CTNF 19/184,102 CTNF 94614 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. 12-151 AIA 26-51 12-51 Status of Claims This action is in reply to the communication(s) filed on 21 April 2025. Claim(s) 1-20 is/are currently pending and have been examined. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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. Step 1 of the 101 Analysis: Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recites a system, method, and non-transitory computer-readable medium for artificial intelligence-initiated generation of cloud-created tokens with controls. These are a machine, process, and article of manufacture which are within the four categories of statutory subject matter. Step 2A Prong 1 of the 101 Analysis: The following limitations and/or similar versions are recited in claim(s) 1, 12 and 19: Claims 1, 12 and 20: “generates one or more VCNs,” “provisions,…, each of the one or more VCNs,” “monitors a usage of each of the one or more VCNs,” “identifies at least one of the one or more VCNs for removal, and” “responsive to an identification of at least one of the one or more VCNs for removal, transmits,…, a signal to remove the at least one of the one or more VCNs.” These limitations, as drafted, are a process that, under its broadest reasonable interpretation, describes Fundamental Economic Principles or Practices. That is, other than reciting “a processor circuit”, “one or more user devices” and “A non-transitory computer readable medium” nothing in the claims’ elements precludes the steps from practically describing Fundamental Economic Principles or Practices. For example, but for the recited computer language, the limitations in the context of this claim describes Mitigating Risk. Mitigating Risk is described when provisioning a VCN, monitoring its usage for removal, and removing the VCN. If a claim limitations, under their broadest reasonable interpretation, describes Fundamental Economic Principles or Practices but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Activity” grouping of abstract ideas. Accordingly, the independent claims recite an abstract idea. Step 2A Prong 2 of the 101 Analysis: This judicial exception is not integrated into a practical application. In particular, the independent claim(s) recite the following (or similar) additional elements: Claims 1, 12 and 19: “a processor circuit in data communication with an artificial intelligence (AI) system,” “wherein the AI system:” “…to one or more user devices…” “…to at least one of the one or more user devices…” Claim 20: “A non-transitory computer readable medium comprising instructions implementing an artificial intelligence (AI) system, wherein, when executed by a processor circuit, cause the processor circuit to perform procedures comprising:” The computer components (processor circuit, user devices, non-transitory computer readable medium) are recited at a high level of generality (i.e. as a generic processor, generic devices, and generic storage) such that it amounts to no more than mere instructions to implement the judicial exception on a computer or by using a computer merely as a tool to perform an existing process. These element(s) in combination do not add anything that is not already present when the steps are considered separately. Simply implementing an abstract idea on a computer as a tool to perform an existing process is not indicative of integration into a practical application (See MPEP § 2106.05(f).) The use of artificial intelligence is implemented at a high level of generality (i.e. as simply using the technology) such that it amounts to no more than generally linking the use of the judicial exception to a particular technological environment or field of use. These element(s) in combination do not add anything that is not already present when the steps are considered separately. Generally linking the use of the judicial exception to a particular technological environment or field of use is not indicative of integration into a practical application (See MPEP § 2106.05(h).) Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea. Step 2B of the 101 Analysis: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements identified in Step 2A Prong 2 (if any) amount to no more than mere instructions to implement the judicial exception on a computer or no more than mere data gathering or data outputting which only adds insignificant extra solution activity to the judicial exception. Accordingly, the Examiner in accordance with MPEP §2106.05(II): • Carries over their identification of the additional element(s) in the claim from Step 2A Prong Two; • Carries over their conclusions from Step 2A Prong Two on the considerations discussed in MPEP §§ 2106.05(a) - (c), (e) (f) and (h): • Re-evaluates any additional element or combination of elements that was considered to be insignificant extra-solution activity per MPEP § 2106.05(g), because if such re-evaluation finds that the