DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claim 10 is objected to because of the following informalities: it appears the applicant has inadvertently stricken the word “environment” at the end of the claim. Appropriate correction is required.
Claim Rejections - 35 USC § 101
2. 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, 3-11, 13-20
Claims 1, 3-11, 13-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter. The claims fall within at least one of the four categories of patent eligible subject matter. However, the claimed invention is directed to a mental process of collecting data and performing statistical/mathematical concepts without significantly more.
The following is an analysis of the claims regarding subject matter eligibility in accordance with the 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG):
Subject Matter Eligibility Analysis
Step 1: Do the Claims Specify a Statutory Category?
Claims 1, 3-9, 20 describe a method/process, claims 11, 13-19 describe a system, and claim 10 describes a non-transitory computer-readable medium, therefore satisfying Step 1 of the analysis.
Step 2 Analysis for Claims 1-9
Step 2A – Prong 1: Is a Judicial Exception Recited?
Claim 1 recites generating an incident record based on event records, generating a vector based on the record, detecting similar records based on the vector and similar vector, detecting a remediation action, generating an adapted remediation action, and initiating said adapted action. The limitations describe processes that, under their broadest reasonable interpretation, covers performance of the limitations in the human mind but for the recitation of generic computer components (i.e., use of a processor or a generic computer). That is, nothing in the claim elements preclude the steps from practically being performed in the mind. The limitations involve making evaluations of the collected object information in order to determine a pattern and then identify associated problems for that pattern, thereby describing an observation and/or evaluation of data. Such an observation and/or evaluation of data can be performed by a human and recites a mental process. The step of initiating an adapted remediation action can be interpreted as merely creating a trouble ticket, emailing an admin, etc. all which can be done using a computer as a tool via a mental process.
The amended claim recites matter as previously rejected in now canceled claim 2. The examiner interprets this language as merely displaying identified data.
If a claim limitation, under its broadest reasonable interpretation, covers the practical performance of the limitation in the human mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. See the 2019 Revised Patent Subject Matter Eligibility Guidance. Accordingly, the claim recites an abstract idea.
Claims 3-4 recite generating more prompts using a LLM to output data. Without specific details on how the model performs the claimed steps, the examiner interprets this as merely using a high-level, generic model to output data that can be a result of a mental process.
Claims 5-9 recites more mental processes and mathematical concepts. As explained in the October 2019 Update to the 2019 PEG, when determining whether a claim recites a mathematical concept (i.e., mathematical relationships, mathematical formulas or equations, and mathematical calculations), consideration must be given as to whether a claim recites a mathematical concept or merely includes limitations that are based on or involve a mathematical concept.
Claim 20 recites deploying and initiating a remediation action in a cloud environment. The step of initiating an adapted remediation action can be interpreted as merely creating a trouble ticket, emailing an admin, etc. all which can be done using a computer as a tool via a mental process.
If a claim limitation, under its broadest reasonable interpretation, describes the performance of mathematical calculations (even if a formula is not recited in the claim), then it falls within the “Mathematical Concepts” grouping of abstract ideas. See the 2019 Revised Patent Subject Matter Eligibility Guidance. Accordingly, claims 5-9 each recite an abstract idea.
Step 2A – Prong 2: Is the Judicial Exception Integrated into a Practical Application?
Claims 1, 3-9, 20 recite a computing environment and a large language model. Even if the described methods are implemented on a computer, there is no indication that the combination f elements in the claim solves any particular technological problem other than merely taking advantage of the inherent advantages of using existing computer technology in its ordinary, off-the-shelf capacity to apply the identified judicial exceptions. 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 computing environment and models cited in the claim is described at a high level of generality such that it represents no more than mere instructions to apply the judicial exception on a computer (see MPEP 2106.05(f)). This limitation can also be viewed as nothing more than an attempt to generally link the judicial exception to the technological environment of a computer (see MPEP 2106.05(h)).
Claims 1, 3-9, 20 also recite collecting data, generating records and vectors with said data. The claims also recite comparing the data to prior data to generate an adapted remediation action and initiating it. These limitations describe insignificant extra-solution activity pertaining to mere data gathering, generating results, and generically applying a resolution to an identified problem, respectively, without providing any details regarding a specific problem being solved or specific remedial actions being taken. As such, these limitations do not integrate the abstract idea(s) into a practical application.
Claims 3-9 further recite using an LMM and mathematical concepts. 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 applicant has also added claim 20 to recite deploying and initiating a remediation action. The examiner interprets this language as using an equivalent language of “apply it”. See MPEP 2106.04(d)I, “The courts have also identified limitations that did not integrate a judicial exception into a practical application. Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea.” The applicant has also added language of the remediation deployment in a cloud environment. The examiner refers the applicant to the same section of the MPEP, wherein it states “Generally linking the use of a judicial exception to a particular technological environment or field of use.”
