DETAILED ACTION
Response to Amendment
This Office Action is responsive to Applicant’s arguments and request for reconsideration of application 18/775,388 (07/17/24) filed on 01/28/26.
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 - 5, 7 - 15 and 17 - 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
ALICE/ MAYO: TWO-PART ANALYSIS
2A. First, a determination whether the claim is directed to a judicial exception (i.e., abstract idea).
Prong 1: A determination whether the claim recites a judicial exception (i.e., abstract idea).
Groupings of abstract ideas enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Mathematical concepts- mathematical relationships, mathematical formulas or equations, mathematical calculations.
Certain methods of organizing human activity- 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- concepts performed in the human mind (including an observation, evaluation, judgement, opinion).
Prong 2: A determination whether the judicial exception (i.e., abstract idea) is integrated into a practical application.
Considerations indicative of integration into a practical application enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Improvement to the functioning of a computer, or an improvement to any other technology or technical field
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition
Applying the judicial exception with, or by use of a particular machine.
Effecting a transformation or reduction of a particular article to a different state or thing
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception
Considerations that are not indicative of integration into a practical application enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea.
Adding insignificant extra-solution activity to the judicial exception.
Generally linking the use of the judicial exception to a particular technological environment or field of use.
2B. Second, a determination whether the claim provides an inventive concept (i.e., Whether the claim(s) include additional elements, or combinations of elements, that are sufficient to amount to significantly more than the judicial exception (i.e., abstract idea)).
Considerations indicative of an inventive concept (aka “significantly more”) enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Improvement to the functioning of a computer, or an improvement to any other technology or technical field
Applying the judicial exception with, or by use of a particular machine.
Effecting a transformation or reduction of a particular article to a different state or thing
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception NOTE: The only consideration that does not overlap with the considerations indicative of integration into a practical application associated with step 2A: Prong 2.
Considerations that are not indicative of an inventive concept (aka “significantly more”) enumerated in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea.
Adding insignificant extra-solution activity to the judicial exception.
Generally linking the use of the judicial exception to a particular technological environment or field of use.
Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. NOTE: The only consideration that does not overlap with the considerations that are not indicative of integration into a practical application associated with step 2A: Prong 2.
See also, 2010 Revised Patent Subject Matter Eligibility Guidance; Federal Register; Vol. 84, No. 4; Monday, January 7, 2019
Claims 1 - 5, 7 - 15 and 17 - 20 is/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.
1: Statutory Category
Applicant’s claimed invention, as described in independent claim 11, is/are directed to a process (i.e. a method).
2(A): The claim(s) are directed to a judicial exception (i.e., an abstract idea).
PRONG 1: The claim(s) recite a judicial exception (i.e., an abstract idea).
Mathematical Concepts
The claim recites a mathematical formula or calculation that includes computing at least a correlation coefficient between the first variable and the second variable based on the comparison; generating the correlation matrix as a function of the at least a correlation coefficient; selecting a Levenberg-Marquardt training algorithm; and using the assigned score containing the numerical value indicating the probability of the event occurring. Thus, the claim recites a mathematical concept. Thus, the claim recites an abstract idea.
