DETAILED ACTION
This action is in response to the filing on 03/31/2023. Claims 1-20, are pending and have been considered below.
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:
Para. 56, last line, recites “etc.0.”, should recite -- etc.). --.
Appropriate correction is required.
Claim Objections
Claims 2, 4-6, 10, 12-14, 18, and 20 objected to because of the following informalities:
Claim 2, last line, recites "the first recover point", should recite -- the first recovery point --.
Claim 4, line 2, recites "a temporal ordering the", should recite -- a temporal ordering of the --.
Claim 5, line 2, recites "the first previous of the inference model", should recite -- the first previous version of the inference model --.
Claim 6, lines 1-2, recites "the second previous of the inference model", should recite -- the second previous version of the inference model --.
Claim 10, last line, recites "the first recover point", should recite -- the first recovery point --.
Claim 12, lines 2-3, recites "a temporal ordering the", should recite -- a temporal ordering of the --.
Claim 13, lines 2-3, recites "the first previous of the inference model", should recite -- the first previous version of the inference model --.
Claim 14, lines 2, recites "the second previous of the inference model", should recite -- the second previous version of the inference model --.
Claim 18, last line, recites "the first recover point", should recite -- the first recovery point --.
Claim 20, line 2, recites "a temporal ordering the", should recite -- a temporal ordering of the --.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1, 9, and 17 rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 9, and 17 of U.S. Patent No. 12,306,936 B2 (hereinafter Pat’936) in view of Kapoor et al. US 2007/0185922 A1 (hereinafter Kapoor).
Regarding independent claim 1 in the table below, the left side contains claim 1 of the instant application while the right side contains claim 1 of Pat’396 in view of Kapoor.
18/193,805 (Instant Application)
U.S. 12,306,936 B2 (Pat’936)
(Claim 1) A method for managing inference models, the method comprising:
identifying an inference model of the inference models that is compromised;
identifying a first resource cost for reverting the inference model to an uncompromised state and second resource cost for reverting the inference model to a partially compromised state;
obtaining a reversion plan for the inference model using a graphical user interface based at least in part on the first resource cost and the second resource cost;
performing the reversion plan to obtain an updated inference model; and
using the updated inference model to provide computer implemented services.
(Claim 1) A method for managing inference models, the method comprising:
identifying an inference model of the inference models that is tainted through training using poisoned training data;
identifying a first resource cost for reverting the tainted inference model to remove influence of the poisoned training data on the tainted inference model;
obtaining, using a graphical user interface, user input indicating a selection of a portion of the poisoned training data;
identifying a second resource cost for reverting the tainted inference model to remove influence of the portion of the poisoned training data on the tainted inference model;
obtaining a reversion plan for the tainted inference model based on the second resource cost;
(Kapoor)
(Claim 1)
…
performing the reversion plan to obtain an updated inference model; and
using the updated inference model to provide computer implemented services.
Instant application claim 1’s limitation of “identifying an inference model of the inference models that is compromised” is obvious in view of Pat’396 claim 1’s recitation of “identifying an inference model of the inference models that is tainted through training using poisoned training data” because an inference model that is tainted by poisoned training data is a compromised inference model, though it is compromised in a specific manner as opposed to broadly compromised as recited in the instant application.
Instant application claim 1’s limitation of “identifying a first resource cost for reverting the inference model to an uncompromised state and second resource cost for reverting the inference model to a partially compromised state“ is obvious in view of Pat’396 claim 1’s recitation of “identifying a first resource cost for reverting the tainted inference model to remove influence of the poisoned training data on the tainted inference model” because reverting the inference model to remove influence of the poisoned training data is effectively analogous to reverting to an uncompromised state as the model is compromised by poisoned training data as explained above, thus, the first resource cost are the same, and Pat’396 claim 1’s recitation of “identifying a second resource cost for reverting the tainted inference model to remove influence of the portion of the poisoned training data on the tainted inference model” because reverting the inference model to remove influence of a portion of poisoned training data is effectively analogous to reverting to a partially compromised state as the inference model is compromised by poisoned training data as explained above, thus, the second resource cost are the same.
Further, in the same field of endeavor of managing data systems by restoring to a previous state, Kapoor discloses a database backup/restore system that can perform a restore operation on a database to restore the database to a previous state corresponding to a previous backup operation or an intermediate state after the backup operation and before the restore operation [see Kapoor, para. 37-40 and FIG. 3A], and further discloses obtaining a reversion plan using a graphical user interface based at least in part on a plurality of reversion states [see Kapoor, para. 48-60 and FIGS. 4A-4C].
