AUTONOMOUS DECISION MAKING BASED ON PREDICTING FUTURE USER ACTIONS

DETAILED CORRESPONDENCE 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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on August 13, 2026 has been entered. Response to Amendment Claims 1, 7-8, and 14-15 have been amended. New Claims 22-24 were added. Claims 1-4, 7-11, 14-18, and 21-24 remain pending in the application and are provided to be examined upon their merits. Applicant’s amendments to the Claims have overcome each and every rejection under 35 U.S.C. § 103 previously set forth in the Final Correspondence mailed May 21, 2026. 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 1-4, 7-11, 14-18, and 21-24 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 significantly more. Claims 1-4, 7-11, 14-18, and 21-24 are directed to the abstract idea of: Claim 1 -: 1. A method for decision- making-, comprising: generating, at a- transaction- server-, a personality profile for a user based on questionnaire data and historical transactional data; tracking, at the- transaction- server- at a first time period, first financial activity of the user, the first financial activity including spending and cash flow of the user obtained from transaction data received from one- or- more- transaction- servers- remotely located from the- transaction- server-; generating labeled emotional-state training records by correlating the first financial activity with user-reported feedback regarding an emotional state of the user at the first time period; updating an emotional state learning- by fine-tuning one or more model parameters using the labeled emotional-state training records, the emotional state learning- having been previously trained on emotional data and financial activity of a group of users; tracking, at the- transaction- server- at a second time period, second financial activity of the user; predicting, via the updated emotional state learning- at a second time period, a current emotional state of the user based on user location data tracked via a positioning- and the second financial activity; predicting, via a learning-, one or more future financial events corresponding to the user in accordance with the personality profile, the second financial activity, user data, and the current emotional state; selecting, via an action learning-, an account-control action based on the one or more future financial events and the current emotional state, the action learning- having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs, generating control instructions based on the selected account-control action; and transmitting-, from the- transaction- server- to the one- or- more- transaction- servers-, the control instructions to modify one or more account parameters associated with one or more future financial accounts of the user, the one or more account parameters corresponding to one or more of a geographic location for use of one or more financial instruments associated with the one or more accounts or an amount that can be withdrawn or spent via the one or more financial instruments. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 2 -: 2. The method of claim 1, wherein the personality profile is a financial personality profile that is generated in accordance with the questionnaire data via an interface-. Claim 3 -: 3. The method of claim 1, further comprising updating the personality profile based on one or both of the first financial activity or the second financial activity, wherein the personality profile used for predicting the one or more financial events is the updated personality profile. Claim 4 -: 4. The method of claim 1, wherein the user data comprises user content consumption habits, and/or user demographic information. Claim 7 -: 7. The method of claim 1, wherein the action learning- selects the account-control action using a reward function that quantifies success of account-control actions based on improved savings rates, reduced debt, a success rate of interventions, and user satisfaction scores. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 8 -: 8. decision- making-, comprising: one- or- more-; and one- or- more- coupled with the one- or- more- and executable that, when executed by the one- or- more-, is configured to cause to: generate, at a- transaction- server-, a personality profile for a user based on questionnaire data and historical transactional data; track, at the- transaction- server- at a first time period, first financial activity of the user, the first financial activity including spending and cash flow of the user obtained from transaction data received from one- or- more- transaction- servers- remotely located from the- transaction- server-; generate labeled emotional-state training records by correlating the first financial activity with user-reported feedback regarding an emotional state of the user at the first time period; update an emotional state learning- by fine-tuning one or more model parameters using the labeled emotional-state training records, the emotional state learning- having been previously trained on emotional data and financial activity of a group of users; track, at the- transaction- server- at a second time period, second financial activity of the user; predict, via the updated emotional state learning- at a second time period, a current emotional state of the user based on user location data tracked via a positioning- and the second financial activity; predict, via a learning-, one or more future financial events corresponding to the user in accordance with the personality profile, the second financial activity, user data, and the current emotional state; select, via an action learning-, an account-control action based on the one or more future financial events and the current emotional state, the action learning- having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs; generate control instructions based on the selected account-control action; and transmit-, from the- transaction- server- to the one- or- more- transaction- servers-, the control instructions to modify one or more account parameters associated with one or more future financial accounts of the user, the one or more account parameters corresponding to one or more of a geographic location for use of one or more financial instruments associated with the one or more accounts or an amount that can be withdrawn or spent via the one or more financial instruments. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 9 -: 9. claim 8, wherein the personality... [id. at 2], Claim 10 -: 10. claim 8, wherein: execution of the executable further causes to update the personality profile based on one or both of the first financial activity or the second financial activity; and the personality profile used for predicting the one or more financial events is the updated personality profile. Claim 11 -: 11. claim 8, wherein the user... [id. at 4], Claim 14 -: 14. claim 8, wherein the action... [id. at 7], (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 15 -: 15. A non-transitory- readable- medium- having program- recorded thereon for decision- making-, the program- executed by one- or- more- and comprising: program- to generate, at a- transaction- server-, a personality profile for a user based on questionnaire data and historical transactional data; program- to track, at the- transaction- server- at a first time period, first financial activity of the user, the first financial activity including spending and cash flow of the user obtained from transaction data received from one- or- more- transaction- servers- remotely located from the- transaction- server-; program- to generate labeled emotional-state training records by correlating the first financial activity with user-reported feedback regarding an emotional state of the user at the first time period; program- to update an emotional state learning- by fine-tuning one or more model parameters using the labeled emotional-state training records, the emotional state learning- having been previously trained on emotional data and financial activity of a group of users; program- to track, at the- transaction- server- at a second time period, second financial activity of the user; program- to predict, via the updated emotional state learning- at a second time period, a current emotional state of the user based on user location data tracked via a positioning- and the second financial activity; program- to predict, via a learning-, one or more future financial events corresponding to the user in accordance with the personality profile, the second financial activity, user data, and the current emotional state; program- to select, via an action learning-, an account-control action based on the one or more future financial events and the current emotional state, the action learning- having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs; program- to generate control instructions based on the selected account-control action; and program- to transmit-, from the- transaction- server- to the one- or- more- transaction- servers-, the control instructions to modify one or more account parameters associated with one or more future financial accounts of the user, the one or more account parameters corresponding to one or more of a geographic location for use of one or more financial instruments associated with the one or more accounts or an amount that can be withdrawn or spent via the one or more financial instruments. (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) Claim 16 -: 16. The non-transitory- readable- medium- of claim 15, wherein the personality... [id. at 2], Claim 17 -: 17. The non-transitory- readable- medium- of claim 15, wherein: the program- further comprises program- to update the personality profile based on one or both of the first financial activity or the second financial activity; and the personality profile... [id. at 10], Claim 18 -: 18. The non-transitory- readable- medium- of claim 15, wherein the user... [id. at 4], Claim 21 -: 21. The non-transitory- readable- medium- of claim 15, wherein the action... [id. at 7], Claim 22 -: 22. The method of claim 1, wherein the one or more account parameters further comprise one or more of a savings rate, a contribution rate, or an investment strategy. Claim 23 -: 23. claim 8, wherein the one or... [id. at 22], Claim 24 -: 24. The non-transitory- readable- medium- of claim 15, wherein the one or... [id. at 22], (fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). ) . The identified limitation(s) falls within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance: b) Certain methods of organizing human activity – fundamental economic principles or practices, commercial or legal interactions, managing personal behavior or relationships or interactions between people, c) Mental processes – concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). These limitation excerpts, under their broadest reasonable interpretation, fall within the grouping(s) of abstract ideas of: Certain methods of organizing human activity – since: autonomous decision making based on predicting future user actions as recited in the claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) as fundamental economic principles or practices, (including hedging, insurance, mitigating risk); commercial or legal interactions, (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions). Mental processes – since: the above-underlined as recited in the claim limitations, under their broadest reasonable interpretation, covers performance of the limitation(s) as concepts performed in the human mind, (including an observation, evaluation, judgment, opinion). Therefore, the limitations fall within the above-identified grouping(s) of abstract ideas. While independent claims 1, 8, and 15 do not explicitly recite verbatim this identified abstract idea, the concept of this identified abstract idea is described by the steps of independent claim 1 and is described by the steps of independent claim 8 and is described by the steps of independent claim 15. Claim 1: Materially with respect to the analysis under Step 2A of the Office's § 101 Subject Matter Eligibility Test for Products and Processes, independent claim 1 further to the abstract idea includes additional elements of "autonomous decision making", "a transaction server", "the transaction server", "electronic", "one or more transaction servers", "machine learning model", "positioning system", and "autonomously transmitting". However, independent claim 1 does not include additional elements that are sufficient to integrate