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 .
Specification
The disclosure is objected to because of the following informalities:
Regarding paragraph [0039], the processors are referenced as "402-506" when they should be referenced as "402-406".
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 7, 15, 19 and 20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 7 recites the limitation "an indication of the cause of the drift" in the last line of the claim. There is insufficient antecedent basis for this limitation in the claim. It is unclear as to what “drift” is being referred to as there was no previously recited “drift” in claim 1. For purposes of examination, Examiner has interpreted this instance of “an indication of the cause of the drift” to refer to the “drift” detected in claim 6.
Claim 15 recites the limitation "an indication of the cause of the drift" in the last line of the claim. There is insufficient antecedent basis for this limitation in the claim. It is unclear as to what “drift” is being referred to as there was no previously recited “drift” in claim 9. For purposes of examination, Examiner has interpreted this instance of “an indication of the cause of the drift” to refer to the “drift” detected in claim 14.
Claim 19 recites the limitation "The system of claim 18" in the first line of the claim. There is insufficient antecedent basis for this limitation in the claim. It is unclear as to what “system” is being referred to as there was no previously recited “system” in claim 18. For purposes of examination, Examiner has interpreted this instance of “The system of claim 18” to refer to the “device” detected in claim 18.
Claim 20 recites the limitation "The system of claim 19" in the first line of the claim. There is insufficient antecedent basis for this limitation in the claim. It is unclear as to what “system” is being referred to as there was no previously recited “system” in claim 19. For purposes of examination, Examiner has interpreted this instance of “The system of claim 19” to refer to the “device” detected in claim 19.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Subject Matter Eligibility Analysis Step 1:
Claims 1-8 recite method claims. Claims 9-20 are machine/system/product claims. Therefore, claims 1-20 are directed to one of the four statutory categories of patentable subject matter.
Regarding claim 1:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 1 recites the step:
“generating, …, based on the inputs and the training data, a confidence score indicative of the probability.” (mental process – a user can manually make a prediction with respect to the inputs and the training data; e.g., if a server configuration has performed well in the past, then a prediction can be made that it will perform well in the future)
Thus, claim 1 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 1 recites the additional elements:
“detecting, …, that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
“by at least one processor of an edge computing device,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“providing, …, a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)) (Examiner’s note: high level recitation of trained machine learning model with predetermined data)
“by the at least one processor,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“Inputting, …, settings and configurations associated with the provisioning of the server as inputs to the neural network;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
“by the at least one processor,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“by the at least one processor,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“using the neural network” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
Therefore, claim 1 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 1 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“detecting, …, that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g) in the form of receiving or transmitting data over a network, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
“by at least one processor of an edge computing device,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“providing, …, a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)) (Examiner’s note: high level recitation of trained machine learning model with predetermined data)
“by the at least one processor,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“Inputting, …, settings and configurations associated with the provisioning of the server as inputs to the neural network;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
“by the at least one processor,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“by the at least one processor,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“using the neural network” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
Therefore, claim 1 is subject-matter ineligible.
Regarding Claim 2:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 2 recites
“The method of claim 1,” (mental process – refers to the mental process continued from claim 1.)
Thus, claim 2 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 2 recites the additional element
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) Examiner’s note: High level recitation of settings and configurations comprising all of the settings and configurations for the server.)
Therefore, claim 2 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 2 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) Examiner’s note: High level recitation of settings and configurations comprising all of the settings and configurations for the server.)
Therefore, claim 2 is subject-matter ineligible.
Regarding Claim 3:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 3 recites
“The method of claim 2,” (mental process – refers to the mental process continued from claim 2.)
“further comprising: determining, …, a subset of the settings and the configurations to monitor for the server.” (Mental process – a person can mentally decide what settings and configurations they would like to monitor.)
Thus, claim 3 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 3 recites the additional element
“using the neural network” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 3 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 3 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“using the neural network” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 3 is subject-matter ineligible.
Regarding Claim 4:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 4 recites
“The method of claim 3,” (mental process – refers to the mental process continued from claim 3.)
Thus, claim 4 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 4 recites the additional element
“wherein determining the subset occurs without user selection of the subset.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 4 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 4 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein determining the subset occurs without user selection of the subset.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 4 is subject-matter ineligible.
Regarding Claim 5:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 5 recites
“The method of claim 1,” (mental process – refers to the mental process continued from claim 1.)
“further comprising: determining that the confidence score is below a threshold score;” (mental process – A person can mentally decide that a score is below another score through a simple comparison.)