Certain Method of Organizing Human Activity
The claim as a whole recites a method of organizing human activity. The claimed invention involves processing a plurality of multimodal data associated with a first fungible asset; generating, using a correlation module, a correlation matrix as a function of the plurality of multimodal data, wherein generating the correlation matrix comprises:
comparing a first variable of the plurality of multimodal data to a second variable of the plurality of multimodal data; computing at least a correlation coefficient between the first variable and the second variable based on the comparison, wherein computing the at least a correlation coefficient comprises: updating, using a temporal datum, the first variable and the second variable, wherein the temporal datum is configured to iteratively update one or more values of the first variable and the second variable, wherein the temporal datum comprises at least a timestamp associated with the plurality of multimodal data; iteratively re-computing, using the correlation module, a second correlation coefficient between the updated first variable and the updated second variable; and generating the correlation matrix as a function of the at least a correlation coefficient; generating a prediction module as a function of the correlation matrix using the at least a correlation coefficient generated by the updated correlation module, wherein generating the prediction module comprises using an iteratively trained machine learning model using a plurality of training data as input and selecting a Levenberg-Marquardt training algorithm, wherein the machine learning model is configured to receive the correlation matrix generated as a function of the at least a correlation coefficient using the updated correlation module and output at least an acquisition outline for a second fungible asset, and wherein iteratively training the machine learning model comprises: training the machine learning model using the plurality of training data as input; adjusting one or more connections and one or more weights between nodes in adjacent layers of the machine learning model; and
retraining the machine learning model as a function of the correlations to produce the output layer of the nodes; generating at least an acquisition outline for a second fungible asset using the prediction module, wherein the at least an acquisition outline comprises a purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring;
recommending a procurement strategy using the assigned score containing the numerical value indicating the probability of the event occurring; transmitting the at least an acquisition outline and displaying the recommended procurement strategy, which is a fundamental economic principles or practices (data management (e.g., multimodal data associated with a fungible asset) and analysis (e.g., generating at least an acquisition outline for a second fungible asset/ purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring)); commercial or legal (data management (e.g., multimodal data associated with a fungible asset) and analysis (e.g., generating at least an acquisition outline for a second fungible asset/ purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring)); and managing personal behavior or relationships or interactions between people (processing, generating, comparing, computing, updating, iteratively update, iteratively re-computing, selecting, training, adjusting, retraining, recommending, transmitting, and displaying).
The mere nominal recitation of “at least a processor” does not take the claim out of the method of organizing human activity grouping. Thus, the claim recites an abstract idea.
Mental Processes
The claim recites limitations directed to processing a plurality of multimodal data associated with a first fungible asset; generating, using a correlation module, a correlation matrix as a function of the plurality of multimodal data, wherein generating the correlation matrix comprises: comparing a first variable of the plurality of multimodal data to a second variable of the plurality of multimodal data; computing at least a correlation coefficient between the first variable and the second variable based on the comparison, wherein computing the at least a correlation coefficient comprises: updating, using a temporal datum, the first variable and the second variable, wherein the temporal datum is configured to iteratively update one or more values of the first variable and the second variable, wherein the temporal datum comprises at least a timestamp associated with the plurality of multimodal data; iteratively re-computing, using the correlation module, a second correlation coefficient between the updated first variable and the updated second variable; and generating the correlation matrix as a function of the at least a correlation coefficient; generating a prediction module as a function of the correlation matrix using the at least a correlation coefficient generated by the updated correlation module, wherein generating the prediction module comprises using an iteratively trained machine learning model using a plurality of training data as input and selecting a Levenberg-Marquardt training algorithm, wherein the machine learning model is configured to receive the correlation matrix generated as a function of the at least a correlation coefficient using the updated correlation module and output at least an acquisition outline for a second fungible asset, and wherein iteratively training the machine learning model comprises: training the machine learning model using the plurality of training data as input; adjusting one or more connections and one or more weights between nodes in adjacent layers of the machine learning model; and retraining the machine learning model as a function of the correlations to produce the output layer of the nodes; generating at least an acquisition outline for a second fungible asset using the prediction module, wherein the at least an acquisition outline comprises a purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring; recommending a procurement strategy using the assigned score containing the numerical value indicating the probability of the event occurring; transmitting the at least an acquisition outline and displaying the recommended procurement strategy.
