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 .
Response to Amendment
Applicant’s submission filed on 07/29/2025 has been entered. The status of claims is as follows:
Claims 1-2, 4-21 remain pending in the application.
Claim 3 is cancelled.
Claims 1, 9 and 16 are amended.
Response to Arguments
In reference to the Claim Rejections under 35 U.S.C 101:
Applicant asserts on Remarks pg. 1-3 that the amended are patent-eligible under 101 because, although they recite a judicial exception, the claims integrate that exception into a practical application that improves the functioning and reliability of a computer system – specifically, an artificial neural network (ANN) retrained in situ within the same memory after deployment. The specification explains that remotely deployed sensors face reliability, error-propagation, and maintenance challenges, and the invention addresses these issues by enabling in-memory retraining when performance falls below a threshold. This disclosed improvement enhances mean-time-to-failure and overall system reliability, demonstrating a technological advancement as required by MPEP 2106.04(d). Therefore, the Applicant contends that the Examiner’s characterization of the retraining as insignificant extra-solution activity is incorrect because the in-situ post-deployment retraining forms the core technological solution to the identified problems.
Applicant’s arguments have been fully considered but are not persuasive. Although the amended claims now recite that the remote sensor system may be deployed in locations such as 5G network, smart camera, radar, or space/ subsea equipment, and further recite in-situ retraining of the artificial neural network (ANN) after evaluating its performance, the claims still recite an abstract idea and do not integrate that abstract idea into a practical application as required by Step 2A Prong Two of the eligibility analysis. The claim continues to be directed to the abstract idea of mathematical analysis and mathematical manipulation of data, including classification, identification, analysis, comparison of ANN outputs to known outputs, determining a difference, and updating weights/ biases – all of which fall within the judicial exception of mathematical concepts. The recited “retraining circuitry”, “memory” and “controller” are described generically and perform only their well-understood functions of storing data and executing mathematical operations. The specification likewise describes the retraining as conventional ANN training activity.
The additional elements – deploying the sensor system in various environments, performing ANN evaluation post-deployment, and retraining “in-situ” – do not impose any meaningful limits that would amount to a practical application. The claim does not recite any specific technological improvement to the memory, controller, communication hardware, or ANN architecture. Instead, the claim merely applies the abstract mathematical operations in the context of a generic remote sensor system, which is insufficient under MPEP 2106.04(d). Improving “mean time to failure” of the sensor system is stated only as a result of performing the abstract mathematical processes, not as a technological improvement rooted in the claim’s structure. As such, the claims do not effect an improvement to the functioning of a computer or other technology, but instead use generic computer components as tools to implement the abstract idea. Accordingly, the claims fail to integrate the judicial exception into a practical application and do not amount to significantly more under Step 2B. The 101 rejection is therefore maintained.
Applicant’s arguments filed 07/29/2025 have been fully considered but they are not persuasive.
In reference to the Claim Rejections under 35 U.S.C 103:
Applicant argues on Remarks pg. 4 that the cited prior arts do not teach, suggest or render obvious every limitation of independent claims 1, 9 and 16, wherein each of the independent claims recites “wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure”.
Examiner respectfully disagrees and notes that although the Examiner indicated during the interview that the proposed amendments appeared to overcome the 103 rejections, upon further consideration of the full claim amendments as submitted in the response, the Examiner finds that the previously cited references still teach or render obvious the newly added limitations “wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure”. Specifically, Turcot discloses in ¶[0078]: “The sensor data can be obtained from the vehicle occupant along with the video data or the audio data, instead of the video data or the audio data, etc. In embodiments, the sensor data can include one or more of vehicle temperature, outside temperature, time of day, level of daylight, weather conditions, headlight activation, windshield wiper activation, entertainment center selection, or entertainment center volume.”, ¶[0079]: “Images, which can include facial or torso data, human perception state data, audio data, and physiological data, can be collected using multiple mobile devices. The image data can be applied to neural network training, where the neural network training can enable deep learning. The deep learning can include in situ retraining.”, and ¶[0081]: “A mobile device can include a front-side camera and/or a back-side camera that can be used to collect expression data. A mobile device can include a microphone, audio transducer, or other audio capture apparatus that can be used to capture the speech and nonspeech vocalizations. Sources of expression data can include a webcam 1222, a phone camera 1242, a tablet camera 1252, a wearable camera 1262, and a mobile camera 1230. A wearable camera can comprise various camera devices, such as a watch camera 1272. Sources of audio data 1282 can include a microphone 1280.”. Accordingly, the 103 rejections are maintained.
Applicant’s arguments filed 07/29/2025 have been fully considered but they are not persuasive.
