Prosecution Insights
Last updated: July 17, 2026
Application No. 18/061,305

METHOD AND SYSTEM FOR OPTIMIZING QUANTIZATION MODEL

Final Rejection §101
Filed
Dec 02, 2022
Priority
Dec 03, 2021 — RE 10-2021-0171945 +1 more
Examiner
BEAN, GRIFFIN TANNER
Art Unit
2121
Tech Center
2100 — Computer Architecture & Software
Assignee
Nota Inc.
OA Round
2 (Final)
25%
Grant Probability
At Risk
3-4
OA Rounds
9m
Est. Remaining
46%
With Interview

Examiner Intelligence

Grants only 25% of cases
25%
Career Allowance Rate
7 granted / 28 resolved
-30.0% vs TC avg
Strong +21% interview lift
Without
With
+21.4%
Interview Lift
resolved cases with interview
Typical timeline
4y 4m
Avg Prosecution
25 currently pending
Career history
68
Total Applications
across all art units

Statute-Specific Performance

§101
9.1%
-30.9% vs TC avg
§103
82.2%
+42.2% vs TC avg
§102
6.1%
-33.9% vs TC avg
§112
2.6%
-37.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 28 resolved cases

Office Action

§101
DETAILED ACTION This Action is responsive to Claims filed 02/27/2026. 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 . Status of the Claims Claims 1-5, 7-10, and 12-17 have been amended. Claim 19 is new. Claims 1-19 are currently pending. Response to Amendment The amendments to Claim 12 are acknowledged. The amendments overcome the Objections to Informalities. Response to Arguments Applicant's arguments, see Pages 9-11, filed 02/27/2026, regarding the 35 U.S.C. 101 Rejection of Claims 1-18 have been fully considered but they are not persuasive. The Applicant argues on Page 9 that the newly amended limitation “…generated by a deep learning compiler…” is not practically performed within the human mind. The Examiner agrees with the Applicant that human mind is not equipped to generate a quantization model by a deep learning compiler. However, when read in the context of the limitation as a whole, the pre-generated model is merely generically received, a limitation found to be mere data-gathering in the Non-Final Office Action. How this pre-generated model was created does not change the interpretation of the limitation. As presently drafted, the BRI of a model may include a system of equations and/or its outputs, and is not exclusively tied to a computing environment or implementation precluding a human mind from performing the interpretable abstract idea mental process steps. The computing environment recited in the claims, including the newly-amended “compiler,” are recited highly generally, and amount to generic computer components performing the interpretable abstract idea mental process steps. Given the BRI of a “model,” the Examiner submits a human mind with or without the aid of pen and paper is capable of performing the series of algorithmic steps recited in the independent claims interpretable as abstract idea mental process steps. The BRI of “parse” does not preclude a human mind with or without the aid of pen and paper from performing the limitation. The generic use of “file” also does not preclude a human mind with or without the aid of pen and paper from generically “parsing” it. As to the Applicant’s arguments regarding Claim 7 on Pages 10 and 11, the Examiner again points to the BRI of a “model” not precluding the human mind from performing the claimed steps, especially when the generating is merely tied to a generic processor performing the claimed steps. See the updated 35 U.S.C. 101 Rejection below. Applicant’s arguments, see Pages 11-16, filed 02/27/2026, with respect to Claims 1-18 have been fully considered and are persuasive. The 35 U.S.C. 103 Rejection(s) of Claims 1-18 have been withdrawn. Further citation of relevant prior art is included below. Claim Rejections - 35 USC § 101 The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action. Claims 1-19 rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more; and because the claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than the abstract idea, see Alice Corporation Pty. Ltd. v. CLS Bank International, et al, 573 U.S. (2014). In determining whether the claims are subject matter eligible, the Examiner applies the 2019 USPTO Patent Eligibility Guidelines. (2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, Jan. 7, 2019.) Step 1: Claims 1-6 and 19 recite a method of optimizing a quantization model, which falls under the statutory category of a process. Claims 7-12 recite a method of optimizing a quantization model performed by a computer device comprising at least one processor, which would fall under the statutory category of a process. Claims 13-18 recite a computer device comprising: at least one processor configured to execute a computer-readable instruction on the computer device, which falls under the statutory category of a machine. Step 2A – Prong 1: Claim 1 recites an abstract idea, law of nature, or natural phenomenon. The limitations of “parsing, by the at least one processor, the file of the quantization model to extract i) a weight of each layer of the quantization model included in the file and/or an activation value being an output of said each layer, and ii) a quantization parameter related to the weight and/or the activation value, wherein the extracted quantization parameter includes a scale factor and a zero point stored in the file;”, “selecting, by the at least one processor, at least one of the weight and the activation of the input quantization model as a target element to be modified;”, “calculating, by the at least one processor, a clipping range associated with a target quantization parameter related to the target element based on a scale factor and a zero point included in the target quantization parameter;”, “adjusting, by the at least one processor, the calculated clipping range related to the quantization parameter of the target element;”, “recomputing, by the at least one processor, the quantization parameter of the target element based on the adjusted clipping range, wherein the recomputed quantization parameter includes a scale factor and a zero point recomputed based on the adjusted clipping range;”, and “generating, by the at least one processor, an adjusted quantization model by applying the recomputed quantization parameter to the quantization model, wherein the recomputed scale factor and zero point are reflected and stored in the file.” under the broadest reasonable interpretation, cover a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. Parsing a generically recited file in order to extract a weight and quantization parameter is practically performed within the human mind or with the aid of pen and paper. Selecting the weight and/or the activation as a target is practically performed within the human mind or with the aid of pen and paper. Calculating a clipping based on the selected target amounts to a series of algorithmic steps practically performed within the human mind or with the aid of pen and paper. Adjusting the clipping range is practically performed within the human mind or with the aid of pen and paper. Recomputing the quantization parameter based on the adjusted clipping range amounts to series of algorithmic steps practically performed within the human mind or with the aid of pen and paper. Generating a generically recited model and generically storing the recomputed values in a generically recited file