Accordingly, It would have been obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate a database backup/restore system that can perform a restore operation on a database to restore the database to a previous state corresponding to a previous backup operation or an intermediate state after the backup operation and before the restore operation. It would have been obvious to do so because Pat’396 recites identifying a first resource cost for reverting the tainted inference model to remove influence of the poisoned training data on the tainted inference model, which in combination with the disclosure of Kapoor could identify a first resource cost for reverting an inference model to a backup state, and claim 1 of Pat’396 further recites identifying a second resource cost for reverting the tainted inference model to remove influence of the portion of the poisoned training data on the tainted inference model, which in combination with the disclosure of Kapoor could identify a second resource cost for reverting an inference model to an intermediate state after the backup state and before the restore operation. Further, it would have been obvious to incorporate obtaining a reversion plan using a graphical user interface based at least in part on a plurality of reversion states to teach “obtaining a reversion plan for the inference model using a graphical user interface based at least in part on the first resource cost and the second resource cost” because the combination of Pat’396 and Kapoor would identify the first and second resource cost for reverting to a backup state or an intermediate state as explained above, thus, in combination with the GUI of Kapoor, the reversion plan for the inference model would be obtained using a graphical user interface based at least in part of the first resource cost and second resource cost. It would have been desirable to do so because when an unintentional loss or corruption of data is identified by a user, it would be desirable to allow the user to restore the database to the database state that existed just prior to the unintentional loss or corruption of data [see Kapoor, para. 6], the same desire would be present for inference models such that when an unintentional loss or corruption of data of data is identified by a user, it would be desirable to allow the user to restore the inference model to a state that existed just prior to the unintentional loss or corruption of data.
Therefore, although claim 1 of the instant application is not identical to claim 1 of Pat’396, claim 1 of the instant application is not patently distinct from and is obvious in light of claim 1 of Pat’396 in view of Kapoor.
Regarding instant application claim 9, this is a manufacture claim that recites similar subject matter as the combination of Claim 9 of Pat’396 in view of Kapoor for similar reasons as instant application claim 1. Thus, instant application claim 9 is rejected on the ground of nonstatutory obvious-type double patenting over claim 9 of Pat’396 in view of Kapoor.
Regarding instant application claim 17, this is a manufacture claim that recites similar subject matter as the combination of Claim 17 of Pat’396 in view of Kapoor for similar reasons as instant application claim 1. Thus, instant application claim 17 is rejected on the ground of nonstatutory obvious-type double patenting over claim 17 of Pat’396 in view of Kapoor.
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.
Independent Claims 1, 9, and 17
Step 1:
Claims 1, 9, and 17 recite a method, manufacture, and system, respectively; therefore, they are directed to one of the four categories of statutory subject matter (process/method, machine/product/apparatus, manufacture, or composition of matter).
Step 2A Prong 1:
Claims 1, 9, and 17 recite a method, manufacture, and system comprising:
a method for managing inference models, the method comprising: — Under its broadest reasonable interpretation, this limitation encompasses the abstract idea of a mental process, or a concept that can be performed in the human mind with the use of a physical aid (e.g. pen and paper), including observation, evaluation, judgement or opinion (see MPEP § 2106.04(a)(2)(III)).
identifying an inference model of the inference models that is compromised — Under its broadest reasonable interpretation, this limitation encompasses the abstract idea of a mental process, or a concept that can be performed in the human mind with the use of a physical aid (e.g. pen and paper), including observation, evaluation, judgement or opinion (see MPEP § 2106.04(a)(2)(III)).
identifying a first resource cost for reverting the inference model to an uncompromised state and second resource cost for reverting the inference model to a partially compromised state — Under its broadest reasonable interpretation, this limitation encompasses the abstract idea of a mental process, or a concept that can be performed in the human mind with the use of a physical aid (e.g. pen and paper), including observation, evaluation, judgement or opinion (see MPEP § 2106.04(a)(2)(III)). Or a mathematical concept (see MPEP § 2106.04(a)(2)(I)), specifically organizing information and manipulating information through mathematical correlations.
obtaining a reversion plan for the inference model based at least in part on the first resource cost and the second resource cost — Under its broadest reasonable interpretation, this limitation encompasses the abstract idea of a mental process, or a concept that can be performed in the human mind with the use of a physical aid (e.g. pen and paper), including observation, evaluation, judgement or opinion (see MPEP § 2106.04(a)(2)(III)). Or a mathematical concept (see MPEP § 2106.04(a)(2)(I)), specifically organizing information and manipulating information through mathematical correlations.
