Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are presented for examination.
Information Disclosure Statement
The information disclosure statement (IDS) was submitted on March 16th, 2026. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments, see Pages 10-11, filed March 16th, 2026, with respect to the drawing objections and 35 U.S.C. 103 rejections have been fully considered and are persuasive. The drawing objection and 35 U.S.C. 103 of claims 1-20 have been withdrawn.
Applicant’s arguments with respect to the rejections of claims 1-20 under 35 U.S.C § 101 are not persuasive for the following reasons:
Applicant asserts “The Action rejects claims 1-20 under 35 U.S.C 101 as allegedly being directed toward non-statutory subject matter.” (See Page 12 of remarks). As a preliminary matter, contrary to applicant’s assertion, examiner notes that claims 1-20 were rejected under 35 U.S.C 101 as being directed to an abstract idea without significantly more, not as being directed to non-statutory subject matter.
Applicant’s remaining arguments regarding the rejections under section 101 are addressed below.
35 U.S.C. 101:
Step 2A Prong 1:
Applicant argues that independent claims 1, 16, and 20 (See Page 12 of remarks) are not directed to a mental process because it requires a neural network and layer-wise computations that cannot be practically performed in the human mind. The Examiner respectfully disagrees. As detailed below in the rejections, the recited mental process steps (e.g., determining relevance scores, generating scores based on weights/biases) and the mathematical concept step (e.g. forming vectors via dot products) are abstract ideas that can be performed conceptually in the human mind or with pen and paper. The claimed limitation “determining a first output relevance score based on the first network output…” was analyzed under Step 2A Prong One as being an abstract idea. The action of determining a relevance score is a limitation recited at a high-level of generality and, under the Broadest Reasonable Interpretation (BRI), can be interpreted as a process of human observation, evaluation, judgement, or opinion. There are no explicit steps or details recited that meaningfully limit the claimed limitation to falling outside the grouping of abstract ideas. The claimed limitation can be performed mentally with the aid of pen and paper, and is therefore a mental process.
The claimed limitation “generating a plurality of first relevance scores… based on the first output relevance score the neuron weights in the last layer, and the neuron biases in a lower layer…” was analyzed under Step 2A Prong One as being an abstract idea. The action of determining a relevance score is a limitation recited at a high-level of generality and, under the Broadest Reasonable Interpretation (BRI), can be interpreted as a procedure of human observation, evaluation, judgement, or opinion. There are no explicit steps or details recited that meaningfully limit the claimed limitation to falling outside the grouping of abstract ideas. The claimed limitation can be performed mentally with the aid of pen and paper, and is therefore a mental process.
The claimed limitation “generating a plurality of first relevance scores… based on the first output relevance score the neuron weights in the last layer, and the neuron biases in a lower layer…” was analyzed under Step 2A Prong One as being an abstract idea. The action of generating relevance scores based on the weights and biases is a limitation recited at a high-level of generality and, under BRI, can be interpreted as a procedure of human observation, evaluation, judgement, or opinion. There are no explicit steps or details recited that meaningfully limit the claimed limitation to falling outside the grouping of abstract ideas. The claimed limitation can be performed mentally with the aid of pen and paper, and is therefore a mental process.
The claimed limitation “generating a local explainability dataset comprising the first feature relevance vector; and generating a local explanation of a prediction of the neural network model based on the local explainability dataset” was analyzed under Step 2A Prong One as being an abstract idea. The action of generating a local explainability dataset and a local explanation is a limitation recited at a high-level of generality and, under BRI, can be interpreted as a procedure of human observation, evaluation, judgement, or opinion. There are no explicit steps or details recited that meaningfully limit the claimed limitation to falling outside the grouping of abstract ideas. The claimed limitation can be performed mentally with the aid of pen and paper, and is therefore a mental process.
The claimed limitation “forming a first feature relevance vector based on a dot product of the first test input vector and a vector comprising the plurality of first relevance scores obtained at the first layer…” was analyzed under Step 2A Prong One as being an abstract idea. The action of computing a dot product between two vectors is a limitation that can be interpreted as a mathematical concept, including a mathematical relationship, calculation, or formula (See MPEP 2106.04(a)(2)). There are no explicit steps or details recited that meaningfully limit the claimed limitation to falling outside the grouping of abstract ideas. The claimed limitation merely involves manipulation of data using mathematical operations, and is therefore a mathematical concept.
