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 .
Status of Claim
This action is in response to application filed on 22 of May 2026.
Claims 1-20 have been amended.
Claims 1-20 are currently pending and are rejected as described below.
Response to Amendment/Argument
35 USC § 101
The applicant asserts that the amended claims cannot practically be performed in the human mind, including using a pen and paper. For example, the human mind is not equipped to perform high-speed, recursive re-weighting of disparate data streams-retrieved from physical memory-against a stored numerical threshold in a real-time feedback loop. Such iterative optimization is a computational task that moves the claim from a general mental observation to a specific algorithmic architecture. The examiner respectfully disagrees. Estimating a bias-correct effect of the particular event by calculating a numerical variance, generating an adjusted forecast by mathematically integrating multiple variables, and refining the adjusted forecast by calculating a performance metric are both a mental process because the human can perform math mentally or with the aid of pen and paper and a mathematical calculation by applicant’s own admission or concession. Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer"). Therefore, the claims remain an abstract idea. The examiner notes that “real-time” is not claimed and that “automatically” under BRI is interpreted as by a computer, a topic to be discussed under 2A Prong II.
Applicant asserts for example, as discussed in Applicant's specification, Applicant's claimed invention, such as claimed in claims 1, 8 and 15, improves the technology or technical
field of demand planning and supply chain management as discussed in ¶18-20 of the instant application. The examiner respectfully disagrees. While the specification may help illuminate the true focus of a claim, when analyzing patent eligibility, reliance on the specification must always yield to the claim language in identifying that focus." Id. at 766; see also Trinity Info Media, 72 F.4th at 1363 ("Our focus is on the claims, as informed by the specification."). At bottom, we must "articulate what the claims are directed to with enough specificity to ensure the step one inquiry is meaningful." Thales Visionix Inc. v. United States, 850 F.3d 1343, 1347 (Fed. Cir. 2017). Therefore, the invention remains an observation (i.e. a mental process) and a mathematical calculation (i.e. a mathematical concept) merely applied by generic computer components disclosed at a high level of generality and do not satisfy the Alice Test. The examiner notes that the ML is disclosed at a high level of generality, and it is interpreted under BRI to be an algorithm. The claims do not disclose any specific type of ML or the steps performed to achieve the desired results and the specification does not provide an any details that shows said improvement. To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology.
Applicant asserts that claimed invention amounts to significantly more than the abstract idea of' a mental process. Because it has been determined that the judicial exception is not integrated into a practical application, the examiner proceeds to Step 2B of the Eligibility Guidelines, which asks whether there is an inventive concept. In making this Step 2B determination, the examiner must consider whether there are specific limitations or elements recited in the claim “that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present” or whether the claim “simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, indicative that an inventive concept may not be present.” Eligibility Guidance, 84 Fed. Reg. 56 (footnote omitted). The examiner must also consider whether the combination of steps perform “in an unconventional way and therefore include an ‘inventive step, ’ rendering the claim eligible at Step 2B ” Id. In this part of the analysis, the examiner considers “the elements of each claim both individually and ‘as an ordered combination’” to determine “whether the additional elements ‘transform the nature of the claim’ into a patent-eligible application.” Alice, 134 S. Ct. at 2354. As discussed above, there is no evidence in the record that the steps of detecting movements, the presence of operators, and gestures, is accomplished in a non-conventional way. Claim 1 amounts to nothing significantly more than an instruction to apply the abstract ideas using generic computer components performing routine computer functions. That is not enough to transform an abstract idea into a patent-eligible invention. See Alice, 573 U.S. at 225-26.
Allowable Subject Matter
Claims 1-20 are objected to as being currently rejected as below, but would be allowable if the independent claims were amended in such a way as to overcome the 35 USC 101 rejection set forth in the action. The prior art of record most closely resembling the applicant’s claimed invention includes Singh et. al. (US 20020169657), Allison et. al. (WO 2024259083), Huber et. al. (US 11625562), and Kakouros et. al. (US 20040088211).
Singh teaches systems and methods for demand forecasting that enable multiple-scenario comparisons and analyses by letting users create forecasts from multiple history streams (for example, shipments data, point-of-sale data, customer order data, return data, etc.) with various alternative forecast algorithm theories. The multiple model framework of the present invention enables users to compare statistical algorithms paired with various history streams (collectively referred to as “models”) so as to run various simulations and evaluate which model will provide the best forecast for a particular product in a given market. Once the user has decided upon which model it will use, it can publish forecast information provided by that model for use by its organization (such as by a downstream supply planning program).
