DETAILED ACTION
Claims 1-5, 8-17, and 20 have been examined.
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 .
Claim Rejections - 35 U.S.C. § 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.
The invention, as taught in Claims 1-5, 8-17, and 20, is directed to “mental steps” and “mathematical steps” without significantly more.
The claims recite:
• n input variables (n is a natural number greater than or equal to 2) to an input layer of a first neural network
• calculating a predicted value through an output layer
• training the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data
• intermediate value in an lth hidden layer (l is a natural number greater than or equal to 1) of the first neural network from a second neural network
• deep neural network
• calculating an intermediate point value between a point at which the input value is observed and a point at which the target value is observed
• training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data
• calculating the intermediate value in the 1th hidden layer on the basis of an activation function in the 1th hidden layer of the first neural network, the activation function comprising an adjacency matrix containing causality between the n input variables, model parameters, and an intermediate value in an (1-1)th hidden layer
• constructing the adjacency matrix from the n input variables
• wherein the adjacency matrix has a size corresponding to the square of the number (n) of
input variables and contains an element value with causality between 0 and 1, which is relatively
expressed according to a strength of causality relationships between the input variables
Claim 1
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “1. A deep neural network training method for detecting causality between input values, which is performed by a computer including a memory and a processor, the deep neural network training method comprising operations of…” Therefore, it is a “method” (or “process”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES”.
Step 2A (Prong One) inquiry:
Are there limitations in Claim 1 that recite abstract ideas?
YES. The following limitations in Claim 1 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps” and “mathematical steps”:
• n input variables (n is a natural number greater than or equal to 2) to an input layer of a first neural network
• calculating a predicted value through an output layer
• training the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data
• intermediate value in an lth hidden layer (l is a natural number greater than or equal to 1) of the first neural network from a second neural network
• deep neural network
• calculating an intermediate point value between a point at which the input value is observed and a point at which the target value is observed
• training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) An “inputting” of “an input value of training data”
(2) A “receiving” of “an intermediate value in an lth hidden layer”
(3) providing the adjacency matrix of the trained first neural network to a user via a user interface device
A “inputting” of “an input value of training data” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
This “inputting” of “an input value of training data” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “receiving” of “an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
This “receiving” of “an intermediate value in an lth hidden layer” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “providing the adjacency matrix of the trained first neural network to a user via a user interface device” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (h) recites in part:
Examples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include:
***
vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
***
Examiners should be aware that the courts often use the terms “technological environment” and “field of use” interchangeably, and thus for purposes of the eligibility analysis examiners should consider these terms interchangeable. Examiners should also keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05(g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation.
This “providing the adjacency matrix of the trained first neural network to a user via a user interface device” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) An “inputting” of “an input value of training data”
(2) A “receiving” of “an intermediate value in an lth hidden layer”
(3) providing the adjacency matrix of the trained first neural network to a user via a user interface device
A “receiving” of “an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “receiving” of “an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “providing the adjacency matrix of the trained first neural network to a user via a user interface device” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (h) recites in part:
Examples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include:
***
vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
***
Examiners should be aware that the courts often use the terms “technological environment” and “field of use” interchangeably, and thus for purposes of the eligibility analysis examiners should consider these terms interchangeable. Examiners should also keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05(g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 1 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 2
Claim 2 recites:
2. The deep neural network training method of claim 1, wherein the training data comprises an input value observed at time t and a target value observed at time t+1 which is immediately after time t.
Applicant’s Claim 2 merely teaches mathematical training data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 2 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 3
Claim 3 recites:
3. The deep neural network training method of claim 1, wherein the operation of inputting an input value of training data acquired from n input variables to an input layer of a first neural network, which is based on a graph neural network, and calculating a predicted value through an output layer comprises:
inputting n input values obtained from the n input variables to the input layer of the graph neural network; and
calculating n predicted values corresponding to the n input values and outputting the predicted values through the output layer.
Applicant’s Claim 3 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 3 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 4
Claim 4 recites:
4. The deep neural network training method of claim 1, wherein the operation of training the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data, comprises generating the first training information on the basis of an error between the predicted value and the target value.