Even when in consideration as an ordered combination, the recited sequence of transformations amounts to mathematical operations (e.g. calculating, propagating, and combining values) performed on data at a high level of generality without reciting a specific technological improvement.
Step 2A Prong 2:
Applicant argues that the claims are directed to an improvement in neural network technology, particularly with respect to explainability and model performance. However, the argument is not persuasive. The claim does not recite a specific improvement to the functioning of the neural network itself (e.g. improved architecture, training technique, or efficiency), but instead uses the neural network as a tool to perform math analysis (relevance scoring and explanation generation).
Applicant argues that the reverse propagation of relevance scores is a technical process rooted in computer technology. However, the argument is not persuasive because the reverse propagation of the relevance scores is recited at a high level and amounts to mathematical manipulation of values (e.g. linear combinations using weights and biases). The claim lacks specific implementation details that would tie this operation to a particular technological improvement, and thus remains a mathematical concept.
Applicant argues that the claims provide a practical application by generating and presenting explanations to users. However, the argument is not persuasive because the steps of generating and presenting explanations are recited at a high level and merely involve outputting results of abstract calculations. The feedback loop is also recited at a high level of generality without specifying how the user response is used to provide a technological improvement to the model. Instead, it merely indicates that the abstract idea is applied in the context of model refinement, which amounts to field-of -use rather than a meaningful integration to a practical application.
Applicant argues that the office action lacks factual support under Berkheimer and Ex parte Mercer, and that the ordered combination provides an inventive concept. However, the argument is not persuasive. The additional elements are recited at a high level of generality that deals with conventional computer functions (e.g., receiving, processing, and outputting data). The claimed combination merely describes these sequences to provide the purported inventive concept.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an
abstract idea without significantly more.
Claim 1
Step 1: The claim recites a method; therefore, it is directed to the statutory category of processes.
Step2A Prong 1: The claim recites, inter alia:
[D]etermining a first output relevance score based on the first network output: This limitation encompasses a mental process of determining a relevance score based on the network output which can be performed in the human mind.
[G]enerating a plurality of first relevance scores… based on the first output relevance score the neuron weights in the last layer, and the neuron biases in a lower layer: This limitation can be seen as a mental process as it involves generating a relevance score based on the weights and the biases which can be performed in the human mind.
[O]btaining a plurality of first relevance scores corresponding to the expected plurality of input features at a first layer of the sequence of layers by reverse propagating the first relevance scores generated at the last layer through the sequence of layers other than the last layer using the neuron weights and the neuron biases: This limitation is a mathematical concept as it is a calculation that involves linear combinations and activation functions and calculating relevance scores. See Paragraph 61 of the instant specification where it deals with calculating the relevance scores, “In one example, the relevance at each hidden layer can be expressed as follows:
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[F]orming a first feature relevance vector based on a dot product of the first test input vector and a vector comprising the plurality of first relevance scores obtained at the first layer: This limitation is seen as a mathematical concept because it deals with creating a relevance vector based on a group of scores by calculating the dot product of two vectors.
[G]enerating a local explainability dataset comprising the first feature relevance vector; and generating a local explanation of a prediction of the neural network model based on the local explainability dataset: This limitation is seen as a mental process as it deals with generating an explanation of a neural network model using a dataset, which can be performed mentally.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[R]eceiving a request identifying a neural network model, wherein the neural network model comprises a plurality of neurons arranged in a sequence of layers, a plurality of neuron weights distributed across the sequence of layers, a plurality of neuron biases distributed across the sequence of layers, and an input layer configured to receive an input vector with a plurality of input features; feeding a first test input vector having an expected plurality of input features to the input layer to generate a first network output from the neural network model: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
…at a last layer of the sequence of layer… preceding the last layer in the sequence of layers: 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 (MPEP 2106.05(f)).
for improving neural networks: 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 (MPEP 2106.05(f)). This limitation is seen as intended use language with no patentable weight.
