DETAILED 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 .
Response to Preliminary Amendment
Applicant’s preliminary amendment dated August 20, 2025 amending claims, specification, and abstract of the invention has been fully considered and is entered. Claims 1-3, 5, 7-13, 15-18, 20-21, 33-34, and 37 are examined.
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.
Claims 1-3, 5, 7-13, 15-18, 20-21, 33-34, and 37 are 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 regards as the invention.
As to claims 1, 8, and 15, the preamble states that the claims are directed to a method for monitoring a performance of an artificial intelligence (AI) model. However, none of these claims actually perform any type of monitoring. The only active step of the claim is sending (or receiving) performance monitoring information that is collected (supposedly by monitoring) elsewhere, rendering the scope of the claim indefinite.
While various dependent claims further clarify what the performance monitoring value is and how it is calculated, none of the dependent claims have an active step that would corresponding to monitoring the performance of the AI model. Also, it is noted that language such as “for calculating” suggests intended use and does not actually require calculating a performance monitoring value.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3, 5, 7-13, 15-18, 20-21, 33-34, and 37 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Sun et al. (US 2025/0254549 A1).
As to claim 1, Sun teaches a method for monitoring a performance of an artificial intelligence (AI) model, performed by a terminal (Fig. 6), wherein the AI model comprises a first model and a second model [multiple AI models], the terminal is deployed with the first model and the second model (par. [0133]), and a network device is deployed with the second model (par. [0144]), and the method comprises:
reporting performance monitoring indication information to the network device [step 605 in Fig. 6] (par. [0143]).
As to claims 2 and 7, these claims further define the performance monitoring value of the second model. However, this feature is not required by claim 1 that reports performance monitoring indication.
As to claims 3 and 5, these claims further define the relevant information for calculating the performance monitoring value. However, this feature is not required by claim 1 that reports performance monitoring indication.
As to claim 33, Sun teaches a terminal (Fig. 10), comprising: a processor; and a transceiver connected to the processor, wherein the processor is configured to load and execute executable instructions to implement the method for monitoring the performance of the AI model according to claim 1 (par. [0194]-[0195]).
As to claim 8, Sun teaches a method for monitoring a performance of an artificial intelligence (AI) model, performed by a terminal (Fig. 6), wherein the AI model comprises a first model and a second model [multiple AI models], the terminal is deployed with the first model, and a network device is deployed with the second model (par. [0133]), and the method comprises:
reporting relevant information for calculating a performance monitoring value of the second model to the network device [step 605 in Fig. 6] (par. [0143]).
As to claim 9, Sun teaches that the relevant information for calculating the performance monitoring value comprises a relevant value [performance monitoring results] for calculating first data [for determining whether to activate or deactivate the AI model] (par. [0063]).
As to claim 10, Sun teaches that the relevant value for calculating the first data comprises the first input value [performance monitoring results based on the provided configuration parameters] (par. [0062]).
As to claim 12, the subject matter of this claim is not required by the preceding claims.
As to claim 11, Sun teaches multiple models (par. [0133]). Having models named “a channel status information (CSI) compression” model and “a CSI recovery” model is deemed to be a non-functional description material that is a mere name tag and does not limit the step of reporting.
As to claim 13, Sun teaches that reporting the relevant information for calculating the performance monitoring value of the second model to the network device comprises: reporting the relevant information for calculating the performance monitoring value of the second model to the network device in a case where reporting indication information sent by the network device is received [network device transmits configuration parameters for monitoring performance of the one or more AI models to the terminal equipment] (step 301 in Fig. 3, par. [0057]).
As to claim 37, Sun teaches a terminal (Fig. 10), comprising: a processor; and a transceiver connected to the processor, wherein the processor is configured to load and execute executable instructions to implement the method for monitoring the performance of the AI model according to claim 8 (par. [0194]-[0195]).
As to claim 15, Sun teaches a method for monitoring a performance of an artificial intelligence (AI) model, performed by a network device (Fig. 3), wherein the AI model comprises a first model and a second model [multiple AI models], a terminal is deployed with the first model and the second model, and the network device is deployed with the second model (par. [0133]), and the method comprises:
receiving performance monitoring indication information [step 605 in Fig. 6] (par. [0143]).
As to claims 16 and 20, these claims further define the performance monitoring value of the second model. However, this feature is not required by claim 15 that receives performance monitoring indication information.
As to claims 17 and 18, these claims further define the relevant information for calculating the performance monitoring value. However, this feature is not required by claim 1 that reports performance monitoring indication.
As to claim 34, Sun teaches a network device (Fig. 9), comprising: a processor; and a transceiver connected to the processor, wherein the processor is configured to load and execute executable instructions to implement the method for monitoring the performance of the AI model according to claim 15 (par. [0190]-[0191]).
Conclusion
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/OLEG SURVILLO/Primary Examiner, Art Unit 2457
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