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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. JP2021-110283, filed on 07/01/2021.
Response to Arguments
Applicant’s argument filed 07/20/2026 have been fully considered but the arguments for the 101 rejections are not persuasive.
Applicant’s Argument: On pages 9-10 of Applicant’s response to rejections under 35 U.S.C. 101, applicant states that the amended claim 1 is recited with sufficient specificity that the claim integrates the alleged abstract idea into a practical application and the claim as a whole is directed to specific improvements to the functioning of the trained model. Applicant argues that the technical improvement is stabilization of anomaly degrees output across updates of a trained model. Claim 1 recites specific mathematical calculations used as a tool to achieve the actual disclosed and claimed improvement of output stability and anomaly detection accuracy of the trained model. Claim 1 also recites additional feature of controlling display of information on the anomaly degree, the loss function, and the first loss value to integrate the abstract idea into a practical application.
Examiner’s Response: Applicant’s argument is not persuasive. During examination, the examiner should analyze the "improvements" consideration by evaluating the specification and the claims to ensure that a technical explanation of the asserted improvement is present in the specification, and that the claim reflects the asserted improvement (see MPEP §2106.05(a)). The MPEP (§2106.05(a)(II)) also warns, “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology.” The specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement in the functioning of a computer, or an improvement to other technology or a technical field. Applicant argues that claim 1 is not an improvement to an abstract idea itself, but rather it is an improvement to the operation of the trained model. The claim as a whole does not disclose any details on how the operation of the trained model is improved. Claim 1 recites a series of mathematical calculations that are steps to adjust the model’s output. Here, the alleged improvement in the form of “defines the model’s output behavior after update” is an improvement to the abstract idea of a mathematical calculation. The updating of the model parameter is based on minimizing the first loss value, which is a mathematical calculation. Thus, the claimed improvement is directed to an abstract idea and the improvement is not related to any improvement to the functioning of the machine learning model. Claim 1 does not recite any specific improvement to the functioning of a computer, or an improvement to other technology or a technical field.
In the previous Office Action (04/20/2026; pg. 3), “fundamental economic concepts was provided as an example of an improvement in the abstract idea itself and it is not directed to the claimed improvement of the instant application.
Applicant argues with reference to Desjardins that the claimed invention is an improvement to the machine learning model. Applicant does not provide any explanation on how the claims of the instant application is similar to the claims in Desjardins. In Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision), the claimed invention was a method of training a machine learning model on a series of tasks. The Appeals Review Panel (ARP) overall credited benefits including reduced storage, reduced system complexity and streamlining, and preservation of performance attributes associated with earlier tasks during subsequent computational tasks as technological improvements that were disclosed in the patent application specification. Specifically, the ARP upheld the Step 2A Prong One finding that the claims recited an abstract idea (i.e., mathematical concept). In Step 2A Prong Two, the ARP then determined that the specification identified improvements as to how the machine learning model itself operates, including training a machine learning model to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting” encountered in continual learning systems.
An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome (see MPEP 2106.05(a)). The amended claims do not provide sufficient details to describe any technological improvement. If the specifications explicitly set forth an improvement but in a conclusory manner (see MPEP 2106.04(d)(1): a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. The additional feature of controlling display of information is mere instructions to apply the exception using a generic computer component (see MPEP 2106.05(f)) and does not integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
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 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
Subject Matter Eligibility Analysis Step 1:
Claim 1 recites “A learning apparatus comprising a processor configured to” and is thus a machine, one of the four statutory categories of patentable subject matter.
Subject Matter Eligibility Analysis Step 2A Prong 1:
“calculate an anomaly degree indicating a degree to which the data is the anomalous data using an output of a model for the data” (a mathematical calculation; See pg. 6-7 and Equation 1 in Spec.)
“calculate a first loss value related to the anomaly degree using a loss function based on (a) an adjustment parameter which is calculated based on a second loss value derived from one or more previously calculated loss values and (b) the label” (a mathematical calculation; See pg. 7 and Equation 2 in Spec.)
