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 2/27/25 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-8, 11-13, 24-29 are rejected by 102(a)(1) as being anticipated byBhide et al. (hereinafter “Bhide”, US Patent Application 20220147597 A1).
As per claims 1, 24, 25, Bhide discloses A method, communication apparatus, non-transitory computer-readable storage medium for updating an artificial intelligence (AI) service policy, performed by an application function (AF) network element, comprising:
sending an AI service policy update request to a network exposure function (NEF) network element, wherein the AI service policy update request comprises an identifier of the AF network element, and updated policy information (paragraphs [0021, 0027, 0030, 0037-38], A control unit is used to evaluate an AI model against the rules and policies which are encoded into the AI policy engine. Model metadata is editable by model metrics computation tools which includes fields identifying service IDs registered to authorized systems to update model metrics).
receiving a policy update response returned by the NEF network element (paragraphs [0030, 0037], The AI policy engine detects changes and in response, initiates a review of models and provides an API which enables users to check if models meet the policies. Notification is outputted to a device. The notification is in response to an on-demand request for validation via the API).
As per claim 2, Bhide discloses The method of claim 1, wherein the AI service policy update request further comprises at least one of: a public land mobile network (PLMN) identifier, or a service based interface (SBI) address (paragraph [0027]).
As per claim 3, Bhide discloses The method of claim 1,
As per claims 4, 26,28, Bhide discloses A method, communication apparatus, and non-transitory computer-readable storage medium for updating an artificial intelligence (AI) service policy, performed by a network exposure function (NEF) network element, comprising:
receiving an AI service policy update request sent by an application function (AF) network element, wherein the AI service policy update request comprises an identifier of the AF network element and updated policy information (paragraphs [0021, 0027, 0030, 0037-38], A control unit is used to evaluate an AI model against the rules and policies which are encoded into the AI policy engine. Model metadata is editable by model metrics computation tools which includes fields identifying service IDs registered to authorized systems to update model metrics);
sending the identifier of the AF network element and the updated policy information to a unified data repository (UDR) network element (paragraphs [0021, 0027, 0030, 0037-38], A control unit is used to evaluate an AI model against the rules and policies which are encoded into the AI policy engine. Model metadata is editable by model metrics computation tools which includes fields identifying service IDs registered to authorized systems to update model metrics);
returning a policy update response to the AF network element (paragraphs [0030, 0037], The AI policy engine detects changes and in response, initiates a review of models and provides an API which enables users to check if models meet the policies. Notification is outputted to a device. The notification is in response to an on-demand request for validation via the API).
As per claim 5, Bhide discloses The method of claim 4, wherein sending the identifier of the AF network element and the updated policy information to the UDR network element comprises:
sending the identifier of the AF network element and the updated policy information to the UDR network element in a case that it is determined that the AI service policy update request is legal (paragraphs [0016, 0023]).
As per claim 6, Bhide discloses The method of claim 5, further comprising at least one of:
determining that the AI service policy update request is legal in response to that a preset registered AF list comprises the identifier of the AF network element (paragraphs [0027, 0029]);
or determining that the AI service policy update request is illegal in response to that a preset registered AF list does not comprise the identifier of the AF network element (paragraphs [0029, 0038]).
As per claim 7, Bhide discloses The method of claim 4, wherein the AI service policy update request further comprises at least one of: a public land mobile network (PLMN) identifier, or a service based interface (SBI) address (paragraph [0027]).
As per claim 8, Bhide discloses The method of any one of claim 4,
.
9-10. (Canceled)
As per claims 11, 27, 29, Bhide discloses A method, communication apparatus, and non-transitory computer-readable storage medium for updating an artificial intelligence (AI) service policy, performed by a policy control function (PCF) network element, comprising:
receiving an identifier of an application function (AF) network element and updated policy information sent by a unified data repository (UDR) network element (paragraphs [0021, 0027, 0030, 0037-38], A control unit is used to evaluate an AI model against the rules and policies which are encoded into the AI policy engine. Model metadata is editable by model metrics computation tools which includes fields identifying service IDs registered to authorized systems to update model metrics);
updating a policy control and charging (PCC) rule associated with the identifier of the AF network element according to the updated policy information (paragraphs [0021, 0027, 0030, 0037-38], A control unit is used to evaluate an AI model against the rules and policies which are encoded into the AI policy engine. Model metadata is editable by model metrics computation tools which includes fields identifying service IDs registered to authorized systems to update model metrics);
sending the identifier of the AF network element and the PCC rule updated to a session management function (SMF) network element (paragraphs [0021, 0027, 0030, 0037-38], A control unit is used to evaluate an AI model against the rules and policies which are encoded into the AI policy engine. Model metadata is editable by model metrics computation tools which includes fields identifying service IDs registered to authorized systems to update model metrics).
As per claim 12, Bhide discloses The method of claim 11, wherein sending the identifier of the AF network element and the PCC rule updated to the SMF network element comprises:
sending the identifier of the AF network element and the PCC rule updated to the SMF network element in response to that an AI service associated with the identifier of the AF network element is in an invoked state (paragraphs [0022, 0030, 0041].
As per claim 13, Bhide discloses The method of claim 11
14-23. (Canceled)
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BARBARA BURGESS ANYAN whose telephone number is (571)272-3996. The examiner can normally be reached IFP M-F 8am-5pm.
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August 8, 2026
/BARBARA B Anyan/Primary Examiner, Art Unit 2457
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