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 .
Amendments
This action is in response to amendments filed August 7th, 2026, in which Claims 22, 26, and 29-32 are amended. The amendments have been entered, and Claims 21-32 are currently pending.
Claim Objections
Claim 26 is objected to because of the following informalities: Claim 26 recites the trained neural n network model. This appears to be a typographical error.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim 21 -32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 21 recites an apparatus comprising: processor circuitry, thus an article of manufacture, one of the four statutory categories of patentable subject matter. However, the claim further recites a step to convert [a] trained neural network model to an optimized model comprising parameters that are fit to an execution platform, which is a mental process capable of performance in the human mind (i.e. choosing weight connections to prune or converting weights from floating point to fixed point values). Thus, the claim recites an abstract idea of converting a neural network model to an optimized model.
The claim does not recite any additional elements which could integrate the abstract idea into a practical application, because the additional elements consist of:
circuitry to perform the mental process step, and performance of an abstract idea on generic computer components cannot integrate the abstract idea into a practical application (MPEP 2106.05(f)(2))
to receive a trained neural network model which is insignificant extra-solution activity of data gathering necessary for all uses of the abstract idea (MPEP 2106.05(g))
neither of which can integrate the abstract idea into a practical application. Thus, the claim is directed towards the abstract idea of converting a neural network model to an optimized model.
Finally, the additional elements, taken alone and in combination, do not recite significantly more than the abstract idea itself, because implementation on generic computer components cannot provide an inventive concept (MPEP 2106.05(f)(2)), because receiving data is well-understood, routine, and conventional (MPEP 2106.05(d), transmitting and receiving data over a network), and because there is no nexus between the additional elements that could provide an inventive concept. Thus, the claim is subject-matter ineligible.
Claim 22, dependent upon Claim 21, recites an additional mental process step of the abstract idea (to prune one or more nodes from the neural network model is merely determining a connection status in the model), but no new additional elements, thus the claim recites no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claim 23, dependent upon Claim 21, recites an additional mental process step of the abstract idea (to reorder one or more operations in the neural network model is merely determining a format of the model), but no new additional elements, thus the claim recites no additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself.
Claim 24, dependent upon Claim 21, only recites details of the particular execution platform for which the neural network is optimized; that is, limits the particular technological environment or field of use in which the abstract idea is performed, or the information used in the abstract idea. Field of use limitations cannot integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself (MPEP 2106.05(h)), and thus the claim is ineligible.
Claims 25-28 recite precisely the methods performed by the apparatus of Claims 21-24, respectively, and are thus rejected for reasons set forth in the rejections of those claims, respectively. Claims 29-32 recite at least one computer-readable medium having stored thereon instructions to cause a computing device such as the apparatus of Claims 21-24 to perform those methods. As execution of an abstract idea using generic computer components can neither integrate the abstract idea into a practical application nor provide an inventive concept (MPEP 2106.05(f)(2)), Claims 29-32 are rejected for reasons set forth in the rejections of Claims 21-24, respectively.
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.
Claims 21, 22, 24; 25, 26, 28; and 29, 30, and 32 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Brothers, US PG Pub 2016/0358070, cited by the applicant in the IDS dated 12/15/2023.
Regarding Claim 21, Brothers teaches an apparatus comprising: processor circuitry (Brothers, [0006], “an apparatus for tuning a neural network. The apparatus includes a memory storing code and a processor”) to: receive a trained neural network model in a model optimizer circuitry (Brothers, Fig. 3, element 305, “Receive a first neural network”); and convert the trained neural network model to an optimized model comprising parameters that are fit to an execution platform of the apparatus (Brothers, [0022], “systems to modify and/or optimize neural network are described herein that automatically tune neural network parameters to achieve required performance. The term “performance” may be used herein in describing certain aspects of operation of a neural network such as accuracy … of the neural network as implemented and/or executed for a target application on target hardware”).
Regarding Claim 22, Brothers teaches the apparatus of Claim 21 (and thus the rejection of Claim 21 is incorporated). Brothers further teaches to: prune one or more nodes from the trained neural network model (Brothers, [0046], “Examples of different modification types that may be applied to the first neural network include … pruning”).
Regarding Claim 24, Brothers teaches the apparatus of Claim 21 (and thus the rejection of Claim 21 is incorporated). Brothers further teaches wherein the execution platform comprises processing resources on a single integrated circuit (Brothers, [0035], “target hardware such as a neural network accelerator 265 [which] may be implemented as an integrated circuit”).
Claims 25, 26, and 28 recite precisely the methods performed by the apparatus of Claims 21, 22, and 24, respectively, and are thus rejected for reasons set forth in the rejections of those claims, respectively. Claims 29, 30, and 32 recite at least non-transitory one computer-readable medium having stored thereon instructions which, when executed, cause a computing device to perform the operations performed by the apparatus of Claims 21, 22, and 24, respectively. As Brothers teaches such a medium (Brothers, [0007], “a computer readable storage medium having program code stored thereon for tuning a neural network”), Claims 29, 30, and 32 are rejected for reasons set forth in the rejections of Claims 21, 22, and 24, respectively.
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.
The factual inquiries 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 23, 27, and 31 are rejected under 35 U.S.C. 103 as being unpatentable over Gysel, in view of Daultani et al., “Convolutional Neural Network Layer Reordering for Acceleration.”
