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 03/09/2023, 03/20/2023, and 05/10/2024 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 § 112b
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 3 and 4 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.
Regarding claim 3, the claim recites “The data processing system according to claim 1, wherein, when the input data being abnormal are input, a value of a plurality of values included in the intermediate data that is not selected as the output data falls within a range on which a value included in the output data, when the input data being normal are input, may take.” The language is unclear. For examination purposes, the examiner interprets the claims as abnormal values that fall within a range is not selected.
The term “partially” in claim 4 is a relative term which renders the claim indefinite. The term “partially” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The amount of abnormal data is rendered indefinite by the use of the “partially”.
Dependent claim 5 are also rejected under 112(b) due to inheriting the deficiencies of claim 3 and 4.
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 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 1:
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?
“converting the input data according to a conversion rule;” 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 convert input data by using a conversion rule.
“generating output data by selecting at least one value located in a predetermined position” 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 generate output data by selecting at least one value located in a predetermined position within an array.
“after a predetermined arithmetic operation is performed on the intermediate data” which is an abstract idea because it is directed to a mathematical relationships, mathematical formulas or equations, mathematical calculations. (MPEP 2106.04(a)(2)(l)(c)).
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“A data processing system comprising: a first computer; and a second computer, wherein the first computer comprises: at least one first memory storing first instructions; at least one first processor configured to execute the first instructions to perform first operations, the first 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)).
“acquiring input data formed of a plurality of values,” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“outputting, by processing the input data after conversion, intermediate data formed of a plurality of rows and/or a plurality of columns of data formed of a plurality of value,” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“And wherein the second computer comprises: at least one second memory storing second instructions; at least one second processor configured to execute the second instructions to perform second operations, the second 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)).
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 data processing system comprising: a first computer; and a second computer, wherein the first computer comprises: at least one first memory storing first instructions; at least one first processor configured to execute the first instructions to perform first operations, the first 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)).
“acquiring input data formed of a plurality of values,” (well-understood, routine, conventional MPEP 2106.05(d))
“outputting, by processing the input data after conversion, intermediate data formed of a plurality of rows and/or a plurality of columns of data formed of a plurality of value,” (well-understood, routine, conventional MPEP 2106.05(d))
“And wherein the second computer comprises: at least one second memory storing second instructions; at least one second processor configured to execute the second instructions to perform second operations, the second 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)).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
In reference to claim 2:
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 first operations comprise generating the intermediate data [by using a model generated] by using training data,” 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 generate intermediate data by using training data.
“and the conversion rule is to increase a number of values included in the input data by adding dummy data to the input data.” 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 include dummy data into the input data to increase a number of values included in the input data.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“by using a model generated” 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 data processing system according to claim 1, wherein a plurality of values included in the input data are a result of measuring a state of a target object by indexes different from each other,” (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?
“by using a model generated” 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 data processing system according to claim 1, wherein a plurality of values included in the input data are a result of measuring a state of a target object by indexes different from each other,” (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 4:
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 data processing system according to claim 3, wherein the first operations comprise generating the intermediate data [by using a model generated] by using training data,” 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 generate intermediate data from training data.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“by using a model generated” 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 training data used when the model is generated include first training data formed of normal data, and second training data partially including abnormal data,” 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 the model is generated by repeating, for a plurality of times, a step of being trained by using the first training data, and then being trained by using the second training data after conversion by the conversion rule.” 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?
“by using a model generated” 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 training data used when the model is generated include first training data formed of normal data, and second training data partially including abnormal data,” 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 the model is generated by repeating, for a plurality of times, a step of being trained by using the first training data, and then being trained by using the second training data after conversion by the conversion rule.” 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 5:
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 data processing system according to claim 4, wherein the first training data are used without being converted by the conversion rule.” 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 use first training data without converting it with conversion rule.
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 7:
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 data processing system according to claim1, wherein, when a value that satisfies a predetermined condition is included in the input data, the first operations comprise replacing the value with another value.” 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 a value satisfies a predetermined condition is included in the input data and replace the value with another value.
