DETAILED ACTION
This Office Action is in response to the amendments filed on 06/05/2025.
Claims 1, 15, and 20 currently amended.
Claim 8 currently cancelled.
Claim 21 newly added.
Claims 1-7 and 9-21 are currently pending in this application and have been examined.
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 Arguments
In reference to Applicant’s arguments on page(s) 8-10 regarding rejections made under 35 U.S.C. 101:
Claims 1-20 are rejected under 35 USC § 101 because the claimed invention is directed to judicial exception, an abstract idea, it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception.
The amended independent claims (claims 1, 15, and 20) are directed to statutory subject matter under 35 U.S.C. § 101, and the rejection should be withdrawn. The claims, as amended, are not directed to an abstract idea but instead recite an inventive concept that contributes to the technical improvement of machine learning training. Specifically, the claim details how the specific arrangement and randomization of data chunks, combined with the marking and clearing of flags, address technical challenges in training machine learning algorithms, thereby integrating the abstract idea into a practical application. The inventive concept lies in the detailed process of creating and managing data chunks for training a machine learning algorithm. The claims include specific steps that are neither routine nor conventional, such as creating a plurality of chunks of samples with a predetermined proportion of smaller and larger data sets, randomly selecting samples consistent with the predetermined proportion, marking selected samples with flags to make them ineligible for re-selection, and clearing the flags from the smaller data set after its samples are exhausted. These steps ensure that the training data maintains an optimized balance between real-world and simulated data, preventing bias in the machine learning algorithm and improving computational efficiency.
The claimed method addresses a recognized technical problem in machine learning training: the imbalance between smaller and larger data sets, which can lead to biased models and reduced performance. By randomizing the order of samples and ensuring that all samples in the larger data set are distributed across chunks, the method avoids bias caused by sequential or repetitive data input. Additionally, the marking and clearing of flags reduce redundant operations and ensure that the smaller data set is used efficiently. These improvements are specific to the technical field of machine learning training and are not generic or abstract. The claims integrate the abstract idea of data selection into a practical application by specifying how the data chunks are created, randomized, and managed to train a machine learning algorithm. The steps of random selection, flagging, and clearing are implemented in a computer system and are essential to achieving the claimed technical improvement.
The inventive concept transforms the abstract idea of data selection into a specific, computer-implemented process that improves the functioning of machine learning algorithms. The Federal Circuit has recognized that claims directed to improving the functioning of a computer or a specific technological process are patent-eligible, as demonstrated in McRO, Inc. v. Bandai Namco Games America Inc. and DDR Holdings, LLC v. Hotels.com, L.P.. Here, the amended claims solve a specific problem in machine learning training—data imbalance and bias—through a novel arrangement and management of data chunks. The specific steps recited in amended claim 1 are not routine or conventional. The marking and clearing of flags, combined with the randomization of data chunks, represent a novel approach to managing training data. These steps are explicitly supported by the specification and are not found in the prior art cited by the examiner. Therefore, amended claims 1, 15, and 20 recites an inventive concept that contributes to the technical improvement of machine learning training, integrates the abstract idea into a practical application, and is not directed to well- understood, routine, or conventional activity. Accordingly, amended claims 1, 15, and 20 are patent-eligible under 35 U.S.C. § 101.
Examiner’s response:
Applicant’s arguments have been fully considered but are found to be not persuasive in light of the amendments made on the claims.
Applicant argues that the claims as presented recite an inventive concept that contributes to the technical improvement of machine learning training, however the only mention of any training in the independent claims is in the form of limitations that state the data is provided to a machine learning algorithm. The claims as presented provide methods for organizing data that is eventually fed into a machine learning model. Organizing data in a certain way is not an improvement to the training of a machine learning model, and the actions presented in the amended claims still recite abstract ideas of mental processes related to organizing data in a certain way.
In light of the amendments made on the claims, the rejections made under 35 U.S.C. 101 are withdrawn and new grounds for rejection is presented below.
In reference to Applicant’s arguments on page(s) 10 regarding rejections made under 35 U.S.C. 102:
Claims 1, 3-6, 9-12, 15, and 17-20 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Rand (US 20220253748 Al). Applicants respectfully traverse this rejection.
Applicants have amended independent claims 1, 15, and 22 to, inter alia, incorporate the subject matter of claim 8, which was not rejected under 35 U.S.C. 102 or 103. Applicants respectfully submit that these amendments render this rejection moot.
Examiner’s response:
Applicant’s arguments have been fully considered and are found to be persuasive.
The only amendment made to the independent claims was to roll cancelled claim 8 into the independent claims. As cancelled claim 8 was previously unrejected by any art, this amendment does overcome the primary reference used in the previous office action.
The rejections made under 35 U.S.C. 102 are withdrawn.
Claim Rejections - 35 USC § 101
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claims 1-7 and 9-21 rejected under 35 U.S.C. 101 because they are directed to an abstract idea without significantly more.
