Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This is the initial office action based on the application filed on August 05th, 2024, which claims 1-15 are presented for examination.
Status of Claims
3. Claims 1-15 are pending, of which claims, of which claim 1, 6 and 11 are in independent form.
Priority
4. No priority has been considered for this application.
The Office's Note:
5. The Office has cited particular paragraphs / columns and line numbers in the reference(s) applied to the claims above for the convenience of the Applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim(s), other passages and figures may apply as well. It is respectfully requested from the Applicant in preparing responses, to fully consider the references in entirety as potentially teaching all or part of the claimed invention, as well as the context of the cited passages as taught by the prior art or relied upon by the Examiner.
Claim Objections
6. Claim 10 objected to because of the following informalities: on line 1, claim 10 recites “They system of claim 1”, but it should be “They system of claim 6”. Appropriate correction is required.
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.
7. Claims 6-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 6 recites “A system” for harnessing generative artificial intelligence (“GenAI”) to provide dynamic feedback to developers. Claim 6 does not disclose any hardware component to realize any of the underlying functionality of the said a program product’s implementation. Therefore, examiner will reasonably interpret functionality of this system as an implementation of software alone, Software and computer program per se do not fall within any category of patent-eligible subject matter. Furthermore, claims 7-10 depend from claim 6, and therefore, claims 7-10 do not overcome the deficiency stated above for claim 6, and do not fall within any category of patent-eligible subject maters. Claims 6-10 are therefore ineligible for patent protection. See MPEP § 2106. The Office suggested applicants to add “a processor” into the system to overcome the 101 rejection.
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.
8. Claims 12-15 recite the limitation “The computer-readable media of claim 11”. There is insufficient antecedent basis for this limitation in the claim. The Office suggested applicants to amend the limitation from “The computer-readable media of claim 11” to ““The non-transitory computer-readable media of claim 11”.
Double Patenting
A rejection based on double patenting of the “same invention” type finds its support in the language of 35 U.S.C. 101 which states that “whoever invents or discovers any new and useful process... may obtain a patent therefor...” (Emphasis added). Thus, the term “same invention,” in this context, means an invention drawn to identical subject matter. See Miller v. Eagle Mfg. Co., 151 U.S. 186 (1894); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Ockert, 245 F.2d 467, 114 USPQ 330 (CCPA 1957).
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Instant application 18/794,178
Co-pending application 18/794,129
1. A method for harnessing generative artificial intelligence (“GenAI”) to provide dynamic feedback to developers, the method comprising:
receiving a plurality of processed data elements, each processed data element, included in the plurality of the processed data elements, comprising two or more iterations of:
a software element generated by a developer; and
a feedback document generated by a tester in response to receiving the software element;
training a large language model with the plurality of processed data elements, said large language model operating in tandem with an artificially intelligent feedback engine;
enabling a first developer to create a software element;
pushing the software element to an artificially intelligent feedback engine;
assessing the software element at the artificially intelligent feedback engine, said assessing comprising using the large language model operating in tandem with the artificially intelligent feedback engine to generate a feedback document for the software element, said feedback document comprising:
one or more comments on the software element;
one or more modifications for the software element; and
a quality index for the software element;
providing the feedback document to the first developer; when the quality index is above a first threshold, enabling the first developer to:
override the feedback document; and
send an unedited version of the software element to publication, said unedited version of the software element absent incorporation of the one or more comments and/or the one or more modifications;
when the quality index is below the first threshold and above a second threshold enabling the first developer to:
override the feedback document and push the software element for publication;
modify the software element and push the software element for publication; and
modify the software element and push the software element for an additional assessment by the artificially intelligent feedback engine;
when the quality index is below the second threshold:
disabling publishing the software element; and forcing incorporation of one or more of the one or more comments and/or one or more of the one or more revisions prior to sending the software element for publication.
1. A method for harnessing generative artificial intelligence (“GenAI”) to provide dynamic feedback to developers, the method comprising:
receiving a plurality of processed data elements, each processed data element, included in the plurality of the processed data elements, comprising two or more iterations of:
a software element generated by a developer; and
a feedback document generated by a tester in response to receiving the software element;
training a large language model with the plurality of processed data elements, said large language model operating in tandem with an artificially intelligent feedback engine;
enabling a first developer to create a software element;
pushing the software element to the artificially intelligent feedback engine;
assessing the software element at the artificially intelligent feedback engine, said assessing comprising using the large language model operating in tandem with the artificially intelligent feedback engine to generate the feedback document for the software element, said feedback document comprising:
one or more comments on the software element;
one or more modifications for the software element; and
a quality index for the software element;
providing the feedback document to the first developer;
enabling the first developer to:
override the feedback document; and
send an unedited version of the software element to publication, said unedited version of the software element absent incorporation of the one or more comments and/or one or more modifications.
