Ny 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
This is a final rejection. Claims 1-21 are pending.
Information Disclosure Statement (IDS)
The information disclosure statement(s) filed on 03/12/2021 comply with the provisions 37 CFR 1.97, 1.98, and MPEP 609 and is considered by the Examiner.
Status of Claims
Applicant’s amendment date 12/30/2025, amending claims 1, 8, and 15.
Response to Amendment
The previously pending rejection under 35 USC 101, will be maintained. The 101 rejection is updated in light of the amendments.
With regard to the rejection under 35 USC 103- Applicant’s arguments, see pages 24-25, filed 05/20/2025, with respect to the art rejection have been fully considered and are persuasive, the rejection under 35 USC 103 has been withdrawn. No art rejection has been put forth in the rejection for the reason found in the “Allowable Subject Matter” section found below.
Response to Arguments
Applicant's arguments filed 12/30/2025 have been fully considered but they are not persuasive.
Response to Arguments under 35 USC 101:
Applicant argues (Pages 19-20 of the remarks):
here, the amended Claim 1 employs these operations as a specific mechanism to correct data drift within an automated inventory tracking system. In other words, the quoted claim operations use mathematics as a tool to improve a technical process, rather than claiming the mathematical concept itself.
Therefore, amended Claim 1, as a whole, is not directed to a mental process itself. Rather, the claim is rooted in the functioning of computer and network technology to achieve a reliable and automated, end-to-end logistics solution. Accordingly, the amended Claim 1 recites elements that are not directed to the alleged mental process and does not fall within a judicial exception under Step 2A, Prong One of the Alice/Mayo analysis.
Examiner respectfully disagrees:
The Applicant's Specification titled " PROACTIVE REQUEST COMMUNICATION SYSTEM WITH IMPROVED DATA PREDICTION BASED ON ANTICIPATED EVENTS" emphasizes the business need for data analysis, "In summary, the present disclosure relates to methods and systems for predicting a recommended amount of the first item at a future time " (see specification)
As the bolded claim limitations (see 101 rejection below) demonstrate, independent claims 1, 8 and 15 are recites the abstract idea of various data observations, evaluations, judgements, and/or opinions regarding supply chain data/parameters including predicting a recommended amount of the first item at a future time, and visualizing/formatting of the resulting output prediction, which are concepts capable of being performed mentally and/or with the aid of pen and paper. which is considered Mental processes – concepts performed in the human mind (including an observation, evaluation, judgement, opinion. See MPEP §2106.04(a)(2)(II).
As the bolded claim limitations (see 101 rejection below) above demonstrate, independent claims 1, 8 and 15 are recites the abstract idea of predicting a removal of an item and recommending amount of the first item at a future time which is part of commercial interactions, e.g. managing sales activities or behaviors and/or business relations. In example aspects, predicting a recommended amount of the first item at a future time. which is considered certain methods of organizing human activity because the bolded claim limitations pertain to (i) commercial or legal interactions and (II) fundamental economic principles or practices . See MPEP §2106.04(a)(2)(II).
Applicant argues (Pages 23-27 of the remarks):
Amended Claim 1 recites elements that are directed to this specific technical solution. For example, amended Claim 1 recites that the "processor is configured to" "detect an anomalous activity with respect to the received event data," where the anomaly corresponds to an "unexpected amount of item removal events that is greater than an expected number of item removal events according to a recent trend in the event data for the [first] item," and "in response to detecting the anomalous activity, adjust .. The process of cumulative error redistribution is not a generic computer implementation of an abstract idea. Instead, it is a specific, technical improvement to the functioning of computer-based inventory prediction systems.
…
Amended Claim 1 is Analogous to Eligible USPTO Examples: Example 40 … Example 46 Prong One and Prong Two analysis. See MPEP § 2106.04(II)(A)(2); see also, § 2106.04(d)(l) and § 2016.05(1). Even assuming arguendo that the claims are directed to an abstract idea, they are nevertheless directed to significantly more than such an abstract idea and thus are patent-eligible under Step 2B. See MPEP § 2106.05.