element is unconventional or otherwise more than what is well-understood, routine, conventional activity in the field, this finding may indicate that the additional element is no longer considered to be insignificant. The claim elements which recite additional elements are: Claims 1, 12 and 19: “a processor circuit in data communication with an artificial intelligence (AI) system,” “wherein the AI system:” “…to one or more user devices…” “…to at least one of the one or more user devices…” Claim 20: “A non-transitory computer readable medium comprising instructions implementing an artificial intelligence (AI) system, wherein, when executed by a processor circuit, cause the processor circuit to perform procedures comprising:” Examiner incorporates the corresponding rationale provided in Step 2A Prong Two herein by carrying over their conclusions from Step 2A Prong Two on the considerations discussed in MPEP §§ 2106.05(a) – (c), (e), (f) and (h). These element(s) in combination do not add anything that is not already present when the steps are considered separately. Adding insignificant extra-solution activity cannot provide an inventive concept when the activities are well-understood routine and conventional. The independent claims contain no elements which are considered to be insignificant extra-solution activity. The independent claims are not patent eligible. Dependent Claim(s) 2-11, 13-18 and 20 recite limitations that are similar to the abstract idea noted in the independent claims because they further narrow the independent claim(s) which recite one or more judicial exceptions. Accordingly, these claim elements do not serve to confer subject matter eligibility to the claims since they recite abstract ideas. The claims are not patent eligible. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 1-2, 11-12 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Learned et al. (US 2022/0245640 A1 hereinafter Learned) . Claim 1 A virtual card number (VCN) management system, comprising: a processor circuit in data communication with an artificial intelligence (AI) system, (Learned discloses processor in communication with recurrent neural network (i.e. AI system). See at least paragraph [0006]) wherein the AI system: (Learned discloses employing machine learning and neural networks (i.e. AI) to embody monitoring operations of the monitoring and instructions for responding to the compromised VCN. See at least paragraph [0044].) generates one or more VCNs, (Learned discloses generating a plurality of VCNs. See at least paragraph [0006].) provisions, to one or more user devices, each of the one or more VCNs, (Learned discloses associating each of the VCNs with a user device (i.e. provisioning). See at least paragraph [0005].) monitors a usage of each of the one or more VCNs, (Learned discloses monitoring usage of the VCN by determining if they have been compromised and sending notifications. See at least paragarph [0029].) identifies at least one of the one or more VCNs for removal, and (Learned discloses identifying exposed VCNs, transmitting a message about the exposed VCNs to the user device and deleting the exposed VCNs. See at least paragraph [0018] and [0044].) responsive to an identification of at least one of the one or more VCNs for removal, transmits, to at least one of the one or more user devices, a signal to remove the at least one of the one or more VCNs. (Learned discloses identifying exposed VCNs, transmitting a message about the exposed VCNs to the user device and deleting the exposed VCNs. See at least paragraph [0018] and [0044].) Although Learned does disclose using AI for their monitoring and instructions for responding to the compromised VCN, they might not explicitly disclose using the AI for their generating and provisioning. Learned does however disclose that the various aspects of the system may be used in communication with the machine learning system. See at least paragraphs [0005]-[0007]. It would be obvious to one of ordinary skill in the art before the effective filing date to apply machine learning as shown in one embodiment to the generation and provisioning embodiments because using the machine learning of one embodiment in Learned to perform the other steps of Learned is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 2 The VCN management system of claim 1, wherein the identification of at least one of the one or more VCNs for removal is based upon whether the at least one of the one or more VCNs meets a removal setting. (Learned discloses identifying exposed VCNs (i.e. it meets a removal setting), transmitting a message about the exposed VCNs to the user device and deleting the exposed VCNs. See at least paragraph [0018] and [0044].) Claim 11 The VCN management system of claim 1, wherein: the processor circuit is contained with a server, and (Learned discloses a server with a processor. See at least Fig. 3.) the AI system is stored externally to the server. (Learned