DETAILED ACTION
Claims 1-20 are pending with Claims 13-18 having been non-elected/withdrawn. Claims 1-12 and 19-20 are considered in this Office action.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/18/2025 has been acknowledged.
The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. The initialed and dated copy of Applicant’s IDS form 1449 is attached to the instant Office action.
Election/Restrictions
Claims 13-18 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Claims 13-18 have been non-elected/withdrawn by Applicant.
Applicant's election without traverse of the non-elected Claims in the interview of 9/29/2026 with Kenneth Knox is acknowledged and attached to this Action.
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 claims at issue 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); and 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 a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form 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 http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1 and 19 of the current application (Hereby known as ‘861) is provisionally rejected on the grounds of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent Application No. 18/826,622 (Hereby known as ‘622). Although the claims at issue are not identical, they are not patentably distinct from each other because:
Regarding Claims 1 and 19, Claims 1 and 19 of the current application (‘861) recite substantially similar steps of '622 – Claim 1.
Claims 1 and 19 of ‘861 recites the steps of:
performing, by a first network element, inference for a task based on a first model;
determining, by the first network element, first accuracy corresponding to the first model, wherein the first accuracy is used to indicate accuracy of an inference result of the task obtained by the first model; and
in a case that the first accuracy meets a preset condition, sending, by the first network element, first information to a second network element, wherein the first information is used to indicate that accuracy of the first model does not meet an accuracy requirement or has decreased;
wherein the second network element is a network element that triggers the task.
Whereas Claim 1 of ‘622 states:
determining, by a first network element, first accuracy of a first model, wherein the first accuracy indicates an accuracy of a result of inference performed on a task by using the first model; and
sending first information to a second network element in a case that the first network element determines that the first accuracy meets a preset condition, wherein the first information indicates that accuracy of the first model degrades, wherein
the first network element is a network element providing the first model, and the second network element is a network element that performs inference on the task.
These are obvious variants of each other as both recite substantially the same limitations. Further, elimination of an element or its functions is deemed to be obvious in light of prior art teachings of at least the recited element or its functions (see In re Karlson, 136 USPQ 184, 186; 311 F2d 581 (CCPA 1963)), thereby rendering the elimination of any elements recited in the claims of the related patent (that are not recited in the instant claims) obvious.
Thus, Claims 1 and 19 of the current application is an obvious variant of claim 1 in ‘622.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim 11 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor.
Claim 11 recites the limitations of “wherein after the sending second information to a third network element…”. Claim 9 recites the limitation of “second information to a third network element…” This is unclear as are these the same third network element or are they different. Thus, the claim is indefinite. For examiner purposes, this will be taken as the same third network element.
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.
Alice – Claims 1-12 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 and 19 recite the limitations for performing inference for a task based on a first model (Receiving and Analyzing Information, an Observation and Evaluation, a Mental Process; Managing Human Behavior, i.e. managing tasks; a Certain Method of Organizing Human Activity),determining first accuracy corresponding to the first model, wherein the first accuracy is used to indicate accuracy of an inference result of the task obtained by the first model (Analyzing the Information, an Evaluation, a Mental Process; Managing Human Behavior, i.e. managing tasks; a Certain Method of Organizing Human Activity), and in a case that the first accuracy meets a preset condition, sending first information to a second network element, wherein the first information is used to indicate that accuracy of the first model does not meet an accuracy requirement or has decreased (Receiving, Analyzing, and Transmitting Information, an Observation, Evaluation, and Judgment, a Mental Process; Managing Human Behavior, i.e. managing tasks; a Certain Method of Organizing Human Activity), that triggers the task (Transmitting the Analyzed Information, a Judgment, a Mental Process; Managing Human Behavior, i.e. managing tasks; a Certain Method of Organizing Human Activity), which under their broadest reasonable interpretation, covers performance of the limitation in the mind for the purposes of managing tasks, which is Organizing Human Behavior, but for the recitation of generic computer components. That is, other than reciting a first network element, second network element, network-side device, processor, and memory, nothing in the claim elements preclude the step from practically being performed or read into the mind for the purposes of Managing Human Activity. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas, an observation, evaluation, and judgment. Further, as described above, the claims recite limitations for Managing Human Activity/Behavior, a “Certain Method of Organizing Human Activity”. Accordingly, the claim recites an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claim recites the above stated additional elements to perform the abstract limitations as above. The first network element, second network element, network-side device, processor, and memory are recited at a high-level of generality (i.e., as a generic software/module performing a generic computer function of storing, retrieving, sending, and processing data) such that they amount to no more than mere instructions to apply the exception using generic computer components. Even if taken as an additional element, the receiving and transmitting steps above are at best insignificant extra-solution activity as these are receiving, storing, and transmitting data as per the MPEP 2106.05(d). Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception, when considered both individually and as an ordered combination. As discussed above with respect to integration of the abstract idea into a practical application, the additional element being used to perform the abstract limitations stated above amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The claim is not patent eligible. Applicant’s Specification states:
“[0029] FIG. 1 is a block diagram of a wireless communication system to which an embodiment of this application is applicable. The wireless communication system includes a terminal 11 and a network-side device 12. The terminal 11 may be a terminal-side device such as a mobile phone, a tablet personal computer, a laptop computer or a notebook computer, a personal digital assistant (PDA), a palmtop computer, a netbook, an ultra-mobile personal computer (UMPC), a mobile internet device (MID), an augmented reality (AR)/virtual reality (VR) device, a robot, a wearable device, vehicle user equipment (VUE), pedestrian user equipment (PUE), smart household (home devices with wireless communication functions, such as refrigerators, televisions, washing machines, or furniture), a game console, a personal computer (PC), a teller machine, or a self-service machine.”
Which shows that these steps can be performed on any generic computing device with a processor and memory, which can be used to perform the abstract limitations, such as a laptop, phone, desktop, etc., and from this interpretation, one would reasonably deduce the aforementioned steps are all functions that can be done on generic components, and thus application of an abstract idea on a generic computer, as per the Alice decision and not requiring further analysis under Berkheimer, but for edification the Applicant’s specification has been used as above satisfying any such requirement. This is “Applying It” by utilizing current technologies. For the receiving and transmitting steps that were provisionally considered extra-solution activity in Step 2A above, if they were to be considered additional elements, they have been re-evaluated in Step 2B and determined to be well-understood, routine, conventional, activity in the field. The background does not provide any indication that the additional elements, such as the devices, elements, processor, etc., nor the receiving and transmitting steps as above, are anything other than a generic, and the MPEP Section 2106.05(d) indicates that mere collection or receipt, storing, or transmission of data is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here). For these reasons, there is no inventive concept. The claim is not patent eligible.
Claims 2-12 and 20 contain the identified abstract ideas, further narrowing them, with the additional elements of a third network element which is highly generalized when considered as part of a practical application or under prong 2 of the Alice analysis of the MPEP, thus not integrated into a practical application, nor are they significantly more for the same reasons and rationale as above.
After considering all claim elements, both individually and in combination, Examiner has determined that the claims are directed to the above abstract ideas and do not amount to significantly more. Therefore, the claims and dependent claims are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter. See Alice Corporation Pty. Ltd. v. CLS Bank International, No. 13–298.
Claim Rejections - 35 USC § 103
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-11 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Meijuan (U.S. Publication No. 2023/003,0296) in view of Zhang (U.S. Publication No. 2024/030,6011).
