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 .
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 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.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 08/12/2024 has been entered.
This action is in response to the arguments filed on 08/12/2024. Claims 1-7 and 9-19 are pending in the application and have been considered below.
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 1-7 and 9-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
For Step 1, the claim is a method so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “identifying a plurality of features...” The identifying limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the identifying step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining an importance score for each of the plurality of features.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining a probability of prediction for each dataset from the plurality of the datasets based on one or more features from the plurality of features for the prediction of each dataset, and respective importance scores for the one or more features.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “comparing each probability of prediction of each dataset to a probability threshold.” The comparing limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the comparing step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “calculating resource requirements of the job.” The calculating limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the calculating step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “minimizing a loss function...” The minimizing limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the minimizing step from practically being performed in the human mind. This limitation is a mathematical concept process.
The claim recites the limitation of “detecting a user interaction...” The detecting limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the detecting step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining a probability of a prediction of a dataset.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
For Step 2A, Prong 2, the claim recites additional elements: “generating a custom predictive model, displaying a user interface, computer application, model training module, model inference module, provides a first input field to receive a job name, a second input field to receive a model type, a third input field to receive a model path, and a train icon; obtaining the job name, model type, and model path; receiving a plurality of datasets, “sending, based on the comparison, datasets of the plurality of datasets to an exception queue,” “training a custom predictive model,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets,” “sending, based on the resource requirements of the job, the job to either a central processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system,”. "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model.”
The “generating a custom predictive model” is a generic computer component to apply an abstract idea under 2106.05(f).
The “displaying a user interface “step is an intended use and linked to the judicial exception
The “user interface, computer application, model training module and model inference module” are generic computer components to apply an abstract idea under 2106.05(f).
The “generating a job at an application server in communication with the computer
application based on remaining datasets of the plurality of datasets” is a generic computer component to apply an abstract idea under 2106.05(f),
The” provides (i.e., transmit) a first input field to receive a job name, a second input field to receive a model type, a third input field to receive a model path, and a train icon” is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining” (i.e., .data gathering) step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “receiving a plurality of datasets” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The “sending, based on the comparison, datasets of the plurality of datasets to an exception queue” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The “sending, based on the resource requirements of the job, the job to either a central
processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The recited "training either the first machine learning model within the first virtual
container or the second machine learning model within the second virtual container to produce a custom predictive model” is a generic training recitation that may amount to a generic computer component to apply an abstract idea under MPEP 2106.05(f).
Step 2B
The additional elements of ““user interface, computer application, model training module, model inference module,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets” and "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
The “provides (i.e., transmit)” step is a form of insignificant extra-solution activity. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining” (i.e., .data gathering) step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The “receiving a plurality of datasets” step is a form of insignificant extra-solution activity. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). (MPEP 2106.05(d)(II)(i)).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “sending, based on the comparison, datasets of the plurality of datasets to an exception queue” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Here the “sending, based on the resource requirements of the job, the job to either a central processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
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 “user interface, computer application, model training module, model inference module,” “generating a job at an application server in communication with the computer
application based on remaining datasets of the plurality of datasets” and "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model” to perform the claim steps amounts 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.
Therefore, the claim is not eligible.
Regarding Claim 2:
Claim 2, which incorporates the rejection of claim 1, recites further limitations such as “…selecting a type of the custom predictive model…” and “identifying one or more categorical variables…” that are part of the abstract idea and do not amount to an inventive concept.
The claim recites additional elements: “first user interface” and “second user interface.”
The “first user interface” and “second user interface” are generic computer components to apply an abstract idea under 2106.05(f).
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 “first user interface” and “second user interface” to perform the claim steps amounts 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. Therefore, the claim is not eligible.
Regarding Claim 3:
Claim 3, which incorporates the rejection of claim 1, recites further additional elements:
“providing an encrypted subscription code to the user interface, decrypts the subscription code using secret-key cryptography-based decryption, and validates the user has authentication to interact with the computer application based on the decryption.”
The “providing an encrypted subscription code to the user interface, decrypts the subscription code using secret-key cryptography-based decryption, and validates the user has authentication to interact with the computer application based on the decryption” are generic computer components to apply an abstract idea under 2106.05(f).
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 “providing an encrypted subscription code to the user interface, decrypts the subscription code using secret-key cryptography-based decryption, and validates the user has authentication to interact with the computer application based on the decryption” to perform the claim steps amounts 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. Therefore, the claim is not eligible.
.
