Prosecution Insights
Last updated: October 02, 2026
Application No. 17/637,890

ROBUST ARTIFICIAL NEURAL NETWORK HAVING IMPROVED TRAINABILITY

Non-Final OA §101
Filed
Feb 24, 2022
Priority
Sep 11, 2019 — DE 10 2019 213 898.5 +1 more
Examiner
THOMPSON, KYLE ALLMAN
Art Unit
2125
Tech Center
2100 — Computer Architecture & Software
Assignee
Robert Bosch GmbH
OA Round
2 (Non-Final)
64%
Grant Probability
Moderate
2-3
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 64% of resolved cases
64%
Career Allowance Rate
7 granted / 11 resolved
+8.6% vs TC avg
Strong +43% interview lift
Without
With
+43.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 8m
Avg Prosecution
4 currently pending
Career history
32
Total Applications
across all art units

Statute-Specific Performance

§101
39.1%
-0.9% vs TC avg
§103
45.5%
+5.5% vs TC avg
§102
7.3%
-32.7% vs TC avg
§112
8.2%
-31.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 11 resolved cases

Office Action

§101
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 . Claims 23 – 43 are presented for examination. Response to Arguments Applicant’s arguments with respect to the rejection of the claims 35 U.S.C. 101 have been fully considered but they are not persuasive: With respect to 101: Applicant argues: Step 2A Prong 1: Applicant submits that the Patent Office has failed to discharge its burden of establishing that any limitation of the independent claims recites a judicial exception in the form of mathematical concepts. Page 3 of the Office Action contends that every component of the claimed normalizer recites a mathematical concept, Rather than provide a detailed, reasoned analysis individually tailored to the particular wording of each of the above-referenced normalizer elements that establish why each one of them recites a mathematical concept, the Patent Office simply attaches the same conclusory label on all of them: "Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations." Determining whether a claim element satisfies one of the above three definitions is necessary to distinguish "whether the claim recites a mathematical concept or merely limitations that are based on or involve a mathematical concept." MPEP at 2106.04(a)(2). Since the Patent Office has not provided this level of analysis in its treatment of Prong One, Applicant submits that the Patent Office has failed to establish that the independent claims recite a judicial exception. Step 2A Prong 2: The purpose of Prong Two is to determine "if the recited judicial exception is integrated into a practical application of that exception." MPEP at 2106.04, Part II, Subsection A. The focus of this inquiry is on the "additional elements" of the claim, namely, those elements that do not recite a judicial exception. MPEP at 2106.04. ("Prong Two asks does the claim recite additional elements that integrate the judicial exception into a practical application?"). This passage explains that the stability of the normalization performed by the claimed normalizer is improved by virtue of the regime change made as a function of the input vector and parameter p. In particular, this regime change approach counteracts the rounding errors and noise that had afflicted previous normalizers. Although the improvement in the normalizer is attributed to the regime change feature that is recited in the normalizing element of the normalizer that the Patent Office considers to recite a judicial exception, Prong Two does not bar consideration of this benefit because the regime change feature represents an improvement to the normalizer "additional element," and is in keeping with the emphasis placed in the Advance Notice that Prong Two does not require an additional elements to be evaluated in a vacuum, but instead requires the Prong Two determination to evaluate whether "the claims as a whole integrated what would otherwise be a judicial exception instead into a practical application." Advance Notice at 2 (Prong Two "evaluate[s] the claims as a whole in discerning at least the limitation...reflected the improvement disclosed in the specification."). Therefore, in the present case, the claims as a whole, as represented by the normalizer implementing the regime change feature of the normalization element, results in an improved trainability in the technology of artificial neural networks. Therefore, the claims are eligible under Prong Two. Step 2B: Applicant traverses this analysis because it is merely conclusory and thus ignores the requirement, set forth in Section 2106.05(d) of the MPEP, that in a Step 2B analysis a "factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity." A proper factual determination under Step 2B requires conformity with Berkheimer v. HP, Inc., 881 F.3d 1360, 1368, 125 USPQ2d 1649, 1654 (Fed. Cir. 2018). More to the point, Section 2106.07(a) of the MPEP implements Berkheimer by stating that under Step 2B. The Patent Office does not make any of factual determinations (A)-(D) in support of its Step 2B analysis. Therefore, in view of this discussion, withdrawal of the Section 101 rejection is requested. Examiner’s answer: Step 2A Prong 1: The provided analysis of abstract ideas is sufficient to convey the identified Mathematical Concepts. The Applicant argues that a tailored analysis is needed for each identified abstract idea. This is not necessary because a person of ordinary skill would understand that the act of “normalizing” is a Mathematical Calculation, a calculation that can be done with paper and pencil. Step 2A Prong 2: The Applicant argues that claim is integrated into a practical application. The Applicant cites to paragraph 13 of their provided specification for support of this claim but the provided citation only recites a high level of generality of using normalizing layers on input vectors. This is nothing more than a mathematical process applied to a technological environment. Step 2B: The applicant points out that Berkheimer evidence is needed when stating an additional element (or combination of additional elements) is well-understood, routine and conventional activity. The Examiner did NOT state that the cited limitations on page 4 were well-understood, routine and conventional activity. Instead, the Examiner has cited the limitations as Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h). With respect to 102/103: The Examiner has found the arguments with respect to 102/103 persuasive and the rejection has been withdrawn 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 23 – 43 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The following sections following the 2019 PEG guidelines for analyzing subject matter eligibility. Claim 23 Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: a transformation element, which is configured to transform input quantities directed into the normalizer into one or more input vectors, using a predefined transformation, each of the input quantities going into exactly one of the one or more input vectors (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) a normalizing element, which is configured to normalize each input vector of the one or more input vectors using a normalization function, to form one or more output vectors, the normalization function having at least two different regimes and is configured to change between the regimes as a function of a norm of the input vector at a point and/or in a range, whose position is a function of a predefined parameter p, and (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) an inverse transformation element, which is configured to transform the one or more output vectors, using an inverse of the predefined transformation, into output quantities, which have the same dimensionality as the input quantities supplied to the normalizer. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application a plurality of processing layers connected in series, which are each configured to process input quantities in accordance with trainable parameters of the ANN to form output quantities; and (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) at least one normalizer inserted into at least one of the processing layers and/or between at least two of the processing layers, each normalizer of the at least one normalizer including: (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. a plurality of processing layers connected in series, which are each configured to process input quantities in accordance with trainable parameters of the ANN to form output quantities; and (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) at least one normalizer inserted into at least one of the processing layers and/or between at least two of the processing layers, each normalizer of the at least one normalizer including: (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Claim 24 incorporates the rejections of claim 23. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 23 are incorporated. The ANN as recited in claim 23, wherein the normalization function of at least one of the at least one normalizer is configured to leave input vectors, whose norm is less than the parameter p, unchanged and to normalize input vectors, whose norm is greater than the parameter p, to a uniform norm, while retaining a direction. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 25 incorporates the rejections of claim 23. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 23 are incorporated. The ANN as recited in claim 23, wherein the change of the normalization function of at least one of the at least one normalizer between the different regimes is controlled by a softplus function, whose argument has a zero crossing when the norm of the input vector is equal to the parameter p. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 26 incorporates the rejections of claim 23. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 23 are incorporated. The ANN as recited in claim 23, wherein from a tensor of the input quantities, in which a number f of feature maps are combined that each assign a feature information item to n different locations, the predefined transformation of at least one of the at least one normalizer includes combining all feature information items into one or more input vectors. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 27 incorporates the rejections of claim 26. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 26 are incorporated. The ANN as recited in claim 26, wherein for each feature map of the f feature maps, the predefined transformation of at least one of the at least one normalizer includes combining the feature information items for all locations contained in the feature map to form an input vector assigned to the feature map. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 28 incorporates the rejections of claim 26. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 26 are incorporated. The ANN as recited in claim 26, wherein for each location of the n locations, the predefined transformation of at least one of the at least one normalizer includes combining the feature information items assigned to the location by all of the feature maps, to form an input vector assigned to the location. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 29 incorporates the rejections of claim 26. Step 1: The recites a method, one of the four categories of eligible matter. The ANN as recited in claim 26, wherein the predefined transformation of at least one of the at least one normalizer includes combining all feature information items from the tensor to form a single input vector. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 30 incorporates the rejections of claim 26. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 26 are incorporated. The ANN as recited in claim 26, wherein the predefined transformation of at least one of the at least one normalizer includes subtracting, in each instance, an arithmetic mean calculated over all of the feature information items, from all of the feature information items. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 31 incorporates the rejections of claim 26. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 26 are incorporated. The ANN as recited in claim 26, wherein the predefined transformation of at least one of the at least one normalizer includes subtracting, in each instance, from the feature information items contained in each feature map of the f feature maps, an arithmetic mean of the feature information items calculated over the feature map. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 32 incorporates the rejections of claim 26. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 26 are incorporated. The ANN as recited in claim 26, wherein the predefined transformation of at least one of the at least one normalizer includes subtracting, from the feature information items assigned by all of the feature maps to each location of the n locations, in each instance, an arithmetic mean, which is of the feature information items belonging to the location and is calculated over all feature maps. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 33 incorporates the rejections of claim 23. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 23 are incorporated. to calculate output quantities of the processing layer. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application wherein a normalizer of the at least one normalizer receives a weighted summation of input quantities of a processing layer as input quantities, and output quantities of the normalizer are directed into a nonlinear activation function (Mere data gathering, Insignificant extra solution activity in MPEP 2106.05(g)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. wherein a normalizer of the at least one normalizer receives a weighted summation of input quantities of a processing layer as input quantities, and output quantities of the normalizer are directed into a nonlinear activation function (receiving or transmitting data, using components and functions claimed at a high level of generality have been determined by the courts as being well-understood, routine, and conventional activities in the field of computer functions (See MPEP 2106.05(d)(II)(i)) Claim 34 incorporates the rejections of claim 23. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 23 are incorporated. which are calculated, using a nonlinear activation function, and the output quantities of the normalizer are directed as input quantities into a further processing layer, which sums the input quantities in a weighted manner in accordance with the trainable parameters. (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application wherein a normalizer of the at least one normalizer receives, as input quantities, output quantities of a first processing layer (Mere data gathering, Insignificant extra solution activity in MPEP 2106.05(g)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. wherein a normalizer of the at least one normalizer receives, as input quantities, output quantities of a first processing layer (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Claim 35 incorporates the rejections of claim 23. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 23 are incorporated. The ANN as recited in claim 23, wherein the ANN takes the form of a classifier and/or regressor for determining a classification and/or a regression and/or a semantic segmentation, from actual and/or simulated physical measurement data. (Mental Processes: Can be performed in the human mind, or by a human using a pen and paper, making observations, evaluations and judgments as claimed) Claim 36 incorporates the rejections of claim 35. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 35 are incorporated. The ANN as recited in claim 35, wherein the ANN takes the form of a classifier and/or regressor for identifying and/or quantitatively evaluating objects and/or states in the input quantities of the ANN, the objects and/or states being sought within the scope of a specific application. (Mental Processes: Can be performed in the human mind, or by a human using a pen and paper, making observations, evaluations and judgments as claimed) Claim 37 incorporates the rejections of claim 35. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 35 are incorporated. The ANN as recited in claim 35, wherein the ANN takes the form of a classifier for identifying, from physical measurement data which are obtained by monitoring a traffic situation in surroundings of a reference vehicle using at least one sensor: traffic signs, and/or pedestrians, and/or other vehicles, and/or other objects which characterize the traffic situation. (Mental Processes: Can be performed in the human mind, or by a human using a pen and paper, making observations, evaluations and judgments as claimed) Claim 38 Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: transforming the input quantities for the normalization by a predefined transformation into one or more input vectors, each of the input quantities going into exactly one of the one or more input vectors; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) normalizing each input vector of the one or more input vectors using a normalization function to form one or more output vectors, the normalization function having at least two different regimes and is configured to change between the regimes as a function of a norm of the input vector at a point and/or in a range, whose position is a function of a predefined parameter p; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) transforming the output vectors by an inverse of the predefined transformation into output quantities of the normalization, which have the same dimensionality as the input quantities of the normalization; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application in at least one processing layer of the processing layers and/or between at least two of the processing layers, extracting, a set of quantities ascertained as input quantities during processing, from the ANN for normalization; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) continuing processing in the ANN, the output quantities of the normalization taking the place of the input quantities of the normalization extracted previously. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. in at least one processing layer of the processing layers and/or between at least two of the processing layers, extracting, a set of quantities ascertained as input quantities during processing, from the ANN for normalization; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) continuing processing in the ANN, the output quantities of the normalization taking the place of the input quantities of the normalization extracted previously. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Claim 39 Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: at least one sensor configured to record physical measurement data; (Mental Processes: Can be performed in the human mind, or by a human using a pen and paper, making observations, evaluations and judgments as claimed) an ANN into which the physical measurement data are directed as input quantities, the ANN including: (Mental Processes: Can be performed in the human mind, or by a human using a pen and paper, making observations, evaluations and judgments as claimed) a transformation element, which is configured to transform input quantities directed into the normalizer into one or more input vectors, using a predefined transformation, each of the input quantities going into exactly one of the one or more input vectors, (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) a normalizing element, which is configured to normalize each input vector of the one or more input vectors using a normalization function, to form one or more output vectors, the normalization function having at least two different regimes and is configured to change between the regimes as a function of a norm of the input vector at a point and/or in a range, whose position is a function of a predefined parameter p, and (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) an inverse transformation element, which is configured to transform the one or more output vectors, using an inverse of the predefined transformation, into output quantities, which have the same dimensionality as the input quantities supplied to the normalizer; and (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application a plurality of processing layers connected in series, which are each configured to process the input quantities in accordance with trainable parameters of the ANN to form output quantities, and (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) at least one normalizer inserted into at least one of the processing layers and/or between at least two of the processing layers, each normalizer of the at least one normalizer including: (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) a control unit configured to generate, from the output quantities of the ANN, a control signal for: (i) a vehicle or another autonomous agent, and/or (ii) a classification system, and/or (iii) a system for quality control of mass-produced products, and/or (iv) a system for medical imaging. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. a plurality of processing layers connected in series, which are each configured to process the input quantities in accordance with trainable parameters of the ANN to form output quantities, and (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) at least one normalizer inserted into at least one of the processing layers and/or between at least two of the processing layers, each normalizer of the at least one normalizer including: (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) a control unit configured to generate, from the output quantities of the ANN, a control signal for: (i) a vehicle or another autonomous agent, and/or (ii) a classification system, and/or (iii) a system for quality control of mass-produced products, and/or (iv) a system for medical imaging. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Claim 40 Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: a transformation element, which is configured to transform input quantities directed into the normalizer into one or more input vectors, using a predefined transformation, each of the input quantities going into exactly one of the one or more input vectors, (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) a normalizing element, which is configured to normalize each input vector of the one or more input vectors using a normalization function, to form one or more output vectors, the normalization function having at least two different regimes and is configured to change between the regimes as a function of a norm of the input vector at a point and/or in a range, whose position is a function of a predefined parameter p, and (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) an inverse transformation element, which is configured to transform the one or more output vectors, using an inverse of the predefined transformation, into output quantities, which have the same dimensionality as the input quantities supplied to the normalizer, (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) ascertaining an evaluation of the output quantities, which specifies how effectively the output quantities are in accord with output learning quantities belonging to the input learning quantities, in accordance with a cost function; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application a plurality of processing layers connected in series, which are each configured to process the input quantities in accordance with trainable parameters of the ANN to form output quantities, and (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) at least one normalizer inserted into at least one of the processing layers and/or between at least two of the processing layers, each normalizer of the at least one normalizer including: (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) processing the input learning quantities by the ANN to form the output quantities; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) optimizing the trainable parameters of the ANN together with at least