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 .
Status of Claims
Claims 1, 2, 9, 10, 17, 18 are amended. Claims 3, 11, 19 are canceled. Claims 1-2, 4-10, 12-18 and 20 are pending and examined herein.
Claims 1-2, 4-10, 12-18 and 20 are rejected under 35 U.S.C. 112(b).
Claims 1-2, 4-10, 12-18 and 20 are rejected under 35 U.S.C. 101.
Response to Amendment
The amendment filed January 22th, 2026 has been entered. Claims 1, 2, 9, 10, 17, 18 are amended. Claims 3, 11, 19 are canceled. Claims 1-2, 4-10, 12-18 and 20 are pending and examined herein. Applicant’s amendments to the specification have overcome specification objection previously set forth in the Non-Final Rejection Office Action mailed October 28th, 2025. Applicant’s amendments to the claims have been considered but are not persuasive. Although the amendment clarifies the antecedent basis for “the logic of the first model” in claims 1, 9, and 17, the claims remain indefinite with the amended limitation. Further explanation is provided in the 112(b) section of the current office action.
Response to Arguments
Applicant's arguments filed January 22th, 2026 regarding the 35 U.S.C. 101 rejection of claims 1-2, 4-10, 12-18 and 20 have been fully considered but they are not persuasive. Under Step 2A, Prong One, claim 1 as amended continues to recite abstract ideas. The amended limitations recite selecting background data randomly, determining an inference from model output, generating explanation information, ranking features, determining features that impact model logic and the explanation, computing a distance metric indicating similarity between model logic and the explanation, filtering background data based on contrastive feature relationships, and generating a second explanation with ranking or accuracy. These limitations fall within the mathematical concept and/or mental process grouping of abstract idea as further explained in the below 101 rejection section. Under Step 2A, Prong two, claim 1 as amended includes the additional elements that do not integrate the abstract idea into a practical application. The processor, memory, communication interface, computer readable storage medium, data gathering and outputting, and training the model at a high level merely provide the generic computer environment and model architecture for performing the abstract analysis. The claim does not recite a technical action taken based on the distance metric or second explanation, such as modifying model parameters, changing model architecture, reducing training iterations, allocation computing resources, or controlling a technical system.
Applicant further argues, on pages 19 – 20, that the claimed invention improves AI technology by reducing unnecessary retraining and conserving computing resources. Examiner respectively disagrees. The aligned improvement is not recited in the claims. Claim 1 does not recite reducing training iterations, curtailing retraining, reducing CPU/GPU/memory usage, allocating computing resources, modifying model architecture, or modifying model parameters. The claim also does not recite controlling any technical system based on the distance metric or the second explanation. The claim computes information about a model explanation, including various differentiators, a distance metric, and explanations. Any reduction in retraining or computing resource usage would result from an unclaimed decision made after the claimed computations. A benefit outside the scope of the claim does not integrate the judicial exception into a practical application.
Applicant further argues, on pages 17 – 18, that the claims are analogous to Enfish and consistent with Ex parte Desjardins. In Enfish, the claims recited a specific self-referential table structure that improved computer database operation. Here, claim 1 does not recite a new data structure or an improvement to the operation of the processor, memory, communication interface, or storage medium. These components perform their ordinary generic functions. Desjardins case noted claims directed to a specific machine learning training improvement, where model parameters were adjusted during training while preserving performance on prior tasks, reducing storage, and reducing system complexity. The present claim 1 does not recite these types of improvements. The amended claim 1 states that training occurs separately, but does not recite how the training is technically improved. The remaining amended limitations compute explanation, ranking, differentiator, distance metric, contrastive relationship, and accuracy information about the trained model’s outputs. They do not improve how the model itself trains or operates.
Applicant further argues, on pages 16 – 17, that the 101 Reminders require the claims must be viewed as a whole and more than 50% of the claim must be ineligible to be rejected under 101. The claims have been considered as a whole, including the amended limitations and the alleged improvement identified by applicant. The rejection is not based on viewing the amended limitations in isolation. Rather, even when the limitations are considered together, claim 1 recites mathematical and evaluative analysis of machine learning model explanation information. The amended limitations add random data selection, feature impact comparisons, similarity or distance analysis, contrastive relationship data filtering, and determining accuracy of information. These limitations remain part of the abstract mathematical or evaluative analysis on top of previous rejection. Accordingly, it remains more than 50% likely that the claims are directed to patent ineligible subject matter. The claims do not recite a limitation that improves computer functionality, improves machine learning training, improves model architecture, modifies model parameters, reduces computing resources usage, or controls a technical system.
