DETAILED ACTION
This Final Office Action is in response Applicant communication filed on
9/26/2025. In Applicant’s amendment, claims 15, 21, and 32 were amended.
Claims 15-34 are currently pending and have been rejected as follows. IDS filed 11/21/2025 was considered.
Response to Amendments
Rejections under 35 USC 101 are maintained. Rejections under 35 USC 103 are withdrawn.
Response to Arguments
Applicant’s 35 USC 101 rebuttal arguments and amendments have been fully considered but they are not persuasive to overcome the rejection.
Applicant argues on p. 10 that the claims are directed to a specific improvement in how a computing system trains and deploys machine learning models for solution configuration tasks by separating solution-selection and configuration into distinct models, which yields more accurate recommendations than if a single, general model were used because training separate models per solution avoids domain conflicts and allows each configuration model to specialize to its respective solution. Examiner respectfully disagrees. The claimed improvement above is to the accuracy of the result, not an improvement to how a computing system trains and deploys machine learning models. The claimed separation and training of solution specific models is directed to the abstract idea of mathematical concepts.
Applicant argues on p. 10-11 that McRO and Thales show improved accuracy can be eligible. Examiner respectfully disagrees. In McRO, the incorporation of particular claimed rules improved the existing technological process allowing computers to produce realistic lip synchronization and facial expressions in animated characters. The human artists did not use the claimed rules and instead relied on subjective determinations to set morph weights and manipulated the animated face to match pronounced phonemes. In Thales, the claims did not merely recite abstract mathematical concepts. Instead, the claims were tied to a particular configuration of inertial sensors and a method of using the raw data from the particular configuration of inertial sensors in order to more accurately calculate the position and orientation of an object on a moving platform. In contrast, the present claims do not recite a particular technical configuration tied to the abstract mathematical concepts.
Applicant argues on p. 11 that the claimed design also improves efficiency by the identification of one or more candidate solutions and only invoking the corresponding configuration model. Examiner respectfully submits the claim does not recite the technical detail and structure to show an improvement to the efficiency of the computing system.
Applicant argues on p. 11 that the modularity of the claimed approach enhances scalability because the models are distinct and separately trained, which allows them to be updated independently as more products or configurations are added. Examiner respectfully submits the claim does not recite updating individual models, retraining models, deployment or evolution as new products or configurations are added.
Applicant's prior art arguments have been fully considered and they are persuasive to overcome the rejection. In particular, see applicant’s remarks on p. 8-9. Further search identified prior art considered relevant to applicant’s disclosure but it did not cure the deficiencies of the Prabhu and Veillon references.
Claim Rejections - 35 USC § 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 15-34 are clearly drawn to at least one of the four categories of patent eligible subject matter recited in 35 U.S.C. 101 (method, system, and non-transitory computer readable storage media). Claims 15-34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without integrating the abstract idea into a practical application or amounting to significantly more than the abstract idea.
Regarding Step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance (‘2019 PEG”), Claims 15-20 are directed toward the statutory category of an article of manufacturer (reciting a “non-transitory computer readable storage media”). Claims 21-31 are directed toward the statutory category of a machine (reciting a “system”). Claims 32-34 are directed toward the statutory category of a process (reciting a “method”).
Regarding Step 2A, prong 1 of the 2019 PEG, Claims 15, 21 and 32 are directed to an abstract idea by reciting […] training a first machine learning model using a first data set comprising requirements data and configuration data for a plurality of solutions, wherein the first data set associates the requirements and configuration data with a solution identifier for a respective solution, the solution identifier serving as a training label for the first machine learning model; training a plurality of second machine learning models using a respective plurality of second data sets, where a respective second data set of the respective plurality of second data sets comprises (1) requirements data; and (2) configuration data for a respective solution of the plurality of solutions and excludes configuration data for other solutions of the plurality of solutions, wherein the configuration data of the respective data sets serve as training labels for the corresponding second machine learning models; receiving a request for a solution configuration recommendation, the request for a solution configuration recommendation comprising an input set of requirements data; and generating at least one final configuration recommendation based at least in part on both of (1) a first inference result obtained by submitting the input set of requirements data to the first machine learning model; and (2) a second inference result obtained by submitting the input set of requirements data to a second machine learning model of the plurality of second machine learning models (Example Claim 32).
The claims are considered abstract because these steps recite mathematical concepts and mental processes. The claims recite training machine learning models (mathematical concepts) and obtaining a configuration recommendation based on two machine learning model outputs regarding an input set of requirements data (mathematical concepts and mental processes). Applicant’s disclosure suggests the claimed steps aim to bridge the gap between a user knowing what their needs are but not knowing how to satisfy those needs (Applicant’s Specification, [0002]-[0005]). By this evidence, the claims recite a type of mathematical concepts and mental processes common to judicial exception to patent-eligibility. By preponderance, the claims recite an abstract idea (e.g., a model for technical requirements configuration).
Regarding Step 2A, prong 2 of the 2019 PEG, the judicial exception is not integrated into a practical application because the claims (the judicial exception and the additional elements such as at least one hardware processor and at least one memory) are not an improvement to a computer or a technology, the claims do not apply the judicial exception with a particular machine, the claims do not effect a transformation or reduction of a particular article to a different state or thing nor do the claims apply the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment such that the claims as a whole is more than a drafting effort designed to monopolize the exception (see MPEP §§ 2106.05(a-c, e)).
Dependent claims 16-20, 22-31, and 33-34 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea ‐ see MPEP 2106.05(f).
Regarding Step 2B of the 2019 PEG, the additional elements have been considered above in Step 2A Prong 2. The claim limitations do not amount to significantly more than the judicial exception because they are directed to limitations referenced in MPEP 2106.05I.A. that are not enough to qualify as significantly more when recited in a claim with an abstract idea because the limitations recite mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea ‐ see MPEP
2106.05(f).
Applicant's claims mimic conventional, routine, and generic computing by their similarity to other concepts already deemed routine, generic, and conventional [Berkheimer Memorandum, Page 4, item 2] by the following [MPEP § 2106.05(d) Part (II)]. The claims recite steps like: “Receiving or transmitting data over a network, e.g., using the Internet to gather data,” Symantec, “Performing repetitive calculations,” Flook, and “storing and retrieving information in memory,” Versata Dev. Group, Inc. v. SAP Am., Inc. (citations omitted), by performing steps to “training” machine learning models, “receiving” a request, and “generating” a result (Example Claim 32).
By the above, the claimed computing “call[s] for performance of the claimed information collection, analysis, and display functions ‘on a set of generic computer components' and display devices” [Elec. Power Group, 830 F.3d at 1355] operating in a “normal, expected manner” [DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d at 1245, 1258 (Fed. Cir. 2014)].
Conclusively, Applicant's invention is patent-ineligible. When viewed both individually and as a whole, Claims 15-34 are directed toward an abstract idea without integration into a practical application and lacking an inventive concept.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US 11361758 B2; WO 2022258775 A1; Al Ridhawi et al., Generalizing AI: Challenges and Opportunities for Plug and Play AI Solutions, 2020.
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 extension fee 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 MOHAMED EL-BATHY whose telephone number is (571)270-5847. The examiner can normally be reached on M-F 8AM-4:30PM.
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/MOHAMED N EL-BATHY/Primary Examiner, Art Unit 3624