discloses machine learning engine external to the server. See at least Fig. 3.) Claim 12 A method for virtual card number (VCN) management, comprising: … The remainder of Claim 12 is substantially similar to the corresponding elements in Claim 1 and is therefore rejected using similar reasoning. Claim 19 A non-transitory computer readable medium comprising instructions implementing an artificial intelligence (AI) system, wherein, when executed by a processor circuit, cause the processor circuit to perform procedures comprising: (Learned discloses a non-transitory computer-readable media embodying the system with AI and executed by a processor. See at least paragraphs [0005] and [0050].) … The remainder of Claim 19 is substantially similar to the corresponding elements in Claim 1 and is therefore rejected using similar reasoning . 07-21-aia AIA Claim (s) 3-4 and 17-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Learned et al. (US 2022/0245640 A1 hereinafter Learned) in view of Finlow-Bates et al. (US 2024/0281796 A1 hereinafter Finlow-Bates) . Claim 3 The VCN management system of claim 1, wherein the removal setting comprises at least one selected from the group of an allotted number of uses and an allotted spending limit. (Learned does not disclose the features of Claim 3.) Learned does not disclose the features of Claim 3, Finlow-Bates discloses a maximum spending limit per time period for funds(i.e. the virtual card number) and one-time codes. See at least paragraphs [0008] and [0448]. It would be obvious to one of ordinary skill in the art before the effective filing date to set the virtual card numbers of Learned with either spending limits per time period or a one-time use as taught by Finlow-Bates because Finlow-Bates additionally teaches the motivation that this lets a system evaluate if requests are safe. See at least paragraph [0005]. Also, setting the virtual card numbers of Learned with either spending limits per time period or a one-time use as taught by Finlow-Bates is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 4 The VCN management system of claim 3, wherein the allotted number of uses is a single use. (single use codes are taught by the combination with Finlow-Bates as shown above in Claim 3.) Claim 17 The method of claim 12, wherein monitoring the usage of the one or more VCNs comprises periodically scanning a library of provisioned VCNs. (Learned discloses access of VCN numbers for behavior and deletion (i.e. scanning the library). See at least paragraph [0018]. Learned does not disclose periodic scanning.) Learned does not disclose periodic scanning. Finlow-Bates discloses that wallet may be audited (i.e. scanned) for compliance and that wallet smart contracts may executed periodically (i.e. periodic scanning). See at least paragraphs [0246], [0269], [0280]. It would be obvious to one of ordinary skill in the art before the effective filing date to perform the scanning of Learned periodically as taught by Finlow-Bates because Finlow-Bates teaches that such auditing determines whether they match certain requirements. See at least paragraph [0246]. Also, performing the scanning of Learned periodically as taught by Finlow-Bates is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 18 The method of claim 12, wherein monitoring the usage of the one or more VCNs comprises continuously scanning a library of provisioned VCNs. (Learned discloses access of VCN numbers for behavior and deletion (i.e. scanning the library). See at least paragraph [0018]. Learned does not disclose continuous scanning.) Learned does not disclose continuous scanning. Finlow-Bates discloses that wallet may be audited (i.e. scanned) for compliance and that blockchain access may comprise near-real-time access (i.e. continuous scanning). See at least paragraphs [0246], [0269], [0280]. It would be obvious to one of ordinary skill in the art before the effective filing date to perform the scanning of Learned continuously as taught by Finlow-Bates because Finlow-Bates teaches that such auditing determines whether they match certain requirements. See at least paragraph [0246]. Also, performing the scanning of Learned continuously as taught by Finlow-Bates is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable . 07-21-aia AIA Claim (s) 5-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Learned et al. (US 2022/0245640 A1 hereinafter Learned) in view of Davidson et al. (WO 02/097632 A1 hereinafter Davidson) . Claim 5 The VCN management system of claim 1, wherein the removal setting comprises a predetermined amount of time with no use. (Learned does not disclose wherein the removal setting comprises a predetermined amount of time with no use.) Learned does not disclose wherein the removal setting comprises a predetermined amount of time with no use. Davidson teaches releasing memory capacity by removing data entries which have not been accessed and have gone unused for a pre-determined period of time. See at least page 5, lines 6-14. It would be obvious to one of ordinary skill in the art before the effective filing date to remove the VCNs of Learned by removing entries which have not been accessed and have gone unused for a pre-determined period of time as taught by Davidson because Davidson additionally teaches the motivation that this automation does not require the user to willfully remember to remove old, unused data entries. See at least page 5, lines 6-14. Also, removing the VCNs of Learned by removing entries which have not been accessed and have gone unused for a pre-determined period of time as taught by Davidson is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 6 The VCN management system of claim 1, wherein the removal setting comprises a predetermined amount of time since the creation of the at least one of the one or more VCNs. (Learned does not disclose wherein the removal setting comprises a predetermined amount of time since the creation of the at least one of the one or more VCNs.) Learned does not disclose wherein the removal setting comprises a predetermined amount of time since the creation of the at least one of the one or more VCNs. Davidson teaches compressing or removing an entry based on the data entry chronology or age (i.e. predetermined amount of time since creation). See at least page 1, lines 4-8, page 3, lines 4-9 and page 5, lines 16-19. It would be obvious to one of ordinary skill in the art before the effective filing date to take the VCNs of Learned and compress or remove them based on age as taught by Davidson because Davidson additionally teaches the motivation that this allows more information to be stored on smaller devices and address the issue of finite capacity of storage media. Also, taking the VCNs of Learned and compressing or removing them based on age as taught by Davidson is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 7 The VCN management system of claim 1, wherein the identification of at least one of the one or more VCNs for removal is based upon a user prompt received by at least one of the one or more user devices. (Learned does not disclose wherein the identification of at least one of the one or more VCNs for removal is based upon a user prompt received by at least one of the one or more user devices.) Learned does not disclose wherein the identification of at least one of the one or more VCNs for removal is based upon a user prompt received by at least one of the one or more user devices. Davidson teaches that a user may be notified when a data entry compression is at its maximum and given an option to delete said data entry. See at least page 9, line 28 – page 10, line 14. It would be obvious to one of ordinary skill in the art before the effective filing date to allow a user to select and delete data entries as taught by Davidson for the VCNs of Learned because Davidson additionally teaches the motivation that this allows a user to delete the data entry altogether. See at least page 9, line 28 – page 10, line 14. Also, allowing a user to select and delete data entries as taught by Davidson for the VCNs of Learned is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 8 The VCN management system of claim 1, wherein the generation of the one or more VCNs is responsive to a user prompt received by at least one of the one or more user devices. (This limitation is taught by the combination with Davidson as shown above in Claim 7.) 07-21-aia AIA Claim (s) 9-10, 13-14, 16 and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Learned et al. (US 2022/0245640 A1 hereinafter Learned) in view of Wieker et al. (US 2022/0335411 A1 hereinafter Wieker . Claim 9 The VCN management system of claim 1, wherein the identification of at least one of the one or more VCNs for removal is based upon a prediction generated by the AI system. (Learned does not disclose making predictions generated by the AI system.) Learned does not disclose making predictions generated by the AI system. Wieker teaches machine learning making predictions for VCN. See at least paragraphs [0010] and [0053]. It would be obvious to one of ordinary skill in the art before the effective filing date to have the removal AI of Learned make VCN predictions as taught by Wieker because Wieker additionally teaches the motivation that this determines a correlation between the customer purchasing behavior and an unbound VCN. See at least paragraphs [0010] and [0053]. Also, having the removal AI of Learned make VCN predictions as taught by Wieker is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 10 The VCN management system of claim 1, wherein: the processor circuit is contained with a server, and (Learned discloses a server with a processor. See at least Fig. 3.) the AI system is stored by the server. (Learned does not disclose the AI system stored by the server.) Learned does not disclose the AI system stored by the server. Wieker teaches an AI system stored within a server. See