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 .
This is a Final Office Action in response to application 17/879,489 entitled "SYSTEMS AND METHODS FOR VEHICLE DAMAGE IDENTIFICATION AND INSURANCE CLAIM PROCESSING" filed on March 17, 2025, with claims 1, 3-8, 11-15, and 17- 20 pending.
Status of Claims
Claims 1, 8, 12 and 15 have been amended and are hereby entered.
Claims 2, 9, 16, and 21 were previously cancelled.
Claims 1, 3-8, 11-15, and 17- 20 are pending and have been examined.
Response to Amendment
The amendment filed April 20, 2026, has been entered. Claims 1, 3-8, 11-15, and 17- 20 remain pending in the application. Applicant’s amendments to the Specification, Drawings, and/or Claims have been noted in response to the Non-Final Office Action mailed December 19, 2025.
Information Disclosure Statements
The information disclosure statements (IDSs) submitted on September 25, 2023; March 13, 2023; February 22, 2023; October 20, 2022; August 5, 2022; and January 29, 2024, are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the Examiner.
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, 3-8, 11-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see MPEP 2106 for additional information regarding Patent Subject Matter Eligibility Guidance.
Claims 1, 3-8, 11-15, and 17- 20 are directed to a system, method/process, machine/apparatus, or composition of matter, which are/is one of the statutory categories of invention. (Step 1: YES).
The claimed invention is directed to an abstract idea without significantly more.
Independent Claim 1 recites:
“A …method for processing insurance claims, the method comprising:
receiving, …and during a period, an indication of damage to an article caused by a particular weather event, wherein the indication specifies a particular location of the article where the damage to the article occurred;
selecting, from a model …a first instance of a weather-based damage prediction model, wherein the weather-based damage prediction model was …based on one or more historical weather events that occurred proximate to the particular location and indications of damage to a plurality of articles determined to be caused by the one or more historical weather events;
receiving, from the selected first instance of the weather-based damage prediction model, a first damage prediction that indicates a type and severity of damage caused by the particular weather event to the article;
communicating, to the first user … instructions that cause the first user …for indicating damage to the article and to pre-populate the one or more fields based on the first damage prediction;
after receiving, during the period and from one or more other user ….a threshold number of indications of damage to one or more other articles caused by the particular weather event, generating a second instance of the weather-based damage prediction model that is distinct from the first instance of the weather-based damage prediction model, wherein the second instance of the weather-based damage prediction model is trained specifically for the particular weather event using the threshold number of indications of damage received from the one or more other user computing devices and has a higher prediction accuracy than the first instance of the weather-based damage prediction model for predicting damage caused by the particular weather event;
…the second instance of the weather-based damage prediction model based on characteristics of the particular weather event and the respective indications of damage received from the respective user …
after…the second instance of the weather-based damage prediction model receiving, from a second user … and during the period, an indication of damage to an article caused by the particular weather event;
and communicating, to the second user … and based on a second damage prediction generated …second instance of the weather-based damage prediction model, instructions that cause the second user …. for indicating damage to the article and to pre-populate the one or more fields based on the second damage prediction.”
These limitations clearly relate to storm damage prediction modeling. These limitations, under their broadest reasonable interpretation, covers performance of the limitation as mental processes but for the recitation of generic computer components. For example, “receiving.... an indication of damage to an article” and “selecting....a first instance of a weather-based damage prediction model” encompasses a person simply determining or deciding the best statistical model relating to storm damage insurance claims. “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea… 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 (e.g., pen and paper or a slide rule) to perform the claim limitation… Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, ‘[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind.’”, see MPEP 2106 – III. MENTAL PROCESSES. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a one that a person may perform by thinking then it falls within the “Mental Processes” grouping of abstract ideas. (Step 2A-Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
[computer-implemented][from a first user computing device][database][computing device][computing devices]:
merely applying computer processing, storage, and networking technology as tools to perform an abstract idea
[previously trained] [re-training] [by the re-trained]:
merely applying machine learning technology as a tool to perform an abstract idea
[to generate a user interface that comprises one or more fields]:
generally linking to the judicial exception of user interface design
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For example, the Applicant’s Specification reads,
“[0036] the components of the provider computing system 102. In some embodiments, the input/output circuit 124 includes any combination of hardware components, communication circuitry, and machine-readable media … [0037] The customer device 104 is a device (e.g., mobile device, laptop computer, desktop computer, tablet, smart device, public computer, etc.) that a customer of the insurance provider may use to access insurance provider resources (e.g., applications, databases, account information, websites, etc.)”.
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, Claim 1 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. The claim further defines the abstract idea and hence is abstract for the reasons presented above. The claim does not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination.
For the [to generate a user interface that comprises one or more fields] step that was considered extra-solution activity and determined to be well-understood, routine, conventional activity in the field, the background does not provide any indication that the network appliance is anything other than a generic, off-the-shelf computer user interface component that is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
MPEP 2106.04(a)(2)(C) - A Claim That Requires a Computer May Still Recite a Mental Process: Using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. … 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of “anonymous loan shopping”, which was a concept that could be “performed by humans without a computer.” 811 F.3d. at 1324, 117 USPQ2d at 1699. … The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53.
