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 .
Priority
This U.S. non-provisional application claims the benefit of priority under 35 U.S.C. § 119 to Korean Patent Application No. 10-2023-0110857 filed on August 23, 2023, and Korean Patent Application No. 10-2024-0004165 filed on January 10, 2024, in the Korean Intellectual Property Office.
Examiner’s Note:
The claims of the copending applications 18/813479, 19/375528, 18813452, 18813375, and current application 18813625 are considered related but currently nonobvious. If subsequent amendments render the claims obvious, an obviousness-type double patenting rejection will follow.
Response to Amendment
Claims 1, 12 and 16 are amended. Claims 11 and 20 are cancelled. Claims 1-10 and 12-19 are presented for examination.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-10 and 12-19 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Objections
Claim 14 is objected to because of the following informalities: Claim 14 is depended on cancelled claim 11. Appropriate correction is required.
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.
The factual inquiries 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.
And
KSR, 550 U.S. at 418, 82 USPQ2d at 1396. Exemplary rationales that may support a conclusion of obviousness include:
(A) Combining prior art elements according to known methods to yield predictable results;
(B) Simple substitution of one known element for another to obtain predictable results;
(C) Use of known technique to improve similar devices (methods, or products) in the same way;
(D) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results;
(E) "Obvious to try" – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success;
(F) Known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations are predictable to one of ordinary skill in the art;
(G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.
See MPEP § 2143 for a discussion of the rationales listed above along with examples illustrating how the cited rationales may be used to support a finding of obviousness. See also MPEP § 2144 - § 2144.09 for additional guidance regarding support for obviousness determination.
Claims 1-2, 4, 7-8, 10-17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Socher (US 20240020538 ) and further in view of Adada ( US 20240256618) and further in view of Rayit ( US 20240256623)
Regarding claim 1, Socher teaches a dynamic content creation method of a computer device having at least one processor, the dynamic content creation (response is modified based on user constraint, Para 0136-0137; Figs 10a-10e – based on user input within the chat the content is modified ( dynamic content) ) method comprising: generate ( verifying in the sense that results are atleast produced) , by the at least one processor, LLM results created based on a large language model (LLM) for a prompt of a user ( obtain one or more search results, S706, Para 0108; S906, Para 0130-0131) ; creating, by the at least one processor, an instance for content of an information provider ( instance of content (product description and summary) , Para 0136-0137) using the LLM results and a pre-registered asset of the information provider ( output containing the search result with AI summary with reference to data sources like Looria or PCMag is displayed, Fig 7, Para 0045; Prior to performing the search, the search server may identify potential data sources that are relevant to the modified query. In some embodiments, particular data sources may be identified due to the provided user constraints determined in step 906, Para 0131; In step 914, the search sever modifies the response based on user constraints, Para 0134 ); and providing, by the at least one processor, the created instance such that the created instance is displayed in relation to the LLM results ( results is displayed, Fig 10a-10e)
providing a first answer as LLM results through a search service and a second mode of providing the first answer as LLM results through conversation between the LLM-based artificial intelligence module and the user ( user can use the Youchat window to chat and get the results, Fig 10b user can chat based on the results fetched; additionally system provides suggested follow up questions about alternative parameters, Para 0024) : and providing a plurality of recommendation prompts in conjunction with the created instance, wherein when the user selects one of the recommendation prompts, the second mode is provided to the user using the selected recommendation prompt as the prompt of the user ( additional follow up with alternative parameter, Para 0024, 0080, Fig 10a-e)
Socher does not explicitly teach verifying, by the at least one processor, LLM results created based on a large language model (LLM) for a prompt of a user
However, Adada teaches verifying, by the at least one processor, LLM results created based on a large language model (LLM) for a prompt of a user ( The model can start looking at its own output as it is being generated to Initiate additional background processes: e.g., RAI (responsible AI classifiers), fact checking processors, etc. This can happen token by token, at sentence boundaries, etc. this feature applies to multi-modal generation (text, images, video, speech, etc.), Para 0081)
It would have been obvious having a concept of Socher to further modify with the teachings of Adada before effective filing date to generate more accurate answer hence, improving user experience
Socher does not explicitly teach verifying, by the at least one processor, LLM results created based on a large language model (LLM) for a prompt of a user and providing a mode switching function configured to switch between a first mode of providing a first answer as machine learning results through a search service and a second mode of providing the first answer as LLM results through conversation between the artificial intelligence module and the user: and providing a plurality of recommendation prompts in conjunction with the created instance, wherein the mode switching function is included in each of the recommendation prompts in a form of a link for executing the mode switching function
