WDETAILED ACTION
Notice of Pre-AIA or AIA Status
The Action is res e present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The Action is responsive to the Application filed 10/08/2025.
Please note claims 1-9 are pending and stand rejected in which claims 1 and 9 are independent.
Information Disclosure Statement
The information disclosure statements filed 10/08/2025 are compliant with 37 CFR 1.97(c) and herein have been considered. Its corresponding PTO-1449 have been electronically signed as attached.
Foreign Priority
Applicant’s claim for the benefit of a prior-filed INDIA Patent Application INDIA 202341026640 filed 04/10/2023, under 35 U.S.C. 119(a)-(d) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged.
Claim Interpretation
A “patent is invalid for indefiniteness if its claims, read in light of the specification delineating the patent, and the prosecution history, fail to inform, with reasonable certainty, those skilled in the art about the scope of the invention.” Nautilus, Inc. v. Biosig Instruments, Inc., 134 S.Ct. 2120, 2124, 110 USPQ2d 1688 (2014). The Office does not interpret claims when examining patent applications in the same manner as the courts. The Office construes claims by giving them their broadest reasonable interpretation during prosecution in an effort to establish a clear record of what the applicant intends to claim. See, MPEP 2173.02 (Determining Whether Claim Language is Definite). Such claim construction during prosecution may effectively result in a lower threshold for ambiguity than a court's determination. Id. However, Applicant has the ability to amend the claims during prosecution to ensure that the meaning of the language is clear and definite prior to issuance or provide a persuasive explanation (with evidence as necessary) that a person of ordinary skill in the art would not consider the claim language unclear. Id. (citing In re Buszard, 504 F.3d 1364, 1366 (Fed. Cir. 2007) (claims are given their broadest reasonable interpretation during prosecution “to facilitate sharpening and clarifying the claims at the application.
Claim Objections
Claim 1 is objected to because of the following informalities:
The claim recites “at least one processor in communication with a client processor (104)” in which “(104)” seems to be an extra.
Appropriate correction is required.
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.
Claims 9 and 1-8 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, regards as the invention.
As per claims 9 and 1, the claims recite “the one or more first input queries” in “collecting, by an objective collection module of the processing subsystem, a plurality of objectives of the one or more first input queries” and “… wherein the objective gathering module is configured to collect a plurality of objectives of the one or more first input queries”, respectively.
The claims recite “input query” and “first queries prompt”, however, there is insufficient antecedent basis for the limitations reciting “the one or more first input queries” in the claims.
As per claims 9 and 1, the claims recite “the selected option of the plurality of options” in “validating, by an assumption validation module of the processing subsystem, the selected option of the plurality of options for the one or more prompts based on a plurality of predefined utility validation rules” and “… wherein the assumption validation module is configured to validate the selected option of the plurality of options for the one or more prompts based on a plurality of predefined utility validation rules”, respectively.
However, there is insufficient antecedent basis for the limitations reciting “the selected option of the plurality of options” in the claims.
Claims 9 and 1 are further rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, regards as the invention. The claims are generally narrative and indefinite, failing to conform with current U.S. practice. They appear to be a literal translation into English from a foreign document and are replete with grammatical and idiomatic errors.
As per claim 1, the claim recites “… wherein the expected utility validation module is configured quantify the utility of the one or more …” in which ‘configured quantify’ seems to be of grammatical and idiomatic error and is indefinite.
As per claim 9, the claim recites “understanding, by a risk assessment and mitigation module of the processing subsystem, risk one or more input prompt related to a sensitive information and mitigation related to the one or more prompts for providing a holistically privacy optimized synthetic prompt generated with minimal identified risk;". The limitation, as a phrase, does not seem grammatically correct. It seems to be a fragmented, run-on sentence that misses proper verbs, prepositions, and clear structural connections, making it very difficult to read.
Further per claim 1, the claim recites “… to understand risk of one or more input prompt …” in which “risk” is not quantified or described definitely as a risk, one risk or the risk, is therefore indefinite.
As per claims 2-8, the claims respectively depend upon claim 1 directly and inherit the deficiency of being non-statutory from claim 8 and do not rectify the deficiency individually or by inheritance. Therefore, the consequence is non-statutory.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-9 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
As per claims 1-2 and 4-5, the claims recite various modules being coupled to other modules or [plainly] operatively configured to perform a series of operations. Based on the specification, the modules were described plainly as being configured to perform. However, the specification did not seem to describe configuring the modules nor how “operatively” the modules were configured to.
