DETAILED ACTION
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 .
Status of Claims
This action is in reply to the response filed on 10/30/2025. Claims 2, 3, 9 and 10 have been amended. Claims 1, 4-8 and 11-14 have been cancelled. Claims 2, 3, 9 and 10 are currently pending and have been examined. It is respectfully noted that claims 2, 3, 9 and 10 did not include a status indicator such as “(Currently Amended”). Appropriate correction is requested.
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 2, 3, 9 and 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. A Section 101 analysis is below.
Step 1 – are the claims directed to a process, machine, manufacture or composition of matter. The system of claim 2 and method of claim 9 are within the statutory categories of invention. For the purposes of this analysis, representative claim 2 is addressed.
Step 2A, prong one – do the claims recite a judicial exception, which is an abstract idea enumerated in MPEP 2106, a law of nature, or a natural phenomenon. Abstract ideas are in bold below, and represent the abstract idea of certain methods of organizing human activity of the commercial or legal interaction of sending money. Please see MPEP 2106.04(a)(2)(II)(B).
2. A system for digitally sending units using a mobile cellular device, said mobile cellular device including a cellular phone application accessible on the mobile device, said cellular phone application including a contacts list of entities that are each selectable from the contacts list for sending messages to the entities in the contacts list, said mobile cellular device further including a banking application accessible on the mobile device that is a different application than the cellular phone application, said banking application including a digital units transfer application operable to digitally transfer money using the banking application, said digital units transfer application including a recipients list of entities that are each selectable from the recipients list for digitally sending units to the entities in the recipients list, said recipients list of entities being a different list than the contacts list of entities, said digital units transfer application including a search feature that allows a user to simultaneously search both the contacts list and the recipient list so as to allow the user to identify an entity to digitally send units to that is in the contacts list but is not in the recipients list, said system comprising:
a back-end server including: at least one processor for processing data and information;
a communications interface communicatively coupled to the at least one processor; and
a memory device storing data and executable code that, when executed, causes the at least one processor to:
train, using training test data, a neural network to predict factors for searching for an entity in the contacts list and the recipients list using the search feature,
the training including: iteratively predicting the factors from the training test data that correlate to searching for an entity in the contacts list and the recipients list using the search feature, the predicting generating a prediction;
testing and comparing, during each iteration, the prediction to a target variable;
indicating, for each iteration and via a feedback loop, modifications to weights assigned to nodes of the neural network to improve the neural network’s ability to predict the target variable and reduce error of the prediction;
deploy the trained neural network;
search for an entity using the search feature and the deployed neural network;
identifying an entity that is in the contacts list but is not in the recipients list from the search using the deployed neural network,
wherein the entity not in the recipients list first joins the digital units transfer application by attaching a financial account to their contact information; and
digitally send units to the identified entity using the digital units transfer application.
Step 2A, prong two – do the claims recite additional elements that integrate the judicial exception into a practical application. Integration of the judicial exception into a practical application requires an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. The additional elements are considered as follows:
The “mobile cellular device”, “cellular phone application”, “banking application”, “digital units transfer application”, “search feature that allows a user to simultaneously search both the contacts list and the recipient list so as to allow the user to identify an entity to digitally send units to that is in the contacts list but is not in the recipients list”, “back-end server”, “at least one processor”, “communications interface”, “memory device”, and “train, using training test data, a neural network to predict factors for searching for an entity in the contacts list and the recipients list using the search feature, the training including: iteratively predicting the factors from the training test data that correlate to searching for an entity in the contacts list and the recipients list using the search feature, the predicting generating a prediction; testing and comparing, during each iteration, the prediction to a target variable; indicating, for each iteration and via a feedback loop, modifications to weights assigned to nodes of the neural network to improve the neural network’s ability to predict the target variable and reduce error of the prediction; deploy the trained neural network”. Referring to MPEP 2106.05(f), the preceding recited additional elements are no more than mere instructions to implement an abstract idea or other exception on a computer. The computer components are recited at a high-level of generality (e.g., to receive, store, or transmit data) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, the additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Please see MPEP 2106.05(f)(1) discussing when the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished this does not show integration into a practical application. Please see MPEP 2106.05(f)(2) discussing when the claim invokes computers or other machinery merely as a tool to perform an existing process including use of a computer or other machinery for economic tasks this does not show integration into a practical application.
