DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application is being examined under the pre-AIA first to invent provisions.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/08/2023 and 05/07/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 42-62 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In reference to claim 42:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a process
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“A computer-implemented method for building a custom model comprising: registering at least one module;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could register/mentally note at least one module.
“filling a request queue with request information related to the request;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could mentally keep track of request information related to request queue.
“processing at least part of the request based on data assets related to the request;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could process data assets related to the request.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“receiving a request from a user application;” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“triggering the at least one module based on the request information;” is 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 (MPEP 2106.05(f)).
“and building a custom model based on, at least in part, the processing of the at least part of the request.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“receiving a request from a user application;” (well-understood, routine, conventional MPEP 2106.05(d))
“triggering the at least one module based on the request information;” is 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 (MPEP 2106.05(f)).
“and building a custom model based on, at least in part, the processing of the at least part of the request.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 43:
Claim 43 is directed to a judicial exception from claim(s) depended on and does not recite additional elements that integrate the judicial exception into a practical application and amount to significantly more than the judicial exception.
In reference to claim 44:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a process
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer-implemented method of claim 42, further comprising registering at least one second module” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could register/mentally note at least one second module.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“and triggering the at least one second module based on the request information.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“and triggering the at least one second module based on the request information.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 45:
Claim 45 is directed to a judicial exception from claim(s) depended on and does not recite additional elements that integrate the judicial exception into a practical application and amount to significantly more than the judicial exception.
In reference to claim 46:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a process
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer-implemented method of claim 42, wherein filling the request queue with the request information comprises: building a request workflow;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could build a request workflow.
“and adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could add the request workflow to the request.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
No
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
In reference to claim 47:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a process
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer-implemented method of claim 46, wherein the at least one module analyzes the augmented request for the request workflow,” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could analyze the augmented request for request workflow.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“and wherein the at least one module distributes information about required processing managers in the request queue having associated one or more topics.” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“and wherein the at least one module distributes information about required processing managers in the request queue having associated one or more topics.” (well-understood, routine, conventional MPEP 2106.05(d))
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 48:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a process
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer-implemented method of claim 47, wherein a topic of the one or more topics of the augmented request is added or changed depending on a stage in the request workflow,” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could add or changed the topic of the augmented request depending on the stage of the workflow.
“and wherein the at least one module determines that the augmented request relates to at least one processing manager or a group of processing managers based on the added or changed topic being associated with the at least one processing manager or the group of processing managers.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could determine that the augmented request relates to at least one processing manager based on the added or changed topic.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
No
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
In reference to claim 49:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a manufacture
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“registering at least one module;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could register/mentally note at least one module.
“filling a request queue with request information related to the request;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could mentally keep track of request information related to request queue.
“processing at least part of the request based on data assets related to the request;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could process data assets related to the request.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:” is 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 (MPEP 2106.05(f)).
“receiving a request from a user application;” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“triggering the at least one module based on the request information;” is 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 (MPEP 2106.05(f)).
“and building a custom model based on, at least in part, the processing of the at least part of the request.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising:” is 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 (MPEP 2106.05(f)).
“receiving a request from a user application;” (well-understood, routine, conventional MPEP 2106.05(d))
“triggering the at least one module based on the request information;” is 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 (MPEP 2106.05(f)).
“and building a custom model based on, at least in part, the processing of the at least part of the request.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 50:
Claim 50 is directed to a judicial exception from claim(s) depended on and does not recite additional elements that integrate the judicial exception into a practical application and amount to significantly more than the judicial exception.
In reference to claim 51:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a manufacture
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer program product of claim 49, wherein the operations further comprise registering at least one second module” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could register/mentally note at least one second module.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“and triggering the at least one second module based on the request information.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“and triggering the at least one second module based on the request information.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 52:
Claim 52 is directed to a judicial exception from claim(s) depended on and does not recite additional elements that integrate the judicial exception into a practical application and amount to significantly more than the judicial exception.
In reference to claim 53:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a manufacture
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer program product of claim 49, wherein filling the request queue with the request information comprises: building a request workflow;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could build a request workflow.