Examiner respectfully disagrees:
First, with regard to applicant argument that the instant claims are similar to examples 36 examiner respectfully disagree, the current claims are irreconcilably different than example 36, the model is developed using a supervised training algorithm using numerous images of each item at multiple distances and positions with respect to the camera. During training, characteristics of each item are extracted from the images including character information such as the item’s name and identification code and contour information such as the shape of the item and/or the shape of the packaging for the item. The recognition model may be updated as needed when items are added or discontinued based on imaging data in real-time. Example 46 Claim 2 depends from claim 1, and adds a wherein clause specifying that the system further comprises a feed dispenser, and that the monitoring component is further configured for performing limitation (d) regarding a control signal that is sent to the feed dispenser. It is important to remember during claim interpretation that no limitations can be disregarded and the mere fact that the limitation appears in a “wherein” clause does not automatically mean that it is not given weight. In this case, when the wherein clause is considered in view of the specification, it is clear that the wherein clause has patentable weight, in that the claim requires the presence of the feed dispenser, and that the monitoring component is further configured for performing limitation (d). Also, because claim 2 is a system claim, its BRI requires the structure for performing the function of limitation (d) to be present, even though that function (sending a control signal) only needs to occur if a condition precedent is met (i.e., when the analysis results for the animal indicate that the animal is exhibiting an aberrant behavioral pattern indicative of grass tetany). In contrast here, the currently argued claims are devoid of any technological improvement remotely similar to facial image adjustment or recognition in example 39 independent claims 1, 10, and 16 recites the abstract idea of the abstract idea of predicting a removal of an item and recommending amount of the first item at a future time which is part of commercial interactions, e.g. managing sales activities or behaviors and/or business relations. In example aspects, predicting a recommended amount of the first item at a future time.
In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional element, that integrate the exception into a practical application of that exception. An “additional element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use exception, such that it is more than a drafting effort designed to monopolize the exception.
The claims recites the additional limitation a system, comprising: tracking subsystem a data prediction subsystem, a network communications/interface, first processor communicatively coupled to the network interface, algorithm, AI, user interface, display and device are recited in a high level of generality and recited as performing generic computer functions routinely used in computer applications. Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp. 134 S. Ct, at 2360,110 USPQ2d at 1984 (see MPEP 2106.05(f). All of these additional elements are not significantly more because these, again, are merely the software and/or hardware components used to implement the abstract idea on a general purpose computer.
The additional elements of a “algorithm, AI, and model”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “algorithm, AI, and model” is insufficient to show a practical application of the recited abstract idea. All of these additional elements are not significantly more because these, again, are merely the software and/or hardware components used to implement the abstract idea on a general purpose computer.
The use of generic computer component to determining an offer for a transaction processing system service based on revenue forecast does not impose any meaningful limit on the computer implementation of 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. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (step 2A-prong two: NO).
Further, with regard to mining (i.e., searching over a network), receiving, processing, storing data, and parsing (i.e. extract, transform data), the courts have recognized the following computer functions as well-understood, routing, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (i.e. “receiving, processing, transmitting, storing data”, etc.) are well-understood, routine, etc. (MPEP 2106.05(d))
The Alice framework, step 2B (Part 2 of Mayo) determine if the claim is sufficient to ensure that the claim amounts to “significantly more” than the abstract idea itself. These additional elements recite conventional computer components and conventional functions of:
Claims 1, 8 and 15 does not include my limitations amounting to significantly more than the abstract idea, along. Claims 1, 8, and 15 includes various elements that are not directed to the abstract idea. These elements include a system, comprising: tracking subsystem a data prediction subsystem, a network communications/interface, first processor communicatively coupled to the network interface, algorithm, AI, user interface, display and device. Examiner asserts that the additional elements are a generic computing element performing generic computing functions. (See MPEP 2106.05(f))
Therefore, the claims at issue do not require any nonconventional computer, network, or display components, or even a “non-conventional and non-generic arrangement of know, conventional pieces,” but merely call for performance of the claimed on a set of generic computer components” and display devices.