For these reasons, there is no inventive concept. The claims are not patent eligible. Therefore, the claim is directed to an abstract idea. Thus, the claim is not patent eligible. (Step 2B: NO. The claim does not provide significantly more)
Dependent Claims recite additional elements.
This judicial exception is not integrated into a practical application. In particular, the recited additional elements of
Claim 3:
“computer-implemented”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 4:
“computer-implemented”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: generally linking to machine learning and artificial intelligence a means to perform an abstract idea
Claim 5:
“computer-implemented”, “computing device”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“to generate the user interface”: generally linking to user interface design a means to perform an abstract idea
Claim 6:
“computer-implemented”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 7:
“computer-implemented”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: generally linking to machine learning and artificial intelligence a means to perform an abstract idea
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, the claim is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Dependent claims further define the abstract idea that is present in their respective independent claims and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the dependent claims are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Independent Claim 8 recites:
“…comprising:
receiving, …and during a period, an indication of damage to an article caused by a particular weather event, wherein the indication specifies a particular location of the article where the damage to the article occurred;
selecting, from a model …a first instance of a weather-based damage prediction model, wherein the weather-based damage prediction model was …based on one or more historical weather events that occurred proximate to the particular location and indications of damage to a plurality of articles determined to be caused by the one or more historical weather events;
receiving, from the selected first instance of the weather-based damage prediction model, a first damage prediction that indicates a type and severity of damage caused by the particular weather event to the article;
communicating, to the first user … instructions that cause the first user …for indicating damage to the article and to pre-populate the one or more fields based on the first damage prediction;
after receiving, during the period and from one or more other user ….a threshold number of indications of damage to one or more other articles caused by the particular weather event, generating a second instance of the weather-based damage prediction model that is distinct from the first instance of the weather-based damage prediction model, wherein the second instance of the weather-based damage prediction model is trained specifically for the particular weather event using the threshold number of indications of damage received from the one or more other user computing devices and has a higher prediction accuracy than the first instance of the weather-based damage prediction model for predicting damage caused by the particular weather event;
…the second instance of the weather-based damage prediction model based on characteristics of the particular weather event and the respective indications of damage received from the respective user …
after…the second instance of the weather-based damage prediction model receiving, from a second user … and during the period, an indication of damage to an article caused by the particular weather event;
and communicating, to the second user … and based on a second damage prediction generated …second instance of the weather-based damage prediction model, instructions that cause the second user …. for indicating damage to the article and to pre-populate the one or more fields based on the second damage prediction.”
These limitations clearly relate to storm damage prediction modeling. These limitations, under their broadest reasonable interpretation, covers performance of the limitation as mental processes but for the recitation of generic computer components. For example, “receiving.... an indication of damage to an article” and “selecting....a first instance of a weather-based damage prediction model” encompasses a person simply determining or deciding the best statistical model relating to storm damage insurance claims. “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea… 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 (e.g., pen and paper or a slide rule) to perform the claim limitation… Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, ‘[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind.’”, see MPEP 2106 – III. MENTAL PROCESSES. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a one that a person may perform by thinking then it falls within the “Mental Processes” grouping of abstract ideas. (Step 2A-Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
[A computing system, comprising: one or more processors; and one or more storage devices that store instruction code executable by the one or more processors to cause the computing system to perform operations] [from a first user computing device][database][computing device][computing devices]:
merely applying computer processing, storage, and networking technology as tools to perform an abstract idea
[previously trained] [re-training] [by the re-trained]:
merely applying machine learning technology as a tool to perform an abstract idea
[to generate a user interface that comprises one or more fields]:
generally linking to the judicial exception of user interface design
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, Claim 8 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. The claim further defines the abstract idea and hence is abstract for the reasons presented above. The claim does not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination.
For the [to generate a user interface that comprises one or more fields] step that was considered extra-solution activity and determined to be well-understood, routine, conventional activity in the field, the background does not provide any indication that the network appliance is anything other than a generic, off-the-shelf computer user interface component that is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
MPEP 2106.04(a)(2)(C) - A Claim That Requires a Computer May Still Recite a Mental Process: Using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. … 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of “anonymous loan shopping”, which was a concept that could be “performed by humans without a computer.” 811 F.3d. at 1324, 117 USPQ2d at 1699. … The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53.
For these reasons, there is no inventive concept. The claims are not patent eligible. Therefore, the claim is directed to an abstract idea. Thus, the claim is not patent eligible. (Step 2B: NO. The claim does not provide significantly more)
Dependent Claims recite additional elements.