“and adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could add the request workflow to the request.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
No
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
In reference to claim 54:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a manufacture
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer program product of claim 53, wherein the at least one module analyzes the augmented request for the request workflow,” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could analyze the augmented request for request workflow.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“and wherein the at least one module distributes information about required processing managers in the request queue having associated one or more topics.” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“and wherein the at least one module distributes information about required processing managers in the request queue having associated one or more topics.” (well-understood, routine, conventional MPEP 2106.05(d))
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 55:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a manufacture
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computer program product of claim 54, wherein a topic of the one or more topics of the augmented request is added or changed depending on a stage in the request workflow,” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could add or changed the topic of the augmented request depending on the stage of the workflow.
“and wherein the at least one module determines that the augmented request relates to at least one processing manager or a group of processing managers based on the added or changed topic being associated with the at least one processing manager or the group of processing managers.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could determine that the augmented request relates to at least one processing manager based on the added or changed topic.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
No
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
In reference to claim 56:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a machine
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“registering at least one module;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could register/mentally note at least one module.
“filling a request queue with request information related to the request;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could mentally keep track of request information related to request queue.
“processing at least part of the request based on data assets related to the request;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could process data assets related to the request.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“A computing system including one or more processors and one or more memories configured to perform operations comprising:” is 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 (MPEP 2106.05(f)).
“receiving a request from a user application;” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“triggering the at least one module based on the request information;” is 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 (MPEP 2106.05(f)).
“and building a custom model based on, at least in part, the processing of the at least part of the request.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“A computing system including one or more processors and one or more memories configured to perform operations comprising:” is 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 (MPEP 2106.05(f)).
“receiving a request from a user application;” (well-understood, routine, conventional MPEP 2106.05(d))
“triggering the at least one module based on the request information;” is 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 (MPEP 2106.05(f)).
“and building a custom model based on, at least in part, the processing of the at least part of the request.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 57:
Claim 57 is directed to a judicial exception from claim(s) depended on and does not recite additional elements that integrate the judicial exception into a practical application and amount to significantly more than the judicial exception.
In reference to claim 58:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a machine
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computing system of claim 56, wherein the operations further comprise registering at least one second module” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could register/mentally note at least one second module.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“and triggering the at least one second module based on the request information.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“and triggering the at least one second module based on the request information.” is 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 (MPEP 2106.05(f)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 59:
Claim 59 is directed to a judicial exception from claim(s) depended on and does not recite additional elements that integrate the judicial exception into a practical application and amount to significantly more than the judicial exception.
In reference to claim 60:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a machine
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computing system of claim 56, wherein filling the request queue with the request information comprises: building a request workflow;” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could build a request workflow.
“and adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could add the request workflow to the request.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
No
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
In reference to claim 61:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a machine
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computing system of claim 60, wherein the at least one module analyzes the augmented request for the request workflow,” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could analyze the augmented request for request workflow.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“and wherein the at least one module distributes information about required processing managers in the request queue having associated one or more topics.” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
The claim does not include additional elements that are integrated into a practical application.
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
“and wherein the at least one module distributes information about required processing managers in the request queue having associated one or more topics.” (well-understood, routine, conventional MPEP 2106.05(d))
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 62:
Step 1 - Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is directed to a manufacture
Step 2A Prong 1 - Does the claim recite an abstract idea, law of nature, or natural phenomenon?
“The computing system of claim 61, wherein a topic of the one or more topics of the augmented request is added or changed depending on a stage in the request workflow,” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could add or changed the topic of the augmented request depending on the stage of the workflow.