The computing elements with a computing device is recited at high level of generality (e.g. a generic device performing a generic computer function of processing data). Thus, this step is no more than mere instructions to apply the exception on a generic computer. In addition, using a processor to process data has been well-understood routing, conventional activity in the industry for many years.
Generic computer features, such as system or storage, do not amount to significantly more than the abstract idea. These limitations merely describe implementation for the invention using elements of a general-purpose system, which is not sufficient to amount to significantly more. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976; Versata Dev. Group, Inc. v. SAP Am. Inc., 793 F .3d 1306, 1334, 115 USPQ2d 1681, 1791 (Federal Circuit 2015).
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 1-21 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea without a practical application or significantly more than the abstract idea.
Under the 35 U.S.C. §101 subject matter eligibility two-part analysis, Step 1 addresses whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. See MPEP §2106.03. If the claim does fall within one of the statutory categories, it must then be determined in Step 2A [prong 1] whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea). See MPEP §2106.04. If the claim is directed toward a judicial exception, it must then be determined in Step 2A [prong 2] whether the judicial exception is integrated into a practical application. See MPEP §2106.04(d). Finally, if the judicial exception is not integrated into a practical application, it must additionally be determined in Step 2B whether the claim recites "significantly more" than the abstract idea. See MPEP §2106.05.
Examiner note: The Office's 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) is currently found in the Ninth Edition, Revision 10.2019 (revised June 2020) of the Manual of Patent Examination Procedure (MPEP), specifically incorporated in MPEP §2106.03 through MPEP §2106.07(c).
Regarding Step 1
Claims 1-7 are directed to “a system”(Machine), claims 8-14 are directed to a method (process), and claims 15-21 are directed to a system (Machine). Thus, all claims fall within one of the four statutory categories as required by Step 1.
Regarding Step 2A [prong 1]
Claims 1-21 are directed toward the judicial exception of an abstract idea.
Independent claims 8 and 15 recites essentially the same abstract features as claim 1, thus are abstract for the same reasons as claim 1.
Regarding independent claim 1, the bolded limitations emphasized below correspond to the abstract ideas of the claimed invention:
Claim 1. A system, comprising:
at each of a plurality of locations, an event tracking subsystem comprising a first processor configured to detect item removal events at at least one location of the plurality of locations;
a data prediction subsystem comprising:
a network interface configured to receive event data based on the item removal events detected at the plurality of locations, the event data comprising a first set of event data indicating amounts of a first item removed from a first location on each day over a previous period of time and a second set of event data indicating amounts of the first item removed from other locations than the first location on each day over the previous period of time; and
a second processor communicatively coupled to the network interface, the second processor configured to:
receive the event data;
detect an anomalous activity with respect to the received event data, wherein the anomalous activity corresponds to an unexpected amount of item removal events that is greater than an expected number of item removal events according to a recent trend in the event data for the first item:
in response to detecting the anomalous activity, adjust the received event data by reducing the unexpected amount of item removal events according to the recent trend in the event data;
generate training data based on the event data, wherein generating the training data comprises:
determine training data based on the event for days with a not-empty status associated with the first item, a longitudinal component comprising a weighted average of removal event amounts for the first item at the first location over a first period of time;
determine, based on the event data for days with the not-empty status associated with the first item, a cross-sectional component comprising a second set of weighted averages of removal event amounts for the first item or for another item from an item category associated with the first item at one or more of the other locations for a second period of time different than the first period of time;
train an algorithm associated with an artificial intelligence model on the training data, wherein training the algorithm associated with the artificial intelligence model on the training data comprises:
use actual item removal values for the first item on days with the not-empty status as a plurality of target values, wherein each target value from among the plurality of target values indicates an actual amount of removal event for the first item at the first location on a respective day having the not-empty status;
use the longitudinal component and the cross-sectional component as a plurality of predictors, wherein:
