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 .
Examiner’s Note
In regards to the 35 USC § 103 rejection, has been withdrawn in light of the instant amendments to the claims, see Allowable Subject Matter section.
Response to Arguments
Applicant's arguments filed 11/25/2025 ("Arguments/Remarks") have been fully considered but they are not persuasive.
Argument – 1: (page: 12) Applicant contends: “Applicant respectfully submits that one of ordinary skill in the art recognizes that the rejected claims recite a clear and specific improvement in current technology. Improving the capability of a machine learning model to process inputs that may be beyond current capacity in a computer's relational database management system and reducing power and memory consumption by the computer at least are clear and specific improvements that direct patent eligibility under Pathway A streamlined analysis. The Pathway B analysis of the Office Action is therefore not required or applicable.”
Regarding the above argument, the Examiner respectfully notes that, per MPEP 2106.06 Streamlined Analysis, the Examiner may use a streamlined eligibility analysis (Pathway A) when a claim’s eligibility is self-evident, such as when the claim clearly improve a technology or computer functionality. If there is any doubt that the claim might be directed to a judicial exception, which the rejected claim is, the Examiner must perform the full eligibility analysis under MPEP 2106 (i.e.: Step 2A and if needed, Step 2B) to determine whether the claim integrates the exception into a practical application or recites significantly more.
Argument – 2: (page: 12) Applicant contends: “Arguendo, even if one only looks at the features the Office Action asserts in Pathway B analysis to be steps that can be performed in the human mind, the Office Action appears to ignore that the USPTO August 04, 2025 Memorandum on "evaluating subject matter eligibility of claims under 35 U.S.C. 101" reminds "not to expand [the mental processes] grouping in a manner that encompasses claim limitations that cannot practically be performed in the human mind." One of ordinary skill in the art recognizes that a human mind cannot process - and certainly not in real time thousands of coded inputs commonly received by a machine learning model.”
Regarding the above argument, the Examiner respectfully notes that the August 2025 memorandum provides reminders of existing policy, which reminders the Examiner to carefully distinguish between claim limitations that merely involve a judicial exception versus these that recite an exception. It states that it is not intended to announce any new subject matter evaluation. The analysis in the office action is consistent with the USPTO’s August 2025 memorandum. In addition, The Examiner emphasize that, steps of: receiving, in an artificial intelligence predictive system, the set of inputs for storage …, is not classified as a mental process, these steps are directed to mere data gathering as deemed insufficient to transform the judicial exception because claimed elements are considered insignificant extra-solution activity, under Step 2A, prong 2.
Argument – 3: (page: 12 – 13) Applicant contends: “But even if recited features might be considered abstract, the rejected claims recite features that are patent eligible at Prong Two of Step 2A of the Alice/Mayo because they are directed to a practical application. The features recited in the rejected claims provide the practical application of updating a machine learning model in real time through a novel process and utilization of structured query language tables in a relational database that reduces consumption of computer storage resources and improves an accuracy of a predictive output.”
Regarding the above argument, the Examiner respectfully notes that the amended claims do not recite sufficient technical details to establish that the claimed feature provide a technological improvement. While the claims generally assert reduced consumption of computer storage resources and improved accuracy of a predictive output, they fail to specify how the one or more groups of correlated features are determined based on pairwise correlations. In particular, the claim do not describe the process or method used to select which representative features are stored, do not explain specific operations used to prioritize disjointed groups and do not define how the number of groups is constrained by the number of available columns in the table. To determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art: "reduces consumption of computer storage resources and improves an accuracy of a predictive output"), the Examiner should not determine the claim improves technology, See (MPEP 2106.04(d)(1)).
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.
Claim(s) 1 – 20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1, in step 1 of the 101-analysis set forth in MPEP 2106, the claims recite a series of steps feature management platform. A process is one of the four statutory categories of invention.
In step 1 of the 101-analysis set forth in the MPEP 2106, the examiner has determined
that the following limitations recite a process that, under the broadest reasonable interpretation, falls within one or more statutory categories
In step 2A, prong 1 of the 101-analysis set forth in the MPEP 2106, the examiner has determined
that the following limitations recite a process that, under the broadest reasonable interpretation, recites a judicial exception (mental process) but for recitation of generic computer
components (machine learning model).
creating, based on the values of the features, pairwise correlations of the feature vector in each input in the set of features;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation and judgment and could be performed on human mind or using pen and paper, for example: from a list of features, a person could reasonably identify which of the features are related to each other).
limiting the set of inputs by establishing a number of groups of correlated features of the set of features based on the pairwise correlations, while prioritizing disjoint groups
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation, and judgment could be performed on human mind or using pen and paper, for example: from a list of features, a person could reasonably categorize or organize which of the features are related to each other and group them accordingly, while giving significance to groups with unique (disjointed) features.)
concatenating vector predictions to columns in the correlation table and assigning correlations between the values of each feature of the groups of features and a set of prediction values of the machine learning model encoding vector predictions and forming prediction correlations;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could observe the structure of the correlation table and the vector predictions, evaluate the relationships and values to make a decision how to combine or align them.)
selecting from each group a representative feature based on the prediction correlations that represents all of the features of the set of inputs for the each group:
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation, and judgment could be performed on human mind or using pen and paper, for example: a person could observe the predictions and make a judgement to choose representative from each group based on prediction correlations.)