As per claims 2-8, the claims respectively depend upon claim 1 directly and inherit the deficiency of being non-statutory from claim 8 and do not rectify the deficiency individually or by inheritance. Therefore, the consequence is non-statutory.
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 of this title, 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.
In the event the determination of the status of the application as subject to 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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 non-obviousness.
For application naming joint inventors, in considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. § 102(b)(2)(C) for any potential 35 U.S.C. § 102(a)(2) prior art against the later invention.
Claims 1 and 7-9 are rejected under 35 U.S.C. § 103 as being unpatentable over
CALBUCCI et al.: “QUERY RECOGNIZER”, (China Patent Application Document CN 1629845 A, DATE PUBLISHED 2005-06-22 and DATE FILED 2004-12-16, hereafter “CALBUCCI") in view of
SELANDER et al.: “DEVICE AND METHOD FOR OBTAINING CODE PROMPTING”, (China Patent Application Document CN 103917980 A, DATE PUBLISHED 2014-07-09 and DATE FILED 2011-11-08, hereafter “SELANDER"), and further in view of
POTTER et al.: “DIAGNOSING RECOGNITION PROBLEMS FROM UNTRANSCRIBED DATA”, (Korea Patent Application Document KR 20080020649 A, DATE PUBLISHED 2008-03-05and DATE FILED 2007-12-28, hereafter “POTTER").
As per claim 9, CALBUCCI teaches a method for conducting a prescriptive and protected prompt engineering for a generative artificial intelligence comprising:
characterized in that:
receiving, by a user requirement module of a processing subsystem, first queries prompt from a user as a user requirement (See Page 5, query analyzer 10 receives a query from the user);
collecting, by a context gathering module of the processing subsystem, an information related to a context of the input query (See Page 6, receiving the input query 110 and access 120 for a specific user query context information, geographic and Internet (web) according to the query starting point, website recently visited by the user and the latest from the query input by the user and the query result selected by the user.);
collecting, by an objective collection module of the processing subsystem, a plurality of objectives of the one or more first input queries (See Page 13, query of interest expansion. considering these two examples: example 1: text box input by user through the search phrase "Restaurants in Redmond in his or her browser, WA (Washington gossypium commercial restaurant)". expanding the query to form a phrase identifier "Restaurants III Redmond, WA zip: 98052:90 gcat: Ks-local: 60", wherein "zip 98052:90" refers to such a query with 90% chance relates to zip code 98052, which is a piece of useful information to a search engine. Furthermore, the "Ks-local: 60" classification refers to the confidence of the query to 60% request for local search content. Here the query form expansion modifying queries and collecting modified user interest reads on collecting the objectives of user queries); and
understanding, by a risk assessment and mitigation module of the processing subsystem, risk one or more input prompt related to a sensitive information and mitigation related to the one or more prompts for providing a holistically privacy optimized synthetic prompt generated with minimal identified risk (See Page 7, the query processor identifier or identification phrase acting as a query, an indicator of a type of word, types such as position-sensitive local query, or search query of the item to be purchased. identification of these words or can prompt a query processor to query expansion context-specific information, such as based on zip code and area code information of the origin of the geographical starting point query).
CALBUCCI does not explicitly teach generating, by a prompt creation module of the processing subsystem, the one or more holistically optimized and privacy preserved prompts by consideration of output of context gathering module and object gathering module.
However, SELANDER teaches generating, by a prompt creation module of the processing subsystem, the one or more holistically optimized and privacy preserved prompts by consideration of output of context gathering module and object gathering module (See Page 12, running local password reminder application 105a to perform herein described for various functions (e.g., creating code, creating a password prompt, storing the password prompt, retrieving a password prompt). Here the password of the password reads on the holistically optimized and privacy preserved).
It would have been obvious to one having ordinary skill in the art at the time of the Applicant's application was filed to combine the teaching of SELANDER with CALBUCCI reference because CALBUCCI is dedicated to effectively providing a response to the inquiry of automatic query analyzer, and SELANDER is dedicated to obtaining code prompting providing a password prompt, and the combined teaching would have enhanced the system security of CALBUCCI because of password protection.