each predictor from among the plurality of predictors indicates an expected amount of removal event for the first item or another item associated with item category at the first location or at the one or more other locations on the respective day having the an empty status; and a given predictor from among the plurality of predictors is associated with a counterpart target value from among the plurality of target values; and determine a relationship between the given predictor and the counterpart target value;
execute the trained algorithm;
for a first day of the first set of event data having zero events corresponding to the empty status indicating that the first item is not believed to be present at the first location:
determine, by the executed trained algorithm and using the determined relationship between the given predictor and the counterpart target value,
determine, by the executed trained algorithm and using the determined relationship between the given predictor and the counterpart target value, the longitudinal component, and the cross-sectional component, an anticipated event value for the first item at the first location, the anticipated event value indicating an expected amount of removal events for the first item per historical day that would have occurred at the first location based on the first set of weighted averages of removal events and the second set of weighted averages of removal events for the days with the not-empty status associated with the first item; and
determine, based at least in part on the anticipated event value and the updated status for the first item at the first location, a prediction value corresponding to a recommended amount of the first item to request at a future time;
determine, for a given day from among a plurality of days in a future prediction period, a rounded value that represents aninteger quantity of predicted item removals for the given day, based at least in part upon a respective prediction value for the given day and a previous cumulative error carried over from one or more previous days;
determine, based at least in part upon a plurality of rounded values for the plurality of days in the future prediction period, a cumulative rounding error across the future prediction period, wherein the cumulative rounding error indicates a difference between a sum of non-integer prediction values and a sum of rounded prediction values for the plurality of days, wherein each rounded value from among the plurality of days is associated with an adjusted prediction value that comprises a redistributed portion of the cumulative rounding error;redistribute the cumulative rounding error across the plurality of days in the future prediction period;
adjust the prediction value to an integer value for each day of the future prediction period based on the redistributed cumulative rounding error;
reduce a number of item transportation requests for the first item based on the prediction value as compared to a greater number of transportation requests for the first item if the prediction value was based only on removal events of the first item recorded for the days when the first item had the not-empty status;
an item request device associated with the first location, the item request device comprising a third processor configured to:
receive the prediction value;
in response to receiving the prediction value, automatically populate the prediction value in a field of an interface on a display; and
in response to receiving the prediction value and the prediction value being automatically populated on the field of the interface, automatically initiate a network communication to send a request for an amount of the first item based at least in part on the prediction value.
The Applicant's Specification titled " PROACTIVE REQUEST COMMUNICATION SYSTEM WITH IMPROVED DATA PREDICTION BASED ON ANTICIPATED EVENTS" emphasizes the business need for data analysis, "In summary, the present disclosure relates to methods and systems for predicting a recommended amount of the first item at a future time " (see specification)
As the bolded claim limitations above demonstrate, independent claims 1, 8 and 15 are recites the abstract idea of various data observations, evaluations, judgements, and/or opinions regarding supply chain data/parameters including predicting a recommended amount of the first item at a future time, and visualizing/formatting of the resulting output prediction, which are concepts capable of being performed mentally and/or with the aid of pen and paper. which is considered Mental processes – concepts performed in the human mind (including an observation, evaluation, judgement, opinion. See MPEP §2106.04(a)(2)(II).
As the bolded claim limitations above demonstrate, independent claims 1, 8 and 15 are recites the abstract idea of predicting a removal of an item and recommending amount of the first item at a future time which is part of commercial interactions, e.g. managing sales activities or behaviors and/or business relations. In example aspects, predicting a recommended amount of the first item at a future time. which is considered certain methods of organizing human activity because the bolded claim limitations pertain to (i) commercial or legal interactions and (II) fundamental economic principles or practices . See MPEP §2106.04(a)(2)(II).