presenting the local explanation to a user: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
receiving a user response to the local explanation: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
and updating the neural network model based on the user response: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself (MPEP 2106.05(h)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[R]eceiving a request identifying a neural network model, wherein the neural network model comprises a plurality of neurons arranged in a sequence of layers, a plurality of neuron weights distributed across the sequence of layers, a plurality of neuron biases distributed across the sequence of layers, and an input layer configured to receive an input vector with a plurality of input features; feeding a first test input vector having an expected plurality of input features to the input layer to generate a first network output from the neural network model...: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and is well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
…at a last layer of the sequence of layer… preceding the last layer in the sequence of layers: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
for improving neural networks: 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 and cannot provide inventive concept (MPEP 2106.05(f)). This limitation is seen as intended use language with no patentable weight (e.g. for reduced data processing).
presenting the local explanation to a user: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
receiving a user response to the local explanation: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
and updating the neural network model based on the user response: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself which cannot provide inventive concept (MPEP 2106.05(h)).
The elements in combination as an ordered whole still do not amount to significantly more than the
judicial exception. The claim merely integrates the abstract idea of explaining a neural network model into a computer-implemented process using data gathering and standard computer equipment and implemented instructions.
Therefore, the claim as a whole remains focused on the abstract idea and fails Step 2B of the
eligibility analysis.
Claim 2
Step 1: A process, as above.
Step2A Prong 1: This claim does not recite an additional abstract idea, but the claim depends on
claim 1 which recites an abstract idea.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
the sequence of layers comprises a plurality of hidden layers and the last layer, wherein the first layer of the sequence of layers is one of the hidden layers, and wherein the input layer is a lower layer preceding the first layer: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself (MPEP 2106.05(h)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
the sequence of layers comprises a plurality of hidden layers and the last layer, wherein the first layer of the sequence of layers is one of the hidden layers, and wherein the input layer is a lower layer preceding the first layer: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself which/and cannot provide inventive concept (MPEP 2106.05(h)).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 3
Step 1: A process, as above.
Step2A Prong 1: This claim does not recite an additional abstract idea, but the claim depends on
claim 2 that depends on claim 1, which recites an abstract idea.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
the network output is a probability of a predicted output of a neuron in the last layer of the sequence of layers: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
the network output is a probability of a predicted output of a neuron in the last layer of the sequence of layers: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 4
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[D]etermining the first output relevance score based…: This limitation is seen as a mental process as determining a relevance score based on a network output can be performed mentally.
[A]pplying a probability function to the first network output to obtain a probability: This limitation is a mathematical concept as it deals with using a function to obtain a probability.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[O]n the first network output comprises… a predicted output of a neuron in the last layer of the sequence of layers: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[O]n the first network output comprises… a predicted output of a neuron in the last layer of the sequence of layers: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 5
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[E]ach first relevance score generated at the last layer is a linear combination of a neuron bias in a lower layer preceding the last layer and a neuron weight in the last layer multiplied by the first output relevance score: This limitation is a mathematical concept as it deals with calculating a linear combination of the weight and bias and then multiplying it by the relevance score.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 6
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[R]everse propagating the first relevance scores generated at the last layer through the sequence of layers other than the last layer comprises computing for each one of the hidden layers a plurality of first relevance scores based on one or more neuron weights in the each one of the hidden layers, one or more neuron biases in a lower layer preceding the each one of the hidden layers, and one or more first relevance scores computed in a higher layer succeeding the each one of the hidden layers: This limitation is seen as a mathematical concept as it involves using mathematical functions to calculate the relevance scores in the back propagation phase.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 7
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[E]ach first relevance score computed at each one of the hidden layers is a linear combination of a weighted relevance term and a bias term, wherein the weighted relevance term is based on the neuron weights in the each one of the hidden layers and the first relevance scores in the higher layer succeeding the each one of the hidden layers, and wherein the bias term is based on the neuron biases in the lower layer preceding the each one of the hidden layers: This limitation is seen as a mathematical concept as it involves calculating the linear combination of the weight, bias, and the relevance score.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 8
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[D]iscarding the first relevance scores: This limitation is a mental process as it deals with discarding a score, which can be performed in the human mind.
