Prosecution Insights
Last updated: August 17, 2026
Application No. 18/436,384

METHOD AND DEVICE FOR PROVIDING AI/ML MEDIA SERVICE IN WIRELESS COMMUNICATION SYSTEM

Final Rejection §103
Filed
Feb 08, 2024
Priority
Feb 10, 2023 — RE 10-2023-0018276
Examiner
CARDONE, JASON D
Art Unit
2458
Tech Center
2400 — Computer Networks
Assignee
Samsung Electronics Co., Ltd.
OA Round
2 (Final)
88%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
85%
With Interview

Examiner Intelligence

Grants 88% — above average
88%
Career Allowance Rate
46 granted / 52 resolved
+30.5% vs TC avg
Minimal -4% lift
Without
With
+-3.6%
Interview Lift
resolved cases with interview
Typical timeline
2y 5m
Avg Prosecution
22 currently pending
Career history
68
Total Applications
across all art units

Statute-Specific Performance

§101
7.1%
-32.9% vs TC avg
§103
57.8%
+17.8% vs TC avg
§102
20.0%
-20.0% vs TC avg
§112
8.9%
-31.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 52 resolved cases

Office Action

§103
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 Arguments Applicant's arguments, filed 05/15/2026, have been fully considered but they are not persuasive. Applicants’ Arguments: “Applicant submits that the applied references do not disclose or render obvious” [Reply, page 10]. “Applicant submits that independent claim 1 is patentable over Pogorelik and Zhao. Furthermore, because independent claim 6 recites similar elements, Applicant submits that claim 6 is patentable over Pogorelik and Zhao for similar reasons” [Reply, page 11]”. Applicant submits that independent claim 11 is patentable over Pogorelik and Zhao [Reply, page 13]. In response to applicant's arguments: These statements are conclusionary, since they do not have an argument within it. Applicant must also discuss the references applied against the claims, explaining how the claims avoid the references or distinguish from them. Applicant's argument fails to comply with 37 CFR 1.111(b) because it amounts to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references. 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, 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, 2, 6, 7, 11, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Pogorelik et al. ("Pogorelik") [PGPUB 2021/0406652] in view of Zhao [PGPUB 2024/0022616] (the cited subject matter is supported by provisional application 63/397,281). Regarding claim 1, the Pogorelik reference discloses a method performed by a user equipment (UE) for an artificial intelligence/machine learning (AI/ML) media service in a wireless communication system [ie. client ("UE")with face recognition service ("Al/ML media service"); Pogorelik; figures 4 and 5B-5C; paragraph 0026, 0029-0030, and 0047], the method comprising: receiving, from a network server providing the AI/ML media service, service access ("service access information") from client ("receiving" at UE); Pogorelik; fig 4 and 6; para 0063, 0070, and 0089]; obtaining information on client AI media inferencing capabilities and functions [ie. obtain capabilities and functions to be sent to server; Pogorelik; fig 6; para 0063; 0077, 0081, and 0126]; negotiating with the network server for splitting an AI media inference processing, based on the received service access information and the obtained information on client AI media inferencing capabilities and functions [Pogorelik; para 0054-0055, 0063-0064, and 0087]; receiving, from the network server, UE AI model data for performing a first split inferencing for a first portion of an AI model [ie. partition of a Neural Network architecture (“UE AI model data”); “for performing” is intended use of the model data; Pogorelik; fig 4, 6, and 9A; para 0062-0063 and 0101]; receiving, from the network server, intermediate data corresponding to a second split inferencing for a second portion of the AI model, wherein the second split inferencing is associated with network AI model data [Pogorelik; fig 4, 6 and 9A; para 0064 and 0101-0102]; and processing the received UE AI model data and the received intermediate data to output inference output data to be provided to the UE [Pogorelik; fig 4, 6, and 9A; para 0102-0103]. The Pogorelik reference discloses a client receiving discovery inquiry for access security requirements and establishing a trust from a network server providing the Al/ML media service [Pogorelik; fig 4 and 6; para 0063, 0070, and 0088-0089] but does not specifically state "service access information including at least one of information for media session handling and information for media streaming access". However, in the same field of endeavor, the Zhao reference discloses receiving, from a network server providing the Al/ML media service, service access information including at least one of information for media session handling and information for media streaming access [ie. "5GMS defined media-streaming architecture for both uplink and downlink streaming. A 5GMS-aware application is enabled to utilize the MS interface for media session handling and the M4 interface for streaming transport handling"; Zhao; fig 1; para 0021, 0024-0025, and 0 123]. The Pogorelik and Zhao references are analogous art, since they have similar problem solving area in data channel management for media streaming. