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 1-2 and 5-20, and 22 are rejected under 35 U.S.C. 101
Claims 1-2 and 5-20, and 22 are rejected under 35 U.S.C. 103
Claims 3, 4, and 21 have been cancelled by Applicant
Response to Amendment
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-2, 5-20, and 22 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. 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 on a generic computer.
The claimed invention uses generic computing models to determine a high-level resolution to a generic failure in a computing environment based off of known data. The specification describes the invention as automizing and optimizing procedures previously done by humans (Paragraphs 0018 and 0022-0023).
Claim 1
Step 2A Prong 1: Identification of Abstract Ideas
Claim 1 recites:
summarizing … the information related to the incident as a textual prompt (MPEP 2106.04(a)(2)(III)(A), judgments, particularly “collecting information, analyzing it, …” are mental processes) … wherein the first machine learning model is a question answering large language model (LLM) (answering questions is considered observing, evaluating, judging, and forming opinions, and thus is considered to be a mental process with respect to MPEP 2106.04(a)(2)(III)(A));
… wherein the second machine learning model is a configuration generation coding LLM … generates … based on at least … (an opinion of what a configuration should be based on known, observed information is considered a mental process with regards to MPEP 2106.04(a)(2)(III)(A));
Step 2A Prong 2: Identification of Additional Elements
Claim 1 recites:
A computer-implemented method comprising (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application) …
obtaining (MPEP 2106.05(g), mere data gathering is considered insignificant extra-solution activity), by an observability tool of a processing platform (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application), information related to an incident detected in the computing environment, the information comprising a dynamic state information set and a static state information set, the dynamic information set comprising one or more of events, traces, logs, and metrics related to the incident and the static state information set comprising one or more of types and numbers of entities within the computing environment and hardware and infrastructure configurations within the computer environment (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity; MPEP 2106.05(h)(vi), limiting the data collection and analysis to a particular field of use does not integrate the abstract idea into a practical application);
… by a prompt system of the processing platform … using a first machine learning model of a dual machine learning model architecture (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application) …
and inputting, by the prompt system of the processing platform, the textual prompt into a second machine learning model of the dual machine learning model architecture … such that the second machine learning model, in response (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application) … an output comprising (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity) a resolution to the incident (MPEP 2106.05(f)(1), high level, generic solutions are considered mere instructions to apply a judicial exception and thus are not enough to integrate a claim into a practical application; MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) … the dynamic information set and the static information set (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity);
generating, by the processing platform, an automated control signal based on the output from the second machine learning model (MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity; MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application);
sending, by the processing platform, the automated control signal to a system on which the computing environment is hosted to automatically reconfigure the computing environment in response to the control signal (MPEP 2106.05(f)(2), “using a computer in its ordinary capacity … e.g. to receive, store, or transmit data … does not integrate a judicial exception into a practical application”; MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity; MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application);
wherein the computer-implemented method is performed by the processing platform executing program code, the processing platform comprising one or more processing devices, each of the one or more processing devices comprising a processor coupled to a memory (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application).
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 computer is simply used as a tool to complete the mental process (MPEP 2106.05(f)(2)).
Claim 2
Claim 2 recites:
applying a root cause failure analysis process on the obtained information such that a reduced set of information is generated that relates to a subset of entities within the computing environment (MPEP 2106.04(a)(2)(III)(A), “observations, evaluations, judgments, and opinions,” comparing known information, and pattern matching are mental processes; MPEP 2106.05(f)(1), high level, generic solutions are considered mere instructions to apply a judicial exception and thus are not enough to integrate a claim into a practical application; MPEP 2106.05(h), specifying a field of use or technological environment cannot integrate a judicial exception into a practical application).
Claim 5
Claim 5 recites:
wherein the configuration generation LLM is trained on historical data, the historical data comprising prior incidents in the computing environment and prior resolutions to the prior incidents in the computing environment (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity; MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application).
Claim 6
Claim 6 recites:
wherein the one or more of events, traces, logs of the dynamic state information set comprise one or more of events, traces, logs, and metrics of a given time window before and after the detection of the incident (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:
wherein the static state information set further comprises one or more of a state of one or more applications in the computing environment, a state of one or more infrastructure components of the computing environment, a configuration of the computing environment, a configuration of one or more entities in the computing environment and one or more resource types of the computing environment (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity).
Claim 8
Claim 8 recites:
wherein the incident indicates a potential functional failure of the computing environment (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity; MPEP 2106.05(h), specifying a field of use or technological environment cannot integrate a judicial exception into a practical application).