Allison teaches systems and methods for implementing advanced statistical models and machine-learning algorithms to generate predictions. The method includes receiving a plurality of data from one or more sources; processing the plurality of data to select one or more relevant variables; training one or more prediction models based on the one or more relevant variables, and a combination of an advanced statistical model and a machine-learning model; evaluating performance of the one or more trained prediction models based on one or more validation techniques; and deploying at least one prediction model based on the performance for generating predictions.
Huber teaches a method for generating human-machine hybrid predictions of answers to forecasting problems includes: parsing text of an individual forecasting problem to identify keywords; generating machine models based on the keywords; scraping data sources based on the keywords to collect scraped data relevant to the individual forecasting problem; providing the scraped data to the machine models; receiving machine predictions of answers to the individual forecasting problem from the machine models based on the scraped data; providing, by the computer system via a user interface, the scraped data to human participants; receiving, by the computer system via the user interface, human predictions of answers to the individual forecasting problem from the human participants; aggregating the machine predictions with the human predictions to generate aggregated predictions; and generating and outputting a hybrid prediction based on the aggregated predictions.
Kakouros teaches systems and methods of monitoring a demand forecasting process are described. In accordance with a demand forecasting monitoring method, a measure of forecast error variability is computed at each period of a selected time frame, and an indicator of forecast bias is computed at a given period within the selected time frame based on forecast error consistency over periods of the selected time frame prior to the given period. A computer program for implementing the demand forecasting monitoring method is described. A system for monitoring a demand forecasting process that includes a graphical user interface configured to display a measure of standard deviation of percent forecast error at each period of a selected time frame also is described.
None of the above prior art explicitly teaches “estimating a bias-corrected effect of the particular event by calculating a numerical variance between a plurality of prior human-provided estimates and corresponding historical demand data to generate a weighting factor that compensates for human judgement bias”, and these are the reasons which adequately reflect the Examiner's opinion as to why Claims 1-20 are allowable over the prior art of record, and are objected to as provided below.
Claim Rejections - 35 USC § 101
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machines, article of manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea. Alice Corporation Pty. Ltd. v. CLS Bank International, et al., 573 U.S. ____ (2014). See MPEP 2106.03(II).
The claims are then analyzed to determine if the claims are directed to a judicial exception. MPEP §2106.04(a). In determining, whether the claims are directed to a judicial exception, the claims are analyzed to evaluate whether the claims recite a judicial exception (Prong One of Step 2A), and whether the claims recite additional elements that integrate the judicial exception into a practical application (Prong Two of Step 2A). See 2019 Revised Patent Subject Matter Eligibility Guidance (“PEG” 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (Jan. 7, 2019)).
With respect to 2A Prong 1, claim 15 recites “a memory for storing a computer program for collaborative human-machine learning for demand planning; and a processor connected to the memory, wherein the processor is configured to execute program instructions of the computer program comprising: receiving, from a base machine comprising at least one of a statistical model and a machine learning algorithm, an initial forecast for the demand planning produced by processing public information; receiving, via a user interface, an indication from a user of a particular event identified using private information; estimating a bias-corrected effect of the particular event by calculating a numerical variance between a plurality of prior human-provided estimates and corresponding historical demand data to generate a weighting factor that compensates for human judgement bias; receiving lagged demand data and lagged judgement data from memory; generating an adjusted forecast for the demand planning by mathematically integrating the initial forecast, the weighting factor, the lagged demand data, and the lagged judgement data; and automatically refining the adjusted forecast by calculating a performance metric that compares the adjusted forecast against a threshold error value stored in the memory and re-weighting the integration of the lagged demand data and the weighting factor in a recursive feedback loop until the performance metric exceeds the threshold error value”. Claims 1 and 8 discloses similar limitations as Claim 15 as disclosed, and therefore recites an abstract idea.
More specifically, claims 1, 8, and 15 are directed to “Mental Process” in particular “concepts performed in the human mind (including an observation, evaluation, judgment, opinion)”, “Mathematical Concepts” in particular “mathematical calculations”, and “Certain Methods of Organizing Human Activity in particular “commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations)” as discussed in MPEP §2106.04(a)(2), and in the 2019-01-08 Revised Patent Subject Matter Eligibility Guidance. Accordingly, the claims recite an abstract idea.
