DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is responsive to claims filed 10/14/2025 and Applicant’s communication regarding application 17/383323 filed 10/14/2025.
Claims 1-25 have been examined with this office action.
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 1-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of portfolio return computation without significantly more.
Subject Matter Eligibility Standard
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas include fundamental economic practices; certain methods of organizing human activities; an idea itself; and mathematical relationships/formulas. Alice Corporation Pty. Ltd. v.CLS Bank International, et al., 573 U.S. _ (2014) as provided by the interim guidelines FR 12/16/2014 Vol. 79 No. 241.
Analysis
Step 1, the claimed invention must be to one of the four statutory categories. 35 U.S.C. 101 defines the four categories of invention that Congress deemed to be the appropriate subject matter of a patent: processes, machines, manufactures and compositions of matter. In this case independent claims 1 and 24 and all claims which depend from it are directed toward an apparatus, independent claim 25 and all claims which depend from it are directed toward a method, and independent claim 23 and all claims which depend from it are directed toward a computer readable medium storing instruction to perform functions/steps. As such, all claims fall within one of the four categories of invention deemed to be the appropriate subject matter.
Step 2A Prong 1, Under Step 2 A, Prong 1 of the 2019 Revised § 101 Guidance, it is determined whether the claims are directed to a judicial exception such as a law of nature, a natural phenomenon, or an abstract idea (See Alice, 134 S. Ct. at 2355) by identify the specific limitation(s) in the claim that recites abstract idea(s); and then determine whether the identified limitation(s) falls within at least one of the groupings of abstract ideas enumerated in the 2019 PEG.
Specifically, claim 1 comprises inter alia the functions or steps of “A machine learning predefined scenario constructing apparatus, comprising: at least one memory; a component collection stored in the at least one memory; any of at least one processor disposed in communication with the at least one memory, the any of at least one processor executing processor-executable instructions from the component collection, storage of the component collection structured with processor-executable instructions comprising:
obtain a user selection of a set of simulated market scenarios via any of a simulation selection interaction-interface mechanism, the set of simulated market scenarios generated using a set of deep learning neural networks, each simulated market scenario in the set of simulated market scenarios structured including a set of simulated market factor values corresponding to a set of market factors; determine a range of unfiltered simulated market factor values for each market factor from the set of market factors, the range of unfiltered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of simulated market scenarios for the respective market factor; generate a set of market factor interaction-interface mechanisms, each market factor interaction-interface mechanism in the set of market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of unfiltered simulated market factor values for the respective market factor; obtain, via any of at least one processor, a user modification to a range of allowable values of a market factor from the set of market factors via the market factor interaction-interface mechanism associated with the modified market factor; update a set of customized market factors from the set of market factors based on the user modification; determine a range of allowable values for each customized market factor from the set of customized market factors; filter the set of simulated market scenarios based on the determined ranges of allowable values for the set of customized market factors determining a set of filtered simulated market scenarios having simulated market factor values that fall within the range of allowable values for each customized market factors from the set of customized market factors; determine a range of filtered simulated market factor values for each market factor from the set of market factors, the range of filtered simulated market factor values for a market factor structured to include a minimum simulated market factor value and a maximum simulated market factor value in the set of filtered simulated market scenarios for the respective market factor; and generate an updated set of market factor interaction-interface mechanisms, each updated market factor interaction-interface mechanism in the set of updated market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of filtered simulated market factor values for the respective market factor”.
Claim 23 comprises inter alia the functions or steps of “A machine learning predefined scenario constructing processor-readable, non- transient medium, the medium storing a component collection, storage of the component collection structured with processor-executable instructions comprising:
obtain a user selection of a set of simulated market scenarios via a simulation selection interaction-interface mechanism, the set of simulated market scenarios generated using a set of deep learning neural networks, each simulated market scenario in the set of simulated market scenarios structured including a set of simulated market factor values corresponding to a set of market factors; determine a range of unfiltered simulated market factor values for each market factor from the set of market factors, the range of unfiltered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of simulated market scenarios for the respective market factor; generate a set of market factor interaction-interface mechanisms, each market factor interaction-interface mechanism in the set of market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of unfiltered simulated market factor values for the respective market factor; obtain a user modification to a range of allowable values of a market factor from the set of market factors via the market factor interaction-interface mechanism associated with the modified market factor; update a set of customized market factors from the set of market factors based on the user modification; determine a range of allowable values for each customized market factor from the set of customized market factors; filter the set of simulated market scenarios based on the determined ranges of allowable values for the set of customized market factors determining a set of filtered simulated market scenarios having simulated market factor values that fall within the range of allowable values for each customized market factors from the set of customized market factors; determine a range of filtered simulated market factor values for each market factor from the set of market factors, the range of filtered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of filtered simulated market scenarios for the respective market factor; and generate an updated set of market factor interaction-interface mechanisms, each updated market factor interaction-interface mechanism in the set of updated market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of filtered simulated market factor values for the respective market factor”.