If the claim limitations, under their broadest reasonable interpretation, covers performance of the limitations as a mental process, but for the recitation of generic computer components, then it falls within the mental process. Accordingly, the claim recites an abstract idea.
In step 2A, prong 2 of the 101-analysis set forth in MPEP 2106, in addition to the generic
computer components identified above; the examiner has determined that the additional elements do not integrate this judicial exception into a practical application.
The preamble is insufficient to transform the judicial exception to a patentable invention because the preamble recites limitation which does not amount to more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer.
receiving, in an artificial intelligence predictive system, the set of inputs for storage in a table in a relational database management system associated with the machine learning model each input of the set of inputs comprising, respectively, a feature vector comprising a number of values of a set of features;
(i.e.: deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation directed to mere data gathering as deemed insufficient to transform the judicial exception because claimed elements are considered insignificant extra-solution activity, See MPEP (2106.05(g))).
by applying an algorithm code snippet acting on columns in a correlation table,
(i.e.: deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation which does not amount to more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer. See MPEP 2106.05(f)).
wherein the number of groups of correlated features is based upon the storage capacity and do not exceed a number of columns available in the table.
(i.e.: deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation generally links the use of a judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)).
reducing memory usage and preventing overloading the storage capacity in the machine learning model by, instead of storing all of the set of inputs, storing only representative feature for each group in the table with a prediction from the machine learning model associated with the representative feature
(i.e.: deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation directed to mere data gathering as deemed insufficient to transform the judicial exception because claimed elements are considered insignificant extra-solution activity, See MPEP (2106.05(g))).
In Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. MPEP 2106.05.
First, the additional limitation (II), recite mere application of the abstract idea or mere instructions to implement an abstract idea on a computer are deemed insufficient to transform the judicial exception to a patentable invention because the limitations generally apply the use of a generic computer and/or process with the judicial exception, see MPEP 2106.05(f).
Second, the additional limitation (III) considered insufficient to transform the judicial exception to a patentable invention because they generally link the judicial exception to the technology environment, see MPEP 2106.05(h).
Third, the additional limitation (I), considered extra/post solution activity, as analyzed above, are activity that are well-understood routine and conventional, specifically: the courts have recognized the computer functions as well‐understood, routine, and conventional functions.
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TL| Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). See MPEP 2106.05(d)(II).
Fourth, the additional limitation (IV), additional elements considered extra/post solution activity, as analyzed above, are activity that are well-understood routine and conventional, specifically: the courts have recognized the computer functions as well‐understood, routine, and conventional functions.
Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;
As analyzed above, the additional elements, analyzed above, do not integrate the noted judicial exception into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore, the claim is directed to an abstract idea.
Regarding claim 10,
The rest of the limitations recite similar subject matter as claim 1, so is rejected under the same rationale.
in real-time monitor and validate performance of and overcome inputs that exceed a storage capacity of a machine learning model,
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation and judgment and could be performed on human mind or using pen and paper, for example: a person could monitor model’s performance, identify when an input exceeds storage limit and decide how to reduce or split the input.)
If the claim limitations, under their broadest reasonable interpretation, covers performance of
the limitations as a mental process, but for the recitation of generic computer components, then it falls within the mental process. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 of the 101-analysis, set forth in MPEP 2106, the examiner has determined that
the following additional elements do not integrate this judicial exception into a practical application:
A system, wherein the system comprises comprising: a computer memory that comprises a structured query language; and a processor coupled to the computer memory, the processor configured to:
Deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation which does not amount to more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer. See MPEP 2106.05(f)).
reduce power consumption of the processor, and reduce memory consumption in the processor;
Deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation which does not amount to more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer. See MPEP 2106.05(f)).
Regarding claim 16,
The rest of the limitations recite similar subject matter as claim 1, so is rejected under the same rationale.
monitor and validate performance of and overcome inputs that exceed a storage capacity of a machine learning model in the computer program product;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation and judgment and could be performed on human mind or using pen and paper, for example: a person could monitor model’s performance, identify when an input exceeds storage limit and decide how to reduce or split the input.)