one parameter p, which optimizes a transition between the regimes of the normalization function, with an objective of obtaining, during further processing of the input learning quantities, output quantities whose evaluation by the cost function is expected to be more effective. (Mere instructions to apply an exception as it recites only the idea of a solution or outcome as discussed in MPEP 2106.05(f)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. a plurality of processing layers connected in series, which are each configured to process the input quantities in accordance with trainable parameters of the ANN to form output quantities, and (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) at least one normalizer inserted into at least one of the processing layers and/or between at least two of the processing layers, each normalizer of the at least one normalizer including: (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) processing the input learning quantities by the ANN to form the output quantities; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) optimizing the trainable parameters of the ANN together with at least one parameter p, which optimizes a transition between the regimes of the normalization function, with an objective of obtaining, during further processing of the input learning quantities, output quantities whose evaluation by the cost function is expected to be more effective. (Mere instructions to apply an exception as it recites only the idea of a solution or outcome as discussed in MPEP 2106.05(f)) Claim 41 incorporates the rejections of claim 40. Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: The judicial exceptions of claim 40 are incorporated. generating from the output quantities a control signal for: (i) a vehicle or another autonomous agent, and/or (ii) a classification system, and/or (iii) a system for quality control of mass-produced products, and/or (iv) a system for medical imaging; (Mental Processes: Can be performed in the human mind, or by a human using a pen and paper, making observations, evaluations and judgments as claimed) Step 2A Prong 2: The judicial expectations are not integrated into a practical application supplying to the trained ANN physical measurement data recorded by at least one sensor as input quantities, and processing the physical measurement data by the trained ANN to form the output quantities; (Mere instructions to apply an exception as it recites only the idea of a solution or outcome as discussed in MPEP 2106.05(f)) controlling, using the control signal, the vehicle and/or the classification system and/or the system for the quality control of mass-produced products and/or the system for medical imaging. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. supplying to the trained ANN physical measurement data recorded by at least one sensor as input quantities, and processing the physical measurement data by the trained ANN to form the output quantities; (Mere instructions to apply an exception as it recites only the idea of a solution or outcome as discussed in MPEP 2106.05(f)) controlling, using the control signal, the vehicle and/or the classification system and/or the system for the quality control of mass-produced products and/or the system for medical imaging. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Claim 42 Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: transforming the input quantities for the normalization by a predefined transformation into one or more input vectors, each of the input quantities going into exactly one of the one or more input vectors; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) normalizing each input vector of the one or more input vectors using a normalization function to form one or more output vectors, the normalization function having at least two different regimes and is configured to change between the regimes as a function of a norm of the input vector at a point and/or in a range, whose position is a function of a predefined parameter p; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) transforming the output vectors by an inverse of the predefined transformation into output quantities of the normalization, which have the same dimensionality as the input quantities of the normalization; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application in at least one processing layer of the processing layers and/or between at least two of the processing layers, extracting, a set of quantities ascertained as input quantities during processing, from the ANN for normalization; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) continuing processing in the ANN, the output quantities of the normalization taking the place of the input quantities of the normalization extracted previously. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. in at least one processing layer of the processing layers and/or between at least two of the processing layers, extracting, a set of quantities ascertained as input quantities during processing, from the ANN for normalization; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) continuing processing in the ANN, the output quantities of the normalization taking the place of the input quantities of the normalization extracted previously. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Claim 43 Step 1: The recites a method, one of the four categories of eligible matter. Step 2A Prong 1: transform the input quantities for the normalization by a predefined transformation into one or more input vectors, each of the input quantities going into exactly one of the one or more input vectors; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) normalize each input vector of the one or more input vectors using a normalization function to form one or more output vectors, the normalization function having at least two different regimes and is configured to change between the regimes as a function of a norm of the input vector at a point and/or in a range, whose position is a function of a predefined parameter p; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) transform the output vectors by an inverse of the predefined transformation into output quantities of the normalization, which have the same dimensionality as the input quantities of the normalization; (Mathematical Concepts: are defined as mathematical relationships, mathematical formulas or equations, or mathematical calculations.) Step 2A Prong 2: The judicial expectations are not integrated into a practical application in at least one processing layer of the processing layers and/or between at least two of the processing layers, extract, a set of quantities ascertained as input quantities during processing, from the ANN for normalization; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) continue to process in the ANN, the output quantities of the normalization taking the place of the input quantities of the normalization extracted previously. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. in at least one processing layer of the processing layers and/or between at least two of the processing layers, extract, a set of quantities ascertained as input quantities during processing, from the ANN for normalization; (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) continue to process in the ANN, the output quantities of the normalization taking the place of the input quantities of the normalization extracted previously. (Field of use and technological environment, it does no more than generally link a judicial exception to a particular technological environment. MPEP 2106.05(h)) 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 KYLE ALLMAN THOMPSON whose telephone number is (571)272-3671. The examiner can normally be reached Monday - Thursday, 6 a.m. - 3 p.m. ET.. 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, Kamran Afshar can be reached at (571) 272-7796. 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. /K.A.T./Examiner, Art Unit 2125 /KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125
Read full office action