the exception into a practical application because "autonomous decision making", "a transaction server", "the transaction server", "electronic", "one or more transaction servers", "machine learning model", "positioning system", and "autonomously transmitting" of independent claim 1 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality that perform functions ("A method for autonomous decision making, comprising", "generating, at a transaction server, … and historical transactional data", "tracking, at the transaction server … from the transaction server", "generating labeled emotional-state training records … the first time period", "updating an emotional state machine … a group of users", "tracking, at the transaction server … activity of the user", "predicting, via the updated emotional … the second financial activity", "predicting, via a machine learning … the current emotional state", "selecting, via an action machine … account-control actions as outputs", "generating control instructions based on … selected account-control action; and" and "autonomously transmitting, from the transaction … or more financial instruments") that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself (e.g. all or portion(s) of the noted recited steps) and/or that recite generic computer and/or field of use functions that are recited at a high-level of generality that include only steps narrowing the abstract idea [Step 2A Prong I] (e.g. all or portion(s) of the noted recited steps) and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, [Step 2A Prong II] adding the words "apply it" (or an equivalent) with the judicial exception, or 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) (all or portions of the "generating, at a transaction server, … and historical transactional data", "tracking, at the transaction server … from the transaction server", "updating an emotional state machine … a group of users", "tracking, at the transaction server … activity of the user", "predicting, via the updated emotional … the second financial activity", "predicting, via a machine learning … the current emotional state", "selecting, via an action machine … account-control actions as outputs", "autonomously transmitting, from the transaction … or more financial instruments" step(s)), and adding insignificant extra-solution activity to the judicial exception -- see MPEP 2106.05(g) (all or portions of the "autonomously transmitting, from the transaction … or more financial instruments" step(s)), and generally linking the use of the judicial exception to a particular technological environment or field of use -- see MPEP 2106.05(h) (all or portions of the noted step(s)). Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Furthermore, the additional method steps comprise or include: reciting additional elements in implementing the abstract idea that do not constitute significantly more than the abstract idea because they comprise or include well-understood, routine, and conventional activities previously known to the industry (e.g. all or portion(s) of the "autonomously transmitting, from the transaction … or more financial instruments", (insignificant extra-solution activity) steps), see Alice Corp., 134 S. Ct. at 2360, and/or that are otherwise not significant toward constituting any inventive concept beyond the abstract idea. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited steps.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: receiving or transmitting data over a network, e.g., using the Internet to gather data, Intellectual Ventures I v. Symantec Corp., 838 F.3d at 1321, 120 USPQ2d at 1362 (2016) (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). Independent claim 1 further does not specify any particular machine element(s) for the "generating labeled emotional-state training records … the first time period", "updating an emotional state machine … a group of users", and "generating control instructions based on … selected account-control action" steps and under the broadest reasonable interpretation, these steps may be manually performed by a human only which also does not add significantly more than the abstract idea. None of the additional elements taken individually or when taken as an ordered combination amount to significantly more than the abstract idea. Accordingly, independent claim 1 is ineligible. Claim 8: Materially pertaining to the analysis under Step 2A of the Office's § 101 Subject Matter Eligibility Test for Products and Processes, independent claim 8 further to the abstract idea includes additional elements of "apparatus", "autonomous decision making", "one or more processors", "one or more memories", "storing", "processor-executable code", "a transaction server", "the transaction server", "electronic", "one or more transaction servers", "machine learning model", "positioning system", and "autonomously transmit". However, independent claim 8 does not include additional elements that are sufficient to integrate the exception into a practical application because "apparatus", "autonomous decision making", "one or more processors", "one or more memories", "storing", "processor-executable code", "a transaction server", "the transaction server", "electronic", "one or more transaction servers", "machine learning model", "positioning system", and "autonomously transmit" of independent claim 8 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality that perform functions ("An apparatus for autonomous decision making, comprising", "one or more processors; and", "one or more memories coupled … cause the apparatus to", "generate, at a transaction server, … and historical transactional data", "track, at the transaction server … from the transaction server", "generate labeled emotional-state training records … the first time period", "update an emotional state machine … a group of users", "track, at the transaction server … activity of the user", "predict, via the updated emotional … the second financial activity", "predict, via a machine learning … the current emotional state", "select, via an action machine … account-control actions as outputs", "generate control instructions based on … selected account-control action; and" and "autonomously transmit, from the transaction … or more financial instruments") that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself (e.g. all or portion(s) of the noted recited steps) and/or that recite generic computer and/or field of use functions that are recited at a high-level of generality that include only steps narrowing the abstract idea [Step 2A Prong I] (e.g. all or portion(s) of the noted recited steps) and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, [Step 2A Prong II] adding the words "apply it" (or an equivalent) with the judicial exception, or 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) (all or portions of the "one or more processors; and", "one or more memories coupled … cause the apparatus to", "generate, at a transaction server, … and historical transactional data", "track, at the transaction server … from the transaction server", "update an emotional state machine … a group of users", "track, at the transaction server … activity of the user", "predict, via the updated emotional … the second financial activity", "predict, via a machine learning … the current emotional state", "select, via an action machine … account-control actions as outputs", "autonomously transmit, from the transaction … or more financial instruments" step(s)), and adding insignificant extra-solution activity to the judicial exception -- see MPEP 2106.05(g) (all or portions of the "one or more memories coupled … cause the apparatus to", "autonomously transmit, from the transaction … or more financial instruments" step(s)), and generally linking the use of the judicial exception to a particular technological environment or field of use -- see MPEP 2106.05(h) (all or portions of the noted step(s)). Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Moreover, the additional method steps comprise or include: reciting additional elements in implementing the abstract idea that do not constitute significantly more than the abstract idea because they comprise or include well-understood, routine, and conventional activities previously known to the industry (e.g. all or portion(s) of the "one or more memories coupled … cause the apparatus to", "autonomously transmit, from the transaction … or more financial instruments", (insignificant extra-solution activity) steps), see Alice Corp., 134 S. Ct. at 2360, and/or that are otherwise not significant toward constituting any inventive concept beyond the abstract idea. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited steps.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: receiving or transmitting data over a network, Intellectual Ventures I v. Symantec Corp., (2016); TLI Communications LLC v. AV Auto. LLC, (Fed. Cir. 2016); OIP Techs., Inc., v. Amazon.com, Inc., (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., (Fed. Cir. 2014), see previous legal citations herein Re: Claim 1, electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 134 S. Ct. at 2359, 110 USPQ2d at 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, Inc. v. Hulu, LLC, 772 F.3d at 716, 112 USPQ2d at 1755 (Fed. Cir. 2014) (updating an activity log), and storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d at 1363, 115 USPQ2d at 1092-93 (Fed. Cir. 2015). None of the additional elements taken individually or when taken as an ordered combination amount to significantly more than the abstract idea. Accordingly, independent claim 8 is ineligible. Claim 15: Specifically with respect to the analysis under Step 2A of the Office's § 101 Subject Matter Eligibility Test for Products and Processes, independent claim 15 further to the abstract idea includes additional elements of "non-transitory computer-readable medium", "program code", "autonomous decision making", "one or more processors", "a transaction server", "the transaction server", "electronic", "one or more transaction servers", "machine learning model", "positioning system", and "autonomously transmit". However, independent claim 15 does not include additional elements that are sufficient to integrate the exception into a practical application because "non-transitory computer-readable medium", "program code", "autonomous decision making", "one or more processors", "a transaction server", "the transaction server", "electronic", "one or more transaction servers", "machine learning model", "positioning system", and "autonomously transmit" of independent claim 15 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality that perform functions ("A non-transitory computer-readable medium having … more processors and comprising", "program code to generate, at … and historical transactional data", "program code to track, at … from the transaction server", "program code to generate labeled … the first time period", "program code to update an … a group of users", "program code to track, at … activity of the user", "program code to predict, via … the second financial activity", "program code to predict, via … the current emotional state", "program code to select, via … account-control actions as outputs", "program code to generate control … selected account-control action; and" and "program code to autonomously transmit, … or more financial instruments") that merely perform, conduct, carry out, implement, and/or narrow the abstract idea itself (e.g. all or portion(s) of the noted recited steps) and/or that recite generic computer and/or field of use functions that are recited at a high-level of generality that include only steps narrowing the abstract idea [Step 2A Prong I] (e.g. all or portion(s) of the noted recited steps) and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, [Step 2A Prong II] adding the words "apply it" (or an equivalent) with the judicial exception, or 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) (all or portions of the "A non-transitory computer-readable medium having … more processors and comprising", "program code to generate, at … and historical transactional data", "program code to track, at … from the transaction server", "program code to update an … a group of users", "program code to track, at … activity of the user", "program code to predict, via … the second financial activity", "program code to predict, via … the current emotional state", "program code to select, via … account-control actions as outputs", "program code to autonomously transmit, … or more financial instruments" step(s)), and adding insignificant extra-solution activity to the judicial exception -- see MPEP 2106.05(g) (all or portions of the "A non-transitory computer-readable medium having … more processors and comprising", "program code to autonomously transmit, … or more financial instruments" step(s)), and generally linking the use of the judicial exception to a particular technological environment or field of use -- see MPEP 2106.05(h) (all or portions of the noted step(s)). Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. Moreover, the additional method steps comprise or include: reciting additional elements in implementing the abstract idea that do not constitute significantly more than the abstract idea because they comprise or include well-understood, routine, and conventional activities previously known to the industry (e.g. all or portion(s) of the "A non-transitory computer-readable medium having … more processors and comprising", "program code to autonomously transmit, … or more financial instruments", (insignificant extra-solution activity) steps), see Alice Corp., 134 S. Ct. at 2360, and/or that are otherwise not significant toward constituting any inventive concept beyond the abstract idea. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited steps.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: receiving or transmitting data over a network, Intellectual Ventures I v. Symantec Corp., (2016); TLI Communications LLC v. AV Auto. LLC, (Fed. Cir. 2016); OIP Techs., Inc., v. Amazon.com, Inc., (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., (Fed. Cir. 2014), see previous legal citations herein Re: Claim 1, and electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, (2014); Ultramercial, Inc. v. Hulu, LLC, (Fed. Cir. 2014), see previous legal citations herein Re: Claim 8. None of the additional elements taken individually or when taken as an ordered combination amount to significantly more than the abstract idea. Accordingly, independent claim 15 is ineligible. Independent Claims: Nothing in independent claims 1, 8, and 15 improves another technology or technical field, improves the functioning of any claimed computer device itself, applies the abstract idea with any particular machine, solves any computer problem with a computer solution, or includes any element that may otherwise be considered to amount to significantly more than the abstract idea. None of the dependent claims 2-4, 7, 9-11, 14, 16-18, and 21-24 when separately considered with each dependent claim's corresponding parent claim overcomes the above analysis because none presents any method step not directed to the abstract idea that amounts to significantly more than the judicial exception or any physical structure that amounts to significantly more than the judicial exception. Claims 2, 9, and 16: Dependent claims 2, 9, and 16 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, "web interface" of dependent claims 2, 9, and 16 recite generic computer and/or field of use components pertaining to the particular technological environment that are recited a high-level of generality. No additional element introduced in these claims taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Claims 2, 9, and 16: Dependent claims 2, 9, and 16 add an additional method step of "wherein the personality profile is a financial personality profile that is generated in accordance with the questionnaire data via a web interface". However, the additional method step of dependent claim 2, 9, and 16 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 1 above. Regarding Step 2B, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not add more than insignificant extra-solution activity to the judicial exception, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited step.) For example regarding well-understood, routine, and conventional activities, the cited rationale have recognized the following computer function as well-understood, routine, and conventional functions when it is claimed or as insignificant extra-solution activity: a web browser's back and forward button functionality, Internet Patent Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015); and the cited rationale have found the following type of activity to be well-understood, routine, and conventional activity when it is claimed or as insignificant extra-solution activity: recording a customer's order, Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1244, 120 USPQ2d 1844, 1856 (Fed. Cir. 2016), and presenting offers and gathering statistics, OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93 (Fed. Cir. 2015), pertaining to all or portion(s) of the noted recited step. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claims 2, 9, and 16 are ineligible. Claim 3: Dependent claim 3 adds an additional method step of "updating the personality profile based on one or both of the first financial activity or the … profile used for predicting the one or more financial events is the updated personality profile". However, the additional method step of dependent claims 3 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited step) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, Regarding Step 2B, the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited step.) Dependent claim 3 further does not specify any particular machine element(s) for the "updating the personality profile based on one or both of the first financial activity or the … profile used for predicting the one or more financial events is the updated personality profile" step and under the broadest reasonable interpretation, this step may be manually performed by a human only which also does not add significantly more than the abstract idea. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 3 is ineligible. Claims 4, 11, and 18: Dependent claims 4, 11, and 18 add an additional method step of "wherein the user data comprises user content consumption habits, and/or user demographic information". However, the additional method step of dependent claim 4, 11, and 18 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 3 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 3 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited steps.) Dependent claims 4, 11, and 18 further do not specify any particular machine element(s) for the "wherein the user data comprises user content consumption habits, and/or user demographic information" step and under the broadest reasonable interpretation, this step may be manually performed by a human only which also does not add significantly more than the abstract idea. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claims 4, 11, and 18 are ineligible. Claims 7, 14, and 21: Dependent claims 7, 14, and 21 add additional method steps of "wherein the action machine learning model selects the account-control action using a reward function that quantifies … on improved savings rates, reduced debt, a success rate of interventions, and user satisfaction scores". However, the additional method steps of dependent claim 7, 14, and 21 are directed to the abstract idea noted above and do not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method steps merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrow the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method steps comprise or include: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, Regarding Step 2B, the additional elements do not amount to more than a recitation of the words "apply it" (or an equivalent) or are not more than mere instructions to implement an abstract idea or other exception on a computer, and the additional elements do not amount to more than generally linking the use of a judicial exception to a particular technological environment or field of use. (E.g. The above-italicized grounds of rejection apply at least to all or portion(s) of the noted recited steps.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claims 7, 14, and 21 are ineligible. Claim 10: Dependent claim 10 adds an additional method step of "execution of the processor-executable code further causes the apparatus to update the personality profile based on one or both of the first financial activity or the second financial activity; and", "the personality profile used for predicting the one or more financial events is the updated personality profile". However, the additional method step of dependent claims 10 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claims 7, 14, and 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claims 7, 14, and 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited steps.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 10 is ineligible. Claim 17: Dependent claim 17 adds an additional method step of "the program code further comprises program code to update the personality profile based on one or both of the first financial activity or the second financial activity; and", "the personality profile used for predicting the one or more financial events is the updated personality profile". However, the additional method step of dependent claims 17 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claims 7, 14, and 21 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claims 7, 14, and 21 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited steps.) No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claim 17 is ineligible. Claims 22, 23, and 24: Dependent claims 22, 23, and 24 add an additional method step of "wherein the one or more account parameters further comprise one or more of a savings rate, a contribution rate, or an investment strategy". However, the additional method step of dependent claim 22, 23, and 24 is directed to the abstract idea noted above and does not otherwise alter the analysis presented above, and do not integrate the exception into a practical application, because the additional method step merely perform, conduct, carry out, and/or implement the abstract idea itself and/or only narrows the abstract idea (e.g. all or portion(s) of the noted recited steps) and/or because the additional method step comprises or includes: evaluated additional elements individually and in combination for which the courts have identified examples in which a judicial exception has not been integrated into a practical application, as previously discussed regarding Claim 3 above. Regarding Step 2B treatment of the evaluated additional elements individually and in combination, the same previously-stated legal authority and/or rationale supporting the grounds of rejection applied to the above Claim 3 also applies hereto. (E.g. These previously-stated grounds of rejection that were italicized when applied to the referenced previous Claim(s) apply at least to all or portion(s) of the noted recited steps.) Dependent claims 22, 23, and 24 further do not specify any particular machine element(s) for the "wherein the one or more account parameters further comprise one or more of a savings rate, a contribution rate, or an investment strategy" step and under the broadest reasonable interpretation, this step may be manually performed by a human only which also does not add significantly more than the abstract idea. No additional step introduced in this claim taken individually or when taken as an ordered combination amounts to significantly more than the abstract idea. Accordingly, dependent claims 22, 23, and 24 are ineligible. PNG media_image1.png 930 645 media_image1.png Greyscale PNG media_image2.png 200 400 media_image2.png Greyscale §101 Subject Matter Eligibility Test for Products and Processes Response to Arguments Regarding eligibility rejections under 35 U.S.C. § 101, the Applicant's arguments submitted August 13, 2026 (hereinafter "REMARKS") in response to the Official Correspondence mailed May 21, 2026 (hereinafter "Final Correspondence") have been fully considered but are not persuasive. Further to the May 21, 2026 Final Correspondence, the reiterated grounds of rejection are fully set forth above under the 35 U.S.C. § 101 heading as applied to the herein examined current claims. • The Applicant argued: "[] Applicants respectfully traverse all rejections of all pending claims []. "Applicants respectfully traverse the rejection under 35 U.S.C. [sec.] 101. [] 'The Office Action further states that the claims recite "fundamental economic principles or practices include mitigating risks" [;] claim 8 recites predicting "one or more future financial risk events." Applicants respectfully disagree. "[C]laim 1 does not merely recite modifying account parameters or mitigating financial risk. [C]laim 1 recites a particular machine-learning control process that includes, among other things, [amended claim limitations]. The amended claim [] recites a specific sequence of machine-learning model updating, machine-learning prediction, machine-learning action selection, control-instruction generation, and remote transaction-server control. 