Thus, claim 5 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 5 recites the additional element
“presenting an indication to a user that the confidence score is below the threshold score.” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 5 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 5 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“presenting an indication to a user that the confidence score is below the threshold score.” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of presenting offers and gathering statistics, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 5 is subject-matter ineligible.
Regarding Claim 6:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 6 recites
“The method of claim 1,” (mental process – refers to the mental process continued from claim 1.)
“determining, based on a comparison of the settings and the configurations to an existing network topology implemented using the edge computing network device, a cause of the drift.” (mental process – a person could reasonably compare two sets of settings and configurations and mentally decide what may have caused a difference)
Thus, claim 6 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 6 recites the additional element
“detecting a drift of the settings or the computing network device compared to threshold performance criteria;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 6 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 6 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“detecting a drift of the settings or the computing network device compared to threshold performance criteria;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 6 is subject-matter ineligible.
Regarding Claim 7:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 7 recites
“The method of claim 1,” (mental process – refers to the mental process continued from claim 1.)
Thus, claim 7 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 7 recites the additional element
“further comprising: presenting, to a user, an indication of the cause of the drift.” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 7 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 7 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“further comprising: presenting, to a user, an indication of the cause of the drift.” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of presenting offers and gathering statistics, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 7 is subject-matter ineligible.
Regarding Claim 8:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 8 recites
“The method of claim 1,” (mental process – refers to the mental process continued from claim 1.)
Thus, claim 8 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 8 recites the additional element
“further comprising: updating, based on the confidence score, criteria with which the neural network is to generate the confidence score.” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 8 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 8 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“further comprising: updating, based on the confidence score, criteria with which the neural network is to generate the confidence score.” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 8 is subject-matter ineligible.
Regarding Claim 9:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 9 recites
“generate, …, based on the inputs and the training data, a confidence score indicative of the probability.” (mental process – a user can manually make a prediction with respect to the inputs and the training data; e.g., if a server configuration has performed well in the past, then a prediction can be made that it will perform well in the future)
Thus, claim 9 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 9 recites the additional element
“at least one processor of the edge computing device coupled to memory of the edge computing device, wherein the at least one processor is configured to:” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“detect that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
“provide a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)) (Examiner’s note: high level recitation of trained machine learning model with predetermined data)
“input settings and configurations associated with the provisioning of the server as inputs to the neural network;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
“using the neural network,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
Therefore, claim 9 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 9 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“at least one processor of the edge computing device coupled to memory of the edge computing device, wherein the at least one processor is configured to:” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“detect that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g) in the form of receiving or transmitting data over a network, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
“provide a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)) (Examiner’s note: high level recitation of trained machine learning model with predetermined data)
“input settings and configurations associated with the provisioning of the server as inputs to the neural network;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
“using the neural network,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
Therefore, claim 9 is subject-matter ineligible.
Regarding Claim 10:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 10 recites
“The system of claim 9,” (mental process – refers to the mental process continued from claim 9.)
Thus, claim 10 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 10 recites the additional element
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) Examiner’s note: High level recitation of settings and configurations comprising all of the settings and configurations for the server.)
Therefore, claim 10 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 10 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) Examiner’s note: High level recitation of settings and configurations comprising all of the settings and configurations for the server.)
Therefore, claim 10 is subject-matter ineligible.
Regarding Claim 11:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 11 recites
“The system of claim 10,” (mental process – refers to the mental process continued from claim 10.)
“determine, …, a subset of the settings and the configurations to monitor for the server.” (Mental process – a person can mentally decide what settings and configurations they would like to monitor.)
Thus, claim 11 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 11 recites the additional element
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“using the neural network,” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 11 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 11 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“using the neural network,” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 11 is subject-matter ineligible.
Regarding Claim 12:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 12 recites
“The system of claim 11,” (mental process – refers to the mental process continued from claim 11.)
Thus, claim 12 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 12 recites the additional element
“wherein to determine the subset occurs without user selection of the subset.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 12 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 12 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein to determine the subset occurs without user selection of the subset.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 12 is subject-matter ineligible.
Regarding Claim 13:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 13 recites
“The system of claim 9,” (mental process – refers to the mental process continued from claim 9.)
“determine that the confidence score is below a threshold score;” (mental process – A person can mentally decide that a score is below another score through a simple comparison.)
Thus, claim 13 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 13 recites the additional element
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“and present an indication to a user that the confidence score is below the threshold score.” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 13 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 13 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“and present an indication to a user that the confidence score is below the threshold score.” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of presenting offers and gathering statistics, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 13 is subject-matter ineligible.