Step 2A Prong 2:
This judicial exception is not integrated into a practical application.
Claim 1 recites the additional elements of:
using a graphical user interface — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a graphical user interface. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces).
performing the reversion plan to obtain an updated inference model — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to reverting an inference model.
using the updated inference model to provide computer implemented services — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer-implemented services.
Claim 9 recites the additional elements of:
A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for managing for managing inference models, the operations comprising — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer components.
using a graphical user interface — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a graphical user interface. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces).
performing the reversion plan to obtain an updated inference model — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to reverting an inference model.
using the updated inference model to provide computer implemented services — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer-implemented services.
Claim 17 recites the additional elements of:
A data processing system, comprising: a processor; and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing data collection for managed devices and unmanaged devices, the operations comprising — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a generic computer with generic computer components.
using a graphical user interface — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a graphical user interface. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces).
performing the reversion plan to obtain an updated inference model — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to reverting an inference model.
using the updated inference model to provide computer implemented services — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer-implemented services.
Step 2B:
The claims do not contain significantly more than the judicial exception.
Claim 1 recites the additional elements of:
using a graphical user interface — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a graphical user interface. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces).
performing the reversion plan to obtain an updated inference model — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to reverting an inference model.
using the updated inference model to provide computer implemented services — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer-implemented services.
Claim 9 recites the additional elements of:
A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for managing for managing inference models, the operations comprising — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer components.
using a graphical user interface — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a graphical user interface. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces).
performing the reversion plan to obtain an updated inference model — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to reverting an inference model.
using the updated inference model to provide computer implemented services — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer-implemented services.
Claim 17 recites the additional elements of:
A data processing system, comprising: a processor; and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing data collection for managed devices and unmanaged devices, the operations comprising — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a generic computer with generic computer components.
using a graphical user interface — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a graphical user interface. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces).
performing the reversion plan to obtain an updated inference model — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to reverting an inference model.
using the updated inference model to provide computer implemented services — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to generic computer-implemented services.
As such claims 1, 9, and 17 are not patent eligible.
Dependent Claims 2-8, 10-16, and 18-20
Step 1:
Claims 2-8, 10-16, and 18-20 recite a method, manufacture, and system, respectively; therefore, they are directed to one of the four categories of statutory subject matter (process/method, machine/product/apparatus, manufacture, or composition of matter).
Step 2A Prong 1:
Claims 2-8, 10-16, and 18-20 merely narrow the previously cited abstract idea limitations. For the reasons described above with respect to independent claims 1, 9, and 17, this judicial exception is not meaningfully integrated into a practical application, or significantly more than the abstract idea. The claim(s) disclose similar limitations described for the independent claim(s) above and do not provide anything more than the abstract idea.
Claims 2, 10, and 18 recite a method, manufacture, and system comprising:
obtaining, from the user and to define the reversion plan, user input indicating a selection of the first recover point or the second recovery point — Under its broadest reasonable interpretation, this limitation encompasses the abstract idea of a mental process, or a concept that can be performed in the human mind with the use of a physical aid (e.g. pen and paper), including observation, evaluation, judgement or opinion (see MPEP § 2106.04(a)(2)(III)).
Step 2A Prong 2:
This judicial exception is not integrated into a practical application.
Claims 2, 10, and 18 recite the additional elements of:
wherein obtaining the reversion plan comprises: presenting, to a user, the graphical user interface comprising: a range bar, a model indicator positioned with the range bar, a first recovery point positioned with the range bar, and a second recovery point positioned with the range bar — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to particular graphical user interface elements. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces, and pg. 4, Section 2, discloses that a user interface may differ from one application to another depending upon the developer).