Dependent claims 2-7, 9-14, and 16-21 further reiterate the same abstract ideas with further embellishments (the bolded limitations), such as
claim 2 (Similarly Claims 9 and 16) wherein the second period of time associated with the cross-sectional component is less than the first period of time associated with the longitudinal component.
claim 3 (Similarly Claims 10 and 17) determining an average regional event amount for a location region associated with the first location;
determining a region-to-location coefficient based on a ratio of total removal event amount for the first location and an average event amount for an average location in the location region, wherein:
the average event amount indicates a location-normalized event amount where a total event amount is normalized by a number of location in the location region; and
the average location represents a location associated with the average event amount;
determining the longitudinal component using the average regional event amount and the region-to-location coefficient.
claim 4 (Similarly Claims 11 and 18) determining an average regional event amount for a location region associated with the first location;
determining a location-to-category coefficient based on a ratio of a total removal event amount for the first location and an average event amount for an item category associated with the first item in the location region, wherein the average event amount indicates a location-normalized event amount where a total event amount is normalized by a number of location in the location region; and
determining the cross-sectional component using the average regional event amount and the location-to-category coefficient.
claim 5 (Similarly Claims 12 and 19) determine event data properties associated with the plurality of locations, the event data properties comprising characteristics of the received event data; and
determine, from a predefined hierarchy of models, a model configured to
determine the anticipated event value for the first item at the first location, based at least in part on the event data properties.
claim 6 (Similarly Claims 13 and 20) determine that the event properties are greater than one or more predefined threshold values; and
after determining that the event properties are greater than the one or more predefined threshold values,
determine the anticipated event value as a weighted combination of the longitudinal component and the cross-sectional component.
claim 7 (Similarly Claims 14 and 21) determine that at least one of the event properties is less than a corresponding threshold value; and
after determining that the at least one of the event properties is less than the corresponding threshold value,
determine the anticipated event value as the cross-sectional component.
which are nonetheless directed towards fundamentally the same abstract ideas as indicated for independent claims 1, 8 and 15.
Regarding Step 2A [prong 2]
Claims 1-21 fail to integrate the abstract idea into a practical application. Independent claims 1, 8 and 15 include the following additional elements which do not amount to a practical application:
Claim 1. A system, comprising:
at each of a plurality of locations, an event tracking subsystem
a data prediction subsystem comprising:
a network interface configured
algorithm
AI
first processor communicatively coupled to the network interface, the first processor configured to:
a network communication
user interface, a display and device
Claim 8. A system, comprising:
A processor, a data prediction subsystem, at each of a plurality of locations, an event tracking subsystem;
a data prediction subsystem comprising:
a network interface configured
algorithm
AI
first processor communicatively coupled to the network interface, the first processor configured to:
user interface, a display and device
Claim 15. A non-transitory computer-readable medium, a subsystem, comprising:
at each of a plurality of locations, an event tracking subsystem
a data prediction subsystem comprising:
a network interface configured
algorithm
AI
first processor communicatively coupled to the network interface, the first processor configured to:
user interface, a display and device
The bolded limitations recited above in independent claims 1, 8 and 15 pertain to additional elements which merely provide an abstract-idea-based-solution implemented with computer hardware and software components, including the additional elements of a system, a non-transitory computer-readable medium, comprising: tracking subsystem a data prediction subsystem, a network communication/interface, first processor communicatively coupled to the network interface, algorithm, AI, user interface, display and device. which fail to integrate the abstract idea into a practical application because there are (1) no actual improvements to the functioning of a computer, (2) nor to any other technology or technical field, (3) nor do the claims apply the judicial exception with, or by use of, a particular machine, (4) nor do the claims provide a transformation or reduction of a particular article to a different state or thing, (5) nor provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment, in view of MPEP §2106.04(d)(1) and §2106.05 (a-c & e-h), (6) nor do the claims apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, in view of MPEP §2106.04(d)(2). The Specification provides a high level of generality regarding the additional elements claimed without sufficient detail or specific implementation structure so as to limit the abstract idea, for instance, (fig. 1). Nothing in the Specification describes the specific operations recited in claims 1, 8 and 15 as particularly invoking any inventive programming, or requiring any specialized computer hardware or other inventive computer components, i.e., a particular machine, or that the claimed invention is somehow implemented using any specialized element other than all-purpose computer components to perform recited computer functions. The claimed invention is merely directed to utilizing computer technology as a tool for solving a business problem of data analytics. Nowhere in the Specification does the Applicant emphasize additional hardware and/or software elements which provide an actual improvement in computer functionality, or to a technology or technical field, other than using these elements as a computational tool to automate and perform the abstract idea. See MPEP §2106.05(a & e).
