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 31 August 2024 and the preliminary amendment filed 9 March 2026. Claims 1-15, 24, and 32-35 are pending. Claims 1, 24, and 32 are independent claims. Claims 16-23 and 25-31 are cancelled. Information Disclosure Statement The information disclosure statements (IDS) submitted on 31 August 2023 and 9 February 2024 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 31 August 2023. Claim Objections Claim 14 is objected to because of the following informalities: With respect to claim 14, the claim recites “wherein the compute device is an Edge device within an Edge computing environment (lines 1-2).” The claim appears to unnecessarily capitalize the work “Edge”. Appropriate correction is required. For the purpose of examination, the examiner will interpret the claim as though it recites “wherein the compute device is an edge device and within an edge computing environment.” Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b ) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the appl icant regards as his invention. Claims 33-35 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. With respect to dependent claim 33, the claim recites the “non-transitory machine readable storage medium of claim 16 (line 1).” However, claim 16 has been cancelled by the supplemental amendment filed 9 March 2026. Therefore, claim 33 depends upon a cancelled base claim. For the purpose of examination, and consistent with the preliminary amendment filed 31 August 2023, the examiner will treat claim 33 as though it recites the “non-transitory machine readable storage medium of claim 32 [[16]].” Appropriate correction is required. With respect to dependent claim 34, the claim recites the “non-transitory machine readable storage medium of claim 17 (line 1).” However, claim 17 has been cancelled by the supplemental amendment filed 9 March 2026. Therefore, claim 34 depends upon a cancelled base claim. For the purpose of examination, and consistent with the preliminary amendment filed 31 August 2023, the examiner will treat claim 34 as though it recites the “non-transitory machine readable storage medium of claim 33 [[17]].” Appropriate correction is required. With respect to dependent claim 35, the claim recites the “non-transitory machine readable storage medium of claim 18 (line 1).” However, claim 18 has been cancelled by the supplemental amendment filed 9 March 2026. Therefore, claim 35 depends upon a cancelled base claim. For the purpose of examination, and consistent with the preliminary amendment filed 31 August 2023, the examiner will treat claim 35 as though it recites the “non-transitory machine readable storage medium of claim 34 [[18]].” Appropriate correction is required. 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 1-15, 24, and 32-35 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Step 1: According to Step 1 of the two Step analysis, claims 1-14 are directed toward an apparatus (machine). Claims 24 is directed toward a method (process). Claims 32-35 are directed toward a non-transitory machine readable medium (manufacture). Therefore, each of these claims falls within one of the four statutory categories. Claim 1 : Step 2A, Prong 1: With respect to claim 1, the claim recites: create a super-network based on the pre-trained machine learning model (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 creation of a super-network based upon a user observation of a pre-trained machine learning model ) create a plurality of subnetworks based on the super-network (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 creation of a plurality of subnetworks based upon a user evaluation of the super-network) search the plurality of subnetworks to select a subnetwork (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 evaluation of a plurality of subnetworks using a set of search parameters to select a subnetwork) Step 2A, Prong 2: The claims disclose the following additional elements: at least one memory machine readable instructions processor circuitry to at least one of instantiate or execute the machine readable instructions These additional elements of a memory, machine readable instructions, and processing circuitry to at least one of instantiate or execute the machine readable instructions 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)). The claim discloses the additional elements: access a pre-trained machine learning model The machine learning model and use of the machine learning model is recited at a high-level of generality and amounts 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: The claims disclose the following additional elements: at least one memory machine readable instructions processor circuitry to at least one of instantiate or execute the machine readable instructions These additional elements of a memory, machine readable instructions, and processing circuitry to at least one of instantiate or execute the machine readable instructions 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)). The claim discloses the additional elements: access a pre-trained machine learning model The machine learning model and use of the machine learning model is recited at a high-level of generality and amounts 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. The analysis of claim 1 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 2, the claim recites: determine whether a laye r of the pre-trained machine learning model is of a type that can be converted to an elastic layer (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 an observation to determine that the layer can be converted to an elastic layer ) responsive to the determination that the layer is of a type that can be converted to the elastic layer, convert the layer to the elastic layer, and add the elastic layer to the super-network (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 determination that the layer may be converted to an elastic layer, converting the layer, and adding the layer to the observed super-network ) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 3 : With respect to dependent claim 3, the claim depends upon dependent claim 2. The analysis of claim 2 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 3, the claim recites: wherein the elastic layer includes at least one variable property (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 an observation to determine that the layer can be converted to an elastic layer based upon identifying at least variable property) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 4 : With respect to dependent