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 21-26,29-34,37-40 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) mental processes – concepts performed in the human mind.
Regarding claim 21, with the exception of the recitation of the limitation ‘A computer program product comprising instructions stored on a non-transitory computer-readable storage medium…’, the claim recites mental processes that can be performed in the human mind.
The limitation ‘detect a temporal pattern of component states of the plurality of components, based on the component states; and predict a future application state of the at least one application, based on the temporal pattern of the component states; identify at least one root cause component of the plurality of components and at least one corresponding root cause anomaly that occurs earliest in the service model and for which resolution of the at least one corresponding anomaly would prevent the future application state from occurring’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional element ‘A computer program product comprising instructions stored on a non-transitory computer-readable storage medium…; train at least one unsupervised machine learning algorithm to construct a corresponding anomaly detection model for each component of the plurality of components, wherein a distinct anomaly detection model is trained at each component of the service model using multi-variate performance metrics specific to its respective component; process the performance metrics for each component, using its corresponding anomaly detection model, including processing, at each component of the plurality of components, an output of a preceding anomaly detection model of a preceding component within the service model, to thereby determine component states of the plurality of components’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘receive a data stream of performance metrics characterizing a technology landscape, the technology landscape including at least one application provided by a plurality of components, the at least one application being associated with a service model that provides causal relationships between the plurality of components and the at least one application; modify the at least one root cause component of the plurality of components to resolve the at least one corresponding root cause anomaly and thereby prevent the future application state from occurring’ is directed to adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), in this case mere data gathering.
Regarding claim 22, the limitation ‘receive the data stream of performance metrics including a set of Known Performance Indicators (KPIs) characterizing the plurality of components and the at least one application’ is directed to adding insignificant solution activity to the judicial exception (MPEP 2106.05(g)), in this case data gathering; ‘reduce the set of KPIs by applying a Principal Component Analysis (PCA) to the set of KPIs and thereby obtain a reduced set of KPIs’ is directed to mathematical concepts; and ‘determine the component states and an application state of the at least one application at corresponding timestamps, based on the reduced set of KPIs’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Regarding claim 23, the limitation ‘receive the data stream of performance metrics including reports of user interactions with the at least one application’ is directed to adding insignificant solution activity to the judicial exception (MPEP 2106.05(g)), in this case data gathering; and ‘determine, based on the reports, the component states and an application state of the at least one application at a corresponding timestamp of each report of the reports’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Regarding claim 24, the limitation ‘determine the component states and application states of the at least one application at corresponding timestamps, using each corresponding anomaly detection model’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 25, the limitation ‘apply each component state of the component states, and each application state of the application states, as a label of each corresponding timestamp, to obtain labelled training data’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment; ‘train a supervised machine learning algorithm using the labelled training data, to obtain at least one state prediction model; and predict the future application state, using the at least one state prediction model to classify the temporal pattern of the component states’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 26, the limitation ‘ classify the component states and application states with respect to anomaly thresholds, using each corresponding anomaly detection model’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)); and ‘generate an alert when one or more of the component states or the application states crosses one of the anomaly thresholds’ is directed to adding insignificant solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 29, the limitation ‘predict the future application state of the at least one application, including predicting a bounded time window during which the future application state will occur’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Regarding claim 30, the limitation ‘detect a temporal pattern of application states of the at least one application, based on the performance metrics; and predict the future application state of the at least one application, based on the temporal pattern of application states’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Regarding claim 31, the claim recites mental processes that can be performed in the human mind.
The limitations ‘detecting a temporal pattern of component states of the plurality of components, based on the component states; and predicting a future application state of the at least one application, based on the temporal pattern of the component states; identifying at least one root cause component of the plurality of components and at least one corresponding root cause anomaly that occurs earliest in the service model and for which resolution of the at least one corresponding root cause anomaly would prevent the future application state from occurring’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional element ‘A computer program product comprising instructions stored on a non-transitory computer-readable storage medium…; training at least one unsupervised machine learning algorithm to construct a corresponding anomaly detection model for each component of the plurality of components, wherein a distinct anomaly detection model is trained at each component of the service model using multi-variate performance metrics specific to its respective component; processing the performance metrics for each component, using its corresponding anomaly detection model, including processing, at each component of the plurality of components, an output of a preceding anomaly detection model of a preceding component within the service model, to thereby determine components states of the plurality of components’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘receiving a data stream of performance metrics characterizing a technology landscape, the technology landscape including at least one application provided by a plurality of components, the at least one application being associated with a service model that provides causal relationships between the plurality of components and the at least one application; modifying at least one root cause component of the plurality of components to resolve the at least one corresponding root cause anomaly and thereby prevent the future application state from occurring’ is directed to adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), in this case mere data gathering.
