parsing the output generated by the custom language mode (col 3 line 59-col 4 line 11);
determining an action associated with the output wherein the action comprises performing operations within the content creation structured interface comprising at least one of: (i) populating an input field or providing a recommendation (col 7 line 44-col 8 line 2; col 25 lines 36-55);
generating an action data structure comprising executable instructions that cause a processor to perform an operation associated with completing the action (col 7 line 44-col 8 line 2; col 25 lines 36-55);
determining a natural language response by:
parsing the output generated by the custom language model (col 3 line 59-col 4 line 11);
generating a response data structure comprising a natural language response to the obtained natural language input (col 1 line 61-col2 line 7; col 3 line 59-col 4 line 11; col 10 lines 13-25);
Setlur does not expressly disclose transmitting, to an action component, the action data structure comprising executable instructions that cause the action component to automatically perform operations associated with completing the action;
transmitting to the conversation campaign assistant interface, the response data structure comprising the natural language response to be provided for display to a user via the conversational campaign assistant interface;
obtaining, subsequent to transmitting the action data structure and response data structure, user input indicative of a validation of the action data structure or the response data structure; and
updating the custom language model based on the user input.
Mishchenko teach transmitting, to an action component, the action data structure comprising executable instructions that cause the action component to automatically perform operations associated with completing the action (col. 5 lines 10-39; col 7 line 8-25; col. 19 line 14-36);
transmitting to the conversation campaign assistant interface, the response data structure comprising the natural language response to be provided for display to a user via the conversational campaign assistant interface (col. 5 lines 10-39; col 7 line 8-25; col. 19 line 14-36);
obtaining, subsequent to transmitting the action data structure and response data structure, user input indicative of a validation of the action data structure or the response data structure (col. 5 lines 10-39; col 7 line 8-25; col. 19 line 14-36); and
updating the custom language model based on the user input (col 8 lines 43-66; col 17 lines 42-66).
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one or ordinary skill in the art to combine Mishchenko with Setlur for the benefit of improving the trainability, scalability, and generation of natural language models with respect to external data and applications.
Regarding dependent claims 2 and 10, Setlur disclose the computing system of claims 1 and 8 respectively, wherein the action data structure comprises data to be populated within one or more fields of a content creation structured interface (col 7 line 44-col 8 line 2; col 25 lines 36-55).
Regarding dependent claims 3 and 11, Setlur in view of Mishchenko disclose the computing system of claims 1 and 8 respectively, wherein the natural language input comprises a uniform resource locator (URL), and wherein the action component comprises a generative model that generates a summary of information parsed from a page associated with the URL (col 7 line 50 – col 8 line 4 and col 8 lines 43-66).
Regarding dependent claims 7 and 15, Setlur in view of Mishchenko disclose the computing system of claims 1 and 8 respectively, wherein the action component comprises a generative model, wherein the generative model obtains the action data structure as an input prompt and generates an output comprising a creative asset (col 9 lie 65-col 10 line 19).
Regarding dependent claim 9, Setlur in view of Mishchenko disclose the computer-implemented method of claim 8, comprising:
updating the custom language model based on the user input (col 8 lines 43-66; col 17 lines 42-66).
Regarding dependent claim 17, Setlur in view of Mishchenko disclose the one or more non-transitory computer readable media of claim 16, the operations comprising:
obtaining, subsequent to transmitting the action data structure and response data structure, user input indicative of a validation of the action data structure or the response data structure (col. 5 lines 10-39; col 7 line 8-25; col. 19 line 14-36); and
updating the custom language model based on the user input (col 8 lines 43-66; col 17 lines 42-66).
Regarding dependent claim 18, Setlur in view of Mishchenko disclose the one or more non-transitory computer readable media of claim 16, wherein the action component comprises a generative model, wherein the generative model obtains the action data structure as an input prompt and generates an output comprising a creative asset (col 9 line 65-col 10 line 19).
Regarding dependent claim 19, Setlur disclose the one or more non-transitory computer readable media of claim 18, wherein the generative model comprises a machine learning model (col 1 lines 30-40).
Claims 4-6, 12-14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Setlur in view of Mishchenko, further in view of Deng et al. (Pat. No.: US 11,868,884 B2; Filed: Jun. 17, 2020) (hereinafter “Deng”).
Regarding dependent claims 4 and 12, Setlur in view of Mishchenko does not expressly disclose the computing system of claims 1 and 8 respectively, wherein the action component comprises a content campaign performance model.
Deng teach wherein the action component comprises a content campaign performance model (col 13 line 24-39).
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one or ordinary skill in the art to combine Deng with Setlur for the benefit of improving privacy issues concerning massive data collection and/or serving machine learning models.
Regarding dependent claims 5 and 13, Setlur in view of Mishchenko does not expressly disclose the computing system of claims 1 and 8 respectively, wherein the action component comprises a content campaign analysis model.
Deng teach wherein the action component comprises a content campaign analysis model (col 13 line 24-39).
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one or ordinary skill in the art to combine Deng with Setlur for the benefit of improving privacy issues concerning massive data collection and/or serving machine learning models.
Regarding dependent claims 6 and 14, Setlur in view of Mishchenko does not expressly disclose the computing system of claims 1 and 8 respectively, wherein the action component comprises a bidding strategy model.
Deng teach wherein the action component comprises a bidding strategy model (col 13 line 24-39).
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one or ordinary skill in the art to combine Deng with Setlur for the benefit of improving privacy issues concerning massive data collection and/or serving machine learning models.
Regarding dependent claim 20, Setlur in view of Mishchenko does not expressly disclose the one or more non-transitory computer readable media of claim 19, wherein the generative model is trained using a knowledge distillation technique.
Deng teach wherein the generative model is trained using a knowledge distillation technique (col 13 line 24-39).
Therefore, before the effective filing date of the claimed invention, it would have been obvious to one or ordinary skill in the art to combine Deng with Setlur for the benefit of improving privacy issues concerning massive data collection and/or serving machine learning models.
NOTE
It is noted that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAMES J DEBROW whose telephone number is (571)272-5768. The examiner can normally be reached on 09:00 - 06:00.
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/James J Debrow/
Primary Patent Examiner
Art Unit 2174
571-272-5768