The limitation(s), as drafted, is/are a process that, under it’s broadest reasonable interpretation, covers performance of the limitation(s) in the mind. That is, other than reciting “at least a processor”, nothing in the claim element precludes the steps from practically being performed in the mind. In other words, the claim encompasses the user manually processing a plurality of multimodal data associated with a first fungible asset; generating, using a correlation module, a correlation matrix as a function of the plurality of multimodal data, wherein generating the correlation matrix comprises: comparing a first variable of the plurality of multimodal data to a second variable of the plurality of multimodal data; computing at least a correlation coefficient between the first variable and the second variable based on the comparison, wherein computing the at least a correlation coefficient comprises: updating, using a temporal datum, the first variable and the second variable, wherein the temporal datum is configured to iteratively update one or more values of the first variable and the second variable, wherein the temporal datum comprises at least a timestamp associated with the plurality of multimodal data; iteratively re-computing, using the correlation module, a second correlation coefficient between the updated first variable and the updated second variable; and generating the correlation matrix as a function of the at least a correlation coefficient; generating a prediction module as a function of the correlation matrix using the at least a correlation coefficient generated by the updated correlation module, wherein generating the prediction module comprises using an iteratively trained machine learning model using a plurality of training data as input and selecting a Levenberg-Marquardt training algorithm, wherein the machine learning model is configured to receive the correlation matrix generated as a function of the at least a correlation coefficient using the updated correlation module and output at least an acquisition outline for a second fungible asset, and wherein iteratively training the machine learning model comprises: training the machine learning model using the plurality of training data as input; adjusting one or more connections and one or more weights between nodes in adjacent layers of the machine learning model; and retraining the machine learning model as a function of the correlations to produce the output layer of the nodes; generating at least an acquisition outline for a second fungible asset using the prediction module, wherein the at least an acquisition outline comprises a purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring; recommending a procurement strategy using the assigned score containing the numerical value indicating the probability of the event occurring; transmitting the at least an acquisition outline and displaying the recommended procurement strategy.
The mere nominal recitation of “at least a processor” does not take the claim out of the method of organizing human activity grouping. Thus, the claim recites an abstract idea.
PRONG 2: The judicial exception (i.e., an abstract idea) is not integrated into a practical application.
The claim recites the combination of additional elements of “at least a processor” being used to perform some of the positively recited steps or acts. The claim recites the combination of additional elements of “transmitting” step being “to a downstream device communicatively connected to the at least a processor” and “displaying” step being “on a graphical user interface to the user of the downstream device”. The additional element(s) is/ are recited at a high level of generality (i.e., generic computer functions of (a) data receipt/ transmission (e.g., “transmitting”, etc. step(s) as claimed); (b) data processing (e.g., “processing”, “generating”, “comparing”, “computing”, “updating”, “iteratively update”, “iteratively re-computing”, “selecting”, “training”, “adjusting”, “retraining”, “recommending”, etc. step(s) as claimed); and (c) data display (e.g., “displaying”, etc. step(s) as claimed)). The additional element(s) is/ are recited at a high level of generality (i.e., as general means of gathering multimodal data associated with a first fungible asset), and amounts to mere data gathering, which is a form of insignificant extra-solution activity. The claim is recited at a high level of generality, and merely automates the step(s). Accordingly, the additional element(s) does not integrate the abstract idea into a practical application because it does not impose any meaningful limitations on practicing the abstract idea. The claim is directed to an abstract idea. NOTE: (a) The claim is exclusively from the perspective of “at least a processor”. (b) Although a “downstream device communicatively connected to the at least a processor” is referenced in the claim, the claimed invention is not from the perspective of the “downstream device communicatively connected to the at least a processor” and the “downstream device communicatively connected to the at least a processor” does not perform any of the positively recited steps or acts required. The “downstream device communicatively connected to the at least a processor” merely interacts with the machine (i.e., “at least a processor”) from whose perspective the invention is claimed.
Since the claim(s) recite a judicial exception and fails to integrate the judicial exception into a practical application, the claim(s) is/are “directed to” the judicial exception. Thus, the claim(s) must be reviewed under the second step of the Alice/ Mayo analysis to determine whether the abstract idea has been applied in an eligible manner.
2(B): The claims do not provide an inventive concept (i.e., The claim(s) do not include additional elements, or combinations of elements, that are sufficient to amount to significantly more than the judicial exception (i.e., abstract idea)).