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 1-2, 4-21 are rejected under U.S.C 101 for containing an abstract idea without significantly more.
Regarding claim 1:
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
evaluating performance of the artificial neural network by the controller post-deployment of the remote sensor system; - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
comparing an output of the artificial neural network to a known output for the representative dataset; - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
determining a difference between the output and the known output; - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
operating an artificial neural network allocated to memory post-deployment of a remote system including the memory and a controller coupled to the memory, wherein the controller includes retraining circuitry; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
wherein operating the artificial neural network includes performing operations with respect to data from the sensor, the operations comprising one or more of classification, identification, and analysis of the data from the sensor. – This limitation is directed to field of use (see MPEP 2106.05(h))
wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
wherein [evaluating comprises] inputting a representative dataset to the artificial neural network This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
retraining, in-situ by the retraining circuitry post-deployment of the remote system, the artificial neural network at least partially in response to the evaluation yielding a sub-threshold result. This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
wherein the method is performed by the controller; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
applying corrections to reduce the difference, including updating weights and/or biases of the artificial neural network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
operating the retrained artificial neural network in the remote sensor system thereby improving a mean time to failure of the remote sensor system. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
operating an artificial neural network allocated to memory post-deployment of a remote system including the memory and a controller coupled to the memory, wherein the controller includes retraining circuitry; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
wherein operating the artificial neural network includes performing operations with respect to data from the sensor, the operations comprising one or more of classification, identification, and analysis of the data from the sensor. – This limitation is directed to field of use (see MPEP 2106.05(h))
wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
wherein [evaluating comprises] inputting a representative dataset to the artificial neural network – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
retraining, in-situ by the retraining circuitry post-deployment of the remote system, the artificial neural network at least partially in response to the evaluation yielding a sub-threshold result. This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
wherein the method is performed by the controller; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
applying corrections to reduce the difference, including updating weights and/or biases of the artificial neural network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
operating the retrained artificial neural network in the remote sensor system thereby improving a mean time to failure of the remote sensor system. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 2,
Claim 2 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
evaluating performance of the artificial neural network after retraining; and - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
determining whether to retrain the artificial neural network again based on results of the evaluation. This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 4,
Claim 4 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 1 which includes an abstract idea (see rejection for claim 1). The additional limitations:
wherein evaluating comprises periodically evaluating performance of the artificial neural network. This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 5,
Claim 5 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 4 which includes an abstract idea (see rejection for claim 4). The additional limitations:
receiving an indication of a desired frequency of the periodic evaluation from a host of the memory; and – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
wherein periodically evaluating comprises periodically evaluating at the desired frequency. This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 6,
Claim 6 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 4 which includes an abstract idea (see rejection for claim 4). The additional limitations:
detecting an error in the memory; and This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
wherein retraining further comprises retraining at least partially in response to the error. This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)), and also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
Regarding claim 7,
Claim 7 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 6 which includes an abstract idea (see rejection for claim 6). The additional limitations:
wherein retraining accounts for the error without remapping storage of weights in the memory. This claim merely recites a further limitation on the retraining at least partially in response to the error from Claim 6 which was directed to insignificant extra-solution activity (see MPEP 2106.05(g)), and also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
Regarding claim 8,
Claim 8 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 6 which includes an abstract idea (see rejection for claim 6). The additional limitations:
wherein detecting the error comprises detecting a bit error or bit freeze in the memory. This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 9,
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
compare an output of the artificial neural network to a known output for the representative dataset to periodically evaluate performance of an artificial neural network post-deployment of the remote sensor system at a predefined frequency, - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
determining a difference between the output and the known output; - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
a sensor This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
a memory device; and This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
a controller coupled to the memory device and configured to; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
operate an artificial neural network allocated to the memory device post-deployment of the remote sensor system, Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
wherein operating the artificial neural network includes performing operations with respect to data from the sensor, the operations comprising one or more of classification, identification, and analysis of the data from the sensor – This limitation is directed to field of use (see MPEP 2106.05(h))
input a representative dataset to the artificial neural network This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
wherein the artificial neural network is allocated to the memory device; and – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
applying corrections to reduce the difference, including updating weights and/or biases of the artificial neural network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
retrain the artificial neural network in-situ post-deployment of the remote sensor system at least partially in response to a sub-threshold result of the periodic performance evaluation. This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
operate the retrained artificial neural network in the remote sensor system thereby improving a mean time to failure of the remote sensor system; Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure. – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
a sensor This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
