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 .
Examiner’s Note
The Examiner encourages Applicant to schedule an interview to discuss issues related to, for example, the rejections noted below under 35 U.S.C § 101, for moving toward allowance.
Providing supporting paragraph(s) with a clear explanation for each limitation of amended/new claim(s) in Remarks is strongly requested for clear and definite claim interpretations by Examiner.
Priority
Acknowledgment is made of applicant's claim for the provisional application (62/719,849) filed on 08/20/2018.
Response to Arguments
Applicant's arguments filed on 03/02/2026 have been fully considered but they are not persuasive.
In Remarks, pp. 13-29, Applicant contends:
Step 2A: Prong One
The Office Action, on pages 16-18, claims that claim 1 recites an abstract idea, specifically a mental process. Applicant respectfully disagrees.
Step 2A: Prong Two
The claimed invention provides an improvement to the functioning of a computer.
…
If claim 1 plainly recited just "computing infrastructure" ( or the like), this may be found to be a generic computer component; however, it is the claimed three layer computing infrastructure, with each layer having differing capabilities, that is non-generic and provides the improvement to the functioning of the computer. Accordingly, Applicant respectfully submits that claim 1 provides an improvement to the functioning of a computer apparent to one of ordinary skill in the art and is therefore subject matter eligible under 35 U.S.C. 101.
Assuming, arguendo, that the three layer computing infrastructure itself is not an improvement to the functioning of a computer, Applicant submits that the combination of the three layer computing infrastructure and the mapping process is such an improvement.
…
para. [0153] recites that "Starting with sensors layer, the following two layers (gateway layers and cloud layers) may add more processing power but also delay to the entire workflow, therefore depending on task objectives, different steps of the solution plan can be mapped to run on different layers." … One of ordinary skill in the art, then, would realize that mapping each step to one of the three layers based on the task objective would provide the requisite processing power for each step while minimizing the delay of the workflow.
… mapping each step of the solution plan to one of the plurality of layers based on the task objective provides an improvement to the functioning of a computer compared to the alternatives. … one of ordinary skill in the art upon reading the specification would understand that the three layer computing infrastructure requires the mapping step to realize the improvement.
…
The mapping step and three layer computing infrastructure are inextricably tied to the whole invention such that they provide an improvement to the whole invention.
…
By mapping each step of the solution plan to one of the plurality of layers, the mapping step and three layer computing infrastructure minimize delay while providing appropriate computing power to each step, improving the functioning of the computer.
…
Accordingly, one of ordinary skill in the art, upon reading the specification, would realize that the claimed invention provides several improvements over prior treatment methods, such as fewer side effects than levodopa treatment, a more effective stimulation approach using the closed-loop system, causal investigation of neural circuitry, and directly testing inferred models of dynamics, connectivity, and causation in vivo.
Step 2B
Accordingly, Applicant respectfully submits that the additional elements of … when read in combination, are not well-understood, routine, or conventional activity in the art and therefore recite significantly more. Even if one or more of the additional elements are found to be well-understood, routine, or conventional activity when considered individually, Applicant respectfully submits that the combination of additional elements amounts to an inventive concept (MPEP 2106.05(d)(I)(3)). Furthermore, Applicant respectfully submits that the additional elements, when read in combination, amount to more than a recitation of the words "apply it" or the like; in other words, the combination of the additional elements amount to more than mere instructions to apply the alleged judicial exception.
Examiner’s response:
The examiner understands the applicant’s assertion.
However, it appears that each processing step is just applying the abstract idea to a general field of endeavor with additional elements. In addition, improvements to technology or technical field are not necessarily reflected in the claims. Thus, the claim does not integrate the judicial exception into a practical application, and the claim does not amount to significantly more than the judicial exception.
In addition, note that 35 USC § 101 claim eligibility is evaluated and determined based on MPEP, but not based on a comparison to other cases (e.g., the cases that the Applicant mentioned in the Remarks).
Step 2A: Prong One
The examiner understands the applicant’s assertion “The Office Action, on pages 16-18, claims that claim 1 recites an abstract idea, specifically a mental process. Applicant respectfully disagrees”
However, as rejected under Claim Rejections - 35 USC § 101, it appears that each processing step is just applying the abstract idea to a general field of endeavor with additional elements. Even though the claim has different additional elements, under its broadest reasonable interpretation, it covers performance of the limitation in the mind. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, the limitations in the context of this claim encompass the user mentally thinking with a physical aid (e.g., pencil and paper).