Further regarding the steps of “train, using training test data, a neural network to predict factors for searching for an entity in the contacts list and the recipients list using the search feature, the training including: iteratively predicting the factors from the training test data that correlate to searching for an entity in the contacts list and the recipients list using the search feature, the predicting generating a prediction; testing and comparing, during each iteration, the prediction to a target variable; indicating, for each iteration and via a feedback loop, modifications to weights assigned to nodes of the neural network to improve the neural network’s ability to predict the target variable and reduce error of the prediction; deploy the trained neural network”, the preceding recited additional element is additionally no more than insignificant extra-solution activity amounting to no more than manipulating gathered information. Please see MPEP 2106.05(g). Please also see Recentive Analytics, Inc. v. Fox Corp., No. 2023-2437 (Fed. Cir. Apr. 18, 2025), which affirmed the District of Delaware’s dismissal of Recentive’s infringement suit on the ground that the asserted patents were directed to ineligible subject matter under 35 U.S.C. § 101. The decision reinforces the courts’ view that applying generic machine learning techniques to known problems — without technical innovation in the machine learning methods themselves — is insufficient for patent eligibility.
Step 2B – do the claims recited additional elements that 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 amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The computer components implementing the abstract idea appear to be generic in view of at least Applicant’s specification, [0037]-[0040]. Focusing on the additional element of “train, using training test data, a neural network to predict factors for searching for an entity in the contacts list and the recipients list using the search feature, the training including: iteratively predicting the factors from the training test data that correlate to searching for an entity in the contacts list and the recipients list using the search feature, the predicting generating a prediction; testing and comparing, during each iteration, the prediction to a target variable; indicating, for each iteration and via a feedback loop, modifications to weights assigned to nodes of the neural network to improve the neural network’s ability to predict the target variable and reduce error of the prediction; deploy the trained neural network”, identified as extra solution activity above, evidence that this element is well understood, routine and conventional can be found in Cluff (US 2023/0342012) ([0082]-[0104], describing the claimed training of a neural network in nearly identical terms to the present application), and Obradovic (US 2002/0038307) ([0034]).
In view of the above analysis, independent claims 2 and 9 are not patent eligible. Dependent claims 3 and 10 do not cure the deficiencies in their respective base claims. Specifically, claims 3 and 10 merely refine the abstract idea (2A1) by invoking a computer as a tool to perform an existing process (2A2, 2B). Regarding the further additional elements in the dependent claims including the smart phone (claims 3, 10), please see MPEP 2106.05(f)(2) discussing when the claim invokes computers or other machinery merely as a tool to perform an existing process including use of a computer or other machinery for economic tasks this does not show integration into a practical application or provide significantly more.
Claim Rejections - 35 USC § 103
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 for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The 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.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 2, 3, 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Sprague (US 2023/0289767) in view of Patel (US 2023/0066272) and further in view of Cluff (US 2023/0342012).
Claim 2 recites:
A system for digitally sending units using a mobile cellular device, said mobile cellular device including a cellular phone application accessible on the mobile device, (Sprague, Fig. 1, [0019], system 100, user device 110; [0061], application of the user device)
said cellular phone application including a contacts list of entities that are each selectable from the contacts list for sending messages to the entities in the contacts list, (Sprague, [0061], contact list)
said mobile cellular device further including a banking application accessible on the mobile device that is a different application than the cellular phone application, (Sprague, [0061], the application that the contact list is used for is different from the client-side application of the electronic banking platform)
said banking application including a digital units transfer application operable to digitally transfer money using the banking application, (Sprague, Figs. 1, 2A, [0036], application 270, fund transfer)
said digital units transfer application including a recipients list of entities that are each selectable from the recipients list for digitally sending units to the entities in the recipients list, (Sprague, Fig. 6A, [0060], user interface 600a for receiving user input of recipient information. Sprague does not specifically disclose a recipients “list”. Patel, Fig. 4B, [0097] discusses listing recipients. It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the recipient information of Sprague to include the list of Patel so that a user may select an intended recipient as discussed in Patel, [0097], and Sprague, [0024].)
said recipients list of entities being a different list than the contacts list of entities, (Sprague, [0061], the application that the contact list is used for is different from the client-side application of the electronic banking platform)
said digital units transfer application including a search feature that allows a user to simultaneously search both the contacts list and the recipient list so as to allow the user to identify an entity to digitally send units to that is in the contacts list but is not in the recipients list, (Sprague, [0063], search a user database for the recipient. Sprague does not specifically disclose search both the contacts list and the recipient list. Patel, [0040], discusses searching both contacts and payment services. Please also see Patel, [0100].