As discussed with respect to Step 2A Prong Two, the additional element(s) in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Furthermore, the additional element(s) under STEP 2A Prong 2 have been evaluated in STEP 2B to determine if it is more than what is well-understood, routine conventional activity in the field. Applicant’s specification as filed 7/17/24 does not provide any indication that the claimed invention incorporates anything other than generic, off-the-shelf computer components. Furthermore, the prosecution history of the instant application provides Williams, US Pat. No. 10,846,651 and Recasens, US Pub. No. 2024/0220891 operating in a similar environment, suggesting performing tasks such as (a) data receipt/ transmission (e.g., “transmitting”, etc. step(s) as claimed); (b) data processing (e.g., “processing”, “generating”, “comparing”, “computing”, “updating”, “iteratively update”, “iteratively re-computing”, “selecting”, “training”, “adjusting”, “retraining”, “recommending”, etc. step(s) as claimed); and (c) data display (e.g., “displaying”, etc. step(s) as claimed) are well understood, routine and conventional. Furthermore, the courts have recognized that computer functions or tasks analogous to those claimed by applicant such as (a) data receipt/ transmission (e.g., “transmitting”, etc. step(s) as claimed); (b) data processing (e.g., “processing”, “generating”, “comparing”, “computing”, “updating”, “iteratively update”, “iteratively re-computing”, “selecting”, “training”, “adjusting”, “retraining”, “recommending”, etc. step(s) as claimed); and (c) data display (e.g., “displaying”, etc. step(s) as claimed) are well understood, routine and conventional. Symantec, TLI, OIP Techs and buySAFE court decisions cited in MPEP § 2106.05(D) (ii) indicate that mere collection or receipt of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as here). Flook, Bancorp court decisions cited in MPEP § 2106.05(D) (ii) indicate performing repetitive calculations is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as here). SAP America Inc. v. Investpic, LLC, 890 F.3d 1016 USPQ2d 1638 (Fed Cir. 2018) (displaying and disseminating financial information) and Intellectual Ventures 1 LLC v. Capital One Bank (USA) (advanced internet interface providing user display access of customized web pages) indicate displaying information is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as here). Accordingly, a conclusion that the additional elements are well-understood, routine, conventional activity is supported under Berkheimer.
For these reasons, there is no inventive concept in the claim, and thus the claim is ineligible.
Dependent claims 12 - 15 and 17 - 20 are rejected as ineligible subject matter under 35 U.S.C. 101 based on a rationale similar to the claims from which they depend.
Alice Corp. also establishes that the same analysis should be used for all categories of claims (e.g., product and process claims). Therefore, independent apparatus claim 1 is/are also rejected as ineligible subject matter under 35 U.S.C. 101 for substantially the same reasons as the method claims. The components (e.g., “memory”, “at least a processor”) described in independent apparatus claim 1, add nothing of substance to the underlying abstract idea. At best, the product (apparatus) recited in the claim(s) are merely providing an environment to implement the abstract idea.
Dependent claims 2 - 5 and 7 - 10 are rejected as ineligible subject matter under 35 U.S.C. 101 based on a rationale similar to the claims from which they depend.
Response to Arguments
Objections
Withdrawn in light of applicant’s arguments and/ or amendments.
101
Applicant's arguments have been fully considered but they are not persuasive.
(1)Applicant argues the claim(s) are not directed to a judicial exception (i.e., an abstract idea).
Mathematical concepts
The claimed invention recites a mathematical concept and is therefore directed to an abstract idea. As noted MPEP § 2106.04(a)(2)(I) states:
It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018) (holding that claims to a ‘‘series of mathematical calculations based on selected information’’ are directed to abstract ideas); Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (holding that claims to a ‘‘process of organizing information through mathematical correlations’’ are directed to an abstract idea); and Bancorp Servs., LLC v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1280, 103 USPQ2d 1425, 1434 (Fed. Cir. 2012) (identifying the concept of ‘‘managing a stable value protected life insurance policy by performing calculations and manipulating the results’’ as an abstract idea.
The claimed invention is an example a mathematical relationship as it involves organizing information and manipulating information through mathematical correlations (e.g., “computing at least a correlation coefficient between the first variable and the second variable based on the comparison …..”; “generating the correlation matrix as a function of the at least a correlation coefficient”; “selecting a Levenberg-Marquardt training algorithm”; and “using the assigned score containing the numerical value indicating the probability of the event occurring”). The claimed invention is an example of a mathematical equation or formula (e.g., “computing at least a correlation coefficient between the first variable and the second variable based on the comparison …..”; “generating the correlation matrix as a function of the at least a correlation coefficient”; “selecting a Levenberg-Marquardt training algorithm”; and “using the assigned score containing the numerical value indicating the probability of the event occurring”). The mathematical calculations or algorithms are used to address issues related to determining an optimal purchase strategy. For example, para. [0001] [0002] of applicant’s specification as filed 07/17/24 states:
[0001] The present invention generally relates to the field of data management and analysis. In particular, the present invention is directed to an apparatus and a method for predicting fungible asset requirement using statistical relationship modeling.