Step 2A: Prong Two
The examiner understands the applicant’s assertion “If claim 1 plainly recited just "computing infrastructure" ( or the like), this may be found to be a generic computer component; however, it is the claimed three layer computing infrastructure, with each layer having differing capabilities, that is non-generic and provides the improvement to the functioning of the computer. Accordingly, Applicant respectfully submits that claim 1 provides an improvement to the functioning of a computer apparent to one of ordinary skill in the art and is therefore subject matter eligible under 35 U.S.C. 101”
However, even a single "computing infrastructure" may provide improvements if the specification explains the improvements and the claim reflect the disclosed improvements, as explained in MPEP 2106.04(d)(1). As the Applicant mentioned, the claimed three-layer computing infrastructure has three different layers, with each layer having differing capabilities, and par 153 states “Starting with sensors layer, the following two layers (gateway layers and cloud layers) may add more processing power but also delay to the entire workflow, therefore depending on task objectives, different steps of the solution plan can be mapped to run on different layers.” However, MPEP 2106.04(d)(1) states “the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art”, but it is not clear how par 153 along with the claim provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. In other words, it does not appear that par 153 describes the invention such that the improvement would be apparent to one of ordinary skill in the art.
The examiner understands the applicant’s assertion regarding the mapping process along with par 153, including “The mapping step and three layer computing infrastructure are inextricably tied to the whole invention such that they provide an improvement to the whole invention” and “By mapping each step of the solution plan to one of the plurality of layers, the mapping step and three layer computing infrastructure minimize delay while providing appropriate computing power to each step, improving the functioning of the computer.”
However, as rejected under Claim Rejections - 35 USC § 101, and as mentioned in the previous Office Action, par 150 just states “the three layer computing infrastructure (cloud, gateway, sensors) may provide flexibility and adaptability for the entire workflow” and par 153 just states “Starting with sensors layer, the following two layers (gateway layers and cloud layers) may add more processing power but also delay to the entire workflow, therefore depending on task objectives, different steps of the solution plan can be mapped to run on different layers”. Basically, it appears that par 150 just states a common advantage of the three layer computing infrastructure (cloud, gateway, sensors). In other words, it is not clear if “flexibility and adaptability for the entire workflow” are actual key improvements for this invention. It appears that, in general, the three layer computing infrastructure (cloud, gateway, sensors) itself provides flexibility and adaptability, but the present invention just employs the common advantage of the three-layer computing infrastructure, as part of the present invention. In addition, the applicant mentioned “three layer computing infrastructure minimize delay while providing appropriate computing power”. However, it doesn’t appear the claim recites about the feature, but it just recites the three-layer computing infrastructure in a very high level. Thus, it is not clear how the claim reflects the alleged improvements.
The examiner understands the applicant’s assertion “Accordingly, one of ordinary skill in the art, upon reading the specification, would realize that the claimed invention provides several improvements over prior treatment methods, such as fewer side effects than levodopa treatment, a more effective stimulation approach using the closed-loop system, causal investigation of neural circuitry, and directly testing inferred models of dynamics, connectivity, and causation in vivo.”
However, it is not clear how the last two limitations provide the asserted improvements regarding the “severe side effects”. It appears that “executing the at least one machine learning model” just outputs a signal, but it is not clear how the signal helps prevent/remove/reduce/mitigate the severe side effects toward the asserted improvements. In addition, “wherein the at least one implant device is operable to conduct electrophysiologic and/or optogenetic stimulation based on the at least one signal” may be amended to show how “the at least one implant device” is used for the electrophysiologic and/or optogenetic stimulation. (e.g., the at least one implant device performs/delivers/conducts electrophysiologic and/or optogenetic stimulation.) Currently, it is not clear if the implant device is just possible to conduct the stimulation or the implant device actually conducts the stimulation. Furthermore, “at least one signal” may be amended to indicate what kind of data is predicted by “the at least one machine learning model” to operate the implant device (e.g., to alleviate side effects of medical treatments) to provide improvements.
Step 2B
The examiner understands the applicant’s assertion “Accordingly, Applicant respectfully submits that the additional elements … when read in combination, are not well-understood, routine, or conventional activity in the art and therefore recite significantly more”.