Claims 3, 11, and 19 recite the additional element of:
wherein the first recovery point is based on a first previous version of the inference model in the uncompromised state, and the second recovery point is based on a second previous version of the inference model in the compromised state — This element amounts to no more than selecting a particular data source or type of data to be manipulated, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 4, 12, and 20 recite the additional element of:
wherein the first recovery point and the second recovery point are positioned with the range bar based on a temporal ordering the first previous version of the inference model, the second previous version of the inference model, and the inference model — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 3, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 5 and 13 recite the additional element of:
wherein the second previous version of the inference model is a further trained version of the first previous of the inference model based on a first portion of poisoned training data — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 4, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 6 and 14 recite the additional element of:
wherein the inference model is a further trained version of the second previous of the inference model based on a second portion of poisoned training data — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 5, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 7 and 15 recite the additional elements of:
wherein the graphical user interface further comprises: a compromise indicator positioned with the range bar — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a particular GUI element. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces, and pg. 4, Section 2, discloses that a user interface may differ from one application to another depending upon the developer).
the compromise indicator being based on the first portion of the poisoned training data and the second portion of the poisoned training data — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 6, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 8 and 16 recite the additional elements of:
wherein the graphical user interface further comprises: a reversion cost estimate indicator that indicates a computing resource cost for reverting the inference model to previous versions of the inference model based on the user input; and a reversion time estimate indicator that indicates a duration of time for reverting the inference model to the previous versions of the inference model based on the user input — This element amounts to no more than selecting a particular data source or type of data to be manipulated, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces, and pg. 4, Section 2, discloses that a user interface may differ from one application to another depending upon the developer).
Step 2B:
The claims do not contain significantly more than the judicial exception.
Claims 2, 10, and 18 recite the additional elements of:
wherein obtaining the reversion plan comprises: presenting, to a user, the graphical user interface comprising: a range bar, a model indicator positioned with the range bar, a first recovery point positioned with the range bar, and a second recovery point positioned with the range bar — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to particular graphical user interface elements. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces, and pg. 4, Section 2, discloses that a user interface may differ from one application to another depending upon the developer).
Claims 3, 11, and 19 recite the additional element of:
wherein the first recovery point is based on a first previous version of the inference model in the uncompromised state, and the second recovery point is based on a second previous version of the inference model in the compromised state — This element amounts to no more than selecting a particular data source or type of data to be manipulated, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 4, 12, and 20 recite the additional element of:
wherein the first recovery point and the second recovery point are positioned with the range bar based on a temporal ordering the first previous version of the inference model, the second previous version of the inference model, and the inference model — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 3, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 5 and 13 recite the additional element of:
wherein the second previous version of the inference model is a further trained version of the first previous of the inference model based on a first portion of poisoned training data — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 4, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 6 and 14 recite the additional element of:
wherein the inference model is a further trained version of the second previous of the inference model based on a second portion of poisoned training data — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 5, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 7 and 15 recite the additional elements of:
wherein the graphical user interface further comprises: a compromise indicator positioned with the range bar — This element amounts to no more than generally linking the use of a judicial exception to a particular technological environment or field of use (see MPEP § 2106.05(h)). This element merely limits the use of the abstract idea to a particular GUI element. And is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces, and pg. 4, Section 2, discloses that a user interface may differ from one application to another depending upon the developer).
the compromise indicator being based on the first portion of the poisoned training data and the second portion of the poisoned training data — This element amounts to no more than furthering the insignificant extra solution activity recited in claim 6, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) similar to a court recognized well-understood, routine, and conventional element in MPEP 2106.05(d)(II), specifically: arranging a hierarchy of groups, sorting information, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1331, 115 USPQ2d 1681, 1699 (Fed. Cir. 2015).
Claims 8 and 16 recite the additional elements of:
wherein the graphical user interface further comprises: a reversion cost estimate indicator that indicates a computing resource cost for reverting the inference model to previous versions of the inference model based on the user input; and a reversion time estimate indicator that indicates a duration of time for reverting the inference model to the previous versions of the inference model based on the user input — This element amounts to no more than selecting a particular data source or type of data to be manipulated, and is well-understood, routine, and conventional activity analyzed per MPEP 2106.05(d) in light of Sherrick (An Introduction to Graphical User Interfaces and Their Use by CITIS, published July 1992; pg. 6, Section B “Why Use GUIs?”, discloses GUIs are preferred over character-mode interfaces, and pg. 4, Section 2, discloses that a user interface may differ from one application to another depending upon the developer).
As such claims 2-8, 10-16, and 18-20 are not patent eligible.
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.
Claims 1, 9, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki (US 2021/0352190 A1), hereinafter Suzuki, in view of Kapoor et al. (US 2007/0185922 A1), hereinafter Kapoor, and further in view of Manley et al. (US 2023/0185674 A1), hereinafter Manley.