Regarding Claim 14:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 14 recites
“The system of claim 9,” (mental process – refers to the mental process continued from claim 9.)
“determine, based on a comparison of the settings and the configurations to an existing network topology implemented using the edge computing network device, a cause of the drift.” (mental process – a person could reasonably compare two sets of settings and configurations and mentally decide what may have caused a difference)
Thus, claim 14 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 14 recites the additional element
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“detect a drift of the settings or the computing network device compared to threshold performance criteria;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 14 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 14 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“detect a drift of the settings or the computing network device compared to threshold performance criteria;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 14 is subject-matter ineligible.
Regarding Claim 15:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 15 recites
“The system of claim 9,” (mental process – refers to the mental process continued from claim 9.)
Thus, claim 15 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 15 recites the additional element
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“present, to a user, an indication of the cause of the drift.” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 15 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 15 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“present, to a user, an indication of the cause of the drift.” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of presenting offers and gathering statistics, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 15 is subject-matter ineligible.
Regarding Claim 16:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 16 recites
“The system of claim 9,” (mental process – refers to the mental process continued from claim 9.)
Thus, claim 16 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 16 recites the additional element
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“update, based on the confidence score, criteria with which the neural network is to generate the confidence score.” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
Therefore, claim 16 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 16 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“update, based on the confidence score, criteria with which the neural network is to generate the confidence score.” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g)) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
Therefore, claim 16 is subject-matter ineligible.
Regarding Claim 17:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 17 recites
“generate, …, based on the inputs and the training data, a confidence score indicative of the probability.” (mental process – a user can manually make a prediction with respect to the inputs and the training data; e.g., if a server configuration has performed well in the past, then a prediction can be made that it will perform well in the future)
Thus, claim 17 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 17 recites the additional element
“at least one processor coupled to memory, the at least one processor configured to:” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“detect that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
“provide a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)) (Examiner’s note: high level recitation of trained machine learning model with predetermined data)
“input settings and configurations associated with the provisioning of the server as inputs to the neural network;” (This element does not integrate the abstract idea into a practical application because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g))
“using the neural network,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
Therefore, claim 17 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 17 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“at least one processor coupled to memory, the at least one processor configured to:” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
“detect that a server has been provisioned to access a public network cloud using backbone routers of the edge computing device;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g) in the form of receiving or transmitting data over a network, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
“provide a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f)) (Examiner’s note: high level recitation of trained machine learning model with predetermined data)
“input settings and configurations associated with the provisioning of the server as inputs to the neural network;” (This element does not provide significantly more because it amounts to insignificant extra-solution activity to the judicial exception (see MPEP 2106.05(g) in the form of storing and retrieving information, which is well-known, routine, and conventional (see MPEP 2106.05(d)(II)).)
“using the neural network,” (This element does not integrate the abstract idea into a practical application because it amounts to mere “apply it on a computer” (see MPEP 2106.05(f))
Therefore, claim 17 is subject-matter ineligible.
Regarding Claim 18:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 18 recites
“The device of claim 17,” (mental process – refers to the mental process continued from claim 17.)
Thus, claim 18 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 18 recites the additional element
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) Examiner’s note: High level recitation of settings and configurations comprising all of the settings and configurations for the server.)
Therefore, claim 18 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 18 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)) Examiner’s note: High level recitation of settings and configurations comprising all of the settings and configurations for the server.)
Therefore, claim 18 is subject-matter ineligible.
Regarding Claim 19:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 19 recites
“The system of claim 18,” (mental process – refers to the mental process continued from claim 18.)
“determine, …, a subset of the settings and the configurations to monitor for the server.” (Mental process – a person can mentally decide what settings and configurations they would like to monitor.)
Thus, claim 19 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 19 recites the additional element
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“using the neural network,” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 19 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 19 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein the at least one processor is further configured to:” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
“using the neural network,” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 19 is subject-matter ineligible.
Regarding Claim 20:
Subject Matter Eligibility Analysis Step 2A Prong 1:
Claim 20 recites
“The system of claim 19,” (mental process – refers to the mental process continued from claim 11.)
Thus, claim 20 recites an abstract idea.
Subject Matter Eligibility Analysis Step 2A Prong 2:
Claim 20 recites the additional element
“wherein to determine the subset occurs without user selection of the subset.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 20 is not integrated into a practical application.
