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 Claims
The following is an Office Action in response to communications filed on 12/10/2025.
Claims 1-4, 11-14, and 21-24 have been amended.
Claims 5 and 16-20 have been canceled.
Claims 25-26 have been added.
Claims 1-4, 6-15 and 21-26 are currently pending and have been examined.
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 1-4, 6-15 and 21-26 are rejected under 35 USC 103 because the claimed invention is directed to a judicial exception without significantly more. The claims recite an abstract idea. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Under Step 1 of the Subject Matter Eligibility Test for Products and Processes, the claims must be directed to one of the four statutory categories (See MPEP 2106.03(II)). In the instant application, claims 1-4, 6-10, and 25-26 are directed to a process (i.e. a method), and claims 11-15 are directed to a machine (i.e., a system), and claims 21-24 are directed to a manufacture (i.e., a non-transitory computer readable medium). All the claims are directed to one of the four statutory categories (YES).
Under Step 2A of the Patent Subject Matter Eligibility Test (see MPEP 2106.04), it is determined whether the claims are directed to a judicially recognized exception. Step 2A is a two-prong inquiry.
Under Prong 1, it is determined whether the claim recites a judicial exception (See MPEP 2106.04). (YES). Claim 1 recites limitations that fall within the certain methods of organizing human activity grouping of abstract ideas, including:
A method comprising:
receiving, by one or more computing devices and from a computing device associated with a customer of an online shopping concierge platform, data describing one or more search parameters input by the customer;
identifying, by the one or more computing devices and based at least in part on the data describing the one or more search parameters, a plurality of candidate products offered by the online shopping concierge platform that are at least in part responsive to the one or more search parameters;
applying, to each candidate product, a machine-learning classification model to determine a relevance of the candidate product to one or more taxonomy levels of a product catalog associated with the online shopping concierge platform, wherein the machine-learning classification model is trained by:
obtaining a hierarchical taxonomy including a plurality of categories and a hierarchy of levels where lower levels in the hierarchy corresponding to more specific categories, wherein an item in the item catalog is categorized based on the hierarchical taxonomy;
accessing a training dataset comprising a plurality of training items, each training items associated with a category and a set of attributes;
applying the machine-learning classification model to each training item to predict a relevance of the training item to one or more taxonomy levels of the item catalog;
scoring the predicted relevance of the training item to the hierarchical taxonomy;
training the machine-learning classification model based on the score predicted relevance;
updating the training dataset with inventory information from a plurality of warehouses; and
retraining the machine-learning classification model based on the updated training dataset,
applying, to each candidate product, a machine-learning prediction model to determine a likelihood that the candidate product coheres to one or more dietary restrictions of the customer, wherein applying the machine-learning prediction model comprises:
receiving user-specific data associated with the customer characterizing the one or more dietary restrictions of the customer;
generating a feature vector comprising features characterizing the candidate product and features representing the user-specific data;
inputting the feature vector for the candidate product into the machine-learning prediction model; and
receiving as output from the machine-learning prediction model the likelihood that the candidate product cohere to the one or more dietary restrictions of the customer;
filtering, by the one or more computing devices, the plurality of candidate products based on the relevances and the likelihoods that the candidate products coheres to the one or more dietary restrictions of the customer;
generating, by the one or more computing devices, a graphical user interface (GUI) presenting a plurality of ranked candidate products offered by the online shopping concierge platform that result from the filtering; and
communicating, by the one or more computing devices and to the computing device associated with the customer, the GUI for presentation of the plurality of ranked candidate products on an electronic display of the computing device associated with the customer.
Claims 11 and 21 recite similar limitations as claim 1.