This judicial exception is not integrated into a practical application. In particular, the recited additional elements of
Claim 11:
“computing”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 12:
“computing”, “computing device”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“to generate the user interface”: generally linking to user interface design a means to perform an abstract idea
Claim 13:
“computing”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 14:
“computing”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: generally linking to machine learning and artificial intelligence a means to perform an abstract idea
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For example, the Applicant’s Specification reads, “[0036] the components of the provider computing system 102. In some embodiments, the input/output circuit 124 includes any combination of hardware components, communication circuitry, and machine-readable media … [0037] The customer device 104 is a device (e.g., mobile device, laptop computer, desktop computer, tablet, smart device, public computer, etc.) that a customer of the insurance provider may use to access insurance provider resources (e.g., applications, databases, account information, websites, etc.)”. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, the claim is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Dependent claims further define the abstract idea that is present in their respective independent claims and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the dependent claims are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Independent Claim 15 recites:
“…comprising:
receiving, …and during a period, an indication of damage to an article caused by a particular weather event, wherein the indication specifies a particular location of the article where the damage to the article occurred;
selecting, from a model …a first instance of a weather-based damage prediction model, wherein the weather-based damage prediction model was …based on one or more historical weather events that occurred proximate to the particular location and indications of damage to a plurality of articles determined to be caused by the one or more historical weather events;
receiving, from the selected first instance of the weather-based damage prediction model, a first damage prediction that indicates a type and severity of damage caused by the particular weather event to the article;
communicating, to the first user … instructions that cause the first user …for indicating damage to the article and to pre-populate the one or more fields based on the first damage prediction;
after receiving, during the period and from one or more other user ….a threshold number of indications of damage to one or more other articles caused by the particular weather event, generating a second instance of the weather-based damage prediction model that is distinct from the first instance of the weather-based damage prediction model, wherein the second instance of the weather-based damage prediction model is trained specifically for the particular weather event using the threshold number of indications of damage received from the one or more other user computing devices and has a higher prediction accuracy than the first instance of the weather-based damage prediction model for predicting damage caused by the particular weather event;
…the second instance of the weather-based damage prediction model based on characteristics of the particular weather event and the respective indications of damage received from the respective user …
after…the second instance of the weather-based damage prediction model receiving, from a second user … and during the period, an indication of damage to an article caused by the particular weather event;
and communicating, to the second user … and based on a second damage prediction generated …second instance of the weather-based damage prediction model, instructions that cause the second user …. for indicating damage to the article and to pre-populate the one or more fields based on the second damage prediction.”
These limitations clearly relate to storm damage prediction modeling. These limitations, under their broadest reasonable interpretation, covers performance of the limitation as mental processes but for the recitation of generic computer components. For example, “receiving.... an indication of damage to an article” and “selecting....a first instance of a weather-based damage prediction model” encompasses a person simply determining or deciding the best statistical model relating to storm damage insurance claims. “The courts consider a mental process (thinking) that ‘can be performed in the human mind, or by a human using a pen and paper’ to be an abstract idea… 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 (e.g., pen and paper or a slide rule) to perform the claim limitation… Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer. As the Federal Circuit has explained, ‘[c]ourts have examined claims that required the use of a computer and still found that the underlying, patent-ineligible invention could be performed via pen and paper or in a person’s mind.’”, see MPEP 2106 – III. MENTAL PROCESSES. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a one that a person may perform by thinking then it falls within the “Mental Processes” grouping of abstract ideas. (Step 2A-Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
[A non-transitory computer readable medium having computer- executable instructions embodied therein that, when executed by one or more processors of a computing system, cause the computing system to perform operations] [from a first user computing device][database][computing device][computing devices]:
merely applying computer processing, storage, and networking technology as tools to perform an abstract idea
[previously trained] [re-training] [by the re-trained]:
merely applying machine learning technology as a tool to perform an abstract idea
[to generate a user interface that comprises one or more fields]:
generally linking to the judicial exception of user interface design
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, Claim 15 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. The claim further defines the abstract idea and hence is abstract for the reasons presented above. The claim does not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination.
For the [to generate a user interface that comprises one or more fields] step that was considered extra-solution activity and determined to be well-understood, routine, conventional activity in the field, the background does not provide any indication that the network appliance is anything other than a generic, off-the-shelf computer user interface component that is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
MPEP 2106.04(a)(2)(C) - A Claim That Requires a Computer May Still Recite a Mental Process: Using a computer as a tool to perform a mental process. An example of a case in which a computer was used as a tool to perform a mental process is Mortgage Grader, 811 F.3d. at 1324, 117 USPQ2d at 1699. The patentee in Mortgage Grader claimed a computer-implemented system for enabling borrowers to anonymously shop for loan packages offered by a plurality of lenders, comprising a database that stores loan package data from the lenders, and a computer system providing an interface and a grading module. … 811 F.3d. at 1318, 117 USPQ2d at 1695. The Federal Circuit determined that these claims were directed to the concept of “anonymous loan shopping”, which was a concept that could be “performed by humans without a computer.” 811 F.3d. at 1324, 117 USPQ2d at 1699. … The Federal Circuit determined that these claims were directed to mental processes of parsing and comparing data, because the steps were recited at a high level of generality and merely used computers as a tool to perform the processes. 881 F.3d at 1366, 125 USPQ2d at 1652-53.
For these reasons, there is no inventive concept. The claims are not patent eligible. Therefore, the claim is directed to an abstract idea. Thus, the claim is not patent eligible. (Step 2B: NO. The claim does not provide significantly more)
Dependent Claims recite additional elements.