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 8:
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?
“using the second training data after conversion by the conversion rule.” 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 use training data after performing conversion rule.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“A model generation device that generates a model used by another device, the model generation device comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to perform operations, the 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)).
“acquiring first training data formed of normal data, and second training data partially including abnormal data;” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data [after conversion by the conversion rule.]” 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 model generation device that generates a model used by another device, the model generation device comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to perform operations, the 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)).
“acquiring first training data formed of normal data, and second training data partially including abnormal data;” (well-understood, routine, conventional MPEP 2106.05(d))
“repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data [after conversion by the conversion rule.]” 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 13:
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?
“using the second training data after conversion by the conversion rule.” 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 use training data after performing conversion rule.
Step 2A Prong 2 - Does the claim recite additional elements that integrate the judicial exception into a practical application?
“A non-transitory computer readable medium storing a program for causing a first computer to perform operations to generate a model used by a second computer,” 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 operations comprising: acquiring first training data formed of normal data, and second training data partially including abnormal data;” (insignificant extra-solution activity mere data gathering MPEP 2106.05(g))
“and repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data [after conversion by the conversion rule.]” 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 non-transitory computer readable medium storing a program for causing a first computer to perform operations to generate a model used by a second computer,” 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 operations comprising: acquiring first training data formed of normal data, and second training data partially including abnormal data;” (well-understood, routine, conventional MPEP 2106.05(d))
“and repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data [after conversion by the conversion rule.]” 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.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1 and 2 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Kshitij et al; US 20190044918 A1 (hereinafter “Kshitij”).
Regarding claim 1, Kshitij anticipates A data processing system comprising: a first computer; and a second computer, (Kshitij paragraph 0017; "Edge cloud architectures may have security and data privacy concerns, ... These protection needs may implicitly include memory, pooled memory (for example, by using multi-key total-memory-encryption (MK-TME)), any external device connected to the central processing units (CPU) (e.g., any field programmable gate arrays (FPGA) running inferencing), and the links connected from the CPU." Kshitij Paragraph 0048; "the model may be uploaded into the edge cloud provider infrastructure." Kshitij Paragraph 0055; "The client may be a computing device, which is part of an apparatus, such as a vehicle with an onboard computer." Kshitij Paragraph 0069; "Machine (e.g., computer system) 800 may include a hardware processor 802 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, field programmable gate array (FPGA), or any combination thereof), a main memory 804 and a static memory 806, some or all of which may communicate with each other via an interlink (e.g., bus) 808." Examiner notes that provider is first computer and client is second computer)
wherein the first computer comprises: at least one first memory storing first instructions; at least one first processor configured to execute the first instructions to perform first operations, the first operations comprising: (Kshitij paragraph 0017; "Edge cloud architectures may have security and data privacy concerns, ... These protection needs may implicitly include memory, pooled memory (for example, by using multi-key total-memory-encryption (MK-TME)), any external device connected to the central processing units (CPU) (e.g., any field programmable gate arrays (FPGA) running inferencing), and the links connected from the CPU." Kshitij Paragraph 0048; "the model may be uploaded into the edge cloud provider infrastructure.")