Applicant’s Claim 4 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 4 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 5
Claim 5 recites:
5. The deep neural network training method of claim 1, wherein the operation of training the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data, comprises setting the first training information as an input of the output layer of the first neural network, delivering the first training information to a hidden layer and the input layer, and training the first neural network.
Applicant’s Claim 5 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 5 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 8
Claim 8 recites:
8. The deep neural network training method of claim 1, wherein the operation of constructing the adjacency matrix from the n input variables comprises:
calculating each element value of an initial adjacency matrix having a same size as the adjacency matrix;
generating a first diagonal matrix obtained by summing element values in each row of the initial adjacency matrix and a second diagonal matrix obtained by summing element values in each column; and
calculating the adjacency matrix on the basis of a multiplication operation between the initial adjacency matrix and an inverse square root matrix corresponding to the generated first and second diagonal matrices.
Applicant’s Claim 8 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 8 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 9
Claim 9 recites:
9. The deep neural network training method of claim 1, wherein the operation of constructing the adjacency matrix from the n input variables further comprises setting, in the adjacency matrix, a regulation term that targets each row and each column of the adjacency matrix to increase deviation between the element values included in the adjacency matrix.
Applicant’s Claim 9 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 9 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 10
Claim 10 recites:
10. The deep neural network training method of claim 1, wherein in the operation of training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data, the second neural network is trained based on the second training information which allows a first identifier to be output when the input value is received and allows a second identifier different from the first identifier to be output when the intermediate point value is received.
Applicant’s Claim 10 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 10 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 11
Claim 11 recites:
11. The deep neural network training method of claim 10, wherein in the operation of receiving an intermediate value in an lth hidden layer of the first neural network from a second neural network, which is based on a deep neural network, and calculating an intermediate point value between a point at which the input value is observed and a point at which the target value is observed, the second neural network calculates the intermediate point value which allows the first identifier to be output when the intermediate point value for training the second neural network is received in the operation of training the first and second neural networks.
Applicant’s Claim 11 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 11 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 12
Claim 12 recites:
12. The deep neural network training method of claim 10, wherein the operation of training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data comprises training the first neural network by inputting the generated second training information to at least one of the hidden layer and the input layer of the first neural network.
Applicant’s Claim 12 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 12 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 13
Claim 13 recites:
13. The deep neural network training method of claim 10, wherein in the operation of training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data, the second training information is calculated based on similarity between the intermediate point value and an input value that is the same as the input value input to the input layer of the first neural network or an input value that satisfies a predetermined situation condition.
Applicant’s Claim 13 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 13 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 14
Claim 14 recites:
14. The deep neural network training method of claim 10, wherein the operation of training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data is repeated a preset maximum number of training times to train the first and second neural networks.
Applicant’s Claim 14 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 14 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 15
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “15. A method of detecting causality between input variables using a deep neural network, which is performed by a computer including a memory and a processor, the method comprising operations of…” Therefore, it is a “method” (or “process”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES”.
Step 2A (Prong One) inquiry:
Are there limitations in Claim 15 that recite abstract ideas?
YES. The following limitations in Claim 15 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps” and “mathematical steps”:
• n input variables (n is a natural number greater than or equal to 2) to an input layer of a first neural network
• graph neural network
• calculating a predicted value through an output layer
• training the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data
• intermediate value in an lth hidden layer (l is a natural number greater than or equal to 1) of the first neural network from a second neural network
• deep neural network
• calculating an intermediate point value between a point at which the input value is observed and a point at which the target value is observed
• training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data
• repeatedly training the first and second neural networks a preset maximum number of training times
• providing an adjacency matrix of the trained first neural network
• adjacency matrix has a size corresponding to the square of the number (n) of input variables and has an element value with causality between 0 and 1, which is expressed relatively according to a strength of causality relationships between the input variables
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) An “inputting” of “an input value of training data”
(2) A “receiving” of “an intermediate value in an lth hidden layer”
(3) providing the adjacency matrix of the trained first neural network to a user via a user interface device
A “inputting” of “an input value of training data” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
This “inputting” of “an input value of training data” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “receiving” of “an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
This “receiving” of “an intermediate value in an lth hidden layer” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “providing the adjacency matrix of the trained first neural network to a user via a user interface device” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (h) recites in part:
Examples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include:
***
vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
***
Examiners should be aware that the courts often use the terms “technological environment” and “field of use” interchangeably, and thus for purposes of the eligibility analysis examiners should consider these terms interchangeable. Examiners should also keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05(g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation.
