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 .
Claims 1-6 have been examined.
Priority
This is Application 18899703 filed 09/27/2024 Claims Priority from Provisional Application 63541359 , filed 09/29/2023. Therefore, the effective filling date for the subject matter defined in the pending claims of this application is 09/29/2023.
Drawings
The subject matter of this application admits of illustration by a drawing to facilitate understanding of the invention. Applicant is required to furnish a drawing under 37 CFR 1.81(c). No new matter may be introduced in the required drawing. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d).
Specification
The specification filed on 09/27/2024 is acceptable for examination proceedings.
Internet Communications
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http://www.uspto.gov/sites/defauit/files/documents/sb0439.pdf) in the instant patent application to authorize the examiner to communicate with the applicant via email. The authorization will allow the examiner to better practice compact prosecution. The written authorization can be submitted via one of the following methods only. (1) Central Fax which can be found in the Conclusion section of this Office action; (2) regular postal mail; (3) EFS WEB; or (4) the service window on the Alexandria campus. EFS web is the recommended way to submit the form since this allows the form to be entered into the file wrapper within the same day (system dependent). Written authorization submitted via other methods, such as direct fax to the examiner or email, will not be accepted. See MPEP § 502.03.
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 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 negatived by the manner in which the invention was made.
Claims 1-6 are rejected under 35 U.S.C. 103 as being unpatentable over Muriqi (US Pub. No.: US 2024/0046318 A1, hereinafter refer as to Muriqi in view of Xiao et al. (US Pub. No.: US 2025/0078812 A1, hereinafter refer as to Xiao).
As per claim 1, Muriqi discloses a personal security method for establishing and maintaining the pseudonymity of an author containing at least two modules (para. 0223 discloses due to the anonymity or pseudonymity of blockchain, when legal disputes arise from the creation and use of digital assets, it is often not enough to match these assets with the real-life owner or creator of the token, which makes the verification process of assets difficult. (anonymity or pseudonymity are optional, and therefore this may not be a significant problem), for example), comprising executing, in a module, a back-and-forth user interaction with a Large Language Module (LLM) using one or more user prompts (para. 0069 discloses a large language model (LLM), such as a generative pre-trained transformer system, e.g., ChatGPT, to understand the content of a work, its tone, bias, viewpoint, and other factors. The artificial intelligence (AI) system can operate on semantic components of media, or in a multimodal fashion, for example), to generate a dialogue in any format, and collecting said dialogue with a text collecting tool and removing all said user prompts to generate an LLM generated text (para. 0420 discloses characters in paintings or other forms of visual display may begin movement or engage in dialogue when receiving fixations from a subject user. Alternatively, viewing behavior may be used to determine what aspects of programs should be recorded, or to stop, mute or pause playback of a content source such as DVD and the like, for example).
Muriqi failed to expressly discloses to followed by populating a separate objective editing module with said LLM generated text, to create an editing worksheet for completion by a user, wherein said editing worksheet contains one or more input possibilities only for fact-insertion or fact-editing by said user; with a final step of instructing said LLM to generate a text solely from said editing worksheet module, to render a document for which pseudonymity has been established and maintained due to the limited interaction of the user and the constraints of the recited modules.
Xiao discloses followed by populating a separate objective editing module with said LLM generated text, to create an editing worksheet for completion by a user (fig 6A, client device 610, for example), wherein said editing worksheet contains one or more input possibilities only for fact-insertion or fact-editing by said user; with a final step of instructing said LLM to generate a text solely from said editing worksheet module (para. 0068 discloses client device 110 to generate update 130A for the global LLM 162A based on: (i) a corresponding frequency of the LLM response failing to follow an explicit instruction included in the input 110A, for example), to render a document for which pseudonymity has been established and maintained due to the limited interaction of the user and the constraints of the recited modules (figs 6A and 6B depicted to populate the textual reply and/or editing element 684 with the predicted textual segment 654 of “I tested positive for covet and will miss the meeting tomorrow” for editing by the user, some user input can be directed to the edit selectable graphical element 662, thereby populating the textual reply and/or editing element 684, for example).
Muriqi as modified and Xiao are analogous art because they both are directed to a framework for decentralized learning of large global machine learning (ML) model(s), and one of ordinary skill in the art would have had a reasonable expectation of success to modify the teachings of Muriqi with the specified features of Xiao because they are from the same field of endeavor.
In view of the above, having the teaching Muriqi and the well-established teaching of Xiao, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Muriqi with the teachings of Xiao order for updating ML model(s) due to various privacy consideration [Xiao: para. 0001.