This judicial exception is not integrated into a practical application. In particular, the recited additional elements of
Claim 17:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: generally linking to machine learning and artificial intelligence a means to perform an abstract idea
Claim 18:
“non-transitory computer readable medium”, “wherein the instruction code causes the computing system to perform further operations”, “computing device”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“to generate the user interface”: generally linking to user interface design a means to perform an abstract idea
Claim 19:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 20:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: generally linking to machine learning and artificial intelligence a means to perform an abstract idea
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, the claim is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. Dependent claims further define the abstract idea that is present in their respective independent claims and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the dependent claims are directed to an abstract idea. Thus, the dependent claims are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-8, 11-15, and 17- 20 are rejected under 35 U.S.C. 103 as being unpatentable over Splittstoesser ("SYSTEMS AND METHODS FOR DETERMINING BUILDING DAMAGE", U.S. Patent Number: US 11361544 B2),in view of Hynes (“ENSEMBLE FORECAST STORM DAMAGE RESPONSE SYSTEM FOR CRITICAL INFRASTRUCTURE”, U.S. Publication Number: US 20220292408 A1),in view of Franke (“DAMAGE ASSESSMENT AND REPAIR BASED ON OBJECTIVE SURFACE DATA”, U.S. Publication Number: US 20170148102 A1)
Regarding Claim 1,
Splittstoesser teaches,
A computer-implemented method for processing insurance claims, the method comprising: receiving, from a first user computing device and during a period,
(Splittstoesser [Col 1, Lines 53-57] The DA computing device may perform a damage assessment process for a building when an insurance claim may be received and/or when the DA computing device detects an inclement weather condition in a geographic region that includes the building.
Splittstoesser [Col 4, Lines 17-20] The weather parameters may also include information associated with weather conditions of the building over a predetermined period of time.)
an indication of damage to an article caused by a particular weather event, wherein the indication specifies a particular location of the article where the damage to the article occurred;
(Splittstoesser [Col 1, Lines 26-30] To determine damage to a roof, in at least some known systems, a representative of the insurance provider (or other third party) may visit the building. The representative may assess the damage to the roof by analyzing a particular portion of the roof.
Splittstoesser [Col 1, Lins 15-17] a hail storm may impact a roof of a building. The hail may create impact holes in the roof and/or structurally weaken the roof)
selecting, from a model database, a first instance of a weather-based damage prediction model, wherein the weather-based damage prediction model was previously trained based on one or more historical weather events that occurred proximate to the particular location
(Splittstoesser [Col 1, Lines 48-50] computing device may generate a damage model for buildings based on historical damage retrieved from a historical damage database
Splittstoesser [Claim 1] train a machine learning damage model using the historical damage parameters as an input set, the trained damage model including a plurality of predictive model parameters
Splittstoesser [Col 4, Lines 10-28] historical damage parameters may include, weather parameters, building parameters, and/or environment parameters.... Environment parameters may indicate information about an environment surrounding the building that may affect potential damage to the building
Splittstoesser [Col 5, Lines 40-42] The weather database may be configured to collect and store weather data for one or more geographic regions. The geographic region may be an area that is identifiable within the weather data.)
and indications of damage to a plurality of articles determined to be caused by the one or more historical weather events;
(Splittstoesser [Claim 13] plurality of historical damage incidents for a respective plurality of buildings from a historical damage database
Splittstoesser [Col 4, Lines 22-37] Building parameters may indicate information associated with the building and its structural components, such as, but not limited to, age of the roof, material type of the roof, angle or slant of the roof, and/or other building information. ...Building parameters and/or environment parameters for historical damage may be provided by users and/or historical insurance claims for damage incidents....historical damage parameters may include other information about a damage incident, such as .... a damage status of the building. As used herein, a “damage status” may indicate whether or not the building is damaged and to what extent it is damaged. )
receiving, from the selected first instance of the weather-based damage prediction model, a first damage prediction that indicates a type and severity of damage caused by the particular weather event to the article;
(Splittstoesser [Claim 1] identify a building for a roof damage assessment by:
detecting the upcoming weather event in a geographic region including the building by accessing the weather database
Splittstoesser [Col 1, Lines 48-50] computing device may generate a damage model for buildings based on historical damage retrieved from a historical damage database
Splittstoesser [Col 17, Lines 61-65] Machine learning may involve identifying and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. Models may be created based upon example inputs in order to make valid and reliable predictions
Splittstoesser [Col 4, Lines 38-43] As used herein, a “damage status” may indicate whether or not the building is damaged and to what extent it is damaged. In one example, the damage status may be “no damage”, “repairs recommended”, and/or “totaled” (i.e., the cost to repair the damage is greater than the cost to replace the damage component of the building).)
communicating, to the first user computing device, instructions that cause the first user computing device to generate a user interface that comprises one or more fields for indicating damage to the article and to pre-populate the one or more fields based on the first damage prediction;
(Splittstoesser [Abstract] A damage assessment (DA) computing device
Splittstoesser [Col 14, Line 67 - Col Line 1] present a graphical user interface (e.g., a web browser and/or a client application) to user
Splittstoesser [Claim 4] automatically pre-populate an insurance claim for an insurance policy associated with the building, wherein the insurance claim includes the damage status and at least one damage parameter)
after receiving, during the period and from one or more other user computing devices, a threshold number of indications of damage to one or more other articles caused by the particular weather event,
(Splittstoesser [Col 5, Lines 23-28] DA computing device may be communicatively coupled to one or more insurance computing devices associated with one or more insurance providers. The insurance computing devices may be configured to receive, generate, and/or otherwise process insurance claims
Splittstoesser [Col 6, Lines 58-62] a sensor may be configured to monitor a roof for impacts (e.g., impacts from hail). The sensor may provide damage parameters including the number of impacts, force of impacts, the locations of the impacts, and/or other impact-related information.