If the claim limitations, under their broadest reasonable interpretation, covers performance of
the limitations as a mental process, but for the recitation of generic computer components, then it falls within the mental process. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2 of the 101-analysis, set forth in MPEP 2106, the examiner has determined that
the following additional elements do not integrate this judicial exception into a practical application:
A computer program product, wherein the computer program product comprises a computer readable storage medium that comprises program instructions embodied therewith, wherein the program instructions are configured to execute, by a computer, that cause the computer to:
Deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation which does not amount to more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer. See MPEP 2106.05(f)).
reduce power consumption of the processor, and reduce memory consumption in the processor;
Deemed insufficient to transform the judicial exception to a patentable invention because the claim recites limitation which does not amount to more than a recitation of the words "apply it" (or an equivalent), such as mere instructions to implement an abstract idea on a computer. See MPEP 2106.05(f)).
Regarding claim(s) 2 and 11 fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
wherein: the table is a structured query language table comprising 21 columns and the set of inputs comprises thousands of rows of data;
The recitation in the additional limitation simply links the judicial exception to a field of use and/or technology environment, see MPEP 2106.05(h).
Limitations directed to field of use cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim(s) 3, 12 and 18 fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
selecting an additional representative feature from a group when the number of groups is less than the number of columns available in the table;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of evaluation and judgment and could be performed on human mind or using pen and paper, for example: given a table of data with multiple columns (features), a person could manually group correlated features, count the number of groups, compare it to the number of columns and choose an additional feature to represent a group).
arranging the set of features in accordance with a predefined order; and
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation and judgment could be performed on human mind or using pen and paper, for example: a person could reasonably arrange a list of features based on a predefined order.)
iteratively processing each feature of the set of features according to the predefined order, wherein, for each feature, the processing includes determining whether the feature is part of any group of the one or more groups.
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could reasonably determine if a feature is part of any group.)
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 or are sufficient to
amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim(s) 4, 13 and 19 fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
determining that a feature in the set of features is not part of any group of the one or more groups;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could reasonably determine if a feature is not part of any group.)
in response to determining that the feature is not part of any group, searching one or more features having an order higher than the order of the feature and having a correlation that is with the feature and that is higher than a predefined threshold; and
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could reasonably determine, for feature sets, a threshold having higher than a predefined value.)
forming a group from the one or more features.
(i.e.: the broadest reasonable interpretation includes a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could reasonably form a group for sets of features.)
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 or are sufficient to
amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim(s) 5 and 20 fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
the number of columns available in the table being selected to be a number less than a number of unused columns in the table;
The recitation in the additional limitation simply links the judicial exception to a field of use and/or technology environment, see MPEP 2106.05(h).
Limitations directed to field of use cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
selecting a most correlated feature as the representative feature of all of the features of the set of inputs for the each group.
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could review input features, calculate or estimate correlation and select the most correlated feature as the representative of a group.)
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim(s) 6 and 14 fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
receiving a new input;
The recitation in the additional limitation directed to mere data gathering as deemed insufficient to transform the judicial exception because claimed elements are considered insignificant extra-solution activity and well-understood routine and conventional (2106.05(d)).
Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TL| Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). See MPEP 2106.05(d)(II).
The additional limitations as analyze failed to integrate a judicial exception into a practical application at Step 2A and provide an inventive concept in Step 2B, per the analysis above.
processing, via the machine learning model, the new input, the processing resulting in a new prediction;
Deemed insufficient to transform the judicial exception to a patentable invention because the limitation is directed to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and are considered to adding the words “apply it” (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to using the computer as a tool for implementing an abstract idea cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
selecting, representative features of the new input; and
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could review new input features, and select a representative feature.)
using a python function
Deemed insufficient to transform the judicial exception to a patentable invention because the limitation is directed to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and are considered to adding the words “apply it” (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to using the computer as a tool for implementing an abstract idea cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
the machine learning model deriving, using a python code, the prediction from the representative features
Deemed insufficient to transform the judicial exception to a patentable invention because the limitation is directed to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and are considered to adding the words “apply it” (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to using the computer as a tool for implementing an abstract idea cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 7 fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
selected representative features of the new input are stored in a database having a maximum storage size;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could select representative features from a new input and record them in a log or file with a known size limit.)
the method further comprises determining that a number of a set of features of the new input is greater than the maximum storage size.
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could recognize that the number of input features exceeds the storage limit.)
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 8, fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
using the representative feature for each group in a database with the prediction from the machine learning model associated with the representative feature for updating the machine learning model.
Deemed insufficient to transform the judicial exception to a patentable invention because the limitation is directed to mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and are considered to adding the words “apply it” (or an equivalent) with the judicial exception, See MPEP 2106.05(f).
Limitations directed to using the computer as a tool for implementing an abstract idea cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 9, fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
wherein the storing of the selected representative features of the new input is performed in response to the determining that the number of the set of features of the new input is greater than the maximum storage size.
The recitation in the additional limitation simply links the judicial exception to a field of use and/or technology environment, see MPEP 2106.05(h).