“and wherein the at least one module determines that the augmented request relates to at least one processing manager or a group of processing managers based on the added or changed topic being associated with the at least one processing manager or the group of processing managers.” which is an abstract idea because it is directed to a mental process, an observation, evaluation, judgement, or opinion. The limitation as drafted, and under a broadest reasonable interpretation, can be performed in the human mind, or by a human using a pen and paper (MPEP 2106.04(a)(2)(Ill)(c)). For example, a person could determine that the augmented request relates to at least one processing manager based on the added or changed topic.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
No
Step 2B - Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 42-62 are rejected under 35 U.S.C. 103 as being unpatentable over Lukas Carullo et al; US 20200272947 A1 filed on Feb 25, 2019 (hereinafter “Carullo”) in view of Prathameshwar Singh et al; US 20160239275 A1 filed on Dec 28, 2015 (hereinafter “Singh”).
Regarding claim 42, Carullo teaches A computer-implemented method for building a custom model comprising: registering at least one module; (Carullo Paragraph 0057; “The orchestrator 720 may manage a plurality of services 710 which are each configured to perform a function of an analytic engine… It should also be appreciated that other services may be provided.” Examiner notes that at least one module (service) is registered/provided to be used)
receiving a request from a user application; (Carullo Paragraph 0046; “the method 500 may be performed by a web server, an asset controller, a server, a cloud platform, a user device, and/or the like. Referring to FIG. 5, in 510, the method may include receiving a request to create a machine learning model for failure mode detection associated with an asset. For example, the request may be a request to create a new model from scratch, a request to modify an existing model that was previously recorded, and the like.” Carullo Paragraph 0066; “the method may include receiving an identification of a machine learning model. For example, the user may select to create a new model or select to train an existing model.” Examiner notes that a request from a user application (user device) is received)
triggering the at least one module based on the request information; (Carullo Paragraph 0066; “the method may include receiving an identification of a machine learning model. For example, the user may select to create a new model or select to train an existing model.” Carullo Paragraph 0067; “the method may include executing a machine learning pipeline which includes a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process. According to various embodiments, the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Examiner notes that request information (request to train model) triggers the at least one module (service))
processing at least part of the request based on data assets related to the request; and (Carullo Fig 2A and Paragraph 0068; “the executing the machine learning pipeline may include triggering, via the orchestration module, sequential execution of a feature collection service, a modeling service, and a score persistence service.” Examiner notes request to train an existing model is based on data assets (Asset Core 211) related to the request (unsupervised training of model))
building a custom model based on, at least in part, the processing of the at least part of the request. (Carullo Paragraph 0046; “the request may be a request to create a new model from scratch, a request to modify an existing model that was previously recorded” Examiner notes that a custom model (new/existing model) is built based on, at least in part, the processing of the at least part of the request)
Carullo does not teach filling a request queue with request information related to the request;
However, Singh does teach filling a request queue with request information related to the request; (Singh Paragraph 0045; “User may further upload the workflow file to a workflow manager 302. Further, the workflow manager 302 may validate and may process the workflow file to host an integrated service, and may expose end points for the workflow. Workflow execution engine may comprise a job scheduler. User may put a request to execute the integrated service. The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that a request queue (queue) is filled with request information related to the request (workflow file))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 43, Carullo teaches The computer-implemented method of claim 42, wherein the request information includes at least one of: a request workflow, a list of one or more required modules, or a topic. (Carullo Paragraph 0017; “a mechanism by which a user can build a machine learning model for failure mode analysis based on their historical data, train the model, validate the model, and score the model to determine its effectiveness.” Carullo Paragraph 0018; “The user interface may also provide information about each topic such as an identification of top keywords of a topic, etc.” Examiner notes that the request information includes a topic)
Regarding claim 44, Carullo teaches The computer-implemented method of claim 42, further comprising registering at least one second module and triggering the at least one second module based on the request information. (Carullo Fig 7 and Paragraph 0056; “Referring to FIG. 7, the orchestrator 720 can manage various pipelines (e.g., pipelines A and B, etc.) for executing processes for training a machine learning model.” Carullo Paragraph 0057; “The orchestrator 720 may manage a plurality of services 710 which are each configured to perform a function of an analytic engine… It should also be appreciated that other services may be provided.” Examiner notes that a second module (Modeler A) is registered/provided and triggered based on the request information (request to train existing model))
Regarding claim 45, Carullo teaches The computer-implemented method of claim 44, wherein the at least one module is at least one processing manager and the at least one second module is at least one request handing agent. (Carullo Fig 7 shows at least module is at least one processing manager (Orchestrator 720) and the at least one second module is at least one request handing agent (711-713))
Regarding claim 46, Carullo teaches The computer-implemented method of claim 42, wherein filling the request queue with the request information comprises: building a request workflow; and (Carullo Fig 7 and Paragraph 0067; “the method may include executing a machine learning pipeline which includes a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process. According to various embodiments, the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Examiner notes that orchestration module builds a request workflow (order of execution of the services/pipeline))
Carullo does not teach adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue.