Splittstoesser [Claim 10] when the extent of damage exceeds a predefined threshold: automatically pre-populate an insurance claim
Splittstoesser [Col 4, Lines 17-20] The weather parameters may also include information associated with weather conditions of the building over a predetermined period of time.)
generating a second instance of the weather-based damage prediction model;
(Splittstoesser [Col 17, Lines 63-65] Models may be created based upon example inputs in order to make valid and reliable predictions for novel inputs
Splittstoesser [Col 18, Lines 3-14] machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition, …. machine learning programs may include Bayesian program learning (BPL), voice recognition and synthesis, image or object recognition, optical character recognition, and/or natural language processing—either individually or in combination. The machine learning programs may also include natural language processing, semantic analysis, automatic reasoning, and/or machine learning.
Splittstoesser [Col 17, Lines 55-60] may be trained using supervised or unsupervised machine learning, and the machine learning program may employ a neural network, which may be a convolutional neural network, a deep learning neural network, or a combined learning module or program that learns in two or more fields or areas of interest)
re-training the second instance of the weather-based damage prediction model based on characteristics of the particular weather event and the respective indications of damage received from the respective user computing devices; after re-training the second instance of the weather-based damage prediction model receiving, from a second user computing device and during the period, an indication of damage to an article caused by the particular weather event; and communicating, to the second user computing device and based on a second damage prediction generated by the re-trained second instance of the weather-based damage prediction model,
(Splittstoesser [Col 19, Lines 35-38] an element or step recited in the singular and preceded by the word “a” or “an” should be understood as not excluding plural elements or steps, unless such exclusion is explicitly recited
Splittstoesser [Claim 13] re-training, by the DA computing device, the machine learning damage model using the update historical damage parameters as an updated input set.
Splittstoesser [Col 17, Lines 62-64] to facilitate making predictions for subsequent data. Models may be created
Splittstoesser [Col 7, Lines 61-62] the DA computing device may transmit a recommendation
Splittstoesser [Col 4, Lines 17-20] The weather parameters may also include information associated with weather conditions of the building over a predetermined period of time.
Splittstoesser [Col 4, Lines 22-37] Building parameters may indicate information associated with the building and its structural components, such as, but not limited to, age of the roof, material type of the roof, angle or slant of the roof, and/or other building information. ...Building parameters and/or environment parameters for historical damage may be provided by users and/or historical insurance claims for damage incidents....historical damage parameters may include other information about a damage incident, such as .... a damage status of the building. As used herein, a “damage status” may indicate whether or not the building is damaged and to what extent it is damaged. )
instructions that cause the second user computing device to generate the user interface that comprises the one or more fields for indicating damage to the article and to pre-populate the one or more fields based on the second damage prediction
(Splittstoesser [Abstract] A damage assessment (DA) computing device
Splittstoesser [Claim 21] having computer-executable instructions
Splittstoesser [Col 14, Line 67 - Col Line 1] present a graphical user interface (e.g., a web browser and/or a client application) to user
Splittstoesser [Claim 4] automatically pre-populate an insurance claim for an insurance policy associated with the building, wherein the insurance claim includes the damage status and at least one damage parameter
Splittstoesser [Col 13, Lines 11-12] computing device 102 may combine, aggregate, and/or other compute using parameters scores)
Splittstoesser does not teach that is distinct from the first instance of the weather-based damage prediction model…has a higher prediction accuracy than the first instance of the weather-based damage prediction model for predicting damage caused by the particular weather event; wherein the second instance of the weather-based damage prediction model is trained specifically for the particular weather event using the threshold number of indications of damage received from the one or more other user computing devices;
Hynes teaches,
that is distinct from the first instance of the weather-based damage prediction model…has a higher prediction accuracy than the first instance of the weather-based damage prediction model for predicting damage caused by the particular weather event;
(Hynes [0033] from a variety of sources, such as from overhead imaging of the geographic area (e.g., via aircraft, such as drones, and/or satellite imagery), storm response repair crew personnel, consumer response (e.g., based on reported outages or regional damage reports), or a combination thereof. .... The actual windspeed data AWD can thus differ from the forecasted windspeeds associated with the ensemble forecast models ST_EN. As a result, the combination of the damage assessment data DAD and the actual windspeed data AWD can provide for an accurate indication of the damage sustained to the specific relevant components .... damage assessment data DAD and the actual windspeed data AWD can be updated in response to additional actual storms to provide more data and/or more accurate data
Hynes [0034] The damage assessment data DAD and the actual windspeed data AWD can thus be implemented by the model generator 154 to generate a more accurate probabilistic model 156 for subsequent storms…the model generator 154 can access the damage assessment data DAD and the actual windspeed data AWD, such as for similar characteristics of an imminent storm, to refine the probabilistic model 156 that is generated based on the inventory data INV for each ensemble forecast model ST_EN…can be implemented in any of a variety of ways, such as based on a machine learning algorithm.
Hynes [0035] the model generator 154 can generate the probabilistic model 156 for future storms...and the actual windspeed data AWD associated with past storms.