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of media session handling and access, taught by Zhao, into the system, taught by Pogorelik. The motivation for doing so would have been "for immersive RTC signaling and streaming based on SGMS existing interface" [Zhao; para 0025]. Regarding claim 2, the combination of Pogorelik-Zhao further discloses Al model data related to a structure of an Al model for the Al/ML media service includes a UE Al model subset and a network Al model subset and wherein the UE AI model data corresponds to the UE AI model subset, and the network AI model data corresponds to the network AI model subset [Pogorelik; para 0063, 0101-0103, and 0128] [Zhao; para 0123]. Regarding claims 6 and 7, the apparatus of claims 6 an 7 perform the similar steps as the method of claims 1 and 2. The combination of Pogorelik-Zhao teaches the method of claims 1 and 2, as referenced above. The additional limitations of an "network server'', a "transceiver", and a "processor" are rejected with the citation of paragraphs 0034-0036 of Pogorelik. Therefore, claims 6 and 7 are rejected using the same art and rationale set forth above in the rejection of claims 1 and 2, by the teachings of Pogorelik-Zhao. Regarding claim 11, the Pogorelik reference discloses a network server for an artificial intelligence/machine learning (AI/ML) media service in a wireless communication system, the network server comprising: a transceiver; and a processor configured to [Pogorelik; figures 4 and 5B-5C; paragraph 0026, 0029-0030, 0034-0036, and 0047]: transmit, to a user equipment (UE) via the transceiver, service access information [ie. server inquires or discovers ("transmits") security requirements ("service access information") from client and establishes trust; Pogorelik; fig 4 and 6; para 0063, 0070, 0085, and 0089]; negotiate with the UE for splitting an AI media inference processing, based on the transmitted service access information [Pogorelik; para 0054-0055, 0063-0064, and 0087]; transmit, to the UE via the transceiver, UE AI model data associated with a first split inferencing for a first portion of an AI model [ie. partition of a Neural Network architecture (“UE AI model data”); Pogorelik; fig 9A; para 0063-0064 and 0101-0102]; receive, via the transceiver from the UE, intermediate data corresponding to the first split inferencing [ie. back propagating gradients; Pogorelik; para 0095-0096], and process network AI model data and the received intermediate data to output inference output data to be provided to the UE, wherein the network AI model data is associated with a second split inferencing for a second portion of the AI model [ie. classification results from back propagating gradients (“received intermediate data”) and processing vector features (“AI model data”); Pogorelik; para 0094-0096, 0100, and 0105]. The Pogorelik reference discloses a client receiving discovery inquiry for access security requirements and establishing a trust from a network server providing the Al/ML media service [Pogorelik; fig 4 and 6; para 0063, 0070, and 0088-0089] but does not specifically state "service access information including at least one of information for media session handling and information for media streaming access". However, in the same field of endeavor, the Zhao reference discloses service access information including at least one of information for media session handling and information for media streaming access [ie. "SGMS defined media-streaming architecture for both uplink and downlink streaming. A SGMS-aware application is enabled to utilize the MS interface for media session handling and the M4 interface for streaming transport handling"; Zhao; fig 1 and 10; para 0021, 0024-0025, and 0114]. The Pogorelik and Zhao references are analogous art, since they have similar problem solving area in data channel management for media streaming. It would have been obvious to a person of ordinary skill in the art, before the effective filling date of the claimed invention, to combine the teaching of media session handling and access, taught by Zhao, into the system, taught by Pogorelik. The motivation for doing so would have been "for immersive RTC signaling and streaming based on SGMS existing interface" [Zhao; para 0025]. Regarding claim 12, the combination of Pogorelik-Zhao further discloses AI model data related to a structure of an AI model for the AI/ML media service includes a UE AI model subset and a network AI model subset, and wherein the UE AI model data corresponds to the UE AI model subset, and the network AI model data corresponds to the network AI model subset [Pogorelik; para 0063, 0101-0103, and 0128] [Zhao; fig 10; para 0114 and 0123]. Allowable Subject Matter Claims 16-18 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 JASON D CARDONE whose telephone number is (571)272-3933. The examiner can normally be reached Mon-Fri. 8am-4pmEST. 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, Umar Cheema can be reached at 571-270-3037. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /JASON D CARDONE/ Primary Examiner, Art Unit 2458
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Prosecution Timeline

Feb 08, 2024
Application Filed
Feb 17, 2026
Non-Final Rejection mailed — §103
May 15, 2026
Response Filed
Jun 24, 2026
Final Rejection mailed — §103 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
88%
Grant Probability
85%
With Interview (-3.6%)
2y 5m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 52 resolved cases by this examiner. Grant probability derived from career allowance rate.

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