DETAILED ACTION
Claims 1-20 are pending in the present application. Claims 1, 5, 7-10, 14, and 16-19 were amended.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 28 August 2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 3, 14, and 18 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Cheng et al. US Patent Application Publication No. 2024/0303443 A1.
Regarding claim 1, Cheng et al. teaches the following:
A computing system [note: figure 8 (800) computing device ] comprising:
at least one hardware processor [note: figure 8 (810) processor; figure 10; paragraph 0113 one or more processors ];
at least one memory coupled to the at least one hardware processor [note: figures 8 and 10; paragraph 0038 memory ]; and
one or more computer-readable storage media comprising computer-executable instructions that, when executed, cause the computing system to perform operations [note: figures 8 and 10; paragraph 0038; paragraph 0113 building AI infracture] comprising:
receiving input identifying a data set to be processed using computing logic that carries out a predictive analytics technique [note: figure 11 flow chart step (1102) receive via a communications interface; paragraphs 0043-0044 ];
generating a first prompt by executing computing instructions that cause information regarding data objects used by the predictive analytics technique to be inserted into a first prompt template that comprises an instruction to extract information useable to generate the data objects [note: paragraph 0113; paragraphs 0116-0119, “0116] At step 1104, a database of user-specified prompt templates (e.g., prompt store 211 in FIG. 2) may be searched based on the NLP task.[0117] At step 1106, one or more context vectors may be retrieved, from a database of context features (e.g., vector store 312, feature store 313, etc. of FIG. 3), based on the NLP task request. In one implementation, the one or more context vectors may be used to inject knowledge from a domain. For example, domain training data (e.g., 719 in FIG. 7A) may be transformed into one or more semantic vectors and/or task-specific vectors, and then injected the one or more semantic vectors and/or task-specific vectors (e.g., 733a-c in FIG. 7A), which are then injected into the one or more generated prompts.
[0118] At step 1108, one or more user-specified prompt templates may be populated with the retrieved one or more context vectors (e.g., by the prompt completion 206 in FIG. 3). In one implementation, the one or more generated prompts may be augmented with a set of constraints that are specific to the NLP task, wherein the set of constraints are provided by a user via a user interface.[0119] At step 1110, an AI gateway (e.g., 130 in FIG. 1) may transmit one or more generated prompts to a neural network based NLP model (e.g., LLMs 519a-n in FIG. 5) that is housed at a vendor server external to the enterprise server. For example, the neural network NLP model may be selected for the customized generative AI infrastructure based on the NLP task. The one or more generated prompts may be incorporated into a normalized API request (e.g., 513 in FIG. 5) comprising a parameter specifying a specific vendor and/or the selected specific neural network based NLP model.”; also see paragraphs 0121 user interface and neural network based on NLP model ];
submitting the first prompt to a neural language model [note: paragraphs 0116-0119, and 0121 ];
receiving a first response to the first prompt that comprises the information usable to generate the data objects [note: paragraphs 0116-0119, and 0121 ]; and
configuring a procedure to execute the predictive analytics technique, the configuring comprising executing computing instructions to insert an identifier of an object that comprises data of the data set, the information useable to generate the data objects, and insert an identifier of the predictive analytics technique into a procedure template to populate the procedure template and generate the provide a procedure [note: paragraphs 0116-0119, and 0121 ].
Claim 2: The computing system of claim 1, the operations further comprising:
parsing the first response to extract table structures, wherein the information usable to generate the data objects comprises commands that use the extracted table structures [note: figure 11 (1104) search a database ].
Claim 3: The computing system of claim 1, the operations further comprising:
executing the procedure to provide predictive analytics results for data of the data set [note: figure 11 (1112) results; paragraph 0118 through 0119, populating template ].
The limitations of claims 14 and 18 parallel claim 1; therefore, they are rejected under the same rationale.
Allowable Subject Matter
Claims 2, 4-13, 15-17, and 19-20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
The amendment overcomes the rejection cited under 35 USC 112 second; however the reference cited on form PTOL-1449, Cheng et al. appears to apply to claims 1, 3, 14 and 18.
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 GRETA ROBINSON whose telephone number is (571)272-4118. The examiner can normally be reached Mon.-Fri. 9:30AM-6:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hassan Mahmoudi can be reached at 571-272-4078. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/GRETA L ROBINSON/Primary Examiner, Art Unit 2163