Regarding Claims 1 and 19, Meijuan, a task processing method based on defect detection device, apparatus, and medium, teaches a model accuracy determining method, comprising:
performing an inference for a task based on a first model ([0039-41] a target model (element 1) is used to perform an inference task);
in a case that the first accuracy meets a preset condition, sending, by the first network element, first information to a second network element, wherein the first information is used to indicate that accuracy of the first model does not meet an accuracy requirement or has decreased ([0069-80] and [0078] an accuracy threshold (requirement) is used to determine whether there is a retraining of another model, a task);
wherein the second network element is a network element that triggers the task ([0078] triggers the AI model feedback in the 2nd element (node 2) which is the task).
Although Meijuan teaches determining an accuracy rate as in [0122] which is tied to the inference tasks, it does not explicitly state this is tied to the result or with a threshold.
Zhang, a method and apparatus for determining prediction for status of wireless networks,
also teaches performing, by a first network element, inference for a task based on a first model ([0048] node 2, a first network element, performs inference for a certain task based on a model);
determining, by the first network element, first accuracy corresponding to the first model, wherein the first accuracy is used to indicate accuracy of an inference result of the task obtained by the first model ([0069-80] an accuracy of the first model is determined using the previous (first) model which also uses an [0076] inference of the task); and
in a case that the first accuracy meets a preset condition, sending, by the first network element, first information to a second network element, wherein the first information is used to indicate that accuracy of the first model does not meet an accuracy requirement or has decreased ([0069-80] and [0078] an accuracy threshold (requirement) is used to determine whether there is a retraining of another model, a task);
wherein the second network element is a network element that triggers the task ([0078] triggers the AI model feedback in the 2nd element (node 2) which is the task).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the modeling of inference tasks of Meijuan with the modeling and inference tasks of Zhang as they are analogous art along with the claimed invention which all teach the use of modeling of inference tasks, and the combination would lead to an improved system which would lead to improved accuracy of the Ai models as taught in [0022] of Zhang.
Examiner notes Zhang teaches a network-side device with a processor and memory ([0025] a computer/apparatus with a processor and medium/memory)
Regarding Claims 2 and 20, Meijuan teaches wherein the determining, by the first network element, first accuracy corresponding to the first model (As in Claim 1 above) comprises:
obtaining label data corresponding to the inference result data ([0091] labels are used for the results of tasks as are [0140] categories); and
calculating the first accuracy of the first model based on the inference result data and the label data ([0034-35] the label and inference result as in [0091] above are used to come up with an [0036] accuracy rate)
Zhang teaches obtaining inference result data corresponding to the task based on the first model as in [0078] where a result is obtained from the inference in the node/element.
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the modeling of inference tasks of Meijuan with the modeling and inference tasks of Zhang as they are analogous art along with the claimed invention which all teach the use of modeling of inference tasks, and the combination would lead to an improved system which would lead to improved accuracy of the Ai models as taught in [0022] of Zhang.
Regarding Claim 3, Meijuan teaches wherein the first information comprises at least one of the following:
part or all of description information of the task; indication information indicating that accuracy of the first model does not meet an accuracy requirement or has decreased; the first accuracy; recommended operation information; or waiting time information, wherein the waiting time information is used to indicate a time required for the first network element to resume inference for the task ([0031] a waiting time/training time is included, [0091] task information is used along with [0090] task type, [0095] execution time)
Regarding Claim 4, Meijuan teaches The method according to claim 3, wherein the recommended operation information comprises at least one of the following:
information indicating the second network element to continue to use inference result data corresponding to the task; information indicating the second network element to stop to use the inference result data corresponding to the task; or information indicating the second network element to re-trigger the task to obtain new inference result data ([0138] preventing of a continuous loading of new models is a stopping of using the result data)
Regarding Claim 5, Meijuan teaches wherein before the performing inference for a task based on a first model, the method further comprises:
Receiving a task request message from the second network element, wherein the task request message is used to request to perform inference for the task, and the task request message contains description information of the task ([0091] a request of a task which the type and other description information is included)
Regarding Claim 6, Meijuan teaches The method according to claim 2, wherein the obtaining, by the first network element, label data corresponding to the inference result data comprises:
determining, by the first network element, a source device of the label data corresponding to the task; and obtaining, by the first network element, the label data from the source device ([0118] label files from devices (source) are obtained) or,
Examiner notes Zhang teaches wherein after the obtaining inference result data corresponding to the task based on the first model, the method further comprises: sending, by the first network element, the inference result data to the second network element ([0078] triggers the AI model feedback in the 2nd element (node 2) which is the task).