Regarding Claim 23, Brothers teaches the apparatus of Claim 21 (and thus the rejection of Claim 21 is incorporated). Brother does not teach to: reorder one or more operations in the trained neural network model, but Daultani teaches this limitation (Daultani, title, “Convolutional Neural Network Layer Reordering for Acceleration”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply the layer reordering algorithm of Daultani to the neural network optimizer of Brothers. The motivation to do so is that “using the proposed reordering, we can reduce the total time … on CPU [and] GPU”).
Claim 27 recites precisely the method performed by the apparatus of Claim 23, and is thus rejected for reasons set forth in the rejection of Claim 23. Claim 31 recites at least one computer-readable medium having stored thereon instructions which, when executed, cause a computing device to perform the operations performed by the apparatus of Claim 23. As Brothers teaches such a medium (Brothers, [0007], “a computer readable storage medium having program code stored thereon for tuning a neural network”), Claim 31 is rejected for reasons set forth in the rejection of Claim 23.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21, 25, and 29 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 13 of copending Application No. 18/571,150(reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because Claim 13 recites to receive a trained neural network model and convert the trained neural network model to an optimized model comprising parameters (Reference Application, Claim 13, “converting a conventional precision inference model to an optimized inference model”) that are fit to an execution platform (Reference Application, Claim 13, “a hardware-aware cost model ... based on the hardware specifications … convert … based on the result of the performance simulation”). It would have been obvious to one of ordinary skill in the art to perform the method of reference Claim 13 on a computer, thus teaching the apparatus and computer-readable medium limitations of Claims 21 and 29, as well.
Claims 22, 24, 26, 28, 30, and 32 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 13 of copending Application No. 18/571,150(reference application), in view of Brothers. Although the claims at issue are not identical, they are not patentably distinct from each other because a) the claims depend on independent claims which are unpatentable over Claim 13 and b) Brothers teaches both pruning (Brothers, [0046]) and implementing the neural network on a single integrated circuit (Brothers, [0035]). It would have been obvious to one of ordinary skill in the art to make these modifications to reference Claim 13 because both pruning and execution on an integrated circuit platform improve execution speed.
Claims 23, 27, and 31 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 13 of copending Application No. 18/571,150(reference application), in view of Daultani. Although the claims at issue are not identical, they are not patentably distinct from each other because a) the claims depend on independent claims which are unpatentable over Claim 13 and b) Daultani teaches reordering. It would have been obvious to one of ordinary skill in the art to apply the layer reordering algorithm of Daultani to the neural network optimizer of reference Claim 13. The motivation to do so is that “using the proposed reordering, we can reduce the total time … on CPU [and] GPU”).
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Response to Arguments
Applicant’s arguments filed August 7th, 2026 have been fully considered, but are not fully persuasive.
Applicant’s amendments have overcome the objection to the specification and the 35 U.S.C. 112(b) rejection of the previous office action. Claim 26 is objected to as containing what appears to be a typographical error.
Applicant’s arguments regarding the 35 U.S.C. 101 rejections of the claimed invention have been fully considered, but are not fully unpersuasive.
Due to claim amendment, the rejections of Claims 29-32 as not falling into any of the four statutory categories has been withdrawn.
Applicant first argues, with respect to the rejection of Claim 21 as directed to an abstract idea without significantly more, by pointing to examples within the specification. However, limitations from the specification cannot be read into the claims. Further, mere assertion of an improvement in technology (for example, implementing an optimized model without reciting any of the steps which achieve the optimization) is merely claiming the idea of a solution, which by MPEP 2106.05(f)(1) cannot provide an improvement in technology. Further, merely citing examples from the specification which cannot be performed in the human mind does not address the scope of the broadest reasonable interpretation of the claims – citing to “quantizing per IP, generating sparse CPU-optimized code, and transforming kernels” (even if it were agreed that none of these can be performed in the human mind – a human can definitely generate code) – does not address the fact that the claim scope clearly includes embodiments which are mental processes. Such examples are noted in the rejection. Applicant’s arguments regarding the other independent claims and dependent claims rely on the same features of Claim 21, and are thus also unpersuasive.
Applicant’s arguments regarding the prior art rejections of the claims have been fully considered, but are unpersuasive.
Applicant appears to argue that Brothers does not teach receiving a trained neural network model in model optimizer circuitry. However, Brothers clearly implements their model in a computer, and optimizes the model, so Brothers element 305, “Receive a first neural network” is receiving a trained neural network model in optimizer circuitry (in the Neural Network Analyzer of Fig. 1, to be precise). Brothers optimizes the model for a particular execution platform (see [0022], “target hardware” and related description of what optimization for particular target hardware means). Brothers clearly teaches all of the required claim elements, in the recited combination. Applicant may be arguing (based on the use of the word “offline”) that the “target hardware” is not “an execution platform of the apparatus” but “apparatus” can clearly be mapped to any set of elements recited in the prior art (i.e. the neural network analyzer in combination with the target hardware is an apparatus). This clearly falls within the scope of the disclosed invention, see [00277] of the instant application. Alternatively, any target hardware to which the apparatus is applied is “an execution platform of the apparatus” because the apparatus operates concerning that platform.
Applicant’s arguments regarding the other independent claims and dependent claims rely on the same features of Claim 21, and are thus also unpersuasive.
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 BRIAN M SMITH whose telephone number is (469)295-9104. The examiner can normally be reached Monday - Friday, 8:00am - 4pm Pacific.
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, Kakali Chaki can be reached at (571) 272-3719. 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.
/BRIAN M SMITH/Primary Examiner, Art Unit 2122
Prosecution Insights