Dependent claims 2-7, 9-14, and 16-20 further recite abstract idea(s) contained within the independent claims, and do not contribute to significant more or enable practical application. Thus, the dependent claims are rejected under 101 based on the same rationale as the independent claims.
Under Prong Two of Step 2A of the Alice/Mayo test, the examiner acknowledges that Claims 1, 8, and 15 recite additional elements yet the additional elements do not integrate the abstract idea into a practical application. In order for the judicial exception to be “integrated into a practical application”, an additional element or a combination of additional elements in the claim “will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.” PEG, 84 Fed. Reg. 54 (Jan. 7, 2019). The courts have identified examples in which a judicial exception has not been integrated into a practical application when “an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.” PEG, 84 Fed. Reg. 55 (Jan. 7, 2019); MPEP § 2106.05(h). The claims are directed to an abstract idea.
In particular, claims 1, 8, and 15 recite additional elements boldened and underlined above. These are generic computer components recited as performing generic computer functions that are mere instructions to apply an exception, because it does no more than merely invoke computers or machinery as a tool to perform an existing process. Further, the remaining additional element(s) italicized above reflect insignificant extra solution activities to the judicial exception. Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
With respect to step 2B, claims 1, 8, and 15 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional elements described above. These are generic computer components recited as performing generic computer functions that are mere instructions to apply an exception, because it does no more than merely invoke computers or machinery as a tool to perform an existing process, as evidenced by at least ¶29-30 “Computing environment 200 contains an example of an environment for the execution of at least some of the computer code (stored in block 201) involved in performing the disclosed methods, such as improving the accuracy for demand planning by using collaborative human-machine learning. In addition to block 201, computing environment 200 includes, for example, demand planning system 103, wide area network (WAN) 224, end user device (EUD) 202, remote server 203, public cloud 204, and private cloud 205. In this embodiment, demand planning system 103 includes processor set 206 (including processing circuitry 207 and cache 208), communication fabric 209, volatile memory 210, persistent storage 211 (including operating system 212 and block 201, as identified above), peripheral device set 213 (including user interface (UI) device set 214, storage 215, and Internet of Things (IoT) sensor set 216), and network module 217. Remote server 203 includes remote database 218. Public cloud 204 includes gateway 219, cloud orchestration module 220, host physical machine set 221, virtual machine set 222, and container set 223. Demand planning system 103 may take the form of a desktop computer, laptop computer, tablet computer, smart phone, smart watch or other wearable computer, mainframe computer, quantum computer or any other form of computer or mobile device now known or to be developed in the future that is capable of running a program, accessing a network or querying a database, such as remote database 218. As is well understood in the art of computer technology, and depending upon the technology, performance of a computer-implemented method may be distributed among multiple computers and/or between multiple locations. On the other hand, in this presentation of computing environment 200, detailed discussion is focused on a single computer, specifically demand planning system 103, to keep the presentation as simple as possible. Demand planning system 103 may be located in a cloud, even though it is not shown in a cloud in FIG. 2. On the other hand, demand planning system 103 is not required to be in a cloud except to any extent as may be affirmatively indicated”.
As a result, claims 1, 8, and 15 do not include additional elements, when recited alone or in combination, that amount to significantly more than the above-identified judicial exception (the abstract idea). Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually.
Claims 2-7, 9-14, and 16-20 do not disclose additional elements, further narrowing the abstract ideas of the independent claims and thus not practically integrated under prong 2A as part of a practical application or under 2B not significantly more for the same reasons and rationale as above.
After considering all claim elements, both individually and in combination, Examiner has determined that the claims are directed to the above abstract ideas and do not amount to significantly more. See Alice Corporation Pty. Ltd. v. CLS Bank International, No. 13–298.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATHEUS R STIVALETTI whose telephone number is (571)272-5758. The examiner can normally be reached on M-F 8:30-5:30.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao (Rob) Wu can be reached on (571)272-7761. The fax phone number for the organization where this application or proceeding is assigned is 571-273-1822.
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/MATHEUS RIBEIRO STIVALETTI/Examiner, Art Unit 3623 8/6/2026
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