Claim 24 comprises inter alia the functions or steps of “A machine learning predefined scenario constructing processor-implemented system, comprising: means to store a component collection; means to process processor-executable instructions from the component collection, storage of the component collection structured with processor-executable instructions comprising:
obtain a user selection of a set of simulated market scenarios via a simulation selection interaction-interface mechanism, the set of simulated market scenarios generated using a set of deep learning neural networks, each simulated market scenario in the set of simulated market scenarios structured including a set of simulated market factor values corresponding to a set of market factors; determine a range of unfiltered simulated market factor values for each market factor from the set of market factors, the range of unfiltered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of simulated market scenarios for the respective market factor; generate a set of market factor interaction-interface mechanisms, each market factor interaction-interface mechanism in the set of market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of unfiltered simulated market factor values for the respective market factor; obtain a user modification to a range of allowable values of a market factor from the set of market factors via the market factor interaction-interface mechanism associated with the modified market factor; update a set of customized market factors from the set of market factors based on the user modification; determine a range of allowable values for each customized market factor from the set of customized market factors; filter the set of simulated market scenarios based on the determined ranges of allowable values for the set of customized market factors determining a set of filtered simulated market scenarios having simulated market factor values that fall within the range of allowable values for each customized market factors from the set of customized market factors; determine a range of filtered simulated market factor values for each market factor from the set of market factors, the range of filtered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of filtered simulated market scenarios for the respective market factor; and generate an updated set of market factor interaction-interface mechanisms, each updated market factor interaction-interface mechanism in the set of updated market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of filtered simulated market factor values for the respective market factor”.
Claim 25 comprises inter alia the functions or steps of “A machine learning predefined scenario constructing process, including processing processor-executable instructions via any of at least one processor from a component collection stored in at least one memory, storage of the component collection structured with processor-executable instructions comprising:
obtain a user selection of a set of simulated market scenarios via a simulation selection interaction-interface mechanism, the set of simulated market scenarios generated using a set of deep learning neural networks, each simulated market scenario in the set of simulated market scenarios structured including a set of simulated market factor values corresponding to a set of market factors; determine a range of unfiltered simulated market factor values for each market factor from the set of market factors, the range of unfiltered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of simulated market scenarios for the respective market factor; generate a set of market factor interaction-interface mechanisms, each market factor interaction-interface mechanism in the set of market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of unfiltered simulated market factor values for the respective market factor; obtain a user modification to a range of allowable values of a market factor from the set of market factors via the market factor interaction-interface mechanism associated with the modified market factor; update a set of customized market factors from the set of market factors based on the user modification; determine a range of allowable values for each customized market factor from the set of customized market factors; filter the set of simulated market scenarios based on the determined ranges of allowable values for the set of customized market factors determining a set of filtered simulated market scenarios having simulated market factor values that fall within the range of allowable values for each customized market factors from the set of customized market factors; determine a range of filtered simulated market factor values for each market factor from the set of market factors, the range of filtered simulated market factor values for a market factor structured including a minimum simulated market factor value and a maximum simulated market factor value in the set of filtered simulated market scenarios for the respective market factor; and generate an updated set of market factor interaction-interface mechanisms, each updated market factor interaction-interface mechanism in the set of updated market factor interaction-interface mechanisms structured as associated with a market factor from the set of market factors and structured displaying the range of filtered simulated market factor values for the respective market factor”.
The cited limitations as drafted are systems and methods that, under their broadest reasonable interpretation, covers performance of a method of organizing human activity, but for the recitation of the generic computer components. Further, none of the limitations recite technological implementations details for any of the steps but, instead, only recite broad functional language being performed by the generic use of at least one processor. Portfolio return computation is a fundamental economic practice long prevalent in commerce systems. If a claim limitation, under its broadest reasonable interpretation, covers a fundamental economic principle or practice but for the general linking to a technological environment, then it falls within the organizing human activity grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2, Next, it is determined whether the claim is directed to the abstract concept itself or whether it is instead directed to some technological implementation or application of, or improvement to, this concept, i.e., integrated into a practical application. See, e.g., Alice, 573 U.S. at 223, discussing Diamond v. Diehr, 450 U.S. 175 (1981). The mere introduction of a computer or generic computer technology into the claims need not alter the analysis. See Alice, 573 U.S. at 223—24. “[T]he relevant question is whether the claims here do more than simply instruct the practitioner to implement the abstract idea on a generic computer.” Alice, 573 U.S. at 225.