As per claim2, Muriqi discloses a personal security method for establishing and maintaining the pseudonymity of an author containing at least three modules (para. 0223 discloses due to the anonymity or pseudonymity of blockchain, when legal disputes arise from the creation and use of digital assets, it is often not enough to match these assets with the real-life owner or creator of the token, which makes the verification process of assets difficult. (anonymity or pseudonymity are optional, and therefore this may not be a significant problem), for example), comprising executing, in a first module, a series of flag codes regarding input of a user; followed by, in a second module, a back-and-forth user interaction with a Large Language Module (LLM) using one or more user prompts (para. 0069 discloses a large language model (LLM), such as a generative pre-trained transformer system, e.g., ChatGPT, to understand the content of a work, its tone, bias, viewpoint, and other factors. The artificial intelligence (AI) system can operate on semantic components of media, or in a multimodal fashion, for example), to generate a dialogue in any format, and collecting said dialogue with a text collecting tool and removing all said user prompts to generate an LLM generated text (para. 0420 discloses characters in paintings or other forms of visual display may begin movement or engage in dialogue when receiving fixations from a subject user. Alternatively, viewing behavior may be used to determine what aspects of programs should be recorded, or to stop, mute or pause playback of a content source such as DVD and the like, for example).
Muriqi failed to expressly discloses followed by populating a third objective editing module with said LLM generated text, to create an editing worksheet for completion by a user, wherein said editing worksheet contains one or more input possibilities only for fact-insertion or fact-editing by said user; with a final step of instructing said LLM to generate a text solely from said editing worksheet module, to render a document for which pseudonymity has been established and maintained due to the limited interaction of the user and the constraints of the recited modules.
Xiao discloses followed by populating a third objective editing module with said LLM generated text, to create an editing worksheet for completion by a user (fig 6A, client device 610, for example), wherein said editing worksheet contains one or more input possibilities only for fact-insertion or fact-editing by said user; with a final step of instructing said LLM to generate a text solely from said editing worksheet module (para. 0068 discloses client device 110 to generate update 130A for the global LLM 162A based on: (i) a corresponding frequency of the LLM response failing to follow an explicit instruction included in the input 110A, for example), to render a document for which pseudonymity has been established and maintained due to the limited interaction of the user and the constraints of the recited modules (figs 6A and 6B depicted to populate the textual reply and/or editing element 684 with the predicted textual segment 654 of “I tested positive for covet and will miss the meeting tomorrow” for editing by the user, some user input can be directed to the edit selectable graphical element 662, thereby populating the textual reply and/or editing element 684, for example).
Muriqi as modified and Xiao are analogous art because they both are directed to a framework for decentralized learning of large global machine learning (ML) model(s), and one of ordinary skill in the art would have had a reasonable expectation of success to modify the teachings of Muriqi with the specified features of Xiao because they are from the same field of endeavor.
In view of the above, having the teaching Muriqi and the well-established teaching of Xiao, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Muriqi with the teachings of Xiao order for updating ML model(s) due to various privacy consideration [Xiao: para. 0001.
As per claim 3, Muriqi discloses a personal security system and writer's tool comprising three modules (para. 0223 discloses due to the anonymity or pseudonymity of blockchain, when legal disputes arise from the creation and use of digital assets, it is often not enough to match these assets with the real-life owner or creator of the token, which makes the verification process of assets difficult. (anonymity or pseudonymity are optional, and therefore this may not be a significant problem), for example), for user interface with a Large Language Module (LLM), in executable form: a chatbot prompt stylometrics alert module; a text collecting tool module; and 3) an objective editing module (para. 0069 discloses a large language model (LLM), such as a generative pre-trained transformer system, e.g., ChatGPT, to understand the content of a work, its tone, bias, viewpoint, and other factors. The artificial intelligence (AI) system can operate on semantic components of media, or in a multimodal fashion, for example).
Muriqi failed to expressly discloses three modules are deployed in sequence to create an LLM-generated document in which pseudonymity of a user is established and maintained.
Xiao failed to expressly discloses three modules are deployed in sequence to create an LLM-generated document (para. 0068 discloses client device 110 to generate update 130A for the global LLM 162A based on: (i) a corresponding frequency of the LLM response failing to follow an explicit instruction included in the input 110A, for example), in which pseudonymity of a user is established and maintained (figs 6A and 6B depicted to populate the textual reply and/or editing element 684 with the predicted textual segment 654 of “I tested positive for covet and will miss the meeting tomorrow” for editing by the user, some user input can be directed to the edit selectable graphical element 662, thereby populating the textual reply and/or editing element 684, for example).
Muriqi as modified and Xiao are analogous art because they both are directed to a framework for decentralized learning of large global machine learning (ML) model(s), and one of ordinary skill in the art would have had a reasonable expectation of success to modify the teachings of Muriqi with the specified features of Xiao because they are from the same field of endeavor.
In view of the above, having the teaching Muriqi and the well-established teaching of Xiao, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Muriqi with the teachings of Xiao order for updating ML model(s) due to various privacy consideration [Xiao: para. 0001.
Regarding claim 4, the combination of Muriqi as modified by Xiao discloses wherein said first module contains a prescribed set of flag codes or truncations thereof wherein h, i, j, k, 1, m, n, o, p,... correspond to one or more formatives including simple, shorter, clearer, tone, emphasis, sophistication, longer, elaborate, impressive.... and is enabled automatically to screen input from a user for the presence (para. 0090 discloses a user input device may be provided, configured to receive a subjective assessment or comment, wherein the subjective assessment or comment is linked to the social network record, and the at least one automated processor is further configured to credit or debit the account associated with the user for the receipt of the subjective assessment or comment, for example).