However, Rayit teaches providing a mode switching function configured to switch between a first mode of providing a first answer as machine learning results through a search service and a second mode of providing the first answer as LLM results through conversation between the artificial intelligence module and the user ( Fig 3 and Fig 5; when altering from SERP mode to chat mode, the query set forth by the user and the top answer returned by the search engine can be carried forward to chat mode, and a GLM response can be provided beneath such information. This provides a seamless flow in chat mode., Para 0014) : and providing a plurality of recommendation prompts in conjunction with the created instance, wherein the mode switching function is included in each of the recommendation prompts in a form of a link for executing the mode switching function ( transition to and from search engine and conversation mode is facilitated via links in the header and body of the page being viewed. Elements from a traditional search results page such as advertisements and instant answers can be brought into the conversational search results page as well. In this manner, users are allowed to seamlessly switch between a traditional social search results page and a conversational search results page., Para 0013; the GLM 112 can generate query suggestions that are well-suited for submission to the search engine 110, such that the GLM 112 can prompt the user to switch to search engine mode. For instance, based upon the conversational input “What SAT score does the University require”, the GLM 112 can generate several queries that are configured to be received by the search engine 110, such as “locations near me where the SAT exam can be taken”, “dates of SAT exam”, amongst others. The GLM 112 can assign a hyperlink to text in the conversational input and/or text in conversational output, where upon hovering over the hyperlink one or more query suggestions can be presented, Para 0066)
It would have been obvious to POSITA knowing the teachings of Socher and Adada to further include the concept of Rayit before effective filing date to improve the user experience by giving user an option to select the type of response they desire ( Para 0003,0008, 0009, Rayit)
Regarding claim 2, Socher as above in claim 1, teaches , wherein the creating of the instance for the content comprises combining the pre-registered asset ( shopping sites ( pre-registered assets), Para 0137) according to a keyword extracted from the LLM results ( key word within the query, Para 0130) , a material ( for e.g. headphones, Para 0130) , a previous conversation between an artificial intelligence module based on the LLM and the user (for e.g. based on the conversion or user profile, Fig 10d-e; Para 0093) , and a prompt of the information provider(The search server may then transmit a search input based on potential search objects to the identified potential data sources, Para 0131) and modifying at least one of an expression, a format, and a tone and manner of a message in the combined asset (summary based on tone, format etc., Para 0128-0138)
Regarding claim 4, Socher as above in claim 1, teaches wherein the asset of the information provider includes at least one of a uniform resource locator (URL) ( URL, Para 0080) related to content that the information provider desires to provide , a title of the content, an identifier of the content, a category of the content, multimedia related to the content, contents of the content, and contents of an article related to the content ( figs 10a-b)
Regarding claim 7, Socher as above in claim 1, teaches wherein the creating of the instance for the content comprises using the prompt of the user ( user input and user can be associated with user profile, Fig 7-9)
Regarding claim 8, Socher as above in claim 1, teaches , wherein the creating of the instance for the content comprises using information on the user ( user profile Para 0113) , and information on the user includes at least one of the user's demographics, things of interest, and purchase information ( user context 404 may include any combination of user profile information (e.g., user ID, user gender, user age, user location, zip code, device information, mobile application usage information, and/or the like), user configured preferences or dislikes of one or more data sources (e.g., as shown in co-pending and commonly-owned U.S. nonprovisional application Ser. No. 17/981,102), and user past activities approving or disapproving a search result from a specific data source. For instance, if a user previously disapproved of certain websites, then the generative AI system will prioritize other websites to collect information and provide a conversational response. Conversely, if a user previously approved of certain websites, the generative AI system may instead look to find results from the approved websites before searching other webpages to provide a conversational response., Para 0013)
Regarding claim 10, Socher as above in claim 1, teaches wherein the information provider is selected through an auction between information providers related to at least one of the prompt of the user, the LLM results, and a recommendation query created by the large language model among the plurality of information providers ( Figs 10a-e; based on user’s past selections and modified prompts, Para 0131, 0013)
Regarding claim 12, Adada as above in claim 11, teach wherein, when content of a specific brand is exposed through the page provided for the search service, the mode switching function is provided in conjunction with the content of the specific brand ( overlaid on the web page 402 is a semantic SERP 406 constructed by the GLM 112, Para 0052-0055)
Regarding claim 13, Adada as above in claim 12, teach wherein the mode switching function is included in at least one recommendation prompt created in association with the specific brand in a form of a link for executing the mode switching function, and the at least one recommendation prompt is provided through the page in conjunction with the content of the specific brand ( Para 0056, suggestion to search additional stuff; fig 5 – for a particular entity )
Regarding claim 14, Socher modified by Adada and Riyat as above in claim 11, wherein the page provided for the search service includes a search result page provided in response to a search term of the user ( fig 10 a-b items), the mode switching function is included in at least one recommendation prompt created in association with at least one search result among search results included in the search result page in a form of a link for executing the mode switching function , and the at least one recommendation prompt is provided through the search result page in conjunction with the at least one result ( additional follow up with alternative parameter, Para 0024, 0080, Socher; supplemental content and prompt, Fig 4-6, Adada, Fig 3, 5, Para 0039, Riyat)
Regarding claim 15, Socher teaches a non-transitory computer-readable recording media storing a computer program for executing the dynamic content creation method of claim 1 on the computer device ( computer readable media, Para 0052, 0054)
Regarding claim 16, arguments analogous to claim 1, are applicable.
