Prosecution Insights
Last updated: August 17, 2026
Application No. 17/343,286

EQUILIBRIUM MODELS ACCELERATION VIA JACOBIANS STABILIZATION SYSTEMS AND METHODS

Non-Final OA §101§112
Filed
Jun 09, 2021
Examiner
CHAKI, KAKALI
Art Unit
2122
Tech Center
2100 — Computer Architecture & Software
Assignee
Robert Bosch GmbH
OA Round
3 (Non-Final)
24%
Grant Probability
At Risk
3-4
OA Rounds
0m
Est. Remaining
64%
With Interview

Examiner Intelligence

Grants only 24% of cases
24%
Career Allowance Rate
12 granted / 49 resolved
-30.5% vs TC avg
Strong +40% interview lift
Without
With
+40.0%
Interview Lift
resolved cases with interview
Typical timeline
3y 5m
Avg Prosecution
3 currently pending
Career history
70
Total Applications
across all art units

Statute-Specific Performance

§101
24.3%
-15.7% vs TC avg
§103
39.7%
-0.3% vs TC avg
§102
16.2%
-23.8% vs TC avg
§112
17.0%
-23.0% vs TC avg
Black line = Tech Center average estimate • Based on career data from 49 resolved cases

Office Action

§101 §112
DETAILED ACTION 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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on May 28, 2026 has been entered. Claims 1, 9 and 17 have been amended. 1-20 are pending and have been examined. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1 – 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Regarding claim 1, in line 14, “a corresponding amount of solver state” is unclear as to what element/value the claimed amount of solver state corresponds to. For examination purposes, the corresponding amount is interpreted as corresponding to the claimed numerical fixed-point solver. Independent claims 9 and 17 recite the same limitation in line 17 and 21 respectively, and are rejected for the reason set forth in connection with claim 1 above. Dependent claims 2-8, 10-16 and 18-20 are rejected as they do not cure the deficiency of the respective independent claims. 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. Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more. Regarding Claim 1: Step 1: Claim 1 recites a method including steps which falls into the statutory category of a process. Step 2A Prong 1: Claim 1 recites multiple mathematical processes, as explained below. computing a regularization term using a predefined quantity of random samples and the Jacobian matrix of the DEQ, at an equilibrium point z*, the regularization term penalizing the spectral radius of the Jacobian matrix to stabilize fixed-point iterations; including the regularization term in an original loss function of the DEQ to form a regularized loss function that conditions both forward and backward fixed-point systems; computing a gradient of the regularized loss function with respect to model parameters of the DEQ; and using the gradient to update the model parameters, and solving the forward and backward fixed-point systems,,, the conditioning of the forward and backward fixed-point systems bounding a number of iterations. These limitations recite the abstract idea of mathematical calculations, a mathematical concept. (MPEP 2016.4(a)(2)) Step 2A Prong 2: Claim 1 does not integrate the abstract idea into a practical application, as the additional elements of, a numerical fixed-point solver executed by one or more computing devices , performed by the numerical fixed-point solver and a corresponding amount of solver state stored in memory of the one or more computing devices merely indicate instructions to apply the judicial exception with . (MPEP 2106.05(f)). It is noted that the solver and solver state as recited and under the broadest reasonable interpretation, amount to generic computer components such as software. Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea. Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of a numerical fixed-point solver executed by one or more computing devices, performed by the numerical fixed-point solver and a corresponding amount of solver state stored in memory of the one or more computing devices do not amount to an inventive step for the reason set forth in Step 2A Prong 2.. It is noted that the solver and solver state as recited and under the broadest reasonable interpretation, amount to generic computer components such as software. Accordingly, the additional elements when taken individually and in combination, do not amount to an inventive step for the reason set forth in Step 2A Prong 2. Thus, this claim is ineligible. Regarding Claim 2, dependent upon Claim 1, recites the predefined quantity is defined for approximating a Frobenius norm of the DEQ, and further comprising regularizing the Jacobian matrix using the Frobenius norm of the Jacobian matrix, which describes a mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 3, dependent upon Claim 2, recites further comprising using a Hutchinson estimator to estimate the Frobenius norm, which describes a mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 4, dependent upon Claim 3, recites further comprising approximating the Hutchinson estimator using Monte-Carlo estimation, which further elaborates the mathematical calculation of the claim 3. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 5, dependent upon Claim 2, recites further comprising applying an upper bound on the spectral radius of the Jacobian matrix to estimate the Frobenius norm, which is directed to the abstract idea of mental process (including an observation, evaluation, judgement, opinion). The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 6, dependent upon Claim 1, recites wherein the regularization term is weighted in the regularized loss function according to a predefined coefficient, the coefficient controlling a relative importance of the regularization term in the regularized loss function, which is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion). The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 7, dependent upon Claim 1, recites an additional element of further comprising iteratively performing the operations of claim 1 for a plurality of training cycles. The additional element of claim 7 is an insignificant extra-solution activity (performing repetitive calculations) in step 2A prong 2 (MPEP 2106.05(g)), and is further considered well-understood, routine and conventional (WURC) in particular field. (MPEP 2106.05(d)(II)(ii)) in step 2B. Thus, the claim is ineligible. Regarding Claim 8, dependent upon Claim 1, recites an additional element of further comprising utilizing the DEQ for sequence prediction, language modeling, computer vision tasks, image classification, and/or semantic segmentation, which neither integrate the abstract idea into a practical application, nor provide significantly more than the abstract idea itself. Specifically, the claims recite mere instructions to apply to an exception. (MPEP 2106.05(f)) Regarding Claim 9, Step 1: Claim 9 recites a system falls into the statutory category of a machine. Step 2A Prong 1: Claim 9 recites multiple mathematical concepts, as explained below. to compute a regularization term using a predefined quantity of random samples and the Jacobian matrix of the DEQ at an equilibrium point z*, the regularization term penalizing the spectral radius of the Jacobian matrix to stabilize fixed-point iterations, include the regularization term in an original loss function of the DEQ to form a regularized loss function that conditions both forward and backward fixed- point systems, compute a gradient of the regularized loss function with respect to model parameters of the DEQ, use the gradient to update the model parameters, and solve the forward and backward fixed-point systems,,, the conditioning of the forward and backward fixed-point systems bounding a number of iterations. The claim thus recites the abstract idea of mathematical calculations, a mathematical concept. (MPEP 2016.4(a)(2)) Step 2A Prong 2: Claim 9 does not integrate the abstract idea into a practical application, as the additional elements of : system for regularized training of a Deep Equilibrium Model (DEQ), comprising: one or more computing devices programmed, a numerical fixed-point solver executed by one or more computing devices, performed by the numerical fixed-point solver and a corresponding amount of solver state stored in memory of the one or more computing devices merely indicate instructions to apply the judicial exception with . (MPEP 2106.05(f)). It is noted that the solver and solver state as recited and under the broadest reasonable interpretation, amount to generic computer components such as software. Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea. Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements when taken individually and in combination, do not amount to an inventive step for the reason set forth in Step 2A Prong 2. Thus, this claim is ineligible. Regarding Claim 10, dependent upon Claim 9, recites wherein the predefined quantity is defined for approximating a Frobenius norm of the DEQ, to regularized the Jacobian matrix using the Frobenius norm of the Jacobian matrix, which describes a mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 11, dependent upon Claim 10, recites to use a Hutchinson estimator to estimate the Frobenius norm, which is a mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 12, dependent upon Claim 11, recites to approximate the Hutchinson estimator using Monte-Carlo estimation, which further elaborates the mathematical calculation of the claim 11. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 13, dependent upon Claim 10, recites to apply an upper bound on the spectral radius of the Jacobian matrix to estimate the Frobenius norm, which is directed to the abstract idea of a mental process (including an evaluation) and/or more specifics of the mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 14, dependent upon Claim 9, recites wherein the regularization term is weighted in the regularized loss function according to a predefined coefficient, the coefficient being configured to control a relative importance of the regularization term in the regularized loss function, which is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion). The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 15, dependent upon Claim 9, recites an additional element of to iteratively perform the operations of claim 9 for a plurality of training cycles. The additional element of claim 15 is an insignificant extra-solution activity (performing repetitive calculations) in step 2A prong 2 (MPEP 2106.05(g)), and is further