Non-Final Rejection
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 3 and 9 are objected to as having minor informalities
Claims 1-11 are rejected under 35 U.S.C. 101
Claims 1-11 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2)
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) filed on May 16th, 2025, has been considered.
Claim Objections
Claims 3 and 9 are objected to because of the following informalities: Both claims should be rephrased for clarity and smoothness, specifically regarding the “wherein” clauses. 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.
Claims 1-11 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract ideas without significantly more. The claims recite mental processes and mathematics. This judicial exception is not integrated into a practical application because the claims generally link abstract ideas to a generic computer and perform mere data gathering in relation to the mental processes. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because they include mere instructions to perform mental processes and mathematics on a generic computer.
The claims involve analyzing data and making judgments based off of a document.
Claim 1
Step 2A Prong 1: Identification of Abstract Ideas
Claim 1 recites:
… estimation (MPEP 2106.04(a)(2)(III)(A), “evaluations” are mental processes) …
analyze … to determine … classification of … content (MPEP 2106.04(a)(2)(III)(A), judgments, particularly identifying patterns are mental processes);
… extract, … a corresponding sentence … (MPEP 2106.04(a)(2)(III)(A), “observations,” are mental processes; MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process);
… infer … based on the corresponding sentence (a judgment based on text that has been read is considered a mental process with respect to MPEP 2106.04(a)(2)(III)(A)) …;
Step 2A Prong 2: Identification of Additional Elements
Claim 1 recites:
A(n) … system comprising (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application):
a memory having a machine learning model and (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application);
a processor coupled to the memory and configured to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application):
… a log related to a failure to … a failure … a failure … (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity);
cause the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) …, from a predetermined technical document, … corresponding to the determined failure classification (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity);
cause the machine learning model to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) … a first failure cause … extracted by the machine learning model (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity);
and output the first failure cause (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity).
Step 2B: Significantly More Analysis
The additional elements of the claim do not integrate the abstract ideas into a practical application. The claims simply state mental processes with mere instructions to perform these abstract ideas on a generic computer (MPEP 2106.05(f)(3)). The computer is cited at such a high level of generality that it cannot be determined to be a particular machine (MPEP 2106.05(b)) and is simply linking the judicial exception to a particular technology (MPEP 2106.05(h)). The claim recites only the idea of a solution, but fails to recite details as to how the solution to the problem is accomplished, because it leaves a majority of the analysis to the generic computer (MPEP 2106.05(f)(1)). The analysis done by the computer is never used to enact change upon the system, and thus cannot be determined to create an improvement to a computer or any other technology or technical field (MPEP 2106.05(a)).
Claim 2
Claim 2 recites:
generate a sentence extraction prompt for causing the machine learning model to extract the corresponding sentence from the predetermined technical document, input the generated sentence extraction prompt to the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application), and output the corresponding sentence (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity) from the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application), and generate a failure cause analysis prompt (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) for inferring a failure cause based on the corresponding sentence (MPEP 2106.04(a)(2)(III)(A), “observations, evaluations, judgments, and opinions,” are mental processes), input the generated failure cause analysis prompt to the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application), and output (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity) the first failure cause (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) from the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application).
Claim 3
Claim 3 recites:
cause the machine learning model to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) infer an occurrence probability (MPEP 2106.04(a)(2)(III)(A), “evaluations, judgments, and opinions,” are mental processes; MPEP 2106.04(a)(2)(I), mathematical relationships, formulas/equations, and calculations are abstract ideas; MPEP 2106.04(a), math that could be practically performed in the human mind is considered a mental process) for each of the failure classifications (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity), wherein cause the machine learning model to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) extract (MPEP 2106.04(a)(2)(III)(A), “observations,” are mental processes; MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process) the corresponding sentence corresponding to the failure classification the occurrence (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) probability of which is equal to or greater than a threshold (MPEP 2106.04(a)(2)(I), mathematical relationships and formulas/equations are abstract ideas; MPEP 2106.04(a), math that could be practically performed in the human mind is considered a mental process).