[0002] Existing methods for predicting commodity demand often rely on historical data and basic analytical techniques. These methods may not account for the complex relationships between various factors influencing commodity prices and demand. Current approaches may lack the ability to integrate diverse data sources such as economic indicators, weather patterns, and geopolitical events. This limitation may result in less accurate predictions and suboptimal purchasing strategies, leading to inefficiencies and increased costs.
See also, MPEP § 2106.04(a)(2)(I).
Certain Method of Organizing Human Activity
The claimed invention is directed to certain methods of organizing human activity.
Fundamental economic principles or practices relate to the economy and commerce. The claimed invention encompasses fundamental economic principles or practices as it relates to price optimization and placing an order based on displayed market information (data management (e.g., multimodal data associated with a fungible asset) and analysis (e.g., generating at least an acquisition outline for a second fungible asset/ purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring)). As noted above, the claimed invention is directed to determining an optimal purchase strategy. Furthermore, the acquisition outline for a second fungible asset/ purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring is based on multimodal data associated with a fungible asset.
The claimed invention encompasses commercial or legal interactions. The claimed invention relates to price optimization and placing an order based on displayed market information (data management (e.g., multimodal data associated with a fungible asset) and analysis (e.g., generating at least an acquisition outline for a second fungible asset/ purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring)). Price optimization and placing an order based on displayed market information, in the instant scenario, pertains to agreements in the form of “legal obligations”, “sales activities or behaviors” and “business relations”.
The claimed invention encompasses managing personal behavior or relationships or interactions (e.g., processing, generating, comparing, computing, updating, iteratively update, iteratively re-computing, selecting, training, adjusting, retraining, recommending, transmitting, and displaying, etc.).
See also, MPEP §2106.04(a)(2)(II).
Mental Processes
The claimed invention is directed to mental processes. The claimed invention encompasses observations, evaluations, judgements and opinions (e.g., “processing ….. a plurality of multimodal data associated with a first fungible asset”; “generating ….. at least an acquisition outline for a second fungible asset using the prediction module, wherein the at least an acquisition outline comprises a purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring”; and “recommending a procurement strategy using the assigned score containing the numerical value indicating the probability of the event occurring”) which are examples of mental processes.
Contrary to applicant’s arguments, 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. Similarly, the courts do not distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. Although claims 1 - 5 and 7 - 10 suggest the steps or acts are performed on a computer (i.e., “apparatus” comprising “a memory” and “at least a processor” in apparatus claims 1 - 5 and 7 - 10) and claims 11 - 15 and 17 - 20 suggest using a computer as a tool to perform the steps or acts (i.e., “using at least a processor” in method claims 11 - 15 and 17 - 20), nothing forecloses applicant’s claimed invention from being performed by a human and thus applicant’s claimed invention is still directed to a mental process.
See also, MPEP §2106.04(a)(2)(III).
(2)Applicant argues the judicial exception (i.e., an abstract idea) is integrated into a practical application.
Applicant suggests the claimed invention presents a “practical application” because it provides improvements in the functioning of a computer, or to any other technology or technical field. Examiner disagrees.
Applicant’s arguments suggesting the claimed invention provides improvements in the functioning of a computer, or to any other technology or technical field suggests the applicant believes the technical aspects of the invention are substantial. There exists alternative perspectives however.
As noted above, price optimization and placing an order based on displayed market information is directed to the underlying abstract idea, not the functioning of the computer itself. What applicant is really arguing is the use of a computer as a tool or the benefits of automation itself.
Adding the words “apply it” (or an equivalent) with the judicial exception is not
not indicative of integration into a practical application. See also, MPEP § 2106.05(f). Merely using a computer as a tool to perform an abstract idea; and mere instructions to implement an abstract idea on a computer are not indicative of integration into a practical application. See also, MPEP §2106.05(f).
