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 .
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 1-6 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
The claims are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. The claims are directed to the abstract idea of updating domain specific language models, as explained in detail below.
The claims are directed to organizing, processing and generating content based on rules and a user input. The claims fall under the mental processing (receiving an input prompt) along with methods for organizing information and content generation workflows. The claims recite receiving, organizing, displaying and outputting data, which is very close to generic data processing on a computer, which is non-statutory.
The present claim language under its broadest reasonable interpretation, covers performance of mental processing and recites generic computer components, which all falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements which are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
According to Step 1, it includes determining whether the claims fall within a statutory category. The claims include a method, therefore the claims fall within a statutory category. Step 2A Prong one, includes evaluating whether the claims recite a judicial exception. The claims recite a judicial exception, therefore an evaluation is done to determine if the claims fit into one of the categories. As explained, the claims fit into the mental processing concept. Prong 2B is used to evaluate whether the claims recite additional elements that integrate the exception into a practical application. As explained the judicial exception is not integrated into a practical application. In particular, the claim only recites additional elements which are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are non-statutory.
The limitations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “various elements” nothing in the claim element precludes the steps from practically being performed by mental processing, human activity and mathematical concepts. For example, the language, receiving an input prompt requesting domain specific information regarding servicing equipment within an industry (can be done by a user receiving a prompt),determining an initial output response using an industry specific large language machine learning model, wherein the industry specific large language machine learning model is periodically and dynamically fined tuned with an industry specific language database (can be done by a user making a determination and making updates accordingly) and outputting the initial output response to an interface (can be done by a user displaying data).
The dependent claims recite similar language such as generating and outputting data applying data, which is all part of the mental processing/organizing human activity category and is non-statutory.
Claim Rejections - 35 USC § 102
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-6 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gupta et al. (PGPUB 2025/0130124), hereinafter referenced as Gupta.
Regarding claim 1, Gupta discloses a method for communicating with a service provider using language-based communication and one or more artificial intelligence (AI) models, the method comprising:
receiving an input prompt requesting domain specific information regarding servicing equipment within an industry (multiple applications that expand across various domains including industry; p. 0001-0002);
determining an initial output response using an industry specific large language machine learning model (p. 0048, 0001), wherein the industry specific large language machine learning model is periodically and dynamically fined tuned with an industry specific language database (dynamic update/finetune; p.0068, 0075-0078, 0090-0095, 0119, 0194); and
outputting the initial output response to an interface (output; p. 0025-0027).
Regarding claim 2, Gupta discloses a method wherein:
the interface is an application programmable interface (p. 0153).
Regarding claim 3, Gupta discloses a method further comprising:
generating follow up questions based on a prompt (follow-up), the initial output response, and the industry specific large language machine learning model (initial; p. 0155, 0048, 0001); and
outputting follow up questions to the interface (p. 0155, 0048).
Regarding claim 4, Gupta discloses a method wherein:
the input prompt is provided by a user (p. 0153); and
the interface is accessible to the user to receive the initial output response (p. 0153, 0067, 0070).
Regarding claim 5, Gupta discloses a method wherein:
the interface is an output device accessible to a user (p. 0153).
Regarding claim 6, Gupta discloses a method wherein:
the output device is a display device (display; p. 0055, 0161); and
the initial output response is displayed to the user on the display device (display; p. 0055, 0161).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. This information has been detailed in the PTO 892 attached (Notice of References Cited).
Qazvinian et al. teaches intelligent analytics from generative artificial intelligence.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JAKIEDA R JACKSON whose telephone number is (571)272-7619. The examiner can normally be reached Mon - Fri 6:30a-2:30p.
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/JAKIEDA R JACKSON/Primary Examiner, Art Unit 2657
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