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 .
Response to Arguments
Applicant's arguments filed 08/18/2026 have been fully considered but they are not persuasive.
35 U.S.C 103: Egi in view of Li: Claims 1-10, 12-13 and 17.
Claim 1:
Applicant argues that the references fail to teach “receiving [], a feedback reporting related to how the model provided by the first network node to the second network node has been retrained or modified by the second network node, wherein the feedback report comprises one or more information related to at least a condition or event that triggered the re-training or the modification of the model”
Examiner respectfully disagrees.
The claim limitations states that “wherein the feedback report comprises one or more information related to at least a condition or event that triggered the re-training or the modification of the model”
Egi, teaches in par 0100 that the report/communicates the differences (condition) between the initial model supplied by provider and the result of its retrained model. Furthermore, par 0111 indicates the received feedback indicates details about how the result was liked or not liked and how the system might be correct or not corrected action (e.g., information which are connected to at least a condition or event that triggered the retraining or the modification of the model).
Therefore, the arguments are not persuasive, and rejection is therefore maintained.
Claim 2:
Applicant argues that the references teach “transmitting [], further information associated to the model comprising one or more of:’….an indication that model re-training or modification is suggested or recommended”
Examiner respectfully disagrees.
The claim limitation only requires the references to teach at least one of the limitation information stated in claim 2.
Egi teaches two of the limitation information:
associated to; an indication that the model cannot be re-trained or modified (cannot be trained, refer to par 0085);
an indication that the model can be re-trained or modified (contain indication/instruction that the model can be retrained, refer to par 0109, 0110);
With respect to Egi teaches associated to; an indication that the model cannot be re-trained or modified (cannot be trained, refer to par 0085). The model will decided whether or it can or cannot (able or not able to) be retrain or modified based on whether or mt it satisfy the accuracy threshold. If it does not pass the threshold, then the model is not able to retrain/modify, and if it pass the threshold, then the model is able to retrain/modify (refer to par 0085, 0110,0111)
Therefore, the argument is not persuasive, the rejection is therefore maintained.
Claim 8:
Applicant argues that the references fail to disclose the claimed limitation.
Examiner respectfully disagrees.
Egi further discloses wherein, when the first network node indicates to the second network node that the model provided by the first network node can be re-trained or modified, the first network node further transmits to the second network node, either with the FIRST MESSAGE or with the THIRD MESSAGE, one or more information related to re-training or modifying the model, which may comprise one or more of: ……
one or more instructions, policies and/or recommendations related to re-training the
model (policies related to retrain, refer to par 0100);
Egi teaches ..”perform further computation such as to adjusting/instruction its initial model based on the differences/condition/rules related to re-training the model.
Therefore, the argument is not persuasive, and rejection is therefore maintained.
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) 1-10, 12 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Egi et al hereinafter Egi (US 20210225530) in view of Li et al hereinafter Li (US 20240205781).
Referring to Claim 1. Egi discloses a method performed by a first network node, the method comprising:
transmitting a FIRST MESSAGE towards a second network node, the FIRST MESSAGE comprising a model (communicate a new model to the household, refer to par 0100);
receiving a SECOND MESSAGE transmitted by the second network node, the SECOND MESSAGE comprising an indication that the second network node has re-trained or modified the model transmitted by the first network node (household communicate the newly build model or difference to the provider, refer to par 0100); and
receiving either via the SECOND MESSAGE or via a FOURTH MESSAGE, a feedback
reporting related to how the model provided by the first network node to the second network node has been retrained or modified by the second network node, wherein the feedback report comprises one or more information related to at least a condition or event that triggered the re-training or the modification of the model (the report is the differences to the modification of the model, refer to par 0100, 0111).
Although Egi disclosed the invention substantially as claimed, Egi did not explicitly disclosing the details on the feedback reports comprises condition/event that triggers the retrain or modification of the model in RAN environment.
Li, in analogous art, is introduced to emphasize the feedback reports comprises one or more information related to at least condition or event that triggered the re-training or the modification of the model in the RAN environment (refer to par 0224-0227).
It would have been obvious for one of ordinary skill in the art before the filing date of the claimed invention to combine the teaching of Egi with Li because Li’s teaching would allow the system of Egi to timely provide guarantee service in the wireless environment.
Referring to Claim 2. Egi with Li disclosed the method of claim 1 further Egi discloses comprising:
transmitting within the FIRST MESSAGE or with a THIRD MESSAGE, further
information associated to the model comprising one or more of:
an identity or an identifier of the model and/or an identifier of a specific version
or vendor or type of the model to which the transmitted information is applicable to or
associated to; an indication that the model cannot be re-trained or modified (cannot be trained, refer to par 0085);
an indication that the model can be re-trained or modified (contain indication/instruction that the model can be retrained, refer to par 0085, 0109, 0110); and
an indication that model re-training or modification is suggested or recommended.