Subject Matter Eligibility Analysis Step 2B:
The additional elements of claim 20 do not provide significantly more than the abstract idea itself, taken alone and in combination because
“wherein to determine the subset occurs without user selection of the subset.” (Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f))
Therefore, claim 20 is subject-matter ineligible.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1 and 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 2006/0153204 A1) (hereafter referred to as Wang) in view of Portegys et al. (US 2015/0026108 A1)(hereafter referred to as Portegys).
Regarding claim 1, Wang teaches:
“A method for testing servers provisioned in an edge computing device” (Wang Paragraph [0017] “the method comprising [0018] monitoring data packets traversing a first network node, [0019] determining whether at least one first data packet originating from a source node fulfills a predefined criterion”; Paragraph [0073] “The first network node may be, for example, an edge router”; Paragraph [0081] “The monitoring node 81 is in FIG. 8 called an Anti-Virus Monitor Server (AVMS). It is configured to monitor traffic traversing the edge router 41a, especially towards the core network”; Paragraph [0087] “determining fulfillment of a predefined criterion and instructing functionality can be provided in a separate monitoring network node. Alternatively, this functionality can be placed, for example, in the network node which the monitored data packets are traversing. For example, an edge router may be provided with this functionality.”) “the method comprising:”
“detecting, …, that a server has been provisioned to access a public network cloud” (Wang Figures 8 and 9 display a backbone router connected to an edge router (41a in Fig.8 or 41 in Fig. 9) which grants controls access to the internet (Fig. 8’s 11a and the section that says “Internet” in Fig. 9.); Paragraph [0081] “detecting presence of a source node”; Paragraph [0081] “It is evident to a skilled person that data packets typically go in both directions between the sender and the receiver communications devices”) “using backbone routers of the edge computing device;” (Wang Fig. 8 and Fig. 9 displays an Anti-Virus Monitor Server (AVMS)(82) which is connected to a backbone router (42a in Fig.8 and CNBR in the core network of Fig. 9).
Wang does not distinctly disclose:
providing, …, a neural network for evaluating a probability that a performance of the server will satisfy performance criteria, the neural network trained based on training data comprising labeled settings data and feature weights;
inputting, by the at least one processor, settings and configurations associated with the provisioning of the server as inputs to the neural network;
and generating, …, using the neural network, based on the inputs and the training data, a confidence score indicative of the probability.
However, Portegys teaches:
“by at least one processor” (Portegys Paragraph [0008] “An illustrative system may comprise a data store storing load and health measurements, one or more processor, and a memory storing various modules that, when executed by a processor, cause the management of capacity of a plurality of server machines.”)
“providing, by the at least one processor, a neural network for evaluating” (Portegys Paragraph [0064] “The predictor module may use the dynamic neural network to predict (see ref. 311) the health of the system given inputs”) “a probability that a performance of the server will satisfy performance criteria,” (Portegys Paragraph [0052] “In step 402, a computing device 106A may send a value corresponding to a maximum threshold value desired for the health of a system of one or more server machines 106 (e.g., server cloud).” Paragraph [0069] “Meanwhile, in step 418, if the predicted health returned by the predictor module exceeds the preset maximum threshold value, then a resource provisioning module may be sent a request to provision (in step 420) additional resources (e.g., processors, servers, memory, etc.) to the system 106B-106N.”)
“the neural network trained based on training data comprising labeled settings data and feature weights;” (Portegys Paragraph [0064] “The neural network may have been trained using the coupled load-health historical values stored in the data store 128.”)
“inputting, by the at least one processor, settings and configurations associated with the provisioning of the server as inputs to the neural network;” (Portegys Paragraph [0020] “The machine learning may be performed using commercially available products, such as the SNNS product from The University of Stuttgard of Germany The system, which includes a neural network for machine learning, is provided with an identification of inputs and outputs to track, and the system provides correlations between those.”)
and generating, by the at least one processor, using the neural network, based on the inputs and the training data, a confidence score indicative of the probability. (Portegys Paragraph [0020] “Rather than static rules, the machine learning provides dynamic provisioning recommendations with corresponding confidence scores. Based on the data collected/measured by the neural network, the provisioning recommendations will change as well as the confidence scores.”)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang with the techniques of using a neural network to generate a confidence score in order to provide dynamic recommendations rather than static recommendations (Portegys, Paragraph [0020], lines 10-12).
Regarding claim 2, Wang as modified teaches all of the limitations of claim 1.
Wang as modified does not distinctly disclose:
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.”