claim 4, the claim depends upon dependent claim 3. The analysis of claim 3 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 4, the claim recites: wherein the variable property is a variable depth of the elastic layer (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 an observation to determine that the layer can be converted to an elastic layer based upon identifying at least variable property, wherein the variable property is a variable depth of the elastic layer) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 5 : With respect to dependent claim 5, the claim depends upon dependent claim 3. The analysis of claim 3 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 5, the claim recites: wherein the variable property is a variable width of the elastic layer (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 an observation to determine that the layer can be converted to an elastic layer based upon identifying at least variable property, wherein the variable property is a variable width of the elastic layer) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 6 : With respect to dependent claim 6, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 6, the claim recites: wherein… prior to extraction of the plurality of subnetworks, modify the super-network based on training 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. The examiner notes that the claimed super-network has not been defined as a machine learning model. Therefore, f or example, this limitation encompasses an evaluation of some training data to modify a network) Step 2A, Prong 2: The claim discloses the additional elements: processor circuitry These additional elements of a memory, machine readable instructions, and processing circuitry to at least one of instantiate or execute the machine readable instructions 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: The claim discloses the additional elements: processor circuitry These additional elements of a memory, machine readable instructions, and processing circuitry to at least one of instantiate or execute the machine readable instructions 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 7 : With respect to dependent claim 7, the claim depends upon dependent claim 6. The analysis of claim 6 is incorporated herein by reference. Step 2A, Prong 1: The claim is directed to the same abstract idea identified with respect to claim 6. Step 2A, Prong 2: The claim discloses the additional elements: wherein the modification of the super-network is performed using a training algorithm Computer training is recited at a high-level of generality with no detail of the training process and amounts 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: The claim discloses the additional elements: wherein the modification of the super-network is performed using a training algorithm Computer training is recited at a high-level of generality with no detail of the training process and amounts 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 8 : With respect to dependent claim 8, the claim depends upon dependent claim 7. The analysis of claim 7 is incorporated herein by reference. Step 2A, Prong 1: The claim is directed to the same abstract idea identified with respect to claim 7. Step 2A, Prong 2: The claim discloses the additional elements: wherein the training algorithm is Progressive Shrinking Computer training is recited at a high-level of generality with no detail of the training process and amounts 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 discloses the additional elements: wherein the training algorithm is Progressive Shrinking Computer training is recited at a high-level of generality with no detail of the training process and amounts 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 9 : With respect to dependent claim 9, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 9, the claim recites: wherein the selection of the sub-network is based at least on at least one of a performance of a performance characteristic of the sub-network (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 an evaluation of a performance of a performance characteristic to enable selection) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 10 : With respect to dependent claim 10, the claim depends upon dependent claim 9. The analysis of claim 9 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 10, the claim recites: wherein the performance characteristic of the sub-network is an estimated performance characteristic (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 an evaluation, such as an estimation, of a performance of a performance characteristic to enable selection) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 11 : With respect to dependent claim 11, the claim depends upon dependent claim 9. The analysis of claim 9 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 11, the claim recites: wherein the selection of the sub-network is based on the performance characteristic meeting or exceeding a corresponding performance characteristic of the pre-trained machine learning model (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 an evaluation of a performance of a performance characteristic to determine it meets or exceeds a threshold) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 12 : With respect to dependent claim 12, the claim depends upon dependent claim 11. The analysis of claim 11 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 12, the claim recites: wherein the performance characteristic is accuracy (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 an evaluation of a performance of a performance characteristic to determine accuracy) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 13 : With respect to dependent claim 13, the claim depends upon independent claim 1. The analysis of claim 1 is incorporated herein by reference. Step 2A, Prong 1: The claim is directed to the same abstract idea identified with respect to claim 1. Step 2A, Prong 2: The claims disclose the following additional elements: wherein the processor is to distribute the selected sub-network to a compute device for execution These additional element of distributing a selected sub-network to a compute device for execution is 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: The claims disclose the following additional elements: wherein the processor is to distribute the selected sub-network to a compute device for execution These additional element of distributing a selected sub-network to a compute device for execution is 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 