Detailed Action
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This Action is in reply to the Amendment filed on 12/3/2025. Claims 1, 6-7, 10-14, 16-18, and 22-25 are currently pending and have been examined. Claims 3-5, 8-10, 15, and 19-21 are cancelled; claims 3, 4, 9, 15, and 19-21 are cancelled; withdrawn. Claims 1, 7, 10, 12, 14, 16, 17 have been amended. Claims 24-25 have been newly entered. The prior art rejections have been overcome by amendment.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 U.S.C. 112(a) as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 U.S.C. 112(a) or the first paragraph of pre-AIA 35 U.S.C. 112, except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Provisional Application No. 63294457, fails to provide adequate support or enablement in the manner provided by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph for one or more claims of this application. The provisional application fails to provide support for at least the limitations of training & retraining as claimed, processing the selection by facilitating delivery of the one or more items in the cart, or providing a message to, routing, and receiving a message from an autonomous vehicle, as recited in the independent claims.
Claim Rejection - 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, 6-7, 10-14, 16-18, and 22-25 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
First, it is determined whether the claims are directed to a statutory category of invention. In the instant case, claims 1, 6-7, 10-11, 16-18, 22, 24-25 are directed to a process, and claims 12-14 and 23 are directed to a machine. Therefore, claims 1, 6-7, 10-14, 16-18, and 22-25 are directed to statutory subject matter under Step 1 as described in MPEP 2106 (Step 1: YES).
The claims are then analyzed to determine whether the claims are directed to a judicial exception. 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), as well as analyzed to evaluate whether the claims recite additional elements that integrate the judicial exception into a practical application of the judicial exception (Prong Two of Step 2A).
Taking Claim 1 as representative, Claim 1 recites at least the following limitations that are believed to recite an abstract idea:
obtaining a plurality of user features of a plurality of users, a plurality of service provider features of a plurality of service providers, and a procedure;
preparing the procedure by inputting into the procedure the plurality of user features and the plurality of service provider features into the procedure, the preparing comprising iteratively adjusting biases and weights until, when provided an input and an output, the procedure accepts the input and generates an output similar to the output, and updating procedure parameters;
obtaining an updated procedure having the updated procedure parameters;
determining a first plurality of carts using the updated procedure and user features for an end user of the plurality of users, by iterating through the plurality of service providers and generating each of the first plurality of carts for a corresponding service provider among the plurality of service providers, wherein the updated procedure is input, at each iteration, service provider features corresponding to one of the service providers, and wherein each cart of the first plurality of carts includes one or more first items associated with the corresponding service provider;
storing in a candidate cart storage, the first plurality of carts, wherein the candidate cart storage is a scalable system configured to support the plurality of users;
in response to a cart request message received from an end user at the end user location, retrieving first carts of the first plurality of carts from the candidate cart storage;
validating each of the first carts using up-to-date menu information received from the plurality of service providers, to determine whether the one or more first items in each of the first carts are currently available;
sorting the first carts based on a relevance score for each cart, wherein the relevance score is associated with a relevance to the end user and calculated using a process that factors in user features of the end user, service provider features, and user interaction data;
displaying the first carts to the end user, in an order of the relevance score;
receiving from the end user, a selection of a cart of the first carts that is input, the cart being associated with a particular service provider;
processing the selection to facilitate preparation and delivery of the one or more first items in the cart, the processing further including updating fulfillment request records and initiating communication with the particular service provider and delivery means;
transmitting a message comprising an instruction to a delivery means, which is selected among the delivery means, to cause the delivery means to travel to a service provider location of the particular service provider to retrieve the one or more first items and then to the end location of the end user to deliver the one or more first items;
routing the delivery means to the service provider location and then to the end user location, using navigational directions based on location information;
receiving, from the delivery means, a delivery confirmation method that the one or more first items were successfully delivered to the end user location; and
updating the updated procedure using data related to the cart, the data including user features and service provider features associated with completed delivery, to refine the procedure parameters and generate a refined procedure having the refined procedure parameters.
The above limitations recite the concept of personalized purchase recommendations and delivery. These limitations, under their broadest reasonable interpretation, fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106, in that they recite commercial interactions, e.g. sales activities/behaviors, and managing personal behavior or relationships or interactions between people, e.g., following rules or instructions. Accordingly, under Prong One of Step 2A, claims 1, 6-7, 10-14, 16-18, and 22-25 recite an abstract idea (Step 2A, Prong One: YES).
Prong Two of Step 2A is the next step in the eligibility analyses and looks at whether the abstract idea is integrated into a practical application. This requires an additional element or combination of additional elements in the claims to apply, rely on, or user 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 exception.
In this instance, the claims recite the additional elements of:
A server computer
A ML model
Training & re-training the ML model
A user device
A fault-tolerant database
A machine learning process
A graphical user interface
electronic signals
autonomous vehicles
a navigation network including global positioning system (GPS) data
A server computer comprising: a processor; and a computer-readable medium coupled to the processor, the computer- readable medium comprising code executable by the processor for implementing a method
However, these elements do not amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or 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, such that the claim as a whole is more than a drafting effort to monopolize the exception.
