DETAILED ACTION
This office action is in response to the application filed on 08/30/2024. Claims 1-20 are pending and are examined.
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 application is a continuation-in-part of U.S. Patent Application No. 18/661,532 filed on May 10, 2024, which is a continuation-in-part of U.S. Patent Application No. 18/661,519 filed on May 10, 2024, which is a continuation-in-part of U.S. Patent Application No. 18/633,293 filed on April 11, 2024. The content of the foregoing applications is incorporated herein by reference in their entirety.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 09/27/2024 and 01/10/2025 were filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Note: Examiner initiated a telephone call and left a message for Ravi Vishal on 05/19/2026 to discuss an examiner’s amendment to the claims in order to expedite the execution of this application .
Claim Objections
Claim 15 is objected to because of the following informalities:
Claim 15 recites the limitation, “and transmiting the generated model output to a server system enabling access to the generated model output by the user device”.
should be “and transmitting the generated model output to a server system enabling access to the generated model output by the user device”.
Appropriate correction is required.
Claims 16-20 are objected based on their dependency from claim 15.
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 2, 9 and 16 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 pre-AIA the applicant regards as the invention.
Regarding claim 2, the limitations "obtain training input data comprising at least two of (1) historical activity corresponding to previously processed output generation requests, (2) corresponding historical system state data, (3) corresponding user profile data, and (4) corresponding cost data” and “obtain training output data comprising (1) historical output data corresponding to model identifiers associated with the previously processed output generation requests and (2) corresponding routing instructions", recited in the claim is unclear which renders the claim indefinite.
Examiner is unable to determine whether the terms “(2) corresponding historical system state data, (3) corresponding user profile data, and (4) corresponding cost data”, represent historical activity data and also the term “(2) corresponding routing instructions”, represents historical output data.
Claims 9 and 16 include similar limitations as claim 2, therefor they are rejected under 35 U.S.C. 112(b) for the same reasons.
Allowable Subject Matter
Claims 1, 3-8 and 10-14 are allowed.
Claims 2, 9 and 16 would be allowable, should applicant overcome the rejection under 35 U.S.C. 112(b), set forth in this office action.
Claims 15-20 would be allowable, should applicant overcome the claim objections, set forth in this office action.
The following is an examiner’s statement of reasons for allowance and also for identifying allowable subject matter.
The closest prior arts made of records are, Gallegari et al. (U.S. Pub. No. 2024/0,362,422 A1, referred to as Gallegari), Gasser et al. (U.S Pub No. 2025/0,265,347 A1, referred to as Gasser) and Hariri et al. (U.S Pub No. 2024/0,330,580 A1, referred to as Hariri).
Gallegari discloses a computing system for revising large language model (LLM) input prompts. The computing system includes at least one processor configured to receive via a prompt interface a prompt from a user including an instruction for a trained LLM to generate an output and generate a first response to the prompt, to assess the first response according to assessment criteria to generate an assessment report for the first response and generate a revised prompt in response to second input including the first prompt, the first response, the assessment report, and a prompt revision instruction for the LLM to revise the prompt in view of the assessment report and in response to final input including the revised prompt, generate a final response to the revised prompt and output the final response.
Gasser discloses a for executing domain-specific controls on large language model-generated data. The system may receive a textual communication and provide the textual communication to a first model to generate an output. Based on the output and the textual communication, the system may generate a communication profile, determine that the communication profile satisfies first or second criteria. Based on determining that the communication profile satisfies the first criteria, the system may determine rulesets corresponding to domains and provide the communication to a second model to generate a second output according to these rulesets. Based on determining that the communication profile satisfies the second criteria, the system may cause execution of a termination protocol in lieu of generating the second output.
Hariri discloses systems and methods for generating personalized and structured content using a collaborative generator provide a user interface to a user computing system and receive a prompt from the user computing system via the user interface. The systems and methods provide the prompt to a generative model, with the generative model being a machine-learned model trained to process language input prompts to generate a language output, receive a generative output generated by the generative model in response to the prompt, generate a modified output by modifying the generative output based at least in part on historical user data for a user associated with the prompt, and then provide the modified output via the user interface.
However, regarding claims 1 and 8, the prior art of Gallegari, Gasser and Hariri when taken in the context of the claim as a whole do not disclose nor suggest, “dynamically monitor one or more system resource measurements to determine a current system state, wherein the current system state indicates real-time computational resource usage of a computing ecosystem; determine, from a user activity database, a user profile indicating historical user activity data associated with the user identifier, wherein the historical user activity data comprises indications of previous output generation requests associated with the user device; provide the user profile, the current system state, and the output generation request to the first routing model to generate routing instructions and a large-language model identifier, wherein the routing instructions comprise an input modification indicator signaling whether to generate a modified input; determine that the routing instructions comprise an indication to execute a protocol to generate the modified input; responsive to determining that the routing instructions comprise the indication to execute the protocol to generate the modified input, execute instructions associated with the protocol to generate the modified input, wherein the protocol modifies at least one attribute of the input to generate the modified input; identify a first large-language model using the large-language model identifier generated by the first routing model; provide the modified input to the identified first large-language model to generate a model output responsive to the modified input; and transmit the generated model output to a server system enabling access to the generated model output by the user device.”.
Regarding claim 15, the prior art of Gallegari, Gasser and Hariri when taken in the context of the claim as a whole do not disclose nor suggest, “dynamically monitoring one or more system resource measurements to determine a current system state, wherein the current system state indicates real-time computational resource usage of a computing ecosystem; determining, from a user activity database, a user profile indicating historical user activity data associated with the identifier; providing the user profile, the current system state, and the output generation request to the first routing model to generate routing instructions and a model identifier; determining that the routing instructions comprise an indication to apply one or more instructions associated with a protocol to generate a modified input; responsive to determining that the routing instructions comprise the protocol to generate the modified input, executing the one or more instructions to generate the modified input; identifying a first model using the model identifier generated by the first routing model; providing the modified input to the identified first model to generate a model output responsive to the modified input; and transmiting the generated model output to a server system enabling access to the generated model output by the user device.”.
Claims 3-7 depend on claim 1 and claims 10-14 depend on claim 8, and are of consequence allowed.
Claims 16-20 depend on claim 15, and are of consequence identified as allowable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: See PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HASSAN SAADOUN whose telephone number is (571)272-8408. The examiner can normally be reached Mon-Fri 9:00-5:00.
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/HASSAN SAADOUN/Examiner, Art Unit 2435
/AMIR MEHRMANESH/Supervisory Patent Examiner, Art Unit 2435
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