6. A system for harnessing generating artificial intelligence (“GenAI”) to provide dynamic feedback to developers, the system comprising:
an artificially intelligent engine operating in tandem with a large language model, said large language model trained on:
a plurality of processed data elements, each processed data element, included in the plurality of processed data elements comprising two or more iterations of:
a software element generated by a developer; and
a feedback document generated by a tester in response to receiving the software element;
a software development user interface, said software development user interface enabling a developer to:
create a software element;
send a software element for review; and
publish the software element;
the artificially intelligent feedback engine operable to:
intercept a software element sent for review;
assess the software element using the large language model to generate a feedback document for the software element;
provide the feedback document to the developer via the software development user interface, said feedback document comprising:
one or more comments on the software element;
one or more modifications for the software element; and
a quality index for the software element;
upon receipt of the feedback document at the software development user interface, enable the first developer to: when the quality index is above a first threshold:
override the feedback document; and send an unedited version of the software element to publication, said unedited version of the software element absent incorporation of the one or more comments and/or the one or more modifications;
when the quality index is below the first threshold and above a second threshold:
override the feedback document and push the software element for publication;
modify the software element and push the software element for publication; and
modify the software element and push the software element for an additional assessment by the artificially intelligent feedback engine;
when the quality index is below the second threshold:
disable publishing the software element; and
force incorporating one or more of the one or more comments and/or one or more of the one or more revisions prior sending the software element for publication.
7. A system for harnessing generating artificial intelligence (“GenAI”) to provide dynamic feedback to developers, the system comprising:
an artificially intelligent feedback engine operating in tandem with a large language model, said large language model trained on:
a plurality of processed data elements, each processed data element, included in the plurality of processed data elements comprising two or more iterations of:
a software element generated by a developer; and
a feedback document generated by a tester in response to receiving the software element;
a software development user interface, said software development user interface enabling a developer to:
create a software element;
send the software element for review; and
publish the software element;
the artificially intelligent feedback engine operable to:
intercept the software element sent for review;
assess the software element using the large language model to generate the feedback document for the software element;
provide the feedback document to the developer via the software development user interface, said feedback document comprising:
one or more comments on the software element;
one or more modifications for the software element; and
a quality index for the software element;
upon receipt of the feedback document at the software development user interface, enable the developer to:
override the feedback document; and send an unedited version of the software element to publication, said unedited version of the software element absent incorporation of the one or more comments and/or one or more modifications.
11. One or more non-transitory computer-readable media storing computer-executable instructions which, when executed by a processor on a computer system, perform a method for harnessing generating artificial intelligence (“GenAI”) to provide dynamic feedback to developers, the method comprising:
receiving a plurality of processed data elements, each processed data element, included in the plurality of the processed data elements, comprising two or more iterations of:
a software element generated by a developer; and
a feedback document generated by a tester in response to receiving the software element;
training a large language model with the plurality of processed data elements, said large language model operating in tandem with an artificially intelligent feedback engine;
enabling a first developer to create a software element;
pushing the software element to an artificially intelligent feedback engine;
assessing the software element at the artificially intelligent feedback engine, said assessing comprising using the large language model operating in tandem with the artificially intelligent feedback engine to generate a feedback document for the software element, said feedback document comprising:
one or more comments on the software element;
one or more modifications for the software element; and
a quality index for the software element;
providing the feedback document to the first developer;
enabling the first developer to: when the quality index is above a first threshold:
override the feedback document; and
send an unedited version of the software element to publication, said unedited version of the software element absent incorporation of the one or more comments and/or the one or more modifications;
when the quality index is below the first threshold and above a second threshold enabling the first developer to: override the feedback document and push the software element for publication; modify the software element and push the software element for publication; and modify the software element and push the software element for an additional assessment by the artificially intelligent feedback engine;
when the quality index is below the second threshold: disable publishing the software element; and force incorporation of one or more of the one or more comments and/or one or more of the one or more revisions prior to sending the software element for publication.
13. One or more non-transitory computer-readable media storing computer-executable instructions which, when executed by a processor on a computer system, perform a method for harnessing generating artificial intelligence (“GenAI”) to provide dynamic feedback to developers, the method comprising:
receiving a plurality of processed data elements, each processed data element, included in the plurality of the processed data elements, comprising two or more iterations of:
a software element generated by a developer; and
a feedback document generated by a tester in response to receiving the software element;
training a large language model with the plurality of processed data elements, said large language model operating in tandem with an artificially intelligent feedback engine;
receiving a software element, said software element created by a developer; pushing the software element to the artificially intelligent feedback engine;
assessing the software element at the artificially intelligent feedback engine, said assessing comprising using the large language model operating in tandem with the artificially intelligent feedback engine to generate the feedback document for the software element, said feedback document comprising:
one or more comments on the software element;
one or more modifications for the software element; and
a quality index for the software element; providing the feedback document to the developer;
enabling the developer to: override the feedback document; and send an unedited version of the software element to publication, said unedited version of the software element absent incorporation of the one or more comments and/or one or more modifications.
9. Claim 1, claim 6 and claim 11 provisionally rejected on the ground of nonstatutory double patenting over claim 1, claim 7 and claim 13 of co-pending U.S. application 18/794,129. Claim 1, claim 6 and claim 11 of the instant application teaches includes all the features of claim 1, claim 7 and claim 13 of co-pending U.S. application 18/794,129. Both claims teach harnessing GenAI to provide dynamic feedback to developers. This is a provisional non-statutory double patenting rejection.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DUY KHUONG THANH NGUYEN whose telephone number is (571)270-7139. The examiner can normally be reached M-F 8 to 5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lewis Bullock can be reached on 5712723759. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DUY KHUONG T NGUYEN/ Primary Examiner, Art Unit 2199
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