CALBUCCI in view of SELANDER further teaches:
suggesting, by an interactive query module of the processing subsystem, one or more second queries prompt to the user based on the user requirement to generate one or more prompts to allow the user to select and edit the one or more prompts (See SELANDER: Page 28, generating a password prompt or from a predefined password prompt is selected in a combination password prompt); and
validating, by an assumption validation module of the processing subsystem, the selected option of the plurality of options for the one or more prompts based on a plurality of predefined utility validation rules (See SELANDER: Page 32, when the user later (e.g., by reaching a login screen) occupancy (engage) target validation system 605, target verification system can be provided to the user (e.g., by clicking a button) from the IdP retrieving its prompt option. in response to a user request, the target authentication system may be retrieved from the IdP password prompt or (e.g., via heavy orientation or pop-up window) that the client terminal retrieving code prompt.).
CALBUCCI in view of SELANDER does not explicitly teach quantifying, by an expected utility validation module of the processing subsystem, the utility of the one or more generated optimized prompt with minimal risk as optimized by risk assessment and mitigation module and select the most optimal prompt.
However, POTTER teaches quantifying, by an expected utility validation module of the processing subsystem, the utility of the one or more generated optimized prompt with minimal risk as optimized by risk assessment and mitigation module and select the most optimal prompt (Page 23, If the validation associated with the CompareValidator control fails, the Prompt property can specify an executable Prompt object that informs the user that the obtained result was not correct. If the validation fails during the comparison, the associated SemanticItem defined by SemanticItemtoValidate is marked empty, so that the system will prompt the user to get the correct value. However, if an invalid value is used at the prompt for the user to repeat the invalid value, it may be helpful to not clear the invalid value of the associated SemanticItem in the semantic map. Here the value used at the prompt is validated reads on the quantifying the utility of the one or more generated optimized prompt and the marked empty of the SemanticItem reads on optimized prompt with minimal risk as optimized by risk assessment and mitigation module and selecting the most optimal prompt).
It would have been obvious to one having ordinary skill in the art at the time of the Applicant's application was filed to combine the teaching of POTTER with CALBUCCI in view of SELANDER reference because CALBUCCI is dedicated to effectively providing a response to the inquiry of automatic query analyzer, SELANDER is dedicated to obtaining code prompting providing a password prompt and POTTER is dedicated to estimating of semantic recognition accuracy by semantic inferences, and the combined teaching would have allowed CALBUCCI in view of SELANDER to use estimate semantic inferences to improve accuracy of query responses.
CALBUCCI in view of SELANDER and further in view of POTTER further teaches:
translating, by a prompt translation module of the processing subsystem, the selected prompt by the interactive query module based on a language preference of the user (See POTTER: Page 19, It may or may not have a corresponding prompt, such as speech conversion, but has a grammar corresponding to the expected value for recognition and an event handler to process the input, or no speech detected, speech not recognized Handle other recognizer events, such as none or events that run on timeout.).
As per claim 1, the claim recites a system for prescriptive and protected prompt engineering for a generative artificial intelligence comprising:
at least one processor in communication with a client processor (104) (See Page 8, processor executable instructions that may be recorded on any form of computer readable media); and
characterized in that:
at least one memory comprises a set of program instructions in the form of a processing subsystem, configured to be executed by the at least one processor (See Page 8, processor executable instructions that may be recorded on any form of computer readable media),
wherein the processing subsystem is hosted on a server and configured to execute on a network to control bidirectional communications (See Page 8, known computing systems, environments, and / or configurations that may be suitable for use in the present invention include wireless or cellular telephones, ordinary telephones (no screen), personal computers, server computers, hand-held or laptop computers, Including multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like, It is not limited to this) among a plurality of modules (See Page 15, the web server 202 may include a server side plug-in authoring tool or module 209 (e.g., Microsoft's ASP, ASP +, ASP.NET, JSP, Javabeans, etc.). have. Server-side plug-in module 209 can dynamically generate client-side markup and even some form of markup for clients of the type accessing web server 202. Client information may be provided to the web server 202 upon initial establishment of a client / server relationship, or the web server 202 may include a module or routine that detects the performance of the client device. As such, server-side plug-in module 209 provides client-side markup for each voice recognition scenario, i.e., voice only over phone 80 or multimodal for device 30. May occur.) comprising operations recited as steps of the method of claim 9 and rejected above under 35 U.S.C. § 103 as being unpatentable over CALBUCCI in view of SELANDER and further in view of POTTER.
Accordingly, claim 1 is rejected along the same rationale that rejected claim 9.