Limitations directed to field of use cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 15, fails to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
selected representative features of the new input are stored in a database having a maximum storage size;
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could select representative features from a new input and record them in a log or file with a known size limit.)
the method further comprises determining that a number of a set of features of the new input is greater than the maximum storage size; and the selecting of the selected representative features of the new input and the storing of the selected representative features of the new input are performed in response to the determining that the number of the set of features of the new input is greater than the maximum storage size.
(i.e.: the broadest reasonable interpretation, the claim recites abstract idea: mental process: it involves a step of observation, evaluation and judgment could be performed on human mind or using pen and paper, for example: a person could recognize that the number of input features exceeds a storage limit, then decide which features to keep and write then down 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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Regarding claim 17, fail to resolve the deficiencies identified above by integrating the judicial exception into a practical application, or introducing significantly more than the judicial exception. The claim recites:
wherein: the computer program product is further configured to serve an artificial intelligence predictive system: and the one or more groups are disjoint groups.
The recitation in the additional limitation simply links the judicial exception to a field of use and/or technology environment, see MPEP 2106.05(h).
Limitations directed to field of use cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B.
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 or are sufficient to amount to significantly more than the judicial exception. The claim is not patent eligible.
Allowable subject matter
Claim(s) 1 – 20 would be allowable if rewritten or amended to overcome the rejection under 35 U.S.C. 101 set forth in this Office action. The following is a statement of reasons for the indication of allowable subject matter:
Claim(s) 1, 10 and 16 as a whole with regards to technical features recited by the claim limitations including directed to:
A method for reducing power consumption and memory usage in a system evaluating performance of a machine learning model and preventing a set of inputs from overloading a storage capacity in the machine learning model, the method comprising, in real-time:
receiving, in an artificial intelligence predictive system, the set of inputs for storage in a table in a relational database management system associated with the machine learning model, each input of the set of inputs comprising, respectively, a feature vector comprising a number of values of a set of features;
creating, based on the values of the features, pairwise correlations of the feature vector in each input in the set of features;
limiting the set of inputs by establishing a number of groups of correlated features of the set of features based on the pairwise correlations while prioritizing disjoint groups by applying an algorithm code snippet acting on columns in a correlation table, wherein the number of groups of correlated features is based upon the storage capacity and does not exceed a number of columns available in the table;
concatenating vector predictions to columns in the correlation table and assigning correlations between the values of each feature of the groups of features and a set of prediction values of the machine learning model, encoding vector predictions and forming prediction correlations;
selecting from each group a feature based on the prediction correlations that represents all of the features of the set of inputs for the each group; and reducing memory usage and preventing overloading the storage capacity in the machine learning model by, instead of storing all of the set of inputs, storing only the representative feature for each group in the table with a prediction from the machine learning model associated with the representative feature.
The closest prior art(s):
Zhou et al., Pub. No.: US20170270427A1, (2016-03-17).
Zhou proposed analyzing historical inputs from a user and the outputs given in response. This involves gathering features from these inputs, which are identified based on the context related to the user. The features are divided into several groups, and associations are determined based on these groups, focusing on correlations between different groups rather than within a single group. This approach helps reduce the time and computational complexity needed to establish these associations. However, Zhou does not teach: determining a number of correlated features from the set of features based on pairwise correlations, while prioritizing disjoint groups, wherein the number of groups does not exceed the number of columns available in the table and determining prediction correlations between the values of each feature within the groups and a set of prediction values of the machine learning model, thus forming prediction correlations.
Li, et al., “Feature Selection”, (2017)
The article reviews recent research advances, focusing on various feature selection algorithms for different data types. It categorizes these algorithms into four groups: similarity-based, information-theoretical-based, sparse-learning-based, and statistical-based methods. However, Li does not teach: determining a number of correlated features from the set of features based on pairwise correlations, while prioritizing disjoint groups, wherein the number of groups does not exceed the number of columns available in the table and determining prediction correlations between the values of each feature within the groups and a set of prediction values of the machine learning model, thus forming prediction correlations.
Shivashankar et al., Pub. No.: US9912523B2, (2015).
Shivashankar teaches selecting an attribute group from a second subset and obtaining values for each logical connection between this group and another group in a first subset. Using these values, along with a generated correlation value, it determines whether to assign a label to the selected group. If a label is needed, it assigns it and repeats this process for each group in the second subset. However, Shivashankar does not teach: determining a number of correlated features from the set of features based on pairwise correlations, while prioritizing disjoint groups, wherein the number of groups does not exceed the number of columns available in the table and determining prediction correlations between the values of each feature within the groups and a set of prediction values of the machine learning model, thus forming prediction correlations.
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 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.
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/M.T.M./ Examiner, Art Unit 2148
/MICHELLE T BECHTOLD/ Supervisory Patent Examiner, Art Unit 2148