However, Singh does teach adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue. (Singh Paragraph 0045; “User may further upload the workflow file to a workflow manager 302. Further, the workflow manager 302 may validate and may process the workflow file to host an integrated service, and may expose end points for the workflow. Workflow execution engine may comprise a job scheduler. User may put a request to execute the integrated service. The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that the request workflow (workflow file) is added to the request thereby modifying the request to an augmented request (workflow file is added alongside the request to execute the workflow/integrated service) that is pushed into the request queue (queue))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 47, Carullo teaches The computer-implemented method of claim 46, wherein the at least one module analyzes the augmented request for the request workflow, and wherein the at least one module distributes information about required processing managers [in the request queue] having associated one or more topics. (takes two refs; module is just distributing information Carullo Fig 7 and Paragraph 0067; “the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Carullo Paragraph 0069; “the method 900 may further include outputting, via the orchestration module, a user interface for validating the trained topic model. For example, the user interface may receive feedback from the user for validating and/or changing any of the topic mappings generated during the unsupervised learning by the machine learning pipeline. Furthermore, the completion of the validation may cause the orchestration module to trigger execution of the supervised learning process in response to completion of the unsupervised learning process.” Examiner notes that the at least one module (orchestration module) analyzes the augmented request (user feedback) for the request workflow, and wherein the at least one module distributes information about required processing managers (trigger sequential execution of services) having associated one or more topics (user feedback changes topic mappings))
Carullo does not teach processing managers in the request queue
However, Singh does teach processing managers in the request queue (Singh Paragraph 0045; “The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that the processing managers (services waiting to be executed) is in the request queue (queue))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 48, Carullo teaches The computer-implemented method of claim 47, wherein a topic of the one or more topics of the augmented request is added or changed depending on a stage in the request workflow, (Carullo Paragraph 0065; “the user may change or modify the topic to failure mode mappings, or leave them as is. In 810, the user may submit any changes made to the topics to failure modes mappings. In response, in 812, the analytic engine may transmit the user feedback (including any changes made by the user) to a database associated with the machine learning pipeline. In 814, the user may select to publish the labeled data set based on any changes that are made during the validation. In response, in 816, the analytic engine may perform supervised learning via the machine learning pipeline based on the published data set.” Examiner notes that a topic of the one or more topics of the augmented request is added or changed (user submit changes to the topics) depending on a stage in the request workflow (before or after pipeline))
and wherein the at least one module determines that the augmented request relates to at least one processing manager or a group of processing managers based on the added or changed topic being associated with the at least one processing manager or the group of processing managers. (Carullo Fig 7 and Paragraph 0065; “ the user may change or modify the topic to failure mode mappings, or leave them as is. In 810, the user may submit any changes made to the topics to failure modes mappings… In 814, the user may select to publish the labeled data set based on any changes that are made during the validation. In response, in 816, the analytic engine may perform supervised learning via the machine learning pipeline based on the published data set.” Examiner notes that the at least one module (analytic engine) determines that the augmented request relates to at least one processing manager (Orchestrator 720) based on the changed topic (in response to changes made to the topic, analytic engine uses Orchestrator 720 to perform machine learning pipeline); changed topic is associated with the at least on processing manager (Orchestrator 720) because the changes suggest a supervised learning via the machine learning pipeline)
Regarding claim 49, Carullo teaches A computer program product residing on a computer readable storage medium having a plurality of instructions stored thereon which, when executed across one or more processors, causes at least a portion of the one or more processors to perform operations comprising: (Carullo Paragraph 0071; “The computer programs (also referred to as programs, software, software applications, “apps”, or code) may include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language.”)