Regarding claim 1, Suzuki teaches a method for managing inference models, the method comprising: (An information processing apparatus and a method of controlling the information processing apparatus are provided. The information processing apparatus stores a plurality of learned models, determines whether the stored plurality of learned models include confidential information, and presents, to a user, learned models of the plurality of learned models determined to include the confidential information. [see Suzuki, Abstract]):
identifying an inference model of the inference models that is compromised (Suzuki discloses determining if the learned models include confidential information [see Suzuki, Abstract], and that models with confidential information are at risk of leaking the confidential information [see Suzuki, para. 5]);
obtaining a reversion plan for the inference model using a graphical user interface (Suzuki discloses a GUI presented to the user to confirm whether all displayed models can be cleared [see Suzuki, para. 81 and FIG. 13B]);
performing the reversion plan to obtain an updated inference model (Suzuki discloses a GUI presented to the user to confirm whether all displayed models can be cleared, and clearing the models upon confirmation [see Suzuki, para. 81 and FIG. 13B]);
using the updated inference model to provide computer implemented services (Suzuki discloses using the learned model for estimation processing [see Suzuki, para. 51] and notifying the user before using the model that it may contain confidential information to be extracted [see para. 29 and FIG. 15B]. Thus, the cleared model can be used for the estimation processing).
However, Suzuki fails to teach identifying a first resource cost for reverting the inference model to an uncompromised state and second resource cost for reverting the inference model to a partially compromised state; and obtaining a reversion plan for the inference model using a graphical user interface based at least in part on the first resource cost and the second resource cost.
In the same field of endeavor, Kapoor teaches:
identifying a first point for reverting a database to a fully restored state and second point for reverting a database to a partially restored state (Kapoor discloses a plurality of database states in which the database can be restored to, including the last backup operation, and any of states 316-320 which occur after one or more transactions after the backup operation [see Kapoor, para. 37-38 and FIG. 3A]. Kapoor further discloses how the database can be restored to the last backup operation, or any of the points in between the backup operation and the restore operation [see Kapoor, para. 39-40 and FIG. 3A]);
obtaining a reversion plan for a database using a graphical user interface based at least in part on the first point and the second point (Kapoor discloses a plurality of database states in which the database can be restored to, including the last backup operation, and any of states 316-320 which occur after one or more transactions after the backup operation [see Kapoor, para. 37-38 and FIG. 3A]. Kapoor further discloses how the database can be restored to the last backup operation, or any of the points in between the backup operation and the restore operation [see Kapoor, para. 39-40 and FIG. 3A]. Kapoor further discloses GUIs which the user can interact with to obtain the restore plan for the database [see Kapoor, para. 46 and FIGS. 4A-4C]);
It would have been obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate identifying a first point for reverting a database to a fully restored state and second point for reverting a database to a partially restored state as suggested in Kapoor into Suzuki to teach identifying a first point for reverting the inference model to an uncompromised state and second point for reverting the inference model to a partially compromised state because the database backup and restore methodology of Kapoor could be incorporated into the method of resetting learned models described in Suzuki such that the backup and restore methodology can be applied to learned models. Thus, the combination of Suzuki and Kapoor would identify for a learning model [see Suzuki, Abstract], a plurality of points in which the learned model can be restored to, including the last backup operation, and any of one or more intermediate states between the last backup operation and the restore operation [see Kapoor, para. 37-40 and FIG. 3A]. Further, when transactions between the backup operation and the restore operation [see Kapoor, para. 37-40 and FIG. 3A] contain confidential information that can be extracted [see Suzuki, para. 75 and FIG. 11], the learned model can be restored to the last backup operation such that it contains no confidential information that can be extracted, or restored to a point between the backup operation and the restore operation that contains a portion of the confidential information that can be extracted.
It would have been further obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate obtaining a reversion plan for a database using a graphical user interface based at least in part on the first point and the second point as suggested in Kapoor into Suzuki to teach obtaining a reversion plan for the inference model using a graphical user interface based at least in part on the first point and the second point because the database backup and restore methodology of Kapoor could be incorporated into the method of resetting learned models described in Suzuki such that the backup and restore methodology can be applied to learned models. Thus, the restore plan obtained through the GUIs disclosed by Kapoor [see Kapoor, para. 37-40, 46, and FIGS. 3A-4C] could be used to restore the inference model of Suzuki based on the plurality of points.