In particular, the claims contain the following additional elements: a system; a machine learning predefined scenario constructing apparatus; least one memory; a component collection stored in the at least one memory; any of at least one processor; a set of deep learning neural networks; interaction-interface mechanism. However, the specification description of the additional elements a system ([Figure 99] [2527-2530]); a machine learning predefined scenario constructing apparatus ([Figure 99] [2527-2530]); least one memory ([Figure 99, element 9929] [2540]); a component collection stored in the at least one memory ([2541]); any of at least one processor ([Figure 99, element 9903] [2522-2524]); a set of deep learning neural networks ([0172-0185]); interaction-interface mechanism ([Figures 15-19] [0359-0365]) are at a high level of generality using exemplary language or as part of a generic technological environment and are functions any general purpose computer performs such that it amount no more than mere instruction to apply the exception to a particular technological environment. Further, none of the limitations recite technological implementations details for any of the steps but, instead, only recite broad functional language being performed by the generic use of at least one processor. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaning limits on practicing the abstract idea. Thus, the claim is directed toward an abstract idea.
Step 2B, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more that the abstract idea(s). As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the abstract idea(s) amounts to no more than mere instructions to apply the exaction using a generic computer component. Mere instruction to apply an exertion using a generic computer component cannot provide an inventive concept. These generic computer components are claimed at a high level of generality to perform their basic functions which amount to no more than generally linking the use of the judicial exception to the particular technological environment of field of use (Specification as cited above for additional elements) and further see insignificant extra-solution activity MPEP § 2106.05 I. A. iii, 2106.05(b), 2106.05(b) III, 2106.05(g). Thus, the claims are not patent eligible.
As for dependent claims 2-22, these claims recite limitations that further define the same abstract idea noted from the respective independent claims from which they depend. Therefore, the cited dependent claims are considered patent ineligible for the reasons given above.
Prior Art
The claims overcome the prior art of record such that none of the cited prior art reference’s disclosures can be applied to form the basis of a 35 USC § 102 rejection nor can they be combined to fairly suggest in combination, the basis of a 35 USC § 103 rejection when the limitations are read in the particular environment of the claims. Specifically, the prior art of record does show the particular inputs/outputs of the machine learning models and interaction-interface mechanisms. Therefore, the claims may be allowable if amended to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action.
Response to Arguments
Applicant's arguments with regards to claims have been fully considered but they are not persuasive.
EXAMINER’S RESPONSE TO APPLICANT REMARKS CONCERNING Claim Rejections - 35 USC § 101: Applicant's arguments with regards to 35 USC § 101 have been fully considered but is not persuasive. The examiner has given proper weight to and has followed the MPEP which is the current analysis required for patent eligibility and the basis of the factual determination. Nothing in the claims has been “ignore” as applicant contends. The machine learning, deep learning neural network and trainer are all claimed at a high level of generality and are merely applied to the abstract idea of the claims. The machine learning is claimed at a high level of generality and are merely applied to the abstract idea of the claims. The phrase “multi-variate mixture” as used in the claims is a non-functional description of a database. Even if not interpreted as non-functional descriptive matter, the multi-variate mixture datastructure appears to be merely the application of an off-the-self product (Specification [0206] “org.apache.spark.ml.clustering.GaussianMixture multi-variate mixture datastructure”) to the abstract idea. There are no claimed implementation details of an improved database or data structure. The machine learning and deep learning neural network is claimed at a high level of generality and are merely applied to the abstract idea of the claims. There is no improvement to a computer or technology (including to data structures) and does not apply the abstract idea to a particular machine. The examiner notes that a general purpose computer is flexible—it can do anything it is programmed to do. Therefore, the disclosure of a general purpose computer or a microprocessor as corresponding structure for a software function does nothing to limit the scope of the claim and “avoid pure functional claiming.” Further, the “prohibition against patenting abstract ideas ‘cannot be circumvented by attempting to limit the use of the formula to a particular technological environment’ or adding ‘insignificant postsolution activity.’” Bilski v. Kappos, 561 U.S. 593, 610–11 (2010) (quoting Diamond v. Diehr, 450 U.S. 175, 191–92 (1981)). Further, the claims do no apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment.