registering at least one module; (Carullo Paragraph 0057; “The orchestrator 720 may manage a plurality of services 710 which are each configured to perform a function of an analytic engine… It should also be appreciated that other services may be provided.” Examiner notes that at least one module (service) is registered/provided to be used)
receiving a request from a user application; (Carullo Paragraph 0046; “the method 500 may be performed by a web server, an asset controller, a server, a cloud platform, a user device, and/or the like. Referring to FIG. 5, in 510, the method may include receiving a request to create a machine learning model for failure mode detection associated with an asset. For example, the request may be a request to create a new model from scratch, a request to modify an existing model that was previously recorded, and the like.” Carullo Paragraph 0066; “the method may include receiving an identification of a machine learning model. For example, the user may select to create a new model or select to train an existing model.” Examiner notes that a request from a user application (user device) is received)
triggering the at least one module based on the request information; (Carullo Paragraph 0066; “the method may include receiving an identification of a machine learning model. For example, the user may select to create a new model or select to train an existing model.” Carullo Paragraph 0067; “the method may include executing a machine learning pipeline which includes a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process. According to various embodiments, the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Examiner notes that request information (request to train model) triggers the at least one module (service))
processing at least part of the request based on data assets related to the request; and (Carullo Fig 2A and Paragraph 0068; “the executing the machine learning pipeline may include triggering, via the orchestration module, sequential execution of a feature collection service, a modeling service, and a score persistence service.” Examiner notes request to train an existing model is based on data assets (Asset Core 211) related to the request (unsupervised training of model))
building a custom model based on, at least in part, the processing of the at least part of the request. (Carullo Paragraph 0046; “the request may be a request to create a new model from scratch, a request to modify an existing model that was previously recorded” Examiner notes that a custom model (new/existing model) is built based on, at least in part, the processing of the at least part of the request)
Carullo does not teach filling a request queue with request information related to the request;
However, Singh does teach filling a request queue with request information related to the request; (Singh Paragraph 0045; “User may further upload the workflow file to a workflow manager 302. Further, the workflow manager 302 may validate and may process the workflow file to host an integrated service, and may expose end points for the workflow. Workflow execution engine may comprise a job scheduler. User may put a request to execute the integrated service. The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that a request queue (queue) is filled with request information related to the request (workflow file))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 50, Carullo teaches The computer program product of claim 49, wherein the request information includes at least one of: a request workflow, a list of one or more required modules, or a topic. (Carullo Paragraph 0017; “a mechanism by which a user can build a machine learning model for failure mode analysis based on their historical data, train the model, validate the model, and score the model to determine its effectiveness.” Carullo Paragraph 0018; “The user interface may also provide information about each topic such as an identification of top keywords of a topic, etc.” Examiner notes that the request information includes a topic)
Regarding claim 51, Carullo teaches The computer program product of claim 49, wherein the operations further comprise registering at least one second module and triggering the at least one second module based on the request information. (Carullo Fig 7 and Paragraph 0056; “Referring to FIG. 7, the orchestrator 720 can manage various pipelines (e.g., pipelines A and B, etc.) for executing processes for training a machine learning model.” Carullo Paragraph 0057; “The orchestrator 720 may manage a plurality of services 710 which are each configured to perform a function of an analytic engine… It should also be appreciated that other services may be provided.” Examiner notes that a second module (Modeler A) is registered/provided and triggered based on the request information (request to train existing model))
Regarding claim 52, Carullo teaches The computer program product of claim 51, wherein the at least one module is at least one processing manager and the at least one second module is at least one request handing agent. (Carullo Fig 7 shows at least module is at least one processing manager (Orchestrator 720) and the at least one second module is at least one request handing agent (711-713))
Regarding claim 53, Carullo teaches The computer program product of claim 49, wherein filling the request queue with the request information comprises: building a request workflow; and (Carullo Fig 7 and Paragraph 0067; “the method may include executing a machine learning pipeline which includes a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process. According to various embodiments, the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Examiner notes that orchestration module builds a request workflow (order of execution of the services/pipeline))
Carullo does not teach adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue.