a memory device; and This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
a controller coupled to the memory device and configured to; – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
operate an artificial neural network allocated to the memory device post-deployment of the remote sensor system, Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
wherein operating the artificial neural network includes performing operations with respect to data from the sensor, the operations comprising one or more of classification, identification, and analysis of the data from the sensor – This limitation is directed to field of use (see MPEP 2106.05(h))
input a representative dataset to the artificial neural network – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
wherein the artificial neural network is allocated to the memory device; and – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
applying corrections to reduce the difference, including updating weights and/or biases of the artificial neural network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
retrain the artificial neural network in-situ post-deployment of the remote sensor system at least partially in response to a sub-threshold result of the periodic performance evaluation. This limitation is also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
operate the retrained artificial neural network in the remote sensor system thereby improving a mean time to failure of the remote sensor system; Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure. – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
Regarding claim 10,
Claim 10 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 9 which includes an abstract idea (see rejection for claim 9). The additional limitations:
wherein the predefined frequency is a user-defined parameter based at least in part on reliability or lifetime expectations of the apparatus. This claim merely recites a further limitation on the periodically evaluate performance of an artificial neural network at a predefined frequency from Claim 9 which was directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding claim 11,
Claim 11 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 9 which includes an abstract idea (see rejection for claim 9). The additional limitations:
wherein the apparatus stores [[a]] the representative dataset and [[a]] the known output of the artificial neural network for the representative dataset; and – This limitation is directed to storing and retrieving information in memory, which the court have recognized as well-understood, routine, and conventional activity (see MPEP 2106.05 (d) II. iv)
Regarding claim 12,
Claim 12 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 11 which includes an abstract idea (see rejection for claim 11). The additional limitations:
wherein the sub-threshold result comprises a greater difference between the output of the artificial neural network for the representative dataset and the known output than a predefined threshold. This claim merely recites a further limitation on the retrain the artificial neural network at least partially in response to a sub-threshold result of the periodic performance evaluation from Claim 9 which was directed to insignificant extra-solution activity (see MPEP 2106.05(g)), and also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
Regarding claim 13,
Claim 13 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 12 which includes an abstract idea (see rejection for claim 12). The additional limitations:
wherein the controller is configured to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
apply the predefined threshold irrespective of a quantity of bit errors present in the memory device. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 14,
Claim 14 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 9 which includes an abstract idea (see rejection for claim 9). The additional limitations:
wherein the controller is configured to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
retrain the artificial neural network irrespective of a quantity of bit errors present in the memory device. This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)), and also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
Regarding claim 15,
Claim 15 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 9 which includes an abstract idea (see rejection for claim 9). The additional limitations:
wherein the controller is configured to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
detect a plurality of bit errors in the memory device; and This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
wherein the controller being configured to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
retrain the artificial neural network comprises This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)), and also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
the controller being configured to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
map weights to memory cells of the memory device without adjusting weights mapped to particular memory cells corresponding to the bit errors. This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Regarding Claim 16,
Step 1 – Is the claim to a process, machine, manufacture or composition of matter?
Yes, the claim is a process.
Step 2A – Prong 1 – Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes, the claim recites an abstract idea.
comparing an output of the artificial neural network to a known output for the representative dataset to perform the periodic performance evaluation post-deployment of the remote sensor system at a frequency based on the second definition; and - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
determine a difference between the output and the known output; - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
Step 2A – Prong 2 – Does the claim recite additional elements that integrate the judicial exception into a practical application?
No, there are no additional elements that integrate the judicial exception into a practical application. The additional elements:
A non-transitory machine-readable medium storing machine-readable instructions, which when executed by a machine, cause the machine to This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
receive a first definition of a threshold for results of a periodic performance evaluation of an artificial neural network; This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
receive a second definition of at least one of a reliability expectation and a lifetime expectation of a memory device; This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
operate an artificial neural network allocated to the memory device post-deployment of a remote sensor system including the memory device, a sensor, and a controller coupled to the memory device and the sensor – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
wherein the instructions to operate the artificial neural network include instructions to perform operations with respect to data from the sensor, – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
the operations comprising one or more classification, identification, and analysis of the data from the sensor; – This limitation is directed to field of use (see MPEP 2106.05(h))
wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure– This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
input a representative dataset to the artificial neural network This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
applying corrections to reduce the difference, including updating weights and/or biases of the artificial neural network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
retrain the artificial neural network in-situ post-deployment of the remote system at least partially in response to a particular periodic performance evaluation not meeting the first definition. This limitation is directed to insignificant extra-solution activity (see MPEP 2106.05(g)).
operating the retrained artificial neural network in the remote sensor system thereby improving a mean time to failure of the remote sensor system. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Step 2B – Does the claim recite additional elements that amount to significantly more than the judicial exception?