[C]omputed at a higher layer succeeding the each one of the hidden layers after computing the first relevance scores at the each one of the hidden layers: This limitation is a mathematical concept since it deals with using a function to calculate the relevance score in the backpropagation phase.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 9
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
reverse propagating the plurality of first relevance scores generated at the last layer through the sequence of layers other than the last layer comprises computing for each of the hidden layers a plurality of first relevance scores without using neuron activations in the hidden layers: This limitation involves reverse propagating the relevance scores which uses a function for the calculation, thus reciting a mathematical concept.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 10
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[T]he request further identifies a test input dataset comprising a plurality of test input vectors… selecting the first test input vector from the test input dataset: This limitation is seen as a mental process as it involves identifying a input dataset and selecting a test input vector.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[A]nd wherein feeding the first test input vector: Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[A]nd wherein feeding the first test input vector: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 11
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[S]electing a second test input vector having the expected plurality of input features from the test input dataset: This limitation is seen as a mental process as it deals with selecting an input vector from a dataset.
[D]etermining a second output relevance score based on the second network output: This is a mental process as it deals with determining a relevance score based on an output.
[G]enerating a plurality of second relevance scores at the last layer of the sequence of layers based on the second output relevance score, the neuron weights in the last layer, and the neuron biases in the lower layer preceding the last layer in the sequence of layers: This limitation can be seen as a mental process as it involves generating a relevance score based on the weights and the biases which can be performed in the human mind.
…by reverse propagating the second relevance scores generated at the last layer through the sequence of layers other than the last layer using the neuron weights and the neuron biases: This limitation is a mathematical concept as it is a calculation that involves using functions to calculate the relevance score.
[F]orming a second feature relevance vector based on the second test input vector and the plurality of second relevance scores obtained at the first layer: This limitation is a mental process as it deals with creating a relevance vector based on an input vector and a group of scores, which can be performed mentally.
[A]nd prior to generating the local explanation of the prediction of the neural network model based on the local explainability dataset, adding the second feature relevance vector to the local explainability dataset: This limitation is seen as a mental process as it deals with generating an explanation of a neural network model using a dataset and adding the vector to a dataset, which can be performed mentally.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[F]eeding the second test input vector to the input layer to generate a second network output from the neural network model: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
[O]btaining a plurality of second relevance scores corresponding to the expected plurality of input features at the first layer of the sequence of layers…: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[F]eeding the second test input vector to the input layer to generate a second network output from the neural network model: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
[O]btaining a plurality of second relevance scores corresponding to the expected plurality of input features at the first layer of the sequence of layers…: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 12
Step 1: A process, as above.
Step2A Prong 1: This claim does not recite an additional abstract idea, but the claim depends on
claim 1 which recites an abstract idea.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[F]eeding the first test input vector having the expected plurality of input features to the input layer: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
[G]enerates a plurality of network outputs from the neural network model: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[F]eeding the first test input vector having the expected plurality of input features to the input layer: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
[G]enerates a plurality of network outputs from the neural network model: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 13
Step 1: A process, as above.
Step2A Prong 1: The claim recites, inter alia:
[D]etermining a second output relevance score based on a second network output from the plurality of network outputs: This is a mental process as it deals with determining a relevance score based on outputs.
[G]enerating a plurality of second relevance terms at the last layer of the sequence of layers based on the second output relevance score, the neuron weights in the last layer, and the neuron biases in the lower layer preceding the last layer in the sequence of layers: This limitation can be seen as a mental process as it involves generating a relevance score based on the weights and the biases which can be performed in the human mind.
…by reverse propagating the plurality of second relevance terms through the sequence of layers other than the last layer using the neuron weights and the neuron biases: This limitation is a mathematical concept as it is a calculation that involves using functions to calculate the relevance score based on the weights and biases.
[F]orming a second feature relevance vector based on the first test input vector and the plurality of second relevance scores: This limitation is a mental process as it deals with creating a relevance vector based on an input vector and a group of scores, which can be performed mentally.