As per claim 7, CALBUCCI in view of SELANDER and further in view of POTTER teaches the system as claimed in claim 1, wherein the expected utility validation module while selecting the most optimal prompt may involve human in the loop based on configurable threshold parameters based on prompts' utility and level of risk identified (See POTTER: The ExtraAnswers property contains one or more Answer objects that are defined for possible additional information that the user can also speak. In the example provided above, if the information regarding the departure date is also retrieved, the system does not need to prompt the user again to obtain this information, assuming that the confirmation level has exceeded the corresponding ConfirmThreshold. If the confirmation level does not exceed the corresponding threshold, the appropriate Confirms attribute is activated; and SELANDER: [0077] In step 420, in the step 320, the password prompting system for determining spatial mode satisfies the mode request (e.g., sufficient complex). if not (indicated by The negative branch from 420), then password prompt system to remind the user the other mode (e.g. to 410 indicated by the feedback loop));.
As per claim 8, CALBUCCI in view of SELANDER and further in view of POTTER teaches the system as claimed in claim 1, wherein the prompt translation module may translate a prompt to a different language based on user preference or administrator preference or downstream model performance for various languages (See CALBUCCI: Page 4, the query processor comprises a recognizer agent program used to send to the specified one or more plurality of identifier query. One such identifier is the word or language symbol (token) identifier. The system will query input words or language symbols and words stored in the database is matched, and these words with a confidence level for classification. confidence database record history level is derived from user defined level, using a previously submitted query.).
Claim 2-4 are rejected under 35 U.S.C. § 103 as being unpatentable over
CALBUCCI in view of
SELANDER, and further in view of
POTTER as applied to claim 1 and 7-9 above, and further in view of
KIng et al.: “GENERATING CREDIT BUILDING RECOMMENDATIONS THROUGH MACHINE LEARNING ANALYSIS OF USER ACTIVITY-BASED FEEDBACK”, (U.S. Patent US 11900451 B1, DATE PUBLISHED 2024-02-13 and DATE FILED 2020-09-15, hereafter “King")
As per claim 2, CALBUCCI in view of SELANDER, and further in view of POTTER does not explicitly teach the system as claimed in claim 1, is configured to provide a plurality of recommendations based on the information collected.
However, King teaches the system as claimed in claim 1, is configured to provide a plurality of recommendations based on the information collected (See col. 2, lines 38-43, the credit building system makes an assessment in real time to determine potential user actions that can be taken to improve credit health using the collected data and generates, based on that assessment, a recommendation to provide to the user regarding at least one activity that should be performed to reach the goal.).
It would have been obvious to one having ordinary skill in the art at the time of the Applicant's application was filed to combine the teaching of King with CALBUCCI in view of SELANDER, and further in view of POTTER reference because CALBUCCI is dedicated to effectively providing a response to the inquiry of automatic query analyzer, SELANDER is dedicated to obtaining code prompting providing a password prompt, POTTER is dedicated to estimating of semantic recognition accuracy by semantic inferences and King is dedicated to a real-time activity recommendation system, and the combined teaching would have allowed CALBUCCI in view of SELANDER, and further in view of POTTER to make real-time and update recommendation of query responses to the user.
CALBUCCI in view of SELANDER, and further in view of POTTER and King further teaches:
wherein the plurality of recommendation comprises at least one of a grammar change, time change, and a change in financial information (See King: Abstract and col. 20, line 9, User and third party activity is later monitored as the user's financial status changes over time, in circumstances and the recommendations are updated accordingly).
As per claim 3, CALBUCCI in view of SELANDER, and further in view of POTTER and King teaches the system as claimed in claim 1, wherein the processing subsystem comprises an artificial intelligence model operatively coupled with the context gathering module trained based on the context and provides the plurality of prompt recommendation along with a prompt recommendation for selecting one or more foremost prompt by the user (See King: Abstract, Using machine learning models to evaluate patterns of user activity that contribute positively towards the goal, and to evaluate the limitations and opportunities of the user's financial circumstances and profile, the recommendation system makes an assessment in real time to determine user actions that can be taken to improve credit health based on a user's profile and activity data. A user-specific recommendation regarding an activity that should be performed to reach the goal is generated and transmitted to the user.).
As per claim 4, CALBUCCI in view of SELANDER, and further in view of POTTER and King teaches the system as claimed in claim 1, wherein the processing subsystem comprises a feedback capture module operatively coupled to the interactive query module (See King: col. 14, lines 39-50, credit builder system 150 may provide activity recommendations to users based on feedback from machine learning models.; user input module 331 receives data collected from user 110, the data including the user's financial condition, information regarding account enrollment, income, spending, debt, opt-in and opt-out settings to various forms of user monitoring, and the like),
wherein the feedback capture module is configured to allow the user to provide feedback and captures the feedback provided by the user for providing further prompt recommendations (See King: col. 14, lines 39-50, credit builder system 150 may provide activity recommendations to users based on feedback from machine learning models.).