“update a model parameter of the model so as to minimize the first loss value” (a mathematical calculation; See pg. 10 in Spec., model parameter is updated using gradient descent calculation)
“wherein the loss function includes a first term relating to a loss of a normal label indicating the normal data and a second term relating to a loss of an anomaly label indicating the anomalous data” (a mathematical calculation; See pg. 7 and Equation 2 in Spec.)
“the adjustment parameter is calculated to be more influential on the loss function when the acquired data has the anomaly label than when the acquired data has the normal label” (a mathematical calculation; See pg. 8 and Equation 3 in Spec.)
“the adjustment parameter modulates a relative contribution of the first term and the second term of the loss function to balance the first and second terms and stabilize anomaly degrees output by the model across model updates” (a mathematical calculation; See pg. 7-8 and Equation 2 & 3 in Spec.)
Claim 1 therefore recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
"acquire data with a label indicating whether the data is normal data or anomalous data” (This step is directed to data gathering, which is understood to be insignificant extra solution activity - see MPEP 2106.05(g))
"control display of information on the anomaly degree, the loss function during training of the model, and the first loss value” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above. Therefore, Claim 1 is directed to the abstract idea.
Subject Matter Eligibility Analysis Step 2B:
"acquire data with a label indicating whether the data is normal data or anomalous data” (This step is directed to transmitting or receiving information, which is understood to be insignificant extra solution activity and well understood, routine and conventional activity of transmitting and receiving data as identified by the court - see MPEP 2106.05(d))
"control display of information on the anomaly degree, the loss function during training of the model, and the first loss value” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
The additional elements as disclosed above alone or in combination do not recite significantly more than the abstract idea itself as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above. Therefore, Claim 1 is subject-matter ineligible.
Regarding Claim 2:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation; See pg. 7 and Equation 1 in Spec.)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein a probability of appearance of the normal data is higher than a probability of appearance of the anomalous data” (merely specifies a particular technological environment in which the abstract idea is to take place, ie. a field of use, and thus does not integrate the abstract idea into a practical application nor cannot provide significantly more than the abstract idea itself - see MPEP 2106.05(h))
“the processor calculates ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 3:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation; See pg. 7 and Equation 1 in Spec.)
“a negative log-likelihood of probability distribution when the model is a variational autoencoder” (a mathematical calculation; See pg. 7 and Equation 2 in Spec.)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor calculates, ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 4:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“wherein the loss function increases according to the anomaly degree with respect to the normal data and decreases according to the anomaly degree with respect to the anomalous data” (a mathematical relationship; See pg. 7 and Equation 2 in Spec.)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B: None
Regarding Claim 5:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation and relationship; See pg. 7 and Equation 2 in Spec.)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor updates ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 6:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation; See pg. 7 and Equation 2 in Spec.)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor calculates ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 7:
Subject Matter Eligibility Analysis Step 2A Prong 1: None
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the second loss value is a loss value one epoch previous or a loss value one iteration previous in training of the model” (merely specifies a particular technological environment in which the abstract idea is to take place, ie. a field of use, and thus does not integrate the abstract idea into a practical application nor cannot provide significantly more than the abstract idea itself - see MPEP 2106.05(h))
Regarding Claim 8:
The claim recites a process (“A learning method executed by a processor, the learning method comprising”) that performs the method as described in claim 1. Therefore, claim 8 is rejected for the same reasons as disclosed for claim 1.
Regarding Claim 9:
The claim recites a system (“A non-transitory computer readable medium”; a machine, one of the four statutory categories of patentable subject matter) that performs the method as described in claim 1. Therefore, claim 9 is rejected for the same reasons as disclosed for claim 1. The limitations for additional elements of claim 9 are analyzed below.
Subject Matter Eligibility Analysis Step 2A Prong 1:
Please see Step 2A Prong 1 analysis of claim 1
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“A non-transitory computer readable medium including computer executable instructions, wherein the instructions, when executed by a processor, cause the processor to perform a method comprising” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 10:
Subject Matter Eligibility Analysis Step 1:
Claim 10 recites “An inference apparatus comprising a processor configured to” and is thus a machine, one of the four statutory categories of patentable subject matter.