acquiring input data formed of a plurality of values, (Kshitij Paragraph 0036; "the input may be a two-dimensional input of (x, y)." Kshitij Paragraph 0040; "A first transformation β 320 at the client 305, transforms the input 315 to shape [[U″]].sub.n+M 325 that may be specific to a client. Shape [[U″]].sub.n+M 325 is transmitted to the service provider 310 and may be externally observable when transmitted on an unsecure or unencrypted channel." Examiner notes that service provider receives/acquired input data formed of a plurality of values/two dimensional input)
converting the input data according to a conversion rule; (Kshitij paragraph 0040; "The transformation β.sup.−1π 330 is performed to produce [[U′]].sub.n+N 335 for the camouflaged model 340." Examiner notes that transformation is conversion rule that converts the input data)
outputting, by processing the input data after conversion, intermediate data formed of a plurality of rows and/or a plurality of columns of data formed of a plurality of value, (Kshitij Paragraph 0036; "the transformed variation of the input may be (a, b, y, c, x, d)" Kshitij paragraph 0040; "the result of the second transformation, is not visible, nor is it possible to reverse engineer it as it is then processed by the camouflage model 340… The camouflage model produces the output {V′}.sub.k+K 345, which is transformed by the server side hidden transformation ϕθ.sup.−1 350." Examiner notes that camouflage model processes the input data after conversion and outputs intermediate data/output 345 formed of a plurality of rows of data formed of a plurality of value/(a, b, y, c, x, d);)
And wherein the second computer comprises: at least one second memory storing second instructions; at least one second processor configured to execute the second instructions to perform second operations, the second operations comprising: (Kshitij Paragraph 0055; "The client may be a computing device, which is part of an apparatus, such as a vehicle with an onboard computer." Kshitij Paragraph 0069; "Machine (e.g., computer system) 800 may include a hardware processor 802 (e.g., a central processing unit (CPU), a graphics processing unit (GPU), a hardware processor core, field programmable gate array (FPGA), or any combination thereof), a main memory 804 and a static memory 806, some or all of which may communicate with each other via an interlink (e.g., bus) 808." Examiner notes that client is second computer)
generating output data by selecting at least one value located in a predetermined position after a predetermined arithmetic operation is performed on the intermediate data (Kshitij Paragraph 0036; "The transformation may include performing rotations and scaling to the input values. The transformation may include performing rotations and scaling to the input values. Thus, the transformed variation of the input may be (a, b, y, c, x, d), where a, b, c, and d are fake input values." Kshitij Paragraph 0041; "The client may use transformation 0 365 to transform output {V″}.sub.k+J 360 to {V}.sub.k 370 for use by the client 305. Thus, while {V″}.sub.k+J 360 may be externally observable, the data is useless without the transformation θ 365." Examiner notes that output data/370 is generated by selecting at least one value located in a predetermined position after a predetermined arithmetic operation is performed on the intermediate data/transformation 365; transformation is used to undo the scaling and remove dummy data to get/select at least on value located in a predetermined position; rotations and scaling/predetermined arithmetic operation is performed before selecting on the intermediate data)
Regarding claim 2, Kshitij anticipates The data processing system according to claim 1, wherein a plurality of values included in the input data are a result of measuring a state of a target object by indexes different from each other, (Kshitij Paragraph 0038; "The application collects data, such as from sensors of the mobile device, to send as input to the camouflaged model at the service provider." Examiner notes that input data are a result of measuring a state of target object/collects data by indexes different from each other/such as from sensors; plurality of sensors indicates different indexes of measurement)
the first operations comprise generating the intermediate data by using a model generated by using training data, (Kshitij Paragraph 0039; "the camouflaged model is trained using the transformed input, and thus for training or inference, needs transformed input data." Examiner notes that camouflaged model/model is generated/trained by using training data/inputs;)
and the conversion rule is to increase a number of values included in the input data by adding dummy data to the input data. (Kshitij Paragraph 0036; "Thus, the transformed variation of the input may be (a, b, y, c, x, d), where a, b, c, and d are fake input values." Examiner notes that conversion rule/transformation includes adding dummy data/fake input values to the input data to increase a number of values included in the input data)
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) 3 is rejected under 35 U.S.C. 103 as being unpatentable over Kshitij et al; US 20190044918 A1 (hereinafter “Kshitij”) in view of Koichi et al; US 20170337449 A1 (hereinafter “Koichi”).
Regarding claim 3, Kshitij does not teach The data processing system according to claim 1, wherein, when the input data being abnormal are input, a value of a plurality of values included in the intermediate data that is not selected as the output data falls within a range on which a value included in the output data, when the input data being normal are input, may take.