However, as rejected under Claim Rejections - 35 USC § 101, individually and/or as a whole, the limitations have been considered a combination of abstract ideas and different types of additional elements that are insignificant extra-solution activities and well-understood, routine, and conventional. In addition, it appears that the alleged improvements are very board and not clear, and details of how the claims may achieve the alleged improvements is missing and/or not clear.
It does not appear that the limitations clearly show e.g., improvements in computer technology and improvements to other technical fields. Rather, it appears that the improvements in Remarks are about just improving the abstract ideas of the independent claims. It doesn’t seem that the specification and/or the independent claims clearly show how the inventive concept of the claims enables improvements and how they are tied together. The applicant may need to amend the claims to show how the claim languages and improvements are tied together.
For at least these reasons, Applicant's arguments are not convincing.
The Examiner encourages Applicant to schedule an interview to discuss issues related to, for example, the rejections noted below under 35 U.S.C § 101.
Allowable Subject Matter
Claims 1-2, 8-9, 15-16 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph and claim objections and 35 U.S.C. 101, set forth in this Office action.
The following is a statement of reasons for the indication of allowable subject matter: Claims 1-2, 8-9, 15-16 are considered allowable since when reading the claims in light of the specification, none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specific in the independent claim including at least:
From independent claims 1, 8, 15:
obtaining, at a model selector component executing on the computer system, at least one machine learning model relevant to the problem using the qualified and enhanced description of the problem by:
generating, at the computer system, a generated machine learning model;
selecting, at the computer system, at least one selected model from among previously used processed models stored at the computer system using a Bayesian belief network operable to compute at least one probability of at least one of the processed models being appropriate for the problem;
determining, at the computer system, a combination of the at least one selected model and the generated machine learning model that produces higher accuracy results than the at least one selected model and the generated machine learning model, wherein the combination of the at least one selected model and the generated machine learning model is determined by selected and trained heuristics and a machine learning model; and
assembling, at the computer system, the combination of the at least one selected model and the generated machine learning model;
…
selecting, at the computer system, computing infrastructure upon which to execute the at least one machine learning model relevant to the problem, wherein the selected computing infrastructure includes a plurality of layers comprising a sensors layer, a gateway layer, and a cloud layer, wherein the sensors layer is deployed on an edge computing layer, wherein the gateway layer is equipped with a computing capability suitable for executing a neural network, wherein the cloud layer is equipped with a computing capability suitable for training the neural network and/or executing simulation tasks;
mapping each step of the series of processing steps of the processing flow to one of the plurality of layers based on the task objective; and
executing, at the computer system, the at least one machine learning model relevant to the problem, including the generated machine learning model, using the one of the plurality of layers of the selected computing infrastructure corresponding to the each step of the series of processing steps to generate and output at least one signal to at least one implant device (or “generate and output to at least one output device at least one recommendation relevant to the problem” for claims 8 and 15);
The closest prior art of record, Sun et al. (US 2017/0011308 A1) teaches receiving a description of a problem and applying machine learning to automatically solve the problem. The system receives a description of a problem, and assigning, by a clustering engine, the problem to a class, and identifying, by a correlation engine, a database associated with the class. The system also provides a suggestion for solving the problem, based on the retrieved data.
Wu et al. (US 2018/0181877 A1) teaches executing an exploration operation to generate a result and storing an entry in a database that correlates an exploration operation configuration for the exploration operation with at least one performance metric. Each performance metric in the at least one performance metric is a value used to evaluate the result. The exploration operation utilizes a machine learning algorithm to process the dataset, and the exploration operation is executed using at least one node in a computing cluster.
Wang et al. (US 2021/0263508 A1) teaches a system framework including sensors, gateways, a cloud platform and a computer device. The sensors monitor a production line to obtain sample data, and the cloud platform is in communication connection with a plurality of gateways. Each gateway classifies the sample data acquired by the sensors and then uploads the data to the cloud platform. The computer device operates a machine learning model and learns the sample data collected by the cloud platform and predicts the performance of a product manufactured on the production line.
Long et al. (US 20190005237 A1) teaches hack identification training program based on publicly available mathematical models such as a “Replicator Neural Net” (RNN), which is a model that predicts its own inputs and which enables creation of “outlier detection algorithms”, “Restricted Boltzmann Machine” (a 2 layer ANN used for dimensionality reduction, classification, regression, collaborative filtering, feature learning, and modeling), as well as a “Stacked Denoising Autoencoder” which are multiple layers of autoencoders (ANNs that try to reconstruct its input for dimensionality reduction, feature selection and extraction).
