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 final office action is in response to the amendment filed 10 April 2026.
Claims 1-3, 5-10, 12-18, and 20-23 are pending. Claims 21-23 are newly added. Claims 4, 11, and 19 are cancelled. Claims 1, 8, and 15 are independent claims.
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, 5-10, 12-18, and 20-22 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 1-3, 5-7, and 21 are directed toward a process. Claims 8-10, 12-14, and 22 are directed toward a machine. Claims 15-18, 20, and 23 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 in a network and cloud computing system” 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 to generate site-specific weights for each of the plurality of sites
validating… the meta model based on the validation data to create a generic model
tuning… the generic model using the site data and the site-specific weights to generate a plurality of site-specific models, for each of the plurality of sites, based on the site-specific weights 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 in a network and cloud computing system” 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 to generate site-specific weights for each of the plurality of sites
validating… the meta model based on the validation data to create a generic model
tuning… the generic model using the site data and the site-specific weights to generate a plurality of site-specific models, for each of the plurality of sites, based on the site-specific weights 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))
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
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 1:
The claim recites the abstract idea identified with respect to claim 1.
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.
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.
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 1:
The claim recites the abstract idea identified with respect to claim 1.
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))
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
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))
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
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 1:
The claim recites the abstract idea identified with respect to claims 1 and 6.
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 1:
The claim recites the abstract idea identified with respect to claim 8.
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 1:
The claim recites the abstract idea identified with respect to claim 8.
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 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 1:
The claim recites the abstract idea identified with respect to claim 8.
Step 2A, Prong 2:
With respect to claim 12, the claim recites the additional element “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 “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 1:
The claim recites the abstract idea identified with respect to claim 8.
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 1:
The claim recites the abstract idea identified with respect to claim 8.
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 1:
The claim recites the abstract idea identified with respect to claims 1 and 5.
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 claim 3. The analysis of claims 3 is 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 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 21:
With respect to dependent claim 21, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein by reference.
Step 2A, Prong 1:
The claim recites the abstract idea identified with respect to claim 1.
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)).
The claim recites the additional elements:
wherein the site data includes raw data identifying communications in the network and cloud computing systems between the one or more: server devices, network devices, or data structures
This 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 courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
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 recites the additional elements:
wherein the site data includes raw data identifying communications in the network and cloud computing systems between the one or more: server devices, network devices, or data structures
This 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 courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
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 22:
With respect to dependent claim 22, the claim depends upon independent claim 8. The analysis of claim 8 is incorporated herein by reference.
Step 2A, Prong 1:
The claim recites the abstract idea identified with respect to claim 8.
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)).
The claim recites the additional elements:
wherein the key performance indicators include one or more of: bandwidths, throughputs, signal strengths, availability indicators, network resource indicators, voice service indicators, or data service indicators.
This 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 courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
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 recites the additional elements:
wherein the key performance indicators include one or more of: bandwidths, throughputs, signal strengths, availability indicators, network resource indicators, voice service indicators, or data service indicators.
This 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 courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
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 23:
With respect to dependent claim 23, the claim depends upon independent claim 15. The analysis of claim 15 is incorporated herein by reference.
Step 2A, Prong 1:
The claim recites:
detect anomalies at the plurality of sites (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 a judgement to determine whether the received data is anomalous)
Step 2A, Prong 2:
There are no additional elements considered under Step 2A, Prong 2.
Step 2B:
There are no additional elements considered under Step 2B.
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 1-3, 5-6, 8-10, 13-16, 18, 21, and 23 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) and further in view of Madhavan et al. (US 2023/0094940, filed 27 September 2021, hereafter Madhavan).
As per independent claim 1, Suleiman discloses a method, comprising:
receiving, by a device, data identifying raw data or key performance indicators for network traffic (paragraph 0092) associated with a plurality of sites in a network and cloud computing system (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
generate site-specific weights for each of the plurality of sites
validating, by the device the meta model based on the validation data, to create a generic model
tuning, by the device, the generic model using the site data and the site-specific weights to generate a plurality of site specific models, for each of the plurality of sites, based on site-specific model weights 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).
Additionally, 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).
Finally, Madhavan, which is analogous to the claimed invention because it is directed toward continuous learning, discloses:
generate site-specific weights for each of the plurality of sites (paragraphs 0021-0024: Here, site specific variables are used for site-specific tuning of a global model. This includes tuning based upon layer weights)
create a generic model (paragraphs 0021-0025)
tuning, by the device, the generic model using the site data and the site-specific weights to generate a plurality of site specific models, for each of the plurality of sites, based on site-specific model weights and the site data (paragraphs 0021-0025: Here, an incremental site-specific tuning is performed to create local versions/model from the generic (global) 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 Madhavan with Suleiman-Yang-Sims, with a reasonable expectation of success, as it would have allowed for optimizing a model based upon site-specific preferences (Madhavan: paragraph 0025).