This “providing the adjacency matrix of the trained first neural network to a user via a user interface device” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) An “inputting” of “an input value of training data”
(2) A “receiving” of “an intermediate value in an lth hidden layer”
(3) providing the adjacency matrix of the trained first neural network to a user via a user interface device
A “receiving” of “an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “receiving” of “an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “providing the adjacency matrix of the trained first neural network to a user via a user interface device” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (h) recites in part:
Examples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include:
***
vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
***
Examiners should be aware that the courts often use the terms “technological environment” and “field of use” interchangeably, and thus for purposes of the eligibility analysis examiners should consider these terms interchangeable. Examiners should also keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05(g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 15 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 16
Step 1 inquiry: Does this claim fall within a statutory category?
The preamble of the claim recites “16. A deep neural network-based system for detecting causality between input values, the deep neural network-based system comprising…” Therefore, it is a “system” (or “apparatus”), which is a statutory category of invention. Therefore, the answer to the inquiry is: “YES”.
Step 2A (Prong One) inquiry:
Are there limitations in Claim 16 that recite abstract ideas?
YES. The following limitations in Claim 16 recite abstract ideas that fall within at least one of the groupings of abstract ideas enumerated in the 2019 PEG. Specifically, they are “mental steps” and “mathematical steps”:
• input layer of a first neural network, which is based on a graph neural network
• calculates a predicted value through an output layer
• trains the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data
• intermediate value in an lth hidden layer (l is a natural number greater than or equal to 1) of the first neural network from a second neural network, which is based on a deep neural network
• calculates an intermediate point value between a point at which the input value is observed and a point at which the target value is observed
• trains the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data
• detecting the causality between the input values on the basis of training data acquired from n input variables
• the processor calculates the intermediate value in the 1th hidden layer on the basis of an activation function in the 1th hidden layer of the first neural network, and
• the activation function comprises an adjacency matrix containing causality between the n input variables, model parameters, and an intermediate value in an (1-1)th hidden layer; and
• wherein the processor calculates each element value of an initial adjacency matrix having a same size as the adjacency matrix, generates a first diagonal matrix obtained by summing element values in each row of the initial adjacency matrix and a second diagonal matrix obtained by summing element values in each column, and calculates the adjacency matrix on the basis of a multiplication operation between the initial adjacency matrix and the generated first and second diagonal matrices.
Step 2A (Prong Two) inquiry:
Are there additional elements or a combination of elements in the claim that apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception?
Applicant’s claims contain the following “additional elements”:
(1) A memory
(2) A processor configured to execute the program stored in the memory, wherein when the program is executed
(3) A processor inputs an input value of training data to an input layer of a first neural network
(4) A processor receives an intermediate value in an lth hidden layer
(5) provides the adjacency matrix of the trained first neural network to a user via a user interface device
A “memory” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iv. Storing and retrieving 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;
This “memory” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “processor configured to execute the program stored in the memory, wherein when the program is executed” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
This “processor configured to execute the program stored in the memory, wherein when the program is executed” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “processor inputs an input value of training data to an input layer of a first neural network” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
This “processor inputs an input value of training data to an input layer of a first neural network” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “processor receives an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
This “processor receives an intermediate value in an lth hidden layer” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
A “provides the adjacency matrix of the trained first neural network to a user via a user interface device” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (h) recites in part:
Examples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include:
***
vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
***
Examiners should be aware that the courts often use the terms “technological environment” and “field of use” interchangeably, and thus for purposes of the eligibility analysis examiners should consider these terms interchangeable. Examiners should also keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05(g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation.
This “provides the adjacency matrix of the trained first neural network to a user via a user interface device” limitation does not integrate the additional element into a practical application and represents “insignificant extra-solution activity”. (See, M.P.E.P. § 2106.05(I)(A)).
The answer to the inquiry is “NO”, no additional elements integrate the claimed abstract idea into a practical application.
Step 2B inquiry:
Does the claim provide an inventive concept, i.e., does the claim recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception in the claim?