Certain methods of organizing human activity include:
fundamental economic principles or practices (including hedging, insurance, an mitigating risk)
commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; and business relations)
managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions)
The limitations, as emphasized above, recite the concept of providing filtered search results based on product searches. These limitations, under their broadest reasonable interpretations, fall with the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in the MPEP because these limitations recite commercial or legal interactions (such as marketing or sales activities) as well as managing personal behavior or relationships or interactions between people. Specifically, the claims recite receiving search parameters, identifying products responsive to the search parameters, determining one or more values for the products, where the values indicate relevance to a taxonomy or a likelihood that a customer would be offended by the product, filtering the products based on the values, ranking the products, and communicating the ranked products to the customer (see claim 1). Applicant’s specification recites that the taxonomy levels correspond to different categories and/or attributes (e.g., meat, dairy, bakery, and/or the like; brands or quantities; etc.) of products offered for purchase by a warehouse (see specification [0028-0029], [0048]) and further recites that the online concierge system is configured to receive orders from one or more users, where an order species a list of goods (items or products) to be purchased from one or more retailers. Further, the “warehouses” may be physical retailers, such as grocery stores, discount stores, or warehouses storing items (see specification [0023-0025]). In sum, the claims are directed towards receiving search parameters, executing a product search, and returning a ranked list of products to the customer, which amounts to sales activity and therefore is a commercial interaction (see MPEP 2106.04(a)(1)(II)(B)). The claims additionally recite filtering products in response to a user query. Filtering content is an example of managing personal behavior (see MPEP 2106.04(a)(1)(II)(C)). Accordingly, independent claims 1, 11, and 16, as a whole, are directed towards certain methods of organizing human activity and recite an abstract idea.
Under Prong 2, it is determined whether the claim recites additional elements that integrate the exception into a practical application of the exception. This judicial exception is not integrated into a practical application (NO).
Independent claims 1, 11, and 21 recite additional elements beyond the abstract idea, including:
one or more computing devices
a computing device associated with a customer
an online shopping concierge platform
a machine-learning classification model
a machine-learning classification model being trained
retraining the machine-learning classification model
a machine-learning prediction model
a graphical user interface (GUI)
an electronic display
a system comprising one or more processors and a memory storing instructions that when executed by the one or more processors cause the system to perform operations
one or more non-transitory computer-readable media comprising instructions that when executed by one or more computing devices cause the one or more computing devices to perform operations
The additional elements of claims 1, 11, and 21 are recited at a high level of generality (i.e. as generic computing hardware) in Applicant’s specification without meaningful detail regarding their structure, configuration, or function. As such, the additional elements amount to nothing more than mere instructions to implement or apply the abstract idea on a generic computing hardware (or, merely use a computer as a tool to perform an abstract idea.) Specifically, the additional element of the machine learning models, is recited at a high-level of generality (i.e., as a generic computer executing an algorithm) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Further, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (such as computers or computing networks). For example, stating that the search parameters are received from “a device” associated with a customer only generally links the commercial interactions into a computer environment. Employing well-known computer functions to execute an abstract idea, even when limiting the use of the idea to one particular environment, does not integrate the exception into a practical application.
Additionally, the additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to i) reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, ii) apply the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, iii) effect a transformation or reduction of a particular article to a different state or thing, or iv) apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, the judicial exception is not integrated into a practical application.
Under Step 2B, it is determined whether the claims recite additional elements that amount to significantly more than the judicial exception. The claims of the present application do not include additional elements that are sufficient to amount to significantly more than the judicial exception (NO).
As discussed above with respect to Prong Two of Step 2A, although additional computer related elements are recited, the claim merely invokes such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). Moreover, the limitations of claims 1, 11, and 21 are manual processes (e.g., receiving search parameters, identifying products, determining values associated with each product, ranking the products, outputting the ranked products, etc.). The courts have indicated that mere automation of manual processes is not sufficient to show an improvement in computer-functionality (see MPEP 2106.05(a)(I)). Furthermore, as discussed above with respect to Prong Two of Step 2A, claims 1, 11, and 21 merely recite the additional elements in order to further define the field of use of the abstract idea, therein attempting to generally link the use of the abstract idea to a particular technological environment, such as the Internet or computing networks (see Ultramercial, Inc. v. Hulu, LLC. (Fed. Cir. 2014); Bilski v. Kappos (2010); MPEP 2106.05(h)). Similar to Fair Warning v. Iatric Sys., claims 1, 11, and 21 specifying that the abstract idea of providing filtered search results in response to product searches is executed in a computer environment merely indicates a field of use in which to apply the abstract idea because this requirement merely limits the claim to the computer field, i.e., to execution on a generic computer.