[A]nd prior to generating the local explanation of the prediction of the neural network model based on the local explainability dataset, adding the second feature relevance vector to the local explainability dataset: This limitation is seen as a mental process as it deals with generating an explanation of a neural network model using a dataset and adding the vector to a dataset, which can be performed mentally.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[O]btaining a plurality of second relevance scores corresponding to the expected plurality of input features at the first layer of the sequence of layers: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[O]btaining a plurality of second relevance scores corresponding to the expected plurality of input features at the first layer of the sequence of layers: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 14
Step 1: A process, as above.
Step2A Prong 1: This claim does not recite an additional abstract idea, but the claim depends on
claim 1 which recites an abstract idea.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
[T]he neural network model is a trained neural network model: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself (MPEP 2106.05(h)).
[R]etraining the neural network model based at least in part on the local explanation: 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 (MPEP 2106.05(f)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
[T]he neural network model is a trained neural network model: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself which cannot provide inventive concept (MPEP 2106.05(h)).
[R]etraining the neural network model based at least in part on the local explanation: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 15
Step 1: A process, as above.
Step2A Prong 1: This claim recites inter alia:
computing a similarity score based on the data from the user response and data used in training the neural network model: This limitation recites a mathematical concept involving the calculation of a similarity score.
Step 2A Prong 2: This judicial exception is not integrated into a practical application because the additional elements are as follows:
capturing data from the user response: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
wherein updating the neural network model comprises: 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 (MPEP 2106.05(f)).
and triggering retraining of the neural network based on the similarity score: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself (MPEP 2106.05(h)).
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows:
capturing data from the user response: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
wherein updating the neural network model comprises: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
and triggering retraining of the neural network based on the similarity score: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself which cannot provide inventive concept (MPEP 2106.05(h)).
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 16
Step 1: The claim recites an apparatus; therefore, it is directed to the statutory category of apparatus.
Step 2A Prong 1: The claim recites inter alia:
determining an output relevance score based on the network output: This limitation encompasses a mental process of determining a relevance score based on the network output, which can be performed in the human mind.
generating a plurality of relevance scores… based on the output relevance score, the neuron weights in the last layer, and the neuron biases in a lower layer preceding the last layer in the sequence of layers: This limitation can be seen as a mental process as it involves generating a relevance score based on the weights and the biases which can be performed in the human mind.
obtaining a plurality of relevance scores corresponding to the expected plurality of input features at a first layer of the sequence of layers by reverse propagating the relevance scores generated at the last layer through the sequence of layers other than the last layer using the neuron weights and the neuron biases: This limitation is a mathematical concept as it is a calculation that involves linear combinations and activation functions used for calculating relevance scores. See Paragraph 61 of the instant specification, “In one example, the relevance at each hidden layer can be expressed as follows:
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forming a feature relevance vector based on the test input vector and the plurality of relevance scores obtained at the first layer: This limitation is seen as a mental process as it deals with creating a relevance vector based on a group of scores, which can be performed in the human mind.
generating a local explainability dataset comprising the feature relevance vector; and generating a local explanation of a prediction of the neural network model based on the local explainability dataset: This limitation is seen as a mental process as it deals with generating an explanation of a neural network model using a dataset, which can be performed mentally.
Step 2A Prong 2:
One or more non-transitory computer-readable storage media… for causing a computer system to perform operations: 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 (MPEP 2106.05(f)).
[S]toring computer- executable instructions: This limitation is merely a post-solution step of storing the data—a nominal addition to the claim that does not meaningfully limit the claim. The method storing is recited at a high level of generality. Simply implementing the abstract idea in a generic method is not a practical application of the abstract idea. Therefore, storing step is an insignificant extra-solution activity. See MPEP 2106.05(g).
…at a last layer of the sequence of layers…: 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 (MPEP 2106.05(f)).
[R]eceiving a request identifying a neural network model, wherein the neural network model comprises a plurality of neurons arranged in a sequence of layers, a plurality of neuron weights distributed across the sequence of layers, a plurality of neuron biases distributed across the sequence of layers, and an input layer configured to receive an input vector with a plurality of input features; feeding a test input vector having an expected plurality of input features to the input layer to generate a network output from the neural network model: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
…to generate a network output from the neural network model: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
for improving neural networks: 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 (MPEP 2106.05(f)). This limitation is seen as intended use language with no patentable weight.
presenting the local explanation to a user: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
receiving a user response to the local explanation: Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)).
and updating the neural network model based on the user response: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself (MPEP 2106.05(h)).