However, Singh does teach adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue. (Singh Paragraph 0045; “User may further upload the workflow file to a workflow manager 302. Further, the workflow manager 302 may validate and may process the workflow file to host an integrated service, and may expose end points for the workflow. Workflow execution engine may comprise a job scheduler. User may put a request to execute the integrated service. The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that the request workflow (workflow file) is added to the request thereby modifying the request to an augmented request (workflow file is added alongside the request to execute the workflow/integrated service) that is pushed into the request queue (queue))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 54, Carullo teaches The computer program product of claim 53, wherein the at least one module analyzes the augmented request for the request workflow, and wherein the at least one module distributes information about required processing managers [in the request queue] having associated one or more topics. (takes two refs; module is just distributing information Carullo Fig 7 and Paragraph 0067; “the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Carullo Paragraph 0069; “the method 900 may further include outputting, via the orchestration module, a user interface for validating the trained topic model. For example, the user interface may receive feedback from the user for validating and/or changing any of the topic mappings generated during the unsupervised learning by the machine learning pipeline. Furthermore, the completion of the validation may cause the orchestration module to trigger execution of the supervised learning process in response to completion of the unsupervised learning process.” Examiner notes that the at least one module (orchestration module) analyzes the augmented request (user feedback) for the request workflow, and wherein the at least one module distributes information about required processing managers (trigger sequential execution of services) having associated one or more topics (user feedback changes topic mappings))
Carullo does not teach processing managers in the request queue
However, Singh does teach processing managers in the request queue (Singh Paragraph 0045; “The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that the processing managers (services waiting to be executed) is in the request queue (queue))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 55, Carullo teaches The computer program product of claim 54, wherein a topic of the one or more topics of the augmented request is added or changed depending on a stage in the request workflow, (Carullo Paragraph 0065; “the user may change or modify the topic to failure mode mappings, or leave them as is. In 810, the user may submit any changes made to the topics to failure modes mappings. In response, in 812, the analytic engine may transmit the user feedback (including any changes made by the user) to a database associated with the machine learning pipeline. In 814, the user may select to publish the labeled data set based on any changes that are made during the validation. In response, in 816, the analytic engine may perform supervised learning via the machine learning pipeline based on the published data set.” Examiner notes that a topic of the one or more topics of the augmented request is added or changed (user submit changes to the topics) depending on a stage in the request workflow (before or after pipeline))
and wherein the at least one module determines that the augmented request relates to at least one processing manager or a group of processing managers based on the added or changed topic being associated with the at least one processing manager or the group of processing managers. (Carullo Fig 7 and Paragraph 0065; “ the user may change or modify the topic to failure mode mappings, or leave them as is. In 810, the user may submit any changes made to the topics to failure modes mappings… In 814, the user may select to publish the labeled data set based on any changes that are made during the validation. In response, in 816, the analytic engine may perform supervised learning via the machine learning pipeline based on the published data set.” Examiner notes that the at least one module (analytic engine) determines that the augmented request relates to at least one processing manager (Orchestrator 720) based on the changed topic (in response to changes made to the topic, analytic engine uses Orchestrator 720 to perform machine learning pipeline); changed topic is associated with the at least on processing manager (Orchestrator 720) because the changes suggest a supervised learning via the machine learning pipeline)
Regarding claim 56, Carullo teaches A computing system including one or more processors and one or more memories configured to perform operations comprising: (Carullo Paragraph 0071; “The computer programs (also referred to as programs, software, software applications, “apps”, or code) may include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language.”)
