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 .
DETAILED ACTION
Status of Claims
Request for Continued Examination under 37 CFR 1.1141
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 March 6, 2026 has been entered.
This action is a Non-Final action in response to the communications filed on 02/17/2026 and 03/06/2026.
Claims 1, 10 and 17 have been amended. Claims 1 – 20 are currently pending and have been examined in this application.
Response to Amendment
Applicant’s amendment has been considered.
Response to Arguments
Applicant’s remarks have been considered.
Applicant argues, “ This computer implemented optimization and operational control is not practically performable in the human mind at the required scale and with the claimed data-driven predictive modeling.” ( pgs. 8-9)
Examiner respectfully disagrees. The claims encompass Mental Processes related to observation and evaluation of data but for the recitation of generic computer components (e.g. a computing device). For example, determining a plurality of products for a product release, number of features, testing timing using previously trained ML models and generating an optimal product deployment sequence can reasonably be performed using the human mind or with a pen/paper or with a generic computer.
Based on MPEP 2106.04(a)(2)(III)(C), “Claims can recite a mental process even if they are claimed as being performed on a computer.” Here, generic computer components (e.g. a computing device) are performing generic computer functions such as determining a plurality of products for a product release, number of features, testing timing using previously trained ML models (complex mathematics) and generating an optimal product deployment sequence. Regarding the deployment sequence, as written the limitation is merely sending the product deployment sequence to another computer for controlling deployment. There is no active deployment step being performed. Examiner further notes the use of trained ML models is recited in a generic manner in the claims and the training of the ML model is not positively recited.
Additionally, the claims encompass Certain Methods of Organizing Human Activity. Accordingly, the claims recite an abstract idea.
Applicant argues, “ Applicant further submits that the Office Action's analysis also improperly treats "using ML models" as automatically reciting a judicial exception..” (pgs. 9-10)
Examiner respectfully disagrees. The use of ML models is a part of the abstract idea, but is not interpreted solely to be abstract.
See 35 U.S.C. 101 rejection.
Applicant argues, “ The August 4, 2025 USPTO memorandum cautions examiners not to oversimplify claims into "apply it," and to assess eligibility based on the claim as a whole, including how limitations interact to provide a particular way of achieving a technical result.” (pg. 10)
In McRO the claims were directed to an improvement in computer related technology by allowing computers to produce accurate and realistic lip synchronization and facial expressions in animated characters. The court in McRo looked to the specification which described the invention as improving computer animation through the use of specific rules and how the claimed rules enabled the automation of specific animation tasks that previously could not be automated, utilizing rules in a specific technological way (e.g. a particular way to achieve a desired outcome). The McRO court also noted that the claims described a specific way to solve the problem of producing accurate and realistic lip synchronization and animation.
Unlike McRo, the instant application focuses on generic computer components (e.g. a computing device) performing generic computer functions such as determining a plurality of products for a product release, number of features, testing timing using previously trained ML models (complex mathematics) and generating an optimal product deployment sequence. This functionality demonstrates abstract concepts (e.g. Certain Methods of Organizing Human Activity) and may provide an improved business process for providing an optimal product deployment sequence for product release but a does not demonstrate an improvement to technology (e.g. a computer) or a technical field.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites:
receiving, …, a request for a recommendation of an optimal product deployment sequence for a product release from another computing device;
determining, …, a plurality of products associated with the product release, the plurality of products including a product that is being released and one or more interlocks linked to the product release;
determining, .., a number of features that are to be deployed for each product of the plurality of products;
determining, .., a testing that is to be performed for each product of the plurality of products;
determining, .. using one or more machine learning (ML) models trained using a training dataset generated from historical product release data, a probabilistic time to test the features that are to be deployed for each product of the plurality of products, wherein the one or more ML models are configured to determine weights applied to parameters that influence performance of the one or more ML models;
generating,..., the optimal product deployment sequence for the product release to minimize total deployment time and reduce resource contention across testing environments based on a release sequence determined from historical deployments and the probabilistic times to test the features that are to be deployed;
The limitation under its broadest reasonable interpretation covers Certain Methods of Organizing Human Activity related to commercial or legal actions (e.g. business/customer impact of deployment) but for the recitation of generic computer components (e.g. a computing device). For example, determining a plurality of products for a product release, number of features and a probabilistic testing timing are related to business relations/processes. Additionally, the claims encompass Mental Processes related to observation and evaluation of data. The claims can reasonably be performed using the human mind or with a pen/paper or a generic computer component. Accordingly, the claim recite an abstract ideas.
Independent Claims 10 and 17 substantially recite the subject matter of Claim 1 and also include the abstract ideas identified above. The dependent claims encompass the same abstract ideas. For instance, Claim 2 is directed to a ridge regression algorithm, Claim 3 is directed to a linear regression model, Claim 4 is directed to XGBoost algorithm, Claims 5-8 are directed to buffer time for testing, Claim 9 is directed to determining test cases. Claims 12-16 and 18-20 substantially recite the subject matter of claims 2-9 and encompass same abstract concept. Thus, the dependent claims further limit the abstract concepts found in the independent claims.
The judicial exception is not integrated into a practical application. Claim 1 recites the additional element of a computing device. Claims 10 and 17 recites the additional elements of non-transitory machine-readable mediums, one or more processor and a computing device. These are generic computer components recited at a high level of generality as performing generic computer functionality (see Spec ¶0045, general purpose computer).
For instance, the step of receiving a request for a recommendation of product deployment sequence is data gathering activity. The steps of determining a plurality of products associated with a product release, a number of features to be deployed, testing to be performed, a probabilistic time for testing and generating an optimal product deployment sequence involves collecting and analyzing data (data gathering). Examiner notes that the use of ML models that have been previously trained to determine a probabilistic testing time are generically recited. The step of sending information about the optimal product deployment sequence for automatically controlling deployment and testing of the plurality of products is merely data transmission of the recommendation that a user at another computer can implement from a UI (see Spec ¶0063).
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a computing device). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (e.g. a computing device). Therefore, the additional elements do not integrate the abstract ideas into a practical application because it does not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As stated above, the additional elements of a computing device, one or more processors and crm are considered generic computer components performing generic computer functions that amount to no more than instructions to implement the judicial exception. Mere, instructions to apply an exception using generic computer components cannot provide an inventive concept.
The dependent claims when analyzed both individually and in combination are also held to be ineligible for the same reason above and the additional recited limitations fail to establish that the claims are not directed to an abstract. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Therefore, Claims 1-20 are not patent eligible.
Conclusion
The prior art made of record and not relied upon is considered relevant but not applied:
Frank et al. (US 2017/0177324) discloses managing a deployment pipeline using an inheritable and extensible source code template—generally referred to as a live pipeline template (LPT) which are used to launch, maintain and update the services.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Renae Feacher whose telephone number is 571-270-5485. The Examiner can normally be reached Monday-Friday, 9:00 am - 5:00 pm. If attempts to reach the examiner by telephone are unsuccessful, the Examiner's supervisor, Beth Boswell can be reached at 571-272-6737.
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/Renae Feacher/
Primary Examiner, Art Unit 3625
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