Referring to Claim 3. Egi with Li disclosed the method of claim 1 Egi discloses wherein the model is an Artificial Intelligence, AI, and/or Machine Learning, ML, model (AI model, refer to par 0112).
Referring to Claim 4. Egi with Li disclosed the method of claim 1 Egi discloses wherein the SECOND MESSAGE provides a notification to the first network node that the second network node has re-trained or modified an AIML model provided by the first network node (refer to par 0110, that the model is completed train and send the differential to the provider).
Referring to Claim 5. Egi with Li disclosed the method of claim 1 Egi further discloses wherein the information provided with the FIRST MESSAGE or with the THIRD MESSAGE further includes an indication of at least one network node to which the provided indications are associated (refer to par 0108 - 0110).
Referring to Claim 6. Egi with Li disclosed the method of claim 5. Egi further discloses wherein the at least one network node comprises the second network node or a third network node (refer to par 0108 - 0110).
Referring to Claim 7. Egi with Li disclosed the method of claim 5. Egi further discloses wherein the indication comprises an indication of at least a network node which could re-train or modify the model (retrain, refer to par 0100).
Referring to Claim 8. Egi with Li disclosed the method of claim 1. Egi further discloses wherein, when the first network node indicates to the second network node that the model provided by the first network node can be re-trained or modified, the first network node further transmits to the second network node, either with the FIRST MESSAGE or with the THIRD MESSAGE, one or more information related to re-training or modifying the model, which may comprise one or more of:
one or more conditions or events to be fulfilled for re-training the model;
one or more instructions, policies and/or recommendations related to re-training the
model (policies related to retrain, refer to par 0100);
one or more instructions, policies and/or recommendations related to modifying the
model;
a request to transmit to the first network node an indication that the second network node
has updated, re-trained and/or modified the model provided by the first network node;
one or more conditions and/or events to be fulfilled for transmitting to the first network
node an indication that the second network node has updated, re-trained and/or modified a model provided by the first network node, such as changes in the environment where the model is applied;
one or more conditions related to use case(s) or time scale(s) for which re-training or
modification of the model is possible or suggested or recommended.
Referring to Claim 9. Egi with Li disclosed the method of claim 1. Egi further discloses wherein the first network node further requests from the second network node, either within the FIRST MESSAGE, within the THIRD MESSAGE, or within another message information associated to the changes/modifications or updates done by the second network node to the model (the receive message contains a response or a return value associates with the model , refer to par 0114, 0116).
Referring to Claim 10. Egi with Li disclosed the method of claim 1. Li discloses wherein the first network node comprises one or more of: an Operation and Management, OAM, node; and a Service and Management Orchestration, SMO, node, while the second network node comprises one or more of: a Radio Access Network, RAN (refer to par 0003), node; a Next Generation Radio Access Network, NG-RAN, node; a function of a RAN node; a New Radio Base Station, gNB; a gNB-Control Unit-Control Plane,gNB-CU-CP; a network node realizing at least in part a Non-Real Time Radio Intelligent Controller, RIC; a network node realizing at least in part a Near-Real Time RIC; a Core Network node; and a Cloud-based centralized training node.
It would have been obvious for one of ordinary skill in the art before the filing date of the claimed invention to combine the teaching of Egi with Li because Li’s teaching would allow the system of Egi to timely provide guarantee service in the wireless environment.
Referring to Claim 12. Egi with Li disclosed the method of claim 1. Egi further discloses wherein the feedback report comprises one or more information elements in the group of:
one or more information related to how the model has been re-trained (differential of the model being modified, refer to par 0100);
one or more information related to how the model has been modified;
information about the type of training data used;
instances of outputs derived with the retrained/modified model and associated sample
inputs;
an indication that the model has been augmented or reduced;
an indication that the model has been modified and that the type of AIML model has been
changed;
the retrained/modified model;
an identity or an identifier of an AIML model to which the transmitted information is
applicable or associated; and
an identifier of a specific version or vendor of the AIML model.
report comprises one or more information related to at least a condition or event that triggered
the re-training or the modification of the model.
Referring to Claim 15, Claim is rejected under similar rational as claim 1.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KAREN C TANG whose telephone number is (571)272-3116. The examiner can normally be reached on 7am - 4pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Joon H Hwang can be reached on (571) 272-4036. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/KAREN C TANG/Primary Examiner, Art Unit 2447
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