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 .
Detailed Action
In amendments dated 6/15/26, Applicant amended claims 1, 14, and 18, canceled claim 9, and added new claims 21-22. Claims 1-8 and 10-22 are presented for examination.
Examiner notes the claim status for claims 14 and 18 are listed as Original but both claims were amended and should have status Currently Amended.
Objections
Claims 1-4, 10, 14-16, and 18 are objected to because of the following informality: each of independent claims 1, 14, and 18 recites “obtaining, via the one or more processors, review data associated with the first document;” and “obtaining, via the one or more processors, review data associated with the plurality of training documents,” and then recites “generating, via the one or more processors, one or more validation metrics based upon a comparison of the review data” but the antecedent basis of “the review data” is unclear. Claims 2-4, 10, and 15-16 are also objected to as they each recite “the review data” but it also lacks clear antecedent basis.
Rejections under 35 U.S.C. 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-8 and 10-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to mental processes without significantly more. Independent claims 1, 14, and 18 each recites generating, via the one or more processors, a first prompt based upon the at least one prompt criteria; inputting, via the one or more processors, the first prompt and a first document of the corpus of documents into the generative Al model to obtain a classification of the first document; updating, via the one or more processors, the at least one prompt criteria based on the classification of the first document and the review data; generating, via the one or more processors, a second prompt based upon the updated at least one prompt criteria; classifying, via the one or more processors, a plurality of training documents by inputting the second prompt into the generative Al model; generating, via the one or more processors, one or more validation metrics based upon a comparison of the review data and the classifications of documents of the plurality of training documents; and determining, via the one or more processors, that the second prompt is acceptable based on the one or more validation metrics; and classifying, via the one or more processors, a second document by inputting the second prompt into the generative Al model. Generating a prompt and a second prompt and generating one or more validation metrics are each generating data and mental processes accomplishable in the human mind or on paper, inputting the prompt and a first document into a model is inputting data into a process and a mental process accomplishable in the human mind or on paper, and updating a prompt criteria is modifying data and a mental process accomplishable in the human mind or on paper. Examiner notes classifying a first document and a second document and classifying a plurality of training documents with a generative AI model is applying the model and is not significantly more than a mental process per Recentive Analytics v. Fox Broadcasting Corp. (134 F.4th 1205, 2025 U.S.P.Q.2d 628). Determining that the second prompt is acceptable is evaluating and a mental process. Each of these claims recites additional elements of obtaining, via one or more processors, at least one prompt criteria defining context for classifying a corpus of documents using the generative Al model; obtaining, via the one or more processors, review data associated with the first document; and obtaining, via the one or more processors, review data associated with the plurality of training documents, and obtaining a prompt criteria and review data are data gathering steps and insignificant extra-solution activity. Claim 14 recites one or more processors and claim 18 recites one or more processors and one or more non-transitory memories, which are each generic components of a computer system. Examiner notes paragraphs 0004, 0032, and 0034 discuss how deploying machine learning models during an eDiscovery process can be cumbersome and inefficient, such as if different attorneys deploy the models in different ways or if thousands of documents need to be used to train the classifier. The specification begins discussing improvements upon said drawbacks for eDiscovery of documents in paragraph 0033 in describing categories and/or criteria for said prompt. Prompt criteria is further discussed in paragraphs 0058-0077 and figures 2-4. The claim steps do not recite a particular improvement in any technology or function of a computer per MPEP 2106.04(d) and do not recite any unconventional steps in the invention per MPEP 2106.05(a). Therefore, the recited mental processes are not integrated into a practical application. Taking the claims as a whole, the input steps are recited broadly and amount to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II. The one or more processors and one or more non-transitory memories are each still generic components of a computer system. Thus the claims do not include additional elements that are sufficient to amount to significantly more than the recited mental processes.