As per dependent claim 2, Suleiman, Yang, Sims, and Madhavan 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, Sims, and Madhavan disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Yang discloses:
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 5, Suleiman, Yang, Sims, and Madhavan 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, Sims, and Madhavan 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, Sims, and Madhavan 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, Sims, and Madhavan 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 13, Suleiman, Yang, Sims, and Madhavan 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, Sims, and Madhavan 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.
As per dependent claim 21, Suleiman, Yang, Sims, and Madhavan disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Suleiman discloses wherein the site data includes raw data identifying communications in the network and cloud computing system between the one or more server devices, network devices, or data structures (Figure 7; paragraphs 0120-0122).
As per dependent claim 23, Suleiman, Yang, Sims, and Madhavan disclose the limitations similar to those in claim 15, and the same rejection is incorporated herein. Suleiman disclose detect anomalous at a plurality of sites (paragraph 0026: Here, anomalous behavior at a user device causes an alert to be generated at an administrator console).
Claims 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Suleiman, Yang, Sims, and Madhavan and further in view of Bacha (US 2020/0320147, published 8 October 2020).
As per dependent claim 7, Suleiman, Yang, Sims, and Madhavan 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-Madhavan, 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, Sims, and Madhavan and further in view of Cardella et al. (US 12148417, filed 22 June 2021, hereafter Cardella).
As per dependent claim 12, Suleiman, Yang, Sims, and Madhavan 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.
Claim 22 is rejected under 35 U.S.C. 103 as being unpatentable over Suleiman, Yang, Sims, and Madhavan and further in view of Veggalam et al. (US 2022/0124574, filed 19 October 2021, hereafter Veggalam).
As per dependent claim 22, Suleiman, Yang, Sims, and Madhavan disclose the limitations similar to those in claim 8, and the same rejection is incorporated herein. Suleiman fails to specifically disclose wherein the key performance indicators include one or more of: bandwidths, throughputs, signal strengths, availability indicators, network resource indicators, voice service indicators, or data service indicators.
However, Veggalam, which is analogous to the claimed invention because it is directed toward training a machine learning model using KPI, discloses wherein the key performance indicators include one or more of: bandwidths, throughputs (paragraph 0012), signal strengths, availability indicators, network resource indicators, voice service indicators, or data service indicators. 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 Veggalam with Suleiman-Yang-Sims-Madhavan, with a reasonable expectation of success, as it would have allowed for training a machine learning model to optimize performance metrics such as throughput (Veggalam: paragraph 0012).
Response to Arguments
Applicant’s arguments with respect to the rejection of claims under 35 USC 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Suleiman, Yang, Sims, and Madhavan.
Applicant's arguments filed 10 April 2025 have been fully considered but they are not persuasive.
The applicant’s initial argument is that the claim is not an abstract idea because it is not a mental process (pages 10-11). To support this position, the applicant argues that “receiving, by a device, site data identifying raw data or key performance indicator for network traffic with a plurality of sites in a network and cloud system” is not a mental process (page 11). The examiner agrees with this assessment. The examiner considered this limitation as additional elements under Step 2A, Prong 2 and Step 2B.
The applicant further argues that that “identifying, by the device, training data and validation data based on data clusters” is not a mental process (page 11). While the examiner considers “the device” under Step 2A, Prong 2 and Step 2B as an additional element, “identifying… training data and validation data based on data clusters” is a mental process. This limitation encompasses identifying data sets, including training data and validation data based upon a previous evaluation and judgement. For this reason, this argument is not persuasive.
The applicant further argues that “training, by the device, the metamodel based on the training data to generate site-specific weights for each of the plurality of sites,” “tuning, by the device, the generic model using the site data and the site-specific weights to generate a plurality of site-specific models, for each of the plurality of sites, based on the site-specific weights and the site data” is not a mental process,” and “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” is not a mental process. Again, the examiner agrees with this assessment. Instead, the examiner considers these limitations under Step 2A, Prong 2 and Step 2B.
For these reasons, these arguments are not persuasive.
The applicant further argues that the claims integrate the abstract idea into a practical application by improving the functioning of a computer or another technology field (pages 12-14). The examiner respectfully disagrees.
When considering improvements to the functioning of a computer or another technology field, the examiner must whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or mere instructions to implement an abstract idea or other exception on a computer (MPEP 2106.05(f)). Additionally, for improvements considerations, examiners are reminded that there are other judicial considerations to evaluate whether additional elements in the claim integrate a judicial exception into a practical application at Step 2A Prong Two (MPEP 2106.04(d)(2) and 2106.05(b)-(c), (e) and (g)-(h)) or amount to an inventive concept at Step 2B (MPEP 2106.05(b)-(e) and (g)-(h)).
Claims that are determined to improve computer capabilities or improve technology or a technical field support a finding that the claim integrates the judicial exception into a practical application or amounts to significantly more than the judicial exception itself. In this particular instance, the claim does not integrate the judicial exception identified by the examiner in Step 2A, Prong 1 into a practical application or amount to significantly more than the judicial exception itself. For this reason, this argument is not persuasive.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Hirzallah et al. (US 2023/0037704, filed 6 August 2021): Discloses fine-tuning a model to generate a site-specific/device-specific model based upon the training dataset (paragraph 0123)
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
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
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