DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This non-final office action is in response to the application filed 16 May 2022.
Claims 1-20 are pending. Claims 1, 8, and 15 are independent claims.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 16 May 2022, 13 October 2023, and 16 December 2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are being considered by the examiner.
Drawings
The examiner accepts the drawings filed 16 May 2022.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
When considering subject matter eligibility under 35 USC 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1; MPEP 2106.03). If the claim falls within one of the statutory categories, the second step in the analysis is to determine whether the claim is directed toward a judicial exception (Step 2A; MPEP 2106.04). This step is broken into two prongs.
The first prong (Step 2A, Prong 1) determines whether or not the claims recite a judicial exception (e.g., mathematical concepts, mental processes, certain methods of organizing human activity). If it is determined at Step 2A, Prong 1 that the claims recite a judicial exception, the analysis proceeds to the second prong (Step 2A, Prong 2; MPEP 2106.04). The second prong (Step 2A, Prong 2) determines whether the claims integrate the judicial exception into a practical application. If the claims do not integrate the judicial exception into a practical application, the analysis proceeds to determine whether the claim is a patent-eligible exception (Step 2B; MPEP 2106.05).
If an abstract idea is present int the claim, in order to recite statutory subject matter, any element or combination of elements in the claim must be sufficient to ensure that the claim integrates the judicial exception into a practical application or amounts to significantly more than the abstract idea itself (see: 2019 PEG).
Step 1:
According to Step 1 of the two Step analysis, claims 1-7 are directed toward a process. Claims 8-14 are directed toward a machine. Claims 15-20 are directed toward a manufacture. Therefore, each of these claims falls within one of the four statutory categories.
Claim 1:
Step 2A, Prong 1:
Following the determination that the claims fall within one of the statutory categories (Step 1), it must be determined if the claims recite a judicial exception (Step 2A, Prong 1). In this instance, the claims are determined to recite a judicial exception (abstract idea; mental process).
With respect to claim 1, the claims recite:
calculating… a similarity score matrix based on site data (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses calculating a similarity score matrix based upon received data (evaluation))
grouping… the site data into data clusters based on the similarity score matrix (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses grouping data based upon a previous evaluation (judgment))
identifying… training data and validation data based on the data clusters (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses identifying data sets, including training data and validation data based upon a previous evaluation and judgement (judgement))
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
With respect to claim 1, the judicial exception is not integrated into a practical application.
The claim further recites the additional elements of a device, which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Further, the claim recites the additional element of “receiving… site data identifying raw data or key performance indicators associated with a plurality of sites” which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Finally, the claim recites the additional elements:
generating… a meta model
training… the meta model based on the training data
validating… the meta model based on the validation data
creating… site-specific models, for each of the plurality of sites, based on the meta model and the site data
utilizing… the site-specific models with corresponding new site data of the plurality of sites to generate predictions for the plurality of sites
These elements are recited at a high-level of generality and lack details regarding the generating, training, validating, creating, and utilizing. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claim further recites the additional elements of a device, which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Further, the claim recites the additional element of “receiving… site data identifying raw data or key performance indicators associated with a plurality of sites” which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Finally, the claim recites the additional elements:
generating… a meta model
training… the meta model based on the training data
validating… the meta model based on the validation data
creating… site-specific models, for each of the plurality of sites, based on the meta model and the site data
utilizing… the site-specific models with corresponding new site data of the plurality of sites to generate predictions for the plurality of sites
These elements are recited at a high-level of generality and lack details regarding the generating, training, validating, creating, and utilizing. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 2:
With respect to dependent claim 2, the claim depends upon independent claim 1, and the analysis with respect to claim 1 is incorporated herein.