However, Koichi does teach The data processing system according to claim 1, wherein, when the input data being abnormal are input, a value of a plurality of values included in the intermediate data that is not selected as the output data falls within a range on which a value included in the output data, when the input data being normal are input, may take. (Koichi Paragraph 0042; "Nevertheless, since the output values of this sixth layer have a threshold from −∞ to ∞, to put that threshold within a specific range, a sigmoid function can be used to put the output values within a range of from 0 to 1. A sigmoid layer 160 (seventh layer) can have output values between 0 and 1 by applying the sigmoid function indicated by the solid line in FIG. 5." Koichi Paragraph 0044; "After going through the sigmoid layer 160, then, the similarity between a plurality of images is determined at an approximation/distance comparison layer 170, based on a conversion output value in which the output value ranges from 0 to 1." Examiner notes that when the input data being abnormal are input/output of sixth layer that has a range of -INF to INF for distance comparison layer; distance comparison layer does not select intermediate data/data not within 0 and 1 as the output data falls within a range on which a value included in the output data, when the input data being normal input, may take/0 and 1)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Kshitij and Koichi. Kshitij teaches systems and techniques for AI model and data camouflaging for cloud edge. Koichi teaches using sigmoid layer to fit data within a range of values. One of ordinary skill would have motivation to combine Kshitij and Koichi to set out values between 0 and 1 to allow for easy and efficient comparisons “Setting the output value to be between 0 and 1 by going through a sigmoid layer at this stage allows the subsequent approximation or comparison of distance scale to be carried out easily and efficiently.” (Koichi Paragraph 0043).
Claim(s) 4, 5, 8, and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Kshitij et al; US 20190044918 A1 (hereinafter “Kshitij”) in view of Dongdong et al; US 20150092978 A1 (hereinafter “Dongdong”).
Regarding claim 4, Kshitij teaches The data processing system according to claim 3, wherein the first operations comprise generating the intermediate data by using a model generated by using training data, (Kshitij Paragraph 0039; "the camouflaged model is trained using the transformed input, and thus for training or inference, needs transformed input data." Kshitij Paragraph 0041; "The camouflage model produces the output {V′}.sub.k+K 345, which is transformed by the server side hidden transformation ϕθ.sup.−1 350." Examiner notes camouflage model/model is generated/trained by using training data/transformed input data; camouflage model produces/generates output 345/intermediate data)
using the first training data, and then being trained by using the second training data after conversion by the conversion rule. (Kshitij paragraph 0040; "The transformation β.sup.−1π 330 is performed to produce [[U′]].sub.n+N 335 for the camouflaged model 340." Examiner notes that transformation is conversion rule that converts the training data)
Kshitij does not teach the training data used when the model is generated include first training data formed of normal data, and second training data partially including abnormal data,
and the model is generated by repeating, for a plurality of times, a step of being trained by using the first training data, and then being trained by using the second training data after conversion by the conversion rule.
However, Dongdong does teach the training data used when the model is generated include first training data formed of normal data, and second training data partially including abnormal data, (Dongdong Paragraph 0018; "the incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior" Dongdong Paragraph 0040; "the template database can include one or more sets of "normal" behavior datasets and one or more "abnormal" behavior datasets depending on use, settings, and/or subjects." Examiner notes that normal behavior dataset is first training data formed of normal data and abnormal behavior dataset is second training data partially including abnormal data; abnormal behavior classifier/model is generated from training data sets)
and the model is generated by repeating, for a plurality of times, a step of being trained by using the first training data, and then being trained by using the second training data [after conversion by the conversion rule]. (Dongdong Paragraph 0018; "the incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior" Examiner notes that classifier/model is generated by repeating/retraining, for a plurality of times, a step of being train by using the first training data/include newly identified normal behavior, and then being trained by using the second training data/newly identified abnormal behavior)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Kshitij and Dongdong. Kshitij teaches systems and techniques for AI model and data camouflaging for cloud edge. Dongdong teaches training a model with normal and abnormal behavior datasets. One of ordinary skill would have motivation to combine Kshitij and Dongdong to retrain a classifier to include newly identified normal and abnormal behavior “to include newly identified normal and/or abnormal behavior and corresponding features and/or identified features of the newly identified normal and/or abnormal behavior, respectively.” (Dongdong Paragraph 0018).