Step 2B: Do the Claims Provide an Inventive Concept?
When evaluating whether the claims provide an inventive concept, the presence of any additional elements in the claims need to be considered to determine whether they add “significantly more” than the judicial exception.
In the instant case, as detailed in the analysis for Step 2A-Prong 2, claims 1-9 contain additional elements which require evaluation as to whether they provide an inventive concept to the identified abstract idea. The computing environment and LMM recited in the claim describe a generic computer processor and/or computer components at a high level and do not represent “significantly more” than the judicial exception.
The limitations pertaining to gathering of object information, calculating results, and generically applying a resolution to an identified problem describe insignificant extra-solution activity and are written at a high level in a generic manner without providing any details regarding a specific problem being solved or specific remedial actions being taken. Therefore, these limitations recite no additional elements that would amount to significantly more than the abstract ideas defined in the claim.
Step 2 Analysis for Claims 11-19
Claims 11-, 13-19 contain limitations for a system which are similar to the limitations for the methods specified in claims 1, 3-9, respectively. As such, the analysis under Step 2A – Prong 1, Step 2A – Prong 2, and Step 2B for claims 11, 13-19 is similar to that presented above for claims 1, 3-9.
In light of the above, the limitations in claims 11-19 recite and are directed to an abstract idea and recite no additional elements that would amount to significantly more than the identified abstract ideas(s). Claims 11, 13-19 are therefore not patent eligible.
Step 2 Analysis for Claim 10
Claim 10 contains limitations for a non-transitory computer-readable medium which are similar to the limitations for the methods specified in claims 1, 3-9, respectively. As such, the analysis under Step 2A – Prong 1 and Step 2A – Prong 2 for claim 10 is similar to that presented above for claims 1, 3-9.
Step 2B: Do the Claims Provide an Inventive Concept?
When evaluating whether the claims provide an inventive concept, the presence of any additional elements in the claims need to be considered to determine whether they add “significantly more” than the judicial exception.
Claim 10 contains additional elements which require evaluation as to whether they provide an inventive concept to the identified abstract idea.
Claim 10 recites the additional elements of a storage medium and processors. The computer-readable medium and processors cited in the claim describe generic computer components at a high level and do not represent “significantly more” than the identified judicial exception. The enabling of the processors to troubleshoot a performance problem recites intended use of the claimed limitations and does not represent “significantly more” than the identified judicial exception.
Claim Rejections - 35 USC § 102
3. 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.
4. 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)(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.
5. Claim(s) 1, 3-11, 13-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Wong et al. U.S. Patent Application Publication US2025/0130884A1.
As per claim 1, Wong teaches a method for initiating remediation actions in a computing environment based on similar incident detection, comprising: generating a first incident record, based on correlating plurality of event records to an incident , each event record indicating an event in a computing environment (¶ 0021); generating a first vector based on an index category (¶ 0021) of the first incident record (¶ 0038); detecting a similar incident record based on the first vector and a corresponding vector of the similar incident record (¶ 0038, 0044); detecting a remediation action associated with the similar incident record, the remediation action previously executed in the computing environment (¶ 0048); generating a prompt for a large language model (LLM) which when processed by the LLM outputs (¶ 0048) an adapted remediation action based on data extracted from the first incident record and the detected remediation action (¶ 0054); processing the prompt utilizing the LMM to output the adapted remediation action (¶ 0048, 0054), and initiating the adapted remediation action as a set of computer instructions in the computing environment (¶ 0029-0030).
As per claim 3, Wong teaches the method of claim 1, further comprising: generating the prompt based on a predefined template, the predefined template adapted based on any one of: the generated first incident report, the detected similar incident record, the detected remediation action, an instruction, and any combination thereof (¶ 0048-0049).
As per claim 4, Wong teaches the method of claim 1, further comprising: generating a second prompt for the LLM which when processed by the LLM outputs a textual explanation of the adapted remediation action (¶ 0036, 0049).
As per claim 5, Wong teaches the method of claim 1, further comprising: populating a first index category from the first incident record; and generating the first vector based on the populated first index category (¶ 0021, wherein the applicant’s Specification teaches index attributes as identifiers of the device, as taught by Wong).
As per claim 6, Wong teaches the method of claim 5, further comprising: populating a second index category from the first incident record; generating a second vector based on the populated second index category; detecting the similar incident record further based on the generated second vector and a corresponding second vector of the similar incident record (¶ 0022, wherein the first record attributes are compared to the attributes of the prior records/indexes).