at least paragraph [0024] and Fig. 1. It would be obvious to one of ordinary skill in the art before the effective filing date to store the AI system in the server as taught by Wieker in the system of Learned because Wieker additionally teaches the motivation that the memory in the server may perform one or more various functions discussed. See at least paragraph [0024]. Also, storing the AI system in the server as taught by Wieker in the system of Learned is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Claim 13 The method of claim 12, wherein identifying of at least one of the one or more VCNs for removal comprises: generating, by the AI system, a prediction, and (This is taught by the combination with Wieker as shown above in Claim 9.) identifying, by the AI system, the at least one of the one or more VCNs for removal is based upon the prediction. (This is taught by the combination with Wieker as shown above in Claim 9.) Claim 14 The method of claim 13, wherein the AI system is trained based on data comprising previous removals of VCNs. (Learned discloses AI trained on data stored in compromised VCN database (i.e. previous VCN removals). See at least paragraph [0025].) Claim 16 The method of claim 13, wherein the AI system automatically identifies the at least one of the one or more VCNs for removal based on the prediction. (This is taught by the combination with Wieker as shown above in Claim 9.) Claim 20 Claim 20 is substantially similar to the corresponding elements in Claim 13 and is therefore rejected using similar reasoning . 07-21-aia AIA Claim (s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Learned et al. (US 2022/0245640 A1 hereinafter Learned) in view of Wieker et al. (US 2022/0335411 A1 hereinafter Wieker further in view of Finlow-Bates et al. (US 2024/0281796 A1 hereinafter Finlow-Bates) . Claim 15 The method of claim 14, wherein the data further comprises reasons for previous removals of VCNs. (The combined system of Learned/Wieker does not disclose wherein the data further comprises reasons for previous removals of VCNs.) The combined system of Learned/Wieker does not disclose wherein the data further comprises reasons for previous removals of VCNs. Finlow-Bates teaches that the components may store information concerning reasons for a failure (i.e. reasoning for an event). See at least paragarph [0266] and [0457]. It would be obvious to one of ordinary skill in the art before the effective filing date to store reasoning as taught by Finlow-Bates for the removal of VCNs in the combined system of Learned/Wieker because Finlow-Bates additionally teaches the motivation that this allows said reasons to be retrieved and displayed to users in the user interface. See at least paragraphs [0266] and [0457]. Also, storing reasoning as taught by Finlow-Bates for the removal of VCNs in the combined system of Learned/Wieker is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Sarin (US 2022/0067703 A1) discloses one-time use tokens and removing tokens from the user device after they have been used. Ahmad et al. (“Analysis of Optimization Strategies for Big Data Storage Management: A Study”) discloses data storage optimization strategies. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ADAM J HILMANTEL whose telephone number is (571)272-8984. The examiner can normally be reached M-F 8:30AM-5:00PM. 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, Abhishek Vyas can be reached at (571) 270-1836. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ADAM HILMANTEL/Examiner, Art Unit 3691 Application/Control Number: 19/184,102 Page 2 Art Unit: 3691 Application/Control Number: 19/184,102 Page 3 Art Unit: 3691 Application/Control Number: 19/184,102 Page 4 Art Unit: 3691 Application/Control Number: 19/184,102 Page 5 Art Unit: 3691 Application/Control Number: 19/184,102 Page 6 Art Unit: 3691 Application/Control Number: 19/184,102 Page 7 Art Unit: 3691 Application/Control Number: 19/184,102 Page 8 Art Unit: 3691 Application/Control Number: 19/184,102 Page 9 Art Unit: 3691 Application/Control Number: 19/184,102 Page 10 Art Unit: 3691 Application/Control Number: 19/184,102 Page 11 Art Unit: 3691 Application/Control Number: 19/184,102 Page 12 Art Unit: 3691 Application/Control Number: 19/184,102 Page 13 Art Unit: 3691 Application/Control Number: 19/184,102 Page 14 Art Unit: 3691 Application/Control Number: 19/184,102 Page 15 Art Unit: 3691 Application/Control Number: 19/184,102 Page 16 Art Unit: 3691 Application/Control Number: 19/184,102 Page 17 Art Unit: 3691 Application/Control Number: 19/184,102 Page 18 Art Unit: 3691 Application/Control Number: 19/184,102 Page 19 Art Unit: 3691 Application/Control Number: 19/184,102 Page 20 Art Unit: 3691 Application/Control Number: 19/184,102 Page 21 Art Unit: 3691 Application/Control Number: 19/184,102 Page 22 Art Unit: 3691 Application/Control Number: 19/184,102 Page 23 Art Unit: 3691 Application/Control Number: 19/184,102 Page 24 Art Unit: 3691