Regarding Claim 7, Meijuan teaches wherein the preset condition comprises at least one of the following conditions:
the first accuracy is lower than a first threshold; the first accuracy is lower than second accuracy; or the first accuracy is lower than the second accuracy, and a difference between the first accuracy and the second accuracy is greater than a second threshold; wherein the second accuracy is used to indicate accuracy of a model output result presented by the first model during a training phase or a testing phase ([0122] and [0134] an accuracy rate is used in conjunction with the model result and a threshold)
Regarding Claim 8, Meijuan teaches wherein before the performing inference for a task based on a first model, the method further comprises:
obtaining, by the first network element, the first model and the second accuracy of the first model; or, wherein in a case that the first accuracy meets the preset condition, the method further comprises: requesting, by the first network element, to obtain a second model from a fourth network element, wherein the second model is a model provided by the fourth network element for the task; and performing, by the first network element, inference for the task based on the second model to obtain new inference result data of the task ([0129] the models are sent to multiple network elements)
Regarding Claim 9, the combination of Meijuan and Zhang teaches wherein in a case that the first accuracy does not meet the accuracy requirement, the method further comprises:
sending, by the first network element, second information to a third network element that provides the first model, wherein the second information is used to indicate that the accuracy of the first model does not meet the accuracy requirement or has decreased (As in Claim 1 above, there is a sent accuracy of the models for multiple models as in Zhang above)
Regarding Claim 10, Meijuan teaches The method according to claim 9, wherein the second information comprises at least one of the following:
identity information of the first model; identity information of the task; constraint condition information of the task; indication information indicating that the accuracy of the first model does not meet the accuracy requirement or has decreased; the first accuracy; request indication information for retraining the first model; or first data of the task, wherein the first data is used to retrain the first model; wherein the first data comprises at least one of the following: inference input data corresponding to the task; inference result data corresponding to the task; or label data corresponding to the task ([0125] inference input and [0130] inference result)
Regarding Claim 11, Meijuan teaches The method according to claim 9, wherein after the sending second information to a third network element, the method further comprises:
receiving, by the first network element, third information from the third network element, wherein the third information comprises information of the retrained first model; wherein the third information further comprises at least one of the following: applicable condition information of the retrained first model; or third accuracy of the retrained first model, wherein the third accuracy is used to indicate accuracy of a model output result presented by the retrained first model during a training phase or a testing phase ([0143] a third model and layer is used with retraining of the models for tasks)
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Meijuan (U.S. Publication No. 2023/003,0296) in view of Zhang (U.S. Publication No. 2024/030,6011) in further view of Faulhaber (U.S. Publication No. 2019/015,6247).
Regarding Claim 12, the combination of Meijuan and Zhange teaches model inferencing and network elements as in Claim 1 above, but neither teaches a model inference function network element or a consumer network function.
Faulhaber, a system and method for dynamic accuracy based deployment and monitoring of machine learning models, teaches wherein the first network element comprises a model inference function network element; or, wherein the second network element comprises a consumer network function ([0073] inferences functions or calls are used.
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the modeling of inference tasks of the combination of Meijuan and Zhang with the modeling and inference tasks of Faulhaber as they are analogous art along with the claimed invention which all teach the use of modeling of inference tasks, and the combination would lead to an improved system which would lead to improved performance and shifting of traffic due to the Ai models as taught in [0045] of Faulhaber.
Conclusion
The prior art made of record is considered pertinent to applicant's disclosure.
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/JOSEPH M WAESCO/Primary Examiner, Art Unit 3625B 9/30/2026
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