Regarding applicant’s arguments directed toward Core Wireless, the examiner disagrees that the present set of claims are analogous to those found in Core Wireless as being patent eligible. Below are pages 9 and 10 on the Core Wireless decision:
The asserted claims in this case are directed to an improved user interface for computing devices, not to the abstract idea of an index, as argued by LG on appeal. Although the generic idea of summarizing information certainly existed prior to the invention, these claims are directed to a particular manner of summarizing and presenting information in electronic devices. Claim 1 of the ’476 patent requires “an application summary that can be reached directly from the menu,” specifying a particular manner by which the summary window must be accessed. The claim further requires the application summary window list a limited set of data, “each of the data in the list being selectable to launch the respective application and enable the selected data to be seen within the respective application.” This claim limitation restrains the type of data that can be displayed in the summary window. Finally, the claim recites that the summary window “is displayed while the one or more applications are in an un-launched state,” a requirement that the device applications exist in a particular state. These limitations disclose a specific manner of displaying a limited set of information to the user, rather than using conventional user interface methods to display a generic index on a computer. Like the improved systems claimed in Enfish, Thales, Visual Memory, and Finjan, these claims recite a specific improvement over prior systems, resulting in an improved user interface for electronic devices. The specification confirms that these claims disclose an improved user interface for electronic devices, particularly those with small screens. It teaches that the prior art interfaces had many deficits relating to the efficient functioning of the computer, requiring a user “to scroll around and switch views many times to find the right data/functionality.” ’020 patent at 1:47–49. Because
small screens “tend to need data and functionality divided into many layers or views,” id. at 1:29–30, prior art interfaces required users to drill down through many layers to get to desired data or functionality. Id. at 1:29–37. That process could “seem slow, complex and difficult to learn, particularly to novice users.” Id. at 1:45–46. The disclosed invention improves the efficiency of using the electronic device by bringing together “a limited list of common functions and commonly accessed stored data,” which can be accessed directly from the main menu. Id. at 2:55–59. Displaying selected data or functions of interest in the summary window allows the user to see the most relevant data or functions “without actually opening the application up.” Id. at 3:53–55. The speed of a user’s navigation through various views and windows can be improved because it “saves the user from navigating to the required application, opening it up, and then navigating within that application to enable the data of interest to be seen or a function of interest to be activated.” Id. at 2:35–39. Rather than paging through multiple screens of options, “only three steps may be needed from start up to reaching the required data/functionality.” Id. at 3:2–3. This language clearly indicates that the claims are directed to an improvement in the functioning of computers, particularly those with small screens. Because we hold that the asserted claims are not directed to an abstract idea, we do not proceed to the second step of the inquiry. The claims are patent eligible under § 101.
As can be seen from the Core Wireless decision, the particular manner of summarizing and presenting information in the application in Core Wireless improved user interfaced for electron devices particularly those with small screen as confirmed by the specification. Specifically, the decision stated that “Claim 1 of the ’476 patent requires “an application summary that can be reached directly from the menu,” specifying a particular manner by which the summary window must be accessed. The claim further requires the application summary window list a limited set of data, “each of the data in the list being selectable to launch the respective application and enable the selected data to be seen within the respective application.” This claim limitation restrains the type of data that can be displayed in the summary window. Finally, the claim recites that the summary window “is displayed while the one or more applications are in an un-launched state,” a requirement that the device applications exist in a particular state. These limitations disclose a specific manner of displaying a limited set of information to the user, rather than using conventional user interface methods to display a generic index on a computer”. In contrast, rather than solving any technological problem, the present claims simply call for displaying certain information in a user interface. See Trading Techs., 2015 WL 774655 at *4 (“If the claims simply provided for ‘setting, displaying, and selecting’ data information, CQG would be correct in its assessment that the claims are directed to an abstract idea”); Trading Techs., 675 F. App’x at 1005 (“ineligible claims generally lack steps or limitations specific to a solution of a problem, or improvement in the functioning of technology”).
With regard to applicant's argument directed toward case law such as CoreWireless, DDR Enfish, Finjan, McRo, Trading Technologies, the cited applications made an improvement to an underlying technology, whereas, the present application used a generic technology and computer to implement an abstract idea. Thus, the cited case law is readily distinguishable from the present claims. As such, the examiner maintains the rejection.
Conclusion
For prior art made of record and not relied upon is considered pertinent to applicant's disclosure see Notice of References Cited items A-E submitted 02/21/2023 used as prior art and in the conclusion section in the office action submitted 02/21/2023.
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 extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Gregory A Pollock whose telephone number is (571) 270-1465. The examiner can normally be reached M-F 8 AM - 4 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abhishek Vyas can be reached on 571 270-1836. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Gregory A Pollock/Primary Examiner, Art Unit 3691
11/10/2025