said system comprising: a back-end server including: at least one processor for processing data and information; (Sprague, [0035], system, servers, processors)
a communications interface communicatively coupled to the at least one processor; and (Sprague, [0034], [0035], network interface, communication)
a memory device storing data and executable code that, when executed, causes the at least one processor to: (Sprague, [0026], memory)
train, using training test data, a neural network to predict factors for searching for an entity in the contacts list and the recipients list using the search feature, (Sprague, [0063], servers search a user database for the recipient. Patel, [0040], discusses searching both contacts of the user and members of a payment service using machine learning, and further discloses in Patel, [0282], neural networks, and Patel, [0032], discloses training using data. It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the searching of Sprague to include the searching of contact and payment service lists using trained neural networks as in Patel so that a user may select an intended recipient as discussed in Patel, [0097], and Sprague, [0024].)
the training including: iteratively predicting the factors from the training test data that correlate to searching for an entity in the contacts list and the recipients list using the search feature, the predicting generating a prediction; testing and comparing, during each iteration, the prediction to a target variable; indicating, for each iteration and via a feedback loop, modifications to weights assigned to nodes of the neural network to improve the neural network’s ability to predict the target variable and reduce error of the prediction; deploy the trained neural network; (Patel does not disclose training. Sprague, [0282], discloses training component 1538 to train models using machine-learning mechanisms but does not go into specific details of the training. Cluff, Fig. 6, [0104], discusses training including iterative training, testing, comparing target variable, updated weights and model deployment. Please compare Cluff, Fig. 6, to the Applicant’s drawings, Fig. 8, which are virtually identical. It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the searching of Sprague to include the training of Patel as modified by the training of Cluff so that a user may select an intended recipient as discussed in Patel, [0097], Sprague, [0024], and Cluff, [0029].)
search for an entity using the search feature and the deployed neural network; (Sprague, [0063], search. Sprague does not disclose searching using a deployed neural network. Patel, [0040], discusses searching using machine learning, and further discloses in Patel, [0282], neural networks. It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the searching of Sprague to include the searching using neural networks as in Patel so that a user may select an intended recipient as discussed in Patel, [0097], and Sprague, [0024].)
identifying an entity that is in the contacts list but is not in the recipients list from the search using the deployed neural network, (Sprague, [0063], search; [0066], recipient does not have account. Sprague does not disclose the search uses the deployed neural network. Patel, [0040], discusses searching using machine learning, and further discloses in Patel, [0282], neural networks. It would have been obvious to a person of ordinary skill in the art before the time of effective filing to modify the searching of Sprague to include the searching using neural networks as in Patel so that a user may select an intended recipient as discussed in Patel, [0097], and Sprague, [0024].)
wherein the entity not in the recipients list first joins the digital units transfer application by attaching a financial account to their contact information; and (Sprague, Fig. 6B, [0066], the recipient 102 has an account with P2P transfer platform)
digitally send units to the identified entity using the digital units transfer application. (Sprague, [0069], process electronic transfer)
Claim 9 corresponds to claim 2 and is rejected on the same grounds. Regarding method claim 9, Sprague, Fig. 3, [0041], method 300.
Claim 3 recites:
The system according to claim 2 wherein the mobile cellular device is a smart phone. (Sprague, [0019], iPhone)
Claim 10 corresponds to claim 3 and is rejected on the same grounds.
Response to Arguments
Applicant's arguments filed 10/30/2025 have been fully considered and are addressed below.
Regarding the rejections under 35 U.S.C. 112, the rejections under 35 U.S.C. 112 have been withdrawn in view of the amendments to claims 2 and 9, and the cancellation of claims 4-8 and 11-14.
Regarding the rejection under 35 U.S.C. 101, Applicant’s arguments have been fully considered but they are not persuasive. Regarding the arguments concerning Step 2A, prong one, the certain methods of organizing human activity grouping of abstract ideas includes commercial interactions. As recited in the claims, the invention is directed to digitally sending money after first searching a recipient and contact list, which is clearly within the groupings of abstract ideas discussed in MPEP 2106. Please see MPEP 2106.04(a)(2)(II)(B) discussing 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 is an example of subject matter where the commercial or legal interaction is business relations. Here, a processor is used to identify an entity based on a search submitted by a user. Regarding Example 39, facial detection is not claimed. Furthermore, the MPEP is controlling.