However, Portegys teaches:
“wherein the settings and the configurations comprise all settings and configurations selected for the server for the provisioning of the server.” (Portegys [0053] – [0054] “the load of the system may be defined as a triple which is (using module 301) the aggregated sums of the processor (e.g., CPU), memory, and I/O consumption rates of all the processes in the system 106B-106N.
In step 408, the measured load and health values may be provided to a learn module 304 installed on a server 106A. The capacity prediction and learning server 106A may include a neural network (or comparable structure) trained, by the learn module, using incoming and stored load and health measurements. The load value provides the input and the health value provides the output for the neural network,”
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang with the techniques of using a neural network to generate a confidence score in order to provide dynamic recommendations rather than static recommendations (Portegys, Paragraph [0020], lines 10-12).
Claim(s) 3 and 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 2006/0153204 A1)(hereafter referred to as Wang) in view of Portegys et al. (US 2015/0026108 A1) (hereafter referred to as Portegys) as applied to claim 2, further in view of Raman et al. (US 2021/0374345 A1) (hereafter referred to as Raman).
Regarding claim 3, Wang as modified teaches all the limitations of claim 2.
Wang as modified does not distinctly disclose:
“further comprising: determining, using the neural network, a subset of the settings and the configurations to monitor for the server.”
However, Raman teaches:
“further comprising: determining, using the neural network, a subset of the settings and the configurations to monitor for the server.” (Raman [0025] “The described techniques also allow for the system to process the inputs in a data efficient, and, therefore, computing resource efficient manner. Specifically, by identifying proper subsets of respective sequences of output tokens generated by the encoder neural networks and by making use of encoder-specific projection layers, the system can generate compact representations of the inputs to provide to a head neural network for generating high-quality network outputs with minimum loss of representational capacity of the information contained within the original inputs.”)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang as modified with the identification of a subset of the settings and the configurations to monitor for the server of Raman to process the input in a resource efficient manner (Raman, Paragraph [0025], lines 1-5).
Regarding claim 4, Wang as modified teaches all the limitations of claim 3.
Wang as modified does not distinctly disclose:
“wherein determining the subset occurs without user selection of the subset.”
However, Raman teaches:
“wherein determining the subset occurs without user selection of the subset.” (Raman [0025] “The described techniques also allow for the system to process the inputs in a data efficient, and, therefore, computing resource efficient manner. Specifically, by identifying proper subsets of respective sequences of output tokens generated by the encoder neural networks and by making use of encoder-specific projection layers, the system can generate compact representations of the inputs to provide to a head neural network for generating high-quality network outputs with minimum loss of representational capacity of the information contained within the original inputs.”)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang as modified with the identification of a subset of the settings and the configurations to monitor for the server of Raman to process the input in a resource efficient manner (Raman, Paragraph [0025], lines 1-5).
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 2006/0153204 A1)(hereafter referred to as Wang) in view of Portegys et al. (US 2015/0026108 A1)(hereafter referred to as Portegys) as applied to claim 1, further in view of Hong et al. (US 2020/0081912 A1) (hereafter referred to as Hong).
Regarding claim 5, Wang as modified teach all the limitations of claim 1.
Wang as modified does not distinctly disclose:
“further comprising: determining that the confidence score is below a threshold score; and presenting an indication to a user that the confidence score is below the threshold score.”
However, Hong teaches
“further comprising: determining that the confidence score is below a threshold score; and presenting an indication to a user that the confidence score is below the threshold score.” (Hong [0047] “If the confidence score is below a threshold, the online system 140 may present the predicted component type on the user interface and request verification of the predicted component type.”)
Before the effective filing date of the invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang as modified with an evaluation of a confidence score compared to a threshold of Hong in order to verify predictions (Hong, Paragraph [0047], lines 29-33)
Claim(s) 6 and 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 2006/0153204 A1)(hereafter referred to as Wang) in view of Portegys et al. (US 2015/0026108)(hereafter referred to as Portegys) as applied to claim 1, further in view of Kumar et al. (US 11,115,272 B1) (hereafter referred to as Kumar).
Regarding claim 6, Wang as modified teaches all the limitations of claim 1.
Wang as modified does not distinctly disclose:
“further comprising: detecting a drift of the settings or the computing network device compared to threshold performance criteria;”
“determining, based on a comparison of the settings and the configurations to an existing network topology implemented using the edge computing network device, a cause of the drift.”