Independent claims 21-22 each recites generating, via the one or more processors, a first prompt based upon the at least one prompt criteria; inputting, via the one or more processors, the first prompt and a first document of the corpus of documents into the generative Al model to obtain a classification of the first document; determining that the comment associated with the first document is relevant to a second document; updating, via the one or more processors, the at least one prompt criteria based on the classification of the first document and the review data; generating, via the one or more processors, a second prompt based upon the updated at least one prompt criteria; and classifying, via the one or more processors, the second document by inputting the second prompt into the generative Al model. Generating a prompt and generating a second prompt are each mental processes accomplishable in the human mind or on paper. Determining that a comment is relevant to a second document is evaluating and a mental process. Updating a prompt criteria is modifying data and a mental process accomplishable in the human mind or on paper. Classifying a document by inputting the document into a generative AI model is applying the model which is not significantly more than a mental process per Recentive Analytics v. Fox Broadcasting Corp. (134 F.4th 1205, 2025 U.S.P.Q.2d 628). Each claim recites additional elements of obtaining, via one or more processors, at least one prompt criteria defining context for classifying a corpus of documents using the generative Al model, a data gathering step and insignificant extra-solution activity; obtaining, via the one or more processors, review data associated with the first document, also a data gathering step and insignificant extra-solution activity, wherein obtaining the review data comprises: obtaining the review data comprising a comment associated with the first document, also a data gathering step and insignificant extra-solution activity; storing the comment associated with the first document in a memory, which is insignificant extra-solution activity; in response to determining that the comment associated with the first document is relevant to the second document: (i) retrieving the comment associated with the first document from the memory, which is insignificant extra-solution activity, and (ii) presenting both the second document and the comment associated with the first document via a document review user interface presented by a user device, which is an output step and insignificant extra-solution activity. Claim 22 recites one or more processors and one or more non-transitory memories having stored thereon computer-executable instructions, which are generic components of a computer. Examiner notes paragraphs 0004, 0032, and 0034 discuss how deploying machine learning models during an eDiscovery process can be cumbersome and inefficient, such as if different attorneys deploy the models in different ways or if thousands of documents need to be used to train the classifier. The specification begins discussing improvements upon said drawbacks for eDiscovery of documents in paragraph 0033 in describing categories and/or criteria for said prompt. Prompt criteria is further discussed in paragraphs 0058-0077 and figures 2-4. The claim steps do not recite a particular improvement in any technology or function of a computer per MPEP 2106.04(d) and do not recite any unconventional steps in the invention per MPEP 2106.05(a). Therefore, the recited mental processes are not integrated into a practical application. Taking the claims as a whole, the data gathering steps are each recited broadly and amount to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II. The output step is also recited broadly and amounts to sending data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II. Storing data and retrieving data from a memory are each routine and conventional activities per the list of such activities in MPEP 2106.05(d) part II. The one or more processors and one or more non-transitory memories having stored thereon computer-executable instructions are each still generic components of a computer. Thus the claims do not include additional elements that are sufficient to amount to significantly more than the recited mental processes.
Claims 2, 16, and 19 each recites wherein the review data comprises a comment associated with the first document, and review data is data and a mental process accomplishable in the human mind or on paper. Claim 3 recites obtaining, via the one or more processors, first review data comprising a first comment associated with the first document, which is recited broadly and amount to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II; obtaining, via the one or more processors, second review data comprising a second comment associated with the first document, which is recited broadly and amount to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II; and merging, via the one or more processors, the first review data with the second review data to create the review data, and merging data is recited broadly and is a mental process accomplishable in the human mind or on paper. Claims 4 and 15 each recites presenting, via the one or more processors, the first document via a document review user interface presented by a user device, wherein the document review user interface includes document review elements configured to enable a user of the user device to classify the first document, and presenting a document is recited broadly and amount to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II; and detecting, via the one or more processors and via the document review user interface: (i) an indication of whether the classification of the first document is correct, and/or (ii) a user- provided classification of the first document, and detecting that a classification is correct or detecting a classification is a evaluating and a mental process.
Claim 5 recites detecting comprises detecting, via the one or more processors and via the document review user interface, the indication, and wherein the indication indicates that the classification of the first document is not correct, and detecting that a classification is not correct is evaluating and a mental process; and updating the at least one prompt criteria comprises generating, via the one or more processors, a proposed update to the at least one prompt criteria by inputting, into the generative Al model, that the classification of the first document is not correct, and updating a prompt criteria is modifying data and a mental process accomplishable in the human mind or on paper. Claims 6, 17, and 20 each recites generating, via the one or more processors, the first prompt by supplementing the at least one prompt criteria with additional context, and supplementing a criteria with additional text is adding data and a mental process accomplishable in the human mind or on paper. Claim 7 recites generating, via the one or more processors, a proposed update to the at least one prompt criteria via the generative Al model or via a second generative Al model, and applying an AI model and is not significantly more than a mental process per Recentive Analytics v. Fox Broadcasting Corp. (134 F.4th 1205, 2025 U.S.P.Q.2d 628). Claim 8 recites presenting, via the one or more processors, the proposed update via a prompt criteria editor interface presented by a user device, and presenting data is recited broadly and amount to sending data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II; detecting, via the one or more processors, confirmation that the proposed update is acceptable via the prompt criteria editor interface, and detecting input is evaluating and a mental process; and in response to detecting the confirmation, updating, via the one or more processors, the at least one prompt criteria in accordance with the proposed update, and updating a criteria is modifying it and a mental process accomplishable in the human mind or on paper.