Regarding Applicant’s arguments regarding Step 2A, prong two, integration into a practical application requires an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the exception. Limitations that are indicative of integration into a practical application include improvements to the functioning of a computer, applying the judicial exception with a particular machine, effecting transformation of a particular article to a different state or thing or applying the judicial exception in some other meaningful was beyond generally linking the use of the judicial exception to a particular technological environment. The Applicant argues “In particular, Applicant respectfully submits that when evaluating amended claims 2 and 9, as a whole, these recited additional elements outlined above integrate any recited judicial exception into a practical application because they (1) reflect an improvement in the functioning of a technology or technical field by improving predictability of the target variable and functionality of the neural network. By making this adjustment to the weights, the error amount is reduced and the predictability of the target variable becomes more accurate. This improved accuracy and reduction in error is necessarily an improvement on the computing system, the neural network, and to the nodes (i.e., the underlying machines/computers) of the neural network. Specifically, the underlying machine/computer is improved with each iteration of the iterative training and testing loop to make more accurate predictions of a likely future outcome.” The Examiner respectfully disagrees. In the remarks filed 10/30/2025, on page 3, the Applicant cites Applicant’s specification, [0068]-[0091] and [0097], as support for the amendments filed. Applicant’s specification, [0068]-[0091] and [0097], appears to constitute a boiler plate description of known artificial intelligence and machine learning techniques that is used in many of the Applicant’s other applications published prior to the effective filing date. Moreover, it is respectfully noted that Applicant’s specification, [0068]-[0091] and [0097], does not appear to contain any discussion as to how machine learning is actually applied to search for an entity in a recipients list and a contact list. Please see MPEP 2106.05(f)(1) discussing when the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished this does not show integration into a practical application. Please see MPEP 2106.05(f)(2) discussing when the claim invokes computers or other machinery merely as a tool to perform an existing process including use of a computer or other machinery for economic tasks this does not show integration into a practical application. Regarding Example 47, detection of malicious network packets is not claimed.
Regarding Applicant’s arguments regarding Step 2B, Step 2B is directed to whether the claim recites additional elements that amount to an inventive concept (AKA “significantly more”) than the judicial exception. The Applicant argues “using a trained and deployed neural network” is not a WURC activity. The Examiner respectfully disagrees. White (US 5,014,219) is an example from the 1990s disclosing searching using a neural network.
Regarding the rejections under 35 U.S.C. 103, Applicant’s arguments have been fully considered and the amended claims are addressed in detail above. The Applicant argues Patel does not teach searching from both a contact list and recipient list and cites Patel, [0097]. The Examiner respectfully disagrees. Patel, [0040], discusses a “payment service platform” that utilizes machine learning to identify users both on the payment service and contacts. Please also see Patel, Fig. 4G, [0100], which explicitly discloses entering a name in a search field and then subsequently displaying “The user interface 414 may also include the indications 432 of trust signals (e.g., “Joined April 2017,” “Paid by 1 Persons You Know,” and “Not In Your Contacts”)”.
Applicant further argues “Applicant acknowledges that many modern mobile cellular devices include a cellular phone application having a contacts list from which the user can access people to send text messages, make cellular phone calls, send emails, make air drops, etc. and an application for digitally sending money having an added recipient's list that includes contact information of each person that the user sends money to and receives money from if the device includes. Applicant also acknowledges that modern mobile cellular devices include a separate search feature that allows a user to search for people or entities in these two lists. What Applicant states is not known is a single search feature associated with the application for digitally sending money that allows a user to simultaneously search both the contacts list and the recipient list so as to allow the user to identify an entity to digitally send money to that is in the contacts list but is not in the recipients list. That is what is claimed.” In response, it is respectfully noted that by the Applicant’s own admission, the claimed search feature is known. Placing the search feature in one application as opposed to another is an obvious rearrangement of parts. Please see MPEP 2144.04.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure includes: US 20240330826; US 12079706; US 20230342821; US 20230342338; US 20230342361; US 20230342350; US 20230342012; US 20230342361; US 20230342821; US 20230328070; US 20230325786; US 20230316394; US 20170024641; US 20020038307; and US 5014219.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Gregory Harper whose telephone number is (571)272-5481. The examiner can normally be reached on M-Th 7am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Calvin Hewitt II can be reached at (571) 272-6709. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GREGORY HARPER/Examiner, Art Unit 3692 /DAVID P SHARVIN/Primary Examiner, Art Unit 3692
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