CTNF 18/408,668 CTNF 84295 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Specification 06-11 AIA The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-3 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. With regard to claim 1: Step 2A, Prong One: The claim recites the following limitations which are drawn towards an abstract idea: wherein the weight matrix is updated on a basis of a loss function that is divided into cases by a gain of a closed loop and that is switched in a mode of presence or absence of a penalty term (recites mental process steps including mathematical calculations to determine what values to update the weight matrix with as well as evaluation/comparison steps to determine which loss function to use, see equation 22 on page 13 showing the respective loss functions and calculations based on an evaluation and selection of which loss function to use). As seen from above, the identified limitations recite concepts associated with an abstract idea and thus the respective claim recites a judicial exception (see 2106.04(a)) and thus requires further analysis as discussed below. Step 2A, Prong Two: The following limitations have been identified as being additional elements as discussed below. A neural network controller which is a multilayer neural network controller (recites apply-it type limitations of using computer components at a high-level of generality to implement the abstract idea, in particular computer software/program to perform the judicial exception, see MPEP 2106.05(f)) having a weight matrix (recites field of use limitations describing the intended logical data structure type that is storing the information to be manipulated, see MPEP 2106.05(h)), As seen from the above discussion, the identified limitations did not integrate the judicial exception into a practical application (see MPEP 2106.04(d)). This judicial exception is not integrated into a practical application because the additional elements merely describe generic data structure types for logically organizing data to be manipulated as well as merely using generic computer components (software) as a tool to implement the abstract idea. Step 2B: Below is the analysis of the claims: A neural network controller which is a multilayer neural network controller (recites apply-it type limitations of using computer components at a high-level of generality to implement the abstract idea, in particular computer software/program to perform the judicial exception, see MPEP 2106.05(f)) having a weight matrix (recites field of use limitations describing the intended logical data structure type that is storing the information to be manipulated, see MPEP 2106.05(h)), As seen from above, the respective claim elements taken individually do not amount to significantly more than the judicial exception. When taken as a whole (in combination), the claim also does not amount to significantly more than the abstract idea because the additional elements merely describe generic data structure types for logically organizing data to be manipulated as well as merely using generic computer components (software) as a tool to implement the abstract idea. With regard to claim 2, this claim recites wherein the penalty term is a function using an L2 gain of the weight matrix as an argument (recites mental process steps of an algorithmic function/evaluation to determine/calculate the value of a variable). With regard to claim 3, this claim recites wherein a control target is any one of a robot, a plant, and an unmanned aircraft (recites field of use limitations describing the preferred device that is being used, see MPEP 2106.05(h)). Claims 1-3 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claims are drawn to software per se. With regard to claim 1, this claim recites a neural network controller having a weight matrix which recites software elements including a program/software that makes use of a software data structure (logical structure). Additionally, paragraph [0015] of applicant’s specification indicates that the neural network controller may be implemented by software. Therefore, claim 1 is drawn to software per se and is rejected for being directed towards software per se. Claims 2 and 3 discuss additional software calculations (claim 2) and the target for what the controller is meant to provide signals to (claim 3); however, these claims inherit the same deficiencies as their parent claim and are also drawn to a software per se. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-20-02-aia AIA 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. 07-21-aia AIA Claim s 1-3 are rejected under 35 U.S.C. 103 as being unpatentable over Shi et al [US 2020/0183339 A1] in view of Takeshi [WO 2020/241009 A1] . With regard to claim 1, Shi teaches a neural network controller which is a multilayer neural network having a weight matrix (see paragraph [0052]; the system utilizes a multilayer neural network that has a weight matrix), wherein the weight matrix is updated on a basis of a loss function (see paragraphs [0051] and [0052]; the system can compute losses via a function and be able to update the model/weights of the weight matrix accordingly) that is divided into cases b y a gain of a closed loop and that is switched in a mode of presence or absence of a penalty term . Shi teaches a gain of a closed loop (see paragraph [0105]; the system can utilize a closed loop and be able to calculate gain) but does not appear to explicitly teach: wherein the weight matrix is updated on a basis of a loss function that is divided into cases by a gain of a closed loop and that is switched in a mode of presence or absence of a penalty term. Takeshi teaches a loss function that is divided into cases by a gain of a closed loop and that is switched in a mode of presence or absence of a penalty term (see the third paragraph on page 10; see the first four whole paragraphs on page 7; the system can determine the loss function can have at least two cases based on some evaluation where the respective cases include the presence or absence of a penalty/regularization term). It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the regularization usage in an objective/cost/loss function of Shi by utilizing a penalty/regularization term for the function based on observed output conditions/values as taught by Takeshi in order to provide a dynamic mechanism that can still prevent overfitting and enhance generalization of the model while not relying upon a static always-use the penalty term thus allowing the system to quickly adapt and learn while ensuring that undesired conditions/output can be handled/constrained without too much of an adverse effect on the model. Shi in view of Takeshi teach wherein the weight matrix is updated on a basis of a loss function that is divided into cases by a gain of a closed loop and that is switched in a mode of presence or absence of a penalty term (see Takeshi, see the third paragraph on page 10; see the first four whole paragraphs on page 7; see Shi, paragraphs [0051]-[0052] and [0105]; the system can compute losses via a function and be able to update the model/weights of the weight matrix accordingly where the loss function can have at least two cases based on some evaluation where the respective cases include the presence or absence of a penalty/regularization term associated with the gain). With regard to claim 2, Shi in view of Takeshi teach wherein the penalty term is a function using an L2 gain of the weight matrix as an argument (see Shi, paragraphs [0051]-[0052] and [0105]; Takeshi, see the third paragraph on page 10; see the first four whole paragraphs on page 7; see fourth paragraph on page 6; the system can use L2 regularization/gain and be able to utilize that information to determine the value of penalty term). With regard to claim 3, Shi in view of Takeshi teach wherein a control target is any one of a robot, a plant, and an unmanned aircraft (see Shi, paragraph [0041]; robots, plants, or unmanned aerial vehicles can be the control target). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARC S SOMERS whose telephone number is (571)270-3567. The examiner can normally be reached M-F 11-8 EST. 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, Ann Lo can be reached at 5712729767. 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. /MARC S SOMERS/Primary Examiner, Art Unit 2159 6/15/2026 Application/Control Number: 18/408,668 Page 2 Art Unit: 2159 Application/Control Number: 18/408,668 Page 3 Art Unit: 2159 Application/Control Number: 18/408,668 Page 5 Art Unit: 2159 Application/Control Number: 18/408,668 Page 6 Art Unit: 2159 Application/Control Number: 18/408,668 Page 7 Art Unit: 2159 Application/Control Number: 18/408,668 Page 8 Art Unit: 2159