'Under Step 2A, Prong One, the amended claims are not directed merely to "commercial or legal interactions (including sales activities or behaviors)" or "fundamental economic principles or practices include mitigating risks." "The Office Action's abstract-idea formulation omits the recited generation of labeled emotional-state training records, the fine-tuning of one or more model parameters using those labeled emotional-state training records, the later use of the updated emotional state machine learning model, the selection of an account-control action by an action machine learning model trained using action-outcome records, and the generation and transmission of control instructions to one or more remote transaction servers. These limitations define how the claimed machine-learning system processes electronic transaction data, user-reported feedback, location data, model parameters, action-outcome records, and control instructions across time. These limitations do not merely state a result. These limitations recite the technical mechanism that produces the claimed result. "The mere mention of a financial event does not mean that the claim is directed to a fundamental economic principle. The Office Action improperly isolates selected financial context limitations from the claim and does not consider the claim as a whole. When considered as a whole, claim 1 is directed to fine-tuning machine learning models and using the fine-tuned machine learning models to generate control instructions that modify account parameters through remote transaction-server control. [T]he claimed subject matter is not directed merely to a financial objective. [T]he claim recites a particular machine-learning control process that uses labeled emotional-state training records, updated model parameters, a machine leaming model, an action machine learning model, and generated control instructions to perform the recited transaction-server operations. 'The amended claims also do not merely recite a result-oriented instruction to apply a financial concept on a computer. Claim 1 recites that the emotional state machine learning model is updated "by fine-tuning one or more model parameters using the labeled emotional-state training records." 'Claim 1 further recites that the updated model predicts a current emotional state "at a second time period." '[C]laim 1 recites a first time period for generating labeled emotional-state training records, an update to model parameters using those records, and a second time period at which the updated model predicts a current emotional state. Claim 1 also recites a distinct action machine learning model "having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs." "The claim [] recites a multi-model architecture in which one model updates emotional-state prediction using labeled emotional-state training records and another model selects an account-control action using action-outcome records. '[T]he August 4, 2025 USPTO Memorandum titled "Guidance on Patent Subject Matter Eligibility in View of Recentive Analytics, Inc. v. Fox Corp." clarifies that the holding in Recentive Analytics does not categorically render all claims reciting machine learning patent ineligible. The Memorandum instructs that claims reciting machine learning may be patent eligible where the claims recite details about how the machine learning model operates, what inputs the model receives, and what outputs the model produces. "[A]mended claim 1 recites specific inputs to the machine learning models, including first financial activity, user-reported feedback regarding an emotional state, second financial activity, user location data tracked via a positioning system, a personality profile, user data, and a current emotional state. "Amended claim 1 also recites specific intermediate operations, including generating labeled emotional-state training records, fine tuning one or more model parameters of an emotional state machine learning model using the labeled emotional-state training records, predicting a current emotional state via the updated emotional state machine learning model, predicting one or more future financial events via a machine learning model, and selecting an account-control action via an action machine learning model trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs. "Amended claim 1 further recites specific outputs, including a current emotional state, one or more future financial events, an account-control action, and control instructions that the transaction server autonomously transmits to one or more transaction servers to modify one or more account parameters. "These recitations go beyond the mere invocation of generic machine learning and instead define a specific technical pipeline with defined inputs, processing, and outputs. "Even assuming arguendo that the amended claims recite a judicial exception under Step 2A, Prong One, the amended claims integrate any alleged exception into a practical application under Step 2A, Prong Two. 'The Office Action alleges: "This judicial exception is not integrated into a practical application because the additional elements include: An apparatus [...], comprising: one or more processors, and one or more memories coupled with the one or more processors and storing processor-executable code that, when executed by the one or more processors, is configured to cause the apparatus to [...] 'autonomously transmit'; a transaction server, one or more transaction servers remotely located from the transaction server; via a positioning system, transmit from the transaction server to the one or more transaction servers, and a positioning system." The Office Action further states: "Thus, the additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the abstract idea using generic computer and computer networking components or amount to merely using a computer as a tool to perform the abstract idea." Applicants respectfully disagree at least in view of the amendments. "The amended claims integrate any alleged exception into a practical application because claim 1 recites a specific technical pipeline that changes the operation of the emotional state machine learning model itself. 'Claim 1 recites "generating labeled emotional-state training records" and "updating an emotional state machine learning model by fine-tuning one or more model parameters using the labeled emotional-state training records." The claim [] does not merely use a model as a black box. [T]he claim recites generating training records from correlated electronic financial activity and user-reported emotional feedback, followed by fine-tuning of model parameters using those records. 'Paragraph [0101] of the specification states: "During the training phase, the model learns to recognize patterns associated with different emotional states, mapping input features to corresponding emotional labels. In the validation phase, the model's performance is evaluated on a Separate set to fine-tune parameters and avoid overfitting." This is a practical application because the claim uses particular training records to alter the model parameters that govern later emotional-state prediction. 'The amended claims further integrate any alleged exception into a practical application because claim 1 applies the updated emotional state machine learning model at a later time period to data from a positioning system and second financial activity. Claim 1 recites "predicting, via the updated emotional state machine learning model at a second time period, a current emotional state of the user based on user location data tracked via a positioning system and the second financial activity." 'Paragraph [0030] states: "The user's activities may be derived from spending activity and/or physical location. For example, the user's location may be tracked via a device, such as a mobile phone. The user's activity may be determined based on the location tracking." 'Paragraph [0078] states: "The location information may be derived via positioning information, such as GPS data." The amended claim [] uses location data from a positioning system as part of the input to the updated emotional state machine learning model, not as insignificant extra-solution activity. 'The amended claims further integrate any alleged exception into a practical application because claim 1 recites generating and transmitting control instructions from a transaction server to one or more remote transaction servers. Claim 1 recites "generating control instructions based on the selected account-control action" and "autonomously transmitting, from the transaction server to the one or more transaction servers, the control instructions to modify one or more account parameters associated with one or more future financial accounts of the user." 'Paragraph [0086] states: "The one or more actions may be performed based on communications between the system associated with the decision making process 300 and one or more financial institutions or platforms that have been linked with the system. For example, the system associated with the decision making process 300 may have permission from the one or more financial institutions or platforms and/or the user to autonomously perform the one or more actions. Additionally, or alternatively, the system may include a feature to cue one or more actions to respective financial institutions or platforms, such that the respective financial institutions or platforms perform the one or more actions." Thus, the claim does not merely display advice or provide information. The claim recites control instructions that cause remote transaction-server action with respect to account parameters. 'The amended claims further integrate any alleged exception into a practical application because claim 1 recites a particular action machine learning model trained using action-outcome records. Claim 1 recites "selecting, via an action machine learning model, an account-control action based on the one or more future financial events and the current emotional state, the action machine learning model having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs." 'Paragraph [0096] states: "The action model may be trained using supervised learning techniques with historical data where actions were previously taken and their outcomes. Labeled datasets may be created with financial and behavioral features as inputs and actions taken as outputs." 'Paragraph [0106] states: "Key performance metrics may be continuously evaluated to assess the model's effectiveness. These metrics may include the accuracy of spending predictions, the success rate of interventions (e.g., how often blocking a card prevented financial strain), user satisfaction scores, and overall improvements in financial health (e.g., reduced debt, increased savings)." These disclosures correspond to the amended claim language and show that the amended claims recite a trained action-selection model, not a generic instruction to perform a financial act. "[] The amended claims[] now recite more than processor and memory components. The amended claims recite a specific ordered combination of operations involving labeled emotional-state training records, fine-tuning of model parameters, a later prediction via the updated emotional state machine learning model, a separate machine learning model, a separate action machine learning model trained using action-outcome records, generation of control instructions based on the selected account-control action, and autonomous transmission of those control instructions to remote transaction servers. 