Regarding claim 5, Kshitij does not teach The data processing system according to claim 4, wherein the first training data are used without being converted by the conversion rule.
However, Dongdong does teach The data processing system according to claim 4, wherein the first training data are used without being converted by the conversion rule. (Dongdong Paragraph 0018; "the incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior" Examiner notes that the classifier is trained with first training data without being converted by the conversion rule/modified)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Kshitij and Dongdong. Kshitij teaches systems and techniques for AI model and data camouflaging for cloud edge. Dongdong teaches training a model with normal and abnormal behavior datasets. One of ordinary skill would have motivation to combine Kshitij and Dongdong to retrain a classifier to include newly identified normal and abnormal behavior “to include newly identified normal and/or abnormal behavior and corresponding features and/or identified features of the newly identified normal and/or abnormal behavior, respectively.” (Dongdong Paragraph 0018).
Regarding claim 8, Kshitij teaches A model generation device that generates a model used by another device, the model generation device comprising: at least one memory configured to store instructions; and at least one processor configured to execute the instructions to perform operations, the operations comprising: (Kshitij paragraph 0017; "Edge cloud architectures may have security and data privacy concerns, ... These protection needs may implicitly include memory, pooled memory (for example, by using multi-key total-memory-encryption (MK-TME)), any external device connected to the central processing units (CPU) (e.g., any field programmable gate arrays (FPGA) running inferencing), and the links connected from the CPU." Kshitij Paragraph 0048; "the model may be uploaded into the edge cloud provider infrastructure." Examiner notes that model generation device/provider generates a model used by another device/client device; provider device contains memory configured to store instructions and a processor configured to execute the instructions to perform operations)
using the first training data, and then being trained by using the second training data after conversion by the conversion rule. (Kshitij paragraph 0040; "The transformation β.sup.−1π 330 is performed to produce [[U′]].sub.n+N 335 for the camouflaged model 340." Examiner notes that transformation is conversion rule that converts the training data)
Kshitij does not teach acquiring first training data formed of normal data, and second training data partially including abnormal data;
And repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data after conversion by the conversion rule.
However, Dongdong does teach acquiring first training data formed of normal data, and second training data partially including abnormal data; (Dongdong Paragraph 0018; “incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior and corresponding features and/or identified features of the newly identified normal and/or abnormal behavior, respectively.” Dongdong Paragraph 0040; "the template database can include one or more sets of "normal" behavior datasets and one or more "abnormal" behavior datasets depending on use, settings, and/or subjects." Examiner notes that first training data formed of normal data/normal behavior datasets and second training data partially including abnormal data/abnormal behavior datasets is acquired from database)
And repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data [after conversion by the conversion rule.] (Dongdong Paragraph 0018; "the incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior" Examiner notes that classifier/model is generated by repeating/retraining, for a plurality of times, a step of being train by using the first training data/include newly identified normal behavior, and then being trained by using the second training data/newly identified abnormal behavior)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Kshitij and Dongdong. Kshitij teaches systems and techniques for AI model and data camouflaging for cloud edge. Dongdong teaches training a model with normal and abnormal behavior datasets. One of ordinary skill would have motivation to combine Kshitij and Dongdong to retrain a classifier to include newly identified normal and abnormal behavior “to include newly identified normal and/or abnormal behavior and corresponding features and/or identified features of the newly identified normal and/or abnormal behavior, respectively.” (Dongdong Paragraph 0018).