Step 2A, Prong 1:
With respect to claim 2, the claims recite:
wherein the similarity score matrix is a Jensen-Shannon score matrix (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses calculating a similarity score matrix based upon received data (see claim 1), wherein the similarity score matrix is a Jensen-Shannon score matrix (evaluation))
Claim 3:
With respect to dependent claim 3, the claim depends upon independent claim 1, and the analysis with respect to claim 1 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 3, the claim recites the additional element of “receiving new site data for the new site” which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Further, the claim recites the additional elements of “creating a base model for a new site based on the meta model” and “utilizing the base model and the new site data to generate prediction for the new site.” These elements are recited at a high-level of generality and lack details regarding the creating and utilizing. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 3, the claim recites the additional element of “receiving new site data for the new site” which amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Further, the claim recites the additional elements of “creating a base model for a new site based on the meta model” and “utilizing the base model and the new site data to generate prediction for the new site.” These elements are recited at a high-level of generality and lack details regarding the creating and utilizing. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 4:
With respect to dependent claim 4, the claim depends upon dependent claim 3, and the analysis with respect to claim 3 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 4, the claim recites the additional element “wherein the base model is a generic model generated from the meta model” which references the created “base model” of claim 3.This element is recited at a high-level of generality and lack details regarding the creating. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 4, the claim recites the additional element “wherein the base model is a generic model generated from the meta model” which references the created “base model” of claim 3.This element is recited at a high-level of generality and lack details regarding the creating. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 5:
With respect to dependent claim 5, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 5, the claim recites the additional element of “wherein each of the plurality of sites includes: one or more server devices, one or more network devices, or one or more data structures” and references “receiving… site data… associated with a plurality of sites” in independent claim 1. Therefore, this limitation amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 5, the claim recites the additional element of “wherein each of the plurality of sites includes: one or more server devices, one or more network devices, or one or more data structures” and references “receiving… site data… associated with a plurality of sites” in independent claim 1. Therefore, this limitation amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 6:
With respect to dependent claim 6, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein.
Step 2A, Prong 1:
With respect to claim 6, the claims recite:
wherein the similarity score matrix provides an indication of similar data distributions associated with the site data (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses calculating a similarity score matrix based upon received data (see claim 1), wherein the similarity score matrix provides an indication of similar data distributions associated with the site data (evaluation))
Claim 7:
With respect to dependent claim 7, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein.
Step 2A, Prong 1:
With respect to claim 7, the claims recite:
grouping the site data into hierarchical data clusters based on the similarity score matrix (mental process; As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgment, opinion) or with the aid of pencil and paper but for the recitation of generic computer components. For example, this limitation encompasses grouping data based upon a previous evaluation (judgment))
Claim 8:
With respect to independent claim 8, the claim recites the limitations substantially similar to those in claims 1 and 6, respectively. The analysis of claims 1 and 6 are incorporated herein by reference.
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
With respect to claim 8, the judicial exception is not integrated into a practical application.
The claim further recites the additional elements of a device comprising one or more memories and one or more processors, which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claim further recites the additional elements of a device comprising one or more memories and one or more processors, which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 9:
With respect to dependent claim 9, the claim depends upon independent claim 8, and the analysis with respect to claim 8 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 9, the claim recites the additional element “wherein the meta model is a neural network model”. This element is recited at a high-level of generality and lack details regarding the creating. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 9, the claim recites the additional element “wherein the meta model is a neural network model”. This element is recited at a high-level of generality and lack details regarding the creating. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 10:
With respect to dependent claim 10, the claim depends upon independent claim 8, and the analysis with respect to claim 8 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 10, the claim recites the additional element “train the meta model based on the training data, are to: train the meta model on the training data and a model agnostic meta learning model.” This element is recited at a high-level of generality and lack details regarding the training. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 10, the claim recites the additional element “train the meta model based on the training data, are to: train the meta model on the training data and a model agnostic meta learning model.” This element is recited at a high-level of generality and lack details regarding the training. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 11:
With respect to dependent claim 11, the claim depends upon independent claim 8, and the analysis with respect to claim 8 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 11, the claim recites the additional element “train the meta model based on the training data, are to: train the meta model, based on the training data, to generate site-specific weights to be turned to create the site-specific models.” This element is recited at a high-level of generality and lack details regarding the training. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 11, the claim recites the additional element “train the meta model based on the training data, are to: train the meta model, based on the training data, to generate site-specific weights to be turned to create the site-specific models.” This element is recited at a high-level of generality and lack details regarding the training. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 12:
With respect to dependent claim 12, the claim depends upon independent claim 8, and the analysis with respect to claim 8 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 12, the claim recites the additional element “to create the site-specific models, for each of the plurality of sites, based on the meta model and the site data, are to: create the site-specific models based on the training meta model with the training data; calculate losses associated with the site-specific models; utilize the losses to learn gradients; and update the meta model based on the gradients.” This element is recited at a high-level of generality and lack details regarding the creating. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 12, the claim recites the additional element “to create the site-specific models, for each of the plurality of sites, based on the meta model and the site data, are to: create the site-specific models based on the training meta model with the training data; calculate losses associated with the site-specific models; utilize the losses to learn gradients; and update the meta model based on the gradients.” This element is recited at a high-level of generality and lack details regarding the creating. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 13:
With respect to dependent claim 13, the claim depends upon independent claim 8, and the analysis with respect to claim 8 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 13, the claim recites the additional element “wherein each of the site-specific models learns with less data than required for models not generated based on the meta model.” This element is recited at a high-level of generality and lack details regarding the training. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 13, the claim recites the additional element “wherein each of the site-specific models learns with less data than required for models not generated based on the meta model.” This element is recited at a high-level of generality and lack details regarding the training. Therefore, these elements amount to no more than adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea (See MPEP 2106.05(f))
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 14:
With respect to dependent claim 14, the claim depends upon independent claim 8. The analysis of claim 8 is incorporated herein.