Contrary to applicant’s arguments, many of the features applicant relies upon are “insignificant”. For example, they amount “selecting a particular data source or type of data to be manipulated” (e.g., “processing, using at least a processor, a plurality of multimodal data associated with a first fungible asset;”). For example, they amount to “necessary data gathering and outputting” (e.g., “transmitting, using the at least a processor, the at least an acquisition outline to a downstream device communicatively connected to the at least a processor”).
Adding insignificant extra-solution activity to the judicial exception is not indicative of integration into a practical application. See also, MPEP §2106.05 (g). Collecting information; analyzing it (e.g., “processing, using at least a processor, a plurality of multimodal data associated with a first fungible asset; generating, using a correlation module, a correlation matrix as a function of the plurality of multimodal data, wherein generating the correlation matrix comprises: comparing a first variable of the plurality of multimodal data to a second variable of the plurality of multimodal data;
computing at least a correlation coefficient between the first variable and the second variable based on the comparison, wherein computing the at least a correlation coefficient comprises: updating, using a temporal datum, the first variable and the second variable, wherein the temporal datum is configured to iteratively update one or more values of the first variable and the second variable, wherein the temporal datum comprises at least a timestamp associated with the plurality of multimodal data;
iteratively re-computing, using the correlation module, a second correlation coefficient between the updated first variable and the updated second variable; and generating the correlation matrix as a function of the at least a correlation coefficient; generating, using the at least a processor, a prediction module as a function of the correlation matrix using the at least a correlation coefficient generated by the updated correlation module, wherein generating the prediction module comprises using an iteratively trained machine learning model using a plurality of training data as input and selecting a Levenberg-Marquardt training algorithm, wherein the machine learning model is configured to receive the correlation matrix generated as a function of the at least a correlation coefficient using the updated correlation module and output at least an acquisition outline for a second fungible asset, and wherein iteratively training the machine learning model comprises: training the machine learning model using the plurality of training data as input; adjusting one or more connections and one or more weights between nodes in adjacent layers of the machine learning model; and
retraining the machine learning model as a function of the correlations to produce the output layer of the nodes; generating, using the at least a processor, at least an acquisition outline for a second fungible asset using the prediction module, wherein the at least an acquisition outline comprises a purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring; recommending a procurement strategy using the assigned score containing the numerical value indicating the probability of the event occurring;”); and displaying certain results of the collection and analysis (e.g., “transmitting, using the at least a processor, the at least an acquisition outline to a downstream device communicatively connected to the at least a processor and displaying the recommended procurement strategy on a graphical user interface to the user of the downstream device.”) merely indicates a field of use or technical environment in which to apply the judicial exception.
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 also, MPEP §2106.05 (h).
(3)Applicant argues the claimed invention provides an inventive concept (i.e., The claim(s) do not include additional elements, or combinations of elements, that are sufficient to amount to significantly more than the judicial exception (i.e., abstract idea)). Applicant argues the claimed invention is not “well-understood, routine or conventional”. Applicant argues the claimed invention is “non-conventional”.
As discussed with respect to Step 2A Prong Two, the additional element(s) in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
Furthermore, the additional element(s) under STEP 2A Prong 2 have been evaluated in STEP 2B to determine if it is more than what is well-understood, routine conventional activity in the field. Applicant’s specification as filed 7/17/24 does not provide any indication that the claimed invention incorporates anything other than generic, off-the-shelf computer components. Furthermore, the prosecution history of the instant application provides Williams, US Pat. No. 10,846,651 and Recasens, US Pub. No. 2024/0220891 operating in a similar environment, suggesting performing tasks such as (a) data receipt/ transmission (e.g., “transmitting”, etc. step(s) as claimed); (b) data processing (e.g., “processing”, “generating”, “comparing”, “computing”, “updating”, “iteratively update”, “iteratively re-computing”, “selecting”, “training”, “adjusting”, “retraining”, “recommending”, etc. step(s) as claimed); and (c) data display (e.g., “displaying”, etc. step(s) as claimed) are well understood, routine and conventional. Furthermore, the courts have recognized that computer functions or tasks analogous to those claimed by applicant such as (a) data receipt/ transmission (e.g., “transmitting”, etc. step(s) as claimed); (b) data processing (e.g., “processing”, “generating”, “comparing”, “computing”, “updating”, “iteratively update”, “iteratively re-computing”, “selecting”, “training”, “adjusting”, “retraining”, “recommending”, etc. step(s) as claimed); and (c) data display (e.g., “displaying”, etc. step(s) as claimed) are well understood, routine and conventional. Symantec, TLI, OIP Techs and buySAFE court decisions cited in MPEP § 2106.05(D) (ii) indicate that mere collection or receipt of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as here). Flook, Bancorp court decisions cited in MPEP § 2106.05(D) (ii) indicate performing repetitive calculations is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as here). SAP America Inc. v. Investpic, LLC, 890 F.3d 1016 USPQ2d 1638 (Fed Cir. 2018) (displaying and disseminating financial information) and Intellectual Ventures 1 LLC v. Capital One Bank (USA) (advanced internet interface providing user display access of customized web pages) indicate displaying information is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as here). Accordingly, a conclusion that the additional elements are well-understood, routine, conventional activity is supported under Berkheimer.