However, Kumar teaches
‘further comprising: detecting a drift of the settings or the computing network device compared to threshold performance criteria;” (Kumar Column 10, lines 48 - 49 ‘In an embodiment, at circle “7,” the infrastructure modeling service 104 performs the drift detection”)
“determining, based on a comparison of the settings and the configurations to an existing network topology implemented using the edge computing network device, a cause of the drift.” (Kumar Column 10, lines 49 - 52 “by comparing the baseline snapshot created at circle “3” to the current snapshot created at circle “6” and determining whether any differences exist”)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang as modified with drift detection of Kumar to provide visibility into configuration changes (Kumar column 5, lines 30-35).
Regarding claim 7, Wang as modified teaches all the limitations of claim 1.
Kumar further teaches
“further comprising: presenting, to a user, an indication of the cause of the drift.” (Kumar Column 10, lines 7-13) “In an embodiment, in response to dynamically detecting that drift has occurred for one or more computing resources of a stack, the infrastructure modeling service 104 may generate a user alert or other type of notification to indicate to a user associated with the computing resource stack that the configuration drift has occurred.”)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang as modified with drift detection of Kumar to provide visibility into configuration changes (Kumar column 5, lines 30-35).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US 2006/0153204 A1)(hereafter referred to as Wang) in view of Portegys et al. (US 2015/0026108)(hereafter referred to as Portegys) as applied to claim 1, in view of Breneisen et al. (US 2017/0007187 A1) (hereafter referred to as Breneisen).
Regarding claim 8, Wang as modified teaches all the limitations of claim 1.
Wang as modified does not distinctly disclose:
“further comprising: updating, based on the confidence score, criteria with which the neural network is to generate the confidence score.”
However, Breneisen teaches
“further comprising: updating, based on the confidence score, criteria with which the neural network is to generate the confidence score.” (Breneisen [0169] “Therefore, a neural network according to the present invention may, in addition to outputting BI-RADS classifications, be configured to produce an initial confidence level, which is then input to an expert system that refines the initial confidence level (e.g., based on the above described scoring and thresholding) to generate a final confidence level.”)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine the method for monitoring and testing within a network of Wang as modified with the use of a confidence score as input of Breneisen to further refine a confidence score (Breneisen Paragraph [0169], lines 14-20).
Regarding claim 9, Wang as modified teaches a system comprising a processor coupled to memory, where the processor executes instructions stored in the memory (Portegys Paragraph [0008] “An illustrative system may comprise a data store storing load and health measurements, one or more processor, and a memory storing various modules that, when executed by a processor, cause the management of capacity of a plurality of server machines.”) to perform the method of claim 1 (see rejection of claim 1) and is therefore rejected under the same analysis.
Regarding claim 10, claim 10 recites substantially similar limitations to claim 2, and is therefore rejected under the same analysis.
Regarding claim 11, claim 11 recites substantially similar limitations to claim 3, and is therefore rejected under the same analysis.
Regarding claim 12, claim 12 recites substantially similar limitations to claim 4, and is therefore rejected under the same analysis.
Regarding claim 13, claim 13 recites substantially similar limitations to claim 5, and is therefore rejected under the same analysis.
Regarding claim 14, claim 14 recites substantially similar limitations to claim 6, and is therefore rejected under the same analysis.
Regarding claim 15, claim 15 recites substantially similar limitations to claim 7, and is therefore rejected under the same analysis.
Regarding claim 16, claim 16 recites substantially similar limitations to claim 8, and is therefore rejected under the same analysis.
Regarding claim 17, see the rejection for claim 9 above. Note the only difference between claim 17 and claim 9 is that claim 17 is directed to the device that carries out the method of claim 1 (i.e. covering the method) whereas claim 9 is directed to the system that carries out the method of claim 1 (i.e. covering the method).
Regarding claim 18, claim 18 recites substantially similar limitations to claim 2, and is therefore rejected under the same analysis.
Regarding claim 19, claim 19 recites substantially similar limitations to claim 3, and is therefore rejected under the same analysis.
Regarding claim 20, claim 20 recites substantially similar limitations to claim 4, and is therefore rejected under the same analysis.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Liu et al. (US 2020/0293914 A1) also discloses a method of using a neural network on an edge computing device.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Peter T Annis whose telephone number is (571)270-1059. The examiner can normally be reached M-F, 7:30am to 5pm ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Alexey Shmatov can be reached at (571) 270-3428. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PETER THOMAS ANNIS/ Examiner, Art Unit 2123
/ALEXEY SHMATOV/ Supervisory Patent Examiner, Art Unit 2123
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