Step 2A, Prong 2:
With respect to claim 14, the claim recites the additional element of “wherein each of the plurality of sites includes multiple virtual machines.” Therefore, this limitation amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
With respect to claim 14, the claim recites the additional element of “wherein each of the plurality of sites includes multiple virtual machines.” Therefore, this limitation amounts to extra-solution activity of gathering data for use in the claimed process. As described in MPEP 2106.05(g), limitations that amount to merely adding insignificant extra-solution activity to a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 15:
With respect to independent claim 15, the claim recites the limitations substantially similar to those in claims 1 and 5, respectively. The analysis of claims 1 and 5 are incorporated herein by reference.
Step 2A, Prong 2:
Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception (MPEP 2106.04(d)).
With respect to claim 15, the judicial exception is not integrated into a practical application.
The claim further recites the additional elements of a non-transitory computer-readable medium storing a set of instructions, which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
Accordingly, at Step 2A, prong two, the additional elements individually or in combination do no integrate the judicial exception into a practical application.
Step 2B:
Based on the determination in Step 2A of the analysis that the claims are directed toward a judicial exception, in must be determined if any claims contain any element or combination of elements sufficient to ensure that the claims amount to significantly more than the judicial exception (Step 2B).
The claim further recites the additional elements of a non-transitory computer-readable medium storing a set of instructions, which are recited at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (See MPEP 2106.05(f)).
In this instance, after considering all claim elements individually and as an ordered combination, it is determined that the claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception.
Claim 16:
With respect to dependent claim 16, the claim depends upon independent claim 15. The analysis of claim 15 is incorporated herein by reference.
Further, the claim recites the limitations substantially similar to those in claims 3 and 4, respectively. The analysis of claims 3 and 4 are incorporated herein by reference.
Claim 17:
With respect to dependent claim 17, the claim depends upon independent claim 15. The analysis of claim 15 is incorporated herein by reference.
Further, the claim recites the limitations substantially similar to those in claim 7. The analysis of claim 7 is incorporated herein by reference.
Claim 18:
With respect to dependent claim 18, the claim depends upon independent claim 15. The analysis of claim 15 is incorporated herein by reference.
Further, the claim recites the limitations substantially similar to those in claim 10. The analysis of claim 10 is incorporated herein by reference.
Claim 19:
With respect to dependent claim 19, the claim depends upon independent claim 15. The analysis of claim 15 is incorporated herein by reference.
Further, the claim recites the limitations substantially similar to those in claim 11. The analysis of claim 11 is incorporated herein by reference.
Claim 20:
With respect to dependent claim 20, the claim depends upon independent claim 15. The analysis of claim 15 is incorporated herein by reference.
Further, the claim recites the limitations substantially similar to those in claim 12. The analysis of claim 12 is incorporated herein by reference.
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-6, 8-11, 13-16, and 18-19 are rejected under 35 U.S.C. 103 as being unpatentable over Suleiman et al. (US 2018/0081912, published 22 March 2018, hereafter Suleiman) and further in view of Yang et al. (US 12182673, filed 7 May 2021, hereafter Yang) and further in view of Sims et al. (WO 2010/042888, published 15 April 2010, hereafter Sims).