The relevant question under Step 2A [prong 2] is not whether the claimed invention itself is a practical application, instead, the question is whether the claimed invention includes additional elements beyond the judicial exception that integrate the judicial exception into a practical application by imposing a meaningful limit on the judicial exception. This is not the case with Applicant's claimed invention which merely pertains to steps for predicting a removal of an item and recommending amount of the first item at a future time. In example aspects, based on different data and the additional computer elements a tool to perform the abstract idea, and merely linking the use of the abstract idea to a particular technological environment. See MPEP §2106.04 and §21062106.05(f-h). Alternatively, the Office has long considered data gathering, analysis and data output to be insignificant extra-solution activity, and these additional elements do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.04 and §2106.05(g). Thus, the additional elements recited above fail to provide an actual improvement in computer functionality, or to a technology or technical field. See MPEP §2106.04(d)(1) and §2106§2106.05 (a & e).
Instead, the recited additional elements above, merely limit the invention to a technological environment in which the abstract concept identified above is implemented utilizing the computational tools provided by the additional elements to automate and perform the abstract idea, which is insufficient to provide a practical application since the additional elements do no more than generally link the use of the abstract idea to a particular technological environment. See MPEP §2106.04. Automating the recited claimed features as a combination of computer instructions implemented by computer hardware and/or software elements as recited above does not qualify an otherwise unpatentable abstract idea as patent eligible. Alternatively, the Office has long considered data gathering and data processing as well as data output recruitment information on a social network to be insignificant extra-solution activity, and these additional elements used to gather and output recruitment information on a social network are insignificant extra-solution limitations that do not impose any meaningful limits on practicing the abstract idea. See MPEP §2106.05(g). The current invention is idea of predicting a removal of an item and recommending amount of the first item at a future time. When considered in combination, the claims do not amount to improvements of the functioning of a computer, or to any technology or technical field. Applicant's limitations as recited above do nothing more than supplement the abstract idea using additional hardware/software computer components as a tool to perform the abstract idea and generally link the use of the abstract idea to a technological environment, which is not sufficient to integrate the judicial exception into a practical application since they do not impose any meaningful limits.
Dependent claims 2-7, 9-14, and 16-21 merely incorporate the additional elements recited above, along with further embellishments of the abstract idea of independent claims 1, 8 and 15 for example claims 5, 12, and 19, model
The additional elements of a “algorithm, AI, and model ”. This language merely requires execution of an algorithm that can be performed by a generic computer component and provides no detail regarding the operation of that algorithm. As such, the claim requirement amounts to mere instructions to implement the abstract idea on a computer, and, therefore, is not sufficient to make the claim patent eligible. See Alice, 573 U.S. at 226 (determining that the claim limitations “data processing system,” “communications controller,” and “data storage unit” were generic computer components that amounted to mere instructions to implement the abstract idea on a computer); October 2019 Guidance Update at 11–12 (recitation of generic computer limitations for implementing the abstract idea “would not be sufficient to demonstrate integration of a judicial exception into a practical application”). Such a generic recitation of “algorithm, AI, and model” is insufficient to show a practical application of the recited abstract idea.