Claim 4
Claim 4 recites:
determine the failure classification using a failure analysis (MPEP 2106.04(a)(2)(III)(A), judgments, particularly identifying patterns are mental processes) logic tree (MPEP 2106.04(a)(2)(I), mathematical relationships, formulas/equations, and calculations are abstract ideas; MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process) indicating a failure classification corresponding to the failure content (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity).
Claim 5
Claim 5 recites:
determine the failure classification using any one of the failure analysis (MPEP 2106.04(a)(2)(III)(A), “observations, evaluations, judgments, and opinions,” are mental processes) logic tree (MPEP 2106.04(a)(2)(I), mathematical relationships, formulas/equations, and calculations are abstract ideas; MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process) automatically generated by artificial intelligence (Al) (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application), the failure analysis logic tree generated based on experience of an expert (MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process; MPEP 2106.04(a)(2)(III)(A), “judgments, and opinions,” are mental processes), or the failure analysis logic tree generated by modifying the logic tree automatically (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) generated by the AI by an expert (MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process; MPEP 2106.04(a)(2)(III)(A), “judgments, and opinions,” are mental processes).
Claim 6
Claim 6 recites:
cause the machine learning model to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) extract a sentence (MPEP 2106.04(a)(2)(III)(A), “observations,” are mental processes; MPEP 2106.04(a)(2)(III), a process that a human could do with a pen and paper is still a mental process) related to the failure classification as the corresponding sentence using the technical document including at least a specification of a system in which the failure has occurred (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity).
Claim 7
Claim 7 recites:
cause the machine learning model to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) infer (MPEP 2106.04(a)(2)(III)(A), “opinions,” are mental processes) a plurality of items as the first failure cause (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) and output (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity) a list of items of the first failure cause (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) from the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application).
Claim 8
Claim 8 recites:
cause the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) to clearly indicate a basis for inferring the first failure cause (identifying reasoning is a mental process with respect to MPEP 2106.04(a)(2)(III)(A)).
Claim 9
Claim 9 recites:
cause the machine learning model to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) infer a second failure cause based on a past case (MPEP 2106.04(a)(2)(III)(A), “observations, evaluations, judgments, and opinions,” are mental processes; MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity), wherein output (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity) the first failure cause inferred based on the corresponding sentence (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) by the machine learning model (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application) and second failure cause inferred based on a past case (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) by the machine learning model together (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application).
Claim 10
Step 2A Prong 1: Identification of Abstract Ideas
Claim 10 recites:
All limitations identified as abstract ideas have been analyzed above with respect to Claim 1.
Step 2A Prong 2: Identification of Additional Elements
Claim 10 recites:
An information processing apparatus comprising (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application):
memory and (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application);
a processor coupled to the memory and configured to (MPEP 2106.05(f), mere instructions to apply an abstract idea on a generic computer is not enough to integrate the claim into a practical application): …
All remaining limitations identified as additional elements have been analyzed above with respect to Claim 1.
Step 2B: Significantly More Analysis
Please see the above analysis of Claim 1.
Claim 11
Step 2A Prong 1: Identification of Abstract Ideas
Claim 11 recites:
An estimation method comprising (MPEP 2106.04(a)(2)(III)(A), “evaluations,” are mental processes): …
All remaining limitations identified as abstract ideas have been analyzed above with respect to Claim 1.
Step 2A Prong 2: Identification of Additional Elements
Claim 11 recites:
All limitations identified as additional elements have been analyzed above with respect to Claim 1.
Step 2B: Significantly More Analysis
Please see the above analysis of Claim 1.
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)(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.
(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.
Claims 1-11 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Zhou et al. (U.S. Publication No. 2022/0101115 A1), hereinafter referred to as Zhou.
With regards to Claim 1, Zhou teaches:
An estimation system comprising (Fig. 10; Fig. 2):
a memory having a machine learning model and (Paragraphs 0064-0068 and 0051-0052, memory; Paragraphs 0044-0045 and 0040-0041, machine learning);
a processor coupled to the memory and configured to (Paragraphs 0064-0068 and 0051-0052, memory):
analyze a log related to a failure to determine a failure classification of a failure content (Paragraphs 0033-0034);
cause the machine learning model to extract, from a predetermined technical document, a corresponding sentence corresponding to the determined failure classification (Paragraphs 0028-0031 and 0033-0034);
cause the machine learning model to infer a first failure cause based on the corresponding sentence extracted by the machine learning model (Paragraph 0035);
and output the first failure cause (Paragraphs 0035 and 0024).