In addition, the recitations are recited at a high level of generality and also do not amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or 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, such that the claim as a whole is more than a drafting effort to monopolize the exception.
The dependent claims also fail to recite elements which amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or 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, such that the claim as a whole is more than a drafting effort to monopolize the exception. For example, claims 7,17-18, 22-23 are directed to the abstract idea itself and do not amount to an integration according to any one of the considerations above. As for claims 6, 10-11, 13-14, and 24-25, these claims are similar to the independent claims except that they recite the further additional elements of a further databases, an additional user device, a central server computer, a hybrid ML model, and a relational database. These additional elements are recited at a high level of generality and also do not amount to an improvement in the functioning of a computer or any other technology or technical field; apply the judicial exception with, or by use of, a particular machine; or 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, such that the claim as a whole is more than a drafting effort to monopolize the exception. Therefore, the dependent claims do not create an integration for the same reasons.
Step 2B is the next step in the eligibility analyses and evaluates whether the claims recite additional elements that amount to an inventive concept (i.e., “significantly more”) than the recited judicial exception. According to Office procedure, revised Step 2A overlaps with Step 2B, and thus, many of the considerations need not be re-evaluated in Step 2B because the answer will be the same.
In Step 2A, several additional elements were identified as additional limitations:
A server computer
A ML model
Training & re-training the ML model
A user device
A fault-tolerant database
A machine learning process
A graphical user interface
electronic signals
autonomous vehicles
a navigation network including global positioning system (GPS) data
A server computer comprising: a processor; and a computer-readable medium coupled to the processor, the computer- readable medium comprising code executable by the processor for implementing a method
These additional limitations, including the limitations in the dependent claims, do not amount to an inventive concept because they were already analyzed under Step 2A and did not amount to a practical application of the abstract idea. Therefore, the claims lack one or more limitations which amount to an inventive concept in the claims.
For these reasons, the claims are rejected under 35 U.S.C. 101.
Allowable over Prior Art of Record
Claims 1, 6-7, 10-14, 16-18, and 22-25 are allowable over prior art though rejected on other grounds [e.g. 35 USC §101] as discussed above. The combination of elements of the claim as a whole are not found in the prior art.
Claims 1, 6-7, 10-14, 16-18, and 22-25 would be allowable if rewritten to overcome the rejections under 35 USC §101 as set forth in this Office Action, and to include all of the limitations of the base claim and any intervening claims.
Upon review of the evidence at hand, it is hereby concluded that the totality of the evidence, alone or in combination, neither anticipates, reasonably teaches, nor renders obvious the below noted features of the Applicant’s invention.
In the present application, claims 1, 6-7, 10-14, 16-18, and 22-25 are allowable over prior art. The most related prior art patent of record is Kysta et al (US 20210035188 A1), hereinafter Kysta, Obaidi (US 20170090484 A1), hereinafter Obaidi, and Reference U (NPL – see attached).
Kysta teaches a method for product recommendation, in which a trained ML model is used [0054, 0135] after being trained on product information and user histories [0049]. Based on user information, such as their current order, the system determines one or more products to recommend based on product similarities [0136]. Upon navigating to checkout, the system examines the items in the user’s cart and determines products similar thereto to recommend [0053]. These are provided to the user on a webpage screen and can be added to their cart directly [0079]. The system facilitates the checkout and supports delivery arrangements for fulfilling the order [0077-0080]. The ML model is re-trained after a period of time to be updated to accommodate changes in user behavior [0050-0051].
Obaidi teaches order delivery systems [Abstract] in which instructions for the pickup and drop-off of an order can be communicated to a drone [0036], which can be directed to the pick-up location [0028]. This can be one of a plurality of drones to be selected from & scheduled to handle the delivery [0048]. Using GPS data [0026], the system can be navigated to the relevant locations [0027-0037]. Upon arrival, the drone provides a notification indicating its arrival to the customer [0030].
Reference U discusses personalized ranking of product options for on-demand food delivery, including a machine learning algorithm that can rank the options from a plurality of restaurants based on a variety of factors.
Other relevant prior art includes Beauchamp (US 20200320607 A1), which teaches systems for product recommendations using a trained machine learning algorithm to generate bundles of items that can be added to a cart together; Mane et al (US 20210056385 A1), which teaches a machine learning recommendation technique for items that can be added to a shopping cart trained on item data. Items are ranked based on relevance by AI; and Fotso et al (US 20220327583 A1), which uses machine learning to generate a plurality of pre-set service offering recommendations for each merchant in a database.