Also, these features only serve to further limit the abstract idea of independent claims 1, 8 and 15. furthermore, merely using/applying in a computer environment such as merely using the computer as a tool to apply instructions of the abstract idea do nothing more than provide insignificant extra-solution activity since they amount to data gathering, analysis and outputting. Furthermore, they do not pertain to a technological problem being solved in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, and/or the limitations fail to achieve an actual improvement in computer functionality or improvement in specific technology other than using the computer as a tool to perform the abstract idea.
Therefore, the additional elements recited in the claimed invention individually, and in combination fail to integrate the recited judicial exception into any practical application.
Regarding Step 2B
Claims 1-21 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element(s) as described above with respect to Step 2A Prong 2, the additional element of claims 1, 8 and 15 include a system, comprising: tracking subsystem a data prediction subsystem, a network interface, first processor communicatively coupled to the network interface, a system, comprising: tracking subsystem a data prediction subsystem, a network interface, first processor communicatively coupled to the network communication/interface, algorithm, AI, user interface, display and device. Further, claims 5, 12, and 19, model. The displaying interface and storing data merely amount to a general purpose computer used to apply the abstract idea(s) (MPEP 2106.05(f)) and/or performs insignificant extra-solution activity, e.g. data retrieval and storage, as described above (MPEP 2106.05(g)) which are further merely well-understood, routine, and conventional activit(ies) as evidenced by MPEP 2106.06(05)(d)(II) (describing conventional activities that include transmitting and receiving data over a network, electronic recordkeeping, storing and retrieving information from memory, electronically scanning or extracting data from a physical document, and a web browser’s back and forward button functionality). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that the claims amount to significantly more than the abstract idea directed to predicting a removal of an item and recommending amount of the first item at a future time.
Claims 1-21 is accordingly rejected under 35 USC 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea(s)) without significantly more.
Allowable Subject Matter
Closest prior art to the invention include Landvater et al. US 2009/0125385: Method and system for determining time-phased product sales forecasts and projected replenishment shipments for a retail store supply chain, Evens et al. US 2011/0225023: Breakout of participants in a conference call. Wynn et al. US 2018/0039951: Prioritized product distribution and Anderson et al. US 2010/0169162 "Methods and apparatus to determine the effects of trade promotions on subsequent sales.
None of the prior art of record, taken individually or in combination, teach, inter alia, teaches the claimed invention as detailed in claims 1, 8, and 15, train an algorithm associated with an artificial intelligence model on the training data, wherein training the algorithm associated with the artificial intelligence model on the training data comprises: use actual item removal values for the first item on days with the not-empty status as a plurality of target values, wherein each target value from among the plurality of target values indicates an actual amount of removal event for the first item at the first location on a respective day having the not-empty status; use the longitudinal component and the cross-sectional component as a plurality of predictors, wherein: each predictor from among the plurality of predictors indicates an expected amount of removal event for the first item or another item associated with item category at the first location or at the one or more other locations on the respective day having an empty status; and a given predictor from among the plurality of predictors is associated with a counterpart target value from among the plurality of target values; and determine a relationship between the given predictor and the counterpart target value; execute the trained algorithm; … for a first day of the first set of event data having zero events corresponding to the empty status indicating that the first item is not believed to be present at the first location. The reason to withdraw the 35 USC 103 rejection of claims 1-21 in the instant application is because the prior art of record fails to teach the overall combination as claimed. Therefore, it would not have been obvious to one of ordinary skill in the art to modify the prior art to meet the combination above without unequivocal hindsight and one of ordinary skill would have no reason to do so. Upon further searching the examiner could not identify any prior art to teach these limitations. The prior art on record, alone or in combination, neither anticipates, reasonably teaches, not renders obvious the Applicant’s claimed invention.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
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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.
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/HAMZEH OBAID/Primary Examiner, Art Unit 3624