CTNF 18/942,827 CTNF 101937 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Examiner’s Note Claims 1,9-10 of co-pending application 18/945,711 are similar to claims 1,9-10 of the current application, but are non-obvious at this time. However, if the claims become obvious due to amendments, a double patenting rejection will be given. Specification Applicant is reminded of the proper language and format for an abstract of the disclosure. The abstract should describe the disclosure sufficiently to assist readers in deciding whether there is a need for consulting the full patent text for details. In addition, the form and legal phraseology often used in patent claims, such as “means” and “said,” should be avoided. 06-11 AIA The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) elements which under their broadest reasonable interpretation are directed to mental processes. This judicial exception is not integrated into a practical application as explained below. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as explained below. Regarding Claim 1, the claim recites An information processing device comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to: (c) acquiring a prompt which is described in natural language and includes a designation of a task; (d) interpreting the prompt using a language model, (e) acquiring related information corresponding to the task designated by the prompt, (f) and acquiring an input variable to be used for prediction corresponding to the task designated, based on the related information; (g) and outputting the input variable acquired. Claim Interpretation : Under the broadest reasonable interpretation, the terms of the claim are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. See MPEP 2111. Claim elements a and b recite generic computer components at a high level of generality. Claim element c as written covers any method for acquiring a natural language prompt. The human mind can acquire a natural language prompt. Claim element d as written covers any method for interpreting a prompt. The human mind can interpret a prompt. Claim element e as written covers any method for acquiring related information. The human mind can acquire information. Claim element f as written covers any method for acquiring a variable from the related information. The human mind can parse through information to identify a variable. Claim element g as written covers any method for outputting the acquired variable. A human can output the identified variable using pen and paper. Additional elements recited are memory configured to store instructions, processor configured to execute the instructions, and language model. Step 1 : This part of the eligibility analysis evaluates whether the claim falls within any statutory category. See MPEP 2106.03. The claim is directed to a machine, which falls within one of the statutory categories of invention. (Step 1: YES). Step 2A, Prong One : This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. As discussed above, the broadest reasonable interpretation of limitations (c)-(g) is that those limitations fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2),subsection III. Element c is directed to a mental step since a human can acquire a prompt through reading or hearing. Element d is directed to a mental step since the human mind can interpret a prompt. Element e is directed to a mental step since the human mind can acquire information and decide if it is related to the prompt. Element f is directed to a mental step since the human mind can parse through related information to identify a variable. Element g is directed to a mental step since the human mind can output an identified variable with the aid of pen and paper. Hence, these steps can be performed by a human, using “observation, evaluation, judgment, [and] opinion,” because they involve making determinations and identifications, which are mental tasks humans routinely do,' ” and thus can practically be performed in the human mind, In re Killian, 45 F.4th 1373, 1379 (Fed. Cir. 2022). Therefore, these limitations are considered together as an abstract idea for further analysis. (Step 2A, Prong One: YES). Step 2A, Prong Two : This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d). The additional elements recited are memory configured to store instructions, processor configured to execute the instructions, and language model. These 3 additional elements provide nothing more than mere instructions to implement an abstract idea on a generic computer . See MPEP 2106.05(f). MPEP2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e. the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES). Step 2B : This part of the eligibility analysis evaluates whether the claim as a whole amount to significantly more than the recited exception, i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05. At Step 2A the additional elements recited were found to represent no more than mere instructions to apply the judicial exception on a computer using generic computer components. Mere instructions to “apply” the abstract ideas, cannot provide an inventive concept . See MPEP 2106.05(f). The analysis under Step 2A, Prong Two is carried through to Step 2B. Further, one or more images of physical environment captured using the one or more cameras was found to be insignificant extra solution activity. However, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B. See MPEP 2106.05, subsection I.A. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept. (Step 2B: NO). As such Claim 1 is not patent eligible. Regarding Claims 9 and 10, analysis analogous to that of Claim 1 is applicable. Regarding Claims 2 and 4, the human mind can come up with a variable related to a prediction task. Hence it is directed to a mental process Regarding Claim 3, additional limitations further limit a mental pr Regarding Claims 5 and 6, the human mind can create a new formula and a new processing method. Hence the claim is directed to a mental process Regarding Claim 7, the storage unit recited is a generic computer component recited at a high level of generality. Additionally, the human mind can store a formula using pen and paper. Regarding Claim 8, the human mind can determine if the variable satisfies the condition. Claim Rejections - 35 USC § 102 07-07-aia AIA 07-07 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 – 07-12-aia AIA (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. 07-15-03-aia AIA Claim s 1,8-10 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Ojha (US PGPub 20240303263) . Regarding Claim 1, Ojha teaches an information processing device comprising: at least one memory configured to store instructions (Device 1000 also may include a main memory 1040, for example, random access memory (RAM), and also may include a secondary memory 1030. Secondary memory 1030, e.g., a read-only memory (ROM), may be, for example, a hard disk drive or a removable storage drive.[0100]) ; and at least one processor configured to execute the instructions to (device 1000 may include a central processing unit (CPU) 1020. CPU 1020 may be any type of processor device[0099]) : acquiring a prompt which is described in natural language (In operation 210, the system may receive a natural language prompt from a user[0062]) and includes a designation of a task (The prompt may, for example, relate to a time series forecast, a trend analysis, or a key driver analysis[0062]) ; interpreting the prompt using a language model (In operation 220, the system may, such as though LLM 111, process the user prompt. In operation 230, the system may, such as though LLM 111, determine a request type of the user prompt. For example, LLM 111 may determine whether the user prompt relates to a time series forecast, a trend analysis, or a key driver analysis[0062]) , acquiring related information corresponding to the task designated by the prompt (In operation 240, the system may, such as though LLM 111, determine what data is to be used to process the user prompt. For example, LLM may access metadata and terminology across broad data sets captured in a semantic graph to determine datasets and variables (i.e., metrics and attributes) that may be relevant to the user prompt[0062]) , and acquiring an input variable to be used for prediction (predictive data 304 may be updated based on updated contextually-relevant information, seasonality, trends, key drivers[0069]) corresponding to the task designated (a key driver(Interpretation: key driver is variable that can be used to predict the task the user is requesting) analysis may be conducted to identify key drivers that cause a change in user relevant data[0080], Fig 7A, Fig 7B) , based on the related information; and outputting the input variable acquired (techniques in the present application may be used to automatically provide contextually-relevant information, forecasts, and/or key drivers to a user[0046]) . Claim 9 is directed to a method claim with similar limitations to that of Claim 1 and is rejected under the same rationale. Claim 10 is directed to a computer readable memory claim with similar limitations to that of Claim 1 and is rejected under the same rationale. Regarding Claim 8, Ojha teaches the prompt includes a condition concerning the task (a user provided threshold[0084]) , and the processor acquires the input variable satisfying the condition (One or more categories that meet a corresponding threshold and/or one or more subcategories that meet a corresponding subcategory threshold may be flagged as a key driver[0085]) . Claim Rejections - 35 USC § 103 07-20-aia AIA The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. 07-23-aia AIA The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 07-21-aia AIA Claim (s) 2-4, 6 are rejected under 35 U.S.C. 103 as being unpatentable over Ojha(US PGPub 20240303263) in view of Lynch(US PGPub 20210117853) . Regarding Claim 2, Ojha does not teach the processor generates a new input variable not included in the related information. However, Lynch teaches the processor generates a new input variable not included in the related information (The new feature(s)(Interpretation: feature is the input variable/key driver) may also be generated in a process that includes discovering related features by mapping features to identifiers in the formulas and applying a set of transformations to the related features independent of any mathematical relationship(s) in the matched formulas.) . It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Ojha with the feature generation of Lynch because it would improve predictive modeling(Lynch 0013). Regarding Claim 3, Ojha does not teach the related information is described in natural language, and the related information includes a predictive formula corresponding to the task designated, the input variable to be used for the prediction corresponding to the task designated, and a processing method of the input variable. However, Lynch teaches the related information is described in natural language (text-based formula in the corpus. The at least one description may include a textual description and/or a semantic concept entry in a database.[0027]) , and the related information includes a predictive formula corresponding to the task designated (In the example shown, the formula 402 (and/or the document 400 as a whole) is related to monthly mortgage payments, and the formula 402 includes identifiers, such as c, r, N, and P.