Regarding claim 32, the limitation ‘determining the component states and application states of the at least one application at corresponding timestamps, using each corresponding anomaly detection model’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 33, the limitation ‘applying each component state of the component states, and each application state of the application states, as a label of each corresponding timestamp, to obtain labelled training data’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment; ‘training a supervised machine learning algorithm using the labelled training data, to obtain at least one state prediction model; and predicting the future application state, using the at least one state prediction model to classify the temporal pattern of the component states’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 34, the limitation ‘ classifying the component states and application states with respect to anomaly thresholds, using each corresponding anomaly detection model’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)); and ‘generating an alert when one or more of the component states or the application states crosses one of the anomaly thresholds’ is directed to adding insignificant solution activity to the judicial exception (MPEP 2106.05(g)).
Regarding claim 37, the limitation ‘predicting the future application state of the at least one application, including predicting a bounded time window during which the future application state will occur’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Regarding claim 38, with the exception of the recitation of the limitation ‘at least one memory including instructions; and at least one processor that is operation coupled to the at least one memory…’, the claim recites mental processes that can be performed in the human mind.
The limitation ‘detect a temporal pattern of component states of the plurality of components, based on the component states; and predict a future application state of the at least one application, based on the temporal pattern of the component states; identify at least one root cause component of the plurality of components and at least one corresponding root cause anomaly that occurs earliest in the service model and for which resolution of the at least one corresponding anomaly would prevent the future application state from occurring’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment.
Step 2A: Prong two
This judicial exception is not integrated into a practical application because the additional element ‘at least one memory including instructions; and at least one processor that is operation coupled to the at least one memory; train at least one unsupervised machine learning algorithm to construct a corresponding anomaly detection model for each component of the plurality of components, wherein a distinct anomaly detection model is trained at each component of the service model using multi-variate performance metrics specific to its respective component; process the performance metrics for each component, using its corresponding anomaly detection model, including processing, at each component of the plurality of components, an output of a preceding anomaly detection model of a preceding component within the service model, to thereby determine components states of the plurality of components’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements ‘receive a data stream of performance metrics characterizing a technology landscape, the technology landscape including at least one application provided by a plurality of components, the at least one application being associated with a service model that provides causal relationships between the plurality of components and the at least one application; modify at least one component of the plurality of components to resolve the at least one corresponding anomaly and thereby prevent the future application state from occurring’ is directed to adding insignificant extra-solution activity to the judicial exception (MPEP 2106.05(g)), in this case mere data gathering.
Regarding claim 39, ‘determine the component states and application states of the at least one application at corresponding timestamps, using each corresponding anomaly detection model’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Regarding claim 40, the limitation the limitation ‘apply each component state of the component states, and each application state of the application states, as a label of each corresponding timestamp, to obtain labelled training data’ is a mental process that can be performed by a human based on observation, evaluation, and/or judgment; ‘train a supervised machine learning algorithm using the labelled training data, to obtain at least one state prediction model; and predict the future application state, using the at least one state prediction model to classify the temporal pattern of the component states’ is directed to generic computer components recited at a high-level of generality such that they amount to nothing more than mere instructions to apply the exception using generic computer components (MPEP 2106.05(f)).
Response to Arguments
Applicant’s arguments and amendments have been fully considered. Concerning the 35 USC 101 – abstract idea rejection, the newly added limitations do not integrate the claims into a practical application nor do no provide technical improvements. The additional limitations to training recite the use of a trained machine learning environment without any specification of details pertaining to how the associated machine learning environment is trained and/or how the actual machine learning is performed. Such details would include description of specific algorithms used in training the machine learning model. As currently written, the limitations in the claims describe merely certain data inputted to the machine learning environment and received. There is no indication that the combination of elements solves a technological problem other than merely taking advantage of the inherent advantages of using existing artificial intelligence technology (i.e., machine learning) in its ordinary, off-the-shelf capacity to apply the identified judicial exception. Simply implementing the abstract idea(s) on a general purpose processor or other generic computer component is not a practical application of the abstract idea(s). The identify limitation is still a mental process and the modify limitation is still insignificant extra-solution activity of generically modifying a component that is found to be a root cause of an anomaly.
The reference to Ex parte Carmody and Desjardins have been considered. However, the training is very generically stated concerning how the training is performed.
Conclusion
THIS ACTION IS MADE FINAL. 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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/Yolanda L Wilson/Primary Examiner, Art Unit 2113
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