As per claim 7, Wong teaches the method of claim 6, wherein the first vector is adapted by a first weight and the second vector is adapted by a second weight (¶ 0024, 0038).
As per claim 8, Wong teaches the method of claim 6, further comprising: determining a first distance between the first vector and the corresponding vector; and determining second distance between the second vector and the corresponding second vector (¶ 0038).
As per claim 9, Wong teaches the method of claim 8, further comprising: determining that the similar incident record is similar to the generated incident record in response to detecting that the first distance and the second distance are each within a threshold value of a predetermined value (¶ 0041).
As per claim 10, Wong teaches a non-transitory computer-readable medium storing a set of instructions for initiating remediation actions in a computing environment based on similar incident detection, the set of instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to: generate a first incident record, based on correlating a plurality of event records to an incident, each event record indicating an event in a computing environment; generate a first vector based on an index category of the first incident record; detect a similar incident record based on the first vector and a corresponding vector of the similar incident record; detect a remediation action associated with the similar incident record, the remediation action previously executed in the computing environment; generate a prompt for a large language model (LLM) which when processed by the LLM outputs (¶ 0048) an adapted remediation action based on data extracted from the first incident record and the detected remediation action (¶ 0054); process the prompt utilizing the LMM to output the adapted remediation action (¶ 0048, 0054) and initiate the adapted remediation action as a set of computer instructions in the computing environment (¶ 0029-0030, 0021, 0038, 0044, 0048, 0029-0030, see claim 1).
As per claim 11, Wong teaches a system for initiating remediation actions in a computing environment based on similar incident detection comprising: a processing circuitry; a memory, the memory containing instructions that, when executed by the processing circuitry, configure the system to: generate a first incident record, based on correlating plurality of event records to an incident, each event record indicating an event in a computing environment; generate a first vector based on an index category of the first incident record; detect a similar incident record based on the first vector and a corresponding vector of the similar incident record; detect a remediation action associated with the similar incident record, the remediation action previously executed in the computing environment; generate a prompt for a large language model (LLM) which when processed by the LLM outputs (¶ 0048) an adapted remediation action based on data extracted from the first incident record and the detected remediation action (¶ 0054); process the prompt utilizing the LMM to output the adapted remediation action (¶ 0048, 0054) and initiate the adapted remediation action as a set of computer instructions in the computing environment (¶ 0029-0030, 0021, 0038, 0044, 0048, 0029-0030, see claim 1).
As per claim 13, Wong teaches the system of claim 11, wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to: generate the prompt based on a predefined template, the predefined template adapted based on any one of: the generated first incident report, the detected similar incident record, the detected remediation action, an instruction, and any combination thereof (¶ 0048-0049).
As per claim 14, Wong teaches the system of claim 11, wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to: generate a second prompt for the LLM which when processed by the LLM outputs a textual explanation of the adapted remediation action (¶ 0036, 0049).
As per claim 15, Wong teaches the system of claim 11, wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to: populate a first index category from the first incident record; and generate the first vector based on the populated first index category (¶ 0021, see claim 5).
As per claim 16, Wong teaches the system of claim 15, wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to: populate a second index category from the first incident record; generate a second vector based on the populated second index category; and detect the similar incident record further based on the generated second vector and a corresponding second vector of the similar incident record (¶ 0022).
As per claim 17, Wong teaches the system of claim 16, wherein the first vector is adapted by a first weight and the second vector is adapted by a second weight (¶ 0024, 0038).
As per claim 18, Wong teaches the system of claim 16, wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to: determine a first distance between the first vector and the corresponding vector; and determine second distance between the second vector and the corresponding second vector (¶ 0038).
As per claim 19, Wong teaches the system of claim 18, wherein the memory contains further instructions which when executed by the processing circuitry further configure the system to: determine that the similar incident record is similar to the generated incident record in response to detecting that the first distance and the second distance are each within a threshold value of a predetermined value (¶ 0041).
As per claim 20, Wong teaches the method of claim 1, further comprising: deploying a workload configured to receive the adapted remediation action in the computing environment, wherein the computing environment is a cloud computing environment; and initiating the adapted remediation action by the workload in the cloud computing environment (¶ 0054, wherein an adapted remediation action is generated; ¶ 0029, wherein the action is sent to a user; ¶ 0065, wherein the user is in a cloud environment).