As per independent claim 1, Suleiman discloses a method, comprising:
receiving, by a device, data identifying raw data or key performance indicators (Figure 1; paragraphs 0023-0024: Here, a data collector collects data from a database system/cluster. Further, an administrative console allows for entry of key performance indicators (KPIs)/metrics)
calculating, by the device, a similarity score based on the data (paragraphs 0077-0080: Here, the similarity of a dataset is determined by comparing the similarity score of the data set to the other suitable datasets)
grouping, by the device, the data into data clusters based on the similarity score (paragraph 0053: Here, data is clustered based on similarity characteristics for use in training a model (paragraph 0025))
identifying, by the device, training data based on the data clusters (paragraph 0025: here, cleaned data is provided to train a new model)
generating, by the device, a meta model (paragraph 0026: Here, a new model is generated)
training, by the device, the meta model based on the training data (paragraph 0025: Here, the model is generated using the cleaned training data)
Suleiman fails to specifically disclose:
site data
score matrix
validation data
validating, by the device the meta model based on the validation data
creating, by the device, site-specific models, for each of the plurality of sites based on the meta model and the site data
utilizing, by the device, the site-specific models with corresponding new site data of the plurality of sites to generate predictions for the plurality of sites
However, Yang, which is analogous to the claimed invention because it is directed toward creating device specific models based upon device constraints, discloses:
site data (column 3, lines 33-35: Here, site data is analogous to the system constraints)
validation data (column 9, lines 29-43: Here, the model is tested for compatibility based upon a plurality of metrics. In this instance, the model is not validated if it is not compatible)
validating, by the device the meta model based on the validation data (column 9, lines 29-43: Here, the models are not deployed to the edge devices (sites) unless they are determined to be compatible (validated))
creating, by the device, site-specific models, for each of the plurality of sites based on the meta model and the site data (column 3, lines 33-44: Here, a device (site) specific model is generated based on the model and the device constraints (site data) (Figures 4-6))
utilizing, by the device, the site-specific models with corresponding new site data of the plurality of sites to generate predictions for the plurality of sites (column 3, lines 25-44: Here, the device (site) specific models are utilized at each edge device)
It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
Finally, Sims, which is analogous to the claimed invention because it is directed toward comparing, classifying, indexing, and cataloging data, discloses a score matrix (Figure 8; page 10, lines 8-32: Here, a Jensen-Shannon similarity (divergence) matrix is calculated for determining similarity). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Sims with Suleiman-Yang, with a reasonable expectation of success, as it would have allowed for comparing, classifying, indexing, and cataloging data based upon a similarity matrix (Sims: page 2, lines 14-24).
As per dependent claim 2, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Sims discloses wherein the similarity score matrix is a Jensen-Shannon score matrix (Figure 8; page 10, lines 8-32: Here, a Jensen-Shannon similarity (divergence) matrix is calculated for determining similarity). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Sims with Suleiman-Yang, with a reasonable expectation of success, as it would have allowed for comparing, classifying, indexing, and cataloging data based upon a similarity matrix (Sims: page 2, lines 14-24).
As per dependent claim 3, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Yang discloses:
creating a base model for a new site based on the meta model (column 3, lines 25-44: Here, a based model is created for a new site. The base model must be compatible with the meta model)
receiving new site data from the new site (column 3, lines 25-44: Here, a device (site) specific model is generated based on the model and the device constraints (received site data) (Figures 4-6))
utilizing the base model and the new site data to generate predictions for a new site (column 3, lines 25-44: Here, the new model is deployed to generate predictions based upon received data)
It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
As per dependent claim 4, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 3, and the same rejection is incorporated herein. Yang discloses wherein the base model is a generic model generated from the meta model (column 3, lines 33-44 and column 9, lines 29-43). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
As per dependent claim 5, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Suleiman discloses wherein each of the plurality of sites includes:
one or more server devices
one or more network devices (Figure 8; paragraph 0118)
or one or more data structures
As per dependent claim 6, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Suleiman discloses wherein similarity score provides an indication of similar data distributions associated with the site data (paragraphs 0077-0080: Here, the similarity of a dataset is determined by comparing the similarity score of the data set to the other suitable datasets).
With respect to independent claim 8, the claim recites the device for performing the method of claims 1 and 6. Claim 8 is rejected under similar rationale.
Further, Suleiman discloses a device comprising one or more memories (Figure 7, item 1408) and one or more processors (Figure 7, item 1407).
As per dependent claim 9, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Yang discloses wherein the meta model is a neural network model (column 2, lines 6-19: Here, a neural network is a machine learning model that is updated and deployed to the edge devices).
It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
As per dependent claim 10, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Yang discloses training the meta model based on the training data and a model agnostic meta learning model (column 3, lines 33-44 and column 9, lines 29-43). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
As per dependent claim 11, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Yang discloses wherein the one or more processors, to train the meta model based on the training data are to train the meta model, based on the training data, to generate site-specific weights to be tuned to create the site-specific models (column 10, lines 5-46: Here, model generation for edge devices implements weight compatibility. This includes implementing weight determination training to tune the model). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
As per dependent claim 13, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Yang discloses wherein each of the site-specific models learns with less data than required for models not generated based on the meta model (column 9, line 44- column 10, line 4: Here, the site-specific models are derived from the initial machine learning model. The site-specific models are therefore generated without receiving training data). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
As per dependent claim 14, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Yang discloses wherein each of the plurality of sites includes multiple machines (column 3, lines 33-44). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Yang with Suleiman, with a reasonable expectation of success, as it would have allowed for generating machine learning models based upon resource constraints while maintaining compatibility across the models deployed at different devices (sites) (Yang: column 2, lines 20-33).