Hynes [0036] configured to run the plurality of iterative probabilistic simulations on the probabilistic model
Hynes [0037] the given ensemble forecast model that is associated with the probabilistic model)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the weather-based damage prediction of Splittstoesser to incorporate the second more accurate model teachings of Hynes “AWD can be updated in response to additional actual storms to provide more data and/or more accurate data.” (Hynes [0033]). The modification would have been obvious, because it is merely applying a known technique (i.e. second more accurate model ) to a known concept (i.e. weather-based damage prediction) ready for improvement to yield predictable result (i.e. “to generate a more accurate probabilistic model 156 for subsequent storms” Hynes [0034])
Hynes does not teach wherein the second instance of the weather-based damage prediction model is trained specifically for the particular weather event using the threshold number of indications of damage received from the one or more other user computing devices;
Franke teaches,
wherein the second instance of the weather-based damage prediction model is trained specifically for the particular weather event using the threshold number of indications of damage
(recognize [0174] classifier or other algorithm may be trained with training data to recognize damage
Franke [0048] determine shape and detect small magnitude defects such as hail dents or other impact damage from small objects
Franke [0064] Any excess damage to the returned vehicle in the report 146 that exceeds an allowance for normal wear and tear may be identified...Where damage or wear can be automatically identified and objectively characterized, e.g., based on scratches, dents, paint deterioration, missing trim, and so forth,... the wear may be directly evaluated and compared to a baseline for physical condition of the vehicle
Franke [0065] A normalized, ideal vehicle model may be used as a baseline and the difference between this ideal vehicle model and the scanned model may be used to detect candidate damage areas.
Franke [0136] an accurate recommendation can be made on totaling and replacing the damaged vehicle.)
received from the one or more other user computing devices;
(Franke [0083] previously generated models, previously scanned models, models supplied by a manufacturer, models that serve as a baseline, and so forth.
Franke [0062] may interactively incorporate and aggregate information from a variety of users
Franke [0182] other system users to communicate with an insurer that is responsible for the repair
Franke [0016] executing on one or more computing devices)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the weather-based damage prediction of Splittstoesser to incorporate the damage threshold teachings of Franke “A normalized, ideal vehicle model may be used as a baseline” (Franke [0065]). The modification would have been obvious, because it is merely applying a known technique (i.e. damage threshold) to a known concept (i.e. weather-based damage prediction) ready for improvement to yield predictable result (i.e. “Any excess damage to the returned vehicle in the report 146 that exceeds an allowance for normal wear and tear may be identified...Where damage or wear can be automatically identified and objectively characterized” Franke [0064])
Regarding Claim 3,
Splittstoesser, Hynes, and Franke teach the insurance claim processing of Claim 1 as described earlier.
Splittstoesser teaches,
wherein the particular weather event corresponds to a hail storm
(Splittstoesser [Col 6, Lines 58-62] a sensor may be configured to monitor a roof for impacts (e.g., impacts from hail).)
Regarding Claim 4,
Splittstoesser, Hynes, and Franke teach the insurance claim processing of Claim 1 as described earlier.
Splittstoesser teaches,
wherein the weather- based damage prediction model is generated by an artificial intelligence algorithm.
(Splittstoesser [Col 18, Lines 3-14] machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition, and may be trained after processing multiple examples. The machine learning programs may include Bayesian program learning (BPL), ...The machine learning programs may also include natural language processing, semantic analysis, automatic reasoning, and/or machine learning.)
Regarding Claim 5,
Splittstoesser, Hynes, and Franke teach the insurance claim processing of Claim 1 as described earlier.
Splittstoesser teaches,
after communicating the instructions that cause the first user computing device to generate the user interface, receiving, from the first user computing device, first storm damage information that comprises damage information and damage images.
(Splittstoesser [Col 14, Line 67 to ] configured to present a graphical user interface (e.g., a web browser and/or a client application) to user 301. A graphical user interface may include, for example, an interface for viewing prompts and damage statuses
Splittstoesser [Col 15, Lines 28-30] to display and interact with media and other information typically embedded on a web page or a website
Splittstoesser [Col 12, Lines 25-28] a set of damage parameters 220 in response to the prompt. User input 222 may include, but is not limited to, text data, image data, video data, and/or audio data. In one example, policyholder 116 may capture image data of roof)
Regarding Claim 6,
Splittstoesser, Hynes, and Franke teach the insurance claim processing of Claim 5 as described earlier.
Splittstoesser teaches,
validating the first storm damage information by verifying whether the damage images correspond to the damage information.
(Splittstoesser [Col 12, Lines 30-42] a drone and/or a satellite may be used to capture image data of roof 115. DA computing device 102 may be configured to receive the image data and perform image analysis on the image data to extract damage parameters... user computing device 106 may display one or more questions to policyholder 116. Policyholder 116 may then provide user input 222 in response to the questions.
Splittstoesser [Claim 6] receive image data associated with the building from the user ...analyze the image data to identify at least one point ...extract the set of additional damage parameters from the image data based at least partially upon the analysis;
Splittstoesser [Col 17, Lines 63-65] Models may be created based upon example inputs in order to make valid and reliable predictions for novel inputs.)
Regarding Claim 7,
Splittstoesser, Hynes, and Franke teach the insurance claim processing of Claim 6 as described earlier.
Splittstoesser teaches,
extracting using an artificial intelligence algorithm, characteristics from the damage images; and comparing the characteristics from the damage images to the damage information.
(Splittstoesser [Col 18, Lines 3-14] machine learning programs may utilize deep learning algorithms that may be primarily focused on pattern recognition, and may be trained after processing multiple examples. The machine learning programs may include Bayesian program learning (BPL), ...The machine learning programs may also include natural language processing, semantic analysis, automatic reasoning, and/or machine learning.