Even when considered as an ordered combination, the additional elements do not add anything that is not already present when they are considered individually. In Alice Corp., the Court considered the additional elements “as an ordered combination,” and determined that “the computer components…‘[a]dd nothing…that is not already present when the steps are considered separately’ and simply recite intermediated settlement as performed by a generic computer.” Id. (citing Mayo, 566 U.S. at 79, 101 USPQ2d at 1972). Similarly, viewed as a whole, claims 1, 11, and 21 simply convey the abstract idea itself facilitated by generic computing components. Therefore, under Step 2B of the Alice/Mayo test, there are no meaningful limitations in claims 1, 11, and 21 that transform the judicial exception into a patent eligible application such that the claim amounts to significantly more than the judicial exception itself.
Even considered as an ordered combination (as a whole), the additional elements do not add anything significantly more than when considered individually. Therefore, claims 1, 11, and 16 do not provide an inventive concept and do not qualify as eligible subject matter.
Claims 2-4, 6-10, 12-15, and 22-26 are dependencies of claims 1, 11, and 21. Dependent claims 2-4, 6-10, 12-15, and 22-26, when analyzed as a whole, are held to be patent-ineligible under 35 U.S.C. 101 because they recite an abstract idea, are not integrated into a practical application, and do not add “significantly more” to the abstract idea. More specifically, dependent claims 2-4, 6-10, 12-15, and 22-26 further fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in the MPEP, in that they further recite commercial or legal interactions, such as advertising, marketing, or sales activities or behaviors and managing personal behavior or relationships or interactions between people. Dependent claims 2-4, 6-10, 12-15, and 22-26 do not recite additional elements but rather recite limitations that further define the abstract idea. Therefore, claims 2-4, 6-10, 12-15, and 22-26 are not indicative of integration into a practical application and are not significantly more than the judicial exception. Similar to discussion above the with respect to Prong Two of Step 2A, although additional computer-related elements are recited, the claims merely invoke such additional elements as a tool to perform the abstract idea. See MPEP 2106.05(f). As such, under Step 2A, dependent claims 2-4, 6-10, 12-15, and 22-26 are “directed to” an abstract idea. Similar to the discussion above with respect to independent claims 1, 11, and 21, dependent claims 2-4, 6-10, 12-15, and 22-26, analyzed individually and as an ordered combination, invoke such additional elements as a tool to perform the abstract idea and merely indicate a field of use in which to apply the abstract idea because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, and therefore, do not amount to significantly more than the abstract idea itself. See MPEP 2106.05(f)(2).
Accordingly, under the Alice/Mayo test, the Examiner concludes that there are no meaningful
limitations in claims 1-4, 6-15 and 21-26 that transform the judicial exception into a patent eligible application such that the claim amounts to significantly more than the judicial exception itself. The analysis above applies to all statutory categories of invention.
Reasons for Allowance
Claims 1-4, 6-15 and 21-26 would be allowable if rewritten or amended to overcome rejections under 35 U.S.C. 101, set forth in this Office action.
The following is an examiner’s statement of reasons for allowance:
Upon review of the evidence at hand, it is hereby concluded that the evidence obtained and made of record, alone or in combination, neither anticipates, reasonably teaches, nor renders obvious the below noted features of applicant’s invention as the noted features amount to more than a predictable use of elements in the prior art.
The most relevant prior art made of record includes previously cited previously cited Iyer et al. (US 11,947,548 B2), previously cited Qu (US 20220284491 A1), previously cited Hadad et al. (US 2019/0290172 A1), and newly cited NPL reference U.
Although individually the references teach concepts such as determining using machine learning a relevance of a product to a taxonomy, applying a classification model, retraining a model, and determining a likelihood that options cohere to dietary restrictions, none of the references teach nor render obvious that distinct products are identified based on search terms, where values are determined for these products based on a machine learning model, the values indicating a likelihood that items cohere to dietary restrictions, determined based on a machine learning model using a specific process, and filtering results for a user.