Response to Arguments
6. Applicant's arguments filed 3/12/26 have been fully considered but they are not persuasive.
The applicant has argued the examiner has erred in the USC 101 rejection. The examiner respectfully disagrees. In the submitted Remarks, page 2, the applicant has argued the step of initiating a remediation action cannot be interpreted as merely creating a ticket, email an admin, etc., as stated by the examiner in the prior action. The applicant argues the remediation is initiated in a computing environment. The examiner directs the applicant to the MPEP 2106(a)(2)IIIC2, wherein a mental process of can also be performed in a computer environment; that is, the user can use a computer and its environment to initiate a remediation action
The applicant has also argued a human cannot detect similar incidents based on vector representations. The examiner respectfully disagrees. The examiner contends that a human can use vectors to identify values and can also use a computer as a tool to do so, see MPEP2106.04(a)(2)IIIC3.
The applicant also argues the processing of a prompt using a LMM and initiating a remediation action as a set of computer instructions can not achieved via a human. Again, the examiner directs the applicant to the MPEP wherein a mental process can still be achieved using a computer as a tool and also using high-level, generic computing components and the inherent instructions that would be resultant of using such a computer and computing component.
The applicant further argues, page 3 of the Remarks, that the present claims are directed to a technical improvement and practical application of a technical improvement of the networked computing environment. The examiner respectfully disagrees. The examiner contends the claims are not directed to a technical improvement since there are no details of what the incident pertains to or how a remediation action corrects such an incident. As it reads now, the claims are only directed to a generic network computing system and can cover any incident and remediation therein. Generically initiating a remediation to a non-disclosed problem is interpreted as merely an equivalent language to the “apply it” rule. See MPEP 2106.04(d)I, “The courts have also identified limitations that did not integrate a judicial exception into a practical application. Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea.”
The applicant further states the claims describe a restoration a functional state of the computer. The examiner contends that such language is not present. The applicant is urged to place such language in the claims as to actual remediation of a disclosed error as to transform the system.
The applicant has also argued the cited art, Wong, does not teach the claimed limitations. The examiner respectfully disagrees. The applicant argues Wong does not teach generating an incident record based on correlating a plurality of event records. The examiner contends that Wong teaches the generation of an incident records (paragraph 0021, item 140) and this record is correlated with similar incident records. Wong also teaches correlating the current incident with similar incidents to generate an incident cluster, which can also be interpreted as an incident record (¶ 0025).
The applicant also argues Wong does not teach generating a vector based on an index category. The examiner contends Wong does teach the tokenization of the information of the incident record and creates a vector of these tokens (¶ 0038). As for the claimed index category, the examiner presented the interpretation of such in the claim 5 and 6 rejection in the prior action. The current invention specifies in paragraph 0063 of the Specification that index attributes are merely identifiers of the incident. The examiner interprets Wong as teaching this limitation as he teaches the matching of current identifiers to existing incident identifiers. A category of identifiers that are used to correlate could be a time window of the incidents, as taught by Wong.
The applicant also argues Wong does not teach generating an adapted remediation action. The examiner contends that Wong teaches, in paragraph 0054, the fine-tuning of the initial AI model as to the root cause and the mitigation steps of prior mitigation actions. Wong further teaches the initiating of the mitigation steps as presented to an engineer in the form of instructions/code (¶ 0053).
With respect to claims 3, 13, 4 and 14, the applicant has argued that Wong does not a teach a prompt nor a second prompt which outputs a textual explanation of the adapted remediation action. The examiner contends Wong teaches the generation of a prompt in 0048, and a further prompt which includes context information to the user (¶ 0049).
With respect to claims 5, 15, 6, and 16, the applicant has argued that Wong does not teach first and, therefore, not a second category of indices. The examiner refers back to the above argument of Wong teaching multiple identifiers as included in the incident records and used for correlation.
With respect to claims 7 and 17, the applicant has argued that Wong does not teach applying weights on vectors. The examiner maintains that Wong does teach this in paragraph 0024, wherein the clustering system generates weights based on the records and these records include information vectors (¶ 0038).
With respect to claims 8 and 18, the applicant argues Wong does not teach determining distances between vectors. The examiner maintains that Wong does teach this in paragraph 0038 wherein distances are measured between tokenized embeddings which would include the tokens in each vector.
With respect to claims 9 and 19, the applicant has argued that Wong does not teach threshold values when comparing distances, as claimed in claims 8 and 18. The examiner maintains that Wong does teach this claim language in paragraph 0041 wherein distance metrics are compared to a threshold value to determine similarity.
7. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Christopher McCarthy whose telephone number is (571)272-3651. The examiner can normally be reached Monday-Friday 8:30-5:00.
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, 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.
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.
/CHRISTOPHER S MCCARTHY/Primary Examiner, Art Unit 2113