[0076]) , the input variable to be used for the prediction corresponding to the task designated, and a processing method of the input variable (the document 400 also includes information or descriptions of identifiers r, N, and P in sections 404, 406, and 408, respectively, along with information/descriptions of identifier c in the formula[0076]) . It would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Ojha with the related information of Lynch because it would improve the “explainability” or “interpretability” of results generated using the features and/or machine learning model(Lynch 0085). Regarding Claim 4, Ojha modified by Lynch, as applied in Claim 3, teaches the processor generates a new input variable from among a plurality of existing input variables included in the related information (New candidate features may then be generated in several ways. For example, related features maybe combined to create new features based on their relationship(s) in the identified formula(s) and/or related features may be combined using common mathematical transformations, such as multiplication, division, etc.[Lynch 0074]) , based on the prompt (, the system may, such as though LLM 111, determine what data is to be used to process the user prompt[Ojha 0062]) and the related information. Regarding Claim 6, Ojha modified by Lynch, as applied in Claim 3, teaches the processor generates a new processing method of the input variable (generate candidate descriptions for identifiers[ Lynch 0071]) and a new input variable which is acquired by the processing method, based on the prompt and the related information (New candidate features may then be generated in several ways. For example, related features maybe combined to create new features based on their relationship(s) in the identified formula(s) and/or related features may be combined using common mathematical transformations, such as multiplication, division, etc.[Lynch 0074]) . 07-22-aia AIA Claim (s) 5 is rejected under 35 U.S.C. 103 as being unpatentable over Ojha in view of Lynch as applied to claim 3 above, and further in view of Muraoka(US PGPub 20160117588) . Regarding Claim 5, Ojha modified by Lynch does not teach the processor generates a new predictive formula which uses the new input variable. However, Muraoka teaches the processor generates a new predictive formula which uses the new input variable (using a set of samples that include explanatory variables(interpretation: the new input variable from Claim 4) and an objective variable as training data, creating a prediction function to derive the objective variable[0024]) . It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Ojha modified by Lynch with the function creation of Muraoka because it can carry out prediction with high accuracy(Muraoka 0014) . 07-22-aia AIA Claim (s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Ojha in view of Lynch as applied to claim 3 above, and further in view of Xu(US PGPub 20170076210) . Regarding Claim 7, Ojha modified by Lynch teaches the related information is stored in a storage unit (The knowledge base (or index or semantic formula index)[ Lynch 0019]) , the processor acquires the related information from the storage unit (A feature for the machine learning model is generated based on a formula within a corpus (step 608). The formula is associated with the at least one textual description (i.e., via the semantic formula index)[Lynch 0089]) . Ojha modified by Lynch also teaches the new processing method (generate candidate descriptions for identifiers[ Lynch 0071]) and the new input variable which are generated (New candidate features may then be generated in several ways. For example, related features maybe combined to create new features based on their relationship(s) in the identified formula(s) and/or related features may be combined using common mathematical transformations, such as multiplication, division, etc.[Lynch 0074]) . Ojha modified by Lynch does not teach the processor stores the generated values in the storage unit. However, Xu teaches the processor stores the generated (the curve fitting unit can generate the predictive formula[0044]) values in the storage unit (The predictive formula is stored in the metadata store along with the service request parameters and the server response data[0045]) . It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the system of Ojha modified by Lynch with the storage of Xu because it would assist with refining predictive formulas(Xu 0031) . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure : Okamoto(US20230252067) teaches a system for ranking explanatory variables given an objective variable. Yu et al(Temporal Data Meets LLM Explainable Financial Time Series Forecasting) teaches explaining to a user factors that would influence a forecasting problem, similar to the objective of the claimed application. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARJUN R SWAMY whose telephone number is (571)272-9763. The examiner can normally be reached Mon-Fri 8-5. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hai Phan can be reached at (571) 272-6338. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ARJUN SWAMY/Examiner, Art Unit 2654 /HAI PHAN/Supervisory Patent Examiner, Art Unit 2654 Application/Control Number: 18/942,827 Page 2 Art Unit: 2654 Application/Control Number: 18/942,827 Page 3 Art Unit: 2654 Application/Control Number: 18/942,827 Page 4 Art Unit: 2654 Application/Control Number: 18/942,827 Page 5 Art Unit: 2654 Application/Control Number: 18/942,827 Page 6 Art Unit: 2654 Application/Control Number: 18/942,827 Page 7 Art Unit: 2654 Application/Control Number: 18/942,827 Page 8 Art Unit: 2654 Application/Control Number: 18/942,827 Page 9 Art Unit: 2654 Application/Control Number: 18/942,827 Page 10 Art Unit: 2654 Application/Control Number: 18/942,827 Page 11 Art Unit: 2654 Application/Control Number: 18/942,827 Page 12 Art Unit: 2654 Application/Control Number: 18/942,827 Page 13 Art Unit: 2654
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