Claim 9
Claim 9 recites:
wherein the incident indicates a potential performance failure of the computing environment (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity; MPEP 2106.05(h)(vi), limiting the data collection and analysis to a particular field of use does not integrate the abstract idea into a practical application).
Claim 10
Claim 10 recites:
wherein the resolution to the incident comprises recommended changes to a configuration of the computing environment (MPEP 2106.04(a)(2)(III)(A), “observations, evaluations, judgments, and opinions,” and pattern matching are mental processes; MPEP 2106.05(f)(1), high level, generic solutions are considered mere instructions to apply a judicial exception and thus are not enough to integrate a claim into a practical application).
Claim 11
Claim 11 recites:
wherein the output from the second machine learning model is input into the first machine learning model to retrain the first machine learning model (MPEP 2106.05(g), mere data gathering is considered insignificant extra-solution activity; 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; MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity) with the resolution to the incident, wherein the resolution to the incident comprises at least one remediated configuration (MPEP 2106.04(a)(2)(III)(A), “observations, evaluations, judgments, and opinions,” and pattern matching 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; MPEP 2106.05(f)(1), high level, generic solutions are considered mere instructions to apply a judicial exception and thus are not enough to integrate a claim into a practical application).
Claim 12
Step 2A Prong 1: Identification of Abstract Ideas
Claim 12 recites:
Please see the above rejection of Claim 1 regarding limitations that have been identified as abstract ideas.
Step 2A Prong 2: Identification of Additional Elements
Claim 12 recites:
A computer system comprising: a processor set (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application);
a set of one or more computer-readable storage media (MPEP 2106.05(f)(2), “using a computer in its ordinary capacity … e.g. to receive, store, or transmit data … does not integrate a judicial exception into a practical application”);
and program instructions, collectively stored in the set of one or more storage media, for causing the processor set to perform computer operations comprising (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application) …
Please see the above rejection of Claim 1 regarding the remaining limitations that have been identified as additional elements.
Step 2B: Significantly More Analysis
Please see the above rejection of Claim 1 for the analysis under Step 2B.
Claims 13-15
All limitations of Claims 13-15 have been addressed in the analyses of Claims 2 and 6-7, respectively. Please see the above rejections for further details.
Claim 16
wherein the incident indicates at least one of a potential functional failure of the computing environment and a potential performance failure of the computing environment (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity; MPEP 2106.05(h), specifying a field of use or technological environment cannot integrate a judicial exception into a practical application).
Claim 17
Step 2A Prong 1: Identification of Abstract Ideas
Claim 17 recites:
Please see the above rejection of Claim 1 regarding limitations that have been identified as abstract ideas.
Step 2A Prong 2: Identification of Additional Elements
Claim 17 recites:
A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by one or more processors to cause the one or more processors to perform computer operations comprising (MPEP 2106.05(f), mere instructions to apply an abstract idea on a computer is not enough to integrate the claim into a practical application) …
Please see the above rejection of Claim 1 regarding the remaining limitations that have been identified as additional elements.
Step 2B: Significantly More Analysis
Please see the above rejection of Claim 1 for the analysis under Step 2B.
Claims 18-20
All limitations of Claims 18-20 have been addressed in the analyses of Claims 2 and 6-7, respectively. Please see the above rejections for further details.
Claim 22
Claim 22 recites:
wherein the recommended changes to a configuration of the computing environment comprises one or more configuration remediation recommendations phrased in at least one of natural language or code (MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated” is considered insignificant extra-solution activity; MPEP 2106.05(g), the display and output of data is considered insignificant extra-solution activity; an opinion formed in natural language or code is considered a mental process with respect to MPEP 2106.04(a)(2)(III)(A)).
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.
Claim 5 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 5 recites the limitation "the configuration generation LLM." There is insufficient antecedent basis for this limitation in the claim. Claim 1 has been amended to change a “configuration generation LLM” to a “configuration generation coding LLM.” Examiner recommends making a similar amendment to Claim 5, or making it clear if these are separate LLMs.
Claim Rejections - 35 USC § 103
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-2 and 5-20, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Bellam et al. (U.S. Publication No. 2024/0345911 A1), hereinafter referred to as Bellam, in view of Côrte-Real et al. (U.S. Patent No. 12,487,875 B1), hereinafter referred to as Côrte-Real.