Claim 10 recites obtaining, via the one or more processors, the review data comprising a comment associated with the first document, and obtaining review data is recited broadly and amounts to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II; storing, via the one or more processors, the comment associated with the first document in a memory, and storing data in a memory is routine and conventional per the list of such activities in MPEP 2106.05(d) part II; determining, via the one or more processors, that the comment associated with the first document is relevant to the second document, and determining a comment is relevant is evaluating and a mental process; and in response to determining that the comment associated with the first document is relevant to the second document: (i) retrieving, via the one or more processors, the comment associated with the first document from the memory, and (ii) presenting, via the one or more processors, both the second document and the comment associated with the first document via a document review user interface presented by a user device, and retrieving data from a memory is routine and conventional per the list of such activities in MPEP 2106.05(d) part II, and presenting retrieved data is recited broadly and amounts to receiving data across a network per specification 0045 and figure 10, which is routine and conventional activity per the list of such activities in MPEP 2106.05(d) part II.
Claim 11 recites wherein the at least one prompt criteria includes one or more categories of: case summary; relevance; and/or key documents, and prompt criteria is data and a mental process accomplishable in the human mind or on paper. Claim 12 recites wherein the classification includes classifying a document as one of: junk; responsive; not responsive; likely responsive; or likely not responsive, and a classification is data and a mental process accomplishable in the human mind or on paper. Claim 13 recites wherein the generative AI model is configured to output a confidence score that the classification of the first document is correct, and applying a generative AI model to output a score is applying the AI model which is not significantly more than a mental process per Recentive Analytics v. Fox Broadcasting Corp. (134 F.4th 1205, 2025 U.S.P.Q.2d 628).
Relevant Prior Art
During his search for prior art, Examiner found the following references to be relevant to Applicant's claimed invention. Each reference is listed on the Notice of References form included in this office action:
Tal et al (US 20230376858) teaches parallelization of routines for training machine learning models to update model parameters in accordance with the training data to improve the accuracy of the models, does not teach inputting first and second prompts to the machine learning models, obtaining review data, and generating validation metrics based on comparison of the review data (paragraphs 0003, 0022, 0059-0064 figure 3); and
Garera et al (US 20140297570) teaches classifying records using a machine learning algorithm, identifying high confidence classifications for records and other classifications are sent for crowdsourcing validations, does not teach inputting first and second prompts to the machine learning models, obtaining review data, and generating validation metrics based on comparison of the review data (paragraphs 0035-0052 figure 3).
Responses to Applicant’s Remarks
Regarding rejections of claims 1-20 under 35 U.S.C. 101 for reciting mental processes without significantly more, Applicant’s arguments have been considered but are not persuasive. On pages 10-13 of his Remarks Applicant reprints the amended limitations and asserts the amended claims integrate any abstract ideas into a practical application. On page 11 Applicant states “under MPEP § 2106.04(d)(1), a claim integrates a judicial exception into a practical application when it improves the functioning of a computer or improves another technology or technical field. To evaluate such an improvement, (1) the specification should provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement, and (2) the claim itself must reflect the disclosed improvement.” Examiner disagrees and notes that (2) from MPEP 2106.04(d)(1) is not met in the claims. Each of the amended independent claims 1, 14, and 18 still recite mental process steps as conclusive statements which lack details showing how the invention performs the recited steps. Each claim recites “generating, via the one or more processors, a first prompt based upon the at least one prompt criteria” and “generating, via the one or more processors, a second prompt based upon the updated prompt criteria” without details showing how the invention generates the prompts. Each claim also recites “generating, via the one or more processors, one or more validation metrics based upon a comparison of the review data and the classifications of documents of the plurality of training documents;” and “determining, via the one or more processors, that the second prompt is acceptable based on the one or more validation metrics;” but the generating and determining are recited broadly and do not recite how the invention generates validation metrics or how the invention determines the second prompt is acceptable. Furthermore, validation metrics are merely recited as data and the recited comparison of review data also lacks detail showing how the invention performs the comparison between the review data and the classifications. Thus these mental process steps recite no improvement in the function of a computer or to any technical field and they merely use the processor as a tool to perform the recited actions, and thus do not integrate the claims into a practical application. Regarding rejections of claims 1-8 and 11-20 under 35 U.S.C. 103 by Badr in view of Hall, Applicant’s amendments overcome Badr’s and Hall’s teachings.
Conclusion
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.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRUCE M MOSER whose telephone number is (571)270-1718. The examiner can normally be reached M-F 9a-5p.
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/BRUCE M MOSER/Primary Examiner, Art Unit 2154 8/24/26
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