Subject Matter Eligibility Analysis Step 2A Prong 1:
“calculate an anomaly degree of the target data using a trained model generated by the learning apparatus according to claim 1” (a mathematical calculation; See pg. 6-7 and Equation 1 in Spec.)
Claim 10 therefore recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
"acquire target data to be processed” (This step is directed to data gathering, which is understood to be insignificant extra solution activity - see MPEP 2106.05(g))
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above. Therefore, Claim 10 is directed to the abstract idea.
Subject Matter Eligibility Analysis Step 2B:
"acquire data with a label indicating whether the data is normal data or anomalous data” (This step is directed to transmitting or receiving information, which is understood to be insignificant extra solution activity and well understood, routine and conventional activity of transmitting and receiving data as identified by the court - see MPEP 2106.05(d))
The additional elements as disclosed above alone or in combination do not integrate the judicial exception into practical application as they are mere insignificant extra solution activity in combination of generic computer functions being implemented with generic computer elements in a high level of generality to perform the disclosed abstract idea above. Therefore, Claim 10 is subject-matter ineligible.
Regarding Claim 11:
Subject Matter Eligibility Analysis Step 2A Prong 1: None
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor is further configured to control display of the anomaly degree” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 12:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation/relationship; See pg. 7 and Equation 2 in Spec., calculating a value for a parameter based on satisfying a relationship between 2 variables)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor updates ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 13:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation; See pg. 7 and Equation 2 in Spec., calculating a value for a parameter based on satisfying a relationship between 2 variables)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor updates ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 14:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“determine whether or not the first loss value is equal to or less than a threshold value, or whether or not a decrease in the first loss value has converged” (a mental process that can be performed in the human mind, i.e. judgement)
“update the model parameter when a result of the determination is negative” (a mathematical calculation; See pg. 10 in Spec., model parameter is updated using gradient descent calculation)
“calculate the anomaly degree for the another data and calculate the first loss value for the another data” (a mathematical calculation; See pg. 7 Equation 1 and Equation 2 in Spec.)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“acquire another data with a label indicating whether the another data is the normal data or the anomalous data” (This step is directed to data gathering, which is understood to be insignificant extra solution activity (2106.05(g) in step 2A prong 2) and well understood, routine and conventional activity of transmitting and receiving data as identified by the court (2106.05(d) in step 2B))
Regarding Claim 15:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“determine, based on the anomaly degree, whether the target data is anomalous data, the target data being determined to be the anomalous data when the anomaly degree is equal to or greater than a threshold value and to be normal data when the anomaly degree is less than the threshold value” (a mental process that can be performed in the human mind, i.e. judgement)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“output a result of the determination” (This step is directed to data gathering, which is understood to be insignificant extra solution activity (2106.05(g) in step 2A prong 2) and well understood, routine and conventional activity of gathering and analyzing information using conventional techniques and displaying the result as identified by the court (2106.05(d) in step 2B))
Regarding Claim 16:
Subject Matter Eligibility Analysis Step 2A Prong 1:
“” (a mathematical calculation; See pg. 10 in Spec., model parameter is updated using gradient descent calculation)
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the processor is configured to ” (mere instructions to apply the exception using a generic computer component - see MPEP 2106.05(f))
Regarding Claim 17:
Subject Matter Eligibility Analysis Step 2A Prong 1: None
Subject Matter Eligibility Analysis Step 2A Prong 2 & 2B:
“wherein the predetermined condition is a condition that a predetermined number of epochs have been completed, that the first loss value is equal to or less than a threshold value, or that a decrease in the first loss value converges” (merely specifies a particular technological environment in which the abstract idea is to take place, ie. a field of use, and thus does not integrate the abstract idea into a practical application nor cannot provide significantly more than the abstract idea itself - see MPEP 2106.05(h))
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GARY MAC whose telephone number is (703)756-1517. The examiner can normally be reached
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abdullah Kawsar can be reached on (571) 270-3169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GARY MAC/Examiner, Art Unit 2127
/ABDULLAH AL KAWSAR/Supervisory Patent Examiner, Art Unit 2127