Thus, the remarks in response to the 35 U.S.C. 101 rejection are not persuasive.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 4-10, 12-18 and 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 as amended recites determining a second set of background data that is “contrastive with respect to the first feature while not being contrastive with respect to the second feature.” in lines 31-37 of claim 1. Same section of the claim 1 further recites that the data points forming that second set are selected randomly from the first set of raw data “while being filtered to remove data that is contrastive with respect to the first feature while not being contrastive with respect to the second feature.” It appears to require the second set of background data to include data having the recited contrastive and non-contrastive property, while also requiring that data having that same property to be removed. It is not reasonably certain whether the second set of background data is intended to include or exclude data points having the recited contrastive of first feature and non-contrastive to the second feature. Accordingly, the scope of claim 1 is unclear and need to be clarified.
Claims 2 , 4 – 8 are dependent on claim 1 and claims 9, 10, 12 – 18, 20 recite same limitations corresponding to claim 1 in different statutory forms. They do not resolve the issue of indefiniteness and are rejected with the same rationale.
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 - 2, 4 - 10, 12 - 18, 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
MPEP § 2109(III) sets out steps for evaluating whether a claim is drawn to patent-eligible subject matter. The analysis of claims 1 – 20, in accordance with these steps, follows.
Step 1 Analysis:
Step 1 is to determine whether the claim is directed to a statutory category (process, machine, manufacture, or composition of matter.
Claims 1 – 2, 4 – 8 are directed to a method, meaning that it is directed to the statutory category of process. Claims 9 – 10, 12 – 16 are directed to a computing apparatus, which is the statutory category of machine. Claims 17 – 18, 20 are directed to a non-transitory computer-readable storage medium storing instruction, which can be an article of manufacture.
Step 2A Prong One, Step 2A Prong Two, and Step 2B Analysis:
Step 2A Prong One asks if the claim recites a judicial exception (abstract idea, law of nature, or natural phenomenon). If the claim recites a judicial exception, analysis proceeds to Step 2A Prong Two, which asks if the claim recites additional elements that integrate the abstract idea into a practical application. If the claim does not integrate the judicial exception, analysis proceeds to Step 2B, which asks if the claim amounts to significantly more than the judicial exception. If the claim does not amount to significantly more than the judicial exception, the claim is not eligible subject matter under 35 U.S.C. 101.
Regarding claim 1, the following claim elements are abstract ideas:
selecting … a first set of background data based on the at least the first set of raw data; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper.)
wherein the first set of background data is selected randomly (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Also, random selection process could recite mathematical relationship, which is mathematical concept. )
determining … a first inference that indicates a logic of the first model; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper.)
drawing an inference based on an output of the first model (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper.)
computing … a first explanation based on an output of the first model and the first set of background data, (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Computing explanation could also be done with mathematical calculations, which is mathematical concept.)
ranking, …, each of the plurality of features that affects the first inference for generating a plurality of ranking values. (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper. Ranking features and generating ranking values could recite mathematical calculations, which is mathematical concept.)
computing … a model differentiator that indicates a first feature, among the plurality of features, that impacts the logic of the first model while not impacting the first explanation; (Comparing or evaluating impact or relationship among features, logic and explanation is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Computing a model differentiator and the impact of features on models with explanations could recite mathematical calculations, which is mathematical concept.)
computing … an explanation differentiator that indicates a second features, among the plurality of features, that impacts the first explanation while not impacting the logic of the first model; (Comparing or evaluating impact or relationship among features, logic and explanation is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Computing a explanation differentiator and the impact of features on models with logics could recite mathematical calculations, which is mathematical concept.)
computing … a distance metric that indicates a degree of similarity between the logic of the first model and the first explanation for determining accuracy of the first model; (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Computing a distance metric could also be done with mathematical calculations, which is mathematical concept.)
determining … the explanation differentiator, and the distance metric, a second set of background data that is contrastive with respect to the first feature while not being contrastive with respect to the second feature (Comparing data relationships to features and determining contrastive relationship is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper. Defining or selecting data based on feature relationships could recite mathematical relationship, which is mathematical concept.)
wherein data points forming the second set of background data is selected randomly from the first set of raw data (Selecting data points randomly is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Random selection process/algorithm also recites mathematical relationship, which is mathematical concept.)
while being filtered to remove data that is contrastive with respect to the first feature while not being contrastive with respect to the second feature; (Comparing data relationships to features and determining contrastive relationship is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper. Removing data based on feature relationships could recite mathematical relationship, which is mathematical concept.)
computing … a second explanation that includes at least one feature that affects the first inference and a respective ranking score that relates to each of the at least one feature, (This is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components. Computing a second explanation and ranking score could also be done with mathematical calculations, which is mathematical concept.)
wherein the second explanation includes information provides an indication of accuracy of the first model based on alignment of the logic of the first model with the explanation provided by the first model. (Evaluating alignment between model logic and explanation to provide indication of accuracy is practical to perform in the human mind under its broadest reasonable interpretation aside from the recitation of generic computer components or by a human using a pen and paper. Generating indication of accuracy based on these alignments could recite mathematical calculation, which is mathematical concept.)