For these reasons, there is no inventive concept in the claim, and thus the claim is ineligible.
Dependent claims 12 - 15 and 17 - 20 are rejected as ineligible subject matter under 35 U.S.C. 101 based on a rationale similar to the claims from which they depend.
Alice Corp. also establishes that the same analysis should be used for all categories of claims (e.g., product and process claims). Therefore, independent apparatus claim 1 is/are also rejected as ineligible subject matter under 35 U.S.C. 101 for substantially the same reasons as the method claims. The components (e.g., “memory”, “at least a processor”) described in independent apparatus claim 1, add nothing of substance to the underlying abstract idea. At best, the product (apparatus) recited in the claim(s) are merely providing an environment to implement the abstract idea.
Dependent claims 2 - 5 and 7 - 10 are rejected as ineligible subject matter under 35 U.S.C. 101 based on a rationale similar to the claims from which they depend.
(4)Applicant argues Example 47
The facts associated with the claimed invention are more aligned with Example 47, claim 2 from the July 2024 Subject Matter Eligibility Examples which were found to be ineligible.
For example, the claimed invention refers to the steps or acts being performed “using at least a processor”. This language is very similar to the “at a computer” and “by the computer” language recited in Example 47, claim 2. In Example 47, claim 2 this language was considered to be recited at a high level of generality i.e., as a generic computer performing generic computer functions.
For example, the claimed invention refers to “generating ….. a prediction module as a function of the correlation matrix using the at least a correlation coefficient generated by the updated correlation module, wherein generating the prediction module comprises using an iteratively trained machine learning model using a plurality of training data as input and selecting a Levenberg-Marquardt training algorithm, wherein the machine learning model is configured to receive the correlation matrix generated as a function of the at least a correlation coefficient using the updated correlation module and output at least an acquisition outline for a second fungible asset, and wherein iteratively training the machine learning model comprises: training the machine learning model using the plurality of training data as input; adjusting one or more connections and one or more weights between nodes in adjacent layers of the machine learning model; and retraining the machine learning model as a function of the correlations to produce the output layer of the nodes; generating ….. at least an acquisition outline for a second fungible asset using the prediction module, wherein the at least an acquisition outline comprises a purchase schedule of a plan for fungible asset procurement and an assigned score containing a numerical value indicating the probability of an event occurring;” This language is very similar to the “using the trained ANN” and “outputting the anomaly data from the trained ANN” recited in Example 47, claim 2. In Example 47, claim 2 this language was determined not to provide any details about how the trained artificial neural network (ANN) operates and merely provided a generic output.
Adding insignificant extra-solution activity to the judicial exception is not indicative of integration into a practical application. See also, MPEP §2106.05 (g).
Mere instructions to implement an abstract idea on a computer, merely using a computer as a tool to perform an abstract idea or an equivalent of an “apply it” rational are not indicative of integration into a practical application. See also, MPEP §2106.05 (f).
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 also, MPEP §2106.05 (h).
112
Withdrawn in light of applicant’s arguments and/ or amendments.
Conclusion
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.
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SARA CHANDLER HAMILTON
Primary Examiner
Art Unit 3695
/SARA C HAMILTON/Primary Examiner, Art Unit 3695