14 : With respect to dependent claim 14, the claim depends upon dependent claim 13. The analysis of claim 13 is incorporated herein by reference. Step 2A, Prong 1: The claim is directed to the same abstract idea identified with respect to claim 13. Step 2A, Prong 2: The claims disclose the following additional elements: wherein the compute device is an Edge device within an Edge computing environment These additional element of compute device is an Edge device within an Edge computing environment is 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: The claims disclose the following additional elements: wherein the compute device is an Edge device within an Edge computing environment These additional element of compute device is an Edge device within an Edge computing environment is 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 15 : With respect to dependent claim 15, the claim depends upon dependent claim 13. The analysis of claim 13 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 15, the claim recites: select the sub-network such that an operational characteristic of the sub-network meets an operational requirement of the compute device (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 an evaluation of operational characteristics of a sub-network and a computing device in order to select a sub-network) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 24 : Step 2A, Prong 1: With respect to claim 24, the claim recites: c reating… a super-network based on the pre-trained machine learning model (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 creation of a super-network based upon a user observation) extracting… a plurality of subnetworks from the super-network (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 creation of a plurality of subnetworks based upon a user evaluation of the super-network) searching the plurality of subnetworks to select a subnetwork (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 evaluation of a plurality of subnetworks using a set of search parameters to select a subnetwork) Step 2A, Prong 2: The claims disclose the following additional elements: executing an instruction with at least one processor These additional element executing an instruction with at least one processor is 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)). The claim discloses the additional elements: access a pre-trained machine learning model The machine learning model and use of the machine learning model is recited at a high-level of generality and amounts 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: The claims disclose the following additional elements: executing an instruction with at least one processor These additional element executing an instruction with at least one processor is 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)). The claim discloses the additional elements: access a pre-trained machine learning model The machine learning model and use of the machine learning model is recited at a high-level of generality and amounts 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 32 : Step 2A, Prong 1: With respect to claim 32, the claim recites: create a super-network based on the pre-trained machine learning model (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 creation of a super-network based upon a user observation) create a plurality of subnetworks based on the super-network (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 creation of a plurality of subnetworks based upon a user evaluation of the super-network) search the plurality of subnetworks to select a subnetwork (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 evaluation of a plurality of subnetworks using a set of search parameters to select a subnetwork) Step 2A, Prong 2: The claims disclose the following additional elements: a non-transitory machine readable storage medium comprising instructions that, when executed, cause the processor circuitry to… These additional element of a non-transitory machine readable storage medium comprising instructions that, when executed, cause the processor circuitry is 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)). The claim discloses the additional elements: access a pre-trained machine learning model The machine learning model and use of the machine learning model is recited at a high-level of generality and amounts 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: The claims disclose the following additional elements: a non-transitory machine readable storage medium comprising instructions that, when executed, cause the processor circuitry to… These additional element of a non-transitory machine readable storage medium comprising instructions that, when executed, cause the processor circuitry is 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)). The claim discloses the additional elements: access a pre-trained machine learning model The machine learning model and use of the machine learning model is recited at a high-level of generality and amounts 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 33 : With respect to dependent claim 33, the claim depends upon independent claim 32. The analysis of claim 32 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 33, the claim recites: determine whether a laye r of the pre-trained machine learning model is of a type that can be converted to an elastic layer (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 an observation to determine that the layer can be converted to an elastic layer) responsive to the determination that the layer is of a type that can be converted to the elastic layer, convert the layer to the elastic layer, and add the elastic layer to the super-network (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 determination that the layer may be converted to an elastic layer, converting the layer, and adding the layer to the observed super-network) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 34 : With respect to dependent claim 34, the claim depends upon dependent claim 33. The analysis of claim 33 is incorporated herein by reference. Step 2A, Prong 1: With respect to claim 34, the claim recites: wherein the elastic layer includes at least one variable property (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 an observation to determine that the layer can be converted to an elastic layer based upon identifying at least variable property) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Claim 35 : With respect to dependent claim 35, the claim depends upon dependent claim 34. The analysis of claim 34 is incorporated herein by reference. 