The following claim elements are additional elements which, taken alone or in combination with the other additional elements, do not integrate the judicial exception into a practical application nor amount to significantly more than the judicial exception:
the method being implemented by at least one processor (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
,by the at least one processor, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
receiving … at least a first set of raw data that is usable for training a first model; (This is mere data gathering, an insignificant extra solution activity, which is a well-understood, routine conventional activity. It does not integrate the judicial exception into a practical application. See MPEP § 2106.05(d). Therefore, this does not amount to significantly more than the judicial exception.)
training … the first model by using the at least the first set of raw data, wherein the first model is trained separately for each set of raw data (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
wherein the first inference is determined by inputting a data point not included in the first set of raw data (This is mere data gathering and outputting, an insignificant extra solution activity, which does not integrate the judicial exception into a practical application. The broadest reasonable interpretation of this claim is storing information in memory, which is a well-understood, routine conventional activity. See MPEP § 2106.05(d)(II)(iv). Therefore, this does not amount to significantly more than the judicial exception.)
, the first explanation including first information that relates to a plurality of features that affects the first inference; (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
, by the at least one processor based on the first inference and the first explanation including the first information that relates to the plurality of features, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
, by the at least one processor based on the model differentiator and the explanation differentiator, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
, by the at least one processor based on the model differentiator, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
, by the at least one processor based on the second set of background data, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
Regarding claim 2, the rejection of claim 1 is incorporated herein. Further, claim 2 recites the following abstract ideas:
initializing the distance metric with a value of zero (0); (Initializing the distance metric with zero is merely mathematical relationship, which is mathematical concept.)
incrementing the distance metric by one (+1); (Incrementing the distance metric by one is merely mathematical calculation, which is mathematical concept.)
calculating a difference between a value of the feature as expressed in the first explanation and a value of the feature as expressed in the logic of the first model, and increasing the distance metric by an amount that is equal to the calculated difference. (Calculating a difference between values and incrementing the distance metric by the difference is merely mathematical calculation, which is mathematical concept.)
Claim 2 further recites following additional elements:
for each feature included in the logic of the first model and not included in the first explanation, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
for each feature included in the first explanation and not included in the logic of the first model, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
and for each feature included in both of the first explanation and the logic of the first model, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
Regarding claim 4, the rejection of claim 1 is incorporated herein. Further, claim 4 recites the following additional element:
the first explanation comprises a first plurality of features that relate to the first model and, for each respective feature from among the first plurality of features, a corresponding ranking value. (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
Regarding claim 5, the rejection of claim 4 is incorporated herein. Further, claim 5 recites the following abstract idea:
the computing of the first explanation comprises applying a Shapley Additive exPlanations (SHAP) technique to each feature from among the first plurality of features. (Applying Shapley Additive exPlanations to features is merely mathematical calculation, which is mathematical concept.)
Claim 5 does not recite additional elements.
Regarding claim 6, the rejection of claim 1 is incorporated herein. Further, claim 6 recites the following additional element:
the second explanation comprises a second plurality of features that relate to the first model and, for each respective feature from among the second plurality of features, a corresponding second ranking value. (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
Regarding claim 7, the rejection of claim 6 is incorporated herein. Further, claim 6 recites the following abstract idea:
the computing of the second explanation comprises applying a Shapley Additive exPlanations (SHAP) technique to each feature from among the second plurality of features. (Applying Shapley Additive exPlanations to features is merely mathematical calculation, which is mathematical concept.)
Claim 7 does not recite additional elements.
Regarding claim 8, the rejection of claim 1 is incorporated herein. Further, claim 8 recites the following abstract idea:
wherein the first model is configured to generate a projected price of the first bond at a particular time. (This recites mathematical relationship as specific value is generated when specific input is given, which is merely mathematical concept.)
Claim 8 further recites following additional element:
the first set of raw data comprises bond pricing data that relates to a first bond, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
Regarding claim 9, the following is an additional element:
A processor; a memory; and a communication interface coupled to each of the processor and the memory, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
The rest of claims 9 -10, 12 – 16 recite substantially similar subject matter to claims 1 – 2, 4 – 8 respectively and are rejected with the same rationale, mutatis mutandis.
Regarding claim 17, the following is an additional element:
A processor; a memory; and a communication interface coupled to each of the processor and the memory, (This falls under mere instructions to apply abstract idea on a generic computer. See MPEP § 2106.05(f). Therefore, this does not amount to significantly more than the judicial exception.)
The rest of claims 17 – 18 , 20 recite substantially similar subject matter to claims 1 – 2, 4 respectively and are rejected with the same rationale, mutatis mutandis.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BYUNGKWON HAN whose telephone number is (571)272-5294. The examiner can normally be reached M-F: 9:00AM-6PM PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Li B Zhen can be reached at (571)272-3768. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BYUNGKWON HAN/ Examiner, Art Unit 2121
/Li B. Zhen/ Supervisory Patent Examiner, Art Unit 2121
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