However, each of these references fail to disclose or render obvious at least the limitations of: determining, by the server computer, a first plurality of carts using the updated ML model and user features for an end user of the plurality of users, by iterating through the plurality of service providers and generating each of the first plurality of carts for a corresponding service provider among the plurality of service providers, wherein the updated ML model is input, at each iteration, service provider features corresponding to one of the service providers, and wherein each cart of the first plurality of carts includes one or more first items associated with at
Ultimately, the particular combination of limitations as claimed, is not anticipated nor rendered obvious in view of the cited references, and the totality of the prior art. While certain references may disclose more general concepts and parts of the claim, the prior art available does not specifically disclose the particular combination of these limitations.
The references, however, do not teach or suggest, alone or in combination the claimed invention. Examiner emphasizes that the prior art/additional art 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).
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 be obvious to one of ordinary skill in the art as combining various references from the totality of evidence to reach the combination of features as claimed would be a substantial reconstruction of Applicant’s claimed invention relying on improper hindsight bias.
It is thereby asserted by Examiner that, in light of the above and further deliberation over all of the evidence at hand, that the claims are allowable over prior art (though rejected under 35 USC §101) 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 12/3/2025 have been fully considered but are not persuasive.
Claim Rejections – 35 USC § 101
Applicant argues that claim 1 “does not simply recite recommending products; it specifies a sequence of technical operations,” arguing that “the claim language requires specific technological steps and architecture, not a mere automation of a business practice.”
Examiner disagrees. With reference to the rejection above, the claims recite steps, which, except for the recitation of additional elements as analyzed in the subsequent steps of the analysis, recite within the concept of personalized purchase recommendations and delivery, falling within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, enumerated in MPEP 2106, in that they recite commercial interactions, e.g. sales activities/behaviors, and managing personal behavior or relationships or interactions between people, e.g., following rules or instructions.
Applicant argues that the abstract idea is integrated into a practical application, stating that “the integration may be shown by incorporation of …non-generic, fault-tolerant, and scalable candidate cart database …real-time validation using up-to-date menu data… sorting by ML-generated relevance score…graphical user interface for interactive selection …automated fulfillment via autonomous vehicle with GPS-based routing and network signaling …retraining based on fulfillment data,” such that the claims “recite a specific, non-generic system, not a general-purpose computer performing an abstract idea.” Applicant asserts that the “technological improvements are not post-solution activity or field of use limitations; they are central to the invention.”
Examiner disagrees. Each of these additional elements is recited at a high level of generality, and invoked as mere instructions to apply the abstract idea to a technological environment [MPEP 2106.05(f)], creating only a general linking to computer technology. The database is merely stated to be “fault-tolerant” and “scalable,” without detail in the claims or in the Specification to explain how such a database is implemented in a non-generic way, or what improvements such a database offers beyond the improved efficiency inherent to a computer [MPEP 2106.05(a)]. The validation of suggested items using up-to-date menu data is not recited as being real-time in the claims, nor is such a recitation suggested by the Specification. This step is part of the abstract idea itself, as identified above, except for a general linking to computer technology by the mere instruction to apply the step on a generic “Server computer.” Similarly, the use of ML to generate a score and the updating of the process being a retraining of an ML model, along with data being displayed on and received via a generic GUI, also fail to integrate the abstract idea into a practical application, with these elements similarly creating only a general linking to computer technology. In addition, the claimed autonomous, GPS-capable vehicles are recited at a high level of generality, and, rather than providing an improvement in the functioning of the technology, are invoked merely as generic computer-related tools to perform abstract delivery steps, providing mere instructions to apply the abstract idea to a general technological environment [MPEP 2106.05(f)]. Each of these additional elements, alone or in combination offer at best only the improved speed or efficiency inherent to a computer [MPEP 2106.05(a)].
Applicant argues that claim 1 recites a combination of features that is not routine conventional or generic, arguing that the “claim language requires a particular sequence and interaction of technical components, not found in or suggested by prior art or generic computer operation.” Applicant argues that “the ML model is not static, it is retrained…making the system adaptive and technically distinct.”
Examiner disagrees. Similar to the analysis under Prong 2 as addressed above, the additional elements are generic computer components recited at a high level of generality which provide only a general linking to computer technology [MPEP 2106.05(f)]. A machine learning model being able to re-train is not an unconventional or non-routine computer element, nor is it significantly more than the abstract idea’s ability to update in a loop “based on real-world fulfillment.” With respect to the argument that claim elements are not “found in or suggested by prior art,” it is noted that “a claim for a new abstract idea is still an abstract idea” [MPEP 2106.05(I)], with the analysis under 101 being distinct from findings with respect to prior art. The additional elements of the claim, considered individually and as a whole, fail to amount to significantly more than the abstract idea, and amount to mere instructions to apply the abstract idea to a technical technological environment [MPEP 2106.05(f)], offering only the improved speed or efficiency inherent to a computer [MPEP 2106.05(a)].
Applicant further argues that “claims 12 and 16 would conform to a similar analysis.”
Examiner disagrees for the reasons addressed in the rejection & response above.
Conclusion
THIS ACTION IS MADE FINAL. 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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/T.J.S./Examiner, Art Unit 3689
/MARISSA THEIN/Supervisory Patent Examiner, Art Unit 3689