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 non-Final office action in merits. Claims 1-20, as originally filed, 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 Objections
Claims 1 and 20 are objected to because of the following informalities:
Claim 1 recites: ”assigning, by device, priorities to each of the outputs of the nodes” in which “device” appears to be “the device” for a proper antecedent basis. Similar limitation is recited in claim 20 and it is rejected with the same reason.
Appropriate correction is required.
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 2022/0222531 A1, Tomioka et al. (hereinafter Tomioka).
As to claim 1, Chowdhery discloses a method comprising: generating, by a 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 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.
Nevertheless, Ismailsheriff, in the same or similar field of endeavor, further teaches 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, among other criteria (pars 0023, 0114, 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 (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’s teachings in Chowdhery’s method to provide a neural network system architected/configured in a distributed manner for more efficient resources utilization and implementation.
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 he 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 12-18, they are rejected with the same reason as set forth in claims 2-8, respectively.
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.
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.
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/QUN SHEN/
Primary Examiner, Art Unit 2662
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