Applicant’s claims contain the following “additional elements”:
(1) A memory
(2) A processor configured to execute the program stored in the memory, wherein when the program is executed
(3) A processor inputs an input value of training data to an input layer of a first neural network
(4) A processor receives an intermediate value in an lth hidden layer
(5) provides the adjacency matrix of the trained first neural network to a user via a user interface device
A “memory” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
***
iv. Storing and retrieving 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;
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “processor configured to execute the program stored in the memory, wherein when the program is executed” is a broad term which is described at a high level and includes general purpose computers. M.P.E.P. § 2016.05(f) recites:
2106.05(f) Mere Instructions To Apply An Exception [R-10.2019]
Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words “apply it” (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do “‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’”. Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984 (warning against a § 101 analysis that turns on “the draftsman’s art”).
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “processor inputs an input value of training data to an input layer of a first neural network” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “processor receives an intermediate value in an lth hidden layer” is a broad term which is described at a high level. M.P.E.P. § 2106.05(d)(I)(2) recites in part:
2. A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity. Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination. For example, in many instances, the specification of the application may indicate that additional elements are well-known or conventional. See, e.g., Intellectual Ventures v. Symantec, 838 F.3d at 1317; 120 USPQ2d at 1359 ("The written description is particularly useful in determining what is well-known or conventional"); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1418 (Fed. Cir. 2015) (relying on specification’s description of additional elements as "well-known", "common" and "conventional"); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (Specification described additional elements as "either performing basic computer functions such as sending and receiving data, or performing functions ‘known’ in the art.").
Further, M.P.E.P. § 2106.05(d)(II) recites:
The courts have recognized the following computer functions as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity.
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); …
Merely using the conventional computer to receive data is well known, understood, and conventional. Thus, it adds nothing significantly more to the judicial exception.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
A “provides the adjacency matrix of the trained first neural network to a user via a user interface device” is a broad term which is described at a high level. M.P.E.P. § 2106.05 (h) recites in part:
Examples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include:
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vi. Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid, because limiting application of the abstract idea to power-grid monitoring is simply an attempt to limit the use of the abstract idea to a particular technological environment, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016);
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Examiners should be aware that the courts often use the terms “technological environment” and “field of use” interchangeably, and thus for purposes of the eligibility analysis examiners should consider these terms interchangeable. Examiners should also keep in mind that this consideration overlaps with other considerations, particularly insignificant extra-solution activity (see MPEP § 2106.05(g)). For instance, a data gathering step that is limited to a particular data source (such as the Internet) or a particular type of data (such as power grid data or XML tags) could be considered to be both insignificant extra-solution activity and a field of use limitation.
Therefore, the claim as a whole does not amount to significantly more than the exception itself (i.e., there is no inventive concept in the claim). (See, M.P.E.P. § 2106.05(II)).
Therefore, the answer to the inquiry is “NO”, no additional elements provide an inventive concept that is significantly more than the claimed abstract ideas the claimed abstract idea into a practical application.
Claim 16 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 17
Claim 17 recites:
17. The deep neural network-based system of claim 16, wherein the processor generates the first training information on the basis of an error between the predicted value and the target value, sets the first training information as an input of the output layer of the first neural network, delivers the first training information to a hidden layer and the input layer, and trains the first neural network.
Applicant’s Claim 17 merely teaches mathematical steps. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 17 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Claim 20
Claim 20 recites:
20. The deep neural network-based system of claim 16, wherein the processor trains the second neural network on the basis of the second training information which allows a first identifier to be output when the input value is received and allows a second identifier different from the first identifier to be output when the intermediate point value is received, and calculates the intermediate point value which allows the first identifier to be output when the second neural network receives the intermediate point value.
Applicant’s Claim 20 merely teaches the training of a neural network (mathematical steps), and the input and output of data. It does not integrate the abstract idea to a practical application, nor is it anything significantly more than the abstract idea. (See, 2106.05(a)(II).)
Claim 20 is, therefore, NOT ELIGIBLE subject matter under 35 U.S.C. § 101.