It would have been obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate the teachings of Kapoor into Suzuki because both methods control information processing systems (see Suzuki, Abstract; see Kapoor, Abstract). Incorporating the teaching of Kapoor into Suzuki would provide the functionality to store data of various types and contain data of every file type [see Kapoor, para. 24] and automatically formulate the command set necessary to restore to the state that existed at the specified point in time without any effort on the part of the user to determine which backup versions need to be restored [see Kapoor, para. 76].
However, the combination of Suzuki and Kapoor fails to teach identifying a first resource cost for reverting the inference model to an uncompromised state and second resource cost for reverting the inference model to a partially compromised state; and obtaining a reversion plan for the inference model using a graphical user interface based at least in part on the first resource cost and the second resource cost.
In the same field of endeavor, Manley teaches:
identifying a resource cost for reverting the data (Manley discloses a time estimator configured to estimate the time taken to restore backup data to a restore location [see Manley, Abstract]);
obtaining a reversion plan for the data using a graphical user interface based at least in part on the resource cost (Manley discloses presenting the estimated time for restoring the backup data to the user [see Manley, para. 53] and generating an optimal schedule for restoring data using the time estimation [see Manley, para. 54]).
It would have been obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate identifying a resource cost for reverting the data as suggested in Manley into the combination of Suzuki and Kapoor to teach identifying a first resource cost for reverting the inference model to an uncompromised state and second resource cost for reverting the inference model to a partially compromised state because it would have been obvious to further combine the combination of Suzuki and Kapoor as indicated above, with the time estimation of Manley to estimate the time taken to restore for each of the plurality of points in the backup/restore methodology of Kapoor on the inference model of Suzuki.
It would have been further obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate text as suggested in Manley into the combination of Suzuki and Kapoor to teach obtaining a reversion plan for the inference model using a graphical user interface based at least in part on the first resource cost and the second resource cost because it would have been obvious to one of ordinary skill in the art before the effective filing date to further combine the combination of Suzuki and Kapoor as indicated above, with the time estimation of Manley to estimate the time taken to restore for each of the plurality of points in the backup/restore methodology of Kapoor on the inference model of Suzuki. Further, the combination could present the time estimation of restoring the backup to a point [see Manley, para. 53] for each point between the backup operation and the restore operation including the backup point itself [see Kapoor, para. 37-40, 46, and FIGS. 3A-4C], for obtaining the restoration plan.
It would have been obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate the teachings of Manley into the combination of Suzuki and Kapoor because both systems are directed to data backups and restore operations (see Kapoor, Abstract; see Manley, Abstract). Incorporating the teaching of Manley into the combination of Suzuki and Kapoor would optimize scheduling of a data backup and/or restore of a backup data in a data backup and/or restore environment (see Manley, para. 5).
Regarding claim 9, claim 9 contains substantially similar limitations to those found in claim 1. Therefore it is rejected for the same reason as claim 1 above. Additionally, the combination of Suzuki, Kapoor, and Manley further teaches:
A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for managing for managing inference models, the operations comprising (Suzuki discloses that the present invention can be realized by instructions on a non-transitory computer-readable storage medium [see Suzuki, para. 96]).
Regarding claim 17, claim 17 contains substantially similar limitations to those found in claim 1. Therefore it is rejected for the same reason as claim 1 above. Additionally, the combination of Suzuki, Kapoor, and Manley further teaches:
A data processing system, comprising: a processor; and a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing data collection for managed devices and unmanaged devices, the operations comprising (Suzuki discloses that the present invention can be realized by instructions on a non-transitory computer-readable storage medium [see Suzuki, para. 96]).
Claims 2-8, 10-16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki (US 2021/0352190 A1), hereinafter Suzuki, in view of Kapoor et al. (US 2007/0185922 A1), hereinafter Kapoor, and further in view of Manley et al. (US 2023/0185674 A1), hereinafter Manley, as applied in claim 1 above, and further in view of Kochar et al. (US 2021/0357297 A1), hereinafter Kochar.