Muriqi failed to expressly discloses prior to any execution of said input by said user, of one or more formatives and to alert the presence of one or more said formatives , via flag code, by means of any of an alarm event selected from the group consisting of a color, a sound, a marker, a pop-up text box, a symbol, a light, and a vibration,
Xiao discloses prior to any execution of said input by said user, of one or more formatives and to alert the presence of one or more said formatives (para. 0124 discloses a user's identity may be treated so that no personal identifiable information can be determined for the user, or a user's geographic location may be generalized where geographic location information is obtained (such as to a city, ZIP code, or state level), so that a particular geographic, for example), via flag code, by means of any of an alarm event selected from the group consisting of a color, a sound, a marker, a pop-up text box, a symbol, a light, and a vibration (para. 0039 discloses the on-device ASR model may be end-to-end speech recognition model. In these implementations, the on-device ML engine 122 generates one or more predicted textual segments, as the one or more predicted outputs 122B, directly using the on-device ASR model (e.g., the one or more predicted outputs 122B may correspond to the one or more predicted textual segments).
Muriqi as modified and Xiao are analogous art because they both are directed to a framework for decentralized learning of large global machine learning (ML) model(s), and one of ordinary skill in the art would have had a reasonable expectation of success to modify the teachings of Muriqi with the specified features of Xiao because they are from the same field of endeavor.
In view of the above, having the teaching Muriqi and the well-established teaching of Xiao, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Muriqi with the teachings of Xiao order for updating ML model(s) due to various privacy consideration [Xiao: para. 0001.
Regarding claim 5, the combination of Muriqi as modified by Xiao discloses wherein said objective editing module further generates said editing worksheet in electronic, paper or any other interactive form with editing prompts therein (fill-in-the-blank content or check box content) and wherein said editing module and said editing worksheet prohibit any editing of said editing worksheet except for editing said editing prompts by said user (figs 6A and 6B of Xiao depicted the textual reply and/or editing element 684 can be automatically populated with the predicted textual segment 654 of “I tested positive for covet and will miss the meeting tomorrow” for editing by the user, and the user input can be directed to the textual reply and/or editing element 684 to, for example, modify “covet” to “covid” as also indicated by 656A (e.g., cursor identifiers). In additional or alternative implementations, the automated assistant can visually render a send selectable graphical element 661, an edit selectable graphical element 662, and/or a cancel selectable graphical element 663. In some versions of those implementations, to populate the textual reply and/or editing element 684 with the predicted textual segment 654 of “I tested positive for covet and will miss the meeting tomorrow” for editing by the user, some user input can be directed to the edit selectable graphical element 662, thereby populating the textual reply and/or editing element 684, for example).
Regarding claim 6, the combination of Muriqi as modified by Xiao discloses wherein said LLM generated text from said second module is populated into said third module, with no additional text population to said third module (figs 6A and 6B depicted to populate the textual reply and/or editing element 684 with the predicted textual segment 654 of “I tested positive for covet and will miss the meeting tomorrow” for editing by the user, some user input can be directed to the edit selectable graphical element 662, thereby populating the textual reply and/or editing element 684, for example).
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Austin et al. (US Pub. No.: US 2024/0420012 A1) provide obtaining one or more information items or documents, checking the one or more information items or documents for determined sensitivity and determining role-based access for the one or more information items or documents, based on the checking and the determining, performing a preliminary analysis of the one or more information items or documents, wherein the preliminary analysis involves one or more pre-processing procedures, one or more chunking procedures, one or more embedding procedures, one or more customization procedures for particular use cases, or a combination thereof, and storing results of the preliminary analysis in a vector knowledge base for training one or more generative artificial intelligence (AI) large language models (LLMs).
Maheshwari (US Pub. No.: US 2025/0373575 A1) provide security, privacy, and data use restrictions in group communication with multiple large language model (LLM) chatbots or agents are provided. In-context user consent is obtained for operations performed by LLM agents on behalf of the user as and when needed. A first message directed to a first LLM agent is received via a user interface (UI). Based on a determination that the first message is to invoke a second LLM agent, a consent request for consent of a user to invoke the second LLM agent is provided via the UI. Upon receiving the consent of the user to invoke the second LLM agent, the second LLM agent is invoked within the context of the UI. In some examples, a command to enter private mode may be received to limit the communication in the private mode only selected LLM agents.
Mukherjee et al. (US Pub. No.: US 2024/0354436 A1) provide computer-implemented systems and methods are disclosed, including systems and methods utilizing language models for searching a large corpus of data. A computer-implemented method may include: receiving a first user input comprising a natural language query; vectorizing the first user input into a query vector; executing, using the query vector, a similarity search in a document search model to identify one or more similar document portions, where the document search model includes a plurality of vectors corresponding to a plurality of portions of a set of documents; generating a first prompt for a large language model (“LLM”), the first prompt including at least the first user input, and the one or more similar document portions; transmitting the first prompt to the LLM; receiving a first output from the LLM in response to the first prompt; and providing, via a user interface, the first output from the LLM.
Conclusion
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A.G.
December 7, 2025
/ABIY GETACHEW/ Primary Examiner, Art Unit 2434