DETAILED ACTION
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 .
This action is in response to amendments filed March 2nd, 2026. The status of the claims is as follows. Claims 1, 7 and 13 are amended. Claims 1-18 are currently pending.
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 1-18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1,
(Step 1): Claim 1 recites a process for detecting errors in a base neural network classifier to improve trustworthiness of the base neural network classifier, thus a process, one of the four statutory categories of patentable subject matter.
(Step 2A Prong 1): However, Claim 1 further recites predicting … a classification for each of multiple input data points x, which constitutes the evaluation of multiple input data points to determine a predicted classification associated with the evaluated input data points, thus corresponding to a mental process which can be done mentally or by pen and paper;
assigning a target detection score c to each training sample (X, y) based on correctness of a classification prediction
y
^
for the training sample by the base neural network classifier, which falls in the mathematical concept and mental process (evaluation) groupings of abstract ideas;
predicting …, a residual r between the target detection score c and an original maximum class probability
c
^
, which falls in the mathematical concept and mental process (evaluation) groupings of abstract ideas;
for a given data point
x
*
, providing a Gaussian distribution of estimated residual
r
^
*
, wherein
r
^
*
is defined by a residual mean
r
¯
^
*
and a variance var(
r
^
*
) which falls in the mathematical concept grouping of abstract ideas;
adding
r
¯
^
*
and
c
^
*
,
wherein
c
^
*
is a class probability for a given data point
x
*
, to calculate an error detection score
c
^
*
'
, wherein var(
r
^
*
)
indicates a corresponding uncertainty of the error detection score, which falls in the mathematical concept grouping of abstract ideas;
and determining, using the calculated error detection score, if the base neural network classifier classification for the given data points x is erroneous which constitutes the evaluation of calculated error detection scores to determine if a classification is erroneous, thus corresponding to a mental process which can be done mentally or by pen and paper. Thus, Claim 1 recites an abstract idea.
(Step 2A Prong 2): The claim does not recite any additional elements which integrate the abstract idea into a practical application because the additional elements consist of:
by the base neural network classifier, which is merely implementing an abstract idea on generic computer components (MPEP 2106.05(f))
by a trained model with input-output (I/O) kernel, which is merely implementing an abstract idea on generic computer components (MPEP 2106.05(f))
if the classification prediction for the given data point x* is determined to be erroneous, flagging the classification prediction for additional review, which merely recites the particular technological environment or field of use in which the abstract idea is to be performed (MPEP 2106.05(h))
and thus, the claim is directed to the abstract idea of determining whether predicted neural network classifications are erroneous through a Gaussian distribution of residuals.
(Step 2B) The additional elements, taken alone or in combination, cannot provide significantly more than the abstract idea because elements a) and b) ((via MPEP 2106.05(f), “apply it on a computer”) cannot provide an inventive concept and element c) (via MPEP 2106.05(h)) cannot integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, Claim 1 is subject-matter ineligible.
Claim 2, dependent upon Claim 1, recites an abstract idea step wherein the input-output kernel utilizes raw features x and softmax outputs σ to predict the residual r (disembodied mathematical algorithms and formulas) but no more additional elements.
Claim 3, dependent upon Claim 1, recites an abstract idea step wherein the I/O kernel includes an input kernel kin(
x
i
,
x
j
), which measures covariances in raw feature space, and a modified multi-output kernel kout(
σ
i
,
σ
j
), which calculates covariances in softmax output space (disembodied mathematical algorithms and formulas) but no more additional elements.
Claim 4, dependent upon Claim 1, recites an abstract idea step wherein hyperparameters of the I/O kernel are optimized to maximize the log marginal likelihood logp(r I X, σ) (disembodied mathematical algorithms and formulas) but no more additional elements.
Claim 5, dependent upon Claim 1, recites an abstract idea step wherein the Gaussian distribution for the estimated residual
r
^
*
〜 N(
r
¯
^
*
, var(
r
^
*
)) (disembodied mathematical algorithms and formulas) but no more additional elements.
Claim 6, dependent upon Claim 1, recites an abstract idea step wherein the error detection score c' is calculated according to
c
^
*
'
〜 N(
c
^
*
+
r
¯
^
*
, var(
r
^
*
)) (disembodied mathematical algorithms and formulas) but no more additional elements.
Claims 7-12 recite a non-transitory computer-readable medium with instructions to perform the process of Claims 1-6 respectively. As performance of an abstract idea on generic computing components (non-transitory computer readable medium) cannot integrate an abstract idea into a practical application nor provide significantly more than the abstract idea itself (see MPEP 2106.05(f)), Claims 7-12 are thus rejected for reasons set forth in the rejection of Claims 1-6.
Claims 13-18 recite a system comprising non-transitory computer-readable mediums with instructions to perform the process of Claims 1-6 respectively. As performance of an abstract idea on generic computing components (non-transitory computer readable medium) cannot integrate an abstract idea into a practical application nor provide significantly more than the abstract idea itself (see MPEP 2106.05(f)), Claims 13-18 are thus rejected for reasons set forth in the rejection of Claims 1-6 respectively.
Response to Arguments
The Examiner acknowledges the Applicant’s amendments to Claims 1, 7, and 13.
Applicant’s arguments filed March 2nd, 2026, traversing the rejection of claims 1-18 under 35 U.S.C. § 101 have been fully considered, but are not fully persuasive.
Applicant recites, on Pages 6-9 of the Remarks, that all pending claims are directed to an improvement to a technological process under Desjardins and Baker, specifically that the claims are directed to technological improvements in a base neural network classifier .
Examiner respectfully disagrees. While the specification may disclose claimed improvements in technology that may integrate the judicial exception into practical application, such improvements are not necessarily recited in the claim language. Examiner notes that the claimed invention does not directly improve the base classifier, but rather the claimed invention merely flags the classifier’s predicted output as erroneous or not erroneous. Flagging the output of a classifier for review, however, does not meaningfully change or improve the functionality of the base neural network classifier. As such, the claims are not directed to improvements in the functionality of a neural network unlike the case of Baker, where the classifier itself was directly improved to make fewer errors due to overfitting data. Applicant’s claimed improvements to technology are not clearly recited by the claim language, and thus Claim 1 remains directed to an abstract idea.
Examiner believes that although the claim language does not necessarily recite such improvements in technology, applicant’s specification may disclose possible improvements in technology. Notably, paragraph [0022] could possibly recite concrete technological improvements over applicant’s current amendments broadly reciting improved trustworthiness of classifier output and classifier output necessitating review.
The rejection of Claim 1 under 35 U.S.C. § 101 has been maintained. Similarly, the rejection of Claims 7 and 13 under 35 U.S.C. § 101 have been maintained.
The rejection of Claims 2-6 under 35 U.S.C. § 101, which depend directly or indirectly from Claim 1, have been maintained.
The rejection of Claims 8-12 under 35 U.S.C. § 101, which depend directly or indirectly from Claim 7, have been maintained.
The rejection of Claims 14-18 under 35 U.S.C. § 101, which depend directly or indirectly from Claim 13, have been maintained.
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 JONATHAN J KIM whose telephone number is (571)272-0523. The examiner can normally be reached 8-6.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matt Ell can be reached on (571) 270-3264. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JONATHAN J KIM/Examiner, Art Unit 2141
/ANDREW L TANK/Primary Examiner, Art Unit 2141
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