Regarding claim 2, the combination of Suzuki, Kapoor, and Manley as applied in claim 1 above teaches all the limitations of claim 1 and further teaches:
wherein obtaining the reversion plan comprises: presenting, to a user, the graphical user interface comprising: (Suzuki discloses a GUI presented to the user to confirm whether all displayed models can be cleared [see Suzuki, para. 81 and FIG. 13B]).
a first recovery point and a second recovery point (Kapoor discloses a plurality of database states in which the database can be restored to, including the last backup operation, and any of states 316-320 which occur after one or more transactions after the backup operation [see Kapoor, para. 37-38 and FIG. 3A]);
obtaining, from the user and to define the reversion plan, user input indicating a selection of the first recover point or the second recovery point (Kapoor discloses a plurality of database states in which the database can be restored to, including the last backup operation, and any of states 316-320 which occur after one or more transactions after the backup operation [see Kapoor, para. 37-38 and FIG. 3A]. Kapoor further discloses how the database can be restored to the last backup operation, or any of the points in between the backup operation and the restore operation [see Kapoor, para. 39-40 and FIG. 3A]. Kapoor further discloses GUIs which the user can interact with to obtain the restore plan for the database [see Kapoor, para. 46 and FIGS. 4A-4C]).
However, the combination of Suzuki, Kapoor, and Manley fails to teach a range bar, a model indicator positioned with the range bar, a first recovery point positioned with the range bar, and a second recovery point positioned with the range bar.
In the same field of endeavor, Kochar teaches:
a range bar (Kochar discloses a timeline presenting recoverable ranges on the UI [see Kochar, para. 17, and timeline 200A of FIG. 5]);
a first recovery point positioned with the range bar (Kochar discloses the UI having a plurality of points in time that correspond with the state of the database at that point in time [see Kochar, para. 28 and FIG. 2], and the UI having a timeline indicating restoration availability [see Kochar, para. 36 and FIG. 5]);
a second recovery point positioned with the range bar ([Kochar discloses the UI having a plurality of points in time that correspond with the state of the database at that point in time [see Kochar, para. 28 and FIG. 2], and the UI having a timeline indicating restoration availability [see Kochar, para. 36 and FIG. 5]]).
It would have been obvious to one of ordinary skill, in the art at the time before the effective filing date of the invention to incorporate a range bar as suggested in Kochar into the combination of Suzuki, Kapoor, and Manley to teach a model indicator positioned with the range bar (It would have been obvious to one of ordinary skill in the art before the effective filing date that when viewing the timeline disclosed by Kochar [see Kochar, para. 28 and 36, and FIG. 5], it could range from the most recent backup operation to the current restore operation as disclosed for the timeline in Kapoor [see Kapoor, para. 37 and FIG. 3A], the restore operation indicating where the model currently is in the timeline.) and to further incorporate a first recovery point positioned with the range bar, and a second recovery point positioned with the range bar as suggested in Kochar into the combination of Suzuki, Kapoor, and Manley because both methods provide GUIs for performing restore operations (see Kapoor, Abstract; see Kochar, Abstract). Incorporating the teaching of Kochar into the combination of Suzuki, Kapoor, and Manley would provide ease of use for users derived from having a visual representation of recoverability (see Kochar, para. 14).
Regarding claim 3, the combination of Suzuki, Kapoor, Manley, and Kochar as applied in claim 2 above teaches all the limitations of claim 2 and further teaches:
wherein the first recovery point is based on a first previous version of the inference model in the uncompromised state, and the second recovery point is based on a second previous version of the inference model in the compromised state (The combination of Suzuki and Kapoor would identify for a learning model [see Suzuki, Abstract], a plurality of points in which the learned model can be restored to, including the last backup operation, and any of one or more inbetween states between the last backup operation and the restore operation [see Kapoor, para. 37-40 and FIG. 3A]. Further, when transactions between the backup operation and the restore operation [see Kapoor, para. 37-40 and FIG. 3A] contain confidential information that can be extracted [see Suzuki, para. 75 and FIG. 11], the learned model can be restored to the last backup operation such that it contains no confidential information that can be extracted, or restored to a point between the backup operation and the restore operation that contains a portion of the confidential information that can be extracted. Further, when combined with the timeline UI including the recovery points of Kochar [see Kochar para. 28 and 36, and FIGS. 2 and 5], would include recovery points corresponding to versions of the inference model corresponding to states including no confidential information and states including confidential information).
Regarding claim 4, the combination of Suzuki, Kapoor, Manley, and Kochar as applied in claim 3 above teaches all the limitations of claim 3 and further teaches:
wherein the first recovery point and the second recovery point are positioned with the range bar based on a temporal ordering the first previous version of the inference model, the second previous version of the inference model, and the inference model (Kochar discloses the timeline presenting a plurality of recovery points corresponding to versions at that point in time, with Version 2 at a point in time subsequent to Version 1 [see Kochar, para. 28 and FIG. 2]. Thus, the combination of Suzuki and Kochar would present point in time points temporally ordered for the inference models of Suzuki).