With regards to Claim 2, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to, generate a sentence extraction prompt for causing the machine learning model to extract the corresponding sentence from the predetermined technical document, input the generated sentence extraction prompt to the machine learning model (Fig. 2 and Paragraphs 0033-0034, keywords extracted and used to extract the sentence), and output the corresponding sentence from the machine learning model, and generate a failure cause analysis prompt for inferring a failure cause based on the corresponding sentence, input the generated failure cause analysis prompt to the machine learning model (Fig. 2; Paragraphs 0033-0035; Paragraphs 0044-0045 and 0040-0041, machine learning), and output the first failure cause from the machine learning model (Paragraphs 0035 and 0024).
With regards to Claim 3, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to: cause the machine learning model to infer an occurrence probability for each of the failure classifications (Paragraphs 0046-0047), wherein cause the machine learning model to extract the corresponding sentence corresponding to the failure classification the occurrence probability of which is equal to or greater than a threshold (Paragraphs 0046-0047; Paragraph 0042, result; Paragraph 0035, downstream analysis; Paragraphs 0028-0031 and 0033-0034). Please note that Paragraphs 0036-0038 appear to describe the probability as the probability that the classification is correct.
With regards to Claim 4, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to, determine the failure classification using a failure analysis logic tree indicating a failure classification corresponding to the failure content (Paragraphs 0044-0045 and 0040-0041; Paragraphs 0033-0034).
With regards to Claim 5, Zhou teaches the system of Claim 4 as cited above. Zhou further teaches:
wherein the processor is further configured to, determine the failure classification using any one of the failure analysis logic tree automatically generated by artificial intelligence (Al), the failure analysis logic tree generated based on experience of an expert, or the failure analysis logic tree generated by modifying the logic tree automatically generated by the AI by an expert (Paragraphs 0044-0045 and 0040-0041; Paragraph 0050, retraining; Paragraph 0026).
With regards to Claim 6, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to, cause the machine learning model to extract a sentence related to the failure classification as the corresponding sentence using the technical document including at least a specification of a system in which the failure has occurred (Paragraphs 0028-0031 and 0033-0034).
With regards to Claim 7, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to, cause the machine learning model to infer a plurality of items as the first failure cause and output a list of items of the first failure cause from the machine learning model (Paragraphs 0046-0047).
With regards to Claim 8, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to, cause the machine learning model to clearly indicate a basis for inferring the first failure cause (Paragraph 0035).
With regards to Claim 9, Zhou teaches the system of Claim 1 as cited above. Zhou further teaches:
wherein the processor is further configured to, cause the machine learning model to infer a second failure cause (Paragraphs 0046-0047, multiple causes) based on a past case (Paragraph 0050, retraining; Paragraph 0026, training), wherein output the first failure cause inferred based on the corresponding sentence by the machine learning model and second failure cause inferred based on a past case by the machine learning model together (Paragraphs 0046-0047).
With regards to Claim 10, Zhou teaches:
An information processing apparatus comprising (Fig. 10; Fig. 2):
memory and (Paragraphs 0064-0068 and 0051-0052);
a processor coupled to the memory and configured to (Paragraphs 0064-0068 and 0051-0052):
Zhou further teaches the remaining limitations of Claim 10. Please see the above rejection of Claim 1 for citations of these limitations.
With regards to Claim 11, Zhou teaches:
An estimation method comprising (Fig. 2): …
Zhou further teaches the remaining limitations of Claim 11. Please see the above rejection of Claim 1 for citations of these limitations.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GABRIELLA SHELTON whose telephone number is (571)272-3117. The examiner can normally be reached Monday-Friday 8AM-3PM EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bryce Bonzo can be reached at (571) 272-3655. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/G.K.S./Examiner, Art Unit 2113 /BRYCE P BONZO/Supervisory Patent Examiner, Art Unit 2113
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