Claim 5 is rejected under 35 U.S.C. § 103 as being unpatentable over
CALBUCCI in view of
SELANDER, and further in view of
POTTER as applied to claim 1 and 7-9 above, and further in view of
Motiian et al.: “SINGLE IMAGE CONCEPT ENCODER FOR PERSONALIZATION USING A PRETRAINED DIFFUSION MODEL”, (U.S. Patent Application Publication US 20240153259 A1, DATE PUBLISHED 2024-05-09 and DATE FILED 2022-11-08, hereafter “Motiian")
As per claim 5, CALBUCCI in view of SELANDER, and further in view of POTTER does not explicitly teach the system as claimed in claim 1, wherein the objective gathering module is configured to collect a plurality of objectives from the prompt, user role, configured usage and chain of thoughts based on which the objective of creating an optimized synthetic prompt is created.
However, Motiian teaches the system as claimed in claim 1, wherein the objective gathering module is configured to collect a plurality of objectives from the prompt, user role, configured usage and chain of thoughts based on which the objective of creating an optimized synthetic prompt is created (See [0040] and [0057], diffusion model 255 receives a text prompt indicating content for the synthetic image, generates guidance vector based on the text prompt, where the style vector is in a same latent space as the guidance vector, and where the synthetic image is generated to include the content based on the guidance vector; and . A style vector for a training image may be optimized by updating the style vector based on comparing the training image to a synthetic image generated using the training image, a prompt generated for the training image, and the style vector (e.g., a previous value of the style vector).).
It would have been obvious to one having ordinary skill in the art at the time of the Applicant's application was filed to combine the teaching of Motiian with CALBUCCI in view of SELANDER, and further in view of POTTER reference because CALBUCCI is dedicated to effectively providing a response to the inquiry of automatic query analyzer, SELANDER is dedicated to obtaining code prompting providing a password prompt, POTTER is dedicated to estimating of semantic recognition accuracy by semantic inferences and Motiian is dedicated to machine learning for image processing, and the combined teaching would have allowed CALBUCCI in view of SELANDER, and further in view of POTTER to use diffusion model to create an optimized synthetic prompt.
As per claim 6, CALBUCCI in view of SELANDER, and further in view of POTTER and Motiian teaches the system as claimed in claim 1, wherein the prompt creation module helps in holistically optimized and privacy preserved prompts by rewriting the complete prompt based on the context gathering module, user role, configured usage, chain of thoughts and historic behavior (See SELANDER: Page 12, running local password reminder application 105a to perform herein described for various functions (e.g., creating code, creating a password prompt, storing the password prompt, retrieving a password prompt). Here the password of the password reads on the holistically optimized and privacy preserved; and Motiian: [0040] and [0057], diffusion model 255 receives a text prompt indicating content for the synthetic image, generates guidance vector based on the text prompt, where the style vector is in a same latent space as the guidance vector, and where the synthetic image is generated to include the content based on the guidance vector; and . A style vector for a training image may be optimized by updating the style vector based on comparing the training image to a synthetic image generated using the training image, a prompt generated for the training image, and the style vector (e.g., a previous value of the style vector)).
Related Prior Arts
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the PTO-892 Notice of Reference Cited.
Conclusion
Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. SEE MPEP 2141.02 [R-5] VI. PRIOR ART MUST BE CONSIDERED IN ITS ENTIRETY, INCLUDING DISCLOSURES THAT TEACH AWAY FROM THE CLAIMS: A prior art reference must be considered in its entirety, i.e., as a whole, including portions that would lead away from the claimed invention. W.L. Gore & Associates, Inc. v. Garlock, Inc., 721 F.2d 1540, 220 USPQ 303 (Fed. Cir. 1983), cert. denied, 469 U.S. 851 (1984) In re Fulton, 391 F.3d 1195, 1201, 73 USPQ2d 1141, 1146 (Fed. Cir. 2004). >See also MPEP §2123.
In the case of amending the Claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KUEN S LU whose telephone number is (571)272-4114. The examiner can normally be reached on M-F, 8-19, Mid-Flex 2 hours.
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, Mr. Aleksandr Kerzhner can be reached on 571-270-1760. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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KUEN S LU /Kuen S Lu/
Art Unit 2165
Primary Patent Examiner
August 15, 2026
Prosecution Insights