Step 2B:
One or more non-transitory computer-readable storage media… for causing a computer system to perform operations: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
[S]toring computer- executable instructions: These elements amount to storing… information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; See MPEP 2106.05(d) (II)(iv). The courts have recognized the computer functions of storing as well‐understood, routine, and conventional function when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
…at a last layer of the sequence of layers…: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
[R]eceiving a request identifying a neural network model, wherein the neural network model comprises a plurality of neurons arranged in a sequence of layers, a plurality of neuron weights distributed across the sequence of layers, a plurality of neuron biases distributed across the sequence of layers, and an input layer configured to receive an input vector with a plurality of input features; feeding a test input vector having an expected plurality of input features to the input layer…: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
…to generate a network output from the neural network model: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
for improving neural networks: 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 and cannot provide inventive concept (MPEP 2106.05(f)). This limitation is seen as intended use language with no patentable weight (e.g. for reduced data processing).
presenting the local explanation to a user: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
receiving a user response to the local explanation: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
and updating the neural network model based on the user response: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself which cannot provide inventive concept (MPEP 2106.05(h)).
The elements in combination as an ordered whole still do not amount to significantly more than the judicial exception. The claim merely integrates the abstract idea of explaining a neural network model into a computer-implemented process using data gathering and standard computer equipment and implemented instructions.
Therefore, the claim as a whole remains focused on the abstract idea and fails Step 2B of the
eligibility analysis.
Claim 17
Step 1: An apparatus, as above.
Step 2A Prong 1: The claim recites, inter alia:
[T]he sequence of layers comprises a plurality of hidden layers and the last layer, wherein the first layer of the sequence of layers is one of the hidden layers, and wherein the input layer is a lower layer preceding the first layer: This limitation is seen as a mental process as one can picture the neural network framework in their mind.
…wherein reverse propagating the first relevance scores through the sequence of layers other than the last layer comprises computing for each of the hidden layers a plurality of relevance scores without using neuron activations in the hidden layers: This limitation is seen as a mathematical concept as it involves using mathematical functions during the back propagation process.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 18
Step 1: An apparatus, as above.
Step 2A Prong 1: The claim recites, inter alia:
[R]everse propagating the first relevance scores through the sequence of layers other than the last layer comprises computing for each of the hidden layers a plurality of relevance scores, wherein each relevance score computed at each of the hidden layers is a linear combination of a weighted relevance term and a bias term, wherein the weighted relevance term is based on the neuron weights in the each of the hidden layers and the relevance scores in the higher layer succeeding the each one of the hidden layers, and wherein the bias term is based on the neuron biases in the lower layer preceding the each one of the hidden layers: This limitation is seen as a mathematical concept as it deals with using math functions during the back propagation phase.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 19
Step 1: An apparatus, as above.
Step 2A Prong 1: The claim recites, inter alia:
[E]ach first relevance score determined at the last layer: This is seen as a mental process as it involves determining a score, which can be performed in the human mind.
…is a linear combination of a neuron bias in a lower layer preceding the last layer and a product of a neuron weight in the last layer and the output relevance score: This limitation involves using a math function to get the relevance score, which is a mathematical concept.
Step 2A Prong 2 and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible.
Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible.
Claim 20
Step 1: The claim recites an apparatus; therefore, it is directed to the statutory category of apparatus.