'The amended claims satisfy Step 2A, Prong Two because the claim recites a specific improvement to the operation of the machine-learning system. Paragraph [0102] states: "Realtime feedback from users is incorporated to refine predictions, and periodic retraining with new data ensures the model adapts to changing user behaviors and external conditions." Paragraph [0105] states: "once the machine learning models for determining an emotional state, determining or updating a user's personality profile, predicting future events, and/or taking actions are deployed, they can be continuously updated based on real-world results to maintain their accuracy and relevance." Paragraph [0107] states: "New data may be incorporated into the training sets to ensure the models adapt to changing user behaviors and financial patterns." These passages describe the claimed model-update framework. The amended claims recite that framework by requiring labeled emotional-state training records, fine-tuning of model parameters, and later prediction via the updated emotional state machine learning model. "The amended claims also satisfy Step 2A, Prong Two because the claim recites a particular machine implementation. Claim 1 recites a transaction server, one or more transaction servers remotely located from the transaction server, electronic transaction data received from the one or more remotely located transaction servers, user location data tracked via a positioning system, an updated emotional state machine learning model, a financial machine learning model, an action machine learning model, generated control instructions, and autonomous transmission of the control instructions to the one or more remote transaction servers. These limitations tie the claimed process to a particular networked transaction-server architecture and a particular machine-learning control pipeline. "The amended claims also satisfy Step 2A, Prong Two because the claim recites a transformation of information and machine state. Claim 1 transforms electronic transaction data and user-reported feedback into labeled emotional-state training records. Claim 1 then uses the labeled emotional-state training records to fine-tune one or more model parameters of an emotional state machine learning model. Claim 1 then uses the updated model to predict a current emotional state at a later time period. Claim 1 then uses a machine learning model to predict one or more future financial events. Claim 1 then uses an action machine learning model to select an account-control action. Claim 1 then transforms the selected account-control action into control instructions. Claim 1 then transmits the control instructions to remote transaction servers to modify account parameters. These recitations impose meaningful limits and integrate any alleged exception into a practical application. "The amended claims also satisfy Step 2A, Prong Two under the reasoning of DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245 (Fed. Cir. 2014), Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016), and McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299 (Fed. Cir. 2016). [T]he amended claims recite a particular networked transaction-server environment, a particular model-update process using labeled emotional-state training records, and particular machine-learning action-selection logic that produces control instructions for remote transaction servers. The amended claims therefore do not merely invoke computers as tools to perform an abstract idea. '[T]he amended claims specify what the machine learning models receive, including first financial activity, user-reported feedback regarding an emotional state, second financial activity, user location data tracked via a positioning system, a personality profile, user data, a current emotional state, and action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs. The amended claims also specify what the machine learning models determine, including labeled emotional -state training records, fine-tuned model parameters, a current emotional state, one or more future financial events, and an account-control action. The amended claims further specify what the machine learning models generate, including control instructions based on the selected account-control action. These recitations impose meaningful limits on the claims and are not equivalent to the words "apply it." "The amended claims further satisfy Step 2B. Even if the claims were considered directed to a judicial exception under Step 2A, the claims recite significantly more than the alleged exception[ u]nder Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018)[]. 'The Office Action alleges: "The claim does not include additional elements, individually and in combination, that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using generic computer components or merely using a computer as a tool to perform the abstract ideas amount to no more than mere instructions to apply the exception using generic computer and computer network components." The Office Action further alleges: "Mere instructions to apply an exception using generic computer components cannot provide an inventive concept." Applicants respectfully disagree. "The Office Action does not provide evidence that the amended ordered combination was well-understood, routine, and conventional. [T]he Office Action does not show that it was well-understood, routine, and conventional to fine-tune an emotional state machine learning model, use the updated model with positioning-system data and second financial activity, select an account-control action via an action machine learning model trained using action-outcome records, and generate and transmit control instructions to remote transaction servers to modify account parameters. The Office Action's citation to generic processor and memory disclosures does not establish that this ordered combination was well-understood, routine, and conventional. 'The amended claims recite an inventive concept at least because the claims recite a nongeneric ordered combination of machine-learning operations that produces a concrete machine-control output. Claim 1 does not merely recite "use machine learning." Claim 1 recites specific training-record generation, parameter fine-tuning, later model use, action-model selection based on action-outcome training records, control-instruction generation, and transmission of control instructions to remote transaction servers. The ordered combination improves the way the claimed system updates emotional-state prediction and selects account-control actions. Paragraph [0102] states: "Real-time feedback from users is incorporated to refine predictions, and periodic retraining with new data ensures the model adapts to changing user behaviors and external conditions." Paragraph [0106] states: "Key performance metrics may be continuously evaluated to assess the model's effectiveness. These metrics may include the accuracy of spending predictions, the success rate of interventions (e.g., how often blocking a card prevented financial strain), user satisfaction scores, and overall improvements in financial health (e.g., reduced debt, increased savings)." These disclosures provide record support for the non-generic model-update and action-selection pipeline recited in the amended claims. "The amended claims also do not preempt all ways of modifying financial accounts, all ways of predicting financial risk, or all uses of machine learning in financial systems. Claim 1 recites a specific ordered combination that uses labeled emotional-state training records, fine-tuned emotional-state model parameters, a later prediction via the updated emotional state machine learning model, a separate machine learning model, a separate action machine learning model trained using action-outcome records, control-instruction generation, and autonomous transmission of the control instructions to remote transaction servers. Many other systems may predict risk or modify accounts without this claimed ordered combination. The limited scope of the amended claims further confirms that the claims recite significantly more than the alleged abstract idea. '[C]laim 1 is patent-eligible under Step 2A, Prong One, because the claim does not merely recite "commercial or legal interactions (including sales activities or behaviors)" or "fundamental economic principles or practices include mitigating risks." [C]laim 1 is patent-eligible under Step 2A, Prong Two, because the claim integrates any alleged exception into a practical application. [C]laim 1 is patent-eligible under Step 2B, because the claim recites significantly more than any alleged exception and the Office Action provides no evidence that the amended ordered combination was well-understood, routine, and conventional. "Independent claims 8 and 15 recite limitations corresponding to claim 1 and are patent-eligible for at least the same reasons. Dependent claims 2-4, 7, 9-11, 14, 16-18, and 21 are patent-eligible at least by virtue of their dependence from a patent-eligible independent claim and for the additional limitations recited therein. Accordingly, Applicants respectfully request withdrawal of the rejection of claims 1-4, 7-11, 14-18, and 21 under 35 U.S.C. [sec.] 101." (REMARKS [as abridged], pp. 9-20). Notwithstanding respectively the foregoing, the above-quoted arguments submitted August 13, 2026 at REMARKS pp. 9-20 regarding rejections under 35 U.S.C. § 101 have been fully considered, but are not persuasive. Materially, the Office respectfully disagrees with the Applicant's above-quoted factual allegations and legal conclusion. '[T]he "invention" is what is claimed'. Zoltek Corp. v. United States, 672 F.3d 1309, 1318, 102 USPQ2d 1001, 1008 (Fed. Cir. 2012). The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. See MPEP 2106(b)(I): "[a] general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine." Ultramercial, Inc. v. Hulu, LLC, 772, F.3d 709, 716-17, 112 USPQ2d 1750, 1755-56 (Fed. Cir. 2014). Questions of preemption are inherently addressed within the two-part framework from Alice Corp. and Mayo (incorporated into the above depicted § 101 Subject Matter Eligibility Test for Products and Processes as Steps 2A and 2B), and are resolved using this framework to identify preemptive claims. While a preemptive claim may be ineligible, the absence of complete preemption does not establish that a claim is eligible. Contrary to the Applicant's above-quoted assertions, the Applicant's alleged invention as delineated by the currently pending claims appears to be deeply rooted in the abstract idea. Contrary to the Applicant's above-quoted assertions, the Applicant's alleged invention as delineated by the currently pending claims appears to be deeply rooted in the abstract idea. The Applicant's claims do not purport to improve the functioning of the computer itself, or to improve any other technology or technical field, rather "the focus of the claims is not on [] an improvement in computers as tools, but on certain independently abstract ideas that use computers as tools." Electric Power Group, LLC, v. Alstom, 830 F.3d 1350, 1354, 119 U.S.P.Q.2d 1739, 1742 (Fed. Cir. 2016). The Federal Circuit has held that "communicating requests to a remote server and receiving communications from that server, i.e., communication over a network" is itself an abstract idea. See ChargePoint, Inc. v. SemaConnect, Inc., 2019 U.S.P.Q.2d at 108516: "It is clear from the language of claim 1 that the claim involves an abstract idea--namely, the abstract idea of communicating requests to a remote server and receiving communications from that server, i.e., communication over a network. [] We therefore continue our analysis to determine whether the focus of claim 1, as a whole, is the abstract idea. As explained below, we conclude that it is." ChargePoint, Inc. v. SemaConnect, Inc., 2019 U.S.P.Q.2d 108512 (Fed. Cir. 2019). In response to Applicant's argument that the claimed subject matter provides any improvement to any technology or technical field, the alleged improvement(s) in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. Example(s) that the courts have indicated may not be sufficient to show an improvement in computer-functionality: ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016); iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential); Examples that the courts have indicated may not be sufficient to show an improvement to technology include: i. A commonplace business method being applied on a general purpose computer, Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); iii. Gathering and analyzing information using conventional techniques and displaying the result, TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48; See Alice Corp., 134 S. Ct. at 2358: 'Stating an abstract idea "while adding the words 'apply it'" is not enough for patent eligibility. Mayo, supra, at ___, 132 S. Ct. 1289, 182 L. Ed. 2d 321, 325. Nor is limiting the use of an abstract idea "'to a particular technological environment.'" Bilski, supra, at 610-611, 130 S. Ct. 3218, 177 L. Ed. 2d 792.' Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011). For Step 2B, relying on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine and conventional, the claims in the present application are ineligible under Step 2B. For example, the courts have recognized the following computer functions to be well-understood, routine, and conventional functions when they are claimed in a merely generic manner: performing repetitive calculations, receiving, processing, and storing data, electronically scanning or extracting data from a physical document, electronic recordkeeping, automating mental tasks, and receiving or transmitting data over a network, e.g., using the Internet to gather data. Courts have held computer-implemented processes not to be significantly more than an abstract idea (and thus ineligible) where the claim as a whole amounts to nothing more than generic computer functions merely used to implement an abstract idea, such as an idea that could be done by a human analog (i.e., by hand or by merely thinking). The certain methods of organizing human activity abstract idea grouping include concepts relating to: fundamental economic principles or practices (including, e.g., hedging, insurance, mitigating risk); commercial or legal interactions (including, e.g., agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations); and managing personal behavior or relationships or interactions between people, (including, e.g., social activities, teaching, and following rules or instructions). See MPEP 2106.04(a)(2)(II). "Certain methods of organizing human activity" encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer (for example a method of anonymous loan shopping that a person conducts using a mobile phone) may fall within the "certain methods of organizing human activity" grouping. It is noted that the number of people involved in the activity is not dispositive as to whether a claim limitation falls within this grouping. See MPEP 2106.04(a)(2)(II). The courts have used the phrases "fundamental economic practices" or "fundamental economic principles" to describe concepts relating to the economy and commerce. Fundamental economic principles or practices include hedging, insurance, and mitigating risks. See MPEP 2106.04(a)(2)(II)(A). Examples of "fundamental economic principles or practices" include: hedging or protecting against risk, Bilski v. Kappos, 561 U.S. 593, 609, 95 USPQ2d 1001, 1009 (2010); managing a stable value protected life insurance policy, [and then instruct the use of well-known calculations to help establish some of the inputs into the equation]; e.g., managing a life insurance policy on behalf of a policy holder, which comprised steps including generating a life insurance policy including a stable value protected investment with an initial value based on a value of underlying securities, calculating surrender value protected investment credits for the life insurance policy; determining an investment value and a value of the underlying securities for the current day; and calculating a policy value and a policy unit value for the current day, Bancorp Services., L.L.C. v. Sun Life Assurance Co. of Canada (U.S.), 687 F.3d 1266, 103 USPQ2d 1425 (Fed. Cir. 2012); mitigating settlement risk, Alice Corp. v. CLS Bank,573 U.S. 208, 218, 110 USPQ2d 1976, 1982 (2014); rules for conducting a wagering game, In re Smith, 815 F.3d 816, 818-19, 118 USPQ2d 1245, 1247 (Fed. Cir. 2016); financial instruments that are designed to protect against the risk of investing in financial instruments, In re Chorna, 656 Fed. App'x 1016, 1021 (Fed. Cir. 2016) (non-precedential); offer-based price optimization, OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1362GÇô63, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015); local processing of payments for remotely purchased goods, Inventor Holdings, LLC v. Bed Bath Beyond, 876 F.3d 1372, 1378-79, 125 USPQ2d 1019, 1023 (Fed. Cir. 2017); using a marking affixed to the outside of a mail object to communicate information about the mail object, i.e., the sender, recipient, and contents of the mail object, Secured Mail Solutions LLC v. Universal Wilde, Inc., 873 F.3d 905, 911, 124 USPQ2d 1502, 1506 (Fed. Cir. 2017); and placing an order based on displayed market information, Trading Technologies Int'l, Inc. v. IBG LLC, 921 F.3d 1084, 1092, 2019 USPQ2d 138290 (Fed. Cir. 2019). See MPEP 2106.04(a)(2)(II)(A). "Commercial interactions" or "legal interactions" include agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations. See MPEP 2106.04(a)(2)(II)(B). Examples of subject matter where the commercial or legal interaction is an agreement in the form of contracts include: a transaction performance guaranty, e.g. a method in which a computer operated by the provider of a safe transaction service receives a request for a performance guarantee for an online commercial transaction, the computer processes the request by underwriting the requesting party in order to provide the transaction guarantee service, and the computer offers, via a computer network, a transaction guaranty that binds to the transaction upon the closing of the transaction, buySAFE, Inc. v. Google, Inc., 765 F.3d. 1350, 112 USPQ2d 1093 (Fed. Cir. 2014); managing a stable value protected life insurance policy via performing calculations, Bancorp Servs., LLC v. Sun Life Assur. Co. of Canada (U.S.), 687 F.3d 1266, 1280, 103 USPQ2d 1425, 1434 (Fed. Cir. 2012); and processing insurance claims for a covered loss or policy event under an insurance policy (i.e., an agreement in the form of a contract), Accenture Global Services v. Guidewire Software, Inc., 728 F.3d 1336, 1338-39, 108 USPQ2d 1173, 1175-76 (Fed. Cir. 2013). Examples of subject matter where the commercial or legal interaction is a legal obligation include: real estate investment tool designed to enable tax-free exchanges, e.g. aggregating real property into a real estate portfolio, dividing the interests in the portfolio into a number of deedshares, and subjecting those shares to a master agreement, Fort Properties, Inc. v. American Master Lease, LLC, 671 F.3d 1317, 101 USPQ2d 1785 (Fed Cir. 2012); hedging, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010); mitigating settlement risk, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 218, 110 USPQ2d 1976, 1979 (2014); and arbitration, In re Comiskey, 554 F.3d 967, 981, 89 USPQ2d 1655, 1665 (Fed. Cir. 2009). Examples of subject matter where the commercial or legal interaction is advertising, marketing or sales activities or behaviors include: using advertising as an exchange or currency, e.g. displaying an advertisement (ad) in exchange for access to copyrighted media, comprising steps of receiving copyrighted media, selecting an ad, offering the media in exchange for watching the selected ad, displaying the ad, allowing the consumer access to the media, and receiving payment from the sponsor of the ad, Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 714-15, 112 USPQ2d 1750, 1753-54 (Fed. Cir. 2014); structuring a sales force or marketing company, which pertains to marketing or sales activities or behaviors, In re Ferguson, 558 F.3d 1359, 1364, 90 USPQ2d 1035, 1038 (Fed. Cir. 2009); using an algorithm for determining the optimal number of visits by a business representative to a client, In re Maucorps, 609 F.2d 481, 485, 203 USPQ 812, 816 (CCPA 1979); and offer-based price optimization, which pertains to marketing, OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1362-63, 115 USPQ2d 1090, 1092 (Fed. Cir. 2015). Examples of subject matter where the commercial or legal interaction is business relations includes: processing an application for financing a loan, e.g. maintaining a database of information about the items in a dealer's inventory, obtaining financial information about a customer from a user, combining these two sources of information to create a financing package for each of the inventoried items, and presenting the financing packages to the user, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 123 USPQ2d 1100 (Fed. Cir. 2017); processing information through a clearing-house, where the business relation is the relationship between a party submitted a credit application (e.g., a car dealer) and funding sources (e.g., banks) when processing credit applications, Dealertrack v. Huber, 674 F.3d 1315, 1331, 101 USPQ2d 1325, 1339 (Fed. Cir. 2012). See MPEP 2106.04(a)(2)(II)(B). "Managing personal behavior or relationships or interactions between people" include social activities, teaching, and following rules or instructions. See MPEP 2106.04(a)(2)(II)(C). Examples of managing personal behavior recited in a claim include: tracking financial transactions to determine whether they exceed a pre-set spending limit (i.e., budgeting), e.g. storing user-selected pre-set limits on spending in a database, and when one of the limits is reached, communicating a notification to the user via a device, Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 115 USPQ2d 1636 (Fed. Cir. 2015); filtering content, BASCOM Global Internet v. AT&T Mobility, LLC, 827 F.3d 1341, 1345-46, 119 USPQ2d 1236, 1239 (Fed. Cir. 2016) (finding that filtering content was an abstract idea under step 2A, but reversing an invalidity judgment of ineligibility due to an inadequate step 2B analysis); considering historical usage information while inputting data, BSG Tech. LLC v. Buyseasons, Inc., 899 F.3d 1281, 1286, 127 USPQ2d 1688, 1691 (Fed. Cir. 2018); and a mental process that a neurologist should follow when testing a patient for nervous system malfunctions, In re Meyer, 688 F.2d 789, 791-93, 215 USPQ 193, 194-96 (CCPA 1982). Example of a claim reciting social activities include: voting, verifying the vote, and submitting the vote for tabulation, e.g. presenting an election ballot for voting, accepting input of the votes, storing the votes, printing out the votes, comparing the printed votes to votes stored in the computer, and determining whether the printed ballot is acceptable, Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 126 USPQ2d 1498 (Fed. Cir. 2018); providing information to a person without interfering with the person's primary activity, e.g. providing someone an additional set of information without disrupting the ongoing provision of an initial set of information, (passing a note to a person who is in the middle of a meeting or conversation), or an attention manager for acquiring content from an information source, controlling the timing of the display of acquired content, displaying the content, and acquiring an updated version of the previously-acquired content when the information source updates its content, Interval Licensing LLC, v. AOL, Inc., 896 F.3d 1335, 127 USPQ2d 1553 (Fed. Cir. 2018). Examples of following rules or instructions recited in a claim include: rules for playing games, e.g. a method of playing a dice game including placing wagers on whether certain die faces will appear face up, In re Marco Guldenaar Holding B.V., 911 F.3d 1157, 1161, 129 USPQ2d 1008, 1011 (Fed. Cir. 2018); assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010). See MPEP 2106.04(a)(2)(II)(C). Regarding the mental processes abstract idea grouping, the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1139, 120 USPQ2d 1473, 1474 (Fed. Cir. 2016) (holding that claims to a mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper"). Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, "[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person's mind." Versata Dev. Group v. SAP Am., Inc., 793 F.3d 1306, 1335, 115 USPQ2d 1681, 1702 (Fed. Cir. 2015). See also Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1318, 120 USPQ2d 1353, 1360 (Fed. Cir. 2016) ("[W]ith the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper."); Mortgage Grader, Inc. v. First Choice Loan Servs. Inc., 811 F.3d 1314, 1324, 117 USPQ2d 1693, 1699 (Fed. Cir. 2016) (holding that computer-implemented method for "anonymous loan shopping" was an abstract idea because it could be "performed by humans without a computer"). See MPEP 2106.04(a)(2)(III). Claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include: a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016); claims to "comparing BRCA sequences and determining the existence of alterations," where the claims cover any way of comparing BRCA sequences such that the comparison steps can practically be performed in the human mind, University of Utah Research Foundation v. Ambry Genetics, 774 F.3d 755, 763, 113 USPQ2d 1241, 1246 (Fed. Cir. 2014); a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind, Classen Immunotherapies, Inc. v. Biogen IDEC, 659 F.3d 1057, 1067, 100 USPQ2d 1492, 1500 (Fed. Cir. 2011); and a claim to identifying head shape and applying hair designs, which is a process that can be practically performed in the human mind, In re Brown, 645 Fed. App'x 1014, 1016-17 (Fed. Cir. 2016) (non-precedential). See MPEP 2106.04(a)(2)(III)(A). A Claim that encompasses a human performing the step(s) mentally with or without a physical aid recites a mental process. If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping, and the claim recites an abstract idea. See, e.g., Benson, 409 U.S. at 67, 65, 175 USPQ at 674-75, 674 (noting that the claimed "conversion of [binary-coded decimal] numerals to pure binary numerals can be done mentally," i.e., "as a person would do it by head and hand."); Synopsys, 839 F.3d at 1139, 120 USPQ2d at 1474 (holding that claims to the mental process of "translating a functional description of a logic circuit into a hardware component description of the logic circuit" are directed to an abstract idea, because the claims "read on an individual performing the claimed steps mentally or with pencil and paper"). The use of a physical aid (e.g., pencil and paper or a slide rule) to help perform a mental step (e.g., a mathematical calculation) does not negate the mental nature of the limitation, but simply accounts for variations in memory capacity from one person to another. For instance, in CyberSource, the court determined that the step of "constructing a map of credit card numbers" was a limitation that was able to be performed "by writing down a list of credit card transactions made from a particular IP address." In making this determination, the court looked to the specification, which explained that the claimed map was nothing more than a listing of several (e.g., four) credit card transactions. The court concluded that this step was able to be performed mentally with a pen and paper, and therefore, it qualified as a mental process. 654 F.3d at 1372-73, 99 USPQ2d at 1695. See also Flook, 437 U.S. at 586, 198 USPQ at 196 (claimed "computations can be made by pencil and paper calculations"); University of Florida Research Foundation, Inc. v. General Electric Co., 916 F.3d 1363, 1367, 129 USPQ2d 1409, 1411-12 (Fed. Cir. 2019) (relying on specification's description of the claimed analysis and manipulation of data as being performed mentally "'using pen and paper methodologies, such as flowsheets and patient charts'"); Symantec, 838 F.3d at 1318, 120 USPQ2d at 1360 (although claimed as computer-implemented, steps of screening messages can be "performed by a human, mentally or with pen and paper"). See MPEP 2106.04(a)(2)(III)(B). Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer's shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer"). For instance, if the claimed invention is described as a concept that is performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer, or 2) in a computer environment, or 3) is merely using a computer as a tool to perform the concept, the claim is considered to recite a mental process. See MPEP 2106.04(a)(2)(III)(C). An example of a case identifying a mental process performed on a generic computer as an abstract idea is Voter Verified, Inc. v. Election Systems & Software, LLC, 887 F.3d 1376, 1385, 126 USPQ2d 1498, 1504 (Fed. Cir. 2018). In this case, the Federal Circuit relied upon the specification in explaining that the claimed steps of voting, verifying the vote, and submitting the vote for tabulation are "human cognitive actions" that humans have performed for hundreds of years. The claims therefore recited an abstract idea, despite the fact that the claimed voting steps were performed on a computer. 887 F.3d at 1385, 126 USPQ2d at 1504. Another example is Versata, in which the patentee claimed a system and method for determining a price of a product offered to a purchasing organization that was implemented using general purpose computer hardware. 793 F.3d at 1312-13, 1331, 115 USPQ2d at 1685, 1699. The Federal Circuit acknowledged that the claims were performed on a generic computer, but still described the claims as "directed to the abstract idea of determining a price, using organizational and product group hierarchies, in the same way that the claims in Alice were directed to the abstract idea of intermediated settlement, and the claims in Bilski were directed to the abstract idea of risk hedging." 793 F.3d at 1333; 115 USPQ2d at 1700-01. See MPEP 2106.04(a)(2)(III)(C)(1). An example of a case identifying a mental process performed in a computer environment as an abstract idea is Symantec Corp., 838 F.3d at 1316-18, 120 USPQ2d at 1360. In this case, the Federal Circuit relied upon the specification when explaining that the claimed electronic post office, which recited limitations describing how the system would receive, screen and distribute email on a computer network, was analogous to how a person decides whether to read or dispose of a particular piece of mail and that "with the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper". 838 F.3d at 1318, 120 USPQ2d at 1360. Another example is FairWarning IP, LLC v. Iatric Sys., Inc., 839 F.3d 1089, 120 USPQ2d 1293 (Fed. Cir. 2016). The patentee in FairWarning claimed a system and method of detecting fraud and/or misuse in a computer environment, in which information regarding accesses of a patient's personal health information was analyzed according to one of several rules (i.e., related to accesses in excess of a specific volume, accesses during a pre-determined time interval, or accesses by a specific user) to determine if the activity indicates improper access. 839 F.3d. at 1092, 120 USPQ2d at 1294. The court determined that these claims were directed to a mental process of detecting misuse, and that the claimed rules here were "the same questions (though perhaps phrased with different words) that humans in analogous situations detecting fraud have asked for decades, if not centuries." 839 F.3d. at 1094-95, 120 USPQ2d at 1296. See MPEP 2106.04(a)(2)(III)(C)(2). An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The interface prompts a borrower to enter personal information, which the grading module uses to calculate the borrower's credit grading, and allows the borrower to identify and compare loan packages in the database using the credit grading. 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of "anonymous loan shopping", which was a concept that could be "performed by humans without a computer." 811 F.3d. at 1324, 117 USPQ2d at 1699. Another example is Berkheimer v. HP, Inc., 881 F.3d 1360, 125 USPQ2d 1649 (Fed. Cir. 2018), in which the patentee claimed methods for parsing and evaluating data using a computer processing system. The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53. See MPEP 2106.04(a)(2)(III)(C)(3). Both product claims (e.g., computer system, computer-readable medium, etc.) and process claims may recite mental processes. For example, in Mortgage Grader, the patentee claimed a computer-implemented system and a method for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. The Federal Circuit determined that both the computer-implemented system and method claims were directed to "anonymous loan shopping", which was an abstract idea because it could be "performed by humans without a computer." 811 F.3d. at 1318, 1324-25, 117 USPQ2d at 1695, 1699-1700. See also FairWarning IP, 839 F.3d at 1092, 120 USPQ2d at 1294 (identifying both system and process claims for detecting improper access of a patient's protected health information in a health-care system computer environment as directed to abstract idea of detecting fraud); Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 1345, 113 USPQ2d 1354, 1356 (Fed. Cir. 2014) (system and method claims of inputting information from a hard copy document into a computer program). Accordingly, the phrase "mental processes" should be understood as referring to the type of abstract idea, and not to the statutory category of the claim. Examples of product claims reciting mental processes include: An application program interface for extracting and processing information from a diversity of types of hard copy documents - Content Extraction, 776 F.3d at 1345, 113 USPQ2d at 1356; A computer-implemented system for enabling anonymous loan shopping - Mortgage Grader, 811 F.3d at 1318, 117 USPQ2d at 1695; A computer readable medium containing program instructions for detecting fraud - CyberSource, 654 F.3d at 1368 n. 1, 99 USPQ2d at 1692 n.1; A post office for receiving and redistributing email messages on a computer network - Symantec, 838 F.3d at 1316, 120 USPQ2d at 1359; A self-verifying voting system - Voter Verified, 887 F.3d at 1384-85, 126 USPQ2d at 1504; A wide-area real-time performance monitoring system for monitoring and assessing dynamic stability of an electric power grid - Electric Power Group, 830 F.3d at 1351 and n.1, 119 USPQ2d at 1740 and n.1; and Computer readable storage media comprising computer instructions to implement a method for determining a price of a product offered to a purchasing organization - Versata, 793 F.3d at 1312-13, 115 USPQ2d at 1685. See MPEP 2106.04(a)(2)(III)(D). With respect to the DDR Holdings v. Hotels.com court decision cited by the Applicant, the Office determines that the legal holdings of DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 113 U.S.P.Q.2d 1097 (Fed. Cir. 2014), when applied to the facts pertaining to the Applicant's claims, do not support the eligibility of Applicant's claims under Step 2A or 2B of the above-depicted § 101 Subject Matter Eligibility Test for Products and Processes flowchart. In taking into consideration the particular facts and the particular holdings of DDR Holdings v. Hotels.com in the Applicant's pending matter, the Office notes that in DDR Holdings, claims were found to be eligible in Step 2A for methods and system regarding expanding commercial opportunities for internet websites by matching website "look and feel". Nevertheless, the specific facts present in the Applicant's pending matter are significantly unlike the material facts in DDR Holdings v. Hotels.com regarding DDR's holdings. DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 113 USPQ2d 1097 (Fed. Cir. 2014), provides an example of additional elements that favored eligibility because they were more than well-understood, routine conventional activities in the field. The claims in DDR Holdings were directed to systems and methods of generating a composite webpage that combines certain visual elements of a host website with the content of a third-party merchant. 773 F.3d at 1248, 113 USPQ2d at 1099. The court found that the claim had additional elements that amounted to significantly more than the abstract idea, because they modified conventional Internet hyperlink protocol to dynamically produce a dual-source hybrid webpage, which differed from the conventional operation of Internet hyperlink protocol that transported the user away from the host's webpage to the third party's webpage when the hyperlink was activated. 773 F.3d at 1258-59, 113 USPQ2d at 1106-07. Thus, the claims in DDR Holdings were eligible. Contrastingly, the Applicant's alleged invention involves autonomous decision making based on predicting future user actions, and the claims in the Applicant's pending matter do not recite additional elements that amount to significantly more than the abstract idea because the claims do not have additional elements that are more than what were well-understood, routine, and conventional in the field as fully analyzed and presented above under the 35 U.S.C. § 101 heading, contrary to the Applicant's above-argued assertions, the Office maintains that the pertinent material facts in the instant pending Application are substantially dissimilar to the facts in DDR Holdings v. Hotels.com. Thus, the Office finds that the legal holdings of DDR Holdings v. Hotels.com can not properly be applied to the Applicant's pending matter to support any finding of eligibility under Step 2A or 2B. Regarding the Enfish v. Microsoft court decision cited by the Applicant, the Office finds that the legal holdings of Enfish LLC v. Microsoft Corp., 822 F.3d 1327, 118 U.S.P.Q.2d 1684 (Fed. Cir. 2016), when applied to the facts pertaining to the Applicant's claims, do not support the eligibility of Applicant's claims under Step 2A or 2B of the above-depicted § 101 Subject Matter Eligibility Test for Products and Processes flowchart. While considering in light of the particular facts and the particular holdings of Enfish v. Microsoft in the Applicant's pending matter, the Office notes that in Enfish, claim was found to be eligible in Step 2A for product regarding an improved information and storage system using a self-referential data table. Notwithstanding the foregoing, the particular facts present in the Applicant's pending matter are considerably dissimilar to the pertinent facts in Enfish v. Microsoft regarding Enfish's holdings. The patentee in Enfish argued that its claimed self-referential table for a computer database was an improvement in an existing technology and thus not directed to an abstract idea. Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1336-37, 118 USPQ2d 1684, 1689-90 (Fed. Cir. 2016). The court agreed with the patentee, based on its interpretation of the claim requiring a four-step algorithm that achieved the improvements. The eligible claims in Enfish recited a self-referential database having two key features: all entity types can be stored in a single table; and the table rows can contain information defining the table columns. Enfish, 822 F.3d at 1332, 118 USPQ2d at 1687. The features were not conventional and thus were considered to reflect an improvement to existing technology. In particular, they enabled the claimed table to achieve benefits over conventional databases, such as increased flexibility, faster search times, and smaller memory requirements. Enfish, 822 F.3d at 1337, 118 USPQ2d at 1690. Contrastingly, the Applicant's alleged invention involves autonomous decision making based on predicting future user actions, and the features in the Applicant's pending claims are well-understood and conventional and/or are not considered to reflect an improvement to existing technology as fully analyzed and presented above under the 35 U.S.C. § 101 heading, contrary to the Applicant's above-argued assertions, the Office maintains that the relevant substantive facts in the instant pending Application are materially dissimilar to the facts in Enfish v. Microsoft. Consequently, the Office determines that the legal holdings of Enfish v. Microsoft can not properly be applied to the Applicant's pending matter to support any finding of eligibility under Step 2A or 2B. With respect to the McRO v. Bandai Namco Games America court decision cited by the Applicant, the Office determines that the legal holdings of McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299, 120 U.S.P.Q.2d 1091 (Fed. Cir. 2016), when applied to the facts pertaining to the Applicant's claims, do not support the eligibility of Applicant's claims under Step 2A or 2B of the above-depicted § 101 Subject Matter Eligibility Test for Products and Processes flowchart. While considering in light of the specific facts and the specific holdings of McRO v. Bandai Namco Games America in the Applicant's pending matter, the Office notes that in McRO, claims were found to be eligible in Step 2A for methods regarding rules for automatically animating lip synchronization and facial expression animation of animated characters. Nevertheless, the precise facts present in the Applicant's pending matter are substantially dissimilar to the material facts in McRO v. Bandai Namco Games America with regard to McRO's holdings. In McRO, the Federal Circuit held the claimed methods of automatic lip synchronization and facial expression animation using computer-implemented rules patent eligible under 35 U.S.C. § 101, because they were not directed to an abstract idea (Step 2A of the USPTO's SME guidance). The basis for the McRO court's decision was that the claims were directed to an improvement in computer-related technology (allowing computers to produce "accurate and realistic lip synchronization and facial expressions in animated characters" that previously could only be produced by human animators), and thus did not recite a concept similar to previously identified abstract ideas. Contrastingly, the Applicant's alleged invention involves autonomous decision making based on predicting future user actions, and the claims in this application are not directed to an improvement in computer-related technology, and recite concepts similar to previously identified abstract ideas as fully analyzed and presented above under the 35 U.S.C. § 101 heading, contrary to the Applicant's above-argued assertions, the Office maintains that the material pertinent facts in the Applicant's pending matter are substantially dissimilar to the facts in McRO v. Bandai Namco Games America. Thus, the Office determines that the legal holdings of McRO v. Bandai Namco Games America can not properly be applied to the Applicant's pending matter to support any finding of eligibility under Step 2A or 2B. The Applicant is encouraged to please see and refer to the current rejection based upon the currently pending claims under the 35 U.S.C. § 101 heading above. Regarding obviousness rejections under 35 U.S.C. § 103, the Applicant's arguments submitted August 13, 2026 (hereinafter "REMARKS") in response to the Official Correspondence mailed May 21, 2026 (hereinafter "Final Correspondence") have been fully considered and are persuasive. • The Applicant argued: "Applicants respectfully traverse the rejection under 35 U.S.C. [sec.] 103. 'The cited portions of Moolla are directed to matching social media posts to financial transactions and recording an association between an item and an emotional state "for future use." The Office Action does not identify any disclosure in Moolla of generating labeled emotional-state training records and using those labeled emotional-state training records to fine-tune one or more model parameters of an emotional state machine learning model. "Cheng does not cure the stated deficiencies of Moolla. Amended claim 1 does not merely recite a sentiment analysis model trained on labeled data. Amended claim 1 recites that the claimed system generates the labeled emotional-state training records by correlating the first financial activity with user-reported feedback regarding an emotional state of the user at the first time period, and then updates the emotional state machine learning model by fine-tuning one or more model parameters using the labeled emotional-state training records. 'Pavletic and Zarlengo do not cure these deficiencies. [] The[] cited disclosures do not disclose the amended limitations of "generating labeled emotional-state training records by correlating the first financial activity with user reported feedback regarding an emotional state of the user at the first time period" and "updating an emotional state machine learning model by fine-tuning one or more model parameters using the labeled emotional-state training records." Thus, the cited references, individually and in combination, do not teach or suggest these amended limitations. "The Office Action's stated reason to combine Pavletic with Moolla also does not bridge the gap. [] "The Office Action's stated reason to combine Pavletic with Cheng also does not bridge the gap. [] 'The cited references also fail to teach or suggest "selecting, via an action machine learning model, an account-control action based on the one or more future financial events and the current emotional state, the action machine learning model having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs," as recited in amended claim 1. '[] The cited portions of Cheng have not been shown to disclose selecting an account-control action based on both "the one or more future financial events" and "the current emotional state," as recited in amended claim 1. "Amended claim 1 recites a different decision basis than the cited portions of Cheng. "Pavletic does not cure this deficiency. [] The cited portions of Pavletic have not been shown to disclose selecting an account-control action based on both a predicted future financial event and a current emotional state, nor have the cited portions of Pavletic been shown to disclose an action machine learning model trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs. "Moolla and Zarlengo also do not cure this deficiency. [] '[T]he cited references, individually and in combination, have not been shown to teach or suggest the amended limitation of "selecting, via an action machine learning model, an account-control action based on the one or more future financial events and the current emotional state, the action machine learning model having been trained using action-outcome records comprising financial and behavioral features as inputs and account-control actions as outputs," as recited in claim 1. "[T]he cited references do not disclose or suggest generating labeled emotional-state training records from first financial activity and user-reported emotional feedback, fine tuning one or more model parameters of an emotional state machine learning model using those labeled emotional-state training records, selecting an account-control action via an action machine learning model trained using action-outcome records, generating control instructions based on the selected account-control action, and autonomously transmitting those control instructions to remote transaction servers to modify account parameters associated with future financial accounts. [] Th[]e cited passages do not teach or suggest the amended claim as a whole. "[I]ndependent claim 1 is patentably distinguishable over the cited references. Independent claims 8 and 15 recite corresponding limitations and are patentably distinguishable for at least the same reasons. []" (REMARKS [as abridged], pp. 22-27). The above-quoted arguments submitted August 13, 2026 at REMARKS pp. 22-27 regarding rejections under 35 U.S.C. § 103 have been fully considered. Regarding eligibility rejections under 35 U.S.C. § 101, the Applicant's arguments submitted August 13, 2026 (hereinafter "REMARKS") in response to the Official Correspondence mailed May 21, 2026 (hereinafter "Final Correspondence") have been fully considered but are not persuasive. Further to the May 21, 2026 Final Correspondence, the reiterated grounds of rejection are fully set forth above under the 35 U.S.C. § 101 heading as applied to the herein examined current claims. • Specifically, the Applicant argued: "[A]pplicants submit that the claims are in condition for allowance[]." (REMARKS [as abridged], p. 28). Notwithstanding respectively the foregoing, the above-quoted arguments are not persuasive. Materially, the Office respectfully disagrees with the Applicant's above-quoted legal conclusion. The Office refers the Applicant to see the current rejection based upon the currently pending claims under the 35 U.S.C. § 101 heading above. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. USPGPub No. US 20190295114 A1 by PAVLETIC; Miro et al. discloses DIGITAL BANKING PLATFORM AND ARCHITECTURE ; wherein: a computer implemented device is described that is adapted for improving memory efficiency for conducting machine learning on multi-dimensional vectors stored as specially configured data structures. The device includes network interfaces adapted for receiving data sets and communicating with data harvesting applications, as well as data storage and memory for storing the configured data structures. The multi-dimensional vectors and the system provide a data architecture that processes disparate data sets to programmatically extract features transformed from raw information, the extracted features stored in the form of data values suitable for conducting data approximations and neural network processing. USPGPub No. US 20210374863 A1 by Zarlengo; Adam et al. discloses INTERACTIVE VIRTUAL ASSISTANT SYSTEM ; wherein: a method, computer program product, and computer system for defining, at a computing device, psychometric data for a user. USPAT No. US 10229442 B1 to Moolla; Roohi discloses Customer emotional state analysis for optimized financial transactions ; wherein: the innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods for optimized communications based on a customer emotional state. USPGPub No. US 20210390445 A1 by CHENG; Lin Ni Lisa et al. discloses SYSTEMS AND METHODS FOR AUTOMATIC DECISION-MAKING WITH USER-CONFIGURED CRITERIA USING MULTI-CHANNEL DATA INPUTS ; wherein: systems and methods for decision-making with multi-channel data inputs are provided. Any inquiry concerning this communication or earlier communications from the examiner should be directed to SLADE E. SMITH whose telephone number is 571- 272-8645. The examiner can normally be reached Monday 9:00 AM EST to 5:00 PM and Friday from 10:00 AM EST to 2:00 PM EST. 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, Matthew S. Gart can be reached on 571-272-3955. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. Sincerely, /SLADE E SMITH/Primary Examiner, Art Unit 3696 09/18/2026