With regards to Claim 1, Bellam teaches:
A computer-implemented method comprising (Paragraph 0025, description of the overall method):
obtaining, by an observability tool of a processing platform (Fig. 1; Paragraphs 0090 and 0092), information related to an incident (Paragraphs 0051-0052, data obtained for an anomaly), the information comprising a dynamic state information set and a static state information set (Paragraph 0052, telemetry and event data; Paragraphs 0033-0036, details of what telemetry and event data may include), the dynamic state information set comprising one or more of events, traces, logs, and metrics related to the incident (Paragraphs 0033 and 0037, data used for the analysis includes logs and metrics; Paragraphs 0034-035, description of logs and metrics) and the static state information set comprising one or more of types and numbers of entities within the computing environment and hardware and infrastructure configurations within the computing environment (Paragraphs 0033 and 0037, data used for the analysis includes change events and hardware changes; Paragraph 0036, versions, configurations management, and change events);
summarizing, by a prompt system of the processing platform, the information related to the incident as a textual prompt (Paragraph 0067, diagnostic results are output in the form of a report) using a first machine learning model of a dual machine learning model architecture (Paragraph 0008; Fig. 1, multiple models; Paragraphs 0049, 0051, and 0066, using resources of AI) … question answering … model (Paragraphs 0029-0031, the system can answer questions “in a human-like way”);
and inputting, by the prompt system of the processing platform, the textual prompt into a second machine learning model of the dual machine learning model architecture, wherein the second learning model is a configuration generation coding LLM, such that the second machine learning model, in response, generates an output comprising a resolution to the incident based on at least the dynamic state information set and the static state information set (Paragraph 0067-0068; Paragraph 0070; Fig. 1; Paragraph 0090);
generating, by the processing platform, an automated control signal based on the output from the second machine learning model (Paragraphs 0068, 0070, and 0090);
and sending, by the processing platform, the automated control signal to a system on which the computing environment is hosted to automatically reconfigure the computing environment in response to the control signal (Paragraphs 0068, 0070, and 0090; Paragraph 0030 and Fig. 1);
wherein the computer-implemented method is performed by the processing platform executing program code (Paragraph 0090), the processing platform comprising one or more processing devices, each of the one or more processing devices comprising a processor coupled to a memory (Paragraph 0092).
Bellam does not explicitly teach:
… wherein the first machine learning model is a … large language … (LLM) …
However, Côrte-Real teaches:
summarizing … the information related to the incident as a textual prompt using a first machine learning model of a dual machine learning model architecture, wherein the first machine learning model is a question answering large language model (LLM) (Col. 12, Lines 44-57; Col. 17, Lines 21-33; Col. 30, Lines 3-11);
and inputting … the textual prompt into a second machine learning model of the dual machine learning model architecture, wherein the second machine learning model is a configuration generation coding LLM, such that the second machine learning model, in response, generates an output comprising a resolution to the incident (Col. 30, Lines 3-26; Col. 11, Lines 60-67; Col. 14, Line 61-Col. 15, Line 5) …;
Therefore, it would have been obvious to one of ordinary skill in the art in which said subject matter pertains to, prior to the effective filing date of the claimed invention, implement an LLM as the first model of the method of Bellam, as taught by Côrte-Real, so that the different LLMs can be fine-tuned for different tasks, allowing for better results (Côrte-Real, Col. 20, Lines 23-50). Additionally, both the first model of Bellam and the LLM of Côrte-Real are used for natural language processing (Côrte-Real, Col. 22, Lines 15-26; Bellam, Paragraph 0031).
With regards to Claim 2, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
applying a root cause failure analysis process on the obtained information such that a reduced set of information is generated that relates to a subset of entities within the computing environment (Bellam, Paragraphs 0053-0055, finding the root cause(s)).
With regards to Claim 5, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the configuration generation LLM is trained on historical data, the historical data comprising prior incidents in the computing environment and prior resolutions to the prior incidents in the computing environment (Bellam, Paragraph 0076, knowledge base of prior troubleshooting guides; Bellam, Paragraph 0088).
With regards to Claim 6, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the one or more of events, traces, logs of the dynamic state information set comprise one or more of events, traces, logs, and metrics of a given time window before and after the detection of the incident (Bellam, Paragraphs 0033 and 0037, data used for the analysis includes logs and metrics; Bellam, Paragraphs 0034-0035, description of logs and metrics).
With regards to Claim 7, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the static state information set further comprises one or more of a state of one or more applications in the computing environment, a state of one or more infrastructure components of the computing environment, a configuration of the computing environment, a configuration of one or more entities in the computing environment and one or more resource types of the computing environment (Bellam, Paragraphs 0033 and 0037, data used for the analysis includes change events; Bellam, Paragraph 0036, versions, configurations management, and change events).