Prosecution Timeline

Feb 24, 2022
Application Filed
Jun 20, 2025
Non-Final Rejection mailed — §101
Dec 19, 2025
Response Filed
Apr 06, 2026
Final Rejection mailed — §101
Sep 08, 2026
Response after Non-Final Action

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12670409
SYSTEMS AND METHODS FOR A DISTRIBUTED TRAINING FRAMEWORK USING UNIFORM CLASS PROTOTYPES
3y 6m to grant Granted Jun 30, 2026
Patent 12639597
GLOBAL EXPLAINABLE ARTIFICIAL INTELLIGENCE
4y 2m to grant Granted May 26, 2026
Patent 12626165
REDUCING COMPUTATIONAL REQUIREMENTS FOR MACHINE LEARNING MODEL EXPLAINABILITY
4y 1m to grant Granted May 12, 2026
Patent 12626788
INCREMENTALLY TRAINING A KNOWLEDGE GRAPH EMBEDDING MODEL FROM BIOMEDICAL KNOWLEDGE GRAPHS
3y 6m to grant Granted May 12, 2026
Patent 12608624
METHOD, DEVICE, AND PROGRAM PRODUCT FOR MANAGING KNOWLEDGE GRAPHS
4y 2m to grant Granted Apr 21, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

2-3
Expected OA Rounds
64%
Grant Probability
99%
With Interview (+43.3%)
3y 8m (~0m remaining)
Median Time to Grant
Moderate
PTA Risk
Based on 11 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month