Previously cited Iyer discloses a method of search results (Iyer: Col. 9, lines 34-45, Fig. 3). A search may be received from a user and search results provided, where a machine learning model is used to rank items based on a relevance to a primary intent of a search (Iyer: Col. 9, lines 34-45, Fig. 3; Col. 5, line 51-Col. 6, line 4, Fig. 3). Iyer additionally discloses the primary intent extractor may obtain query features related to the natural language search query input. The real-time query parser may extract all products, attributes, and metadata from the query. The parsed attributes may include product, food form, type, allergens, product type, allergens not contained, dietary need, restrictions, restricted foods, etc. The primary intent extractor may identify intention terms each corresponding to a product, product type, and/or a brand and may compute a compatibility score for each intention term with respect to its corresponding query context (Iyer: Col. 13, lines 42-Col. 14, line 3, Fig. 6). Yet Iyer does not explicitly disclose all of the limitations regarding the taxonomy, the classification model, or updating the training.
Previously cited Qu teaches a taxonomy method (Qu: [0048]). Qu further teaches a trained machine learning classification model that is applied to attributes and values of attributes of an item to generate a probability of an item being in a category or level of the hierarchical taxonomy. The online concierge system 102 includes an item in a category for which the trained machine learning classification model determines the item as a maximum probability of including the item from the attributes and the values of the attributes of the item
(Qu: [0048]). Yet Qu does not explicitly teach all of the limitations the search information, the value determinations, and the specific machine learning training steps.
Previously cited Hadad teaches a system and method directed to food analysis and recommendations to users. The food items are organized in taxonomies (see Hadad [0200-0201]), and a recommendation engine 230 can predict what types of foods the user will like or dislike and use such one or more predictions to generate personalized recommendations (see Hadad [0238]). However, Hadad does not teach all of the limitations regarding the classification model and taxonomy.
Previously cited NPL reference U teaches recommendation filters. Recommendations may be fine-tuned to provide more tailored experiences that improve customer engagement and conversion. Machine learning is used to create recommendations. However, U does not explicitly teach the limitations regarding the taxonomy.
While these references arguably teach the claimed limitations using a piecemeal analysis, these references would only be combined and deemed obvious based on knowledge gleaned from the applicant's disclosure. Such a reconstruction is improper (i.e., hindsight reasoning). See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971). Accordingly, claims 1, 11, and 21, taken as a whole, are indicated to be allowable over the cited prior art. The examiner emphasizes that it is the interrelationship of the limitations that renders these claims allowable over the prior art/additional art. Claims 2-4, 6-10, 12-15 and 22-26 depend from claims 1, 11, and 21 and therefore the dependent claims are also indicated as containing allowable subject matter.
The examiner further emphasizes the claims as a whole and hereby asserts that the totality of the evidence fails to set forth, either explicitly or implicitly, an appropriate rationale for further modification of the evidence at hand to arrive at the claimed invention. The combination of features as claimed would not have been obvious to one of ordinary skill in the art as combining various references from the totality of the evidence to reach the combination of features as claimed would require a substantial reconstruction of the Applicant's claimed invention relying on improper hindsight bias.
It is thereby asserted by the examiner that, in light of the above and in further deliberation over all the evidence at hand, that the claims are allowable as the evidence at hand does not anticipate the claims and does not render obvious any further modification of the references to a person of ordinary skill in the art.
Response to Arguments
Applicant’s arguments, filed 12/10/2025, have been fully considered.
35 U.S.C. § 101
Applicant argues the claims are eligible because “[t]hese limitations cannot be characterized as directed to the excluded method of organizing human activity abstract idea” (Remarks page 18). The examiner disagrees. The MPEP enumerates groupings of abstract ideas, thereby synthesizing the holdings of various court decisions to facilitate examination. See MPEP 2106.04. Among the enumerated groupings is the Certain Methods of Organizing Human Activity grouping, which includes activity that falls within the enumerated sub-grouping of commercial or legal interactions, including subject matter relating to agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors, and business relations. With respect to the claims, the examiner notes one or more computing devices, a computing device associated with a customer, an online shopping concierge platform, a machine-learning classification model, a machine-learning classification model being trained, retraining the machine-learning classification model, a machine-learning prediction model, a graphical user interface (GUI), an electronic display, a system comprising one or more processors and a memory storing instructions that when executed by the one or more processors cause the system to perform operations, and one or more non-transitory computer-readable media comprising instructions that when executed by one or more computing devices cause the one or more computing devices to perform operations have been analyzed as additional elements and accordingly are not analyzed under Step 2A, Prong 1. The amendments further recite limitations such as determining information such as item relevance and a likelihood, to provide products to a user. These amendments represent certain methods of organizing human activity. Applicant’s specification recites that the taxonomy levels correspond to different categories and/or attributes (e.g., meat, dairy, bakery, and/or the like; brands or quantities; etc.) of products offered for purchase by a warehouse (see specification [0028-0029], [0048]) and further recites that the online concierge system is configured to receive orders from one or more users, where an order species a list of goods (items or products) to be purchased from one or more retailers. Further, the “warehouses” may be physical retailers, such as grocery stores, discount stores, or warehouses storing items (see specification [0023-0025]). Accordingly, the recited limitations pertain to sales activities as they pertain to products for sale. Accordingly, these claims recite Certain Methods of Organizing Human Activity.