Step 1 analysis:
Independent Claim 1 recites, in part, a method for maintaining an optimized mix of samples, therefore falling into the statutory category of process. Independent Claim 15 recites, in part, a system comprising a storage and a processor, therefore falling into the statutory category of machine. Independent Claim 20 recites, in part, a custom data loader embodied in instructions stored on a non-transitory computer- readable medium, therefore falling into the statutory category of machine.
Regarding Claim 1:
Step 2A: Prong 1 analysis:
Claim 1 recites in part:
“creating a plurality of chunks of samples, wherein each chunk contains a predetermined proportion of samples from the smaller data set and the larger data set, while also including substantially all samples in the larger data set are distributed across the plurality of chunks of samples”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses grouping data according to a predetermined proportion of datasets.
“randomizing an order of samples in the first chunk of samples”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses randomizing the order of data.
“randomly selecting samples from both of the smaller data set and the larger data set consistent with the predetermined proportion”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses randomly selecting data according to a predetermined proportion.
“marking selected samples with a selected flag to indicate them as selected to make them ineligible for re-selection”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses flagging pieces of data.
“clearing the selected flag from the samples in the smaller data set after the samples have been exhausted, thereby allowing continued selection of sample from the larger data set to continue while maintaining the predetermined proportion”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses unflagging pieces of data.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“loading a first chunk of samples of the plurality of chunks of samples into a memory”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“providing the samples in the first chunk of samples in the randomized order into the machine learning algorithm”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“wherein maintaining the optimized mix of samples improves a performance of the machine learning algorithm by reducing bias from over reliance on the larger data set”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (biasing) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “loading a first chunk of samples of the plurality of chunks of samples into a memory” and “providing the samples in the first chunk of samples in the randomized order into the machine learning algorithm” is/are recited at a high level of generality and amount(s) to extra-solution activity of receiving data i.e., pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
The additional element(s) of “wherein maintaining the optimized mix of samples improves a performance of the machine learning algorithm by reducing bias from over reliance on the larger data set” is/are directed to particular field(s) of use (data loaders) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 2:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“wherein the smaller data set is a data set derived from real- world driving scenarios, and the larger data set is derived from simulated driving scenarios”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “wherein the smaller data set is a data set derived from real- world driving scenarios, and the larger data set is derived from simulated driving scenarios” is/are recited at a high level of generality and amount(s) to extra-solution activity of receiving data i.e., pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 3:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“wherein the machine learning algorithm is being trained to facilitate self-piloting of an autonomous vehicle”. This additional element is recited at a high level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
As discussed above, the additional element(s) of “wherein the machine learning algorithm is being trained to facilitate self-piloting of an autonomous vehicle” is/are recited at a high-level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 4:
Step 2A: Prong 2 analysis:The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“requesting the first chunk of samples from a cloud storage location prior to loading the first chunk of samples into the memory”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “requesting the first chunk of samples from a cloud storage location prior to loading the first chunk of samples into the memory” is/are recited at a high level of generality and amount(s) to extra-solution activity of receiving data i.e., pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 5:
Step 2A: Prong 1 analysis:Claim 5 recites in part:
“wherein the requesting the first chunk of samples from the cloud storage location includes randomly determining a chunk of samples to request, whereby the chunks of samples are not selected in a predetermined order to prevent the machine learning algorithm from becoming biased by a sequence of chunks of samples”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses randomizing what data to request from storage.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The claim does not recite any additional elements that integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
Regarding Claim 6:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“wherein requesting the first chunk of samples from the cloud storage location is performed by a custom data loader”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (data loaders) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “wherein requesting the first chunk of samples from the cloud storage location is performed by a custom data loader” is/are directed to particular field(s) of use (data loaders) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 7:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“wherein the predetermined proportion is a 1:1 ratio of samples from the smaller data set and the larger data set”. This additional element is recited at a high level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
As discussed above, the additional element(s) of “wherein the predetermined proportion is a 1:1 ratio of samples from the smaller data set and the larger data set” is/are recited at a high-level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 9:
Step 2A: Prong 1 analysis:Claim 9 recites in part:
“randomizing an order of the samples in the second chunk of samples”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses randomizing values.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“after providing the samples in the first chunk into the machine learning algorithm, loading a second chunk of samples into the memory”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“providing the samples in the second chunk of samples in the randomized order into the machine learning algorithm”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “after providing the samples in the first chunk into the machine learning algorithm, loading a second chunk of samples into the memory” and “providing the samples in the second chunk of samples in the randomized order into the machine learning algorithm” is/are recited at a high level of generality and amount(s) to extra-solution activity of receiving data i.e., pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 10:
Step 2A: Prong 2 analysis:The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“wherein loading a first chunk of samples, loading the second chunk of samples, randomizing the order of the samples, and providing the samples to the machine learning algorithm are performed by a custom data loader”. This limitation merely indicates a field of use or technological environment in which the judicial exception is performed (data loaders) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “wherein loading a first chunk of samples, loading the second chunk of samples, randomizing the order of the samples, and providing the samples to the machine learning algorithm are performed by a custom data loader” is/are directed to particular field(s) of use (data loaders) (MPEP 2106.05(h)) and therefore do not provide significantly more than the abstract idea, and thus the claim is subject-matter ineligible.