registering at least one module; (Carullo Paragraph 0057; “The orchestrator 720 may manage a plurality of services 710 which are each configured to perform a function of an analytic engine… It should also be appreciated that other services may be provided.” Examiner notes that at least one module (service) is registered/provided to be used)
receiving a request from a user application; (Carullo Paragraph 0046; “the method 500 may be performed by a web server, an asset controller, a server, a cloud platform, a user device, and/or the like. Referring to FIG. 5, in 510, the method may include receiving a request to create a machine learning model for failure mode detection associated with an asset. For example, the request may be a request to create a new model from scratch, a request to modify an existing model that was previously recorded, and the like.” Carullo Paragraph 0066; “the method may include receiving an identification of a machine learning model. For example, the user may select to create a new model or select to train an existing model.” Examiner notes that a request from a user application (user device) is received)
triggering the at least one module based on the request information; (Carullo Paragraph 0066; “the method may include receiving an identification of a machine learning model. For example, the user may select to create a new model or select to train an existing model.” Carullo Paragraph 0067; “the method may include executing a machine learning pipeline which includes a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process. According to various embodiments, the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Examiner notes that request information (request to train model) triggers the at least one module (service))
processing at least part of the request based on data assets related to the request; and (Carullo Fig 2A and Paragraph 0068; “the executing the machine learning pipeline may include triggering, via the orchestration module, sequential execution of a feature collection service, a modeling service, and a score persistence service.” Examiner notes request to train an existing model is based on data assets (Asset Core 211) related to the request (unsupervised training of model))
building a custom model based on, at least in part, the processing of the at least part of the request. (Carullo Paragraph 0046; “the request may be a request to create a new model from scratch, a request to modify an existing model that was previously recorded” Examiner notes that a custom model (new/existing model) is built based on, at least in part, the processing of the at least part of the request)
Carullo does not teach filling a request queue with request information related to the request;
However, Singh does teach filling a request queue with request information related to the request; (Singh Paragraph 0045; “User may further upload the workflow file to a workflow manager 302. Further, the workflow manager 302 may validate and may process the workflow file to host an integrated service, and may expose end points for the workflow. Workflow execution engine may comprise a job scheduler. User may put a request to execute the integrated service. The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that a request queue (queue) is filled with request information related to the request (workflow file))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 57, Carullo teaches The computing system of claim 56, wherein the request information includes at least one of: a request workflow, a list of one or more required modules, or a topic. (Carullo Paragraph 0017; “a mechanism by which a user can build a machine learning model for failure mode analysis based on their historical data, train the model, validate the model, and score the model to determine its effectiveness.” Carullo Paragraph 0018; “The user interface may also provide information about each topic such as an identification of top keywords of a topic, etc.” Examiner notes that the request information includes a topic)
Regarding claim 58, Carullo teaches The computing system of claim 56, wherein the operations further comprise registering at least one second module and triggering the at least one second module based on the request information. (Carullo Fig 7 and Paragraph 0056; “Referring to FIG. 7, the orchestrator 720 can manage various pipelines (e.g., pipelines A and B, etc.) for executing processes for training a machine learning model.” Carullo Paragraph 0057; “The orchestrator 720 may manage a plurality of services 710 which are each configured to perform a function of an analytic engine… It should also be appreciated that other services may be provided.” Examiner notes that a second module (Modeler A) is registered/provided and triggered based on the request information (request to train existing model))
Regarding claim 59, Carullo teaches The computing system of claim 58, wherein the at least one module is at least one processing manager and the at least one second module is at least one request handing agent. (Carullo Fig 7 shows at least module is at least one processing manager (Orchestrator 720) and the at least one second module is at least one request handing agent (711-713))
Regarding claim 60, Carullo teaches The computing system of claim 56, wherein filling the request queue with the request information comprises: building a request workflow; and (Carullo Fig 7 and Paragraph 0067; “the method may include executing a machine learning pipeline which includes a plurality of services which train the machine learning model via at least one of an unsupervised learning process and a supervised learning process. According to various embodiments, the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Examiner notes that orchestration module builds a request workflow (order of execution of the services/pipeline))
Carullo does not teach adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue.