Regarding claim 5, the combination of Suzuki, Kapoor, Manley, and Kochar as applied in claim 4 above teaches all the limitations of claim 4 and further teaches:
wherein the second previous version of the inference model is a further trained version of the first previous of the inference model based on a first portion of poisoned training data (Kapoor discloses a plurality of states that can be restored to, including the last backup operation, and any of states 316-320 which occur after one or more transactions after the backup operation [see Kapoor, para. 37-38 and FIG. 3A]. Kapoor further discloses how they can restore to the last backup operation, or any of the points in between the backup operation and the restore operation [see Kapoor, para. 39-40 and FIG. 3A]. Thus, when combined with the inference model of Suzuki, the states would be successive states of the inference model when new data is introduced).
Regarding claim 6, the combination of Suzuki, Kapoor, Manley, and Kochar as applied in claim 5 above teaches all the limitations of claim 5 and further teaches:
wherein the inference model is a further trained version of the second previous of the inference model based on a second portion of poisoned training data ([Kapoor discloses a plurality of states that can be restored to, including the last backup operation, and any of states 316-320 which occur after one or more transactions after the backup operation [see Kapoor, para. 37-38 and FIG. 3A]. Kapoor further discloses how they can restore to the last backup operation, or any of the points in between the backup operation and the restore operation [see Kapoor, para. 39-40 and FIG. 3A]. Thus, when combined with the inference model of Suzuki, the states would be successive states of the inference model when new data is introduced. Further, if there is more than one confidential data within a backup cycle, there would be two separate states of the model such that there is a first version with first confidential data and a second version with the first confidential data and a second confidential data]).
Regarding claim 7, the combination of Suzuki, Kapoor, Manley, and Kochar as applied in claim 6 above teaches all the limitations of claim 6 and further teaches:
wherein the graphical user interface further comprises: a compromise indicator positioned with the range bar, the compromise indicator being based on the first portion of the poisoned training data and the second portion of the poisoned training data (Suzuki discloses receiving an instruction to clear the models where the learned models contain confidential information which may be extracted [see Suzuki, para. 81]).
Regarding claim 8, the combination of Suzuki, Kapoor, Manley, and Kochar as applied in claim 7 above teaches all the limitations of claim 7 and further teaches wherein the graphical user interface further comprises:
a reversion cost estimate indicator that indicates a computing resource cost for reverting the inference model to previous versions of the inference model based on the user input (Manley discloses estimating resources and cost to restore to a backup using a recommended schedule [see Manley, para. 44], and presenting the recommended schedule to a user along with other details such as a recommended date and time [see Manley, para. 55]. It would have been obvious to one of ordinary skill in the art to also present the estimated resource and cost for the recommended schedule with the recommended schedule and other details);
a reversion time estimate indicator that indicates a duration of time for reverting the inference model to the previous versions of the inference model based on the user input (Manley discloses using a time estimator to estimate the amount of time to restore to a backup and that the estimated time can be presented to a user [see Manley, para. 53]).
Regarding claims 10 and 18, claims 10 and 18 contains substantially similar limitations to those found in claim 2 above. Consequently, claims 10 and 18 are rejected for the same reasons.
Regarding claims 11 and 19, claims 11 and 19 contains substantially similar limitations to those found in claim 3 above. Consequently, claims 11 and 19 are rejected for the same reasons.
Regarding claims 12 and 20, claims 12 and 20 contains substantially similar limitations to those found in claim 4 above. Consequently, claims 12 and 20 are rejected for the same reasons.
Regarding claim 13, claim 13 contains substantially similar limitations to those found in claim 5 above. Consequently, claim 13 is rejected for the same reasons.
Regarding claim 14, claim 14 contains substantially similar limitations to those found in claim 6 above. Consequently, claim 14 is rejected for the same reasons.
Regarding claim 15, claim 15 contains substantially similar limitations to those found in claim 7 above. Consequently, claim 15 is rejected for the same reasons.
Regarding claim 16, claim 16 contains substantially similar limitations to those found in claim 8 above. Consequently, claim 16 is rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Tatsuoka et al. (US 2008/0208555 A1) teaches a graphical user interface for restore points for reproducing a state of core models at the restore points.
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/J.T.B./Examiner, Art Unit 2143
/JENNIFER N WELCH/Supervisory Patent Examiner, Art Unit 2143