Response to Arguments
Applicant's arguments filed 08 DEC 2025 have been fully considered but they are not persuasive. Specifically, Applicant argues:
Argument 1
Claims 1-5, 8-17 and 20 are rejected under 35 U.S.C. § 101 as being directed to "mental steps" and "mathematical steps" without significantly more. Withdrawal of the rejection is respectfully requested. The claims are not directed to "mental steps" and "mathematical steps" without significantly more for at least the reason that the claims reflect an improvement in a technology or technical field, and thereby integrate the alleged judicial exception into a practical application that imposes a meaningful limit on the alleged judicial exception.
Applicant's argument is conclusory.
The rejections stand.
Argument 2
As discussed in Applicant's response to the first Office Action, the amended claims reflect improvements to the technology of training deep neural networks. The following briefly recaps the improvements.
For example, claim 1's "the activation function comprising an adjacency matrix ... causality relationships between the input variables" introduces specific technical improvements over the conventional art. The specific technical improvements result in better-trained deep neural networks.
The argued deep neural networks are mathematical in nature. Central to the operation of neural networks is the hidden layers. Paragraph [0054] of Applicant’s Specification teaches that the hidden layers of the neural network are, in fact, mathematical equations:
[0054] The hidden layer 122 in the prediction unit 120 is as shown in Equation 3 and FIG 6. FIG 6 is a diagram schematically illustrating a hidden layer 122 of a first neural network. FIGS. 7A and 7B are diagrams illustrating the hidden layer 122 of the first neural network.
Applicant's argument is unpersuasive.
The rejections stand.
Argument 3
Further, the present claims "cover[ ] a particular solution to a problem or a particular way to achieve a desired outcome." Embodiments corresponding to the amended claims achieve improvement to the technology of deep neural network training with the particular solution of using a particular adjacency matrix. The improvement is directly reflected in amended claim l's "the activation function comprising an adjacency matrix ... causality relationships between the input variables."
Abstract (i.e., mathematical) improvement to abstract (i.e., mathematical) claims are not improvements to a technology.
Applicant's argument is unpersuasive.
The rejections stand.
Argument 4
In rejecting the claims, the current Action follows substantially the same procedure for each claim. Independent claim 1 is a representative example. On pages 4 and 5, as "Step 2A (Prong One)" of the subject matter eligibility analysis, the Action broadly characterizes the limitations of claim 1. Then, the Action identifies what the Action calls the "additional elements" of the "Step 2A (Prong Two)" part of the analysis. The Action remarks, on pages 5 and 6:
Applicant's claims contain the following "additional elements":
(1) An "inputting" of "an input value of training data"
(2) A "receiving" of "an intermediate value in an Ith hidden layer"
In the foregoing, the Action oversimplifies the claims, contrary to the guidance of the Enfish case (Enfish v. Microsoft Corp., 822 F.3d 1327 (2016)).
***
The present rejection, like the district court reversed by the Enfish opinion, improperly characterizes claim 1 at a high level of abstraction, reducing the details to, essentially, "inputting" and "receiving" of nonspecific "values," and disregards the detailed solution and improvements reflected by claim 1.
Applicant's argument does not specify the “detailed solution and improvements” that are “reflected by claim 1.”
Only thing that has been mentioned as an improvement is the use of the “adjacency matrix” to improve a mathematical deep neural network. Abstract (i.e., mathematical) improvement to abstract (i.e., mathematical) claims
Applicant's argument is unpersuasive.
The rejections stand.
Argument 5
The present rejection is also at odds with other recent guidance from the USPTO. The USPTO's August 4, 2025 memorandum titled "Reminders on evaluating subject matter eligibility of claims under 35 U.S.C. 101" (hereafter, "USPTO August memorandum") states as follows: "The mental process grouping is not without limits. Examiners are reminded not to expand this grouping in a manner that encompasses claim limitations that cannot practically be performed in the human mind. The MPEP and the AI-SME Update provide examples of claim limitations that cannot be practically performed in the human mind. Claim limitations that encompass Al in a way that cannot be practically performed in the human mind do not fall within this grouping."
Present amended claim 1 includes "training the first neural network on the basis of first training information, which is a result of comparing the predicted value to a target value of the training data ... [and] training the first and second neural networks on the basis of second training information based on similarity between the intermediate point value and the input value of the training data." Moreover, the USPTO August memorandum includes a specific example on page 3 as follows: "The claim limitation 'training the neural network in a first stage using the first training set' of example 39 does not recite a judicial exception."
