Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-20 are pending in the case.
This action is responsive to the Amendment filed on 1/30/2026.
Information Disclosure Statement
Documents listed in applicant’s Information Disclosure Statements dated 1/15/2026, have been considered but have been crossed out, as they patent applications that are not currently published and will not be listed as cited references in any subsequent patent publication resulting from the instant application.
Response to Arguments
Applicant's amendments with regards to the 35 U.S.C. § 112(a) rejection of claim(s) 1-20 have been considered, but are not persuasive. Examiner notes that applicant incorrectly refers to claims 1, 5 and 14, instead of claims 1, 6 and 14. Applicant argues
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Examiner respectfully disagrees. The above paragraph and the rest of Applicant’s specification discloses
- monitoring a trained machine learning model by relying upon reference data, and
- collecting reference data as part of training the trained machine learning model,
and therefore discloses
the reference data, upon which monitoring of the trained machine learning model relies, was collected as part of training the trained machine learning model.
However the original disclosure does not disclose a determination step for making a determination that reference that was collected as part of training,
and therefore does not disclose a determination step for
“determine that the reference data, upon which monitoring of the trained machine learning model relies, was collected as part of training the trained machine learning model according to the selection of the one or more bias metrics or feature attribution received before the training of the trained machine learning model” as recited in claim 1, and
“determining that the reference data was collected, upon which monitoring of the trained machine learning model relies, as part of training the trained machine learning model according to the selection of the one or more bias metrics or feature attribution received before the training of the trained machine learning model” as recited in claims 6 and 14.
The 35 U.S.C. § 112(a) rejection of claim(s) 1-20 is respectfully maintained.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “determine that the reference data, upon which monitoring of the trained machine learning model relies, was collected as part of training the trained machine learning model according to the selection of the one or more bias metrics or feature attribution received before the training of the trained machine learning model”, and
claims 6 and 14, each recite “determining that the reference data was collected, upon which monitoring of the trained machine learning model relies, as part of training the trained machine learning model according to the selection of the one or more bias metrics or feature attribution received before the training of the trained machine learning model” (Emphasis added).
The original specification discloses
- monitoring a trained machine learning model by relying upon reference data, and
- collecting reference data as part of training the trained machine learning model,
and therefore discloses
the reference data, upon which monitoring of the trained machine learning model relies, was collected as part of training the trained machine learning model.
However the original disclosure does not disclose a determination step for making a determination that reference that was collected as part of training,
and therefore does not disclose a determination step for
“determine that the reference data, upon which monitoring of the trained machine learning model relies, was collected as part of training the trained machine learning model according to the selection of the one or more bias metrics or feature attribution received before the training of the trained machine learning model” as recited in claim 1, and
“determining that the reference data was collected, upon which monitoring of the trained machine learning model relies, as part of training the trained machine learning model according to the selection of the one or more bias metrics or feature attribution received before the training of the trained machine learning model” as recited in claims 6 and 14.
Therefore the above noted limitations of claims 1, 6 and 14 do not have support in the original specification.
Claims 2-5, 7-13 and 15-20, merely recite additional functions performed by the inventions of claims 1, 6 and 14. Accordingly, claims 2-5, 7-13 and 15-20 are also rejected under 35 U.S.C. 112(a).
Applicant is requested to make appropriate amendments to the claims or clearly point of the specific portions of paragraphs in the specification that support the claim limitations.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bhide (US 20210406712 A1) discloses determining divergence metrics for a machine learning pipeline.
Wick (US20200372406A1) discloses selecting a subset of one or more bias metrics or the feature attributions.
Merrill (US 20190378210 A1) discloses constantly training and monitoring a deployed machine learning model for divergence.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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SANCHITA ROY
Primary Examiner
Art Unit 2146
/SANCHITA ROY/Primary Examiner, Art Unit 2146