Step 2A Prong 1: The claim recites inter alia:
determining an output relevance score based on the network output: This limitation encompasses a mental process of determining a relevance score based on the network output, which can be performed in the human mind.
generating a plurality of relevance scores… based on the output relevance score, the neuron weights in the last layer, and the neuron biases in a lower layer preceding the last layer in the sequence of layers: This limitation can be seen as a mental process as it involves generating a relevance score based on the weights and the biases which can be performed in the human mind.
obtaining a plurality of relevance scores corresponding to the expected plurality of input features at a first layer of the sequence of layers by reverse propagating the relevance scores generated at the last layer through the sequence of layers other than the last layer without using neuron activations in the sequence of layers: This limitation is a mathematical concept as it is a calculation that involves linear combinations and activation functions used for calculating relevance scores. See Paragraph 61 of the instant specification, “In one example, the relevance at each hidden layer can be expressed as follows:
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forming a feature relevance vector based on the test input vector and the plurality of relevance scores: This limitation is seen as a mental process as it deals with creating a relevance vector based on a group of scores, which can be performed in the human mind.
generating a local explainability dataset comprising the feature relevance vector; and generating a local explanation of a prediction of the neural network model based on the local explainability dataset: This limitation is seen as a mental process as it deals with generating an explanation of a neural network model using a dataset, which can be performed mentally.
Step 2A Prong 2:
A computing system comprising: one or more processing units coupled to memory; and one or more computer readable storage media… that when executed cause the computing system to perform operations: 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 (MPEP 2106.05(f)).
[S]toring instructions: This limitation is merely a post-solution step of storing the data—a nominal addition to the claim that does not meaningfully limit the claim. The method storing is recited at a high level of generality. Simply implementing the abstract idea in a generic method is not a practical application of the abstract idea. Therefore, storing step is an insignificant extra-solution activity. See MPEP 2106.05(g)
…at a last layer of the sequence of layers…: 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 (MPEP 2106.05(f)).
[R]eceiving a request identifying a neural network model, wherein the neural network model comprises a plurality of neurons arranged in a sequence of layers, a plurality of neuron weights distributed across the sequence of layers, a plurality of neuron biases distributed across the sequence of layers, and an input layer configured to receive an input vector with a plurality of input features; feeding a test input vector having an expected plurality of input features to the input layer to generate a network output from the neural network model: Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)).
…to generate a network output from the neural network model: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
for improving neural networks: 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 (MPEP 2106.05(f)). This limitation is seen as intended use language with no patentable weight.
presenting the local explanation to a user: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)).
receiving a user response to the local explanation: Mere data gathering recited at a high level of generality, and thus is an insignificant extra-solution activity (MPEP 2106.05(g)).
and updating the neural network model based on the user response: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself (MPEP 2106.05(h)).
Step 2B:
A computing system comprising: one or more processing units coupled to memory; and one or more computer readable storage media… that when executed cause the computing system to perform operations: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
[S]toring instructions: These elements amount to storing… information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; See MPEP 2106.05(d) (II)(iv). The courts have recognized the computer functions of storing as well‐understood, routine, and conventional function when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
…at a last layer of the sequence of layers…: 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 and cannot provide inventive concept (MPEP 2106.05(f)).
[R]eceiving a request identifying a neural network model, wherein the neural network model comprises a plurality of neurons arranged in a sequence of layers, a plurality of neuron weights distributed across the sequence of layers, a plurality of neuron biases distributed across the sequence of layers, and an input layer configured to receive an input vector with a plurality of input features; feeding a test input vector having an expected plurality of input features to the input layer…: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
…to generate a network output from the neural network model: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
for improving neural networks: 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 and cannot provide inventive concept (MPEP 2106.05(f)). This limitation is seen as intended use language with no patentable weight (e.g. for reduced data processing).
presenting the local explanation to a user: Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). This falls under Well-Understood, Routine, Conventional activity -see MPEP 2106.05(d)(II)(vi).
receiving a user response to the local explanation: The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept.
and updating the neural network model based on the user response: The limitation amounts to merely indicating a field of use or technological environment in which to apply a judicial exception. This does not amount to significantly more than the exception itself which cannot provide inventive concept (MPEP 2106.05(h)).
The elements in combination as an ordered whole still do not amount to significantly more than the
judicial exception. The claim merely integrates the abstract idea of explaining a neural network model into a computer-implemented process using data gathering and standard computer equipment and implemented instructions.
Therefore, the claim as a whole remains focused on the abstract idea and fails Step 2B of the
eligibility analysis.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any 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.
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/M.M.H./Examiner, Art Unit 2125
/KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125
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