considered well-understood, routine and conventional (WURC) in particular field. (MPEP 2106.05(d)(II)(ii) ) in step 2B. Thus, the claim is ineligible. Regarding Claim 16, dependent upon Claim 9, recites an additional element of to utilize the DEQ for sequence prediction, language modeling, computer vision tasks, image classification, and/or semantic segmentation, which neither integrate the abstract idea into a practical application, nor provide significantly more than the abstract idea itself. Specifically, the claims recite mere instructions to apply to an exception. MPEP 2106.05(f) . Thus, the claim is ineligible. Regarding Claim 17, Step 1: Claim 17 recites a non-transitory computer-readable medium which falls into the statutory category of an article of manufacture. Step 2A Prong 1: The claim recited multiple mathematical processes, specifically : compute a regularization term using a predefined quantity of random samples and the Jacobian matrix of the DEQ at an equilibrium point z*, the regularization term penalizing the spectral radius of the Jacobian matrix to stabilize fixed-point iterations, the predefined quantity being defined for approximating a Frobenius norm of the Jacobian matrix; include the regularization term in an original loss function of the DEQ to form a regularized loss function that conditions both forward and backward fixed-point systems to regularize the Jacobian matrix using the Frobenius norm, the regularization term being weighted in the regularized loss function according to a predefined coefficient, the coefficient being configured to control a relative importance of the regularization term in the regularized loss function; compute a gradient of the regularized loss function with respect to model parameters of the DEQ; use the gradient to update the model parameters, and solve the forward and backward fixed-point systems,,, the conditioning of the forward and backward fixed-point systems bounding a number of iterations. The claim thus recites the abstract idea of mathematical calculations, a mathematical concept. (MPEP 2016.4(a)(2)) Further, the claim recites the regularization term being weighted in the regularized loss function according to a predefined coefficient, the coefficient being configured to control a relative importance of the regularization term in the regularized loss function, which is directed to the abstract idea of a mental process (including an evaluation and/or judgement,) which can be performed in the human mind, or by a human using pen and paper. (MPEP 2106.04(a)(2)) . Therefore, the claim recites a judicial exception (mathematical concept and mental process). Step 2A Prong 2: Claim 17 does not integrate the abstract idea into a practical application, as the additional elements of A non-transitory computer-readable medium comprising instructions for regularized training of a Deep Equilibrium Model (DEQ) that, when executed by one or more computing devices, cause the one or more computing device to perform operations, and a numerical fixed-point solver executed by one or more computing devices, performed by the numerical fixed-point solver and a corresponding amount of solver state stored in memory of the one or more computing devices merely indicate instructions to apply the judicial exception with . (MPEP 2106.05(f)). It is noted that the solver and solver state as recited and under the broadest reasonable interpretation, amount to generic computer components such as software. Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea. Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements when taken individually and in combination, do not amount to an inventive step for the reason set forth in Step 2A Prong 2. Thus, this claim is ineligible. Regarding Claim 18, dependent upon Claim 17, recites to use a Hutchinson estimator to estimate the Frobenius norm, which describes a mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 19, dependent upon Claim 17, recites to apply an upper bound on the spectral radius of the Jacobian matrix to estimate the Frobenius norm, which is directed to the abstract idea of a mental process (including an evaluation) and/or more specifics of mathematical calculation. The claim does not include additional elements that are sufficient to amount to an integration of the abstract idea into practical application or significantly more than the judicial exception. Thus, the claim is ineligible. Regarding Claim 20, dependent upon Claim 17, this claim recites an additional element, namely, to utilize the DEQ for sequence prediction, language modeling, computer vision tasks, image classification, and/or semantic segmentation, which neither integrate the abstract idea into a practical application, nor provide significantly more than the abstract idea itself. Specifically, the claims recite mere instructions to apply to an exception. MPEP 2106.05(f). Thus, the claim is ineligible. Response to Arguments Applicant's arguments filed 10/10/2025 regarding the rejection of claims 1-20 under 35 USC 101 have been fully considered but they are not persuasive. Specifically, applicant argues in substance: i) That the Specification provides for an improvement in computer functions and the claims recite the components or steps that