Splittstoesser [Col 12, Lines 30-42] a drone and/or a satellite may be used to capture image data of roof 115. DA computing device 102 may be configured to receive the image data and perform image analysis on the image data to extract damage parameters... user computing device 106 may display one or more questions to policyholder 116. Policyholder 116 may then provide user input 222 in response to the questions.
Splittstoesser [Abstract] retrieve damage data associated with the building, compare the damage data associated with the roof to the damage model, and/or determine a damage status of the roof based upon the comparison.)
Claim 8 is rejected on the same basis as claim 1.
Claim 11 is rejected on the same basis as claim 4.
Claim 12 is rejected on the same basis as claim 5.
Claim 13 is rejected on the same basis as claim 6.
Claim 14 is rejected on the same basis as claim 7.
Claim 15 is rejected on the same basis as claim 1.
Claim 17 is rejected on the same basis as claim 4.
Claim 18 is rejected on the same basis as claim 5.
Claim 19 is rejected on the same basis as claim 6.
Claim 20 is rejected on the same basis as claim 7.
Response to Remarks
Applicant's arguments filed on April 20, 2026, have been fully considered and Examiner’s remarks to Applicant’s amendments follow.
Response Remarks on Claim Rejections - 35 USC § 101
The Applicant states:
“Moreover, the factual parallels between Desjardins and the present application are strong. In Desjardins, the claims recited training a machine learning model to learn new tasks while protecting knowledge about previous tasks, resulting in reduced system complexity. Here, the claims recite generating a second, distinct machine learning model instance that is trained specifically for a particular weather event using real-time user-submitted damage indications received during the event"
Examiner responds:
The focus of the claims is not on an improvement in machine learning as a tool, but on certain independently abstract ideas that use machine learning as a tool.
In Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Indeed, enumerated improvements identified in the Desjardins specification included disclosures of the effective learning of new tasks in succession in connection with specifically protecting knowledge concerning previously accomplished tasks; allowing the system to reduce use of storage capacity; and the enablement of reduced complexity in the system. Such improvements were tantamount to how the machine learning model itself would function in operation and therefore not subsumed in the identified mathematical calculation.
Applicant’s invention incorporates no similar details and is not analogous to Ex Parte Desjardins. Applicant’s use of generic components function as designed with no unexpected results. The machine learning model is trained using (weather damage) data to provide a predicted outcome.
The weather damage data amounts to gathering, sharing, and manipulation of generic data which an Abstract Idea [Intellectual Ventures I v. Capital One Fin. Corp., 850 F.3d 1332, 121 USPQ2d 1940 (Fed. Cir. 2017) “collecting, displaying, and manipulating data” was considered part of the abstract idea]
The resulting expected prediction is outputted from the generic machine learning model. In the absence of unexpected results, changes or alteration of sequence do not make for a patentable invention, see Ex parte Rubin, 128 USPQ 440 (Bd. App. 1959) ; In re Burhans, 154 F.2d 690, 69 USPQ 330 (CCPA 1946); In re Gibson, 39 F.2d 975, 5 USPQ 230 (CCPA 1930)
The Applicant states:
“…The Office Action's characterization of the claims as reciting "generic machine learning performing a generic machine learning functions" is factually incorrect and fails to account for the specific claim language and the supporting Specification. …”
Examiner responds:
The machine learning components are recited at a high-level of generality (i.e., as a generic machine learning performing a generic machine learning functions) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For example, the Applicant’s own Specification reads:
[0020] The damage prediction is generated by the claim processing system using computer processes and/or algorithms, such as artificial intelligence (e.g., machine learning) algorithms, that utilize data corresponding to past storm data
[0026] The prediction circuit 130 generates a damage prediction model by utilizing an artificial intelligence (e.g., machine learning, etc.) algorithm that uses the data from the databases 110 as input variables.
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality.
The Applicant’s usage of “a threshold number”, “specifically for the particular weather event”, and “continual learning”, express abstract ideas. An abstract idea cannot integrate another abstract idea into a practical application.
The Applicant states:
“… Improper Characterization of the Claims as a "Mental Process"…. No human being can perform these operations manually or mentally. A human being cannot monitor incoming damage indications from multiple remote user computing devices in real time during an active weather event, dynamically determine when a threshold number has been reached, generate a distinct second machine learning model instance, re-train that instance on the aggregate real-time data, and deploy the re-trained instance to serve subsequent user requests; all within the time window of a single weather event. These operations require computer processing, data aggregation, machine learning training algorithms, and real-time deployment, none of which can be performed by a human mind or with pen and paper. …”
Examiner responds:
A human can undoubtedly “monitor incoming damage indications from multiple remote user computing devices in real time during an active weather event, dynamically determine when a threshold number has been reached,…; all within the time window of a single weather event”.
The additional elements of “generate a distinct second machine learning model instance, re-train that instance on the aggregate real-time data, and deploy the re-trained instance to serve subsequent user requests” express generic machine learning capabilities. Nothing in the claims, understood in light of the specification, requires anything other than “merely applying” off-the-shelf, conventional machine learning technology for gathering, synthesizing, sending, and presenting the desired information.
