Prosecution Insights
Last updated: April 19, 2026
Application No. 18/109,042

METHOD AND SYSTEM FOR ADAPTIVELY STREAMING ARTIFICIAL INTELLIGENCE MODEL FILE

Final Rejection §102§103
Filed
Feb 13, 2023
Examiner
SANKS, SCHYLER S
Art Unit
2129
Tech Center
2100 — Computer Architecture & Software
Assignee
Samsung Electronics Co., Ltd.
OA Round
2 (Final)
72%
Grant Probability
Favorable
3-4
OA Rounds
2y 11m
To Grant
88%
With Interview

Examiner Intelligence

Grants 72% — above average
72%
Career Allow Rate
362 granted / 501 resolved
+17.3% vs TC avg
Strong +16% interview lift
Without
With
+15.9%
Interview Lift
resolved cases with interview
Typical timeline
2y 11m
Avg Prosecution
40 currently pending
Career history
541
Total Applications
across all art units

Statute-Specific Performance

§101
2.6%
-37.4% vs TC avg
§103
46.7%
+6.7% vs TC avg
§102
17.1%
-22.9% vs TC avg
§112
32.2%
-7.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 501 resolved cases

Office Action

§102 §103
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 . 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. 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)(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. Claim(s) 1-6, 10, 14-16, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hwang (US20190228294). Regarding claim 1, Hwang teaches a method for adaptively streaming an artificial intelligence (AI) model file from a first electronic device (Figure 3: 1000) to a second electronic device (Figure 3: 2000), the method comprising: determining, by the first electronic device, a capability of the first electronic device and a capability of the second electronic device (¶49); determining, by the first electronic device, network information associated with the first electronic device and the second electronic device ¶49); determining, by the first electronic device, Al model information associated with the Al model file (¶49); based on the capability of the first electronic device, the capability of the second electronic device, the network information, and the Al model information, determining, by the first electronic device, whether to adaptively stream the Al model file from the first electronic device to the second electronic device (¶49-51); pre-processing the Al model file, by the first electronic device, based on the determining to adaptively stream the Al model file from the first electronic device to the second electronic device (¶49-51); and adaptively streaming the Al model file, by the first electronic device, from the first electronic device to the second electronic device based on the pre-processing (¶49-51), the second electronic device to process input data stored on the second electronic device using the AI model file (¶97). Regarding claim 2, Hwang teaches all of the limitations of claim 1, wherein the capability of the first electronic device and the capability of the second electronic device are determined based on at least one of a processor, a memory, a battery status, and a device health condition of the first electronic device or the second electronic device (¶49, ¶52 “computation capabilities” is based on a processor and/or memory, e.g. a lack of a processor or memory would indicate no computation capability). Regarding claim 3, Hwang teaches all of the limitations of claim 1, wherein the capability of the first electronic device or of the second electronic device indicates at least one of a processing time for at least one partial Al model, an execution time for the at least one partial Al model, an inference time for the at least one partial Al model, a split time for the at least one partial Al model, and a transfer time for the at least one partial Al model (¶49, “data transmission rate” is based on transfer time because it details how much of the model can be transferred per unit time). Regarding claim 4, Hwang teaches all of the limitations of claim 1, wherein the network information comprises a type of network, a bandwidth information, a latency information, a handover information, a mobility information, a download link information, an uplink information, a data transmission speed, a type of data transfer between the first electronic device and the second electronic device, and a size of the data transfer between the first electronic device and the second electronic device (¶49). Regarding claim 5, Hwang teaches all of the limitations of claim 1, wherein the Al model information comprises a type of AI- architecture, a type of data used in the type of AI-architecture, a type of link used in the type of AI- architecture, and a cross-layer dependency in the AI-architecture (¶49). Regarding claim 6, Hwang teaches all of the limitations of claim 1, wherein the pre-processing indicates at least one of a split of a complete Al model into at least one partial Al model at the first electronic device, a parallel download of the at least one partial Al model at the second electronic device, a parallel inference at the second electronic device, and encoding the at least one partial Al model (¶49). Regarding claim 10, Hwang teaches all of the limitations of claim 1, further comprising: receiving, by the second electronic device, the Al model file from the first electronic device to the second electronic device, wherein the Al model file includes at least one partial Al model from the first electronic device, and wherein the second electronic device downloads the at least one partial Al model to execute the Al model file (¶49). Regarding claim 14, Hwang teaches all of the limitations of claim 1, wherein the capability of the first electronic device and the capability of the second electronic device are determined based on an initial handshake between the first electronic device and the second electronic device (¶107). Regarding claims 15-16 and 20, Hwang according to claims 1, 6, and 10, coupled with the disclosure of the memory and processor (¶66), covers the device of claims 15-16 and 20. 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. This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. Claim(s) 7 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hwang (US20190228294A1) in view of Kupitman (US20190340110A1). Regarding claim 7, Hwang teaches all of the limitations of claim 6, wherein the pre-processing comprises: analyzing, by the first electronic device, an Al architecture of the complete Al model of the Al model file; splitting, by the first electronic device, the complete Al model into the at least one partial Al model based on the capability of the first electronic device , the capability of the second electronic device, the network information, and the Al model information (¶49, the model is split into two or more parts). Hwang does not disclose creating, by the first electronic device, a model description file to send to the second electronic device, wherein the model description file comprises a location information of the at least one partial Al model, and wherein the location information comprises at least one of a recommended tag and a mandatory tag. Kupitman teaches creating a model description file wherein the model description file comprises a location information of the at least one partial Al model, and wherein the location information comprises at least one of a recommended tag and a mandatory tag (¶127, “ “name”: “dense_1”” and “name”: “dense_2”, which can be considered either a recommended or mandatory “name” tag with location information described first and second layers). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to, in Hwang, create by the first electronic device, a model description file to send to the second electronic device, wherein the model description file comprises a location information of the at least one partial Al model, and wherein the location information comprises at least one of a recommended tag and a mandatory tag in order to ensure that the second electronic device receives the correct model definition. Regarding claim 17, Hwang as modified according to claim 7 coupled with the disclosure of the memory and processor (¶66), covers the device of claim 17. Allowable Subject Matter Claims 8-9, 11-13, and 18-19 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. The following is a statement of reasons for the indication of allowable subject matter: The prior art does not establish anticipation or a prima facie case of obviousness for the conversion and sub-model identification of claims 8 and 18 and thereby claims 9 and 19. The prior art does not establish anticipation or a prima facie case of obviousness for the parallelism of claims 11-13. Response to Arguments Applicant’s remarks filed 01/08/2026 have been fully considered. Applicant has argued that Hwang does not disclose the newly claimed features. Further review of Hwang indicates that Hwang discloses the newly amended limitations at ¶97 where training data may be stored on the second device to train the second model, i.e. the AI model file. Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 SCHYLER S SANKS whose telephone number is (571)272-6125. The examiner can normally be reached 06:30 - 15:30 Central Time, M-F. 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, Michael Huntley can be reached at (303) 297-4307. 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. /SCHYLER S SANKS/Primary Examiner, Art Unit 2129
Read full office action

Prosecution Timeline

Feb 13, 2023
Application Filed
Oct 06, 2025
Non-Final Rejection — §102, §103
Nov 18, 2025
Interview Requested
Dec 03, 2025
Examiner Interview Summary
Dec 03, 2025
Applicant Interview (Telephonic)
Jan 08, 2026
Response Filed
Mar 25, 2026
Final Rejection — §102, §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12602588
NEURAL NETWORK MODEL OPTIMIZATION METHOD BASED ON ANNEALING PROCESS FOR STAINLESS STEEL ULTRA-THIN STRIP
2y 5m to grant Granted Apr 14, 2026
Patent 12578694
INTELLIGENT MONITORING METHOD AND APPARATUS FOR ABNORMAL WORKING CONDITIONS IN HEAVY METAL WASTEWATER TREATMENT PROCESS BASED ON TRANSFER LEARNING AND STORAGE MEDIUM
2y 5m to grant Granted Mar 17, 2026
Patent 12578103
HUMIDIFIER FOR PREVENTING POLLUTION OF HUMIDIFYING WATER
2y 5m to grant Granted Mar 17, 2026
Patent 12571549
DESICCANT ENHANCED EVAPORATIVE COOLING SYSTEMS AND METHODS
2y 5m to grant Granted Mar 10, 2026
Patent 12553629
HEAT PUMP AND METHOD FOR INSTALLING THE SAME
2y 5m to grant Granted Feb 17, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

3-4
Expected OA Rounds
72%
Grant Probability
88%
With Interview (+15.9%)
2y 11m
Median Time to Grant
Moderate
PTA Risk
Based on 501 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month