Regarding Claim 4:
Claim 4, which incorporates the rejection of claim 1, recites further limitations such as “…a probability of on-time payment of an invoice” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 5:
Claim 5, which incorporates the rejection of claim 1, recites further limitations such as “…provides a ranking of the plurality of features affecting the prediction…” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 6:
Claim 6, which incorporates the rejection of claim 1 recites further limitations such as “…provides a comparison of an actual dataset and one or more predictive datasets” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 7:
Claim 7, which incorporates the rejection of claim 1 recites further limitations such as “…provides an accuracy of the prediction based on the comparison” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 9:
Claim 9, which incorporates the rejection of claim 1 recites further limitations such as “…provides a data coverage representing a percentage of datasets having a probability greater than a threshold value” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 10:
For Step 1, the claim is a system so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “identifying a plurality of features...” The identifying limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the identifying step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining an importance score for each of the plurality of features.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining a probability of prediction for each dataset from the plurality of the datasets based on one or more features from the plurality of features for the prediction of each dataset, and respective importance scores for the one or more features.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “comparing each probability of prediction of each dataset to a probability threshold.” The comparing limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the comparing step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “calculating resource requirements of the job.” The calculating limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the calculating step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “minimizing a loss function...” The minimizing limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the minimizing step from practically being performed in the human mind. This limitation is a mathematical concept process.
The claim recites the limitation of “detecting a user interaction...” The detecting limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the detecting step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining a probability of a prediction of a dataset.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
For Step 2A, Prong 2, the claim recites additional elements: “system, generating a custom predictive model, memory, processors, displaying a user interface, computer application, model training module, model inference module, provides a first input field to receive a job name, a second input field to receive a model type, a third input field to receive a model path, and a train icon; obtaining the job name, model type, and model path; receiving a plurality of datasets, “sending, based on the comparison, datasets of the plurality of datasets to an exception queue,” “training a custom predictive model,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets,” “sending, based on the resource requirements of the job, the job to either a central processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system,” "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model.”
The processors are recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data. These generic processors limitation are no more than mere instructions to apply the exception using a generic computer component. (MPEP 2106.05(f)).
The “generating a custom predictive model” is a generic computer component to apply an abstract idea under 2106.05(f).
The “displaying a user interface “step is an intended use and linked to the judicial exception
The “system, memory, processors, user interface, computer application, model training module and model inference module” are generic computer components to apply an abstract idea under 2106.05(f).
The “generating a job at an application server in communication with the computer
application based on remaining datasets of the plurality of datasets” is a generic computer component to apply an abstract idea under 2106.05(f),
The” provides (i.e., transmit) a first input field to receive a job name, a second input field to receive a model type, a third input field to receive a model path, and a train icon” is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining” (i.e., .data gathering) step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “receiving a plurality of datasets” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The “sending, based on the comparison, datasets of the plurality of datasets to an exception queue” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The “sending, based on the resource requirements of the job, the job to either a central
processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The recited "training either the first machine learning model within the first virtual
container or the second machine learning model within the second virtual container to produce a custom predictive model” is a generic training recitation that may amount to a generic computer component to apply an abstract idea under MPEP 2106.05(f).
Step 2B
The additional elements of “system, memory, processors, user interface, computer application, model training module, model inference module,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets” and "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
The “provides (i.e., transmit)” step is a form of insignificant extra-solution activity. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). MPEP 2106.05(d)(II)(i).
Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining” (i.e., .data gathering) step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The “receiving a plurality of datasets” step is a form of insignificant extra-solution activity. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). (MPEP 2106.05(d)(II)(i)).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “sending, based on the comparison, datasets of the plurality of datasets to an exception queue” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Here the “sending, based on the resource requirements of the job, the job to either a central processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
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 “system, memory, processors, user interface, computer application, model training module, model inference module,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets” and "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model” to perform the claim steps amounts 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. Therefore, the claim is not eligible.
Regarding Claim 11:
Claim 11, which incorporates the rejection of claim 10, recites further limitations such as “…selecting a type of the custom predictive model…” and “identifying one or more categorical variables…” that are part of the abstract idea and do not amount to an inventive concept.
The claim recites additional elements:” first user interface” and “second user interface.”
The “first user interface” and “second user interface” are generic computer components to apply an abstract idea under 2106.05(f).
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 “first user interface” and “second user interface” to perform the claim steps amounts 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. Therefore, the claim is not eligible.
Regarding Claim 12:
Claim 12, which incorporates the rejection of claim 10, recites further limitations such as “…limited resources by at least one of using….” that are part of the abstract idea and do not amount to an inventive concept.
There is an additional element: memory and processor.
The “memory and processor” are generic computer components to apply an abstract idea under 2106.05(f).
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 “first user interface” and “second user interface” to perform the claim steps amounts 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. Therefore, the claim is not eligible.