Suleiman fails to specifically disclose wherein the machine is a virtual machine. However, the examiner takes official notice that virtual machines were notoriously well-known in the art at the time of the applicant’s effective filing date as providing the ability to implement multiple hosts on a single physical machine. It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined the well-known with Suleiman-Yang-Sims, with a reasonable expectation of success, as it would have allowed for implementing multiple machine learning models on a single hardware device.
With respect to independent claim 15, the claim recites the non-transitory computer-readable medium storing a set of instructions for implementing the method of claims 1 and 5. Claim 15 is rejected under similar rationale.
Additionally, Suleiman discloses a non-transitory computer-readable medium storing a set of instructions (claim 17).
With respect to dependent claim 16, the claim recites the limitations substantially similar to those in claims 3 and 4. Claim 16 is rejected under similar rationale.
With respect to dependent claim 18, the claim recites the limitations substantially similar to those in claim 10. Claim 18 is rejected under similar rationale.
With respect to dependent claim 19, the claim recites the limitations substantially similar to those in claim 11. Claim 19 is rejected under similar rationale.
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Suleiman, Yang, and Sims and further in view of Bacha (US 2020/0320147, published 8 October 2020).
As per dependent claim 7, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Suleiman discloses grouping data into clusters based on the similarity score (paragraph 0053).
However, Suleiman fails to specifically disclose grouping the data into hierarchical data clusters based on the similarity score matrix. Bacha, which is analogous to the claimed invention because it is directed toward hierarchical clustering, discloses grouping the data into hierarchical data clusters based on the similarity score matrix (paragraph 0102: Here, the data is grouped into hierarchical data clusters based upon the distance matrix and similarity scores). It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Bacha with Suleiman-Yang-Sims, with a reasonable expectation of success, as it would have allowed for creating a dendrogram to show relationships based upon a hierarchical structure (Bacha: paragraph 0101).
With respect to dependent claim 17, the claim recites the limitations substantially similar to those in claim 7. Claim 17 is rejected under similar rationale.
Claims 12 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Suleiman, Yang, and Sims and further in view of Cardella et al. (US 12148417, filed 22 June 2021, hereafter Cardella).
As per dependent claim 12, Suleiman, Yang, and Sims disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Suleiman fails to specifically disclose:
create the models based on training the meta model with the training data
calculate losses associated with the specific models
utilize the losses to learn gradients
update the meta model based on the gradients
However, Cardella, which is analogous to the claimed invention because it is directed toward training models, discloses:
create the models based on training the meta model with the training data (column 2, lines 1-16: Here, a model is trained based upon training data)
calculate losses associated with the specific models (column 2, lines 45-57: Here, a cost/loss function is calculated that describes the difference between the expected output and the actual output)
utilize the losses to learn gradients (column 2, lines 45-57: Here, a gradient descent algorithm is used to adjust the weights to decrease the output of the loss function)
update the meta model based on the gradients (column 2, lines 45-57: Here, the parameters of the machine learning model are updated to implement the changes to minimize the loss)
It would have been obvious to one of ordinary skill in the art at the time of the applicant’s effective filing date to have combined Cardella with Suleiman-Yang-Sims, with a reasonable expectation of success, as it would have allowed for improving the model via iterative training (Cardella: column 2, lines 45-57).
With respect to dependent claim 20, the claim recites the limitations substantially similar to those in claim 12. Claim 20 is rejected under similar rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chen et al. (US 2022/0122615): Discloses using similarity scores for hierarchical clustering (paragraph 0024).
Aguilar Achiaga et al. (US 2021/0358065): Discloses applying a hierarchical clustering model using the similarity scores as weights.
Shachar (US 12481890): Discloses using a machine learning optimization algorithm to train an analytic model using gradient decent with the meta-ML optimization engine (claim 9).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KYLE R STORK whose telephone number is (571)272-4130. The examiner can normally be reached 8am - 2pm; 4pm - 6pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez Rivas can be reached at 571/272-2589. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KYLE R STORK/Primary Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128