The functioning of the computer itself is not improved. The computer only performs transmitting of data over network, receiving/processing/storing data, and performing calculation (manipulating data based on model/algorithm). Covered by MPEP 2106.5(d).
The Applicant states:
“… The Specification expressly discloses that the claimed invention provides improvements to machine learning model accuracy and efficiency. … By training the same machine learning model on multiple tasks… through event-specific model refinement… machine learning systems themselves by providing higher accuracy through a specific technical architecture (threshold-triggered branching and event-specific re-training).”
Examiner responds:
Improvements to accuracy are generally expected when “training the same machine learning model on multiple tasks” and “through event-specific model refinement” and “branching and event-specific re-training.” The generic machine learning tool work as expected. The focus of the claims is not on an improvement to machine learning as a tool, but on certain independently abstract ideas that use machine learning as a tool.
The Applicant states:
“… Citation to U.S. Patent Application Publication No. 2021/0398129 Al in Interview Summary… Applicant respectfully submits that this citation is directly relevant to the present § 101 analysis…. These claims are strikingly similar in structure and technical character to the present claims. Both relate to generating and updating machine learning models for insurance-related predictions. Both disclose using training data to refine model accuracy. Both recite computer- implemented methods involving data processing, model generation, and application of predictions.”
Examiner responds:
Application Publication No. 2021/0398129 makes zero reference to insurance anywhere in the Specification nor Claims. The cited Claim 1 is also not from that application. In fact, Claim 1 was cancelled.
In Application Publication No. 2021/0398129 , the entirety of Independent Claim 2 would have been deemed an abstract idea.
Elements of Claim 5 that read, “a plurality of hidden nodes in a hidden layer having a number of nodes less than the plurality of input nodes, and a plurality of output nodes in an output layer corresponding to the plurality of input nodes” could have potentially integrated the abstract idea into a practical application because at the time of filing, it was common practice for the hidden layer to possess the same or greater number of nodes as the input or output layer. This expressed a specific arrangement for a technical purpose, the ability to run an ML model on a less powerful processor.
Applicant’s invention in no manner mirrors this application.
Therefore, the rejection under 35 USC § 101 remains.
Response Remarks on Claim Rejections - 35 USC § 103
Applicant's amendments required the application of new/additional prior art.
Applicant’s remarks regarding the rejection made under 35 USC § 103 are rendered moot by the introduction of additional prior art.
In response to applicant’s argument that there is no teaching, suggestion, or motivation to combine the references, the examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007).
In this case, it is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the weather-based damage prediction of Splittstoesser to incorporate the second more accurate model teachings of Hynes “AWD can be updated in response to additional actual storms to provide more data and/or more accurate data.” (Hynes [0033]). The modification would have been obvious, because it is merely applying a known technique (i.e. second more accurate model) to a known concept (i.e. weather-based damage prediction) ready for improvement to yield predictable result (i.e. “to generate a more accurate probabilistic model 156 for subsequent storms” Hynes [0034])
One cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In reMerck & Co., Inc., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). Where a rejection of a claim is based on two or more references, a reply that is limited to what a subset of the applied references teaches or fails to teach, or that fails to address the combined teaching of the applied references may be considered to be an argument that attacks the reference(s) individually. Where an applicant’s reply establishes that each of the applied references fails to teach a limitation and addresses the combined teachings and/or suggestions of the applied prior art, the reply as a whole does not attack the references individually as the phrase is used in Keller and reliance on Keller would not be appropriate. This is because "[T]he test for obviousness is what the combined teachings of the references would have suggested to [a PHOSITA]." In re Mouttet, 686 F.3d 1322, 1333, 103 USPQ2d 1219, 1226 (Fed. Cir. 2012).v
Therefore, a rejection under 35 USC § 103 remains.
Prior Art Cited But Not Applied
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Konrardy (“AUTONOMOUS VEHICLE COMPONENT DAMAGE AND SALVAGE ASSESSMENT”, U.S. Publication Number: US 20210116256 A1) proposes assessing, detecting, and responding to malfunctions involving components of autonomous vehicle and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the condition of components for salvage following a collision or other loss-event. To this end, the information regarding a plurality of components may be received. A component of the plurality of components may be identified for assessment. Assessment may including causing test signals to be sent to the identified component. In response to the test signal, one or more responses may be received. The received response may be compared to an expected response to determine whether the identified component is salvageable.
Pedersen (“DAMAGE PREDICTION SYSTEM USING ARTIFICIAL INTELLIGENCE”, U.S. Patent: US 11430069 B1) proposes a damage prediction system that uses hazard data and/or aerial images to predict future damage and/or estimate existing damage to a structure is described herein. For example, the damage prediction system may use forecasted hazard data to predict future damage or use actual hazard data to estimate existing damage. The damage prediction system may obtain hazard data in which structures were or will be impacted by a hazard. The damage prediction system can then generate a flight plan that causes an aerial vehicle to fly over the impacted parcels and capture images. The damage prediction system can use artificial intelligence to process the images for the purpose of identifying potential damage. The damage prediction system can also use a hazard model, the hazard data, and structure characteristics to generate a damage score. The damage prediction system can then use the processed images and/or damage score to generate a virtual claim.
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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/C.E./Examiner, Art Unit 3695
/CHRISTINE M Tran/Supervisory Patent Examiner, Art Unit 3695
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