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 11:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“repeating the method of claim 9 until all chunks of samples have been provided to the machine learning algorithm”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “repeating the method of claim 9 until all chunks of samples have been provided to the machine learning algorithm” is/are recited at a high level of generality and amount(s) to extra-solution activity of receiving data i.e., pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 12:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“repeating the method of claim 9 until the machine learning algorithm achieves a threshold accuracy value”. This additional element is recited at a high level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
As discussed above, the additional element(s) of “repeating the method of claim 9 until the machine learning algorithm achieves a threshold accuracy value” is/are recited at a high-level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 13:
Step 2A: Prong 2 analysis:The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“receiving additional samples into the one of the smaller data set and/or the larger data set”. This additional elements is recited at a high level of generality and amounts to extra-solution activity of gathering data i.e. pre-solution activity of gathering data for use in the claimed process.
“repeating the method of claim 1 with the additional samples to create new chunks of samples”. This additional element is recited at a high level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
The additional element(s) of “receiving additional samples into the one of the smaller data set and/or the larger data set” is/are recited at a high level of generality and amount(s) to extra-solution activity of receiving data i.e., pre-solution activity of gathering data for use in the claimed process. The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory").
As discussed above, the additional element(s) of “repeating the method of claim 1 with the additional samples to create new chunks of samples” is/are recited at a high-level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 14:
Step 2A: Prong 1 analysis:Claim 14 recites in part:
“adjusting the predetermined proportion of samples”. As drafted and under its broadest reasonable interpretation, this limitation covers performance of the limitation in the mind (including an observation, evaluation, judgement, or opinion) or with the aid of pencil and paper. For example, this limitation encompasses modifying a proportion.
Accordingly, at Step 2A: Prong 1, the claim is directed to an abstract idea.
Step 2A: Prong 2 analysis:
The claim does not recite any additional elements that integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
Regarding Claim 15:
Due to claim language similar to that of Claim 1, Claim 15 is rejected for the same reasons as presented above in the rejection of Claim 1, with the exception of the limitations covered below.
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“a storage configured to store instructions”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (storage) (See MPEP 2106.05(f)).
“a processor configured to execute the instructions”. This additional element is recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computer component (processor) (See MPEP 2106.05(f)).
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
As discussed above, the additional element(s) of “a storage configured to store instructions” and “a processor configured to execute the instructions” is/are recited at a high-level of generality such that it/they amount(s) to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Regarding Claim 16:
Due to claim language similar to that of Claim 2, Claim 16 is rejected for the same reasons as presented above in the rejection of Claim 2.
Regarding Claim 17:
Due to claim language similar to that of Claim 3, Claim 17 is rejected for the same reasons as presented above in the rejection of Claim 3.
Regarding Claim 18:
Due to claim language similar to that of Claim 4, Claim 18 is rejected for the same reasons as presented above in the rejection of Claim 4.
Regarding Claim 19:
Due to claim language similar to that of Claim 5, Claim 19 is rejected for the same reasons as presented above in the rejection of Claim 5.
Regarding Claim 20:
Due to claim language similar to that of claims 1 and 15, Claim 20 is rejected for the same reasons as presented above in the rejection of claims 1 and 15.
Regarding Claim 21:
Step 2A: Prong 2 analysis:
The judicial exception is not integrated into practical application. In particular, the claim recites the additional elements of:
“further comprising dynamically adjusting the predetermined proportion of samples from the smaller data set and the larger data set during a training process based on performance metrics of the machine learning algorithm, wherein the performance metrics include accuracy, precision, recall, or other measures of the machine learning algorithm's ability to detect objects in sensor data”. This additional element is recited at a high level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished.
Accordingly at Step 2A: Prong 2, the additional elements individually or in combination do not integrate the judicial exception into a practical application.
Step 2B analysis:
In accordance with Step 2B, the claim does not include additional elements that are sufficient to amount to significantly more that the judicial exception.
As discussed above, the additional element(s) of “further comprising dynamically adjusting the predetermined proportion of samples from the smaller data set and the larger data set during a training process based on performance metrics of the machine learning algorithm, wherein the performance metrics include accuracy, precision, recall, or other measures of the machine learning algorithm's ability to detect objects in sensor data” is/are recited at a high-level of generality such that the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished (See MPEP 2106.05(f)).
Accordingly, at Step 2B, the additional elements individually or in combination do not amount to significantly more than the judicial exception.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20220253748 A1 – the implementation of machine learning model training utilities to generate models for advanced driving assistance system (ADAS), driving assistance, and/or automated vehicle (AV) systems
US 20210375392 A1 – methods, apparatus, systems, and computer program products for developing polygenic risk score (PRS) models
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.
/COREY M SACKALOSKY/Examiner, Art Unit 2128
/OMAR F FERNANDEZ RIVAS/Supervisory Patent Examiner, Art Unit 2128
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