However, Singh does teach adding the request workflow to the request thereby modifying the request to an augmented request that is pushed into the request queue. (Singh Paragraph 0045; “User may further upload the workflow file to a workflow manager 302. Further, the workflow manager 302 may validate and may process the workflow file to host an integrated service, and may expose end points for the workflow. Workflow execution engine may comprise a job scheduler. User may put a request to execute the integrated service. The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that the request workflow (workflow file) is added to the request thereby modifying the request to an augmented request (workflow file is added alongside the request to execute the workflow/integrated service) that is pushed into the request queue (queue))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 61, Carullo teaches The computing system of claim 60, wherein the at least one module analyzes the augmented request for the request workflow, and wherein the at least one module distributes information about required processing managers [in the request queue] having associated one or more topics. (takes two refs; module is just distributing information Carullo Fig 7 and Paragraph 0067; “the machine learning pipeline may be controlled by an orchestration module that triggers ordered execution of the services.” Carullo Paragraph 0069; “the method 900 may further include outputting, via the orchestration module, a user interface for validating the trained topic model. For example, the user interface may receive feedback from the user for validating and/or changing any of the topic mappings generated during the unsupervised learning by the machine learning pipeline. Furthermore, the completion of the validation may cause the orchestration module to trigger execution of the supervised learning process in response to completion of the unsupervised learning process.” Examiner notes that the at least one module (orchestration module) analyzes the augmented request (user feedback) for the request workflow, and wherein the at least one module distributes information about required processing managers (trigger sequential execution of services) having associated one or more topics (user feedback changes topic mappings))
Carullo does not teach processing managers in the request queue
However, Singh does teach processing managers in the request queue (Singh Paragraph 0045; “The job scheduler may add the request to a queue and schedule request and accordingly execute the workflow file to execute the integrated service.” Examiner notes that the processing managers (services waiting to be executed) is in the request queue (queue))
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Carullo and Singh. Carullo teaches a method for training and validating models in a machine learning pipeline for failure mode analytics.. Singh teaches using a queue to handle execution of services. One of ordinary skill would have motivation to combine Carullo and Singh to utilize a queue to handle executing services in a machine learning pipeline for better resource management and efficiency.
Regarding claim 62, Carullo teaches The computing system of claim 61, wherein a topic of the one or more topics of the augmented request is added or changed depending on a stage in the request workflow, (Carullo Paragraph 0065; “the user may change or modify the topic to failure mode mappings, or leave them as is. In 810, the user may submit any changes made to the topics to failure modes mappings. In response, in 812, the analytic engine may transmit the user feedback (including any changes made by the user) to a database associated with the machine learning pipeline. In 814, the user may select to publish the labeled data set based on any changes that are made during the validation. In response, in 816, the analytic engine may perform supervised learning via the machine learning pipeline based on the published data set.” Examiner notes that a topic of the one or more topics of the augmented request is added or changed (user submit changes to the topics) depending on a stage in the request workflow (before or after pipeline))
and wherein the at least one module determines that the augmented request relates to at least one processing manager or a group of processing managers based on the added or changed topic being associated with the at least one processing manager or the group of processing managers. (Carullo Fig 7 and Paragraph 0065; “ the user may change or modify the topic to failure mode mappings, or leave them as is. In 810, the user may submit any changes made to the topics to failure modes mappings… In 814, the user may select to publish the labeled data set based on any changes that are made during the validation. In response, in 816, the analytic engine may perform supervised learning via the machine learning pipeline based on the published data set.” Examiner notes that the at least one module (analytic engine) determines that the augmented request relates to at least one processing manager (Orchestrator 720) based on the changed topic (in response to changes made to the topic, analytic engine uses Orchestrator 720 to perform machine learning pipeline); changed topic is associated with the at least on processing manager (Orchestrator 720) because the changes suggest a supervised learning via the machine learning pipeline)
Conclusion
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/D.D.T./Examiner, Art Unit 2147
/VIKER A LAMARDO/Supervisory Patent Examiner, Art Unit 2147