Regarding Claim 13:
Claim 13, which incorporates the rejection of claim 10, recites further limitations such as “…a document type of a dataset in the plurality of datasets and a type of service of datasets in the plurality of datasets” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 14:
Claim 14, which incorporates the rejection of claim 10, recites further limitations such as “…provides a ranking of the plurality of features affecting the prediction…” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 15:
Claim 15, which incorporates the rejection of claim 10, recites further limitations such as “…provides a comparison of an actual dataset and one or more predictive datasets” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 16:
Claim 16, which incorporates the rejection of claim 15, recites further limitations such as “…provides an accuracy of the prediction based on the comparison” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 17:
Claim 17, which incorporates the rejection of claim 10, recites further limitations such as “…probability of the prediction indicates a confidence value of the prediction” that are part of the abstract idea and do not amount to an inventive concept.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 18:
Claim 18, which incorporates the rejection of claim 10, recites further limitations such as “…provides a data coverage representing a percentage of datasets having a probability greater than a threshold value” that are part of the abstract idea and do not amount to an inventive concept.
There is an additional element: custom predictive model.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 19:
For Step 1, the claim is a non-transitory computer readable medium so it does recite a statutory category of invention.
For Step 2A, Prong 1:
For Step 1, the claim is a method so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “identifying a plurality of features...” The identifying limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the identifying step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining an importance score for each of the plurality of features.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining a probability of prediction for each dataset from the plurality of the datasets based on one or more features from the plurality of features for the prediction of each dataset, and respective importance scores for the one or more features.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “comparing each probability of prediction of each dataset to a probability threshold.” The comparing limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the comparing step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “calculating resource requirements of the job.” The calculating limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the calculating step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “minimizing a loss function...” The minimizing limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the minimizing step from practically being performed in the human mind. This limitation is a mathematical concept process.
The claim recites the limitation of “detecting a user interaction...” The detecting limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the detecting step from practically being performed in the human mind. This limitation is a mental process.
The claim recites the limitation of “determining a probability of a prediction of a dataset.” The determining limitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the determining step from practically being performed in the human mind. This limitation is a mental process.
For Step 2A, Prong 2, the claim recites additional elements: “non-transitory computer readable medium, generating a custom predictive model, displaying a user interface, computer application, model training module, model inference module, receiving a plurality of datasets, “sending, based on the comparison, datasets of the plurality of datasets to an exception queue,” “training a custom predictive model,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets,” “sending, based on the resource requirements of the job, the job to either a central processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system,”. "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model.”
The “generating a custom predictive model” is a generic computer component to apply an abstract idea under 2106.05(f).
The “displaying a user interface “step is an intended use and linked to the judicial exception
The “non-transitory computer readable medium, user interface, computer application, model training module and model inference module” are generic computer components to apply an abstract idea under 2106.05(f).
The “generating a job at an application server in communication with the computer
application based on remaining datasets of the plurality of datasets” is a generic computer component to apply an abstract idea under 2106.05(f),
The” provides (i.e., transmit) a first input field to receive a job name, a second input field to receive a model type, a third input field to receive a model path, and a train icon” is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “obtaining” (i.e., .data gathering) step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “receiving a plurality of datasets” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The “sending, based on the comparison, datasets of the plurality of datasets to an exception queue” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The “sending, based on the resource requirements of the job, the job to either a central
processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system” step is a form of insignificant extra-solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g).
The recited "training either the first machine learning model within the first virtual
container or the second machine learning model within the second virtual container to produce a custom predictive model” is a generic training recitation that may amount to a generic computer component to apply an abstract idea under MPEP 2106.05(f).
Step 2B
The additional elements of “non-transitory computer readable medium, user interface, computer application, model training module, model inference module,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets” and "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive model” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the Subject Matter Eligibility, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
The “provides (i.e., transmit)” step is a form of insignificant extra-solution activity. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “obtaining” (i.e., .data gathering) step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The “receiving a plurality of datasets” step is a form of insignificant extra-solution activity. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ 193, 196 (1978). (MPEP 2106.05(d)(II)(i)).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “sending, based on the comparison, datasets of the plurality of datasets to an exception queue” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
Here the “sending, based on the resource requirements of the job, the job to either a central processing unit queue in communication with a first machine learning model stored in a first virtual container of a container system or a graphics processing unit queue in communication with a second machine learning model stored in a second virtual container of the container system” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
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 “non-transitory computer readable medium, user interface, computer application, model training module, model inference module,” “generating a job at an application server in communication with the computer application based on remaining datasets of the plurality of datasets” and "training either the first machine learning model within the first virtual container or the second machine learning model within the second virtual container to produce a custom predictive mode