However, none of the references of record either alone or in combination fairly disclose or suggest the combination of limitations specific in the independent claim including at least:
the limitations recited above from the independent claim 1, 8, 15,
as in the claims for the purpose of providing an intelligent adaptive system that combines input data types, processing history and objectives, research knowledge, and situational context to determine the most appropriate mathematical model, choose the computing infrastructure, and propose the best solution for a given problem. The system chooses an ML model based on accuracy and selects a computing infrastructure to generate at least one recommendation relevant to the problem.
In addition, the dependent claim(s) is/are also considered allowable since the dependent claim(s) is/are dependent on the independent claim(s) above which is/are allowable.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claim(s) 1-2, 8-9, 15-16 is/are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim(s) 1 recite(s) “executing, at the computer system, the at least one machine learning model relevant to the problem, including the generated machine learning model, using the one of the plurality of layers of the selected computing infrastructure corresponding to the each step of the series of processing steps to generate and output at least one signal to at least one implant device; wherein the at least one implant device is operable to conduct electrophysiologic and/or optogenetic stimulation based on the at least one signal”. However, it appears that the specification is silent in regards to i) executing, at the computer system, the at least one machine learning model relevant to the problem … to generate and output at least one signal to at least one implant device, and ii) operating the at least one implant device based on the at least one signal. Instead, pars 50-51 state “A promising therapeutic approach free from the side effects of levodopa treatment is using implanted devices for neural modulation through electrophysiology or optogenetics. The Neural Modulation Treatment Approach. Using electrophysiology and/or optogenetics the chemical behavior of the neurons may be controlled. Brain stimulation is more effective when it is applied in response to specific brain states, via, for example, Closed Loop Monitoring, as opposed to continuous, open loop stimulation. A conceptual sketch of a closed loop control system can be seen in Fig. 3. As shown in Fig. 3, a target input 302 may be applied to an error component 304, which may generate an error signal 306 that may be input to controller 308. Controller 308 may generate a control input signal 310 based on error signal 306, which may be applied to system under control 312. System 312 may generate an output, which may be measured 316 and a signal 318 representing the measured output may be input to error component 304.” Thus, it is not clear, based on the specification, how the machine learning model help generate and output a signal to the implant device, and how the implant device is operated using the signal. This is changing the scope of the claimed invention without support from the specification, therefore it is rejected under 112(a) lack of written description. In addition, claim(s) 8, 15 is/are rejected for the same reason.
Claim(s) 1, 8, 15 each recite(s) limitations that raise issues of indefiniteness as set forth above, and their dependent claims is/are rejected at least based on their direct and/or indirect dependency from the claims listed above. Appropriate explanation and/or amendment is required.
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, 8-9, 15-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: The claim recites a method; therefore, it falls into the statutory category of processes.
Step 2A Prong 1:
The limitations of
“…, the method comprising:
…;
generating, …, a description of the problem, wherein the description conforms to a defined format, by:
enhancing, …, the description of the problem to generate an enhanced description of the problem, using data sets that match or complement the description of the problem by parsing available history of the data sets using characteristics of the data sets for finding added value of the data sets in enhancing the description of the problem;
making qualifications and applying constraints, …, on the enhanced description of the problem, to generate a qualified and enhanced description of the problem for narrowing down a search space; and
determining, …, a processing flow for the problem based on the qualified and enhanced description of the problem …, the processing flow comprising a series of processing steps;
… by:
…;
selecting, …, at least one selected model from among previously used processed models stored at the computer system … compute at least one probability of at least one of the processed models being appropriate for the problem;
determining, …, a combination of the at least one selected model and the generated machine learning model that produces higher accuracy results than the at least one selected model and the generated machine learning model, wherein the combination of the at least one selected model and the generated machine learning model is determined …; and
assembling, …, the combination of the at least one selected model and the generated machine learning model;
…;
selecting, …, computing infrastructure upon which to execute the at least one machine learning model relevant to the problem, …;
mapping each step of the series of processing steps of the processing flow to one of the plurality of layers based on the task objective; and
…;
…”, as drafted, under its broadest reasonable interpretation, covers performance of the limitation in the mind. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example, the limitations in the context of this claim encompass the user mentally thinking with a physical aid (e.g., pencil and paper).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A Prong 2: This judicial exception is not integrated into a practical application.
The claim recites additional elements that are 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). In particular, the claim recites an additional element(s) (“implemented in a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor”, “at a problem formalization component executing on the computer system”, “by a qualifier component executing on the computer system”, “by a data enhancer component of the qualifier component”, “by a requirements generator of the qualifier component”, “by a planner component”, “by running at least one heuristic search algorithm on a bidirectional graph”, “at a model selector component executing on the computer system”, “at the computer system”, “using a Bayesian belief network operable to”, “by selected and trained heuristics and a machine learning model”, “executing, at the computer system, the at least one machine learning model relevant to the problem, including the generated machine learning model, using the one of the plurality of layers of the selected computing infrastructure corresponding to the each step of the series of processing steps to”) – using a device and/or a model to process data. The device and the model in each step are recited at a high-level of generality (i.e., as a generic computer performing a generic computer function of processing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
In particular, the claim recites an additional element(s) (“receiving, from an input device operated by a user, at a problem formalization component executing on the computer system, data relating to a problem to be solved, the data comprising a task objective of the problem to be solved and feedback from a measured output”, “obtaining, at a model selector component executing on the computer system, at least one machine learning model relevant to the problem using the qualified and enhanced description of the problem”) – the act of receiving data. The claim is adding an insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g). The act of receiving data is recited at a high-level of generality (i.e., as a generic act of receiving performing a generic act function of receiving data) such that it amounts no more than a mere act to apply the exception using a generic act of receiving. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
In particular, the claim recites an additional element(s) (“generating, at the computer system, a generated machine learning model”, “training, at the computer system, the generated machine learning model, wherein the generated machine learning model is trained using training data obtained from a corpus of existing research materials and results stored in a History Storage Component storing data relating to experience acquired over past usage of the method, including encountered data sets, previously used models, and achieved results, and a World Knowledge Component storing data relating to knowledge of the world, including data relating to a plurality of disciplines and areas, stored models including previously found public models and previously found proprietary models, and data to be applied to problem formulations, problem solutions, and data sets”). The additional element is recited at such a high level without any details as to how a model is generated/trained such that it amounts to only the idea of a solution or outcome because it fails to recite details of how a solution to a problem is accomplished, and, therefore, represents no more than mere instructions to apply the judicial exception on a computer (see MPEP 2106.05(f)). Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
In particular, the claim recites an additional element(s) (“stored”) – the act of storing data. The claim is adding an insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g). The act of storing data is recited at a high-level of generality (i.e., as a generic act of storing performing a generic act function of storing data) such that it amounts no more than a mere act to apply the exception using a generic act of storing. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
In particular, the claim recites an additional element (“wherein the selected computing infrastructure includes a plurality of layers comprising a sensors layer, a gateway layer, and a cloud layer, wherein the sensors layer is deployed on an edge computing layer, wherein the gateway layer is equipped with a computing capability suitable for executing a neural network, wherein the cloud layer is equipped with a computing capability suitable for training the neural network and/or executing simulation tasks”, “wherein the at least one implant device is operable to conduct electrophysiologic and/or optogenetic stimulation based on the at least one signal”). This is a recitation of a particular type or source of model/data to be used in performing the abstract idea. Limiting the abstract idea to a particular type or source of model/data is an attempt to limit the abstract idea to a particular field of use or technological environment, which does not integrate the abstract idea into a practical application. See MPEP 2106.05(h)
In particular, the claim recites an additional element(s) (“generate and output at least one signal to at least one implant device”) – the act of outputting data. The claim is adding an insignificant extra-solution activity to the judicial exception – see MPEP 2106.05(g). The act of outputting data is recited at a high-level of generality (i.e., as a generic act of performing a generic act function of outputting data) such that it amounts no more than a mere act to apply the exception using a generic act of outputting. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
As discussed above, with respect to integration of the abstract idea into a practical application, the additional elements of using a generic computer component to perform each step amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible. MPEP 2106.05(f).
As discussed above, the claim recites the additional element(s) of receiving data at a high-level of generality and is adding an insignificant extra-solution activity – see MPEP 2106.05(g). However, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood, routine, and conventional. See MPEP 2106.05(d)(II) – “Receiving or transmitting data over a network” or “Storing and retrieving information in memory”. Accordingly, this additional element does not provide an inventive concept and significantly more than the abstract idea. Thus, the claim is not patent eligible.
The additional elements regarding training are recited at such a high level without any details as to how a model is generated/trained such that it amounts to only the idea of a solution or outcome because it fails to recite details of how a solution to a problem is accomplished, and, therefore, represents no more than mere instructions to apply the judicial exception on a computer (see MPEP 2106.05(f)). Accordingly, this additional element does not amount to significantly more than the abstract idea. The claim is directed to an abstract idea.
As discussed above, the claim recites the additional element(s) of storing data at a high-level of generality and is adding an insignificant extra-solution activity – see MPEP 2106.05(g) – storing data. However, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood, routine, and conventional. See MPEP 2106.05(d)(II) – “Receiving or transmitting data over a network” or “Storing and retrieving information in memory”. Accordingly, this additional element does not provide an inventive concept and significantly more than the abstract idea. Thus, the claim is not patent eligible.
This is a recitation of a particular type or source of model/data to be used in performing the abstract idea. Limiting the abstract idea to a particular type or source of model/data is an attempt to limit the abstract idea to a particular field of use or technological environment, which does not amount to significantly more than the abstract idea. See MPEP 2106.05(h).
As discussed above, the claim recites the additional element(s) of outputting data at a high-level of generality and is adding an insignificant extra-solution activity – see MPEP 2106.05(g). However, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood, routine, and conventional. See MPEP 2106.05(d)(II) – “Receiving or transmitting data over a network” or “Storing and retrieving information in memory”. Accordingly, this additional element does not provide an inventive concept and significantly more than the abstract idea. Thus, the claim is not patent eligible.
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.
Step 1: The claim recites a method; therefore, it falls into the statutory category of processes.
Step 2A Prong 1: The claim recites the abstract idea identified above regarding claim 1.
Step 2A Prong 2: This judicial exception is not integrated into a practical application.
In particular, the claim recites an additional element (“wherein the data relating to the problem to be solved comprises at least one of data from sensors, data from devices, data from servers, data from robots, and data from humans”). This is a recitation of a particular type or source of model/data to be used in performing the abstract idea. Limiting the abstract idea to a particular type or source of model/data is an attempt to limit the abstract idea to a particular field of use or technological environment, which does not integrate the abstract idea into a practical application. See 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.
This is a recitation of a particular type or source of model/data to be used in performing the abstract idea. Limiting the abstract idea to a particular type or source of model/data is an attempt to limit the abstract idea to a particular field of use or technological environment, which does not amount to significantly more than the abstract idea. See MPEP 2106.05(h).
Regarding claim 8
The claim recites “A computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor to perform:” to perform precisely the method of Claim 1. As performance of an abstract idea on generic computer components (see MPEP 2106.05(f)) and “Storing and retrieving information in memory” (see MPEP 2106.05(g) on Insignificant Extra-Solution Activity, and MPEP 2106.05(d) on Well-Understood, Routine, Conventional Activity) cannot integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself, the claim is rejected for reasons set forth in the rejection of Claim 1.
Regarding claim 9
The claim is rejected for the reasons set forth in the rejection of Claim 2 under 35 U.S.C. 101, mutatis mutandis, as reciting an abstract idea without integrating the judicial exception into a practical application nor providing significantly more than the judicial exception.
Regarding claim 15
The claim recites “A computer program product comprising a non-transitory computer readable storage having program instructions embodied therewith, the program instructions executable by a computer system, to cause the computer system to perform a method comprising:” to perform precisely the method of Claim 1. As performance of an abstract idea on generic computer components (see MPEP 2106.05(f)) cannot integrate the abstract idea into a practical application nor provide significantly more than the abstract idea itself, the claim is rejected for reasons set forth in the rejection of Claim 1.
Regarding claim 16
The claim is rejected for the reasons set forth in the rejection of Claim 2 under 35 U.S.C. 101, mutatis mutandis, as reciting an abstract idea without integrating the judicial exception into a practical application nor providing significantly more than the judicial exception.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/S.K./Examiner, Art Unit 2129 4/3/2026
/MICHAEL J HUNTLEY/Supervisory Patent Examiner, Art Unit 2129
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