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 35, the claim recites: wherein the variable property is a variable number of channels of the elastic layer (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 an observation to determine that the variable property is a variable number of channels of the elastic layer) Step 2A, Prong 2: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. Step 2B: The claim does not recite any additional elements that when considered alone or in combination provide a practical application or amount to significantly more than the abstract idea. 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. Claim s 1-15, 24, and 32-35 are rejected under 35 U.S.C. 103 as being unpatentable over Yang et al. ( NetAdaptV2: Efficient Neural Architecture Search with Fast Super-Network Training and Architecture Optimization , provided by applicant on IDS filed 31 August 2023, published 31 March 2021, hereafter Yang) and further i n view of Yu et al. (US 2022/0405579, provisional filed 5 March 2020, hereafter Yu). As per independent claim 1, Yang discloses modifying pre-trained machine learning models, the instructions comprising: access a pre-trained machine learning model (Section 2.1: Here, a super network is trained to have the same architecture as an initial network. The initial network is a pre-trained machine learning model, deep neural network (Abstract; Section 1), having sub-networks (Figure 2)) create a super-network based on the pre-trained machine learning model (Section 1; Figure 2: Here, a super-network is trained using the initial networks, DNN, as input . The super-network shares weights across all the DNNs in a search space and is trained by minimizing loss across the DNNs ) create a plurality of subnetworks based on the super-network (Section 2.1: Here, a plurality of sub-networks with different layer widths, network depths, and kernel sizes are created to train and optimize the super-network) search the plurality of subnetworks to select a subnetwork (Section 2.1: Here, the process of sampling the search space to generate samples and determining the next set of samples based upon the current performance continues until a stop criteria is met. At his point, the discovered DNN is trained until convergence) Yang fails to specifically disclose: an apparatus comprising: at least one memory machine readable instructions processor circuitry to at least one of instantiate or execute the machine readable instructions However, Yu , which is analogous to the claimed invention because it is directed to modifying machine learning models, discloses: an apparatus (paragraph 0099 : Here, a computer is an apparatus) comprising: at least one memory (paragraph 0099 : Here, the computer includes a memory) machine readable instructions (paragraph 0099 : Here, the computer includes a central processing unit for executing machine readable instructions) processor circuitry to at least one of instantiate or execute the machine readable instructions (paragraph 0099 : Here, the central processing unit is processing circuitry) 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 Yoon with Yang, with a reasonable expectation of success, as it would have allowed for executing the modification of a machine learning model on a computer device ( Yu : paragraph 0099 ). As per dependent claim 2, Yang and Yu disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Yang discloses wherein to create the super-network: determine whether a layer of the pre-trained machine learning model is of a type that can be converted to an elastic layer (Figure 3; Sections 2-2 and 2.3: Here, it is determined whether a layer may be removed by determining that the removal does not result in the number of output channels becoming zero) responsive to the determination that the layer is of a type that can be converted to the elastic layer, convert the layer to the elastic layer and add the elastic layer to the super-network (Figure 3; Sections 2.2 and 2.3: Here, when it is determined that the number of output channels will not become zero, filters may be removed and channels may be bypassed. If a channel may be bypassed, that channel is considered to be elastic) As per dependent claim 3, Yang and Yu disclose the limitations similar to those in claim 2, and the same rejection is incorporated herein. Yang discloses wherein the elastic layer includes at least one variable property (Section 2.5: Here, the network depth, layer widths, and kernel sizes are variable properties). As per dependent claim 4, Yang and Yu disclose the limitations similar to those in claim 3, and the same rejection is incorporated herein. Yang discloses wherein the variable property is a variable depth of the elastic layer (Section 2.5: Here, the network depth is a variable depth of the elastic layer). As per dependent claim 5, Yang and Yu disclose the limitations similar to those in claim 3, and the same rejection is incorporated herein. Yang discloses wherein the variable property is a variable width of the elastic layer (Section 2.5: Here, the layer width is a variable width of the elastic layer). As per dependent claim 6, Yang and Yu disclose the limitations similar to those in claim 1, and the same rejection is incorporated herein. Yang discloses prior to extraction of the plurality of subnetworks, modify the super-network based on training data (Section 2.1: Here, an initial network and uses the subnetworks by shrinking layers in the initial network. The sub-networks are trained by the super-network using shared weights). As per dependent claim 7, Yang and Yu disclose the limitations similar to those in claim 6, and the same rejection is incorporated herein. Yang discloses wherein the modification of the super-network is performed using a training algorithm (Section 2.1; Figure 2: Here, a super-network is trained using a superkernel). As per dependent claim 8, Yang and Yu disclose the limitations similar to those in claim 7, and the same rejection is incorporated herein. Yang fails to specifically disclose wherein the training algorithm is Progressive Shrinking. However, Yu, which is analogous to the claimed invention because it is directed toward training a super-network, discloses training using a progressive shrinking algorithm (paragraph 0050: Here, a large neural network is trained and progressively distilled to obtain smaller neural networks through additional training). 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 combine Yu with Yang -Yu , with a reasonable expectation of success, as it would have allowed for adj