No, there are no additional elements that amount to significantly more than the judicial exception. The additional elements are:
A non-transitory machine-readable medium storing machine-readable instructions, which when executed by a machine, cause the machine to This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
receive a first definition of a threshold for results of a periodic performance evaluation of an artificial neural network; – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
receive a second definition of at least one of a reliability expectation and a lifetime expectation of a memory device; – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
operate an artificial neural network allocated to the memory device post-deployment of a remote sensor system including the memory device, a sensor, and a controller coupled to the memory device and the sensor – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
wherein the instructions to operate the artificial neural network include instructions to perform operations with respect to data from the sensor, – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
the operations comprising one or more classification, identification, and analysis of the data from the sensor; – This limitation is directed to field of use (see MPEP 2106.05(h))
wherein the remote sensor system is deployed in one of a 5G network, smart camera, radar, space exploration equipment, and subsea exploration equipment and therefore is not accessible by technicians or other computing infrastructure– This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
input a representative dataset to the artificial neural network – This limitation is directed to receiving or transmitting data over a network. The courts have recognized receiving or transmitting data over a network as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (see MPEP 2106.05(d) II.).
applying corrections to reduce the difference, including updating weights and/or biases of the artificial neural network. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
retrain the artificial neural network in-situ post-deployment of the remote system at least partially in response to a particular periodic performance evaluation not meeting the first definition. This limitation is also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
operating the retrained artificial neural network in the remote sensor system thereby improving a mean time to failure of the remote sensor system. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea [see MPEP 2106.05(f)] and therefore fails to integrate the exception into a practical application.
Regarding claim 17,
Claim 17 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 16 which includes an abstract idea (see rejection for claim 16). The additional limitations:
further storing a table comprising correspondences between respective frequencies of the periodic performance evaluation and respective reliability expectations and respective lifetime expectations; and – This limitation is directed to storing and retrieving information in memory, which the court have recognized as well-understood, routine, and conventional activity (see MPEP 2106.05 (d) II. iv)
further storing instructions to select the frequency from the table based on the second definition. – This limitation is directed to storing and retrieving information in memory, which the court have recognized as well-understood, routine, and conventional activity (see MPEP 2106.05 (d) II. iv)
Regarding claim 18,
Claim 18 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 16 which includes an abstract idea (see rejection for claim 16). The additional limitations:
further comprising instructions to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
detect a plurality of bit errors in the memory device; and - This limitation is directed to the abstract idea of a mental process (including an observation, evaluation, judgement, opinion) which can be performed in the human mind, or by a human using pen and paper (see MPEP 2106.04(a)(2) Ill. C.)
wherein the instructions to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
retrain the artificial neural network comprise This limitation is also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
instructions to – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
retrain the artificial neural network irrespective of the plurality of errors. This limitation is also directed to well-understood, routine and conventional as evidenced by Huang et al. (US 20210271809 A1) ([0091]: “For example, in the classification task, features of objects to be labelled passing the verification can be used as features of the training samples and the manual labelling results as labels of the training samples to generate the training samples to retrain or incrementally train and the machine learning model. The retraining or incremental training process of the model is well known in the art, which is not repeated here.”)
Regarding claim 19,
Claim 19 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 16 which includes an abstract idea (see rejection for claim 16). The additional limitations:
further storing [[a]] the representative dataset and [[a]] the known output of the artificial neural network for the representative dataset; and This limitation is directed to storing and retrieving information in memory, which the court have recognized as well-understood, routine, and conventional activity (see MPEP 2106.05 (d) II. iv)
Regarding claim 20,
Claim 20 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 16 which includes an abstract idea (see rejection for claim 16). The additional limitations:
cause weights of the artificial neural network to be stored in a plurality of memory cells of the memory device prior to operation of the artificial neural network; and This limitation is directed to storing and retrieving information in memory, which the court have recognized as well-understood, routine, and conventional activity (see MPEP 2106.05 (d) II. iv)
cause weights of the retrained artificial neural network to be stored in the plurality of memory cells. This limitation is directed to storing and retrieving information in memory, which the court have recognized as well-understood, routine, and conventional activity (see MPEP 2106.05 (d) II. iv)
Regarding claim 21,
Claim 21 is rejected under 35 U.S.C 101 because the claimed invention is directed to an abstract idea without significantly more. The claim is dependent on claim 16 which includes an abstract idea (see rejection for claim 16). The additional limitations:
instructions to operate the retrained artificial neural network. – This limitation is directed to a computer merely used as a tool to perform an existing process (see MPEP 2106.05(f) (2)).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections