Prosecution Insights
Last updated: October 02, 2026
Application No. 18/368,790

COMMUNICATION-AWARE INFERENCE SERVING FOR PARTITIONED NEURAL NETWORKS

Final Rejection §103§112
Filed
Sep 15, 2023
Examiner
SHEN, QUN
Art Unit
2662
Tech Center
2600 — Communications
Assignee
Cisco Technology Inc.
OA Round
2 (Final)
76%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allowance Rate
593 granted / 776 resolved
+14.4% vs TC avg
Strong +38% interview lift
Without
With
+37.5%
Interview Lift
resolved cases with interview
Typical timeline
2y 10m
Avg Prosecution
41 currently pending
Career history
802
Total Applications
across all art units

Statute-Specific Performance

§101
3.0%
-37.0% vs TC avg
§103
64.9%
+24.9% vs TC avg
§102
9.1%
-30.9% vs TC avg
§112
17.5%
-22.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 776 resolved cases

Office Action

§103 §112
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 . DETAILED ACTION This communication is a Final office action in merits. Claims 1-20, after amendment, are presently pending and have been elected and considered below. Information Disclosure Statement The information disclosure statement (IDS) submitted on 9/15/2023 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 § 103 The following is a quotation of the first paragraph of 35 U.S.C. 112(a): (a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention. The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112: The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention. Claim 18 is rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. Claim 18 recites: The apparatus as in claim 11, wherein the processor is further configured to: determine one or more network connection characteristics for a connection between the apparatus and the remote device; wherein the processor is configured to select the subset of the outputs to send to the remote device based on the one or more network connection characteristics. Examiner fails to find sufficient support from original specification for the recited limitations. 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 of this title, 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. The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. 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. Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over US 2022/0253672 A1, Chowdhery et al. (hereinafter Chowdhery) in view of US 2021/0092068 A1, Ismailsheriff et al. (hereinafter Ismailsheriff) and further in view of US 2022/0222531 A1, Tomioka et al. (hereinafter Tomioka). As to claim 1, Chowdhery discloses a method comprising: performing, by a device, inference by executing an upstream layer of a partitioned neural network (Fig 3; pars 0071-0072, 0075-0076, 0085, 0143, the inference being implemented in the attention neural network in parallel across multiple hardware devices (e.g. partitioned) and the output of inference being delivered to a upstream layer (e.g. any hidden layers between inference and outputs, output layer of the neural network); generating, by the device, outputs of nodes in an upstream layer of a partitioned neural network (Fig 1, 4A-4B; pars 0080, 0133-0135, 0137, a neural network with sparce attention being partitioned with outputs of intermediate layers passing to next upstream layer); assigning, by the device, priorities to each of the outputs of the nodes (Fig 2; pars 0083, 0122, each of the outputs of the nodes being assigned based on rank identified); selecting, by the device and based on the priorities, a subset of the outputs to send to a remote device (Fig 2; pars 0083, 0122). Chowdhery does not expressly disclose the subset of the output being sent to a remote device over a computer network for input to a downstream layer of the partitioned neural network. Chowdhery, however, teaches a client and server may be generally remote from each other interacting through a communication network. The client and server may partition or share computation operations in order or in parallel to achieve more desirable results (pars 0153-0156). Nevertheless, Ismailsheriff, in the same or similar field of endeavor, also teaches clients/devices and servers as endpoints with distributed datasets and operations/processes in parallel for resources allocation (pars 0038, 0117-0118, 0120-0121, 0127, 0144), as well as assigning priorities to each of the outputs of the nodes by computer/network device depending on the network resources handling the data traffic and/or quality level between server, among other criteria (pars 0023, 0114, 0144, 0155, Tables 3, 7). Additionally, Tomioka, in the same or similar field of endeavor, teaches the subset of the output being sent to a remote device over a computer network for input to a downstream layer of the partitioned neural network that is executed by the remote device (Figs 1-2; pars 0027, 0029-0033, 0036, 0093, a partitioned neural network being implemented in a distribution manner with layers of the neural network being cross over a network of nodes resided remotely) Therefore, consider Chowdhery, Ismailsheriff, and Tomioka’s teachings as a whole, it would have been obvious to one of skill in the art before the filing date of invention to incorporate Ismailsheriff and Tomioka’s teachings in Chowdhery’s method to provide a neural network system in a distributed manner for more efficient resources utilization and implementation according to the neural network architecture, configuration, and/or resources allocation and optimization. As to claim 2, Chowdhery as modified discloses the method as in claim 1, wherein the device selects the subset of the outputs to send to the remote device based further on a latency associated with a path between the device and the remote device in the computer network (Chowdhery: pars 0006, 0008-0009, 0076-0077; Ismailsheriff: pars 0022-0023, 0068, 0075, meeting the latency requirement/threshold). As to claim 3, Chowdhery as modified discloses the method as in claim 2, further comprising: opting, by the device, to send all outputs of the nodes in the upstream layer to the remote device when the latency is below a threshold (Chowdhery: pars 0008-0009, 0075; Ismailsheriff: Fig 4; pars 0022-0024, 0068, 0103, 109, a choice of design to balance latency vs resource distribution). As to claim 4, Chowdhery as modified discloses the method as in claim 1, further comprising: performing knockout to determine accuracy losses associated with blocking outputs of each of the nodes in the upstream layer of the partitioned neural network (Chowdhery: Fig 2s, 4B, performing knockout by zeroing some of inputs/outs in the partitioned neural network; pars 0070, 0078-0080, 0084, 0086, 0089, the loss being quantified via loss functions; Ismailsheriff: pars 0132, 0136-0137, 0140). As to claim 5, Chowdhery as modified discloses the method as in claim 4, wherein the priorities are based on the accuracy losses (Chowdhery: par 0070; Ismailsheriff: pars 0022, 0110, based on performance including loss on accuracy). As to claim 6, Chowdhery as modified discloses the method as in claim 1, wherein the partitioned neural network is configured to analyze sensor data captured by one or more sensors in the computer network (Ismailsheriff: pars 0036, 0114, sensor data analysis). As to claim 7, Chowdhery as modified discloses the method as in claim 6, wherein the sensor data comprises video data captured by one or more cameras in the computer network (Ismailsheriff: pars 0036, 0116, sensors including cameras). As to claim 8, Chowdhery as modified discloses the method as in claim 1, wherein the priorities are based on a mean and standard deviation of the outputs of the nodes in the upstream layer (Ismailsheriff: Tables 1, 4, par 0146, means and standard deviation). As to claim 9, Chowdhery as modified discloses the method as in claim 1, wherein the device selects the subset of the outputs to send to the remote device based on one or more policies (Ismailsheriff: pars 0015, 0023, 0026-0029, 0032; Tomioka: Figs 1-2; pars 0027, 0029-0033, 0036, 0093). As to claim 10, Chowdhery as modified discloses the method as in claim 1, further comprising: inputting, by the device, outputs of a prior layer of the partitioned neural network to the upstream layer of the partitioned neural network (Chowdhery: Figs 1-2, 4; Tomioka: Figs 1-2). As to claim 11, it is an apparatus claim encompassed claim 1. Rejection of claim 1 is therefore incorporated herein. As to claims 12-17, they are rejected with the same reason as set forth in claims 2-7, respectively. As to claim 18, Chowdhery as modified discloses the apparatus as in claim 11, wherein the processor is further configured to: determine one or more network connection characteristics for a connection between the apparatus and the remote device (Chowdhery: pars 0152-0154; Ismailsheriff: Figs 1, 3, indicating characteristic of communication network among the apparatus and the remote device over the network; pars 0015, 0025-27, 0029-0032); wherein the processor is configured to select the subset of the outputs to send to the remote device based on the one or more network connection characteristics (Chowdhery: pars 0033, 0035-0036, 0054-0055, 0067; Ismailsheriff: Fig 5; pars 0098-0099, 0103, 0122, 0133-0134). As to claim 19, it is rejected with the same reason as set forth in claim 10. As to claim 20, it recites a non-transitory CRM storing instructions executed to perform functions and features of claim 1. Rejection of claim 1 is therefore incorporated herein. Response to Arguments Applicant’s arguments have been considered but they are not persuasive. Additional citations have been provided for amended limitations as well as further articulations addressing applicant’s concern. For details, see citations and rationales indicated in merit rejection above. Applicant is encouraged to further clarify and distinguish from prior art of record. 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. Examiner’s Note Examiner has cited particular column, line number, paragraphs and/or figure(s) in the reference(s) as applied to the claims for the convenience of the Applicant. Although the specified citations are representative of the teachings of the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the reference(s) in entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner. Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to QUN SHEN whose telephone number is (571)270-7927. The examiner can normally be reached on Mon-Fri 8:30-5:50 PT. 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, Amandeep Saini can be reached on 571-272-3382. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /QUN SHEN/ Primary Examiner, Art Unit 2662
Read full office action

Prosecution Timeline

Sep 15, 2023
Application Filed
Dec 31, 2025
Non-Final Rejection mailed — §103, §112
Mar 18, 2026
Interview Requested
Mar 30, 2026
Response Filed
Mar 30, 2026
Applicant Interview (Telephonic)
Mar 30, 2026
Examiner Interview Summary
Jul 15, 2026
Final Rejection mailed — §103, §112
Sep 14, 2026
Interview Requested

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Prosecution Projections

3-4
Expected OA Rounds
76%
Grant Probability
99%
With Interview (+37.5%)
2y 10m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 776 resolved cases by this examiner. Grant probability derived from career allowance rate.

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