Accordingly, claim 1 does not belong to the mental processes group for at least the reason that claim 1 directly corresponds to the example given in the USPTO August memorandum and "encompass[es] Al in a way that cannot be practically performed in the human mind."
The argued deep neural networks are mathematical in nature. Central to the operation of neural networks is the hidden layers. Paragraph [0054] of Applicant’s Specification teaches that the hidden layers of the neural network are, in fact, mathematical equations:
[0054] The hidden layer 122 in the prediction unit 120 is as shown in Equation 3 and FIG 6. FIG 6 is a diagram schematically illustrating a hidden layer 122 of a first neural network. FIGS. 7A and 7B are diagrams illustrating the hidden layer 122 of the first neural network.
Only thing that has been mentioned as an improvement is the use of the “adjacency matrix” to improve a mathematical deep neural network. Abstract (i.e., mathematical) improvement to abstract (i.e., mathematical) claims
Applicant's argument is unpersuasive.
The rejections stand.
Argument 6
The USPTO August memorandum also counsels against oversimplification of the claims, consistently with the Enfish case discussed previously. See the below, from page 4 of the USPTO August memorandum:
Examiners are cautioned not to oversimplify claim limitations and expand
the application of the "apply it" consideration. Moreover, examiners are
reminded that the "apply it" consideration often overlaps with the improvements consideration. When evaluating these two considerations, examiners may consider the following:
1. Whether the claim recites only the idea of a solution or outcome, i.e., the claim fails to recite details of how a solution to a problem is accomplished, or the claim covers a particular solution to a problem or a particular way to achieve a desired outcome.
2. Whether the claim invokes computers or other machinery merely as a tool to perform an existing process, or whether the claim purports to improve computer capabilities or to improve an existing technology.
The present claims are highly detailed and recite specific solutions that improve a technology, and clearly meet the above criteria.
Applicant does not specify an actual technology that is being improved.
Only thing that has been mentioned by Applicant in these arguments is the assertion of an improvement is the use of the “adjacency matrix” to improve a mathematical deep neural network. Abstract (i.e., mathematical) improvement to abstract (i.e., mathematical) claims
Applicant's argument is unpersuasive.
The rejections stand.
Argument 7
Also: "[I]f the additional limitations reflect ... an improvement to [a] technology or technical field, the claim integrates the judicial exception into a practical application and thus imposes a meaningful limit on the judicial exception. No further analysis is required." (The USPTO's memorandum titled "October 2019 Update: Subject Matter Eligibility," page 11.) As discussed above, the claims clearly represent an improvement and are therefore integrated into a practical application. To further emphasize a practical application, claim 1 is amended to add "providing the adjacency matrix of the trained first neural network to a user via a user interface device, to facilitate the user's understanding the causality relationship between input variables which is represented in the adjacency matrix," based on, for example, paragraphs [0037], [00116], [00117] and [00120].
Applicant does not specify an actual technology that is being improved.
Only thing that has been mentioned by Applicant in these arguments is the assertion of an improvement is the use of the “adjacency matrix” to improve a mathematical deep neural network. Abstract (i.e., mathematical) improvement to abstract (i.e., mathematical) claims
Applicant's argument is unpersuasive.
The rejections stand.
Argument 8
Independent claims 15 and 16 as amended correspond substantially to amended claim 1. Accordingly, the claims integrate the alleged judicial exception into a practical application and thus impose a meaningful limit on the judicial exception. The claims are therefore patent-eligible, and withdrawal of the rejection is appropriate.
Similar arguments for similar claims are similarly unpersuasive.
The rejections stand.
Conclusion
Any inquiries concerning this communication or earlier communications from the examiner should be directed to Wilbert L. Starks, Jr., who may be reached Monday through Friday, between 8:00 a.m. and 5:00 p.m. EST. or via telephone at (571) 272-3691 or email: Wilbert.Starks@uspto.gov.
If you need to send an Official facsimile transmission, please send it to (571) 273-8300.
If attempts to reach the examiner are unsuccessful the Examiner’s Supervisor (SPE), Kakali Chaki, may be reached at (571) 272-3719.
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/WILBERT L STARKS/
Primary Examiner, Art Unit 2122
WLS
10 JAN 2026