Regarding claim 13, Kshitij teaches A non-transitory computer readable medium storing a program for causing a first computer to perform operations to generate a model used by a second computer, the operations comprising: (Kshitij paragraph 0017; "Edge cloud architectures may have security and data privacy concerns, ... These protection needs may implicitly include memory, pooled memory (for example, by using multi-key total-memory-encryption (MK-TME)), any external device connected to the central processing units (CPU) (e.g., any field programmable gate arrays (FPGA) running inferencing), and the links connected from the CPU." Kshitij Paragraph 0048; "the model may be uploaded into the edge cloud provider infrastructure." Examiner notes that first computer/provider generates a model used by a second computer/client device;)
using the first training data, and then training by using the second training data after conversion by the conversion rule. (Kshitij paragraph 0040; "The transformation β.sup.−1π 330 is performed to produce [[U′]].sub.n+N 335 for the camouflaged model 340." Examiner notes that transformation is conversion rule that converts the training data)
Kshitij does not teach acquiring first training data formed of normal data, and second training data partially including abnormal data;
And repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data after conversion by the conversion rule.
However, Dongdong does teach acquiring first training data formed of normal data, and second training data partially including abnormal data; (Dongdong Paragraph 0018; “incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior and corresponding features and/or identified features of the newly identified normal and/or abnormal behavior, respectively.” Dongdong Paragraph 0040; "the template database can include one or more sets of "normal" behavior datasets and one or more "abnormal" behavior datasets depending on use, settings, and/or subjects." Examiner notes that first training data formed of normal data/normal behavior datasets and second training data partially including abnormal data/abnormal behavior datasets is acquired from database)
And repeating, for a plurality of times, a step of training the model by using the first training data, and then training by using the second training data [after conversion by the conversion rule.] (Dongdong Paragraph 0018; "the incremental hierarchy module 140 can be configured to build an abnormal behavior classifiers (or database) by retraining or clustering the updated database to include newly identified normal and/or abnormal behavior" Examiner notes that classifier/model is generated by repeating/retraining, for a plurality of times, a step of being train by using the first training data/include newly identified normal behavior, and then being trained by using the second training data/newly identified abnormal behavior)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Kshitij and Dongdong. Kshitij teaches systems and techniques for AI model and data camouflaging for cloud edge. Dongdong teaches training a model with normal and abnormal behavior datasets. One of ordinary skill would have motivation to combine Kshitij and Dongdong to retrain a classifier to include newly identified normal and abnormal behavior “to include newly identified normal and/or abnormal behavior and corresponding features and/or identified features of the newly identified normal and/or abnormal behavior, respectively.” (Dongdong Paragraph 0018).
Claim(s) 6 is rejected under 35 U.S.C. 103 as being unpatentable over Kshitij et al; US 20190044918 A1 (hereinafter “Kshitij”) in view of Tim et al; US 20200164763 A1 (hereinafter “Tim”).
Regarding claim 6, Kshitij does not teach The data processing system according to claim2, wherein the target object is a secondary battery.
However, Tim does teach The data processing system according to claim2, wherein the target object is a secondary battery. (Tim Paragraph 0015; "The battery sensor data includes such things as a battery's existing temperature, pressure and voltage." Examiner notes that target object is a secondary battery)
It would have obvious to one of ordinary skill in the art before the effective filing date of the present application to combine Kshitij and Tim. Kshitij teaches systems and techniques for AI model and data camouflaging for cloud edge. Tim teaches a battery management system for estimating the state of a rechargeable battery. One of ordinary skill would have motivation to combine Kshitij and Tim to collect a variety of factors to have a more accurate estimation of state of battery “Knowledge about a state of the battery during use is, of course, critical to widespread acceptance of electric vehicles as a reliable source for transportation. However, the existing metrics used to determine such quantities as a battery's state of charge (SOC) are often inaccurate, especially as a battery ages.” (Tim Paragraph 0004).
Claim(s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Kshitij et al; US 20190044918 A1 (hereinafter “Kshitij”) in view of Martin et al; US 20110249187 A1 (hereinafter “Martin”).
Regarding claim 7, Kshitij does not teach The data processing system according to clai