With regards to Claim 8, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the incident indicates a potential functional failure of the computing environment (Bellam, Paragraph 0037, monitoring system resources for failure).
With regards to Claim 9, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the incident indicates a potential performance failure of the computing environment (Bellam, Paragraph 0035, performance being monitored to detect a failure; Paragraph 0038, errors related to performance).
With regards to Claim 10, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the resolution to the incident comprises recommended changes to a configuration of the computing environment (Bellam, Paragraph 0068, resolution and changes made; Côrte-Real, Col. 30, Lines 18-26; Côrte-Real, Col. 11, Lines 60-67; Côrte-Real, Col. 14, Line 61-Col. 15, Line 5).
With regards to Claim 11, Bellam in view of Côrte-Real teaches the method of Claim 1 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the output from the second machine learning model is input into the second machine learning model to retrain the second machine learning model with the resolution to the incident (Bellam, Paragraph 0069, solutions reviewed to improve the ML; Bellam, Paragraph 0076, previous solutions stored in the knowledge base), wherein the resolution to the incident comprises at least one remediated configuration (Bellam, Paragraph 0070, TSGs created from existing solutions in the knowledge base).
With regards to Claim 12, Bellam teaches:
A computer system comprising: a processor set (Paragraphs 0092-0093);
a set of one or more computer-readable storage media (Paragraph 0090);
and program instructions, collectively stored in the set of one or more storage media, for causing the processor set to perform computer operations comprising (Paragraph 0090):
Bellam in view of Côrte-Real teaches the remaining limitations. Please see the above rejection of Claim 1 for citations of these limitations, as well as the motivation to combine references in accordance with 35 U.S.C. 103.
All limitations of Claims 13-15 have been addressed in the analyses of Claims 2 and 6-7, respectively. Please see the above rejections for further details.
With regards to Claim 16, Bellam in view of Côrte-Real teaches the system of Claim 12 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the incident indicates at least one of a potential functional failure of the computing environment (Bellam, Paragraph 0037, monitoring system resources for failure) and a potential performance failure of the computing environment (Bellam, Paragraph 0035, performance being monitored to detect a failure; Paragraph 0038, errors related to performance).
With regards to Claim 17, Bellam teaches:
A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by one or more processors to cause the one or more processors to perform computer operations comprising (Paragraph 0090):
Bellam in view of Côrte-Real teaches the remaining limitations. Please see the above rejection of Claim 1 for citations of these limitations, as well as the motivation to combine references in accordance with 35 U.S.C. 103.
All limitations of Claims 18-20 have been addressed in the analyses of Claims 2 and 6-7, respectively. Please see the above rejections for further details.
With regards to Claim 22, Bellam in view of Côrte-Real teaches the method of Claim 10 as referenced above. Bellam in view of Côrte-Real further teaches:
wherein the recommended changes to a configuration of the computing environment comprises one or more configuration remediation recommendations phrased in at least one of natural language or code (Côrte-Real, Col. 14, Line 61-Col. 15, Line 5).
Response to Arguments
Applicant's arguments filed on May 5th, 2026, have been fully considered but they are not persuasive.
The objection to Claim 22 has been withdrawn due to the amendment.
Applicant argues that the claims are eligible under 35 U.S.C. 101 due to reciting an improvement to computer technology. Examiner respectfully disagrees. “An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution … as opposed to merely claiming the idea of a solution.” Additionally, this consideration overlaps with considerations for particular machines and mere instructions to apply an exception (MPEP 2106.05(a)). The claims are still considered “apply it” because the analysis is left to the computer, uses machinery such as machine learning to perform an existing process, and the generality of the application (MPEP 2106.05(f); Applicant’s specification, Paragraphs 0018 and 0022-0023). The solution architecture of putting data into machine learning models is not uniquely tied to issues in computing systems, and the type of incident, the specificity of the solution, and the type of computing environment which experiences the issue are not specified. As previously discussed in other communications, the specification cites “the applicability of a general LLM for use in observability-based configuration remediation” (Paragraph 0061).
Applicant argues that the prior art does not teach the amended features of the claims. As shown above, Bellam in view of Côrte-Real teaches all limitations of the amended claims.
Please see the above rejections for further details.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/G.K.S./Examiner, Art Unit 2113 /BRYCE P BONZO/Supervisory Patent Examiner, Art Unit 2113
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