DETAILED ACTION
Status of the Application
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This communication is a non-final action in response to application filed on 4/27/26. Claims 1-7 and 10-20 are currently pending and have been considered below.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 4/27/26 has been entered.
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 10-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-7 and 10-20 are determined to be directed to an abstract idea.
The claims 1-7 and 10-20 are directed to a judicial exception (i.e., law of nature, natural phenomenon, or abstract idea), without providing a practical application integration and without providing significantly more.
As per Step 1 of the subject matter eligibility analysis, Claims 1-7 and 10-20 are directed to a method, system (i.e., apparatus), and medium (i.e., product) which are within the four statutory categories of invention.
As per Step 2A-Prong 1 of the subject matter eligibility analysis, Claims 1, 19 and 20 recite the abstract idea of interactively communicate with a user to obtain a target goal outcome desired based on varied input conditions by first generating a first estimation outcome from a first plurality of input conditions selected by said user; generating a parallel estimation outcome from a second plurality of input conditions, wherein at least one of said input conditions in said first plurality of input conditions is different from any of said second plurality of input conditions; determining internal and external components as part of input conditions to deploy models that can be managed with shared versus exclusive internal and external components to prevent impacts to cost or outcome of said target goal outcome and updating said parallel and said target goal outcome; analyzing said first and parallel outcomes estimations with one another to determine which estimation produces a similar or identical result with said target goal outcome; when either said first estimation or said parallel estimation outcome do not produce the similar or identical a final target goal outcome, interactively changing said first input conditions until said target goal outcome is achieved based on another parallel outcome estimation generated; performing a batch evaluation simulation so as to generate input conditions that can provide said target goal outcome; selecting either said first, or said parallel estimation or another parallel estimation outcome by analyzing said outcomes with one another and with a said target goal outcome; generating a comparison result between said first and said parallel outcome results; wherein said comparison result includes at least one turning point, said turning point being a deviation point affecting an outcome difference between said first estimation outcome and said parallel estimation outcome; and performing an operation by setting a selected set of input conditions based on said comparison result generated that will result in similar or identical target goal outcome; which include mental processes (observing and evaluating input conditions to generate and perform input conditions to achieve a target outcome), and fundamental economic practice (managing inputs for a target outcome), managing personal behavior and interactions between people (following rules and instructions to generate and perform input conditions to achieve a target outcome). Claims 2-7 and 10-18 are directed to the abstract idea of claim 1 with further details on the parameters/attributes of the abstract idea which includes mental processes and certain methods of organizing human activity for similar reasons as provided above for claim 1. After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
As per Step 2A-Prong 2 of the subject matter eligibility analysis, while the claims 1-7 and 10-20 recite additional limitations which are hardware or software elements, such as computer, a drag and drop menu, computer system, comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method, computer program product, comprising: one or more non-transitory computer-readable storage media and program instructions stored on at least one or more tangible storage media, the program instructions executable by a processor to cause the processor to perform a method; these limitations are not enough to qualify as a practical application being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do not integrate an abstract idea into a practical application (MPEP 2106.05(f)&(h)). The claims do not amount to "practical application" for the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
As per Step 2B of the subject matter eligibility analysis, while the claims 1-7 and 10-20 recite additional limitations which are hardware or software elements, such as computer, a drag and drop menu, computer system, comprising: one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method, computer program product, comprising: one or more non-transitory computer-readable storage media and program instructions stored on at least one or more tangible storage media, the program instructions executable by a processor to cause the processor to perform a method; these limitations are not enough to qualify as “significantly more” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do provide significantly more to an abstract idea (MPEP 2106.05 (f) & (h)). The claims do not amount to "significantly more" than the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the field; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Therefore, since there are no limitations in the claims 1-7 and 10-20 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, and looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant’s arguments have been fully considered and does not overcome al of the rejections. Details are provided below.
Arguments on rejections under 35 U.S.C. 101:
Applicants argued that the claims are not directed to an abstract idea. Examiner respectfully disagrees.
Applicant’s claimed invention recites the abstract idea of mental processes (observing and evaluating input conditions to generate and perform input conditions to achieve a target outcome), and fundamental economic practice (managing inputs for a target outcome), managing personal behavior and interactions between people (following rules and instructions to generate and perform input conditions to achieve a target outcome). Since the claim does not present the argued complexities, the limitations will be evaluated under broadest reasonable interpretation which results in the abstract idea identified above could clearly be performed in human mind.
Applicants also argued that the claims are directed to a practical application and/or significantly more. Examiner respectfully disagrees.
The additional elements are generic computing technologies merely used for data collection/analysis/manipulation and are not enough to qualify as a practical application or significantly more being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment (MPEP 2106.05(f)&(h)). Further, applicant’s claimed invention does not pertain to the fact pattern of McRO or Bascom cases.
Conclusion
Closest prior art to the claimed invention includes Crabtree et al. (Pub. No. US 2017/0124492 A1), Floren et al. (Pub. No. US 11,650,728 B2). None of the prior art alone or in combination teaches the claimed invention, wherein the novelty is in combination of all limitations.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and all the references on PTO-892 Notice of Reference Cited should be duly noted by the Applicant as they can be subsequently used during prosecution, at least note the following:
- Pub. No.: US 7,788,200 B2 see Abstract note “Seeking goals in data that can be expressed as rows and columns is provided through predictive analytics. If a desired goal is achievable, the changes to the rows and/or columns that can achieve the goal are presented to a user. If the desired goal is not achievable, an error message or other indicator can be presented to the user. Predictive analytics can include a predictive algorithm, various data mining techniques, or other predictive techniques. A confidence metric of a goal-seek result can be normalized to estimate the degree of confidence that a particular change will yield the desired outcome.”
- Pub. No.: US 2018/0075371 A1 see Abstract note “A method of training a Machine Learning Algorithm, the method comprising: generating a training set for training the MLA, the training set comprising a plurality of feature vectors and respectively associated estimation errors, the generating comprises: generating the plurality of feature vectors based on history data associated with an industrial process; identifying a respective value of a target process feature within each feature vector; computing a regression function; determining an estimated outcome value for each respective value of the target process feature based on the regression function; and computing the estimation error for each feature vector based on the respectively associated outcome value and the respectively associated estimated outcome value. The method also comprises training the MLA based on the training set for predicting the respective estimation error for each feature vector, the training the MLA comprises inputting each feature vector and the respectively associated estimation error into the MLA.”
- Pub. No.: US 2022/0108215 A1 see Abstract note “The present disclosure provides iterative blackbox optimization techniques that estimate the gradient of a function. According to an aspect of the present disclosure, a plurality of perturbations used at each iteration can be sampled from a non-orthogonal sampling distribution. As one example, in some implementations, perturbations that have been previously evaluated in previous iterations can be re-used at the current iteration. thereby conserving computing resources because the re-used perturbations do not need to be re-evaluated at the current iteration. In another example, in addition or alternatively to the use of previously evaluated perturbations, the perturbations evaluated at the current iteration can be sampled from a non-orthogonal sampling distribution.”
- Pub. No.: WO 2017/000974 A1 see Abstract note “A set of modified records is generated based on a new record and a training set of records. The generated set of records are inputted into a predictive model. The inputted set of records are filtered based on a desired outcome and a predicted outcome of the predictive model for the inputted set of records. At least one of the filtered records is recommended if the desired outcome 1 does not match a predicted outcome of the predictive model for the new record.”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEHMET YESILDAG whose telephone number is (571)272-3257. The examiner can normally be reached M-F 8:30 am - 5:00 pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Sincerely,
/MEHMET YESILDAG/Primary Examiner, Art Unit 3624
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