provide the improvement. In particular, Applicant points to the description in Specification, [0023]-[0025], where the purported improvement is disclosed. Applicant specifically points to claim limitations "solving the forward and backward fixed-point systems with a numerical fixed-point solver executed by the computing device, the conditioning of the forward and backward fixed-point systems bounding a number of iterations performed by the numerical fixed-point solver and a corresponding amount of solver state stored in memory of the one or more computing devices." as reciting the improvement in computer function, similar to Enfish and McRO. Examiner’s response: Examiner respectfully disagrees. As noted in the previous Office Action, the features, as described in the specification, (e.g. "a regularization scheme for DEQ models…explicitly regularizes the Jacobian…to encourage simpler and stabler equilibrium networks being learned" where " to regularize training by instead adding a new component to the loss function … leading to better conditioned fixed-point systems," and further where "[t]his regularization may add only minimal computational cost, but significantly accelerates the fixed-point-solving convergence...". cited by Applicant) are simply improved mathematical functions described only as usable in training a DEQ model. The cited sections of the specification do not describe an improved computer function or another technology such as the process of improved memory access in Enfish , or facial recognition technology in McRO. Unlike the improvements in Enfish and McRO, the improvement described in the specification as cited and asserted by applicant is only an improvement in an abstract idea. In response to Applicant’s assertion that claim limitations "solving the forward and backward fixed-point systems with a numerical fixed-point solver executed by the computing device, the conditioning of the forward and backward fixed-point systems bounding a number of iterations performed by the numerical fixed-point solver and a corresponding amount of solver state stored in memory of the one or more computing devices." as reciting the improvement in computer function, it is noted that the claims as amended, do not positively recite or reflect any improvement in computer functionality or another technology. As pointed out in the rejection in this Office action, the limitations regarding the execution of the fixed-point solver and the solver states amount to invoking computers merely as a tool to perform an existing process, in accordance with MPEP 2106.05(f)(2). As stated in this section, use of a computer or other machinery in its ordinary capacity, or simply adding a general-purpose computer or computer components after the fact does not integrate a judicial exception into a practical application or provide significantly more. The limitation of solver state stored in memory does not amount to a positive recitation of improved computer function such as configuring a memory according to a logical table. Here, the claim only recites that the solver is stored in memory, and does not recite nor reflect any improved computer functionality such as software execution or memory configuration/access. Therefore the claims are ineligible. ii)Under Step 2B, in addition to the aforementioned reasons, the ordered combination, including penalizing the spectral radius of the Jacobian at z* to condition both fixed-point systems, is not well-understood, routine, or conventional in DEQ training. Examiner’s Response: In response, Examiner notes that as indicated in the rejection, the feature of penalizing the spectral radius is part of a mathematical calculation, an abstract idea. Therefore, the consideration of whether it is well-understood, routine, or conventional, a consideration under step 2B, does not apply to this limitation. Applicant has not provided any persuasive reasons why this limitation is not an abstract idea. Therefore, examiner maintains the position that this is an abstract idea. Based on the above, the rejection of claims 1-20 is proper and maintained hereby. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Kakali Chaki whose telephone number is (571)272-3719. The examiner can normally be reached on Mondays through Fridays from 10 am to 5 pm. 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, David Wiley can be reached on 571-272-4150. 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. /KAKALI CHAKI/Supervisory Patent Examiner, Art Unit 2122
Read full office action

Prosecution Timeline

Show 1 earlier event
Apr 14, 2025
Non-Final Rejection mailed — §101, §112
Oct 10, 2025
Response Filed
Jan 28, 2026
Final Rejection mailed — §101, §112
Apr 27, 2026
Examiner Interview Summary
Apr 27, 2026
Applicant Interview (Telephonic)
May 28, 2026
Request for Continued Examination
Jun 03, 2026
Response after Non-Final Action
Jul 01, 2026
Non-Final Rejection mailed — §101, §112 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

3-4
Expected OA Rounds
24%
Grant Probability
64%
With Interview (+40.0%)
3y 5m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 49 resolved cases by this examiner. Grant probability derived from career allowance rate.

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