are practically performed within the human mind or with the aid of pen and paper. Step 2A – Prong 2: The additional elements of claim 1 do not integrate the abstract idea into a judicial exception. The claim recites the additional elements “a computer device comprising at least one processor”, “a file”, and “compiler” which are recognized as generic computer components recited at a high level of generality. Although they have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." (See MPEP 2106.04(d)(2) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application). The additional elements of “a quantization model”, “a weight and an activation, and a quantization parameter”, “a clipping range”, and “an adjusted quantization model” are recognized as non-generic computer components, but are recited at a high level of generality and are found to generally link the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)). The additional elements recited in the limitation of “receiving, by the at least one processor, a file including a pre-generated quantization model including pre-determined quantization parameters, the quantization model being generated by a deep learning compiler;” is found to be mere pre- or post-extra-solution or data transmittal steps (See MPEP 2106.05(g)). Step 2B: The additional elements of claim 1 do not amount to more than the judicial exception. The only limitation on the performance of the described method is a limitation reciting “a computer device comprising at least one processor”, “a file”, and “compiler”. These elements are insufficient to transform a judicial exception to a patentable invention because the recited elements are considered insignificant extra-solution activity (generic computer system, processing resources, links the judicial exception to a particular, respective, technological environment). The claim thus recites computing components only at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components; mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (see MPEP 2106.05(f)). The additional elements of claim 1 do not integrate the abstract idea into a judicial exception. The claim recites the additional elements “a quantization model”, “a weight and an activation, and a quantization parameter”, “a clipping range”, and “an adjusted quantization model” are recognized as non-generic computer components, but are recited at a high level of generality and are found to generally link the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)). The additional elements recited in the limitations “receiving, by the at least one processor, a file including a pre-generated quantization model including pre-determined quantization parameters, the quantization model being generated by a deep learning compiler;” are recognized as well-understood, routine, or conventional activity (See MPEP 2106.05(d)(II)(i) first list). Taken alone or in ordered combination, these additional elements do not amount to significantly more than the above-identified abstract idea. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. For the reasons above, claim 1 is rejected as being directed to non-patentable subject matter under §101. This rejection applies equally to independent claims 7 and 13. Claim 7 recites similar limitations to Claim 1, in addition to the abstract idea mental process steps “generating, by the at least one processor, a plurality of deep learning models by modifying the extracted quantization parameter of the quantization model;”, “measuring, by the at least one processor, an accuracy of each of the plurality of deep learning models by applying a representative dataset generated in advance to represent an arbitrary environment to each of the plurality of deep learning models;”, and “determining, by the at least one processor, one of the plurality of deep learning models as an optimized quantization model for the arbitrary environment based on the measured accuracy” Claim 13 recites similar limitations to claim 1, with the exception of “A computer device comprising: at least one processor configured to execute a computer-readable instruction on the computer device, wherein the at least one processor is configured to,” (generic computer components). Dependent Claims: Claim 2 (claims 8 and 14) recites an abstract ide amental process step “selecting the target element for each channel or for each layer of the quantization model.” Claim 3 (claims 9 and 15) recites an abstract ide amental process step “adjusting the calculated clipping range by increasing or decreasing at least one of a minimum value and a maximum value of the calculated clipping range.” Claim 4 (claims 10 and 16) recites an abstract ide amental process step “recomputing a scale factor and a zero point as the recomputed quantization parameter according to the adjusted clipping range.” Claim 5 (claim 17) recites an abstract idea mental process step “wherein the selecting at least one of the weight and the activation, the adjusting the calculated clipping range and the recomputing the quantization parameter of the target element are iteratively performed.” Claim 6 (claim 18) recites an abstract idea mental process step “determining the recomputed quantization parameter among a plurality of candidate quantization parameters obtained by iteratively performing the selecting, the adjusting and the recomputing.” Claim 11 recites refinements to the abstract idea mental process steps of Claim 7. Claim 12 recites an abstract idea mental process step “wherein the measuring the accuracy and the determining as the optimized quantization model are iteratively performed with different representative datasets generated in advance to represent different environments.” Claim 19 recites abstract idea mental process steps “selecting one of a first mode of performing a process of recomputing the quantization parameter of the target element a single time or a second mode of iteratively performing the process of recomputing the quantization parameter of the target element a plurality of times, based on availability of training data or validation data;” and “performing the process of recomputing the quantization parameter according to the selected mode.” Allowable Over the Prior Art The Examiner submits Claims 1-19 are allowable over the prior art. 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 GRIFFIN T BEAN whose telephone number is (703)756-1473. The examiner can normally be reached M - F 7:30 - 4:30. 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, Li Zhen can be reached at (571) 272-3768. 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. /GRIFFIN TANNER BEAN/Examiner, Art Unit 2121 /Li B. Zhen/Supervisory Patent Examiner, Art Unit 2121
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Prosecution Timeline

Dec 02, 2022
Application Filed
Nov 28, 2025
Non-Final Rejection mailed — §101
Feb 27, 2026
Response Filed
Jun 09, 2026
Final Rejection mailed — §101 (current)

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Prosecution Projections

3-4
Expected OA Rounds
25%
Grant Probability
46%
With Interview (+21.4%)
4y 4m (~9m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 28 resolved cases by this examiner. Grant probability derived from career allowance rate.

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