Applicant argues the claims are integrated into a practical application because the claims “embody an improvement to the field of machine-learning and interface technology” (Remarks pages 19-20). The examiner disagrees. The MPEP provides guidance on how to evaluate whether claims recite an improvement in the functioning of a computer or an improvement to other technology or technical field. For example, the MPEP states “the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement.” The MPEP further states that “[t]he specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art,” and that, “conversely, if the specification explicitly sets forth an improvement but in a conclusory manner…the examiner should not determine the claim improves technology” (see MPEP 2106.04). That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. Looking to the specification is a standard that the courts have employed when analyzing claims as it relates to improvements in technology. For example, in Enfish, the specification provided teaching that the claimed invention achieves benefits over conventional databases, such as increased flexibility, faster search times, and smaller memory requirements. Enfish LLC v. Microsoft Corp., 822 F.3d 1327, 1335-36 (Fed. Cir. 2016). Additionally, in Core Wireless the specification noted deficiencies in prior art interfaces relating to efficient functioning of the computer. Core Wireless Licensing v. LG Elecs. Inc., 880 F.3d 1356 (Fed Cir. 2018). With respect to McRO, the claimed improvement, as confirmed by the originally filed specification, was “…allowing computers to produce ‘accurate and realistic lip synchronization and facial expressions in animated characters…’” and it was “…the incorporation of the claimed rules, not the use of the computer, that “improved [the] existing technological process” by allowing the automation of further tasks”. McRO, Inc. v. Bandai Namco Games America Inc., 837 F.3d 1299, (Fed. Cir. 2016).
While the examiner acknowledges that improvements to the functioning of a computer or to any other technology or technical field may constitute integration into a practical application (see MPEP 2106.05(a)), the instant claims do not provide a technical improvement. Rather, the claims provide an improvement to the abstract idea of providing filtered search results based on product searches. This is illustrated in the specification discussing that the taxonomy levels correspond to different categories and/or attributes (e.g., meat, dairy, bakery, and/or the like; brands or quantities; etc.) of products offered for purchase by a warehouse (see specification [0028-0029], [0048]) and further discussing that the online concierge system is configured to receive orders from one or more users, where an order species a list of goods (items or products) to be purchased from one or more retailers. With respect to Applicant’s argument that the claims are akin to Example 37, the examiner disagrees. The subject matter eligibility examples are hypothetical and only intended to be illustrative of the claim analysis under the MPEP. These examples are to be interpreted based on the fact patterns set forth in each example, as other fact patterns may have different eligibility outcomes. Example 37 provided a technical improvement to the technical problem of users only being able to manually create non-traditional arrangements of icons, by providing a method for rearranging icons on a graphical user interface (GUI), wherein the method moves the most used icons to a position on the GUI, specifically, closest to the ‘start’ icon of the computer system, based on a determined amount of use. The present claims provide no analogous technical solution. While the examiner acknowledges that an interface is generated, the claims provide no similar automatic arrangement of icons in response to an automatic determination by a processor that tracks the number of times each icon is selected or how much memory has been allocated to the individual processes associated with each icon over a period of time. Furthermore, unlike Example 37, Applicant’s specification provides no explanation of an improvement to the functioning of a computer or other technology. Accordingly, there is no evidence, short of attorney argument, that a technological improvement is provided.