Regarding claim 17, arguments analogous to claim 2, are applicable.
Regarding claim 19, arguments analogous to claim 4, are applicable.
Regarding claim 20, arguments analogous to claim 11, are applicable.
Claims 5-6 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Socher ( US 20240020538 ) and further in view of Adada ( US 20240256618) and further in view of Rayit ( US 20240256623) and further in view of Saxena ( US 20240330579)
Regarding claim 5, Socher modified by Adada as above in claim 1, teach wherein the creating of the instance for the content comprises using a prompt of the information provider (The search server may then transmit a search input based on potential search objects to the identified potential data sources, Para 0131)
Socher modified by Adada does not teach prompt is pre-registered
However, Saxena teaches prompt is pre-registered ( The prompt template selector 220 obtains a prompt template to use to generate text for a particular section of a particular webpage,.. using a first template for a webpage associated with a first type of person or company and a second template for a webpage associated with a second type of person or company ( pre-registered), Para 0031)
It would have been obvious having the concept of Socher and Adada to further include the concept of Saxena before effective filing date since it can be difficult to generate prompts that will cause the text produced by a large language model to be appropriate for the context in which the text will appear. It is especially difficult to generate these prompts programmatically and to solve this problem its better to use the prompt template for the particular websites ( Para 0017-0018, Saxena)
Regarding claim 6, Socher as above in claim 5, teaches wherein the pre-registered prompt includes at least one of a phrase or a keyword entered to emphasize a relation to content that the information provider desires to provide ( search input – phrase, Para 0131) , and a tone or a format of an information message to be provided through the instance for the content ( AI summary including the tone etc., based on user profile, Para 0128-0138)
Regarding claim 9, Socher as above in claim 8, teach , wherein the creating of the instance for the content further comprises using a characteristic and a weight of a target included in a pre-registered prompt of the information provider ( the rank module 434 may rank a search result from those specific sources as higher than from others. Additionally, other context 406 may indicate that other users value specific sources related to identified terms in user query 402; thus, the rank module 434 may incorporate this other context when ranking search results., Para 0077- where the rank is the terms and characteristic is the liking or disliking the website from the past etc. ) and the weight includes at least one of a character-specific weight of the target and a contents-specific weight of the target ( identified terms/items, Para 0077)
Socher modified by Adada does not specifically teach creating content using a characteristic and a weight of a target included in a pre-registered prompt of the information provider
However, Saxena teaches creating content using a characteristic and a weight of a target included in a pre-registered prompt of the information provider ( tone parameter value with the confidence includes in the template prompt, Para 0039, 0028)
It would have been obvious having the concept of Socher and Adada to further include the concept of Saxena before effective filing date since it can be difficult to generate prompts that will cause the text produced by a large language model to be appropriate for the context in which the text will appear. It is especially difficult to generate these prompts programmatically and to solve this problem its better to use the prompt template for the particular websites (Para 0017-0018, Saxena)
Claims 3 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Socher (US 20240020538 ) and further in view of Adada ( US 20240256618) and further in view of Rayit ( US 20240256623) and further in view of Jain ( US 20240256582)
Regarding claim 3, Socher as above in claim 1, teach wherein the creating of the instance for the content comprises extracting a plurality of prompts from the LLM results ( updated search summary based on additional input ( prompts ) and searches, Para 0142) and the asset of the information provider and generating a summary ( generate an AI summary based on atleast one result , Fig 10a-b, Para 0035, 0040)
However, Jain teaches extracting a plurality of prompts from the LLM results and the asset of the information provider ( result 1 and result 2, Fig 3a, Para 0069) and inputting the extracted plurality of prompts into the LLM( The summary of search results 323 includes references to Result #1 that refers to the first search result 324 and Result #2 that refers to the second search result 325The summary of search results 323 may have been generated using one or more generative AI models in which a prompt to the one or more generative AI models includes portions of the first search result 324 and the second search result 325, Para 0069)
It would have been obvious having the teachings of Socher and Adada to further include the concept of Jain before effective filing date since the way to generate a summary involving different search results would be to input those search results from different entities to improve the quality of the search results (Para 0069-0070, Jain)
Regarding claim 18, arguments analogous to claim 3, are applicable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20240256764 A1
US 20160328751
US 10380882 B1
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Richa Sonifrank whose telephone number is (571)272-5357. The examiner can normally be reached M-T 7AM - 5:30PM.
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, Phan Hai can be reached at (571)272-6338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/Richa Sonifrank/Primary Examiner, Art Unit 2654
Prosecution Insights