Although the claims include computer technology such as one or more computing devices, a computing device associated with a customer, an online shopping concierge platform, a machine-learning classification model, a machine-learning classification model being trained, retraining the machine-learning classification model, a machine-learning prediction model, a graphical user interface (GUI), an electronic display, a system comprising one or more processors and a memory storing instructions that when executed by the one or more processors cause the system to perform operations, and one or more non-transitory computer-readable media comprising instructions that when executed by one or more computing devices cause the one or more computing devices to perform operations, such elements are merely peripherally incorporated in order to implement the abstract idea. Put another way, these additional elements are merely used to apply the abstract idea of providing filtered search results in response to a search in a technological environment without effectuating any improvement or change to the functioning of the additional elements or other technology. This is unlike the improvements recognized by the courts in cases such as Enfish, Core Wireless, and McRO. Unlike precedential cases, neither the specification nor the claims of the instant invention identify such a specific improvement to computer capabilities. The instant claims are not directed to technological improvements but are directed to improving the business method of providing search results. The claimed process, while arguably resulting in a more accurate process for providing search results, is not providing any improvement to another technology or technical field as the claimed process is not, for example, improving the server and/or computer components that operate the system. Rather, the claimed process is utilizing data sets related to products while still employing the same server and/or computer components used in conventional systems to improve providing of search results, e.g. a business method, and therefore is merely applying the abstract idea using generic computing components. As such, the claims are not integrated into practical application.
Applicant argues the claims provide significantly more because “the additional elements are non-routine, unconventional, and not well understood activity” (Remarks page 20). The examiner disagrees. The MPEP sets forth that if a claim has been determined to be directed to a judicial exception under revised Step 2A, examiners should then evaluate the additional elements individually and in combination under Step 2B to determine whether they provide an inventive concept (i.e., whether the additional elements amount to significantly more than the exception itself). In this case, Applicant's claims merely recite steps of a method with generic computer components being recited in a generic manner. While electronic devices such as one or more computing devices, a computing device associated with a customer, an online shopping concierge platform, the classification model being trained, training the classification model, retraining the classification model, one or more machine learning (ML) models, one or more graphical user interfaces (GUIs), a system comprising one or more processors and a memory storing instructions that when executed by the one or more processors cause the system to perform operations, and one or more non-transitory computer-readable media comprising instructions that when executed by one or more computing devices cause the one or more computing devices to perform operations are included within the claims, they are claimed in a generic manner and merely perform generic functions. The additional elements are merely peripherally incorporated in order to implement the abstract idea. Put another way, these additional elements are merely used to apply the abstract idea of providing search results based on a search in a technological environment without effectuating any improvement or change to the functioning of the additional elements or other technology. Applicant’s disclosure does not articulate or suggest how these additional elements function, individually or in combination, in any manner other than using generic functionality nor does the disclosure articulate how the elements provide a technical improvement. Accordingly, the additional elements do not amount to significantly more because they merely amount to using the additional elements as a tool to perform the abstract idea.
Applicant argues the claims provide significantly more because “the prior art does not teach or suggest the additional elements” (Remarks pages 20). The examiner disagrees. The question of whether a particular claimed invention is novel or obvious is "fully apart" from the question of whether it is eligible. Diamond v. Diehr, 450 U.S. 175, 190, 209 USPQ 1, 9 (1981). As made clear by the courts, the search for an inventive concept is different from an obviousness analysis under 35 U.S.C. 103. See, e.g., BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQ2d 1236, 1242 (Fed. Cir. 2016) ("The inventive concept inquiry requires more than recognizing that each claim element, by itself, was known in the art. . . . [A]n inventive concept can be found in the non-conventional and non-generic arrangement of known, conventional pieces."). Because they are separate and distinct requirements from eligibility, patentability of the claimed invention under 35 U.S.C. 102 and 103 with respect to the prior art is neither required for, nor a guarantee of, patent eligibility under 35 U.S.C. 101. See MPEP 2106.05(I). Accordingly, non-obviousness under 35 U.S.C, 103 has no bearing on the eligibility of the claims over 35 U.S.C. 101.
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 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANNA MAE MITROS whose telephone number is (571)272-3969. The examiner can normally be reached Monday-Friday from 9:30-6.
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/ANNA MAE MITROS/Examiner, Art Unit 3689
/MARISSA THEIN/Supervisory Patent Examiner, Art Unit 3689